Purchasing Power Parities and the Size of World Economies Purchasing Power Parities and the Size of World Economies Results from the 2017 International Comparison Program Purchasing Power Parities and the Size of World Economies Purchasing Power Parities and the Size of World Economies Results from the 2017 International Comparison Program © 2020 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington, DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved 1 2 3 4 23 22 21 20 This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. 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Contents Foreword.................................................................................................................................................... ix  Acknowledgments............................................................................................................................... xi Abbreviations....................................................................................................................................... xiii Chapter 1 Overview of main findings ......................................................1 Size of economies.................................................................................................................................... 1 GDP expenditure components................................................................................................................. 2 Per capita measures................................................................................................................................ 6 Intercountry income inequality................................................................................................................ 7 Price levels............................................................................................................................................... 9 Variability across economies................................................................................................................. 11 Comparison of 2017 results with revised 2011 results ....................................................................... 14 Chapter 2 ICP 2017 results........................................................................17 Tables of 2017 results........................................................................................................................... 17 Survey framework.................................................................................................................................. 19 Chapter 3 Purchasing power parities and real expenditures.............63 Concepts and definitions....................................................................................................................... 63 Use and applications of PPPs and real expenditures........................................................................... 67 Chapter 4 Governance and organization................................................73 Governance of ICP 2017........................................................................................................................ 73 Regional and national organization ..................................................................................................... 74 Chapter 5 Methodology.............................................................................77 Conceptual framework.......................................................................................................................... 78 Expenditure data.................................................................................................................................... 78 Price data............................................................................................................................................... 79 PPP calculation and estimation............................................................................................................. 81 Chapter 6 Looking forward.......................................................................87 Appendix A History of the International Comparison Program............89 Appendix B The ICP’s governance framework.........................................95 The ICP’s governance structure............................................................................................................. 95 The roles and responsibilities of the ICP governance bodies.............................................................. 95 v Appendix C ICP expenditure classification.............................................101 2017 ICP expenditure classification structure.................................................................................... 101 Main aggregates.................................................................................................................................. 102 Deriving actual individual consumption.............................................................................................. 102 Facilitating the input price approach ................................................................................................. 103 Adjusting household expenditure to the national concept................................................................ 103 Updates introduced for the 2017 ICP expenditure classification....................................................... 103 Appendix D Reference PPPs used in ICP 2017........................................115 Appendix E Revised 2011 results and comparisons with original ICP 2011 results......................................................................119 Appendix F Comparison of ICP 2017 results with World Development Indicators data..............................................167 Appendix G ICP research agenda...............................................................179 Appendix H ICP data access and archive policy......................................181 Background.......................................................................................................................................... 181 Data access objectives........................................................................................................................ 182 Guiding principles................................................................................................................................ 182 Procedures for archiving data ............................................................................................................ 183 Procedures for accessing data ........................................................................................................... 184 Appendix I ICP revision policy.................................................................185 Background.......................................................................................................................................... 185 Triggers for revising ICP indicators..................................................................................................... 185 Guidelines for revising ICP indicators................................................................................................. 186 Timing and communication of revisions............................................................................................. 187 Appendix J Classification of the world’s economies.............................189 Glossary��������������������������������������������������������������������������������������������������������195 References����������������������������������������������������������������������������������������������������207 Boxes 3.1 Using market exchange rates and PPPs to convert to a common currency......... 64 3.2 Use of purchasing power parities.......................................................................... 70 4.1 ICP 2017 cycle: Participating economies, by region............................................. 75 Figures 1.1 Share of global PPP-based and market exchange rate–based GDP and share of global population, by region and income group, 2017.......................................... 2 1.2 PPP-based GDP and share of global PPP-based GDP, by economy, 2017............... 3 1.3 Share of PPP-based global actual individual consumption for the six economies with the largest shares, 2017................................................................ 4 1.4 Share of global PPP-based expenditure on selected expenditure components of actual individual consumption, by region and income group, 2017................. 4 vi    Contents 1.5 Nominal expenditure on selected expenditure components of actual individual consumption as a share of nominal GDP, by region and income group, 2017...... 5 1.6 Share of PPP-based global consumption expenditure by government for the six economies with the largest shares, 2017.......................................................... 5 1.7 Share of PPP-based global gross fixed capital formation for the six economies with the largest shares, 2017.................................................................................. 5 1.8 Index of PPP-based GDP per capita and share of global population, by economy, 2011 and 2017................................................................................... 6 1.9 PPP-based actual individual consumption per capita and share of global population, by economy, 2017............................................................................... 7 1.10 PPP-based GDP per capita and actual individual consumption per capita for the 12 economies with the highest PPP-based GDP per capita, 2017.............. 8 1.11 Index of PPP-based expenditure per capita for GDP and major expenditure components, by region and income group, 2017................................................... 8 1.12 Lorenz curves for the distributions of 2017, revised 2011, and original 2011 PPP-based GDP per capita....................................................................................... 9 1.13 Lorenz curves for the distributions of 2017, revised 2011, and original 2011 PPP-based actual individual consumption per capita............................................. 9 1.14 GDP price level index versus PPP-based GDP per capita (and PPP-based GDP), by economy, 2017 and 2011................................................................................. 10 1.15 Price level indexes for GDP and major expenditure components, by region and income group, 2017....................................................................................... 11 1.16 Price level indexes for GDP and 17 expenditure components, by region, 2017....................................................................................................................... 12 1.17 Coefficients of variation: Index of PPP-based expenditure per capita and price level index for GDP and 17 expenditure components, by region, 2017..... 13 1.18 Share of global PPP-based and market exchange rate–based GDP and share of global population, by region and income group, 2011 and 2017.................... 14 1.19 Index of PPP-based expenditure per capita for GDP and major expenditure components, by region and income group, 2011 and 2017................................ 15 1.20 Price level indexes for GDP and major expenditure components, by region and income group, 2011 and 2017....................................................................... 16 4.1 ICP governance structure...................................................................................... 74 B.1 ICP governance structure...................................................................................... 96 Tables 2.1 Gross domestic product (GDP): ICP 2017 results................................................. 20 2.2 Actual individual consumption (AIC): ICP 2017 results...................................... 26 2.3 Individual consumption expenditure by households: ICP 2017 results.............. 32 2.4 Consumption expenditure by government: ICP 2017 results.............................. 38 2.5 Gross fixed capital formation (GFCF): ICP 2017 results....................................... 44 Contents vii 2.6 Domestic absorption: ICP 2017 results................................................................. 50 2.7 Gross domestic product (GDP) and individual consumption expenditure by households for nonparticipating economies: ICP 2017 results....................... 56 2.8 ICP 2017 Individual consumption expenditure by households, survey framework............................................................................................................. 57 C.1 Structure of the ICP expenditure classification, ICP 2017................................. 102 C.2 Expenditure classification, ICP 2017................................................................... 104 D.1 ICP 2017 Reference PPPs.................................................................................... 116 E.1 Gross domestic product (GDP): Revised ICP 2011 results.................................. 120 E.2 Actual individual consumption (AIC): Revised ICP 2011 results...................... 126 E.3 Individual consumption expenditure by households: Revised ICP 2011 results.................................................................................................................. 132 E.4 Consumption expenditure by government: Revised ICP 2011 results.............. 138 E.5 Gross fixed capital formation (GFCF): Revised ICP 2011 results....................... 144 E.6 Domestic absorption: Revised ICP 2011 results.................................................. 150 E.7 Gross domestic product (GDP) and individual consumption expenditure for nonparticipating economies: Revised ICP 2011 results...................................... 156 E.8 Gross domestic product: Comparison of revised ICP 2011 results with original ICP 2011 results..................................................................................... 157 E.9 Individual consumption expenditure by households: Comparison of revised ICP 2011 results with original ICP 2011 results................................................. 162 F.1 Gross domestic product (GDP): Comparison of ICP 2017 results with data in World Development Indicators....................................................................... 168 F.2 Individual consumption expenditure by households: Comparison of ICP 2017 results with data in World Development Indicators........................... 173 J.1 Economies in East Asia and Pacific, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group..................................... 190 J.2 Economies in Europe and Central Asia, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group............. 191 J.3 Economies in Latin America and the Caribbean, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group............. 192 J.4 Economies in Middle East and North Africa, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group............. 193 J.5 Economies in North America, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group................................................ 193 J.6 Economies in South Asia, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group������������������������������������������������������ 193 J.7 Economies in Sub-Saharan Africa, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group������������������������������������ 194 viii    Contents Foreword As this report goes to publication, our planet is in research and development. PPPs are also used the midst of the COVID-19 pandemic, with coun- in other international indicators of economies’ tries facing costs to both lives and livelihoods. socioeconomic development, such as the World This report presents the latest results from the Bank’s twin goals of ending extreme poverty International Comparison Program’s (ICP) 2017 and promoting shared prosperity by 2030, the cycle and provides a view of the global economy United Nations’ human development index, the prior to the emergence of this pandemic. The ICP World Economic Forum’s global competitive- 2017 results will serve as a crucial benchmark of ness index, the Gates Foundation’s Goalkeepers the pre-COVID-19 size of the world economies Report, and the International Labour Organiza- from which to measure the economic impact on tion’s Global Wage Report, to name a few. various countries across the globe. The International Bank for Reconstruction and In 2017, the United States and China were Development and the International Monetary the two largest economies in the world and Fund both rely on the GDP in PPP terms of together accounted for a third of the global economies to determine their shareholding and economy. India, the third largest economy, drawing rights. accounted for around 7 percent of global gross The ICP is globally one of the largest data col- domestic product (GDP). The global economy, lection exercises undertaken—176 economies when measured using purchasing power parities participated in its 2017 cycle. At the same time, (PPPs) rather than market exchange rates, is split it is one of the most enduring—the program more or less equally between high-income and celebrated its 50th anniversary in 2018, having middle-income economies, with low-income grown from a modest research project spear- economies contributing just 1 percent of global headed by the United Nations Statistical Divi- GDP. The United States remained the economy sion and the International Comparisons Unit of with the highest level of per capita consumption, the University of Pennsylvania, supported by at nearly US$45,000 in PPP terms, more than financial contributions from the Ford Founda- four times the world average. Cross-country tion and the World Bank. inequality persisted, with around three-quarters Today the successful execution of the ICP is of the world’s population living in economies reliant on the close collaboration of national where the mean per capita income and con- statistical offices, regional agencies, and interna- sumption were below their respective global tional organizations. That partnership, together averages of US$16,596 and US$10,858. with a robust governance structure, an exten- The ICP is a global statistical initiative to col- sive capacity-building program, and an ambi- lect comparative price and expenditure data tious research agenda, ensures that the program and estimate PPPs for the world’s economies. and its results remain impactful and relevant to PPPs are used in monitoring progress toward its constituents and users and reflect our ever- the United Nations Sustainable Development changing world and its dynamic economies. Goals—in particular, the goals focusing on Looking ahead, we anticipate that the ICP poverty and inequality, agriculture, health, will evolve to meet both our users’ demands education, energy and emissions, labor, and and the challenges of the new decade by ix reflecting the rapid change in buying habits tak- the United Nations Economic and Social Com- ing place across the world, not only in what we mission for Western Asia. Although the respon- consume today but also in the outlets and plat- sibility for oversight rested with the ICP forms through which we purchase these goods Governing Board, the program would not have and services, and by complementing traditional been a success without the invaluable theoreti- surveys with new data sources such as scanner cal, conceptual, and methodological advice of data and web scraping. We also expect participa- the ICP Technical Advisory Group of renowned tion in the program to increase so that we leave experts, chaired by Nobel Laureate Sir Angus no country behind. This is especially true for Deaton. countries that are fragile and those that are The ICP 2017 results are based on the most affected by conflict and violence. We have comprehensive price and national accounts strived to ensure that these countries partook in expenditure data available, using the best meth- ICP 2017 capacity-building activities, and we ods that have been developed to date. We trust hope that they will join subsequent ICP cycles. that users of the ICP 2017 results will find this We would like to thank the participating report useful and that those results will provide economies that conducted the extensive surveys them with a base of crucial information for and data collections that underlie the PPPs. We research in comparative analysis and policy thank as well our partners who contributed to making. the success of ICP 2017—the African Develop- Over time, the ICP has evolved to become a ment Bank, the Asian Development Bank, the leading “global public good” exercise through International Monetary Fund, the Interstate the efforts of its worldwide partnership. We are Statistical Committee of the Commonwealth of two years into the ICP’s second half century, one Independent States, the Organisation for Eco- in which the world is growing more data savvy nomic Co-operation and Development, the Sta- and more data hungry, and we look forward to tistical Office of the European Union, the United PPPs and ICP data entering common parlance Kingdom’s Department for International Devel- and throwing a much-needed spotlight on the opment, the United Nations Economic Commis- economies, big and small, that together make up sion for Latin America and the Caribbean, and our global economy. Mari Elka Pangestu Managing Director for Development Policy and Partnerships The World Bank x    Foreword Acknowledgments The International Comparison Program (ICP) is Department of the IMF, the Fiji Bureau of Statis- one of the world’s largest statistical exercises. tics, the Organisation for Economic Co-opera- The 2017 cycle involved a partnership of 176 tion and Development (OECD), the Kingdom of economies and global, regional, and subre- Saudi Arabia’s General Authority for Statistics, gional agencies, working together within the the National Agency for Statistics and Demogra- program’s governance structure to produce the phy of Senegal, Statistics South Africa, Surina- results presented in this report. These achieve- me’s General Bureau of Statistics, UK DFID, the ments were made possible by the financial sup- US Bureau of Labor Statistics, the United Nations port of donors who contributed to funding this Economic Commission for Latin America and cycle. Special thanks go to the International the Caribbean (UN-ECLAC), the United Nations Monetary Fund (IMF) and the United King- Economic and Social Commission for Western dom’s Department for International Develop- Asia (UN-ESCWA), the United Nations Statistics ment (UK DFID), which contributed to a global Division (UNSD), and the World Bank’s DECDG. Multi-Donor Trust Fund, to the regional devel- Thanks are also extended to previous co-chairs opment banks and implementing agencies that of the Governing Board Konrad Pesendorfer, contributed to funding regional programs, and former Director General, Statistics Austria, and to the World Bank, which contributed to fund- T. C. A. Anant, former Chief Statistician of India ing the global program. and Secretary, Ministry of Statistics and Pro- The program is managed by the ICP Global gramme Implementation. Office, located at the World Bank Development The ICP Technical Advisory Group (TAG) Data Group (DECDG), under the leadership of deserves special acknowledgment. Under the Nada Hamadeh, Program Manager, and the chairmanship of Nobel Laureate Sir Angus Dea- oversight of Haishan Fu, DECDG Director. As ton, technical issues linked to the conceptual the strategic and policy-making body, the ICP integrity and methodological soundness of the Governing Board provides leadership and program were addressed by the group compris- ensures strict adherence to the program’s objec- ing W. Erwin Diewert, Robert C. Feenstra, Alan tives and strategic lines. The board was co- Heston, Walter Radermacher, D. Prasada Rao, chaired by Statistics Austria and India’s Ministry Pronab Sen, Paul Shreyer, and Xianchun Xu. of Statistics and Programme Implementation. Over the cycle, the TAG appointed task forces Thanks are extended to the institutions rep- and task teams to undertake specific research resented on the board: the African Development topics under its research agenda. Task forces and Bank (AfDB), the Asian Development Bank teams comprised the following experts: Alan (ADB), the Brazilian Institute of Geography and Heston, Bettina Aten, Luigi Biggeri, W. Erwin Statistics, the National Statistical Committee of Diewert, Levan Gogoberishvili, Brian Graf, Rob- the Republic of Belarus, China’s National Bureau ert Hill, Robert Inklaar, Massimiliano Iommi, of Statistics, the Interstate Statistical Committee Kaushal Joshi, Patrick Kelly, Francette Koechlin, of the Commonwealth of Independent States Paul Konijn, Dilip Kumar Sinha, Vasily (CIS-STAT), the Statistics Department of the Kuznetsov, Gregory Max Henri Legoff, Michel European Union (Eurostat), the Statistics Mouyelo-Katoula, Bala Bhaskar Naidu Kalimili, xi Liu Nan, Niall O’Hanlon, D. Prasada Rao, David national accounts expenditure data. The 2017 Roberts, Sergey Sergeev, Majed Skaini, Michael participating economies demonstrated complete Smedes, and staff of the Global Office. commitment and dedication to the ICP. We truly The results of ICP 2017 were calculated by owe them the utmost gratitude and appreciation the group of experts forming the computation for the amazing job they did in carrying out task team: Yuri Dikhanov, Alan Heston, Robert rigorous ICP activities over the last few years. Hill, Robert Inklaar, Francette Koechlin, Paul The Global Office team responsible for the Konijn, D. Prasada Rao, Miriam Steurer, and day-to-day work comprised Hanan Abushanab, Sergey Sergeev. Bettina Aten and Eric Figueroa Shriya Chauhan, Rui Costa, Yuri Dikhanov, advised on the process for producing the results. Nancy Kebe, Maurice Nsabimana, Christelle Our achievement was made possible by the Signo Kouame, Elizabeth Purdie, Marko Olavi relentless work of the regional coordinators Rissanen, Inyoung Song, William Vigil Oliver, with their supporting teams: Ben Paul Mungyer- Mizuki Yamanaka, and Zhe Zhao. Several col- eza and Gregoire Mboya De Loubassou (AfDB) leagues from other DECDG units provided valu- for Africa; Kaushal Joshi with the support of able support to the Global Office, including Criselda de Dios and Stefan Schipper (ADB) for Jomo Tariku and David Mariano. Asia and the Pacific; Andrey Kosarev and Vale- This report was drafted by the Global Office rica Accibas (CIS-STAT) for the Commonwealth team and presents a summary of results for of Independent States; Rolando Ocampo, 2017, alongside revised results for 2011. More Giovanni Savio, Bruno Lana, María Paz Col- detailed data for both of these reference years linao, and Federico Dorin (UN-ECLAC) with and data for the interim years can be accessed Philomen Harrison (CARICOM) for Latin Amer- through icp.worldbank.org. It was edited by ica and the Caribbean; and Majed Skaini with Elizabeth Purdie and David Roberts. Final edit- the support of Sadim Sbeiti (UN-ESCWA) for ing was done by Elizabeth Forsyth, and proof- Western Asia. The program also relied on close reading was done by Alfred Imhoff. The cover cooperation with Francette Koechlin and Sophie was designed by Jomo Tariku. Bournot (OECD) and Paul Konijn and Marjanca We are grateful to all of the dedicated Gasic (Eurostat), who led the Eurostat-OECD renowned experts and global, regional, and PPP Programme. subregional institutions that contributed their Although the Global Office and the regional knowledge, expertise, time, and resources to coordinators play a crucial role in implementing this daunting effort. We particularly recognize the ICP, the cornerstone of the program consists the major role played by the national imple- of the national implementing agencies, which menting agencies in all 176 participating econo- are responsible for the bulk of ICP activities, from mies. We all share the credit for the production the collection of price data to the compilation of of this unique global public good. Pravin Srivastava Werner Holzer Chief Statistician of India and Secretary, Director General–Statistics, Ministry of Statistics and Programme Statistics Austria Implementation xii    Acknowledgments Abbreviations ADB Asian Development Bank AfDB African Development Bank AFRISTAT Economic and Statistical Observatory of Sub-Saharan Africa AIC actual individual consumption CAR country approach with redistribution (procedure) CARICOM Caribbean Community CEP consumption expenditure of the population CIS Commonwealth of Independent States CIS-STAT Interstate Statistical Committee of the Commonwealth of Independent States COFOG Classification of the Functions of Government COICOP Classification of Individual Consumption According to Purpose COMECON Council for Mutual Economic Assistance COMESA Common Market for Eastern and Southern Africa COPNI Classification of the Purposes of Nonprofit Institutions Serving Households CPA  Statistical Classification of Products by Activity in the European Economic Community CPD country product dummy (method) CPD-W country product dummy-weighted (method) CPI consumer price index CV coefficient of variation DECDG Development Data Group (World Bank) DFID Department for International Development (United Kingdom) ECOSOC United Nations Economic and Social Council Eurostat Statistical Office of the European Union FISIM financial intermediation services indirectly measured f.o.b. free on board FOC UNSC Friends of the Chair group GCL global core list GDP gross domestic product GEKS Gini-Éltető-Köves-Szulc (method) GFCF gross fixed capital formation GNI gross national income IACG Inter-Agency Coordination Group (ICP) ICP  International Comparison Program (International Comparison Project prior to 1990) IMF International Monetary Fund xiii ISO International Organization for Standardization n.e.c. not elsewhere classified NPISHs nonprofit institution serving households OECD Organisation for Economic Co-operation and Development OEEC Organisation for European Economic Co-operation PLI price level index PPI producer price index PPP purchasing power parity SAR special administrative region SDGs Sustainable Development Goals SHA System of Health Accounts SNA System of National Accounts SPD structured product description TAG Technical Advisory Group (ICP) UNESCO United Nations Educational, Scientific, and Cultural Organization UNSC United Nations Statistical Commission UNSD United Nations Statistics Division UNSO United Nations Statistics Office UN-ECLAC United Nations Economic Commission for Latin America and the Caribbean UN-ESCWA United Nations Economic and Social Commission for Western Asia VAT value added tax WDI World Development Indicators XR market exchange rate All dollar amounts are US dollars unless otherwise indicated. xiv    Abbreviations CHAPTER 1 Overview of main findings Size of economies East Asia and Pacific accounted for the largest regional share under both measures—just under In 2017, global output, when measured by pur- one-third of global GDP. This economic share chasing power parities (PPPs), was $119,547 was roughly in line with the region’s population billion, compared with $79,715 billion, when share of 32 percent. A similar consistency was measured by market exchange rates. In both also seen in Latin America and the Caribbean— cases, global output refers to the sum of gross the region’s share of GDP in PPP terms, GDP in domestic product (GDP) for all 176 economies market exchange rate terms, and population that participated in the International Com­ were all around 7 to 8 percent of the global parison Program (ICP) 2017 cycle. Figure 1.1 total. At the same time, both North America and shows the distribution of global output by geo- Europe and Central Asia had economic shares graphic region and income group and compares under the two alternative economic measures PPP-based shares with market exchange rate– that far exceeded their population shares, while based shares, examining these distributions the converse was true in South Asia and Sub- against shares of the global population. It illus- Saharan Africa. The consequences of these dis- trates that, in PPP terms, low- and middle- tributions are explored further in the analysis of income economies contributed more than half expenditure per capita. of the global economy in 2017, a significantly Figure 1.2 shows, for a given economy, its GDP higher share than when measured using mar- in 2017 and its share of global GDP, represented ket exchange rates. by the size of the economy’s respective box. In 2017 lower-middle-income economies Economies are grouped by geographic region, contributed around 16 percent to PPP-based and each color-coded area represents that region’s global GDP, while upper-middle-income econo- share of global GDP in PPP-based US dollars. mies contributed 34 percent. At the same time, China’s GDP stood at $19,617 billion in PPP high-income economies contributed 49 percent. terms in 2017, while the United States’ GDP was In terms of market exchange rates, these shares $19,519 billion. Together they accounted for one- were 8 percent, 28 percent, and 64 percent, third of global GDP. India, at $8,051 billion, was respectively. Low-income economies contrib- the third-largest economy, followed by Japan, uted less than 1 percent to the global economy Germany, and the Russian Federation. Overall, under both measures—namely, 0.8 percent of 19 economies contributed three-quarters of global GDP in PPP terms and 0.5 percent in mar- global GDP; three of these economies (India, ket exchange rate terms—despite accounting for Indonesia, and the Arab Republic of Egypt) were nearly 8 percent of the world’s population. classified as lower-middle-income economies, 1 Figure 1.1  Share of global PPP-based and market exchange rate–based GDP and share of global population, by region and income group, 2017 East Asia and Pacific 31.1 30.0 31.5 Europe and Central Asia 25.8 26.9 12.1 Latin America and the Caribbean 7.7 6.6 8.0 Middle East and North Africa 6.0 3.9 5.3 North America 17.8 26.6 5.0 South Asia 8.5 4.1 23.9 Sub-Saharan Africa 3.1 1.9 14.2 High income 48.8 64.0 16.6 Upper-middle income 34.4 27.7 35.5 Lower-middle income 15.9 7.8 40.2 Low income 0.8 0.5 7.7 0 20 40 60 0 20 40 60 0 20 40 60 Share of global GDP, PPP-based (%) Share of global GDP, Share of global population (%) market exchange rate–based (%) Source: ICP 2017. Note: PPP = purchasing power parity. and six (China, the Russian Federation, Brazil, 1.4 provides an overview of the regional and Mexico, Turkey, and the Islamic Republic of Iran) income group distribution of global expenditure were classified as upper-middle-income econo- for a selection of the expenditure components mies, with the remainder classified as high- within AIC, while figure 1.5 shows the share of income economies. Together, they represented nominal GDP that is spent on these components nearly 64 percent of the global population. in each income group or region. Of note, Sub-Saharan Africa had a greater share of global expenditure on food and nonal- coholic beverages (8 percent) than its share of GDP expenditure components global health expenditure (2 percent). This out- It is also possible to examine the global distribu- come is explained to a large extent by these tion of the expenditure components of GDP, expenditure components’ share of GDP in the such as expenditure by households, by govern- region: food and nonalcoholic beverages ment, and on investment. accounted for nearly 30 percent of GDP, about Figure 1.3 shows the distribution of expendi- eight times as much as was spent on health. ture on actual individual consumption (AIC), a Despite high-income economies contributing measure to assess average material well-being, half of global GDP, the group collectively defined as individual consumption expenditure accounted for around just one-third of global by households, plus individual consumption expenditure on food and nonalcoholic beverages expenditure by government, plus individual con- and for just over one-third of global spending on sumption expenditure by nonprofit institutions actual education. Furthermore, this income serving households (NPISHs). The United States group, representing 17 percent of the global accounted for just under one-fifth of AIC across population, accounted for more than half of the world. Overall, six economies accounted for global expenditure on health and allocated more around half of all global AIC expenditure. Figure than 10 percent of its collective GDP to that 2    Purchasing Power Parities and the Size of World Economies Figure 1.2  PPP-based GDP and share of global PPP-based GDP, by economy, 2017 2017 PPP $ (billions), and global share (%) Japan $5,173B 4.3% United States Indonesia Korea, Rep. $19,519B $2,894B $2,106B 16.3% 2.4% 1.8% China $19,617B 16.4% Taiwan, China Malaysia Australia $1,113B $818B $1,234B 0.9% 0.7% 1% Singapore Philippines $527B $815B 0.4% Brazil Thailand 0.7% $3,018B $1,203B 2.5% 1% Vietnam $677B 0.6% India $8,051B 6.7% Mexico $2,470B 2.1% United Kingdom France Italy $3,037B $2,994B $2,530B 2.5% 2.5% 2.1% Germany Chile Peru $4,382B Argentina $438B $393B 3.7% $1,038B 0.4% 0.3% 0.9% Switzerland Romania Sweden Pakistan Bangladesh Colombia $567B $535B $530B $991B $711B $700B Turkey Poland 0.5% 0.4% 0.4% 0.8% 0.6% 0.6% $2,266B $1,145B 1.9% 1% Ukraine Austria Kazakhstan $504B $481B $448B Egypt, Arab Rep. United Nigeria South 0.4% 0.4% 0.4% Saudi Arabia Arab $1,263B Emirates $885B Africa Czech Norway Denmark Greece $1,566B 1.1% $624B 0.7% $734B Russian Federation 1.3% Republic $332B $317B $313B 0.5% 0.6% $3,830B Netherlands $408B 3.2% $948B 0.3% 0.3% 0.3% 0.3% Algeria Israel Morocco Angola 0.8% $340B $264B $219B Ireland $478B Spain 0.3% 0.2% 0.2% $376B 0.4% $1,844B Iran, Islamic Rep. Qatar Kenya 0.3% $204B 1.5% Belgium $1,298B $259B Portugal 1.1% Iraq 0.2% 0.2% $578B Sudan $341B $368B 0.5% $177B 0.3% 0.3% 0.1% East Asia and Pacific Latin America and the Caribbean North America Sub-Saharan Africa Europe and Central Asia Middle East and North Africa South Asia Source: ICP 2017. Note: PPP = purchasing power parity. Overview of main findings 3 Figure 1.3  Share of PPP-based global actual individual component. Much of this spending was due to consumption for the six economies with the largest shares, 2017 the large North American share of global health spending (around one-quarter) and the relatively 100 high cost of health care in the United States (around 80 percent higher than the world aver- age). Price levels of this and other expenditure 80 components are examined later in this chapter. Rest of the world 50.9 On average, around 11 percent of GDP was spent on housing and utilities (water, electricity, gas, and other fuels), ranging from nearly 8 per- Share of global AIC (%) 60 cent in Sub-Saharan Africa to nearly 13 percent in Europe and Central Asia and North America. Russian Federation 3.2 Globally, around 5 percent was spent on educa- Germany 3.6 tion, and there is relatively little variation 40 Japan 4.4 between regions and income groups for this India 7.0 category of spending (figure 1.5). Figure 1.6 shows consumption expenditure China 12.2 20 by government. China had the largest share, accounting for around 14 percent of the global United States 18.6 total. Figure 1.7 shows expenditure on investment 0 as defined by gross fixed capital formation Source: ICP 2017. (GFCF). China had by far the largest share of Note: AIC = actual individual consumption; PPP = purchasing power parity. expenditure on investment, nearly double that Figure 1.4  Share of global PPP-based expenditure on selected expenditure components of actual individual consumption, by region and income group, 2017 East Asia and Pacific 25.3 26.0 31.8 28.3 Europe and Central Asia 23.6 25.8 24.8 26.6 Latin America and the Caribbean 10.6 7.4 6.1 13.9 Middle East and North Africa 6.6 9.5 4.2 5.8 North America 11.1 17.9 24.7 11.8 South Asia 15.0 10.1 6.7 9.1 Sub-Saharan Africa 7.8 3.3 1.6 4.5 High income 33.9 47.5 53.6 37.2 Upper-middle income 33.4 32.0 34.0 41.9 Lower-middle income 30.1 19.2 12.0 19.6 Low income 2.6 1.2 0.4 1.3 0 10 20 30 40 50 60 0 10 20 30 40 50 60 0 10 20 30 40 50 60 0 10 20 30 40 50 60 Share of food and Share of housing, water, Share of health (%) Share of education (%) nonalcoholic beverages (%) electricity, gas, and other fuels (%) Source: ICP 2017. Note: PPP = purchasing power parity. 4    Purchasing Power Parities and the Size of World Economies Figure 1.5  Nominal expenditure on selected expenditure components of actual individual consumption as a share of nominal GDP, by region and income group, 2017 East Asia and Pacific 8.2 8.7 7.2 5.2 Europe and Central Asia 7.5 12.9 7.9 4.5 Latin America and the Caribbean 13.6 10.4 7.1 6.0 Middle East and North Africa 11.7 11.4 4.9 5.5 North America 4.3 12.8 15.1 6.2 South Asia 19.5 9.4 3.9 4.5 Sub-Saharan Africa 29.1 7.7 3.8 5.5 World 8.3 11.1 9.2 5.3 High income 5.7 12.7 11.0 5.4 Upper-middle income 10.0 8.2 6.6 5.3 Lower-middle income 22.7 8.5 3.9 4.9 Low income 37.0 10.2 3.0 4.7 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 0 10 20 30 40 Food and nonalcoholic beverages Housing, water, electricity, gas Health share of GDP (%) Education share of GDP (%) share of GDP (%) and other fuels share of GDP (%) Source: ICP 2017. Figure 1.6  Share of PPP-based global consumption Figure 1.7  Share of PPP-based global gross fixed expenditure by government for the six economies with capital formation for the six economies with the largest the largest shares, 2017 shares, 2017 100 100 80 80 Rest of the world 42.9 Share of global consumption by government (%) Rest of the world 55.3 Share of global GFCF (%) 60 60 Indonesia 2.9 Germany 3.1 Japan 4.0 France 3.6 India 6.8 40 Germany 4.2 40 Japan 5.5 United States 13.9 Russian Federation 5.6 20 United States 11.3 20 China 26.4 China 14.5 0 0 Source: ICP 2017. Source: ICP 2017. Note: PPP = purchasing power parity Note: GFCF = global expenditure on gross fixed capital formation; PPP = pur- chasing power parity. Overview of main findings 5 of the United States and equating to more than measure is important for cross-country compari- one-quarter of global investment. sons, as they reflect the purchasing power of a consumer for the goods and services they choose to buy. Figure 1.8 shows the distribution of GDP Per capita measures across economies in both 2011 and 2017. Econ- GDP per capita is sometimes considered an indi- omies are arranged in order of increasing GDP cator of an economy’s average material well- per capita along the vertical axis and presented being. However, GDP per capita assigns high as rectangular boxes. The vertical scale corre- values to “income-rich” economies where the sponds to each economy’s share of the global national wealth is not reflected to the same population. The index of GDP per capita, based extent in the material well-being of their popula- on the world set equal to 100, is shown on the tions. In addition, an economy’s high value of horizontal axis. Each economy’s size in terms of GDP per capita can at times reflect high levels of relative GDP is thus represented by the area of GFCF and consumption expenditure by govern- its box, which is the product of GDP per capita ment, as well as a high level of net exports. AIC and population. per capita is more useful when describing the The dotted lines at world = 100 represent the average material well-being of people within an global mean GDP per capita for each year, which economy. Using PPP-derived estimates of either was $13,920 in 2011 PPPs and $16,596 in 2017 Figure 1.8  Index of PPP-based GDP per capita and share of global population, by economy, 2011 and 2017 100 United States United States Germany Germany 90 Japan Japan Russian Federation Turkey Iran, Islamic Rep. Russian Federation 80 Turkey Mexico Mexico Thailand Brazil Iran, Islamic Rep. Brazil Cumulative share of global population (%) Thailand 70 Egypt, Arab Rep. 60 China China 50 Egypt, Arab Rep. Indonesia Indonesia Philippines 40 Philippines Vietnam Nigeria Vietnam 30 India India 20 Pakistan Pakistan Nigeria Bangladesh 10 Bangladesh Ethiopia Ethiopia Congo, Dem. Rep. Congo, Dem. Rep. 0 700 600 500 400 300 200 100 0 100 200 300 400 500 600 700 Index of GDP per capita (world = 100) 2011 2017 Source: ICP 2017. Note: PPP = purchasing power parity 6    Purchasing Power Parities and the Size of World Economies PPPs. The lines’ intersection with the boxes Figure 1.9  PPP-based actual individual consumption per capita shows the disparity in GDP per capita across the and share of global population, by economy, 2017 globe for the two years. Comparing the two 100 halves of the graph reveals changes in econo- United States mies’ standing relative to each other in the Germany world order of GDP per capita. For example, it 90 Japan shows that between 2011 and 2017, China and India moved up the ladder to occupy relatively Turkey Russian Federation higher positions in 2017 vis-à-vis other econo- 80 Mexico mies than they did in 2011.  Egypt, Arab Rep. In 2017, Luxembourg had the highest GDP Brazil 70 Thailand per capita at $112,701, or 679 percent of the Iran, Islamic Rep. world average, and Burundi had the lowest at Cumulative share of global population (%) $784, at around 5 percent. 60 Figure 1.9 shows the distribution of AIC in China 2017. Economies are arranged in order of increasing AIC per capita along the vertical axis 50 and presented as rectangles. Again, the vertical Indonesia scale corresponds to each economy’s share of Philippines the global population. AIC per capita is shown 40 Vietnam on the horizontal axis. Each economy’s size in Pakistan terms of AIC is thus represented by the area of World: $10,858 30 its box. The United States had the highest level of India AIC per capita, at $44,620, and Niger had the 20 lowest, at $661. The mean AIC per capita for the world was $10,858. Nigeria Figure 1.10 compares PPP-based GDP per Bangladesh 10 capita with PPP-based AIC per capita for the 12 economies with the highest GDP per capita. The Ethiopia Congo, Dem. Rep. big disparities between GDP per capita and AIC 0 $0 $10,000 $20,000 $30,000 $40,000 per capita for Brunei Darussalam and Qatar are explained by the fact that these economies had AIC per capita AIC values that accounted for just 27 percent Source: ICP 2017. and 31 percent of their nominal GDP, respec- Note: AIC = actual individual consumption; PPP = purchasing power parity. tively. They are therefore “income-rich” econo- mies, where the national wealth is not reflected the high-income group of economies all spent to the same extent in the average consumption nearly three times as much on a per capita basis levels of their populations. as the world average on consumption expendi- Figure 1.11 shows the variability in the index ture by government. of PPP-based per capita measures of GDP and its major expenditure components across regions and income groups based on world = 100. The Intercountry income inequality high expenditure on GFCF in China was reflected in a relatively high GFCF per capita Intercountry income inequality can be mea- index of 131 for the East Asia and Pacific sured by the population-weighted Gini measure region, the only expenditure component for of income inequality based on PPP-based GDP that region above the world average. Sub- per capita. Saharan Africa was well below the world aver- Figure 1.12 compares the distribution of GDP age, with an index of 14 for GFCF per capita. per capita in 2017 and 2011. For 2011, both North America, Europe and Central Asia, and revised data and originally published data are Overview of main findings 7 Figure 1.10  PPP-based GDP per capita and actual individual economies common to both the 2011 and 2017 consumption per capita for the 12 economies with the highest ICP cycles are included. A 45-degree line repre- PPP-based GDP per capita, 2017 sents perfect income equality. The Gini coeffi- Luxembourg cient measures the distribution of expenditure across economies and the extent to which an Qatar economy deviates from the hypothetical distri- Singapore bution if all economies had the same share of Ireland global GDP as their share of global population. It reflects the area between the Lorenz curve and Bermuda the line of equality, with a value of 0 reflecting Cayman Islands perfect income equality and a value of 1 repre- Switzerland senting perfect income inequality. While the intercountry Gini coefficient for United Arab Emirates PPP-based GDP per capita improved slightly, Norway from 0.487 in 2011 (for both revised and origi- Brunei Darussalam nal data) to 0.474 in 2017, the share of the United States global population living in economies where the mean GDP per capita is below the global average Hong Kong SAR, China increased from 72.1 percent to 75.9 percent $0 $20,000 $40,000 $60,000 $80,000 $100,000 over the same time period. GDP per capita AIC per capita The same plot can be made for PPP-based AIC Source: ICP 2017. per capita, and figure 1.13 shows a bigger change Note: AIC = actual individual consumption; PPP = purchasing power parity. than that for GDP per capita, with Gini coeffi- cients falling from 0.506 in 2011 to 0.477 in presented, and the three data sets are plotted as 2017. However, the share of the global popula- Lorenz curves of cumulative percentages of tion living in economies where the mean AIC per expenditure against the cumulative population, capita is below the global average increased from beginning with the poorest economy. Only 69.7 percent in 2011 to 74.3 percent in 2017. Figure 1.11  Index of PPP-based expenditure per capita for GDP and major expenditure components, by region and income group, 2017 (world = 100) East Asia and Pacific 99 84 92 131 Europe and Central Asia 212 215 279 188 Latin America and the Caribbean 97 109 113 67 Middle East and North Africa 113 107 140 99 North America 355 401 262 305 South Asia 35 38 18 34 Sub-Saharan Africa 22 27 22 14 High income 294 301 297 273 Upper-middle income 97 88 109 112 Lower-middle income 40 44 27 35 Low income 11 14 10 8 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 Index of GDP per capita Index of AIC per capita Index of consumption expenditure Index of GFCF per capita by government per capita Source: ICP 2017. Note: AIC = actual individual consumption; GFCF = gross fixed capital formation; PPP = purchasing power parity. 8    Purchasing Power Parities and the Size of World Economies Price levels Figure 1.12  Lorenz curves for the distributions of 2017, revised 2011, and original 2011 PPP-based GDP per capita The price level index (PLI)—the ratio of a PPP to 100 its corresponding market exchange rate—is used to compare the price levels of economies. Figure 1.14 (panel a) presents a multidimensional com- parison of PPP-based GDP per capita of each 75 Cumulative share of expenditure (%) economy relative to its GDP PLI based on the world set equal to 100 for 2017. Each economy is represented by a circle with an area propor- tional to its GDP and color-coded by region. As 50 a general observation, PLIs at the GDP level tend to be generally lower in economies with lower GDP per capita. This observation is consistent with the fact that, as an economy develops, con- 25 sumers move from consuming basic goods that Year Gini coefficient are also tradable to consuming more services Original 2011 0.487 Revised 2011 0.487 that are not tradable. As wage rates increase, so 2017 0.474 do the costs of services, which subsequently 0 push up the general price level. 0 25 50 75 100 In the case of most high-income economies, Cumulative share of population (%) toward the right of the figure, price levels Original 2011 Revised 2011 2017 increase very sharply with relatively small Sources: ICP 2011, 2017. Note: Gini coefficients are population-weighted and based on the 173 economies changes in GDP per capita, whereas price levels common to both ICP 2011 and ICP 2017. PPP = purchasing power parity. for less wealthy economies increase less promi- nently with changes in income. Bermuda was the most expensive economy, with a PLI of 205. Figure 1.13  Lorenz curves for the distributions of 2017, revised There are some interesting outliers: small, high- 2011, and original 2011 PPP-based actual individual consumption income economies within the Middle East and per capita North Africa and the East Asia and Pacific 100 regions had relatively low price levels, while Egypt had the lowest PLI of all economies, despite having a GDP per capita in excess of $13,000 and being one of the richest of the 75 Cumulative share of expenditure (%) lower-middle-income group of economies. Figure 1.15 charts the PLIs for major expen- diture components by region and income group. It shows the high price levels prevalent in North 50 America. It also shows both the high cost of GFCF in both Sub-Saharan Africa and the low- income economies and the low PLI for AIC in South Asia and the lower-middle-income 25 group. Year Gini coefficient Original 2011 0.513 Figure 1.16 shows the PLIs for 17 expendi- Revised 2011 0.506 ture components alongside the PLI for GDP for 2017 0.477 0 each region. Across most expenditure compo- 0 25 50 75 100 nents, South Asia recorded the lowest PLIs, Cumulative share of population (%) while North America recorded the highest. The Original 2011 Revised 2011 2017 difference between these two regions was most Sources: ICP 2011, 2017. pronounced for education, ranging from a PLI of Note: Gini coefficients are population-weighted and based on the 173 economies 38 in South Asia to 261 in North America. common to both ICP 2011 and ICP 2017. PPP = purchasing power parity. Overview of main findings 9 Figure 1.14  GDP price level index versus PPP-based GDP per capita (and PPP-based GDP), by economy, 2017 and 2011 a. 2017 200 180 160 GDP price level index (world = 100) United States 140 Japan Luxembourg Germany 120 Brazil 100 China 80 Mexico Congo, Dem. Rep. Nigeria Philippines Thailand Russian Federation 60 Burundi Bangladesh Indonesia Turkey Ethiopia Pakistan Vietnam 40 India Iran, Islamic Rep. 20 Egypt, Arab Rep. 0 $500 $1,000 $2,000 $5,000 $10,000 $20,000 $50,000 $100,000 GDP per capita b. 2011 200 180 Japan 160 Luxembourg GDP price level index (world = 100) 140 Germany United States 120 Brazil 100 Mexico 80 Congo, Dem. Rep. Russian Federation Nigeria China Turkey 60 Philippines Thailand Indonesia Burundi Bangladesh 40 Vietnam Iran, Islamic Rep. Ethiopia Pakistan India Egypt, Arab Rep. 20 0 $500 $1,000 $2,000 $5,000 $10,000 $20,000 $50,000 $100,000 GDP per capita GDP East Asia and Pacific North America $5,000 billion Europe and Central Asia South Asia $10,000 billion Latin America and the Caribbean Sub-Saharan Africa Middle East and North Africa $15,000 billion $20,000 billion Source: ICP 2017. Note: A logarithmic scale is used for GDP per capita. PPP = purchasing power parity. 10    Purchasing Power Parities and the Size of World Economies Figure 1.15  Price level indexes for GDP and major expenditure components, by region and income group, 2017 (world = 100) East Asia and Pacific 96 96 101 99 Europe and Central Asia 104 106 94 98 Latin America and the Caribbean 86 85 73 90 Middle East and North Africa 65 61 59 70 North America 149 149 179 143 South Asia 48 44 60 55 Sub-Saharan Africa 62 57 51 86 High income 131 135 137 121 Upper-middle income 81 76 70 91 Lower-middle income 49 46 47 58 Low income 56 49 48 84 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 GDP PLI AIC PLI Consumption expenditure GFCF PLI by government PLI Source: ICP 2017. Note: AIC = actual individual consumption. GFCF = gross fixed capital formation; PLI = price level index. In Sub-Saharan Africa, PLIs for all expendi- Per capita measures provide another view, as do ture components, except machinery and equip- PLIs. This section reviews the inherent variabil- ment, were significantly below the world aver- ity across economies with regard to expenditure age of 100. In South Asia, the lowest PLIs were per capita and PLIs. recorded for health and housing, and the high- Across the 176 economies analyzed here, est were for alcoholic beverages, narcotics, and PPP-based GDP per capita ranged from $112,701 tobacco and for machinery and equipment. in Luxem­ bourg to $784 in Burundi—a range of Both East Asia and Pacific and Europe and Cen- 144 based on the ratio of the maximum to mini- tral Asia had PLIs across many expenditure mum values. The GDP PLI across the 176 econo- components that clustered near the world aver- mies varied from 205 in Bermuda to 27 in age of 100. This pattern is also seen to a large Egypt—a range of 7.5—suggesting that there is extent in Latin America and the Caribbean— much less variation in price levels than in per however, education is an outlier, with a PLI of capita measures. 54. The Middle East and North Africa had PLIs The coefficient of variation (CV) provides a below the world average, with the PLI for hous- measure of average variability. Figure 1.17 shows ing being the lowest, at 42. the CVs for both the index of PPP-based expendi- ture per capita and the PLI for expenditure com- ponents and examines the homogeneity of econ- Variability across economies omies within each region and across the world. The CV for the index of expenditure per capita The global economy is very complex, with appears on the left-hand side of each graph, and extreme differences in the overall size of econo- the CV for the PLI appears on the right-hand mies as measured by GDP and how it is distrib- side. The number of economies that participated uted across the major expenditure components. in the 2017 cycle within each region differed Overview of main findings 11 Figure 1.16  Price level indexes for GDP and 17 expenditure components, by region, 2017 (world = 100) East Asia and Pacific Europe and Central Asia Latin America and the Caribbean Gross domestic product (GDP) 96 103 86 Actual individual consumption (AIC) 96 106 85 Food and nonalcoholic beverages 116 103 102 Alcoholic beverages, tobacco and narcotics 106 93 84 Clothing and footwear 123 118 108 Actual housing, water, electricity, gas and other fuels 90 121 83 Furnishings, household equipment and routine household maintenance 106 107 89 Health 74 94 83 Transport 93 123 95 Communication 102 87 109 Recreation and culture 84 106 89 Education 104 85 54 Restaurants and hotels 81 121 78 Miscellaneous goods and services 99 101 79 Individual consumption expenditure by households 95 109 89 Consumption expenditure by government 101 94 73 Machinery and equipment 115 89 110 Construction 92 121 89 0 50 100 150 200 250 0 50 100 150 200 250 0 50 100 150 200 250 Middle East and North Africa North America South Asia Gross domestic product (GDP) 65 149 48 Actual individual consumption (AIC) 61 149 44 Food and nonalcoholic beverages 83 124 63 Alcoholic beverages, tobacco and narcotics 95 131 95 Clothing and footwear 74 134 40 Actual housing, water, electricity, gas and other fuels 42 171 34 Furnishings, household equipment and routine household maintenance 68 118 52 Health 49 176 26 Transport 62 112 62 Communication 60 202 40 Recreation and culture 76 118 261 41 Education 69 38 Restaurants and hotels 65 129 42 Miscellaneous goods and services 63 134 48 Individual consumption expenditure by households 60 143 44 Consumption expenditure by government 59 179 60 Machinery and equipment 97 91 250 91 Construction 60 43 0 50 100 150 200 250 0 50 100 150 200 250 0 50 100 150 200 250 Sub-Saharan Africa Gross domestic product (GDP) 62 Actual individual consumption (AIC) 57 Food and nonalcoholic beverages 87 Alcoholic beverages, tobacco and narcotics 60 Clothing and footwear 50 Actual housing, water, electricity, gas and other fuels 41 Furnishings, household equipment and routine household maintenance 54 Health 51 Transport 80 Communication 68 Recreation and culture 56 Education 45 Restaurants and hotels 47 Miscellaneous goods and services 52 Individual consumption expenditure by households 58 Consumption expenditure by government 51 Machinery and equipment 131 Construction 67 0 50 100 150 200 250 Source: ICP 2017. 12    Purchasing Power Parities and the Size of World Economies Figure 1.17  Coefficients of variation: Index of PPP-based expenditure per capita and price level index for GDP and 17 expenditure components, by region, 2017 World East Asia and Pacific Europe and Central Asia Gross domestic product (GDP) 95 43 83 46 60 47 Actual individual consumption (AIC) 79 49 74 48 42 52 Food + nonalcoholic beverages 55 32 44 36 26 31 Alcoholic beverages, tobacco + narcotics 120 49 73 57 63 54 Clothing + footwear 90 43 101 47 66 22 Actual housing, water, electricity, gas + other fuels 86 76 71 82 36 69 Furnishings, household equipment + routine household maintenance 90 39 89 35 61 25 Health 97 67 88 64 46 72 Transport 96 34 83 32 65 33 Communication 84 45 83 41 38 44 Recreation + culture 131 43 126 45 68 40 Education 69 88 60 68 23 93 Restaurants + hotels 126 50 102 56 80 44 Miscellaneous goods + services 115 47 110 43 73 51 Individual consumption expenditure by households 79 47 76 47 43 47 Consumption expenditure by government 89 62 98 56 43 72 Machinery + equipment 132 21 90 10 91 8 Construction 138 57 101 82 65 50 250 200 150 100 50 0 50 100 250 200 150 100 50 0 50 100 250 200 150 100 50 0 50 100 Latin America and the Caribbean Middle East and North Africa North America Gross domestic product (GDP) 63 32 84 35 16 17 Actual individual consumption (AIC) 51 35 56 41 12 22 Food + nonalcoholic beverages 31 28 38 25 29 19 Alcoholic beverages, tobacco + narcotics 81 31 114 36 24 19 Clothing + footwear 69 29 49 35 23 18 Actual housing, water, electricity, gas + other fuels 87 51 63 74 23 24 Furnishings, household equipment + routine household maintenance 59 36 73 32 15 8 Health 59 50 70 50 37 23 Transport 65 27 74 36 10 15 Communication 71 38 59 37 33 8 Recreation + culture 78 32 112 32 27 20 Education 62 67 64 55 5 28 Restaurants + hotels 90 35 122 44 45 19 Miscellaneous goods + services 85 29 74 38 15 17 Individual consumption expenditure by households 53 34 53 39 18 23 Consumption expenditure by government 69 43 75 44 20 15 Machinery + equipment 94 21 157 17 29 28 Construction 82 40 136 48 29 18 250 200 150 100 50 0 50 100 250 200 150 100 50 0 50 100 250 200 150 100 50 0 50 100 South Asia Sub-Saharan Africa Gross domestic product (GDP) 60 22 120 17 Actual individual consumption (AIC) 41 30 107 19 Food + nonalcoholic beverages 19 15 79 22 Alcoholic beverages, tobacco + narcotics 54 46 168 37 Clothing + footwear 42 20 97 33 Actual housing, water, electricity, gas + other fuels 34 70 167 31 Furnishings, household equipment + routine household maintenance 64 25 144 23 Index of PPP-based expenditure Health 69 35 28 per capita CV Transport 83 26 136 20 189 PLI CV Communication 83 53 89 189 34 Recreation + culture 108 34 168 21 Education 62 52 115 43 Restaurants + hotels 113 17 125 38 Miscellaneous goods + services 77 17 164 19 Individual consumption expenditure by households 35 30 100 20 Consumption expenditure by government 89 34 164 25 Machinery + equipment 106 14 222 22 222 15 Construction 99 10 144 15 250 200 150 100 50 0 50 100 250 200 150 100 50 0 50 100 Source: ICP 2017. Note: CV = coefficient of variation; PLI = price level index; PPP = purchasing power parity. Overview of main findings 13 widely—from three economies in North America Comparison of 2017 results with to 46 economies in Europe and Central Asia. revised 2011 results Generally, the variation in index of expendi- ture per capita was much greater than the varia- This section presents summary charts compar- tion in price levels. One exception was the vari- ing 2017 results to the revised 2011 results. ability of education price levels, which was Revised 2011 results are provided in appendix E. driven by the CV of 93 percent for Europe and The set of economies that participated in the Central Asia, the largest CV for the PLI of any 2017 cycle differed somewhat from the set of expenditure component at the regional level. economies in the 2011 cycle. Thus the results The machinery and equipment component from the two years can be compared with some exhibited the lowest price variation at both the caution. The income grouping used for both regional and global levels, which is explained by years reflects the World Bank’s fiscal year 2020 its highly tradable character. However, the vari- classification of economies. ability of the index of expenditure per capita for Figure 1.18 shows the regional and income machinery and equipment exceeded that for group shares of GDP in both PPP terms and mar- most, if not all, other expenditure components ket exchange rate terms as well as their respec- across regions and for the world. tive shares of the global population. Compared Services such as health and education, as well with 2017, high-income economies had a higher as consumption expenditure by government, share of GDP both in PPP terms and in market showed the largest price level variations both exchange rate terms in 2011. Correspondingly, across the globe and across most regions. Hous- both lower-middle- and upper-middle-income ing, too, had high PLI variances. It is notewor- economies increased their share between the two thy that these expenditure components are also cycles. This mostly reflects the increases in the the most difficult to measure. shares of East Asia and Pacific and South Asia. Figure 1.18  Share of global PPP-based and market exchange rate–based GDP and share of global population, by region and income group, 2011 and 2017 East Asia and Pacific Europe and Central Asia Latin America and the Caribbean Middle East and North Africa North America South Asia Sub-Saharan Africa High income Upper-middle income Lower-middle income Low income 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 Share of global GDP, PPP-based (%) Share of global GDP, Share of global population (%) market exchange rate–based (%) 2011 2017 Source: ICP 2017. Note: PPP = purchasing power parity. 14    Purchasing Power Parities and the Size of World Economies Figure 1.19  Index of PPP-based expenditure per capita for GDP and major expenditure components, by region and income group, 2011 and 2017 (world = 100) East Asia and Pacific Europe and Central Asia Latin America and the Caribbean Middle East and North Africa North America South Asia Sub-Saharan Africa High income Upper-middle income Lower-middle income Low income 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 0 100 200 300 400 Index of GDP per capita Index of AIC per capita Index of consumption expenditure Index of GFCF per capita by government per capita 2011 2017 Source: ICP 2017. Note: AIC = actual individual consumption; GFCF = gross fixed capital formation; PPP = purchasing power parity. Comparing the index of PPP-based expendi- for 2017. Comparing 2017 to 2011, the most ture per capita for major expenditure compo- pronounced change is the drift of China and nents across the two years in figure 1.19 reveals India to the right (increasing GDP per capita) that East Asia and Pacific slightly increased its and upward (increasing PLI relative to the world index value versus the world average in all average). expenditure components, while the Middle East and North Africa saw a decrease. Both the upper-middle- and lower- middle-income Notes on the main findings groups saw an increase in their index of GDP per capita and AIC per capita, while the high- Analyses are limited to the economies that income group experienced a decrease in these participated in the specific reference year, and expenditure components’ indexes between this group differs between 2011 and 2017. 2011 and 2017. Macao SAR, China; Guatemala; the República Price levels fell between 2011 and 2017 in Bolivariana de Venezuela; and the Republic of Europe and Central Asia and in Latin America Yemen participated in the 2011 cycle but not and the Caribbean across all expenditure com- in 2017 and, thus, are included only in analy- ponents. They also fell in all but GFCF in Sub- ses for 2011. Conversely, Argentina and Guy- Saharan Africa (figure 1.20). PLIs increased over ana did not participate in 2011, but were part the period in North America and in East Asia of the 2017 cycle and are included in the and Pacific. latter’s analyses only. Uzbekistan participated Figure 1.14 (panel b) plots GDP PLI against in the 2017 cycle on an experimental basis, GDP per capita in PPP terms for each economy with results for actual individual consumption for 2011 and allows comparison with the same and individual consumption expenditure by Overview of main findings 15 Figure 1.20  Price level indexes for GDP and major expenditure components, by region and income group, 2011 and 2017 (world = 100) East Asia and Pacific Europe and Central Asia Latin America and the Caribbean Middle East and North Africa North America South Asia Sub-Saharan Africa High income Upper-middle income Lower-middle income Low income 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 0 50 100 150 200 GDP PLI AIC PLI Consumption expenditure GFCF PLI by government PLI 2011 2017 Source: ICP 2017. Note: AIC = actual individual consumption; GFCF = gross fixed capital formation; PLI = price level index. households only. Furthermore, Bonaire also are geographically distant, such as Organisation participated at the level of individual consump- for Economic Co-operation and Development tion expenditure by households. As a result, (OECD) economies. As the aggregate data pre- data for both of these economies are excluded sented for income groups and geographic from analyses. regions exclude the economies that did not In a number of figures in this chapter, the ICP participate in the ICP, these totals should not be participating economies are classified by the compared with data from non-ICP sources. World Bank’s fiscal year 2020 income groups as Appendix J of this report lists all of the econ- of July 1, 2019. However, three economies— omies by their ICP administrative region, by Anguilla, Bonaire, and Monserrat—are not World Bank fiscal year 2020 income group, and included in the classification because their pop- by geographic region. ulations were below the World Bank’s classifica- In a number of figures, results are presented tion threshold of 30,000. Anguilla and Montser- for the following GDP expenditure components: rat are excluded from these income group–based (a) housing, water, electricity, gas, and other figures, as is Bonaire. fuels; (b) health; (c) recreation and culture; In other figures, a geographic grouping of (d) education; and (e) miscellaneous goods and economies, based largely on the World Bank’s services. These include their respective expendi- regions is used. This approach differs from tures under individual consumption expendi- analyses in previous ICP reports, which pre- ture by households, individual consumption sented results by ICP administrative region. expenditure by nonprofit institutions serving This geographic grouping avoids the issues of households (NPISHs), and individual consump- having dual-participation economies appear in tion expenditure by government. Appendix C more than one region and having economies provides a list of all expenditure components appear in the same group as economies that under the ICP expenditure classification. 16    Purchasing Power Parities and the Size of World Economies CHAPTER 2 ICP 2017 results The 2017 results presented in this report are • Table 2.4. Consumption expenditure by based exclusively on the prices and national government accounts expenditures provided by the econo- • Table 2.5. Gross fixed capital formation mies participating in the 2017 cycle of the Inter- (GFCF) national Comparison Program (ICP). Purchasing • Table 2.6. Domestic absorption. power parities (PPPs) and real expenditures were compiled in accordance with the estab- In addition, supplementary table 2.7 provides lished ICP methods and procedures, as outlined a limited set of results for nonparticipating in chapter 5 of this report. In addition, users economies. The PPPs for these economies were should refer to the correct use and application of imputed following the approach described in PPPs and real expenditures, as described in chapter 5. chapter 3 of this report. The headings are defined as follows: In addition to the summary results presented • Gross domestic product. Actual individual con- here, more detailed data sets are available sumption at purchasers’ prices plus collective through curated online tables and databases, consumption expenditure by government at accessible through the ICP website1 and through purchasers’ prices plus gross capital formation the World Bank’s Databank2 and Data Catalog.3 at purchasers’ prices plus the f.o.b. (free on In addition, researchers may request access to board) value of exports of goods and services unpublished ICP data sets, as detailed in less the f.o.b. value of imports of goods and ap­pendix H. services. Code in ICP expenditure classification, appendix C: 1000000. • Actual individual consumption. The total value Tables of 2017 results of the individual consumption expenditures This report provides the main set of results for of households, nonprofit institutions serving the following headings: households (NPISHs), and government at purchasers’ prices. Code in ICP expenditure clas- • Table 2.1. Gross domestic product (GDP) sification, appendix C: sum of 1100000 + 1200000 • Table 2.2. Actual individual consumption + 1300000. (AIC) • Individual consumption expenditure by house- • Table 2.3. Individual consumption expendi- holds. The total value of actual and imputed ture by households final consumption expenditures incurred by 17 households and NPISHs on individual goods • Column (07). Expenditure per capita index and services. It also includes expenditures on based on market exchange rates with the individual goods and services sold at prices world equal to 100 that are not economically significant. Code in • Column (08). Expenditure per capita index ICP expenditure classification, appendix C: sum of based on PPPs with the United States equal to 1100000 + 1200000. 100 • Consumption expenditure by government. The • Column (09). Expenditure per capita index total value of actual and imputed final con- based on market exchange rates with the sumption expenditures incurred by govern- United States equal to 100 ment on individual goods and services and • Column (10). Share of PPP-based world total final consumption expenditure of govern- expenditures ment on collective services. Code in ICP expen- • Column (11). Share of market exchange rate– diture classification, appendix C: sum of 1300000 + based world total expenditures 1400000. • Column (12). Share of world population • Gross fixed capital formation (GFCF). The total value of acquisitions less disposals of fixed • Column (13). PPP with the US dollar5 equal to 1 assets by resident institutional units during • Column (14). Market exchange rate with the the accounting period plus additions to the USdollar equal to 1 value of nonproduced assets realized by the • Column (15). Nominal expenditures in local productive activity of resident institutional currency unit units. Code in ICP expenditure classification, • Column (16). Resident population. appendix C: 1501000. Column (01) shows the real expenditures of • Domestic absorption. Actual individual con- economies and regions in US dollars. The expen- sumption at purchasers’ prices plus collective ditures reflect only volume differences between consumption expenditure by government at economies and regions. They were obtained by purchasers’ prices plus gross capital formation dividing the nominal expenditures in column at purchasers’ prices. Code in ICP expenditure (15) by the PPPs in column (13). The expendi- classification, appendix C: sum of 1100000 + tures per capita in column (03), the expendi- 1200000 + 1300000 + 1400000 + 1500000. tures per capita indexes in columns (06) and The tables of main results cover the following (08), and the shares of world total expenditures indicators for each heading: in column (10) are all based on the real expen- ditures in column (01). • Column (00). Name of the economy and its Column (02) shows the nominal expendi- International Organization for Standardiza- tures of economies and regions in US dollars. tion (ISO) code The expenditures reflect both price differences • Column (01). Expenditure based on PPPs in US and volume differences between economies dollars4 and regions. They were derived by dividing • Column (02). Expenditure based on market the nominal expenditures in column (15) by exchange rates in US dollars the market exchange rates in column (14). The • Column (03). Expenditure per capita based on expenditures per capita in column (04), the PPPs in US dollars expenditures per capita indexes in columns (07) and (09), and the shares of world GDP in col- • Column (04). Expenditure per capita based on umn (11) are all based on the nominal expendi- market exchange rates in US dollars tures in column (02). • Column (05). Price level index with the world Column (05) shows price level indexes rela- equal to 100 tive to the world average. A value above 100 • Column (06). Expenditure per capita index indicates that the economy’s price level is higher based on PPPs with the world equal to 100 than the world average; a value below 100 18    Purchasing Power Parities and the Size of World Economies indicates that the economy’s price level for the Technical Advisory Group and approved by the analytical category is lower than the world aver- ICP Governing Board. As such, these results are age. They were derived by dividing the nominal not produced by participating economies as part expenditures in US dollars in column (02) by of their national official statistics. the real expenditures of economies and regions in US dollars in column (01) and by subse- quently normalizing the price level to the world Survey framework average. It is important to remember that market Metadata on the ICP 2017 survey framework in exchange rate–converted expenditures are not participating economies are summarized in table reliable measures of either the size of economies 2.8. The table provides information on the geo- or the mean per capita income and consump- graphic scope of the price surveys for individual tion of their populations. They are included in consumption expenditure by households as well the main tables and in the supplementary table as details on the types of outlets and number of for reference only. items covered. The results for participating economies are presented following the World Bank Group Notes geographic regions:6 1.  See icp.worldbank.org. • East Asia and Pacific: 19 economies 2.  See data.worldbank.org. • Europe and Central Asia: 46 economies 3.  See datacatalog.worldbank.org. 4. Real expenditures are not additive, meaning • Latin America and the Caribbean: 39 that the real expenditures at higher levels of economies aggregation are not equal to the sum of the • Middle East and North Africa: 17 economies real expenditures of their components. Addi- • North America: 3 economies tivity can be considered to be an important • South Asia: 7 economies feature of real expenditures. However, in • Sub-Saharan Africa: 45 economies practice it is not possible to maintain the additivity of the component aggregates • World: 176 economies. within real GDP without having real expen- In addition, supplementary table 2.7 provides ditures for GDP that are significantly biased results for 12 nonparticipating economies. between low- and high-income economies In all tables, results are presented by econ- (that is, the Gerschenkron effect). omy and by region and include regional totals 5. The United States serves as the base and the and averages, as well as world totals and aver- US dollar as numéraire. However, PPPs are ages. The results for the nonparticipating econo- base economy–invariant, so they can be mies are not included in world totals. rebased on another economy or on a region Results presented in these tables are pro- by dividing them by the PPP for the econ- duced by the ICP Global Office and regional omy or region selected as the new base. PPPs implementing agencies, based on data supplied also maintain other key characteristics, as by participating economies, and in accordance described in chapter 5. with the methodology recommended by the ICP 6. See appendix J for details. ICP 2017 results 19 Table 2.1  Gross domestic product (GDP): ICP 2017 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 1,233.9 1,386.2 50,153 56,344 168.5 302.2 509.2 83.6 93.9 1.0 1.7 0.3 1.466 1.305 1,808.6 24.60 Brunei Darussalam BRN 25.9 12.1 60,282 28,238 70.3 363.2 255.2 100.5 47.1 0.0 0.0 0.0 0.647 1.381 16.7 0.43 Cambodia KHM 62.9 22.2 3,968 1,399 52.9 23.9 12.6 6.6 2.3 0.1 0.0 0.2 1,428.354 4,050.580 89,830.5 15.85 China CHN 19,617.4 12,143.6 14,150 8,759 92.8 85.3 79.2 23.6 14.6 16.4 15.2 19.2 4.184 6.759 82,075.4 1,386.40 Fiji FJI 11.8 5.4 13,436 6,104 68.1 81.0 55.2 22.4 10.2 0.0 0.0 0.0 0.939 2.067 11.1 0.88 Hong Kong SAR, China HKG 443.0 341.7 59,927 46,225 115.7 361.1 417.7 99.9 77.1 0.4 0.4 0.1 6.011 7.793 2,662.8 7.39 Indonesia IDN 2,893.6 1,015.4 11,049 3,877 52.6 66.6 35.0 18.4 6.5 2.4 1.3 3.6 4,695.659 13,380.872 13,587,212.6 261.89 Japan JPN 5,173.0 4,860.0 40,827 38,356 140.9 246.0 346.6 68.1 63.9 4.3 6.1 1.8 105.379 112.166 545,121.9 126.71 Korea, Rep. KOR 2,105.9 1,623.9 41,001 31,617 115.6 247.1 285.7 68.4 52.7 1.8 2.0 0.7 871.696 1130.425 1,835,698.2 51.36 Lao PDR LAO 50.4 16.8 7,310 2,441 50.1 44.0 22.1 12.2 4.1 0.0 0.0 0.1 2,789.109 8,351.526 140,697.7 6.90 Malaysia MYS 817.9 314.7 25,540 9,828 57.7 153.9 88.8 42.6 16.4 0.7 0.4 0.4 1.655 4.300 1,353.4 32.02 Mongolia MNG 35.2 11.4 11,186 3,628 48.6 67.4 32.8 18.6 6.0 0.0 0.0 0.0 791.436 2,439.777 27,876.3 3.15 Myanmar MMR 234.5 63.2 4,411 1,189 40.4 26.6 10.7 7.4 2.0 0.2 0.1 0.7 366.713 1,360.359 85,980.8 53.15 New Zealand NZL 194.5 200.9 40,261 41,577 154.9 242.6 375.7 67.1 69.3 0.2 0.3 0.1 1.453 1.407 282.7 4.83 Philippines PHL 815.5 313.6 7,772 2,989 57.7 46.8 27.0 13.0 5.0 0.7 0.4 1.5 19.385 50.404 15,807.6 104.92 Singapore SGP 527.4 338.4 93,981 60,297 96.2 566.3 544.9 156.7 100.5 0.4 0.4 0.1 0.886 1.381 467.3 5.61 Taiwan, China TWN 1,112.6 574.9 47,223 24,401 77.5 284.6 220.5 78.7 40.7 0.9 0.7 0.3 15.730 30.442 17,501.2 23.56 Thailand THA 1,203.0 455.3 17,781 6,729 56.8 107.1 60.8 29.6 11.2 1.0 0.6 0.9 12.845 33.940 15,452.0 67.65 Vietnam VNM 676.9 223.8 7,183 2,375 49.6 43.3 21.5 12.0 4.0 0.6 0.3 1.3 7,395.338 2,2370.087 5,005,975.5 94.24 Total (19) EAB 37,235.1 23,923.4 16,392 10,532 96.4 98.8 95.2 27.3 17.6 31.1 30.0 31.5 n.a. n.a n.a. 2,271.55 Europe and Central Asia Albania ALB 37.6 13.1 13,094 4,546 52.1 78.9 41.1 21.8 7.6 0.0 0.0 0.0 41.231 118.748 1,551.3 2.87 Armenia ARM 35.7 11.5 11,974 3,869 48.5 72.2 35.0 20.0 6.4 0.0 0.0 0.0 155.971 482.720 5,564.5 2.98 Austria AUT 480.7 418.3 54,653 47,563 130.5 329.3 429.8 91.1 79.3 0.4 0.5 0.1 0.770 0.885 370.3 8.80 Azerbaijan AZE 139.2 40.9 14,296 4,198 44.0 86.1 37.9 23.8 7.0 0.1 0.1 0.1 0.505 1.721 70.3 9.73 Belarus BLR 173.6 54.7 18,280 5,763 47.3 110.2 52.1 30.5 9.6 0.1 0.1 0.1 0.609 1.932 105.7 9.50 Belgium BEL 577.5 504.3 50,771 44,330 130.9 305.9 400.6 84.6 73.9 0.5 0.6 0.2 0.773 0.885 446.4 11.38 Bosnia and Herzegovina BIH 46.4 18.1 13,843 5,407 58.6 83.4 48.9 23.1 9.0 0.0 0.0 0.0 0.676 1.731 31.4 3.35 Bulgaria BGR 151.8 59.1 21,447 8,351 58.4 129.2 75.5 35.8 13.9 0.1 0.1 0.1 0.674 1.731 102.3 7.08 Croatia HRV 110.1 55.5 26,666 13,430 75.5 160.7 121.4 44.5 22.4 0.1 0.1 0.1 3.327 6.607 366.4 4.13 Cyprus CYP 32.6 22.6 37,915 26,339 104.2 228.5 238.0 63.2 43.9 0.0 0.0 0.0 0.615 0.885 20.0 0.86 Czech Republic CZE 407.8 216.6 38,507 20,453 79.7 232.0 184.8 64.2 34.1 0.3 0.3 0.1 12.378 23.304 5,047.3 10.59 Denmark DNK 317.4 330.3 55,046 57,280 156.1 331.7 517.6 91.8 95.5 0.3 0.4 0.1 6.852 6.585 2,175.1 5.77 Estonia EST 44.6 26.9 33,867 20,416 90.4 204.1 184.5 56.5 34.0 0.0 0.0 0.0 0.534 0.885 23.8 1.32 Finland FIN 261.5 255.1 47,471 46,307 146.3 286.0 418.5 79.1 77.2 0.2 0.3 0.1 0.863 0.885 225.8 5.51 France FRA 2,994.5 2,592.7 44,651 38,661 129.8 269.1 349.4 74.4 64.5 2.5 3.3 0.9 0.766 0.885 2,295.1 67.06 20    Purchasing Power Parities and the Size of World Economies Table 2.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Georgia GEO 50.7 16.2 13,590 4,357 48.1 81.9 39.4 22.7 7.3 0.0 0.0 0.1 0.805 2.510 40.8 3.73 Germany DEU 4,381.8 3,665.9 53,012 44,350 125.5 319.4 400.8 88.4 73.9 3.7 4.6 1.1 0.741 0.885 3,245.0 82.66 Greece GRC 312.8 203.6 29,089 18,931 97.6 175.3 171.1 48.5 31.6 0.3 0.3 0.1 0.576 0.885 180.2 10.75 Hungary HUN 289.0 141.9 29,529 14,497 73.6 177.9 131.0 49.2 24.2 0.2 0.2 0.1 134.363 273.692 38,835.2 9.79 Iceland ISL 19.1 24.5 55,492 71,313 192.7 334.4 644.4 92.5 118.9 0.0 0.0 0.0 137.122 106.701 2,613.0 0.34 Ireland IRL 375.6 335.7 78,211 69,898 134.0 471.3 631.6 130.4 116.5 0.3 0.4 0.1 0.791 0.885 297.1 4.80 Italy ITA 2,529.5 1,961.8 41,785 32,407 116.3 251.8 292.9 69.7 54.0 2.1 2.5 0.8 0.687 0.885 1,736.6 60.54 Kazakhstan KAZ 448.5 166.8 24,863 9,248 55.8 149.8 83.6 41.4 15.4 0.4 0.2 0.3 121.253 326.000 54,378.9 18.04 Kyrgyz Republic KGZ 31.3 7.7 5,263 1,298 37.0 31.7 11.7 8.8 2.2 0.0 0.0 0.1 16.959 68.769 530.5 5.94 Latvia LVA 55.3 30.3 28,505 15,596 82.1 171.8 140.9 47.5 26.0 0.0 0.0 0.0 0.484 0.885 26.8 1.94 Lithuania LTU 95.7 47.8 33,821 16,883 74.9 203.8 152.6 56.4 28.1 0.1 0.1 0.0 0.442 0.885 42.3 2.83 Luxembourg LUX 67.3 64.2 112,701 107,513 143.1 679.1 971.6 187.9 179.2 0.1 0.1 0.0 0.844 0.885 56.8 0.60 Moldova MDA 32.1 9.7 9,045 2,726 45.2 54.5 24.6 15.1 4.5 0.0 0.0 0.0 5.572 18.490 178.9 3.55 Montenegro MNE 12.3 4.9 19,704 7,804 59.4 118.7 70.5 32.8 13.0 0.0 0.0 0.0 0.351 0.885 4.3 0.62 Netherlands NLD 948.2 833.9 55,349 48,677 131.9 333.5 439.9 92.3 81.1 0.8 1.0 0.2 0.778 0.885 738.1 17.13 North Macedonia MKD 32.5 11.3 15,646 5,467 52.4 94.3 49.4 26.1 9.1 0.0 0.0 0.0 19.043 54.505 618.1 2.07 Norway NOR 332.1 399.1 62,940 75,638 180.2 379.3 683.5 104.9 126.1 0.3 0.5 0.1 9.922 8.256 3,295.4 5.28 Poland POL 1,145.0 527.9 29,802 13,740 69.1 179.6 124.2 49.7 22.9 1.0 0.7 0.5 1.737 3.768 1,989.4 38.42 Portugal PRT 340.8 221.4 33,086 21,491 97.4 199.4 194.2 55.2 35.8 0.3 0.3 0.1 0.575 0.885 195.9 10.30 Romania ROU 534.7 212.1 27,293 10,827 59.5 164.5 97.8 45.5 18.1 0.4 0.3 0.3 1.604 4.044 857.9 19.59 Russian Federation RUS 3,829.5 1,578.6 26,079 10,750 61.8 157.1 97.1 43.5 17.9 3.2 2.0 2.0 24.050 58.343 92,101.3 146.84 Serbia SRB 116.5 44.3 16,599 6,305 57.0 100.0 57.0 27.7 10.5 0.1 0.1 0.1 40.795 107.406 4,754.4 7.02 Slovak Republic SVK 168.1 95.5 30,911 17,556 85.2 186.3 158.7 51.5 29.3 0.1 0.1 0.1 0.503 0.885 84.5 5.44 Slovenia SVN 75.7 48.6 36,661 23,508 96.2 220.9 212.4 61.1 39.2 0.1 0.1 0.0 0.568 0.885 43.0 2.07 Spain ESP 1,844.0 1,312.6 39,627 28,207 106.8 238.8 254.9 66.1 47.0 1.5 1.6 0.6 0.630 0.885 1,161.9 46.53 Sweden SWE 530.0 541.8 52,693 53,870 153.3 317.5 486.8 87.8 89.8 0.4 0.7 0.1 8.719 8.529 4,621.0 10.06 Switzerland CHE 567.4 680.4 67,139 80,501 179.8 404.6 727.5 111.9 134.2 0.5 0.9 0.1 1.180 0.984 669.5 8.45 Tajikistan TJK 27.4 7.2 3,105 810 39.1 18.7 7.3 5.2 1.4 0.0 0.0 0.1 2.231 8.550 61.2 8.84 Turkey TUR 2,265.5 852.7 28,209 10,617 56.4 170.0 95.9 47.0 17.7 1.9 1.1 1.1 1.373 3.648 3,110.7 80.31 Ukraine UKR 504.4 112.2 11,871 2,641 33.4 71.5 23.9 19.8 4.4 0.4 0.1 0.6 5.916 26.597 2,983.9 42.49 United Kingdom GBR 3,037.0 2,669.6 45,988 40,424 131.8 277.1 365.3 76.7 67.4 2.5 3.3 0.9 0.682 0.776 2,071.7 66.04 Total (46) ECB 30,810.7 21,449.6 35,255 24,544 104.4 212.4 221.8 58.8 40.9 25.8 26.9 12.1 n.a. n.a n.a. 873.93 Latin America and the Caribbean Anguilla AIA 0.3 0.3 22,877 19,441 127.4 137.9 175.7 38.1 32.4 0.0 0.0 0.0 2.295 2.700 0.8 0.01 Antigua and Barbuda ATG 2.0 1.5 20,494 15,891 116.3 123.5 143.6 34.2 26.5 0.0 0.0 0.0 2.094 2.700 4.1 0.10 Argentina ARG 1,037.8 642.7 23,621 14,627 92.9 142.3 132.2 39.4 24.4 0.9 0.8 0.6 10.257 16.563 10,644.8 43.94 Aruba ABW 4.1 3.1 38,440 29,006 113.2 231.6 262.1 64.1 48.4 0.0 0.0 0.0 1.351 1.790 5.5 0.11 ICP 2017 results 21 Table 2.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 13.5 12.2 35,309 31,828 135.2 212.8 287.6 58.9 53.1 0.0 0.0 0.0 0.901 1.000 12.2 0.38 Barbados BRB 4.3 4.7 14,941 16,457 165.2 90.0 148.7 24.9 27.4 0.0 0.0 0.0 2.203 2.000 9.4 0.29 Belize BLZ 2.7 1.9 7,210 4,957 103.1 43.4 44.8 12.0 8.3 0.0 0.0 0.0 1.375 2.000 3.7 0.38 Bolivia BOL 94.3 37.2 8,424 3,327 59.2 50.8 30.1 14.0 5.5 0.1 0.0 0.2 2.749 6.960 259.2 11.19 Bonaired BON … … … … … … … … … … … … … 1.000 … 0.03 Brazil BRA 3,017.7 2,062.8 14,520 9,925 102.5 87.5 89.7 24.2 16.5 2.5 2.6 2.9 2.182 3.191 6,583.3 207.83 Cayman Islands CYM 4.4 5.1 69,421 81,122 175.2 418.3 733.1 115.7 135.2 0.0 0.0 0.0 0.974 0.833 4.3 0.06 Chile CHL 438.2 277.7 23,657 14,995 95.1 142.6 135.5 39.4 25.0 0.4 0.3 0.3 411.264 648.834 180,211.3 18.52 Colombia COL 699.9 311.8 14,199 6,325 66.8 85.6 57.2 23.7 10.5 0.6 0.4 0.7 1,314.787 2,951.327 920,194.0 49.29 Costa Rica CRI 98.0 60.6 19,823 12,254 92.7 119.4 110.7 33.0 20.4 0.1 0.1 0.1 350.817 567.513 34,386.7 4.94 Curaçao CUW 4.1 3.1 25,183 19,234 114.5 151.7 173.8 42.0 32.1 0.0 0.0 0.0 1.367 1.790 5.6 0.16 Dominica DMA 0.8 0.5 11,304 7,275 96.5 68.1 65.7 18.8 12.1 0.0 0.0 0.0 1.738 2.700 1.4 0.07 Dominican Republic DOM 175.9 80.0 16,735 7,609 68.2 100.8 68.8 27.9 12.7 0.1 0.1 0.1 21.613 47.537 3,802.7 10.51 Ecuador ECU 195.0 104.3 11,618 6,214 80.2 70.0 56.1 19.4 10.4 0.2 0.1 0.2 0.535 1.000 104.3 16.79 El Salvador SLV 53.9 24.9 8,437 3,902 69.4 50.8 35.3 14.1 6.5 0.0 0.0 0.1 0.463 1.000 24.9 6.39 Grenada GRD 1.8 1.1 16,235 10,164 93.9 97.8 91.8 27.1 16.9 0.0 0.0 0.0 1.690 2.700 3.0 0.11 Guyana GUY 7.0 3.5 8,989 4,463 74.5 54.2 40.3 15.0 7.4 0.0 0.0 0.0 105.353 212.190 734.2 0.78 Haiti HTI 20.6 9.2 1,877 840 67.1 11.3 7.6 3.1 1.4 0.0 0.0 0.2 28.498 63.687 587.5 10.98 Honduras HND 52.4 23.0 5,562 2,443 65.9 33.5 22.1 9.3 4.1 0.0 0.0 0.1 10.362 23.588 543.4 9.43 Jamaica JAM 28.1 14.8 9,619 5,080 79.2 58.0 45.9 16.0 8.5 0.0 0.0 0.0 67.582 127.965 1,898.8 2.92 Mexico MEX 2,470.1 1,157.7 20,023 9,385 70.3 120.7 84.8 33.4 15.6 2.1 1.5 1.7 8.871 18.927 21,911.9 123.36 Montserrat MSR 0.1 0.1 18,142 12,030 99.4 109.3 108.7 30.2 20.1 0.0 0.0 0.0 1.790 2.700 0.2 0.00 Nicaragua NIC 38.5 13.8 6,029 2,168 53.9 36.3 19.6 10.1 3.6 0.0 0.0 0.1 10.807 30.051 416.0 6.38 Panama PAN 125.2 62.3 30,486 15,166 74.6 183.7 137.1 50.8 25.3 0.1 0.1 0.1 0.497 1.000 62.3 4.11 Paraguay PRY 86.5 39.4 12,594 5,738 68.3 75.9 51.9 21.0 9.6 0.1 0.0 0.1 2,534.377 5,562.276 219,188.4 6.87 Peru PER 393.3 211.0 12,507 6,712 80.5 75.4 60.7 20.8 11.2 0.3 0.3 0.4 1.749 3.260 688.0 31.44 Sint Maarten SXM 1.3 1.0 31,579 24,461 116.2 190.3 221.0 52.6 40.8 0.0 0.0 0.0 1.387 1.790 1.8 0.04 St. Kitts and Nevis KNA 1.2 0.9 23,966 18,105 113.3 144.4 163.6 40.0 30.2 0.0 0.0 0.0 2.040 2.700 2.5 0.05 St. Lucia LCA 2.3 1.7 12,735 9,413 110.9 76.7 85.1 21.2 15.7 0.0 0.0 0.0 1.996 2.700 4.6 0.18 St. Vincent and the VCT 1.4 0.8 13,075 7,702 88.3 78.8 69.6 21.8 12.8 0.0 0.0 0.0 1.590 2.700 2.3 0.11 Grenadines Suriname SUR 9.3 3.2 16,341 5,580 51.2 98.5 50.4 27.2 9.3 0.0 0.0 0.0 2.578 7.550 24.0 0.57 Trinidad and Tobago TTO 37.1 22.8 26,806 16,458 92.1 161.5 148.7 44.7 27.4 0.0 0.0 0.0 4.162 6.780 154.4 1.38 Turks and Caicos Islands TCA 1.0 1.0 25,982 26,447 152.7 156.6 239.0 43.3 44.1 0.0 0.0 0.0 1.018 1.000 1.0 0.04 Uruguay URY 73.3 59.5 21,325 17,322 121.8 128.5 156.5 35.6 28.9 0.1 0.1 0.0 23.294 28.676 1,707.1 3.44 Virgin Islands, British VGB 1.2 1.3 40,834 43,642 160.3 246.1 394.4 68.1 72.8 0.0 0.0 0.0 1.069 1.000 1.3 0.03 Total (39) LCB 9,198.6 5,262.8 16,048 9,181 85.8 96.7 83.0 26.8 15.3 7.7 6.6 8.0 n.a. n.a n.a. 573.20 22    Purchasing Power Parities and the Size of World Economies Table 2.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 478.5 167.5 11,561 4,048 52.5 69.7 36.6 19.3 6.7 0.4 0.2 0.6 38.856 110.973 18,591.7 41.39 Bahrain BHR 70.9 35.3 47,256 23,517 74.6 284.8 212.5 78.8 39.2 0.1 0.0 0.0 0.187 0.376 13.3 1.50 Djibouti DJI 4.9 2.9 5,197 3,100 89.5 31.3 28.0 8.7 5.2 0.0 0.0 0.0 106.023 177.720 520.2 0.94 Egypt, Arab Rep. EGY 1,263.4 231.3 13,327 2,439 27.4 80.3 22.0 22.2 4.1 1.1 0.3 1.3 3.267 17.847 4,127.1 94.80 Iran, Islamic Rep. IRN 1,298.1 510.3 16,012 6,294 59.0 96.5 56.9 26.7 10.5 1.1 0.6 1.1 13,061.295 33,226.298 16,954,811.5 81.07 Iraq IRQ 368.3 164.4 9,917 4,427 67.0 59.8 40.0 16.5 7.4 0.3 0.2 0.5 560.761 1,256.000 206,530.1 37.14 Israel ISR 339.5 353.3 38,983 40,558 156.0 234.9 366.5 65.0 67.6 0.3 0.4 0.1 3.745 3.600 1,271.6 8.71 Jordan JOR 96.6 41.0 9,610 4,077 63.6 57.9 36.8 16.0 6.8 0.1 0.1 0.1 0.300 0.708 29.0 10.05 Kuwait KWT 199.8 116.9 48,928 28,628 87.7 294.8 258.7 81.6 47.7 0.2 0.1 0.1 0.177 0.303 35.5 4.08 Malta MLT 19.6 12.8 41,741 27,254 97.9 251.5 246.3 69.6 45.4 0.0 0.0 0.0 0.578 0.885 11.3 0.47 Morocco MAR 264.3 109.7 7,583 3,148 62.3 45.7 28.5 12.6 5.2 0.2 0.1 0.5 4.023 9.691 1,063.4 34.85 Oman OMN 135.7 70.6 29,758 15,482 78.0 179.3 139.9 49.6 25.8 0.1 0.1 0.1 0.200 0.385 27.1 4.56 Qatar QAT 259.0 166.5 95,063 61,099 96.4 572.8 552.1 158.5 101.9 0.2 0.2 0.0 2.346 3.650 607.6 2.72 Saudi Arabia SAU 1,565.9 688.6 48,015 21,114 65.9 289.3 190.8 80.0 35.2 1.3 0.9 0.5 1.649 3.750 2,582.2 32.61 Tunisia TUN 121.6 39.9 10,638 3,492 49.2 64.1 31.6 17.7 5.8 0.1 0.1 0.2 0.794 2.419 96.6 11.43 United Arab Emirates ARE 624.3 377.7 67,100 40,594 90.7 404.3 366.8 111.9 67.7 0.5 0.5 0.1 2.222 3.673 1,387.1 9.30 West Bank and Gaza PSE 25.6 14.5 5,756 3,255 84.8 34.7 29.4 9.6 5.4 0.0 0.0 0.1 2.036 3.600 52.2 4.45 Total (17) MEB 7,136.1 3,103.1 18,774 8,164 65.2 113.1 73.8 31.3 13.6 6.0 3.9 5.3 n.a. n.a n.a. 380.10 North America Bermuda BMU 4.6 6.2 72,356 98,868 204.9 436.0 893.4 120.6 164.8 0.0 0.0 0.0 1.366 1.000 6.2 0.06 Canada CAN 1,778.0 1,650.6 48,658 45,171 139.2 293.2 408.2 81.1 75.3 1.5 2.1 0.5 1.205 1.298 2,142.0 36.54 United States USA 19,519.4 19,519.4 59,984 59,984 150.0 361.4 542.1 100.0 100.0 16.3 24.5 4.5 1.000 1.000 19,519.4 325.41 Total (3) NAB 21,302.0 21,176.2 58,843 58,496 149.1 354.6 528.6 98.1 97.5 17.8 26.6 5.0 n.a. n.a n.a. 362.01 South Asia Bangladesh BGD 710.6 262.7 4,392 1,624 55.4 26.5 14.7 7.3 2.7 0.6 0.3 2.2 29.738 80.438 21,131.5 161.80 Bhutan BTN 8.6 2.5 11,787 3,477 44.2 71.0 31.4 19.6 5.8 0.0 0.0 0.0 19.208 65.122 164.6 0.73 India IND 8,050.5 2,552.5 6,149 1,950 47.5 37.1 17.6 10.3 3.3 6.7 3.2 18.2 20.648 65.122 166,225.6 1,309.20 Maldives MDV 9.2 4.9 18,662 9,898 79.5 112.5 89.4 31.1 16.5 0.0 0.0 0.0 8.161 15.387 74.9 0.49 Nepal NPL 83.6 25.0 2,900 867 44.8 17.5 7.8 4.8 1.4 0.1 0.0 0.4 31.235 104.512 2,611.2 28.83 Pakistan PAK 990.5 315.5 4,975 1,585 47.8 30.0 14.3 8.3 2.6 0.8 0.4 2.8 33.589 105.455 33,270.4 199.11 Sri Lanka LKA 269.6 87.4 12,574 4,074 48.6 75.8 36.8 21.0 6.8 0.2 0.1 0.3 49.390 152.446 13,317.3 21.44 Total (7) SAB 10,122.6 3,250.5 5,880 1,888 48.2 35.4 17.1 9.8 3.1 8.5 4.1 23.9 n.a. n.a n.a. 1,721.60 Sub-Saharan Africa Angola AGO 219.1 122.7 7,348 4,117 84.0 44.3 37.2 12.3 6.9 0.2 0.2 0.4 92.952 165.916 20,365.4 29.82 Benin BEN 25.1 9.4 2,250 838 55.9 13.6 7.6 3.8 1.4 0.0 0.0 0.2 216.774 582.075 5,450.9 11.18 Botswana BWA 38.1 17.4 17,276 7,903 68.6 104.1 71.4 28.8 13.2 0.0 0.0 0.0 4.734 10.347 180.3 2.21 ICP 2017 results 23 Table 2.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 34.8 12.5 1,813 650 53.8 10.9 5.9 3.0 1.1 0.0 0.0 0.3 208.757 582.075 7,263.3 19.19 Burundi BDI 8.5 3.2 784 297 56.8 4.7 2.7 1.3 0.5 0.0 0.0 0.2 654.896 1,729.055 5,562.4 10.83 Cabo Verde CPV 3.6 1.8 6,617 3,280 74.3 39.9 29.6 11.0 5.5 0.0 0.0 0.0 48.477 97.799 172.4 0.54 Cameroon CMR 87.1 34.8 3,546 1,418 60.0 21.4 12.8 5.9 2.4 0.1 0.0 0.3 232.801 582.075 20,277.0 24.57 Central African Republic CAF 4.3 2.1 937 462 73.9 5.6 4.2 1.6 0.8 0.0 0.0 0.1 286.829 582.075 1,235.2 4.60 Chad TCD 24.4 10.2 1,622 679 62.8 9.8 6.1 2.7 1.1 0.0 0.0 0.2 243.655 582.075 5,936.3 15.02 Comoros COM 2.5 1.1 3,101 1,350 65.3 18.7 12.2 5.2 2.3 0.0 0.0 0.0 190.126 436.571 479.8 0.81 Congo, Dem. Rep. COD 112.2 49.4 1,378 607 66.1 8.3 5.5 2.3 1.0 0.1 0.1 1.1 645.391 1,464.418 72,390.1 81.40 Congo, Rep. COG 26.3 13.4 5,145 2,631 76.7 31.0 23.8 8.6 4.4 0.0 0.0 0.1 297.674 582.075 7,827.5 5.11 Côte d’Ivoire CIV 87.3 38.1 3,572 1,557 65.4 21.5 14.1 6.0 2.6 0.1 0.0 0.3 253.746 582.075 22,150.8 24.44 Equatorial Guinea GNQ 28.7 12.3 22,771 9,738 64.1 137.2 88.0 38.0 16.2 0.0 0.0 0.0 248.934 582.075 7,153.6 1.26 Eswatini SWZ 9.8 4.6 8,717 4,057 69.8 52.5 36.7 14.5 6.8 0.0 0.0 0.0 6.206 13.334 60.8 1.12 Ethiopia ETH 172.0 61.4 1,617 577 53.5 9.7 5.2 2.7 1.0 0.1 0.1 1.5 8.521 23.866 1,466.0 106.40 Gabon GAB 26.1 12.5 12,631 6,071 72.1 76.1 54.9 21.1 10.1 0.0 0.0 0.0 279.766 582.075 7,296.5 2.06 Gambia, The GMB 4.4 1.4 1,970 646 49.2 11.9 5.8 3.3 1.1 0.0 0.0 0.0 15.286 46.608 66.7 2.21 Ghana GHA 145.5 59.0 4,997 2,026 60.8 30.1 18.3 8.3 3.4 0.1 0.1 0.4 1.764 4.351 256.7 29.12 Guinea GIN 34.4 12.1 2,847 1,003 52.9 17.2 9.1 4.7 1.7 0.0 0.0 0.2 3,216.035 9,125.743 110,474.2 12.07 Guinea-Bissau GNB 3.5 1.3 1,925 737 57.4 11.6 6.7 3.2 1.2 0.0 0.0 0.0 222.749 582.075 784.0 1.83 Kenya KEN 204.0 79.3 4,062 1,578 58.3 24.5 14.3 6.8 2.6 0.2 0.1 0.7 40.185 103.411 8,196.7 50.22 Lesotho LSO 6.3 2.6 2,996 1,237 61.9 18.1 11.2 5.0 2.1 0.0 0.0 0.0 5.506 13.334 34.5 2.09 Liberia LBR 6.0 2.8 1,274 588 69.1 7.7 5.3 2.1 1.0 0.0 0.0 0.1 51.957 112.707 311.4 4.70 Madagascar MDG 39.9 13.0 1,561 508 48.8 9.4 4.6 2.6 0.8 0.0 0.0 0.4 1,013.435 3,116.110 40,445.3 25.57 Malawi MWI 18.5 6.3 1,045 359 51.6 6.3 3.2 1.7 0.6 0.0 0.0 0.2 251.074 730.273 4,635.6 17.67 Mali MLI 41.6 15.3 2,249 829 55.3 13.6 7.5 3.7 1.4 0.0 0.0 0.3 214.509 582.075 8,931.3 18.51 Mauritania MRT 15.8 4.9 3,695 1,150 46.7 22.3 10.4 6.2 1.9 0.0 0.0 0.1 111.258 357.493 1,760.7 4.28 Mauritius MUS 31.7 15.5 25,051 12,265 73.4 151.0 110.8 41.8 20.4 0.0 0.0 0.0 16.882 34.481 534.8 1.26 Mozambique MOZ 35.2 12.7 1,229 442 53.9 7.4 4.0 2.0 0.7 0.0 0.0 0.4 22.856 63.584 804.5 28.65 Namibia NAM 25.5 13.4 10,614 5,597 79.1 64.0 50.6 17.7 9.3 0.0 0.0 0.0 7.021 13.313 179.0 2.40 Niger NER 18.3 8.1 847 376 66.6 5.1 3.4 1.4 0.6 0.0 0.0 0.3 258.460 582.075 4,727.1 21.60 Nigeria NGA 884.6 335.5 4,634 1,758 56.9 27.9 15.9 7.7 2.9 0.7 0.4 2.6 115.978 305.790 102,593.5 190.87 Rwanda RWA 21.6 8.4 1,804 705 58.6 10.9 6.4 3.0 1.2 0.0 0.0 0.2 325.126 831.531 7,025.7 11.98 São Tomé and Príncipe STP 0.7 0.3 3,255 1,505 69.4 19.6 13.6 5.4 2.5 0.0 0.0 0.0 10.055 21.741 6.8 0.21 Senegal SEN 49.3 20.9 3,195 1,355 63.6 19.3 12.2 5.3 2.3 0.0 0.0 0.2 246.787 582.075 12,158.0 15.42 Seychelles SYC 2.7 1.6 27,794 16,228 87.6 167.5 146.7 46.3 27.1 0.0 0.0 0.0 7.969 13.648 21.4 0.10 Sierra Leone SLE 12.3 3.7 1,642 499 45.6 9.9 4.5 2.7 0.8 0.0 0.0 0.1 2,244.995 7,384.432 27,610.8 7.49 South Africa ZAF 733.7 353.6 12,870 6,203 72.3 77.5 56.1 21.5 10.3 0.6 0.4 0.8 6.427 13.334 4,715.2 57.01 Sudan SDN 176.6 40.5 4,331 994 34.4 26.1 9.0 7.2 1.7 0.1 0.1 0.6 4.619 20.130 815.9 40.78 24    Purchasing Power Parities and the Size of World Economies Table 2.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 125.0 49.6 2,287 908 59.6 13.8 8.2 3.8 1.5 0.1 0.1 0.8 885.083 2,228.858 110,651.1 54.66 Togo TGO 11.2 4.6 1,457 600 61.8 8.8 5.4 2.4 1.0 0.0 0.0 0.1 239.722 582.075 2,689.4 7.70 Uganda UGA 91.5 32.2 2,223 782 52.8 13.4 7.1 3.7 1.3 0.1 0.0 0.6 1,270.608 3,611.224 116,251.5 41.17 Zambia ZMB 56.5 24.9 3,354 1,477 66.0 20.2 13.3 5.6 2.5 0.0 0.0 0.2 4.193 9.520 237.0 16.85 Zimbabwe ZWE 36.4 18.6 2,560 1,309 76.7 15.4 11.8 4.3 2.2 0.0 0.0 0.2 0.511 1.000 18.6 14.24 Total (45) SSB 3,742.5 1,549.4 3,665 1,517 62.1 22.1 13.7 6.1 2.5 3.1 1.9 14.2 n.a. n.a n.a. 1,021.22 World (176) WLD 119,547.5 79,715.0 16,596 11,066 100.0 100.0 100.0 27.7 18.4 100.0 100.0 100.0 n.a. n.a. n.a. 7,203.60 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either the Latin America and the Caribbean or d.  the world totals. ICP 2017 results 25 Table 2.2  Actual individual consumption (AIC): ICP 2017 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 838.7 944.5 34,091 38,393 168.6 314.0 529.5 76.4 86.0 1.1 1.8 0.3 1.469 1.305 1,232.4 24.60 Brunei Darussalam BRN 6.9 3.2 16,118 7,560 70.2 148.4 104.3 36.1 16.9 0.0 0.0 0.0 0.648 1.381 4.5 0.43 Cambodia KHM 55.7 18.9 3,512 1,190 50.8 32.3 16.4 7.9 2.7 0.1 0.0 0.2 1,372.850 4,050.580 76,416.3 15.85 China CHN 9,574.3 5,731.9 6,906 4,134 89.6 63.6 57.0 15.5 9.3 12.2 11.0 19.2 4.046 6.759 38,740.6 1,386.40 Fiji FJI 8.7 3.9 9,967 4,451 66.9 91.8 61.4 22.3 10.0 0.0 0.0 0.0 0.923 2.067 8.1 0.88 Hong Kong SAR, China HKG 313.2 242.2 42,371 32,760 115.8 390.2 451.8 95.0 73.4 0.4 0.5 0.1 6.026 7.793 1,887.2 7.39 Indonesia IDN 1,755.5 617.3 6,703 2,357 52.7 61.7 32.5 15.0 5.3 2.2 1.2 3.6 4,705.548 13,380.872 8,260,567.4 261.89 Japan JPN 3,476.7 3,282.1 27,439 25,903 141.4 252.7 357.3 61.5 58.1 4.4 6.3 1.8 105.886 112.166 368,137.8 126.71 Korea, Rep. KOR 1,137.2 908.1 22,140 17,680 119.6 203.9 243.8 49.6 39.6 1.5 1.7 0.7 902.695 1,130.425 1,026,524.0 51.36 Lao PDR LAO 28.7 9.6 4,158 1,387 49.9 38.3 19.1 9.3 3.1 0.0 0.0 0.1 2,785.475 8,351.526 79,927.0 6.90 Malaysia MYS 509.4 193.2 15,908 6,032 56.8 146.5 83.2 35.7 13.5 0.7 0.4 0.4 1.631 4.300 830.7 32.02 Mongolia MNG 21.7 6.7 6,884 2,138 46.5 63.4 29.5 15.4 4.8 0.0 0.0 0.0 757.817 2,439.777 16,427.7 3.15 Myanmar MMR 143.5 37.6 2,700 708 39.3 24.9 9.8 6.1 1.6 0.2 0.1 0.7 356.688 1,360.359 51,180.5 53.15 New Zealand NZL 134.6 137.0 27,860 28,353 152.4 256.6 391.0 62.4 63.5 0.2 0.3 0.1 1.432 1.407 192.8 4.83 Philippines PHL 677.6 247.5 6,458 2,359 54.7 59.5 32.5 14.5 5.3 0.9 0.5 1.5 18.409 50.404 12,474.5 104.92 Singapore SGP 179.4 133.8 31,966 23,836 111.7 294.4 328.7 71.6 53.4 0.2 0.3 0.1 1.030 1.381 184.7 5.61 Taiwan, China TWN 680.0 347.4 28,863 14,746 76.5 265.8 203.4 64.7 33.0 0.9 0.7 0.3 15.553 30.442 10,575.9 23.56 Thailand THA 697.3 253.7 10,307 3,750 54.5 94.9 51.7 23.1 8.4 0.9 0.5 0.9 12.349 33.940 8,611.0 67.65 Vietnam VNM 452.8 143.2 4,805 1,520 47.4 44.3 21.0 10.8 3.4 0.6 0.3 1.3 7,075.976 22,370.087 3,204,308.7 94.24 Total (19) EAB 20,692.0 13,261.8 9,109 5,838 96.0 83.9 80.5 20.4 13.1 26.5 25.4 31.5 n.a. n.a n.a. 2,271.55 Europe and Central Asia Albania ALB 31.2 11.1 10,872 3,865 53.2 100.1 53.3 24.4 8.7 0.0 0.0 0.0 42.215 118.748 1,318.8 2.87 Armenia ARM 32.5 9.8 10,893 3,276 45.0 100.3 45.2 24.4 7.3 0.0 0.0 0.0 145.175 482.720 4,711.6 2.98 Austria AUT 293.9 269.9 33,412 30,693 137.6 307.7 423.3 74.9 68.8 0.4 0.5 0.1 0.813 0.885 239.0 8.80 Azerbaijan AZE 103.7 25.4 10,655 2,612 36.7 98.1 36.0 23.9 5.9 0.1 0.0 0.1 0.422 1.721 43.8 9.73 Belarus BLR 130.1 35.3 13,697 3,714 40.6 126.2 51.2 30.7 8.3 0.2 0.1 0.1 0.524 1.932 68.1 9.50 Belgium BEL 364.8 335.3 32,066 29,475 137.6 295.3 406.5 71.9 66.1 0.5 0.6 0.2 0.814 0.885 296.8 11.38 Bosnia and Herzegovina BIH 40.3 16.1 12,021 4,792 59.7 110.7 66.1 26.9 10.7 0.1 0.0 0.0 0.690 1.731 27.8 3.35 Bulgaria BGR 108.5 40.0 15,336 5,656 55.2 141.2 78.0 34.4 12.7 0.1 0.1 0.1 0.639 1.731 69.3 7.08 Croatia HRV 73.2 37.7 17,736 9,137 77.1 163.4 126.0 39.7 20.5 0.1 0.1 0.1 3.404 6.607 249.3 4.13 Cyprus CYP 22.7 16.6 26,378 19,280 109.5 242.9 265.9 59.1 43.2 0.0 0.0 0.0 0.647 0.885 14.7 0.86 Czech Republic CZE 244.1 124.8 23,054 11,787 76.6 212.3 162.6 51.7 26.4 0.3 0.2 0.1 11.915 23.304 2,908.8 10.59 Denmark DNK 186.3 211.6 32,306 36,688 170.1 297.5 506.0 72.4 82.2 0.2 0.4 0.1 7.478 6.585 1,393.2 5.77 Estonia EST 27.0 16.5 20,554 12,506 91.1 189.3 172.5 46.1 28.0 0.0 0.0 0.0 0.539 0.885 14.6 1.32 Finland FIN 173.7 174.2 31,526 31,632 150.2 290.4 436.3 70.7 70.9 0.2 0.3 0.1 0.888 0.885 154.2 5.51 France FRA 2,061.5 1,802.3 30,740 26,874 130.9 283.1 370.6 68.9 60.2 2.6 3.5 0.9 0.774 0.885 1,595.4 67.06 26    Purchasing Power Parities and the Size of World Economies Table 2.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Georgia GEO 37.7 12.2 10,123 3,267 48.3 93.2 45.1 22.7 7.3 0.0 0.0 0.1 0.810 2.510 30.6 3.73 Germany DEU 2,842.2 2,385.4 34,385 28,859 125.7 316.7 398.0 77.1 64.7 3.6 4.6 1.1 0.743 0.885 2,111.5 82.66 Greece GRC 233.2 157.1 21,688 14,608 100.9 199.7 201.5 48.6 32.7 0.3 0.3 0.1 0.596 0.885 139.1 10.75 Hungary HUN 174.7 84.8 17,851 8,662 72.7 164.4 119.5 40.0 19.4 0.2 0.2 0.1 132.801 273.692 23,203.5 9.79 Iceland ISL 11.3 16.1 32,888 47,021 214.1 302.9 648.5 73.7 105.4 0.0 0.0 0.0 152.553 106.701 1,722.9 0.34 Ireland IRL 128.4 135.3 26,744 28,169 157.7 246.3 388.5 59.9 63.1 0.2 0.3 0.1 0.932 0.885 119.7 4.80 Italy ITA 1,687.2 1,395.8 27,870 23,057 123.9 256.7 318.0 62.5 51.7 2.2 2.7 0.8 0.732 0.885 1,235.6 60.54 Kazakhstan KAZ 295.3 96.4 16,373 5,346 48.9 150.8 73.7 36.7 12.0 0.4 0.2 0.3 106.447 326.000 31,436.8 18.04 Kyrgyz Republic KGZ 29.9 7.0 5,023 1,179 35.1 46.3 16.3 11.3 2.6 0.0 0.0 0.1 16.140 68.769 481.9 5.94 Latvia LVA 37.1 20.7 19,108 10,650 83.5 176.0 146.9 42.8 23.9 0.0 0.0 0.0 0.493 0.885 18.3 1.94 Lithuania LTU 70.0 34.2 24,753 12,084 73.1 228.0 166.7 55.5 27.1 0.1 0.1 0.0 0.432 0.885 30.3 2.83 Luxembourg LUX 22.6 25.5 37,852 42,732 169.1 348.6 589.4 84.8 95.8 0.0 0.0 0.0 0.999 0.885 22.6 0.60 Moldova MDA 32.6 9.2 9,177 2,601 42.4 84.5 35.9 20.6 5.8 0.0 0.0 0.0 5.240 18.490 170.7 3.55 Montenegro MNE 9.9 4.0 15,871 6,501 61.3 146.2 89.7 35.6 14.6 0.0 0.0 0.0 0.363 0.885 3.6 0.62 Netherlands NLD 544.3 506.4 31,775 29,559 139.3 292.7 407.7 71.2 66.2 0.7 1.0 0.2 0.823 0.885 448.2 17.13 North Macedonia MKD 24.0 8.4 11,575 4,060 52.5 106.6 56.0 25.9 9.1 0.0 0.0 0.0 19.120 54.505 459.1 2.07 Norway NOR 189.0 242.8 35,819 46,003 192.3 329.9 634.5 80.3 103.1 0.2 0.5 0.1 10.603 8.256 2,004.2 5.28 Poland POL 817.0 359.0 21,265 9,344 65.8 195.8 128.9 47.7 20.9 1.0 0.7 0.5 1.656 3.768 1,352.9 38.42 Portugal PRT 238.4 163.6 23,148 15,882 102.7 213.2 219.0 51.9 35.6 0.3 0.3 0.1 0.607 0.885 144.8 10.30 Romania ROU 383.0 148.8 19,551 7,594 58.2 180.1 104.7 43.8 17.0 0.5 0.3 0.3 1.571 4.044 601.7 19.59 Russian Federation RUS 2,524.0 948.5 17,188 6,459 56.3 158.3 89.1 38.5 14.5 3.2 1.8 2.0 21.924 58.343 55,336.6 146.84 Serbia SRB 93.1 35.3 13,264 5,034 56.8 122.2 69.4 29.7 11.3 0.1 0.1 0.1 40.767 107.406 3,796.3 7.02 Slovak Republic SVK 106.4 61.7 19,557 11,345 86.9 180.1 156.5 43.8 25.4 0.1 0.1 0.1 0.513 0.885 54.6 5.44 Slovenia SVN 45.9 30.9 22,205 14,977 101.0 204.5 206.6 49.8 33.6 0.1 0.1 0.0 0.597 0.885 27.4 2.07 Spain ESP 1,198.8 909.0 25,763 19,534 113.5 237.3 269.4 57.7 43.8 1.5 1.7 0.6 0.671 0.885 804.6 46.53 Sweden SWE 317.0 346.6 31,514 34,461 163.8 290.2 475.3 70.6 77.2 0.4 0.7 0.1 9.327 8.529 2,956.1 10.06 Switzerland CHE 298.7 406.5 35,344 48,094 203.8 325.5 663.3 79.2 107.8 0.4 0.8 0.1 1.339 0.984 400.0 8.45 Tajikistan TJK 25.0 6.3 2,828 715 37.9 26.0 9.9 6.3 1.6 0.0 0.0 0.1 2.162 8.550 54.0 8.84 Turkey TUR 1,551.1 583.9 19,313 7,270 56.4 177.9 100.3 43.3 16.3 2.0 1.1 1.1 1.373 3.648 2,130.2 80.31 Ukraine UKR 420.6 88.7 9,899 2,089 31.6 91.2 28.8 22.2 4.7 0.5 0.2 0.6 5.612 26.597 2,360.0 42.49 United Kingdom GBR 2,142.6 2,061.8 32,445 31,220 144.1 298.8 430.6 72.7 70.0 2.7 3.9 0.9 0.747 0.776 1,600.0 66.04 Total (46) ECB 20,424.5 14,418.5 23,371 16,499 105.7 215.2 227.5 52.4 37.0 26.1 27.6 12.1 n.a. n.a n.a. 873.93 Latin America and the Caribbean Anguilla AIA 0.3 0.2 18,348 16,076 131.2 169.0 221.7 41.1 36.0 0.0 0.0 0.0 2.366 2.700 0.6 0.01 Antigua and Barbuda ATG 0.9 0.7 9,776 7,801 119.5 90.0 107.6 21.9 17.5 0.0 0.0 0.0 2.155 2.700 2.0 0.10 Argentina ARG 812.2 485.6 18,485 11,052 89.5 170.2 152.4 41.4 24.8 1.0 0.9 0.6 9.903 16.563 8,043.0 43.94 Aruba ABW 2.5 1.9 23,294 17,788 114.4 214.5 245.3 52.2 39.9 0.0 0.0 0.0 1.367 1.790 3.4 0.11 ICP 2017 results 27 Table 2.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 8.2 8.3 21,562 21,762 151.1 198.6 300.1 48.3 48.8 0.0 0.0 0.0 1.009 1.000 8.3 0.38 Barbados BRB 3.3 3.7 11,662 13,053 167.6 107.4 180.0 26.1 29.3 0.0 0.0 0.0 2.239 2.000 7.5 0.29 Belize BLZ 2.0 1.4 5,356 3,674 102.7 49.3 50.7 12.0 8.2 0.0 0.0 0.0 1.372 2.000 2.8 0.38 Bolivia BOL 72.0 26.0 6,436 2,318 53.9 59.3 32.0 14.4 5.2 0.1 0.0 0.2 2.507 6.960 180.6 11.19 Bonaired BON … … … … … … … … … … … … … 1.000 … 0.03 Brazil BRA 2,224.3 1,510.8 10,702 7,269 101.7 98.6 100.3 24.0 16.3 2.8 2.9 2.9 2.168 3.191 4,821.5 207.83 Cayman Islands CYM 2.3 2.9 35,781 46,030 192.6 329.5 634.8 80.2 103.2 0.0 0.0 0.0 1.072 0.833 2.4 0.06 Chile CHL 300.0 201.6 16,199 10,884 100.6 149.2 150.1 36.3 24.4 0.4 0.4 0.3 435.970 648.834 130,809.6 18.52 Colombia COL 545.0 229.1 11,058 4,648 63.0 101.8 64.1 24.8 10.4 0.7 0.4 0.7 1,240.682 2,951.327 676,230.0 49.29 Costa Rica CRI 74.4 46.0 15,052 9,306 92.6 138.6 128.3 33.7 20.9 0.1 0.1 0.1 350.863 567.513 26,114.6 4.94 Curaçao CUW 2.9 2.2 18,181 13,760 113.3 167.4 189.8 40.7 30.8 0.0 0.0 0.0 1.355 1.790 4.0 0.16 Dominica DMA 0.7 0.5 10,481 6,654 95.1 96.5 91.8 23.5 14.9 0.0 0.0 0.0 1.714 2.700 1.3 0.07 Dominican Republic DOM 129.7 59.9 12,340 5,700 69.2 113.7 78.6 27.7 12.8 0.2 0.1 0.1 21.958 47.537 2,848.7 10.51 Ecuador ECU 131.1 70.6 7,812 4,208 80.7 72.0 58.0 17.5 9.4 0.2 0.1 0.2 0.539 1.000 70.6 16.79 El Salvador SLV 46.9 22.5 7,336 3,528 72.0 67.6 48.7 16.4 7.9 0.1 0.0 0.1 0.481 1.000 22.5 6.39 Grenada GRD 1.8 1.1 15,824 9,715 91.9 145.7 134.0 35.5 21.8 0.0 0.0 0.0 1.658 2.700 2.9 0.11 Guyana GUY 5.0 2.5 6,447 3,190 74.1 59.4 44.0 14.4 7.1 0.0 0.0 0.0 104.981 212.190 524.7 0.78 Haiti HTI 21.6 9.7 1,968 883 67.2 18.1 12.2 4.4 2.0 0.0 0.0 0.2 28.588 63.687 617.9 10.98 Honduras HND 43.7 19.3 4,635 2,042 66.0 42.7 28.2 10.4 4.6 0.1 0.0 0.1 10.389 23.588 454.1 9.43 Jamaica JAM 24.9 12.6 8,525 4,317 75.8 78.5 59.5 19.1 9.7 0.0 0.0 0.0 64.797 127.965 1,613.6 2.92 Mexico MEX 1,795.8 826.7 14,557 6,701 68.9 134.1 92.4 32.6 15.0 2.3 1.6 1.7 8.713 18.927 15,645.7 123.36 Montserrat MSR 0.1 0.1 16,099 11,257 104.7 148.3 155.3 36.1 25.2 0.0 0.0 0.0 1.888 2.700 0.2 0.00 Nicaragua NIC 31.4 10.8 4,924 1,697 51.6 45.3 23.4 11.0 3.8 0.0 0.0 0.1 10.355 30.051 325.5 6.38 Panama PAN 73.9 34.5 18,004 8,405 69.9 165.8 115.9 40.4 18.8 0.1 0.1 0.1 0.467 1.000 34.5 4.11 Paraguay PRY 64.5 27.1 9,386 3,953 63.1 86.4 54.5 21.0 8.9 0.1 0.1 0.1 2,342.430 5,562.276 150,972.8 6.87 Peru PER 273.8 146.3 8,708 4,654 80.0 80.2 64.2 19.5 10.4 0.4 0.3 0.4 1.742 3.260 477.1 31.44 Sint Maarten SXM 1.0 0.8 24,297 18,744 115.5 223.8 258.5 54.5 42.0 0.0 0.0 0.0 1.381 1.790 1.4 0.04 St. Kitts and Nevis KNA 0.9 0.7 16,402 13,555 123.8 151.1 186.9 36.8 30.4 0.0 0.0 0.0 2.231 2.700 1.9 0.05 St. Lucia LCA 0.9 0.6 5,042 3,560 105.7 46.4 49.1 11.3 8.0 0.0 0.0 0.0 1.906 2.700 1.7 0.18 St. Vincent and the VCT 1.1 0.7 10,345 6,354 92.0 95.3 87.6 23.2 14.2 0.0 0.0 0.0 1.658 2.700 1.9 0.11 Grenadines Suriname SUR 5.3 1.9 9,306 3,251 52.3 85.7 44.8 20.9 7.3 0.0 0.0 0.0 2.637 7.550 14.0 0.57 Trinidad and Tobago TTO 29.2 17.2 21,101 12,432 88.2 194.3 171.5 47.3 27.9 0.0 0.0 0.0 3.994 6.780 116.6 1.38 Turks and Caicos Islands TCA 0.4 0.4 10,146 11,640 171.8 93.4 160.5 22.7 26.1 0.0 0.0 0.0 1.147 1.000 0.4 0.04 Uruguay URY 56.2 45.0 16,355 13,092 119.9 150.6 180.6 36.7 29.3 0.1 0.1 0.0 22.954 28.676 1,290.2 3.44 Virgin Islands, British VGB 0.5 0.5 15,371 16,199 157.8 141.6 223.4 34.4 36.3 0.0 0.0 0.0 1.054 1.000 0.5 0.03 Total (39) LCB 6,790.9 3,832.5 11,847 6,686 84.5 109.1 92.2 26.6 15.0 8.7 7.3 8.0 n.a. n.a n.a. 573.20 28    Purchasing Power Parities and the Size of World Economies Table 2.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 295.2 91.1 7,133 2,201 46.2 65.7 30.4 16.0 4.9 0.4 0.2 0.6 34.248 110.973 10,111.0 41.39 Bahrain BHR 34.0 17.3 22,643 11,514 76.1 208.5 158.8 50.7 25.8 0.0 0.0 0.0 0.191 0.376 6.5 1.50 Djibouti DJI 3.7 2.1 3,964 2,182 82.4 36.5 30.1 8.9 4.9 0.0 0.0 0.0 97.833 177.720 366.1 0.94 Egypt, Arab Rep. EGY 1,218.2 212.7 12,850 2,243 26.1 118.4 30.9 28.8 5.0 1.6 0.4 1.3 3.116 17.847 3,795.3 94.80 Iran, Islamic Rep. IRN 679.7 257.6 8,385 3,177 56.7 77.2 43.8 18.8 7.1 0.9 0.5 1.1 12,591.238 33,226.298 8,558,679.2 81.07 Iraq IRQ 241.2 101.5 6,495 2,733 63.0 59.8 37.7 14.6 6.1 0.3 0.2 0.5 528.486 1,256.000 127,485.2 37.14 Israel ISR 211.4 236.7 24,273 27,180 167.7 223.6 374.9 54.4 60.9 0.3 0.5 0.1 4.031 3.600 852.1 8.71 Jordan JOR 87.2 37.1 8,673 3,690 63.7 79.9 50.9 19.4 8.3 0.1 0.1 0.1 0.301 0.708 26.3 10.05 Kuwait KWT 103.4 63.9 25,331 15,654 92.5 233.3 215.9 56.8 35.1 0.1 0.1 0.1 0.187 0.303 19.4 4.08 Malta MLT 10.4 7.0 22,102 14,897 100.9 203.6 205.5 49.5 33.4 0.0 0.0 0.0 0.597 0.885 6.2 0.47 Morocco MAR 170.9 72.1 4,902 2,070 63.2 45.2 28.5 11.0 4.6 0.2 0.1 0.5 4.092 9.691 699.1 34.85 Oman OMN 68.3 36.8 14,973 8,072 80.7 137.9 111.3 33.6 18.1 0.1 0.1 0.1 0.207 0.385 14.2 4.56 Qatar QAT 68.8 51.8 25,247 18,997 112.7 232.5 262.0 56.6 42.6 0.1 0.1 0.0 2.746 3.650 188.9 2.72 Saudi Arabia SAU 827.3 369.2 25,368 11,320 66.8 233.6 156.1 56.9 25.4 1.1 0.7 0.5 1.673 3.750 1,384.4 32.61 Tunisia TUN 112.5 32.5 9,842 2,842 43.2 90.6 39.2 22.1 6.4 0.1 0.1 0.2 0.699 2.419 78.6 11.43 United Arab Emirates ARE 240.0 177.1 25,794 19,030 110.5 237.6 262.5 57.8 42.6 0.3 0.3 0.1 2.709 3.673 650.2 9.30 West Bank and Gaza PSE 27.7 14.6 6,226 3,279 78.9 57.3 45.2 14.0 7.3 0.0 0.0 0.1 1.896 3.600 52.6 4.45 Total (17) MEB 4,400.0 1,780.9 11,576 4,685 60.6 106.6 64.6 25.9 10.5 5.6 3.4 5.3 n.a. n.a n.a. 380.10 North America Bermuda BMU 2.6 3.9 40,559 61,155 225.8 373.6 843.4 90.9 137.1 0.0 0.0 0.0 1.508 1.000 3.9 0.06 Canada CAN 1,219.8 1,152.6 33,382 31,543 141.5 307.4 435.0 74.8 70.7 1.6 2.2 0.5 1.226 1.298 1,495.7 36.54 United States USA 14,519.8 14,519.8 44,620 44,620 149.7 411.0 615.4 100.0 100.0 18.6 27.8 4.5 1.000 1.000 14,519.8 325.41 Total (3) NAB 15,742.1 15,676.2 43,485 43,303 149.1 400.5 597.2 97.5 97.0 20.1 30.0 5.0 n.a. n.a n.a. 362.01 South Asia Bangladesh BGD 545.1 186.9 3,369 1,155 51.4 31.0 15.9 7.6 2.6 0.7 0.4 2.2 27.584 80.438 15,036.6 161.80 Bhutan BTN 5.2 1.5 7,169 2,021 42.2 66.0 27.9 16.1 4.5 0.0 0.0 0.0 18.361 65.122 95.7 0.73 India IND 5,457.4 1,588.8 4,169 1,214 43.6 38.4 16.7 9.3 2.7 7.0 3.0 18.2 18.959 65.122 103,467.7 1,309.20 Maldives MDV 3.9 2.3 7,960 4,626 87.0 73.3 63.8 17.8 10.4 0.0 0.0 0.0 8.943 15.387 35.0 0.49 Nepal NPL 72.0 19.7 2,496 683 40.9 23.0 9.4 5.6 1.5 0.1 0.0 0.4 28.577 104.512 2,056.5 28.83 Pakistan PAK 912.0 273.5 4,580 1,374 44.9 42.2 18.9 10.3 3.1 1.2 0.5 2.8 31.623 105.455 28,840.0 199.11 Sri Lanka LKA 184.9 57.8 8,624 2,696 46.8 79.4 37.2 19.3 6.0 0.2 0.1 0.3 47.659 152.446 8,813.7 21.44 Total (7) SAB 7,180.5 2,130.5 4,171 1,238 44.4 38.4 17.1 9.3 2.8 9.2 4.1 23.9 n.a. n.a n.a. 1,721.60 Sub-Saharan Africa Angola AGO 128.5 74.9 4,309 2,513 87.3 39.7 34.7 9.7 5.6 0.2 0.1 0.4 96.738 165.916 12,430.4 29.82 Benin BEN 21.4 7.4 1,917 661 51.6 17.7 9.1 4.3 1.5 0.0 0.0 0.2 200.759 582.075 4,300.8 11.18 Botswana BWA 22.0 9.8 9,972 4,429 66.5 91.8 61.1 22.3 9.9 0.0 0.0 0.0 4.596 10.347 101.1 2.21 ICP 2017 results 29 Table 2.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 24.3 7.8 1,266 406 48.0 11.7 5.6 2.8 0.9 0.0 0.0 0.3 186.741 582.075 4,537.5 19.19 Burundi BDI 8.6 3.0 794 274 51.7 7.3 3.8 1.8 0.6 0.0 0.0 0.2 596.887 1,729.055 5,132.9 10.83 Cabo Verde CPV 2.9 1.3 5,396 2,415 67.0 49.7 33.3 12.1 5.4 0.0 0.0 0.0 43.767 97.799 126.9 0.54 Cameroon CMR 68.2 25.2 2,777 1,027 55.4 25.6 14.2 6.2 2.3 0.1 0.0 0.3 215.335 582.075 14,692.0 24.57 Central African Republic CAF 4.2 2.0 910 434 71.5 8.4 6.0 2.0 1.0 0.0 0.0 0.1 277.743 582.075 1,161.9 4.60 Chad TCD 21.5 8.2 1,429 544 57.0 13.2 7.5 3.2 1.2 0.0 0.0 0.2 221.479 582.075 4,753.2 15.02 Comoros COM 2.4 1.0 2,909 1,259 64.8 26.8 17.4 6.5 2.8 0.0 0.0 0.0 188.913 436.571 447.2 0.81 Congo, Dem. Rep. COD 83.1 33.3 1,021 409 60.0 9.4 5.6 2.3 0.9 0.1 0.1 1.1 586.896 1,464.418 48,775.7 81.40 Congo, Rep. COG 12.5 5.5 2,441 1,082 66.4 22.5 14.9 5.5 2.4 0.0 0.0 0.1 258.018 582.075 3,219.1 5.11 Côte d’Ivoire CIV 66.8 26.9 2,732 1,100 60.3 25.2 15.2 6.1 2.5 0.1 0.1 0.3 234.310 582.075 15,643.8 24.44 Equatorial Guinea GNQ 15.5 6.8 12,302 5,413 65.9 113.3 74.7 27.6 12.1 0.0 0.0 0.0 256.108 582.075 3,976.1 1.26 Eswatini SWZ 8.9 3.8 7,933 3,412 64.4 73.1 47.1 17.8 7.6 0.0 0.0 0.0 5.735 13.334 51.2 1.12 Ethiopia ETH 144.7 47.1 1,360 442 48.7 12.5 6.1 3.0 1.0 0.2 0.1 1.5 7.761 23.866 1,123.0 106.40 Gabon GAB 12.0 5.9 5,823 2,859 73.5 53.6 39.4 13.1 6.4 0.0 0.0 0.0 285.813 582.075 3,436.6 2.06 Gambia, The GMB 4.5 1.3 2,028 605 44.7 18.7 8.3 4.5 1.4 0.0 0.0 0.0 13.904 46.608 62.4 2.21 Ghana GHA 119.1 43.7 4,091 1,502 55.0 37.7 20.7 9.2 3.4 0.2 0.1 0.4 1.597 4.351 190.3 29.12 Guinea GIN 28.9 9.3 2,398 769 48.0 22.1 10.6 5.4 1.7 0.0 0.0 0.2 2,927.525 9,125.743 84,702.7 12.07 Guinea-Bissau GNB 3.2 1.2 1,762 638 54.2 16.2 8.8 3.9 1.4 0.0 0.0 0.0 210.648 582.075 678.4 1.83 Kenya KEN 187.6 69.4 3,735 1,382 55.4 34.4 19.1 8.4 3.1 0.2 0.1 0.7 38.262 103.411 7,177.1 50.22 Lesotho LSO 6.3 2.4 3,019 1,133 56.2 27.8 15.6 6.8 2.5 0.0 0.0 0.0 5.003 13.334 31.6 2.09 Liberia LBR 5.1 2.0 1,076 420 58.4 9.9 5.8 2.4 0.9 0.0 0.0 0.1 43.949 112.707 222.4 4.70 Madagascar MDG 34.4 9.7 1,344 381 42.4 12.4 5.3 3.0 0.9 0.0 0.0 0.4 883.278 3,116.110 30,365.1 25.57 Malawi MWI 18.7 5.7 1,059 324 45.9 9.7 4.5 2.4 0.7 0.0 0.0 0.2 223.770 730.273 4,185.6 17.67 Mali MLI 38.2 12.5 2,063 676 49.1 19.0 9.3 4.6 1.5 0.0 0.0 0.3 190.811 582.075 7,287.4 18.51 Mauritania MRT 9.9 3.1 2,313 729 47.2 21.3 10.1 5.2 1.6 0.0 0.0 0.1 112.644 357.493 1,115.7 4.28 Mauritius MUS 22.9 11.1 18,105 8,759 72.5 166.7 120.8 40.6 19.6 0.0 0.0 0.0 16.683 34.481 381.9 1.26 Mozambique MOZ 31.1 10.2 1,085 357 49.3 10.0 4.9 2.4 0.8 0.0 0.0 0.4 20.935 63.584 650.8 28.65 Namibia NAM 21.7 10.6 9,019 4,421 73.4 83.1 61.0 20.2 9.9 0.0 0.0 0.0 6.526 13.313 141.4 2.40 Niger NER 14.3 5.7 661 264 59.7 6.1 3.6 1.5 0.6 0.0 0.0 0.3 232.238 582.075 3,317.2 21.60 Nigeria NGA 773.4 264.3 4,052 1,385 51.2 37.3 19.1 9.1 3.1 1.0 0.5 2.6 104.502 305.790 80,823.2 190.87 Rwanda RWA 20.1 6.6 1,676 549 49.0 15.4 7.6 3.8 1.2 0.0 0.0 0.2 272.324 831.531 5,468.3 11.98 São Tomé and Príncipe STP 0.7 0.3 3,552 1,579 66.5 32.7 21.8 8.0 3.5 0.0 0.0 0.0 9.662 21.741 7.1 0.21 Senegal SEN 41.6 15.9 2,696 1,029 57.2 24.8 14.2 6.0 2.3 0.1 0.0 0.2 222.146 582.075 9,234.3 15.42 Seychelles SYC 1.9 1.1 19,668 11,375 86.6 181.1 156.9 44.1 25.5 0.0 0.0 0.0 7.893 13.648 15.0 0.10 Sierra Leone SLE 14.1 3.8 1,885 501 39.8 17.4 6.9 4.2 1.1 0.0 0.0 0.1 1,964.228 7,384.432 27,726.4 7.49 South Africa ZAF 526.5 243.5 9,235 4,271 69.3 85.1 58.9 20.7 9.6 0.7 0.5 0.8 6.166 13.334 3,246.3 57.01 Sudan SDN 151.6 36.0 3,717 883 35.6 34.2 12.2 8.3 2.0 0.2 0.1 0.6 4.780 20.130 724.7 40.78 30    Purchasing Power Parities and the Size of World Economies Table 2.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 105.3 34.3 1,926 627 48.7 17.7 8.6 4.3 1.4 0.1 0.1 0.8 725.219 2,228.858 76,360.1 54.66 Togo TGO 9.0 3.5 1,173 456 58.2 10.8 6.3 2.6 1.0 0.0 0.0 0.1 226.395 582.075 2,044.8 7.70 Uganda UGA 78.8 24.1 1,914 586 45.9 17.6 8.1 4.3 1.3 0.1 0.0 0.6 1,106.057 3,611.224 87,153.7 41.17 Zambia ZMB 31.6 13.0 1,872 769 61.5 17.2 10.6 4.2 1.7 0.0 0.0 0.2 3.907 9.520 123.3 16.85 Zimbabwe ZWE 36.1 16.2 2,539 1,141 67.3 23.4 15.7 5.7 2.6 0.0 0.0 0.2 0.449 1.000 16.2 14.24 Total (45) SSB 2,984.0 1,130.4 2,922 1,107 56.7 26.9 15.3 6.5 2.5 3.8 2.2 14.2 n.a. n.a n.a. 1,021.22 World (176) WLD 78,214.1 52,231.0 10,858 7,251 100.0 100.0 100.0 24.3 16.2 100.0 100.0 100.0 n.a. n.a. n.a. 7,203.60 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either the Latin America and the Caribbean or d.  the world totals. ICP 2017 results 31 Table 2.3  Individual consumption expenditure by households: ICP 2017 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 667.5 782.4 27,132 31,801 168.0 302.0 507.5 66.3 77.7 1.0 1.7 0.3 1.529 1.305 1,020.8 24.60 Brunei Darussalam BRN 4.9 2.5 11,464 5,783 72.3 127.6 92.3 28.0 14.1 0.0 0.0 0.0 0.697 1.381 3.4 0.43 Cambodia KHM 48.5 17.8 3,059 1,124 52.7 34.1 17.9 7.5 2.7 0.1 0.0 0.2 1,488.798 4,050.580 72,193.8 15.85 China CHN 7,467.3 4,581.3 5,386 3,304 87.9 60.0 52.7 13.2 8.1 11.5 10.1 19.2 4.147 6.759 30,964.1 1,386.40 Fiji FJI 7.6 3.6 8,636 4,120 68.4 96.1 65.7 21.1 10.1 0.0 0.0 0.0 0.986 2.067 7.5 0.88 Hong Kong SAR, China HKG 286.0 229.1 38,698 30,995 114.8 430.8 494.6 94.6 75.8 0.4 0.5 0.1 6.242 7.793 1,785.5 7.39 Indonesia IDN 1,530.2 582.0 5,843 2,222 54.5 65.0 35.5 14.3 5.4 2.4 1.3 3.6 5,089.686 13,380.872 7,788,168.4 261.89 Japan JPN 2,676.4 2,696.8 21,123 21,284 144.4 235.1 339.6 51.6 52.0 4.1 6.0 1.8 113.023 112.166 302,490.5 126.71 Korea, Rep. KOR 895.9 772.1 17,443 15,032 123.5 194.2 239.9 42.6 36.7 1.4 1.7 0.7 974.206 1,130.425 872,791.4 51.36 Lao PDR LAO 24.4 9.2 3,535 1,326 53.8 39.4 21.2 8.6 3.2 0.0 0.0 0.1 3,133.812 8,351.526 76,447.5 6.90 Malaysia MYS 433.6 174.1 13,541 5,438 57.6 150.7 86.8 33.1 13.3 0.7 0.4 0.4 1.727 4.300 748.9 32.02 Mongolia MNG 17.1 6.1 5,425 1,942 51.3 60.4 31.0 13.3 4.7 0.0 0.0 0.0 873.542 2,439.777 14,922.2 3.15 Myanmar MMR 125.6 36.0 2,363 677 41.1 26.3 10.8 5.8 1.7 0.2 0.1 0.7 389.843 1,360.359 48,963.3 53.15 New Zealand NZL 103.4 115.6 21,405 23,919 160.2 238.3 381.7 52.3 58.5 0.2 0.3 0.1 1.573 1.407 162.7 4.83 Philippines PHL 598.9 230.4 5,708 2,196 55.2 63.5 35.0 14.0 5.4 0.9 0.5 1.5 19.393 50.404 11,614.1 104.92 Singapore SGP 155.3 121.5 27,666 21,647 112.2 308.0 345.4 67.6 52.9 0.2 0.3 0.1 1.080 1.381 167.8 5.61 Taiwan, China TWN 558.2 304.3 23,693 12,918 78.2 263.8 206.1 57.9 31.6 0.9 0.7 0.3 16.598 30.442 9,265.1 23.56 Thailand THA 555.3 217.4 8,208 3,213 56.1 91.4 51.3 20.1 7.9 0.9 0.5 0.9 13.287 33.940 7,378.1 67.65 Vietnam VNM 378.8 132.2 4,019 1,403 50.0 44.7 22.4 9.8 3.4 0.6 0.3 1.3 7,807.612 22,370.087 2,957,279.8 94.24 Total (19) EAB 16,534.8 11,014.5 7,279 4,849 95.5 81.0 77.4 17.8 11.9 25.6 24.4 31.5 n.a. n.a n.a. 2,271.55 Europe and Central Asia Albania ALB 24.6 10.4 8,549 3,625 60.8 95.2 57.9 20.9 8.9 0.0 0.0 0.0 50.357 118.748 1,237.1 2.87 Armenia ARM 26.6 9.2 8,933 3,096 49.7 99.5 49.4 21.8 7.6 0.0 0.0 0.0 167.312 482.720 4,453.3 2.98 Austria AUT 232.7 218.4 26,456 24,835 134.6 294.5 396.3 64.7 60.7 0.4 0.5 0.1 0.831 0.885 193.3 8.80 Azerbaijan AZE 83.2 23.5 8,545 2,418 40.6 95.1 38.6 20.9 5.9 0.1 0.1 0.1 0.487 1.721 40.5 9.73 Belarus BLR 93.4 29.8 9,834 3,138 45.7 109.5 50.1 24.0 7.7 0.1 0.1 0.1 0.617 1.932 57.6 9.50 Belgium BEL 271.5 259.3 23,871 22,796 136.9 265.7 363.8 58.4 55.7 0.4 0.6 0.2 0.845 0.885 229.5 11.38 Bosnia and Herzegovina BIH 31.5 14.2 9,413 4,251 64.7 104.8 67.8 23.0 10.4 0.0 0.0 0.0 0.782 1.731 24.7 3.35 Bulgaria BGR 83.7 35.5 11,822 5,022 60.9 131.6 80.1 28.9 12.3 0.1 0.1 0.1 0.735 1.731 61.5 7.08 Croatia HRV 55.8 32.2 13,510 7,801 82.8 150.4 124.5 33.0 19.1 0.1 0.1 0.1 3.815 6.607 212.8 4.13 Cyprus CYP 19.6 14.8 22,847 17,246 108.2 254.3 275.2 55.8 42.2 0.0 0.0 0.0 0.668 0.885 13.1 0.86 Czech Republic CZE 175.3 102.7 16,555 9,698 84.0 184.3 154.8 40.5 23.7 0.3 0.2 0.1 13.651 23.304 2,393.2 10.59 Denmark DNK 128.3 153.7 22,240 26,653 171.8 247.6 425.3 54.4 65.2 0.2 0.3 0.1 7.891 6.585 1,012.1 5.77 Estonia EST 20.1 13.5 15,240 10,269 96.6 169.7 163.9 37.3 25.1 0.0 0.0 0.0 0.596 0.885 12.0 1.32 Finland FIN 128.7 135.7 23,372 24,642 151.1 260.2 393.2 57.1 60.2 0.2 0.3 0.1 0.933 0.885 120.2 5.51 France FRA 1,483.8 1,400.3 22,126 20,880 135.3 246.3 333.2 54.1 51.0 2.3 3.1 0.9 0.835 0.885 1,239.5 67.06 32    Purchasing Power Parities and the Size of World Economies Table 2.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Georgia GEO 30.8 11.3 8,258 3,043 52.8 91.9 48.6 20.2 7.4 0.0 0.0 0.1 0.925 2.510 28.5 3.73 Germany DEU 2,155.8 1,917.1 26,081 23,193 127.5 290.3 370.1 63.8 56.7 3.3 4.2 1.1 0.787 0.885 1,697.0 82.66 Greece GRC 191.6 139.9 17,813 13,006 104.7 198.3 207.5 43.5 31.8 0.3 0.3 0.1 0.646 0.885 123.8 10.75 Hungary HUN 130.5 70.3 13,333 7,179 77.2 148.4 114.6 32.6 17.5 0.2 0.2 0.1 147.377 273.692 19,232.5 9.79 Iceland ISL 8.5 12.3 24,649 35,957 209.1 274.4 573.8 60.3 87.9 0.0 0.0 0.0 155.648 106.701 1,317.5 0.34 Ireland IRL 98.5 108.0 20,502 22,483 157.2 228.2 358.8 50.1 55.0 0.2 0.2 0.1 0.971 0.885 95.6 4.80 Italy ITA 1,364.5 1,182.6 22,539 19,536 124.2 250.9 311.7 55.1 47.8 2.1 2.6 0.8 0.767 0.885 1,046.8 60.54 Kazakhstan KAZ 228.3 87.7 12,656 4,863 55.1 140.9 77.6 30.9 11.9 0.4 0.2 0.3 125.263 326.000 28,596.7 18.04 Kyrgyz Republic KGZ 22.5 6.3 3,782 1,065 40.4 42.1 17.0 9.2 2.6 0.0 0.0 0.1 19.373 68.769 435.4 5.94 Latvia LVA 28.9 18.1 14,912 9,329 89.7 166.0 148.9 36.5 22.8 0.0 0.0 0.0 0.554 0.885 16.0 1.94 Lithuania LTU 53.8 29.7 19,015 10,491 79.1 211.7 167.4 46.5 25.6 0.1 0.1 0.0 0.488 0.885 26.3 2.83 Luxembourg LUX 17.5 19.1 29,377 32,052 156.4 327.0 511.5 71.8 78.4 0.0 0.0 0.0 0.966 0.885 16.9 0.60 Moldova MDA 24.0 8.3 6,762 2,334 49.5 75.3 37.2 16.5 5.7 0.0 0.0 0.0 6.383 18.490 153.2 3.55 Montenegro MNE 7.7 3.6 12,338 5,837 67.8 137.4 93.1 30.2 14.3 0.0 0.0 0.0 0.419 0.885 3.2 0.62 Netherlands NLD 385.2 369.7 22,487 21,581 137.6 250.3 344.4 55.0 52.8 0.6 0.8 0.2 0.850 0.885 327.3 17.13 North Macedonia MKD 18.6 7.6 8,959 3,644 58.3 99.7 58.1 21.9 8.9 0.0 0.0 0.0 22.167 54.505 412.0 2.07 Norway NOR 137.0 178.2 25,960 33,779 186.5 289.0 539.0 63.5 82.6 0.2 0.4 0.1 10.743 8.256 1,471.7 5.28 Poland POL 629.8 307.9 16,390 8,013 70.1 182.5 127.9 40.1 19.6 1.0 0.7 0.5 1.842 3.768 1,160.2 38.42 Portugal PRT 192.5 143.0 18,687 13,879 106.5 208.0 221.5 45.7 33.9 0.3 0.3 0.1 0.657 0.885 126.5 10.30 Romania ROU 299.4 133.6 15,281 6,820 64.0 170.1 108.8 37.4 16.7 0.5 0.3 0.3 1.805 4.044 540.4 19.59 Russian Federation RUS 1,923.9 831.6 13,101 5,663 62.0 145.9 90.4 32.0 13.8 3.0 1.8 2.0 25.218 58.343 48,516.2 146.84 Serbia SRB 70.2 31.4 9,994 4,466 64.1 111.3 71.3 24.4 10.9 0.1 0.1 0.1 47.992 107.406 3,367.5 7.02 Slovak Republic SVK 81.5 53.3 14,988 9,810 93.8 166.9 156.5 36.6 24.0 0.1 0.1 0.1 0.579 0.885 47.2 5.44 Slovenia SVN 35.4 25.6 17,149 12,378 103.5 190.9 197.5 41.9 30.3 0.1 0.1 0.0 0.639 0.885 22.6 2.07 Spain ESP 965.0 766.2 20,737 16,466 113.8 230.9 262.8 50.7 40.2 1.5 1.7 0.6 0.703 0.885 678.2 46.53 Sweden SWE 225.2 243.6 22,393 24,215 155.0 249.3 386.4 54.7 59.2 0.3 0.5 0.1 9.223 8.529 2,077.2 10.06 Switzerland CHE 264.7 365.5 31,321 43,240 197.9 348.7 690.0 76.6 105.7 0.4 0.8 0.1 1.359 0.984 359.6 8.45 Tajikistan TJK 18.3 5.6 2,071 629 43.5 23.1 10.0 5.1 1.5 0.0 0.0 0.1 2.595 8.550 47.5 8.84 Turkey TUR 1,115.1 503.3 13,884 6,267 64.7 154.6 100.0 33.9 15.3 1.7 1.1 1.1 1.647 3.648 1,836.2 80.31 Ukraine UKR 285.7 75.3 6,725 1,771 37.8 74.9 28.3 16.4 4.3 0.4 0.2 0.6 7.006 26.597 2,001.5 42.49 United Kingdom GBR 1,727.3 1,735.6 26,156 26,281 144.0 291.2 419.4 63.9 64.2 2.7 3.8 0.9 0.780 0.776 1,346.9 66.04 Total (46) ECB 15,596.2 11,844.6 17,846 13,553 108.9 198.7 216.3 43.6 33.1 24.1 26.2 12.1 n.a. n.a n.a. 873.93 Latin America and the Caribbean Anguilla AIA 0.2 0.2 15,529 14,923 137.7 172.9 238.1 38.0 36.5 0.0 0.0 0.0 2.595 2.700 0.6 0.01 Antigua and Barbuda ATG 0.7 0.6 7,154 6,539 131.0 79.6 104.4 17.5 16.0 0.0 0.0 0.0 2.468 2.700 1.7 0.10 Argentina ARG 675.0 440.5 15,363 10,025 93.5 171.0 160.0 37.6 24.5 1.0 1.0 0.6 10.808 16.563 7,295.3 43.94 Aruba ABW 2.2 1.9 21,323 17,636 118.6 237.4 281.4 52.1 43.1 0.0 0.0 0.0 1.480 1.790 3.3 0.11 ICP 2017 results 33 Table 2.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 7.0 7.7 18,222 20,096 158.1 202.9 320.7 44.5 49.1 0.0 0.0 0.0 1.103 1.000 7.7 0.38 Barbados BRB 2.8 3.4 9,918 11,755 169.9 110.4 187.6 24.2 28.7 0.0 0.0 0.0 2.371 2.000 6.7 0.29 Belize BLZ 1.8 1.3 4,662 3,443 105.9 51.9 54.9 11.4 8.4 0.0 0.0 0.0 1.477 2.000 2.6 0.38 Bolivia BOL 67.1 25.2 5,998 2,251 53.8 66.8 35.9 14.7 5.5 0.1 0.1 0.2 2.612 6.960 175.3 11.19 Bonaired BON 0.3 0.2 11,088 9,002 116.4 123.4 143.7 27.1 22.0 0.0 0.0 0.0 0.812 1.000 0.2 0.03 Brazil BRA 1,824.0 1,330.2 8,776 6,400 104.5 97.7 102.1 21.5 15.6 2.8 2.9 2.9 2.327 3.191 4,245.1 207.83 Cayman Islands CYM 2.0 2.8 31,757 43,810 197.7 353.5 699.1 77.6 107.1 0.0 0.0 0.0 1.150 0.833 2.3 0.06 Chile CHL 237.1 175.0 12,800 9,450 105.8 142.5 150.8 31.3 23.1 0.4 0.4 0.3 478.996 648.834 113,565.7 18.52 Colombia COL 444.4 213.7 9,016 4,336 68.9 100.4 69.2 22.0 10.6 0.7 0.5 0.7 1,419.374 2,951.327 630,818.0 49.29 Costa Rica CRI 59.9 39.3 12,112 7,954 94.1 134.8 126.9 29.6 19.4 0.1 0.1 0.1 372.669 567.513 22,319.8 4.94 Curaçao CUW 2.4 2.0 14,573 12,073 118.8 162.2 192.7 35.6 29.5 0.0 0.0 0.0 1.483 1.790 3.5 0.16 Dominica DMA 0.6 0.4 8,908 6,190 99.6 99.2 98.8 21.8 15.1 0.0 0.0 0.0 1.876 2.700 1.2 0.07 Dominican Republic DOM 108.3 55.6 10,299 5,284 73.5 114.7 84.3 25.2 12.9 0.2 0.1 0.1 24.391 47.537 2,641.0 10.51 Ecuador ECU 108.8 62.5 6,479 3,722 82.4 72.1 59.4 15.8 9.1 0.2 0.1 0.2 0.575 1.000 62.5 16.79 El Salvador SLV 40.5 20.8 6,335 3,263 73.8 70.5 52.1 15.5 8.0 0.1 0.0 0.1 0.515 1.000 20.8 6.39 Grenada GRD 1.5 1.0 13,758 9,170 95.5 153.2 146.3 33.6 22.4 0.0 0.0 0.0 1.800 2.700 2.7 0.11 Guyana GUY 4.1 2.2 5,240 2,855 78.1 58.3 45.6 12.8 7.0 0.0 0.0 0.0 115.626 212.190 469.7 0.78 Haiti HTI 18.1 8.8 1,644 803 70.0 18.3 12.8 4.0 2.0 0.0 0.0 0.2 31.103 63.687 561.6 10.98 Honduras HND 38.5 17.7 4,085 1,877 65.9 45.5 30.0 10.0 4.6 0.1 0.0 0.1 10.839 23.588 417.4 9.43 Jamaica JAM 21.2 11.6 7,247 3,987 78.9 80.7 63.6 17.7 9.7 0.0 0.0 0.0 70.392 127.965 1,490.0 2.92 Mexico MEX 1,450.2 755.6 11,756 6,125 74.7 130.9 97.7 28.7 15.0 2.2 1.7 1.7 9.861 18.927 14,301.2 123.36 Montserrat MSR 0.1 0.0 12,382 9,712 112.4 137.8 155.0 30.3 23.7 0.0 0.0 0.0 2.118 2.700 0.1 0.00 Nicaragua NIC 25.6 9.8 4,007 1,537 55.0 44.6 24.5 9.8 3.8 0.0 0.0 0.1 11.528 30.051 294.9 6.38 Panama PAN 61.7 31.3 15,018 7,630 72.8 167.2 121.8 36.7 18.7 0.1 0.1 0.1 0.508 1.000 31.3 4.11 Paraguay PRY 55.1 25.2 8,031 3,667 65.5 89.4 58.5 19.6 9.0 0.1 0.1 0.1 2,539.985 5,562.276 140,077.6 6.87 Peru PER 233.1 135.4 7,412 4,305 83.3 82.5 68.7 18.1 10.5 0.4 0.3 0.4 1.894 3.260 441.3 31.44 Sint Maarten SXM 0.9 0.7 21,227 17,649 119.2 236.3 281.6 51.9 43.1 0.0 0.0 0.0 1.488 1.790 1.3 0.04 St. Kitts and Nevis KNA 0.7 0.6 13,138 12,395 135.2 146.3 197.8 32.1 30.3 0.0 0.0 0.0 2.547 2.700 1.7 0.05 St. Lucia LCA 0.8 0.6 4,239 3,264 110.4 47.2 52.1 10.4 8.0 0.0 0.0 0.0 2.079 2.700 1.6 0.18 St. Vincent and the VCT 0.9 0.6 8,563 5,730 95.9 95.3 91.4 20.9 14.0 0.0 0.0 0.0 1.807 2.700 1.7 0.11 Grenadines Suriname SUR 4.2 1.6 7,434 2,889 55.7 82.8 46.1 18.2 7.1 0.0 0.0 0.0 2.934 7.550 12.4 0.57 Trinidad and Tobago TTO 23.3 14.5 16,835 10,458 89.0 187.4 166.9 41.2 25.6 0.0 0.0 0.0 4.212 6.780 98.1 1.38 Turks and Caicos Islands TCA 0.3 0.4 8,618 10,737 178.6 95.9 171.3 21.1 26.2 0.0 0.0 0.0 1.246 1.000 0.4 0.04 Uruguay URY 46.2 40.0 13,432 11,642 124.2 149.5 185.8 32.8 28.5 0.1 0.1 0.0 24.854 28.676 1,147.3 3.44 Virgin Islands, British VGB 0.4 0.5 13,979 15,319 157.1 155.6 244.5 34.2 37.4 0.0 0.0 0.0 1.096 1.000 0.5 0.03 Total (39) LCB 5,571.5 3,441.4 9,720 6,004 88.5 108.2 95.8 23.8 14.7 8.6 7.6 8.0 n.a. n.a n.a. 573.20 34    Purchasing Power Parities and the Size of World Economies Table 2.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 211.3 72.7 5,104 1,757 49.4 56.8 28.0 12.5 4.3 0.3 0.2 0.6 38.210 110.973 8,071.9 41.39 Bahrain BHR 27.4 14.9 18,267 9,916 77.8 203.4 158.2 44.7 24.2 0.0 0.0 0.0 0.204 0.376 5.6 1.50 Djibouti DJI 3.2 1.9 3,386 1,996 84.5 37.7 31.8 8.3 4.9 0.0 0.0 0.0 104.737 177.720 334.8 0.94 Egypt, Arab Rep. EGY 1,063.3 203.0 11,216 2,142 27.4 124.9 34.2 27.4 5.2 1.6 0.4 1.3 3.408 17.847 3,623.5 94.80 Iran, Islamic Rep. IRN 581.2 243.9 7,169 3,009 60.2 79.8 48.0 17.5 7.4 0.9 0.5 1.1 13,944.904 33,226.298 8,104,686.7 81.07 Iraq IRQ 205.4 90.8 5,530 2,445 63.4 61.6 39.0 13.5 6.0 0.3 0.2 0.5 555.391 1,256.000 114,058.4 37.14 Israel ISR 165.2 193.1 18,969 22,168 167.5 211.2 353.7 46.4 54.2 0.3 0.4 0.1 4.207 3.600 695.0 8.71 Jordan JOR 75.6 35.1 7,518 3,495 66.6 83.7 55.8 18.4 8.5 0.1 0.1 0.1 0.329 0.708 24.9 10.05 Kuwait KWT 79.8 49.3 19,541 12,074 88.6 217.5 192.7 47.8 29.5 0.1 0.1 0.1 0.187 0.303 15.0 4.08 Malta MLT 7.9 5.6 16,957 12,031 101.7 188.8 192.0 41.5 29.4 0.0 0.0 0.0 0.628 0.885 5.0 0.47 Morocco MAR 143.5 63.6 4,118 1,823 63.5 45.8 29.1 10.1 4.5 0.2 0.1 0.5 4.291 9.691 615.9 34.85 Oman OMN 53.4 29.4 11,710 6,444 78.9 130.4 102.8 28.6 15.8 0.1 0.1 0.1 0.212 0.385 11.3 4.56 Qatar QAT 51.6 40.9 18,950 15,019 113.6 211.0 239.7 46.3 36.7 0.1 0.1 0.0 2.893 3.650 149.4 2.72 Saudi Arabia SAU 621.2 285.5 19,049 8,755 65.9 212.1 139.7 46.6 21.4 1.0 0.6 0.5 1.724 3.750 1,070.8 32.61 Tunisia TUN 93.8 28.8 8,200 2,516 44.0 91.3 40.1 20.0 6.1 0.1 0.1 0.2 0.742 2.419 69.6 11.43 United Arab Emirates ARE 181.1 139.8 19,464 15,025 110.6 216.7 239.8 47.6 36.7 0.3 0.3 0.1 2.835 3.673 513.4 9.30 West Bank and Gaza PSE 22.2 12.8 4,990 2,864 82.3 55.5 45.7 12.2 7.0 0.0 0.0 0.1 2.066 3.600 45.9 4.45 Total (17) MEB 3,587.1 1,511.1 9,437 3,976 60.4 105.1 63.4 23.1 9.7 5.5 3.3 5.3 n.a. n.a n.a. 380.10 North America Bermuda BMU 2.1 3.3 33,063 52,096 225.9 368.1 831.3 80.8 127.3 0.0 0.0 0.0 1.576 1.000 3.3 0.06 Canada CAN 949.5 941.4 25,984 25,762 142.1 289.3 411.1 63.5 63.0 1.5 2.1 0.5 1.287 1.298 1,221.6 36.54 United States USA 13,312.1 13,312.1 40,909 40,909 143.3 455.4 652.8 100.0 100.0 20.6 29.5 4.5 1.000 1.000 13,312.1 325.41 Total (3) NAB 14,263.6 14,256.7 39,401 39,382 143.3 438.6 628.4 96.3 96.3 22.0 31.6 5.0 n.a. n.a n.a. 362.01 South Asia Bangladesh BGD 499.8 183.4 3,089 1,133 52.6 34.4 18.1 7.6 2.8 0.8 0.4 2.2 29.514 80.438 14,751.8 161.80 Bhutan BTN 4.2 1.3 5,835 1,834 45.1 65.0 29.3 14.3 4.5 0.0 0.0 0.0 20.474 65.122 86.9 0.73 India IND 5,024.0 1,502.0 3,837 1,147 42.9 42.7 18.3 9.4 2.8 7.8 3.3 18.2 19.469 65.122 97,813.2 1,309.20 Maldives MDV 3.0 1.9 6,198 3,945 91.2 69.0 63.0 15.2 9.6 0.0 0.0 0.0 9.794 15.387 29.8 0.49 Nepal NPL 65.6 19.2 2,277 665 41.9 25.3 10.6 5.6 1.6 0.1 0.0 0.4 30.513 104.512 2,002.9 28.83 Pakistan PAK 822.7 259.4 4,132 1,303 45.2 46.0 20.8 10.1 3.2 1.3 0.6 2.8 33.251 105.455 27,355.3 199.11 Sri Lanka LKA 148.9 54.2 6,943 2,528 52.2 77.3 40.3 17.0 6.2 0.2 0.1 0.3 55.501 152.446 8,262.7 21.44 Total (7) SAB 6,568.4 2,021.4 3,815 1,174 44.1 42.5 18.7 9.3 2.9 10.2 4.5 23.9 n.a. n.a n.a. 1,721.60 Sub-Saharan Africa Angola AGO 110.9 71.7 3,720 2,405 92.7 41.4 38.4 9.1 5.9 0.2 0.2 0.4 107.270 165.916 11,898.4 29.82 Benin BEN 18.1 6.8 1,616 609 54.0 18.0 9.7 4.0 1.5 0.0 0.0 0.2 219.476 582.075 3,964.4 11.18 Botswana BWA 17.7 8.6 8,039 3,891 69.4 89.5 62.1 19.7 9.5 0.0 0.0 0.0 5.009 10.347 88.8 2.21 ICP 2017 results 35 Table 2.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 100.0 Expenditure level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 20.9 7.2 1,089 374 49.2 12.1 6.0 2.7 0.9 0.0 0.0 0.3 199.741 582.075 4,173.7 19.19 Burundi BDI 7.3 2.8 675 255 54.3 7.5 4.1 1.6 0.6 0.0 0.0 0.2 654.422 1,729.055 4,781.8 10.83 Cabo Verde CPV 2.3 1.1 4,268 2,078 69.8 47.5 33.2 10.4 5.1 0.0 0.0 0.0 47.612 97.799 109.2 0.54 Cameroon CMR 59.8 24.3 2,435 991 58.3 27.1 15.8 6.0 2.4 0.1 0.1 0.3 236.912 582.075 14,169.0 24.57 Central African Republic CAF 3.6 1.9 790 416 75.6 8.8 6.6 1.9 1.0 0.0 0.0 0.1 306.808 582.075 1,113.8 4.60 Chad TCD 18.9 7.7 1,257 513 58.5 14.0 8.2 3.1 1.3 0.0 0.0 0.2 237.656 582.075 4,484.7 15.02 Comoros COM 2.0 1.0 2,502 1,224 70.1 27.8 19.5 6.1 3.0 0.0 0.0 0.0 213.518 436.571 434.7 0.81 Congo, Dem. Rep. COD 73.5 31.6 902 389 61.7 10.0 6.2 2.2 0.9 0.1 0.1 1.1 630.606 1,464.418 46,322.8 81.40 Congo, Rep. COG 10.6 5.2 2,068 1,016 70.4 23.0 16.2 5.1 2.5 0.0 0.0 0.1 285.969 582.075 3,022.7 5.11 Côte d’Ivoire CIV 58.9 25.0 2,409 1,023 60.9 26.8 16.3 5.9 2.5 0.1 0.1 0.3 247.134 582.075 14,550.6 24.44 Equatorial Guinea GNQ 10.9 5.7 8,663 4,529 74.9 96.4 72.3 21.2 11.1 0.0 0.0 0.0 304.287 582.075 3,326.9 1.26 Eswatini SWZ 7.6 3.5 6,726 3,086 65.8 74.9 49.2 16.4 7.5 0.0 0.0 0.0 6.118 13.334 46.3 1.12 Ethiopia ETH 124.5 44.3 1,170 417 51.0 13.0 6.6 2.9 1.0 0.2 0.1 1.5 8.496 23.866 1,058.1 106.40 Gabon GAB 10.1 5.5 4,874 2,672 78.6 54.3 42.6 11.9 6.5 0.0 0.0 0.0 319.160 582.075 3,211.8 2.06 Gambia, The GMB 4.0 1.3 1,793 582 46.5 20.0 9.3 4.4 1.4 0.0 0.0 0.0 15.114 46.608 60.0 2.21 Ghana GHA 106.6 42.9 3,660 1,473 57.7 40.7 23.5 8.9 3.6 0.2 0.1 0.4 1.751 4.351 186.6 29.12 Guinea GIN 25.7 9.0 2,126 749 50.5 23.7 11.9 5.2 1.8 0.0 0.0 0.2 3,213.984 9,125.743 82,442.7 12.07 Guinea-Bissau GNB 2.8 1.1 1,543 615 57.2 17.2 9.8 3.8 1.5 0.0 0.0 0.0 232.199 582.075 654.9 1.83 Kenya KEN 148.8 59.9 2,963 1,193 57.7 33.0 19.0 7.2 2.9 0.2 0.1 0.7 41.635 103.411 6,196.5 50.22 Lesotho LSO 5.3 2.1 2,549 1,003 56.4 28.4 16.0 6.2 2.5 0.0 0.0 0.0 5.244 13.334 28.0 2.09 Liberia LBR 4.0 1.7 851 362 61.0 9.5 5.8 2.1 0.9 0.0 0.0 0.1 47.996 112.707 192.1 4.70 Madagascar MDG 30.0 9.3 1,173 363 44.3 13.1 5.8 2.9 0.9 0.0 0.0 0.4 962.960 3,116.110 28,886.2 25.57 Malawi MWI 16.5 5.5 933 309 47.5 10.4 4.9 2.3 0.8 0.0 0.0 0.2 241.931 730.273 3,989.0 17.67 Mali MLI 34.0 12.0 1,838 648 50.6 20.5 10.3 4.5 1.6 0.1 0.0 0.3 205.273 582.075 6,986.4 18.51 Mauritania MRT 7.9 2.8 1,855 646 49.9 20.6 10.3 4.5 1.6 0.0 0.0 0.1 124.453 357.493 988.6 4.28 Mauritius MUS 19.4 10.1 15,332 8,008 74.9 170.7 127.8 37.5 19.6 0.0 0.0 0.0 18.009 34.481 349.2 1.26 Mozambique MOZ 26.0 9.0 908 314 49.6 10.1 5.0 2.2 0.8 0.0 0.0 0.4 21.988 63.584 572.3 28.65 Namibia NAM 18.0 9.3 7,508 3,890 74.3 83.6 62.1 18.4 9.5 0.0 0.0 0.0 6.898 13.313 124.4 2.40 Niger NER 12.8 5.4 591 249 60.4 6.6 4.0 1.4 0.6 0.0 0.0 0.3 245.160 582.075 3,129.6 21.60 Nigeria NGA 709.2 260.0 3,716 1,362 52.5 41.4 21.7 9.1 3.3 1.1 0.6 2.6 112.098 305.790 79,505.3 190.87 Rwanda RWA 17.7 6.2 1,476 522 50.6 16.4 8.3 3.6 1.3 0.0 0.0 0.2 293.705 831.531 5,195.5 11.98 São Tomé and Príncipe STP 0.6 0.3 3,009 1,489 70.9 33.5 23.8 7.4 3.6 0.0 0.0 0.0 10.757 21.741 6.7 0.21 Senegal SEN 35.8 14.7 2,324 953 58.8 25.9 15.2 5.7 2.3 0.1 0.0 0.2 238.578 582.075 8,550.5 15.42 Seychelles SYC 1.3 0.9 13,731 9,082 94.8 152.9 144.9 33.6 22.2 0.0 0.0 0.0 9.027 13.648 12.0 0.10 Sierra Leone SLE 12.8 3.7 1,705 491 41.3 19.0 7.8 4.2 1.2 0.0 0.0 0.1 2,128.519 7,384.432 27,172.5 7.49 South Africa ZAF 429.4 210.9 7,533 3,700 70.4 83.9 59.0 18.4 9.0 0.7 0.5 0.8 6.549 13.334 2,812.5 57.01 Sudan SDN 133.1 35.5 3,262 871 38.3 36.3 13.9 8.0 2.1 0.2 0.1 0.6 5.377 20.130 715.4 40.78 36    Purchasing Power Parities and the Size of World Economies Table 2.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 100.0 Expenditure level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 95.0 32.2 1,738 588 48.5 19.3 9.4 4.2 1.4 0.1 0.1 0.8 754.621 2,228.858 71,675.1 54.66 Togo TGO 7.8 3.3 1,016 431 60.7 11.3 6.9 2.5 1.1 0.0 0.0 0.1 246.596 582.075 1,929.5 7.70 Uganda UGA 67.9 23.0 1,650 558 48.5 18.4 8.9 4.0 1.4 0.1 0.1 0.6 1,221.088 3,611.224 82,956.1 41.17 Zambia ZMB 27.4 12.2 1,625 721 63.6 18.1 11.5 4.0 1.8 0.0 0.0 0.2 4.224 9.520 115.7 16.85 Zimbabwe ZWE 29.1 14.1 2,042 990 69.5 22.7 15.8 5.0 2.4 0.0 0.0 0.2 0.485 1.000 14.1 14.24 Total (45) SSB 2,586.6 1,052.4 2,533 1,030 58.3 28.2 16.4 6.2 2.5 4.0 2.3 14.2 n.a. n.a n.a. 1,021.22 World (176) WLD 64,708.2 45,142.1 8,983 6,267 100.0 100.0 100.0 22.0 15.3 100.0 100.0 100.0 n.a. n.a. n.a. 7,203.60 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either the Latin America and the Caribbean or the world totals. ICP 2017 results 37 Table 2.4  Consumption expenditure by government: ICP 2017 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 266.9 257.7 10,848 10,476 178.7 320.6 572.8 128.0 123.6 1.1 2.0 0.3 1.260 1.305 336.3 24.60 Brunei Darussalam BRN 11.6 3.2 26,911 7,477 51.4 795.3 408.8 317.6 88.2 0.0 0.0 0.0 0.384 1.381 4.4 0.43 Cambodia KHM 7.4 1.9 466 118 46.7 13.8 6.4 5.5 1.4 0.0 0.0 0.2 1,021.905 4,050.580 7,551.7 15.85 China CHN 3,526.8 1,930.2 2,544 1,392 101.3 75.2 76.1 30.0 16.4 14.5 14.7 19.2 3.699 6.759 13,045.7 1,386.40 Fiji FJI 2.7 0.9 3,078 1,049 63.1 91.0 57.4 36.3 12.4 0.0 0.0 0.0 0.705 2.067 1.9 0.88 Hong Kong SAR, China HKG 47.0 33.6 6,362 4,539 132.0 188.0 248.2 75.1 53.6 0.2 0.3 0.1 5.560 7.793 261.5 7.39 Indonesia IDN 403.1 92.3 1,539 352 42.4 45.5 19.3 18.2 4.2 1.7 0.7 3.6 3,062.762 13,380.872 1,234,554.3 261.89 Japan JPN 1,340.7 956.0 10,581 7,545 131.9 312.7 412.6 124.9 89.1 5.5 7.3 1.8 79.983 112.166 107,234.8 126.71 Korea, Rep. KOR 426.6 250.4 8,305 4,875 108.6 245.4 266.6 98.0 57.5 1.7 1.9 0.7 663.553 1,130.425 283,045.8 51.36 Lao PDR LAO 15.9 2.5 2,303 363 29.2 68.1 19.9 27.2 4.3 0.1 0.0 0.1 1,317.505 8,351.526 20,941.2 6.90 Malaysia MYS 128.1 38.3 3,999 1,196 55.3 118.2 65.4 47.2 14.1 0.5 0.3 0.4 1.286 4.300 164.7 32.02 Mongolia MNG 10.4 1.5 3,312 462 25.8 97.9 25.3 39.1 5.5 0.0 0.0 0.0 340.394 2,439.777 3,550.2 3.15 Myanmar MMR 67.4 11.7 1,267 220 32.1 37.4 12.0 15.0 2.6 0.3 0.1 0.7 236.340 1,360.359 15,918.2 53.15 New Zealand NZL 50.2 36.1 10,399 7,467 132.9 307.3 408.3 122.7 88.1 0.2 0.3 0.1 1.011 1.407 50.8 4.83 Philippines PHL 111.0 35.3 1,058 336 58.8 31.3 18.4 12.5 4.0 0.5 0.3 1.5 16.007 50.404 1,776.9 104.92 Singapore SGP 66.9 35.6 11,912 6,337 98.4 352.0 346.5 140.6 74.8 0.3 0.3 0.1 0.735 1.381 49.1 5.61 Taiwan, China TWN 214.2 80.9 9,093 3,432 69.8 268.7 187.7 107.3 40.5 0.9 0.6 0.3 11.491 30.442 2,461.6 23.56 Thailand THA 267.4 73.0 3,953 1,080 50.5 116.8 59.0 46.7 12.7 1.1 0.6 0.9 9.270 33.940 2,479.1 67.65 Vietnam VNM 141.7 25.8 1,503 274 33.7 44.4 15.0 17.7 3.2 0.6 0.2 1.3 4,078.183 22,370.087 577,719.4 94.24 Total (19) EAB 7,105.9 3,866.7 3,128 1,702 100.7 92.4 93.1 36.9 20.1 29.2 29.4 31.5 n.a. n.a n.a. 2,271.55 Europe and Central Asia Albania ALB 10.4 1.5 3,622 521 26.6 107.0 28.5 42.7 6.2 0.0 0.0 0.0 17.086 118.748 177.8 2.87 Armenia ARM 10.2 1.4 3,408 477 25.9 100.7 26.1 40.2 5.6 0.0 0.0 0.0 67.503 482.720 685.5 2.98 Austria AUT 100.7 81.5 11,447 9,272 149.9 338.3 507.0 135.1 109.4 0.4 0.6 0.1 0.717 0.885 72.2 8.80 Azerbaijan AZE 37.1 4.6 3,807 476 23.1 112.5 26.0 44.9 5.6 0.2 0.0 0.1 0.215 1.721 8.0 9.73 Belarus BLR 61.5 8.6 6,475 902 25.8 191.3 49.3 76.4 10.6 0.3 0.1 0.1 0.269 1.932 16.6 9.50 Belgium BEL 142.2 116.3 12,499 10,227 151.4 369.4 559.2 147.5 120.7 0.6 0.9 0.2 0.724 0.885 103.0 11.38 Bosnia and Herzegovina BIH 15.9 3.7 4,739 1,098 42.9 140.1 60.0 55.9 13.0 0.1 0.0 0.0 0.401 1.731 6.4 3.35 Bulgaria BGR 45.0 9.2 6,358 1,306 38.0 187.9 71.4 75.0 15.4 0.2 0.1 0.1 0.356 1.731 16.0 7.08 Croatia HRV 34.1 10.8 8,268 2,622 58.7 244.3 143.4 97.6 30.9 0.1 0.1 0.1 2.095 6.607 71.5 4.13 Cyprus CYP 5.2 3.4 6,079 3,946 120.1 179.7 215.7 71.8 46.6 0.0 0.0 0.0 0.574 0.885 3.0 0.86 Czech Republic CZE 128.2 41.6 12,107 3,924 60.0 357.8 214.6 142.9 46.3 0.5 0.3 0.1 7.554 23.304 968.4 10.59 Denmark DNK 88.3 81.3 15,306 14,104 170.5 452.3 771.2 180.6 166.5 0.4 0.6 0.1 6.067 6.585 535.6 5.77 Estonia EST 13.5 5.3 10,267 4,056 73.1 303.4 221.8 121.2 47.9 0.1 0.0 0.0 0.350 0.885 4.7 1.32 Finland FIN 72.8 58.2 13,216 10,562 147.9 390.5 577.5 156.0 124.7 0.3 0.4 0.1 0.707 0.885 51.5 5.51 France FRA 870.9 614.1 12,986 9,157 130.5 383.8 500.7 153.3 108.1 3.6 4.7 0.9 0.624 0.885 543.6 67.06 38    Purchasing Power Parities and the Size of World Economies Table 2.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Georgia GEO 14.5 2.3 3,898 604 28.7 115.2 33.0 46.0 7.1 0.1 0.0 0.1 0.389 2.510 5.6 3.73 Germany DEU 1,027.4 727.9 12,430 8,806 131.1 367.3 481.5 146.7 103.9 4.2 5.5 1.1 0.627 0.885 644.3 82.66 Greece GRC 81.0 40.3 7,535 3,750 92.1 222.7 205.0 88.9 44.3 0.3 0.3 0.1 0.440 0.885 35.7 10.75 Hungary HUN 92.9 28.9 9,493 2,949 57.5 280.5 161.2 112.0 34.8 0.4 0.2 0.1 85.011 273.692 7,898.8 9.79 Iceland ISL 4.8 5.8 13,936 16,755 222.5 411.8 916.2 164.5 197.7 0.0 0.0 0.0 128.285 106.701 613.9 0.34 Ireland IRL 48.1 40.2 10,022 8,376 154.6 296.2 458.0 118.3 98.9 0.2 0.3 0.1 0.740 0.885 35.6 4.80 Italy ITA 525.8 369.3 8,685 6,100 130.0 256.7 333.6 102.5 72.0 2.2 2.8 0.8 0.622 0.885 326.9 60.54 Kazakhstan KAZ 122.1 17.6 6,767 974 26.6 200.0 53.3 79.9 11.5 0.5 0.1 0.3 46.939 326.000 5,729.3 18.04 Kyrgyz Republic KGZ 13.1 1.3 2,200 222 18.7 65.0 12.2 26.0 2.6 0.1 0.0 0.1 6.950 68.769 90.9 5.94 Latvia LVA 16.7 5.5 8,604 2,824 60.7 254.3 154.4 101.5 33.3 0.1 0.0 0.0 0.291 0.885 4.9 1.94 Lithuania LTU 26.9 7.8 9,523 2,754 53.5 281.4 150.6 112.4 32.5 0.1 0.1 0.0 0.256 0.885 6.9 2.83 Luxembourg LUX 9.2 10.5 15,481 17,662 211.1 457.5 965.8 182.7 208.4 0.0 0.1 0.0 1.010 0.885 9.3 0.60 Moldova MDA 12.4 1.5 3,484 410 21.8 103.0 22.4 41.1 4.8 0.1 0.0 0.0 2.175 18.490 26.9 3.55 Montenegro MNE 4.4 0.9 7,086 1,438 37.6 209.4 78.6 83.6 17.0 0.0 0.0 0.0 0.180 0.885 0.8 0.62 Netherlands NLD 248.8 202.8 14,521 11,836 150.8 429.1 647.2 171.4 139.7 1.0 1.5 0.2 0.722 0.885 179.5 17.13 North Macedonia MKD 9.9 1.7 4,780 816 31.6 141.2 44.6 56.4 9.6 0.0 0.0 0.0 9.301 54.505 92.2 2.07 Norway NOR 84.5 95.8 16,020 18,158 209.7 473.4 992.9 189.1 214.3 0.3 0.7 0.1 9.358 8.256 791.1 5.28 Poland POL 325.6 93.3 8,474 2,429 53.0 250.4 132.8 100.0 28.7 1.3 0.7 0.5 1.080 3.768 351.7 38.42 Portugal PRT 76.7 38.0 7,444 3,693 91.8 220.0 201.9 87.9 43.6 0.3 0.3 0.1 0.439 0.885 33.7 10.30 Romania ROU 153.9 33.3 7,857 1,701 40.1 232.2 93.0 92.7 20.1 0.6 0.3 0.3 0.875 4.044 134.8 19.59 Russian Federation RUS 1,369.1 285.4 9,323 1,943 38.6 275.5 106.3 110.0 22.9 5.6 2.2 2.0 12.161 58.343 16,649.2 146.84 Serbia SRB 41.6 7.2 5,928 1,020 31.8 175.2 55.7 70.0 12.0 0.2 0.1 0.1 18.473 107.406 768.8 7.02 Slovak Republic SVK 53.1 18.1 9,757 3,320 63.0 288.3 181.5 115.2 39.2 0.2 0.1 0.1 0.301 0.885 16.0 5.44 Slovenia SVN 18.4 9.0 8,920 4,333 89.9 263.6 236.9 105.3 51.1 0.1 0.1 0.0 0.430 0.885 7.9 2.07 Spain ESP 406.9 244.4 8,744 5,252 111.1 258.4 287.2 103.2 62.0 1.7 1.9 0.6 0.532 0.885 216.3 46.53 Sweden SWE 148.2 141.2 14,738 14,043 176.3 435.5 767.9 173.9 165.7 0.6 1.1 0.1 8.127 8.529 1,204.6 10.06 Switzerland CHE 63.8 81.9 7,553 9,684 237.2 223.2 529.5 89.1 114.3 0.3 0.6 0.1 1.262 0.984 80.5 8.45 Tajikistan TJK 10.9 1.0 1,236 118 17.7 36.5 6.5 14.6 1.4 0.0 0.0 0.1 0.819 8.550 8.9 8.84 Turkey TUR 667.1 123.5 8,306 1,538 34.3 245.5 84.1 98.0 18.2 2.7 0.9 1.1 0.675 3.648 450.6 80.31 Ukraine UKR 255.9 23.2 6,023 546 16.8 178.0 29.8 71.1 6.4 1.0 0.2 0.6 2.410 26.597 616.6 42.49 United Kingdom GBR 670.3 498.3 10,150 7,545 137.5 299.9 412.6 119.8 89.0 2.7 3.8 0.9 0.577 0.776 386.7 66.04 Total (46) ECB 8,240.0 4,199.3 9,429 4,805 94.3 278.6 262.7 111.3 56.7 33.8 31.9 12.1 n.a. n.a n.a. 873.93 Latin America and the Caribbean Anguilla AIA 0.1 0.1 8,210 3,821 86.1 242.6 208.9 96.9 45.1 0.0 0.0 0.0 1.257 2.700 0.2 0.01 Antigua and Barbuda ATG 0.7 0.3 7,300 2,706 68.6 215.7 148.0 86.2 31.9 0.0 0.0 0.0 1.001 2.700 0.7 0.10 Argentina ARG 313.7 115.6 7,140 2,631 68.2 211.0 143.8 84.3 31.0 1.3 0.9 0.6 6.102 16.563 1,914.3 43.94 Aruba ABW 1.0 0.5 9,448 4,842 94.8 279.2 264.7 111.5 57.1 0.0 0.0 0.0 0.917 1.790 0.9 0.11 ICP 2017 results 39 Table 2.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 3.4 1.6 8,950 4,316 89.2 264.5 236.0 105.6 50.9 0.0 0.0 0.0 0.482 1.000 1.6 0.38 Barbados BRB 1.0 0.9 3,636 3,112 158.4 107.4 170.2 42.9 36.7 0.0 0.0 0.0 1.712 2.000 1.8 0.29 Belize BLZ 0.6 0.3 1,669 814 90.3 49.3 44.5 19.7 9.6 0.0 0.0 0.0 0.976 2.000 0.6 0.38 Bolivia BOL 15.3 6.3 1,364 566 76.8 40.3 31.0 16.1 6.7 0.1 0.0 0.2 2.891 6.960 44.1 11.19 Bonaired BON … … … … … … … … … … … … … 1.000 … 0.03 Brazil BRA 730.6 416.0 3,515 2,002 105.4 103.9 109.5 41.5 23.6 3.0 3.2 2.9 1.817 3.191 1,327.8 207.83 Cayman Islands CYM 0.5 0.5 8,288 7,551 168.6 244.9 412.9 97.8 89.1 0.0 0.0 0.0 0.759 0.833 0.4 0.06 Chile CHL 93.1 38.9 5,028 2,101 77.3 148.6 114.9 59.3 24.8 0.4 0.3 0.3 271.088 648.834 25,246.3 18.52 Colombia COL 203.1 46.5 4,121 943 42.3 121.8 51.5 48.6 11.1 0.8 0.4 0.7 675.127 2,951.327 137,133.0 49.29 Costa Rica CRI 23.7 9.9 4,790 2,012 77.7 141.5 110.0 56.5 23.7 0.1 0.1 0.1 238.378 567.513 5,645.7 4.94 Curaçao CUW 1.0 0.5 6,412 3,301 95.3 189.5 180.5 75.7 39.0 0.0 0.0 0.0 0.922 1.790 1.0 0.16 Dominica DMA 0.2 0.1 3,004 1,263 77.8 88.8 69.1 35.5 14.9 0.0 0.0 0.0 1.136 2.700 0.2 0.07 Dominican Republic DOM 35.4 8.8 3,364 832 45.8 99.4 45.5 39.7 9.8 0.1 0.1 0.1 11.763 47.537 416.0 10.51 Ecuador ECU 36.7 15.2 2,186 905 76.6 64.6 49.5 25.8 10.7 0.2 0.1 0.2 0.414 1.000 15.2 16.79 El Salvador SLV 12.6 4.1 1,973 635 59.5 58.3 34.7 23.3 7.5 0.1 0.0 0.1 0.322 1.000 4.1 6.39 Grenada GRD 0.3 0.1 2,988 1,185 73.4 88.3 64.8 35.3 14.0 0.0 0.0 0.0 1.071 2.700 0.4 0.11 Guyana GUY 2.5 0.7 3,232 877 50.2 95.5 47.9 38.1 10.3 0.0 0.0 0.0 57.542 212.190 144.2 0.78 Haiti HTI 3.4 1.0 307 88 53.4 9.1 4.8 3.6 1.0 0.0 0.0 0.2 18.375 63.687 61.9 10.98 Honduras HND 7.2 3.1 766 330 79.7 22.6 18.0 9.0 3.9 0.0 0.0 0.1 10.160 23.588 73.4 9.43 Jamaica JAM 5.9 2.0 2,012 682 62.7 59.5 37.3 23.7 8.0 0.0 0.0 0.0 43.352 127.965 254.8 2.92 Mexico MEX 556.2 134.6 4,508 1,091 44.8 133.2 59.7 53.2 12.9 2.3 1.0 1.7 4.581 18.927 2,548.0 123.36 Montserrat MSR 0.1 0.0 18,728 6,511 64.3 553.4 356.0 221.0 76.8 0.0 0.0 0.0 0.939 2.700 0.1 0.00 Nicaragua NIC 10.7 2.0 1,669 319 35.3 49.3 17.4 19.7 3.8 0.0 0.0 0.1 5.739 30.051 61.1 6.38 Panama PAN 22.5 6.9 5,481 1,673 56.5 162.0 91.5 64.7 19.7 0.1 0.1 0.1 0.305 1.000 6.9 4.11 Paraguay PRY 13.7 4.3 1,988 621 57.8 58.8 33.9 23.5 7.3 0.1 0.0 0.1 1,736.632 5,562.276 23,712.2 6.87 Peru PER 77.2 27.9 2,454 887 66.9 72.5 48.5 29.0 10.5 0.3 0.2 0.4 1.178 3.260 90.9 31.44 Sint Maarten SXM 0.4 0.2 9,252 4,812 96.2 273.4 263.1 109.2 56.8 0.0 0.0 0.0 0.931 1.790 0.4 0.04 St. Kitts and Nevis KNA 0.5 0.2 9,504 3,104 60.4 280.8 169.7 112.2 36.6 0.0 0.0 0.0 0.882 2.700 0.4 0.05 St. Lucia LCA 0.9 0.4 4,803 2,213 85.2 141.9 121.0 56.7 26.1 0.0 0.0 0.0 1.244 2.700 1.1 0.18 St. Vincent and the VCT 0.5 0.2 4,163 1,513 67.2 123.0 82.7 49.1 17.9 0.0 0.0 0.0 0.981 2.700 0.4 0.11 Grenadines Suriname SUR 3.2 0.5 5,696 947 30.8 168.3 51.8 67.2 11.2 0.0 0.0 0.0 1.255 7.550 4.1 0.57 Trinidad and Tobago TTO 6.5 3.1 4,678 2,238 88.5 138.2 122.4 55.2 26.4 0.0 0.0 0.0 3.243 6.780 21.0 1.38 Turks and Caicos Islands TCA 0.3 0.2 8,646 5,723 122.5 255.5 312.9 102.0 67.5 0.0 0.0 0.0 0.662 1.000 0.2 0.04 Uruguay URY 15.1 8.7 4,396 2,518 106.0 129.9 137.7 51.9 29.7 0.1 0.1 0.0 16.425 28.676 248.1 3.44 Virgin Islands, British VGB 0.1 0.1 3,401 3,701 201.4 100.5 202.4 40.1 43.7 0.0 0.0 0.0 1.088 1.000 0.1 0.03 Total (39) LCB 2,199.9 862.2 3,838 1,504 72.5 113.4 82.2 45.3 17.8 9.0 6.5 8.0 n.a. n.a n.a. 573.20 40    Purchasing Power Parities and the Size of World Economies Table 2.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 173.7 31.9 4,197 771 34.0 124.0 42.1 49.5 9.1 0.7 0.2 0.6 20.381 110.973 3,540.4 41.39 Bahrain BHR 17.3 5.9 11,532 3,923 62.9 340.8 214.5 136.1 46.3 0.1 0.0 0.0 0.128 0.376 2.2 1.50 Djibouti DJI 0.8 0.4 846 392 85.6 25.0 21.4 10.0 4.6 0.0 0.0 0.0 82.209 177.720 65.7 0.94 Egypt, Arab Rep. EGY 182.1 20.7 1,921 218 21.0 56.8 11.9 22.7 2.6 0.7 0.2 1.3 2.024 17.847 368.6 94.80 Iran, Islamic Rep. IRN 371.8 74.3 4,586 917 37.0 135.5 50.1 54.1 10.8 1.5 0.6 1.1 6,641.413 33,226.298 2,469,173.8 81.07 Iraq IRQ 75.7 28.8 2,039 775 70.3 60.3 42.4 24.1 9.1 0.3 0.2 0.5 477.203 1,256.000 36,143.2 37.14 Israel ISR 93.9 80.1 10,779 9,198 157.9 318.5 502.9 127.2 108.6 0.4 0.6 0.1 3.072 3.600 288.4 8.71 Jordan JOR 25.4 6.2 2,523 612 44.9 74.6 33.5 29.8 7.2 0.1 0.0 0.1 0.172 0.708 4.4 10.05 Kuwait KWT 58.6 30.0 14,356 7,360 94.9 424.2 402.4 169.4 86.9 0.2 0.2 0.1 0.156 0.303 9.1 4.08 Malta MLT 4.0 2.0 8,616 4,189 90.0 254.6 229.1 101.7 49.4 0.0 0.0 0.0 0.430 0.885 1.7 0.47 Morocco MAR 61.0 20.8 1,751 598 63.2 51.7 32.7 20.7 7.1 0.3 0.2 0.5 3.308 9.691 201.8 34.85 Oman OMN 42.0 19.8 9,205 4,341 87.2 272.0 237.3 108.6 51.2 0.2 0.2 0.1 0.181 0.385 7.6 4.56 Qatar QAT 49.8 28.3 18,286 10,392 105.2 540.4 568.3 215.8 122.7 0.2 0.2 0.0 2.074 3.650 103.3 2.72 Saudi Arabia SAU 500.6 166.4 15,351 5,101 61.5 453.6 278.9 181.2 60.2 2.1 1.3 0.5 1.246 3.750 623.9 32.61 Tunisia TUN 34.5 8.3 3,016 725 44.5 89.1 39.7 35.6 8.6 0.1 0.1 0.2 0.582 2.419 20.1 11.43 United Arab Emirates ARE 103.7 52.6 11,147 5,653 93.8 329.4 309.1 131.6 66.7 0.4 0.4 0.1 1.862 3.673 193.2 9.30 West Bank and Gaza PSE 10.2 3.8 2,296 855 68.9 67.9 46.8 27.1 10.1 0.0 0.0 0.1 1.341 3.600 13.7 4.45 Total (17) MEB 1,805.2 580.2 4,749 1,526 59.5 140.4 83.5 56.1 18.0 7.4 4.4 5.3 n.a. n.a n.a. 380.10 North America Bermuda BMU 0.9 1.0 14,002 15,815 209.0 413.8 864.8 165.3 186.7 0.0 0.0 0.0 1.130 1.000 1.0 0.06 Canada CAN 456.1 354.3 12,481 9,695 143.7 368.8 530.1 147.3 114.4 1.9 2.7 0.5 1.008 1.298 459.7 36.54 United States USA 2,757.2 2,757.2 8,473 8,473 185.0 250.4 463.3 100.0 100.0 11.3 20.9 4.5 1.000 1.000 2,757.2 325.41 Total (3) NAB 3,214.2 3,112.5 8,879 8,598 179.2 262.4 470.1 104.8 101.5 13.2 23.6 5.0 n.a. n.a n.a. 362.01 South Asia Bangladesh BGD 57.2 16.3 354 100 52.6 10.4 5.5 4.2 1.2 0.2 0.1 2.2 22.859 80.438 1,307.6 161.80 Bhutan BTN 3.0 0.4 4,135 571 25.6 122.2 31.2 48.8 6.7 0.0 0.0 0.0 8.999 65.122 27.1 0.73 India IND 775.6 275.0 592 210 65.6 17.5 11.5 7.0 2.5 3.2 2.1 18.2 23.094 65.122 17,911.5 1,309.20 Maldives MDV 2.1 0.7 4,352 1,517 64.5 128.6 83.0 51.4 17.9 0.0 0.0 0.0 5.365 15.387 11.5 0.49 Nepal NPL 10.5 2.8 366 98 49.7 10.8 5.4 4.3 1.2 0.0 0.0 0.4 28.085 104.512 296.3 28.83 Pakistan PAK 130.7 36.3 656 182 51.4 19.4 10.0 7.7 2.2 0.5 0.3 2.8 29.283 105.455 3,826.9 199.11 Sri Lanka LKA 62.4 7.4 2,909 346 22.0 86.0 18.9 34.3 4.1 0.3 0.1 0.3 18.124 152.446 1,130.8 21.44 Total (7) SAB 1,041.5 339.0 605 197 60.2 17.9 10.8 7.1 2.3 4.3 2.6 23.9 n.a. n.a n.a. 1,721.60 Sub-Saharan Africa Angola AGO 62.1 15.8 2,083 530 47.1 61.6 29.0 24.6 6.3 0.3 0.1 0.4 42.195 165.916 2,621.1 29.82 Benin BEN 7.0 1.6 630 143 42.1 18.6 7.8 7.4 1.7 0.0 0.0 0.2 132.363 582.075 932.3 11.18 Botswana BWA 10.9 3.2 4,945 1,453 54.4 146.1 79.5 58.4 17.2 0.0 0.0 0.0 3.041 10.347 33.2 2.21 ICP 2017 results 41 Table 2.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 10.0 2.7 521 143 50.7 15.4 7.8 6.2 1.7 0.0 0.0 0.3 159.363 582.075 1,595.0 19.19 Burundi BDI 2.4 0.6 218 53 45.2 6.4 2.9 2.6 0.6 0.0 0.0 0.2 422.575 1,729.055 995.4 10.83 Cabo Verde CPV 1.2 0.4 2,262 666 54.5 66.8 36.4 26.7 7.9 0.0 0.0 0.0 28.812 97.799 35.0 0.54 Cameroon CMR 16.5 3.9 671 158 43.7 19.8 8.7 7.9 1.9 0.1 0.0 0.3 137.467 582.075 2,264.4 24.57 Central African Republic CAF 1.0 0.3 221 56 47.0 6.5 3.1 2.6 0.7 0.0 0.0 0.1 147.882 582.075 149.9 4.60 Chad TCD 3.3 1.0 217 69 58.5 6.4 3.8 2.6 0.8 0.0 0.0 0.2 184.106 582.075 600.7 15.02 Comoros COM 0.7 0.1 821 141 31.9 24.3 7.7 9.7 1.7 0.0 0.0 0.0 75.195 436.571 50.2 0.81 Congo, Dem. Rep. COD 18.2 5.6 223 69 57.3 6.6 3.8 2.6 0.8 0.1 0.0 1.1 453.425 1,464.418 8,235.3 81.40 Congo, Rep. COG 6.3 1.6 1,242 321 47.9 36.7 17.6 14.7 3.8 0.0 0.0 0.1 150.549 582.075 955.7 5.11 Côte d’Ivoire CIV 15.6 5.5 640 224 64.6 18.9 12.2 7.6 2.6 0.1 0.0 0.3 203.341 582.075 3,181.2 24.44 Equatorial Guinea GNQ 17.9 3.1 14,200 2,479 32.3 419.6 135.5 167.6 29.3 0.1 0.0 0.0 101.603 582.075 1,820.7 1.26 Eswatini SWZ 3.2 1.1 2,853 970 62.9 84.3 53.0 33.7 11.4 0.0 0.0 0.0 4.534 13.334 14.6 1.12 Ethiopia ETH 36.3 8.3 341 78 42.4 10.1 4.3 4.0 0.9 0.1 0.1 1.5 5.474 23.866 198.9 106.40 Gabon GAB 12.3 2.8 5,959 1,376 42.7 176.1 75.2 70.3 16.2 0.1 0.0 0.0 134.408 582.075 1,653.8 2.06 Gambia, The GMB 0.6 0.1 289 58 37.3 8.5 3.2 3.4 0.7 0.0 0.0 0.0 9.404 46.608 6.0 2.21 Ghana GHA 19.0 4.6 651 157 44.5 19.2 8.6 7.7 1.8 0.1 0.0 0.4 1.047 4.351 19.8 29.12 Guinea GIN 8.9 1.8 735 146 36.7 21.7 8.0 8.7 1.7 0.0 0.0 0.2 1,810.683 9,125.743 16,066.0 12.07 Guinea-Bissau GNB 1.2 0.2 634 137 39.9 18.7 7.5 7.5 1.6 0.0 0.0 0.0 125.408 582.075 145.3 1.83 Kenya KEN 59.6 16.1 1,186 321 50.1 35.1 17.6 14.0 3.8 0.2 0.1 0.7 28.023 103.411 1,669.3 50.22 Lesotho LSO 2.6 0.9 1,222 418 63.3 36.1 22.9 14.4 4.9 0.0 0.0 0.0 4.565 13.334 11.7 2.09 Liberia LBR 1.9 0.7 407 140 63.7 12.0 7.7 4.8 1.7 0.0 0.0 0.1 38.827 112.707 74.2 4.70 Madagascar MDG 9.5 2.1 370 81 40.6 10.9 4.4 4.4 1.0 0.0 0.0 0.4 683.217 3,116.110 6,463.9 25.57 Malawi MWI 2.3 0.6 132 34 47.8 3.9 1.9 1.6 0.4 0.0 0.0 0.2 188.730 730.273 439.4 17.67 Mali MLI 8.1 2.3 439 127 53.4 13.0 6.9 5.2 1.5 0.0 0.0 0.3 168.091 582.075 1,365.4 18.51 Mauritania MRT 6.3 1.1 1,464 255 32.2 43.3 13.9 17.3 3.0 0.0 0.0 0.1 62.288 357.493 390.5 4.28 Mauritius MUS 6.8 1.9 5,383 1,512 52.0 159.1 82.7 63.5 17.9 0.0 0.0 0.0 9.689 34.481 65.9 1.26 Mozambique MOZ 11.8 3.6 412 125 56.1 12.2 6.8 4.9 1.5 0.0 0.0 0.4 19.286 63.584 227.8 28.65 Namibia NAM 8.0 3.2 3,330 1,334 74.1 98.4 72.9 39.3 15.7 0.0 0.0 0.0 5.332 13.313 42.7 2.40 Niger NER 3.5 1.3 162 62 70.5 4.8 3.4 1.9 0.7 0.0 0.0 0.3 221.810 582.075 776.9 21.60 Nigeria NGA 81.0 17.4 425 91 39.7 12.5 5.0 5.0 1.1 0.3 0.1 2.6 65.570 305.790 5,313.5 190.87 Rwanda RWA 4.2 1.4 350 115 60.9 10.3 6.3 4.1 1.4 0.0 0.0 0.2 273.795 831.531 1,146.8 11.98 São Tomé and Príncipe STP 0.2 0.1 1,134 243 39.6 33.5 13.3 13.4 2.9 0.0 0.0 0.0 4.658 21.741 1.1 0.21 Senegal SEN 8.8 2.9 573 187 60.5 16.9 10.2 6.8 2.2 0.0 0.0 0.2 190.274 582.075 1,681.4 15.42 Seychelles SYC 1.1 0.3 11,045 3,280 55.0 326.4 179.4 130.4 38.7 0.0 0.0 0.0 4.053 13.648 4.3 0.10 Sierra Leone SLE 1.8 0.4 240 52 40.1 7.1 2.8 2.8 0.6 0.0 0.0 0.1 1,600.765 7,384.432 2,874.4 7.49 South Africa ZAF 207.4 72.6 3,639 1,273 64.7 107.5 69.6 42.9 15.0 0.9 0.6 0.8 4.666 13.334 967.9 57.01 Sudan (AFR) SDN 34.5 2.8 846 68 14.8 25.0 3.7 10.0 0.8 0.1 0.0 0.6 1.615 20.130 55.7 40.78 42    Purchasing Power Parities and the Size of World Economies Table 2.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 18.5 7.1 338 130 71.2 10.0 7.1 4.0 1.5 0.1 0.1 0.8 857.419 2,228.858 15,859.2 54.66 Togo TGO 3.4 0.9 442 112 46.7 13.1 6.1 5.2 1.3 0.0 0.0 0.1 146.888 582.075 499.7 7.70 Uganda UGA 13.2 2.8 322 68 39.3 9.5 3.7 3.8 0.8 0.1 0.0 0.6 767.411 3,611.224 10,166.4 41.17 Zambia ZMB 8.7 2.7 518 159 56.7 15.3 8.7 6.1 1.9 0.0 0.0 0.2 2.917 9.520 25.5 16.85 Zimbabwe ZWE 11.9 4.8 834 334 74.2 24.6 18.3 9.8 3.9 0.0 0.0 0.2 0.401 1.000 4.8 14.24 Total (45) SSB 769.8 214.2 754 210 51.5 22.3 11.5 8.9 2.5 3.2 1.6 14.2 n.a. n.a n.a. 1,021.22 World (176) WLD 24,376.5 13,174.1 3,384 1,829 100.0 100.0 100.0 39.9 21.6 100.0 100.0 100.0 n.a. n.a. n.a. 7,203.60 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either the Latin America and the Caribbean or the world totals. ICP 2017 results 43 Table 2.5  Gross fixed capital formation (GFCF): ICP 2017 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 285.1 335.1 11,587 13,621 169.5 289.4 490.5 94.4 110.9 1.0 1.7 0.3 1.534 1.305 437.2 24.60 Brunei Darussalam BRN 9.1 5.0 21,241 11,597 78.7 530.6 417.6 173.0 94.5 0.0 0.0 0.0 0.754 1.381 6.9 0.43 Cambodia KHM 5.7 2.4 360 151 60.5 9.0 5.4 2.9 1.2 0.0 0.0 0.2 1,699.937 4,050.580 9,703.4 15.85 China CHN 7,625.8 5,204.0 5,500 3,754 98.4 137.4 135.2 44.8 30.6 26.4 26.0 19.2 4.612 6.759 35,172.3 1,386.40 Fiji FJI 1.9 1.0 2,207 1,086 70.9 55.1 39.1 18.0 8.8 0.0 0.0 0.0 1.017 2.067 2.0 0.88 Hong Kong SAR, China HKG 92.6 73.9 12,529 9,999 115.0 313.0 360.1 102.0 81.4 0.3 0.4 0.1 6.219 7.793 576.0 7.39 Indonesia IDN 846.3 326.6 3,232 1,247 55.6 80.7 44.9 26.3 10.2 2.9 1.6 3.6 5,164.131 13,380.872 4,370,574.8 261.89 Japan JPN 1,156.5 1,158.4 9,128 9,142 144.4 228.0 329.2 74.3 74.5 4.0 5.8 1.8 112.342 112.166 129,927.9 126.71 Korea, Rep. KOR 699.2 511.7 13,613 9,963 105.5 340.1 358.8 110.9 81.1 2.4 2.6 0.7 827.318 1,130.425 578,456.9 51.36 Lao PDR LAO 13.4 5.6 1,936 815 60.7 48.4 29.4 15.8 6.6 0.0 0.0 0.1 3,517.220 8,351.526 46,996.3 6.90 Malaysia MYS 190.7 79.4 5,955 2,480 60.0 148.8 89.3 48.5 20.2 0.7 0.4 0.4 1.791 4.300 341.5 32.02 Mongolia MNG 6.6 2.8 2,101 894 61.4 52.5 32.2 17.1 7.3 0.0 0.0 0.0 1,038.379 2,439.777 6,869.3 3.15 Myanmar MMR 60.0 19.5 1,130 367 46.8 28.2 13.2 9.2 3.0 0.2 0.1 0.7 442.034 1,360.359 26,540.2 53.15 New Zealand NZL 39.1 46.0 8,098 9,522 169.5 202.3 342.9 66.0 77.6 0.1 0.2 0.1 1.655 1.407 64.8 4.83 Philippines PHL 165.3 78.4 1,576 748 68.4 39.4 26.9 12.8 6.1 0.6 0.4 1.5 23.916 50.404 3,953.6 104.92 Singapore SGP 136.7 89.3 24,360 15,920 94.2 608.5 573.3 198.4 129.7 0.5 0.4 0.1 0.902 1.381 123.4 5.61 Taiwan, China TWN 197.0 117.7 8,360 4,998 86.2 208.8 180.0 68.1 40.7 0.7 0.6 0.3 18.199 30.442 3,584.4 23.56 Thailand THA 241.2 103.4 3,565 1,528 61.8 89.1 55.0 29.0 12.4 0.8 0.5 0.9 14.544 33.940 3,507.9 67.65 Vietnam VNM 127.8 53.2 1,356 565 60.0 33.9 20.3 11.0 4.6 0.4 0.3 1.3 9,313.698 22,370.087 1,190,474.0 94.24 Total (19) EAB 11,900.1 8,213.5 5,239 3,616 99.5 130.9 130.2 42.7 29.5 41.3 41.1 31.5 n.a. n.a n.a. 2,271.55 Europe and Central Asia Albania ALB 7.7 3.2 2,678 1,115 60.0 66.9 40.2 21.8 9.1 0.0 0.0 0.0 49.444 118.748 380.6 2.87 Armenia ARM 3.4 2.0 1,138 680 86.1 28.4 24.5 9.3 5.5 0.0 0.0 0.0 288.252 482.720 977.7 2.98 Austria AUT 127.3 98.4 14,473 11,191 111.5 361.5 403.0 117.9 91.1 0.4 0.5 0.1 0.684 0.885 87.1 8.80 Azerbaijan AZE 18.1 9.7 1,856 1,000 77.7 46.4 36.0 15.1 8.1 0.1 0.0 0.1 0.927 1.721 16.8 9.73 Belarus BLR 26.0 14.2 2,741 1,495 78.6 68.5 53.9 22.3 12.2 0.1 0.1 0.1 1.054 1.932 27.4 9.50 Belgium BEL 161.0 116.6 14,154 10,246 104.4 353.6 369.0 115.3 83.5 0.6 0.6 0.2 0.641 0.885 103.2 11.38 Bosnia and Herzegovina BIH 7.2 3.3 2,155 974 65.2 53.8 35.1 17.6 7.9 0.0 0.0 0.0 0.783 1.731 5.7 3.35 Bulgaria BGR 23.4 10.9 3,304 1,534 66.9 82.5 55.2 26.9 12.5 0.1 0.1 0.1 0.804 1.731 18.8 7.08 Croatia HRV 22.8 11.2 5,529 2,704 70.5 138.1 97.4 45.0 22.0 0.1 0.1 0.1 3.231 6.607 73.8 4.13 Cyprus CYP 8.1 4.8 9,384 5,561 85.4 234.4 200.2 76.4 45.3 0.0 0.0 0.0 0.525 0.885 4.2 0.86 Czech Republic CZE 93.9 53.7 8,864 5,067 82.4 221.4 182.4 72.2 41.3 0.3 0.3 0.1 13.319 23.304 1,250.3 10.59 Denmark DNK 78.8 70.0 13,670 12,138 128.0 341.5 437.1 111.3 98.9 0.3 0.3 0.1 5.847 6.585 460.9 5.77 Estonia EST 10.7 6.7 8,155 5,066 89.5 203.7 182.4 66.4 41.3 0.0 0.0 0.0 0.550 0.885 5.9 1.32 Finland FIN 61.8 59.3 11,226 10,765 138.2 280.4 387.6 91.4 87.7 0.2 0.3 0.1 0.849 0.885 52.5 5.51 France FRA 711.4 582.8 10,608 8,691 118.1 265.0 313.0 86.4 70.8 2.5 2.9 0.9 0.725 0.885 515.9 67.06 44    Purchasing Power Parities and the Size of World Economies Table 2.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Georgia GEO 10.4 4.1 2,783 1,111 57.5 69.5 40.0 22.7 9.0 0.0 0.0 0.1 1.002 2.510 10.4 3.73 Germany DEU 886.7 752.3 10,728 9,101 122.3 268.0 327.7 87.4 74.1 3.1 3.8 1.1 0.751 0.885 665.9 82.66 Greece GRC 44.8 26.3 4,162 2,442 84.6 104.0 87.9 33.9 19.9 0.2 0.1 0.1 0.519 0.885 23.2 10.75 Hungary HUN 61.5 31.5 6,286 3,222 73.9 157.0 116.0 51.2 26.2 0.2 0.2 0.1 140.293 273.692 8,631.6 9.79 Iceland ISL 4.9 5.4 14,273 15,621 157.8 356.5 562.5 116.3 127.2 0.0 0.0 0.0 116.782 106.701 572.4 0.34 Ireland IRL 145.6 105.4 30,317 21,939 104.3 757.3 790.0 246.9 178.7 0.5 0.5 0.1 0.641 0.885 93.3 4.80 Italy ITA 554.5 341.0 9,160 5,633 88.6 228.8 202.8 74.6 45.9 1.9 1.7 0.8 0.544 0.885 301.8 60.54 Kazakhstan KAZ 60.5 36.2 3,352 2,007 86.3 83.7 72.3 27.3 16.3 0.2 0.2 0.3 195.136 326.000 11,798.9 18.04 Kyrgyz Republic KGZ 4.8 2.4 808 408 72.9 20.2 14.7 6.6 3.3 0.0 0.0 0.1 34.765 68.769 166.9 5.94 Latvia LVA 11.0 6.3 5,675 3,232 82.1 141.8 116.4 46.2 26.3 0.0 0.0 0.0 0.504 0.885 5.6 1.94 Lithuania LTU 16.7 9.5 5,898 3,375 82.5 147.3 121.5 48.0 27.5 0.1 0.0 0.0 0.507 0.885 8.4 2.83 Luxembourg LUX 15.8 12.0 26,410 20,170 110.1 659.7 726.3 215.1 164.3 0.1 0.1 0.0 0.676 0.885 10.7 0.60 Moldova MDA 3.7 2.2 1,035 608 84.6 25.8 21.9 8.4 4.9 0.0 0.0 0.0 10.857 18.490 39.9 3.55 Montenegro MNE 2.7 1.3 4,366 2,101 69.4 109.1 75.7 35.6 17.1 0.0 0.0 0.0 0.426 0.885 1.2 0.62 Netherlands NLD 215.4 168.0 12,576 9,804 112.4 314.1 353.0 102.4 79.9 0.7 0.8 0.2 0.690 0.885 148.7 17.13 North Macedonia MKD 6.2 2.6 2,984 1,229 59.4 74.5 44.3 24.3 10.0 0.0 0.0 0.0 22.460 54.505 139.0 2.07 Norway NOR 90.9 98.0 17,220 18,578 155.5 430.2 669.0 140.3 151.3 0.3 0.5 0.1 8.907 8.256 809.4 5.28 Poland POL 170.6 92.5 4,439 2,409 78.2 110.9 86.7 36.2 19.6 0.6 0.5 0.5 2.045 3.768 348.7 38.42 Portugal PRT 67.8 37.2 6,578 3,607 79.0 164.3 129.9 53.6 29.4 0.2 0.2 0.1 0.485 0.885 32.9 10.30 Romania ROU 107.5 47.5 5,487 2,426 63.7 137.1 87.4 44.7 19.8 0.4 0.2 0.3 1.788 4.044 192.2 19.59 Russian Federation RUS 584.4 340.8 3,979 2,321 84.1 99.4 83.6 32.4 18.9 2.0 1.7 2.0 34.025 58.343 19,882.6 146.84 Serbia SRB 15.8 7.9 2,252 1,119 71.6 56.2 40.3 18.3 9.1 0.1 0.0 0.1 53.368 107.406 843.7 7.02 Slovak Republic SVK 34.6 20.3 6,367 3,732 84.5 159.1 134.4 51.9 30.4 0.1 0.1 0.1 0.519 0.885 18.0 5.44 Slovenia SVN 15.6 8.9 7,551 4,306 82.2 188.6 155.1 61.5 35.1 0.1 0.0 0.0 0.505 0.885 7.9 2.07 Spain ESP 406.0 245.0 8,724 5,264 87.0 217.9 189.6 71.1 42.9 1.4 1.2 0.6 0.534 0.885 216.8 46.53 Sweden SWE 142.4 136.3 14,157 13,556 138.0 353.7 488.1 115.3 110.4 0.5 0.7 0.1 8.167 8.529 1,162.8 10.06 Switzerland CHE 168.7 166.2 19,955 19,662 142.0 498.5 708.0 162.5 160.1 0.6 0.8 0.1 0.970 0.984 163.5 8.45 Tajikistan TJK 3.8 1.9 428 216 72.6 10.7 7.8 3.5 1.8 0.0 0.0 0.1 4.307 8.550 16.3 8.84 Turkey TUR 648.9 256.5 8,080 3,193 57.0 201.8 115.0 65.8 26.0 2.3 1.3 1.1 1.442 3.648 935.7 80.31 Ukraine UKR 52.2 17.7 1,228 416 48.8 30.7 15.0 10.0 3.4 0.2 0.1 0.6 9.012 26.597 470.3 42.49 United Kingdom GBR 657.0 460.1 9,949 6,968 101.0 248.5 250.9 81.0 56.8 2.3 2.3 0.9 0.543 0.776 357.1 66.04 Total (46) ECB 6,572.8 4,489.8 7,521 5,138 98.5 187.9 185.0 61.3 41.8 22.8 22.4 12.1 n.a. n.a n.a. 873.93 Latin America and the Caribbean Anguilla AIA 0.1 0.1 4,460 4,127 133.4 111.4 148.6 36.3 33.6 0.0 0.0 0.0 2.498 2.700 0.2 0.01 Antigua and Barbuda ATG 0.5 0.5 5,375 5,028 134.8 134.3 181.1 43.8 41.0 0.0 0.0 0.0 2.526 2.700 1.3 0.10 Argentina ARG 117.2 96.7 2,668 2,201 118.9 66.7 79.2 21.7 17.9 0.4 0.5 0.6 13.660 16.563 1,601.5 43.94 Aruba ABW 0.7 0.6 7,110 5,635 114.2 177.6 202.9 57.9 45.9 0.0 0.0 0.0 1.419 1.790 1.1 0.11 ICP 2017 results 45 Table 2.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 3.9 3.2 10,088 8,425 120.4 252.0 303.4 82.2 68.6 0.0 0.0 0.0 0.835 1.000 3.2 0.38 Barbados BRB 0.9 0.8 2,999 2,760 132.7 74.9 99.4 24.4 22.5 0.0 0.0 0.0 1.841 2.000 1.6 0.29 Belize BLZ 0.5 0.3 1,228 914 107.2 30.7 32.9 10.0 7.4 0.0 0.0 0.0 1.488 2.000 0.7 0.38 Bolivia BOL 15.2 7.9 1,361 708 74.9 34.0 25.5 11.1 5.8 0.1 0.0 0.2 3.617 6.960 55.1 11.19 Bonaired BON … … … … … … … … … … … … … 1.000 … 0.03 Brazil BRA 473.0 300.4 2,276 1,446 91.6 56.8 52.1 18.5 11.8 1.6 1.5 2.9 2.027 3.191 958.8 207.83 Cayman Islands CYM 0.6 0.7 9,761 11,095 163.9 243.8 399.5 79.5 90.4 0.0 0.0 0.0 0.947 0.833 0.6 0.06 Chile CHL 99.1 58.6 5,352 3,161 85.1 133.7 113.8 43.6 25.7 0.3 0.3 0.3 383.232 648.834 37,993.7 18.52 Colombia COL 105.7 67.8 2,144 1,375 92.5 53.5 49.5 17.5 11.2 0.4 0.3 0.7 1,893.568 2,951.327 200,075.0 49.29 Costa Rica CRI 14.8 11.1 2,991 2,241 108.0 74.7 80.7 24.4 18.3 0.1 0.1 0.1 425.207 567.513 6,288.0 4.94 Curaçao CUW 1.0 0.9 6,420 5,409 121.5 160.4 194.8 52.3 44.1 0.0 0.0 0.0 1.508 1.790 1.6 0.16 Dominica DMA 0.1 0.1 1,521 1,207 114.4 38.0 43.4 12.4 9.8 0.0 0.0 0.0 2.142 2.700 0.2 0.07 Dominican Republic DOM 36.9 19.0 3,511 1,806 74.1 87.7 65.0 28.6 14.7 0.1 0.1 0.1 24.448 47.537 902.4 10.51 Ecuador ECU 47.9 26.5 2,852 1,579 79.8 71.2 56.8 23.2 12.9 0.2 0.1 0.2 0.553 1.000 26.5 16.79 El Salvador SLV 8.3 3.9 1,292 607 67.8 32.3 21.9 10.5 4.9 0.0 0.0 0.1 0.470 1.000 3.9 6.39 Grenada GRD 0.3 0.3 2,675 2,304 124.2 66.8 83.0 21.8 18.8 0.0 0.0 0.0 2.326 2.700 0.7 0.11 Guyana GUY 1.6 1.1 2,001 1,388 100.0 50.0 50.0 16.3 11.3 0.0 0.0 0.0 147.143 212.190 228.3 0.78 Haiti HTI 4.5 2.5 408 223 78.9 10.2 8.0 3.3 1.8 0.0 0.0 0.2 34.856 63.687 156.2 10.98 Honduras HND 11.7 5.4 1,242 575 66.7 31.0 20.7 10.1 4.7 0.0 0.0 0.1 10.922 23.588 127.9 9.43 Jamaica JAM 4.1 3.3 1,405 1,122 115.1 35.1 40.4 11.4 9.1 0.0 0.0 0.0 102.195 127.965 419.4 2.92 Mexico MEX 441.8 256.2 3,581 2,077 83.6 89.5 74.8 29.2 16.9 1.5 1.3 1.7 10.975 18.927 4,848.8 123.36 Montserrat MSR 0.0 0.0 2,035 1,873 132.7 50.8 67.5 16.6 15.3 0.0 0.0 0.0 2.485 2.700 0.0 0.00 Nicaragua NIC 6.5 3.6 1,019 564 79.7 25.5 20.3 8.3 4.6 0.0 0.0 0.1 16.621 30.051 108.2 6.38 Panama PAN 38.4 24.7 9,344 6,020 92.9 233.4 216.8 76.1 49.0 0.1 0.1 0.1 0.644 1.000 24.7 4.11 Paraguay PRY 11.7 7.6 1,702 1,101 93.2 42.5 39.6 13.9 9.0 0.0 0.0 0.1 3,598.079 5,562.276 42,054.5 6.87 Peru PER 73.6 43.5 2,340 1,383 85.2 58.4 49.8 19.1 11.3 0.3 0.2 0.4 1.927 3.260 141.8 31.44 Sint Maarten SXM 0.2 0.2 4,947 4,319 125.9 123.6 155.5 40.3 35.2 0.0 0.0 0.0 1.563 1.790 0.3 0.04 St. Kitts and Nevis KNA 0.4 0.3 6,953 5,599 116.1 173.7 201.6 56.6 45.6 0.0 0.0 0.0 2.174 2.700 0.8 0.05 St. Lucia LCA 0.3 0.2 1,501 1,376 132.1 37.5 49.6 12.2 11.2 0.0 0.0 0.0 2.475 2.700 0.7 0.18 St. Vincent and the VCT 0.3 0.2 2,757 1,851 96.8 68.9 66.7 22.5 15.1 0.0 0.0 0.0 1.813 2.700 0.5 0.11 Grenadines Suriname SUR 2.4 1.2 4,215 2,069 70.8 105.3 74.5 34.3 16.9 0.0 0.0 0.0 3.706 7.550 8.9 0.57 Trinidad and Tobago TTO 4.0 2.8 2,886 2,033 101.6 72.1 73.2 23.5 16.6 0.0 0.0 0.0 4.776 6.780 19.1 1.38 Turks and Caicos Islands TCA 0.2 0.2 4,958 4,273 124.2 123.8 153.9 40.4 34.8 0.0 0.0 0.0 0.862 1.000 0.2 0.04 Uruguay URY 10.8 9.8 3,143 2,854 130.9 78.5 102.8 25.6 23.2 0.0 0.0 0.0 26.039 28.676 281.2 3.44 Virgin Islands, British VGB 0.3 0.3 8,964 10,435 167.8 223.9 375.7 73.0 85.0 0.0 0.0 0.0 1.164 1.000 0.3 0.03 Total (39) LCB 1,539.2 962.2 2,685 1,679 90.1 67.1 60.4 21.9 13.7 5.3 4.8 8.0 n.a. n.a n.a. 573.20 46    Purchasing Power Parities and the Size of World Economies Table 2.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 118.3 69.3 2,858 1,674 84.5 71.4 60.3 23.3 13.6 0.4 0.3 0.6 65.019 110.973 7,691.1 41.39 Bahrain BHR 20.5 10.1 13,680 6,727 70.9 341.7 242.2 111.4 54.8 0.1 0.1 0.0 0.185 0.376 3.8 1.50 Djibouti DJI 1.5 1.0 1,559 1,096 101.3 38.9 39.5 12.7 8.9 0.0 0.0 0.0 124.927 177.720 183.9 0.94 Egypt, Arab Rep. EGY 97.4 34.7 1,028 366 51.3 25.7 13.2 8.4 3.0 0.3 0.2 1.3 6.349 17.847 618.6 94.80 Iran, Islamic Rep. IRN 187.4 91.0 2,311 1,122 70.0 57.7 40.4 18.8 9.1 0.6 0.5 1.1 16,132.669 33,226.298 3,022,951.0 81.07 Iraq IRQ 58.0 29.1 1,563 784 72.3 39.0 28.2 12.7 6.4 0.2 0.1 0.5 630.220 1,256.000 36,582.2 37.14 Israel ISR 79.0 73.4 9,073 8,433 134.0 226.6 303.7 73.9 68.7 0.3 0.4 0.1 3.346 3.600 264.4 8.71 Jordan JOR 16.2 8.1 1,607 802 71.9 40.2 28.9 13.1 6.5 0.1 0.0 0.1 0.353 0.708 5.7 10.05 Kuwait KWT 69.4 34.2 17,005 8,382 71.1 424.8 301.8 138.5 68.3 0.2 0.2 0.1 0.150 0.303 10.4 4.08 Malta MLT 4.1 2.6 8,657 5,590 93.1 216.3 201.3 70.5 45.5 0.0 0.0 0.0 0.572 0.885 2.3 0.47 Morocco MAR 76.8 31.4 2,202 902 59.0 55.0 32.5 17.9 7.3 0.3 0.2 0.5 3.968 9.691 304.6 34.85 Oman OMN 44.2 19.3 9,688 4,235 63.0 242.0 152.5 78.9 34.5 0.2 0.1 0.1 0.168 0.385 7.4 4.56 Qatar QAT 144.3 74.3 52,960 27,265 74.2 1323.0 981.8 431.3 222.1 0.5 0.4 0.0 1.879 3.650 271.1 2.72 Saudi Arabia SAU 395.4 167.2 12,123 5,126 61.0 302.8 184.6 98.7 41.8 1.4 0.8 0.5 1.586 3.750 626.9 32.61 Tunisia TUN 12.4 7.6 1,085 661 87.8 27.1 23.8 8.8 5.4 0.0 0.0 0.2 1.473 2.419 18.3 11.43 United Arab Emirates ARE 179.5 81.3 19,288 8,738 65.3 481.8 314.6 157.1 71.2 0.6 0.4 0.1 1.664 3.673 298.6 9.30 West Bank and Gaza PSE 5.3 3.3 1,190 730 88.4 29.7 26.3 9.7 5.9 0.0 0.0 0.1 2.207 3.600 11.7 4.45 Total (17) MEB 1,509.6 737.9 3,972 1,941 70.5 99.2 69.9 32.3 15.8 5.2 3.7 5.3 n.a. n.a n.a. 380.10 North America Bermuda BMU 0.6 0.9 9,770 13,765 203.1 244.1 495.7 79.6 112.1 0.0 0.0 0.0 1.409 1.000 0.9 0.06 Canada CAN 423.8 378.3 11,598 10,352 128.7 289.7 372.8 94.5 84.3 1.5 1.9 0.5 1.158 1.298 490.9 36.54 United States USA 3,995.3 3,995.3 12,278 12,278 144.2 306.7 442.1 100.0 100.0 13.9 20.0 4.5 1.000 1.000 3,995.3 325.41 Total (3) NAB 4,419.7 4,374.4 12,209 12,084 142.7 305.0 435.1 99.4 98.4 15.3 21.9 5.0 n.a. n.a n.a. 362.01 South Asia Bangladesh BGD 172.1 81.2 1,064 502 68.0 26.6 18.1 8.7 4.1 0.6 0.4 2.2 37.935 80.438 6,528.9 161.80 Bhutan BTN 3.0 1.3 4,128 1,784 62.3 103.1 64.2 33.6 14.5 0.0 0.0 0.0 28.145 65.122 84.5 0.73 India IND 1,965.9 724.9 1,502 554 53.2 37.5 19.9 12.2 4.5 6.8 3.6 18.2 24.012 65.122 47,205.0 1,309.20 Maldives MDV 4.0 2.0 8,116 4,140 73.5 202.7 149.1 66.1 33.7 0.0 0.0 0.0 7.849 15.387 31.3 0.49 Nepal NPL 18.7 7.9 648 276 61.3 16.2 9.9 5.3 2.2 0.1 0.0 0.4 44.434 104.512 830.7 28.83 Pakistan PAK 112.2 46.9 564 235 60.2 14.1 8.5 4.6 1.9 0.4 0.2 2.8 44.052 105.455 4,942.9 199.11 Sri Lanka LKA 52.6 23.0 2,455 1,071 62.9 61.3 38.6 20.0 8.7 0.2 0.1 0.3 66.518 152.446 3,502.1 21.44 Total (7) SAB 2,328.5 887.2 1,353 515 54.9 33.8 18.6 11.0 4.2 8.1 4.4 23.9 n.a. n.a n.a. 1,721.60 Sub-Saharan Africa Angola AGO 52.7 37.0 1,768 1,239 101.1 44.2 44.6 14.4 10.1 0.2 0.2 0.4 116.327 165.916 6,131.1 29.82 Benin BEN 4.3 2.5 383 220 83.1 9.6 7.9 3.1 1.8 0.0 0.0 0.2 335.364 582.075 1,433.7 11.18 Botswana BWA 9.0 5.1 4,078 2,297 81.2 101.9 82.7 33.2 18.7 0.0 0.0 0.0 5.828 10.347 52.4 2.21 ICP 2017 results 47 Table 2.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 6.0 3.2 314 168 76.9 7.9 6.0 2.6 1.4 0.0 0.0 0.3 310.379 582.075 1,872.8 19.19 Burundi BDI 0.7 0.4 68 41 87.3 1.7 1.5 0.6 0.3 0.0 0.0 0.2 1,047.500 1,729.055 776.9 10.83 Cabo Verde CPV 1.0 0.7 1,864 1,290 99.7 46.6 46.4 15.2 10.5 0.0 0.0 0.0 67.662 97.799 67.8 0.54 Cameroon CMR 13.8 8.0 563 327 83.6 14.1 11.8 4.6 2.7 0.0 0.0 0.3 337.463 582.075 4,670.1 24.57 Central African Republic CAF 0.7 0.4 147 85 83.6 3.7 3.1 1.2 0.7 0.0 0.0 0.1 337.388 582.075 227.4 4.60 Chad TCD 2.6 1.5 172 102 85.3 4.3 3.7 1.4 0.8 0.0 0.0 0.2 344.322 582.075 889.5 15.02 Comoros COM 0.4 0.2 463 267 83.1 11.6 9.6 3.8 2.2 0.0 0.0 0.0 251.528 436.571 94.8 0.81 Congo, Dem. Rep. COD 26.0 16.1 319 198 89.4 8.0 7.1 2.6 1.6 0.1 0.1 1.1 908.478 1464.418 23,608.6 81.40 Congo, Rep. COG 6.1 5.3 1,196 1,033 124.5 29.9 37.2 9.7 8.4 0.0 0.0 0.1 502.828 582.075 3,072.4 5.11 Côte d’Ivoire CIV 14.2 8.1 582 333 82.5 14.5 12.0 4.7 2.7 0.0 0.0 0.3 333.217 582.075 4,740.5 24.44 Equatorial Guinea GNQ 2.6 1.5 2,071 1,218 84.8 51.7 43.8 16.9 9.9 0.0 0.0 0.0 342.274 582.075 894.5 1.26 Eswatini SWZ 0.7 0.4 621 356 82.6 15.5 12.8 5.1 2.9 0.0 0.0 0.0 7.644 13.334 5.3 1.12 Ethiopia ETH 36.5 20.6 343 193 81.2 8.6 7.0 2.8 1.6 0.1 0.1 1.5 13.443 23.866 490.7 106.40 Gabon GAB 4.9 3.1 2,367 1,497 91.2 59.1 53.9 19.3 12.2 0.0 0.0 0.0 368.156 582.075 1,799.5 2.06 Gambia, The GMB 0.5 0.3 236 144 88.1 5.9 5.2 1.9 1.2 0.0 0.0 0.0 28.475 46.608 14.9 2.21 Ghana GHA 25.8 16.3 886 558 90.8 22.1 20.1 7.2 4.5 0.1 0.1 0.4 2.741 4.351 70.7 29.12 Guinea GIN 2.9 1.8 240 145 87.0 6.0 5.2 2.0 1.2 0.0 0.0 0.2 5,507.752 9,125.743 15,970.1 12.07 Guinea-Bissau GNB 0.1 0.1 80 46 82.4 2.0 1.6 0.7 0.4 0.0 0.0 0.0 332.806 582.075 48.7 1.83 Kenya KEN 33.5 16.4 666 326 70.5 16.6 11.7 5.4 2.7 0.1 0.1 0.7 50.590 103.411 1,692.3 50.22 Lesotho LSO 1.1 0.6 534 298 80.4 13.3 10.7 4.3 2.4 0.0 0.0 0.0 7.441 13.334 8.3 2.09 Liberia LBR 1.7 1.1 356 236 95.5 8.9 8.5 2.9 1.9 0.0 0.0 0.1 74.705 112.707 125.2 4.70 Madagascar MDG 3.9 2.3 154 92 85.7 3.9 3.3 1.3 0.7 0.0 0.0 0.4 1,851.792 3,116.110 7,313.8 25.57 Malawi MWI 1.3 0.8 74 47 90.4 1.9 1.7 0.6 0.4 0.0 0.0 0.2 458.113 730.273 600.0 17.67 Mali MLI 5.3 3.1 288 165 82.8 7.2 6.0 2.3 1.3 0.0 0.0 0.3 334.157 582.075 1,782.7 18.51 Mauritania MRT 4.8 2.1 1,116 493 63.7 27.9 17.8 9.1 4.0 0.0 0.0 0.1 157.964 357.493 754.8 4.28 Mauritius MUS 9.0 5.3 7,084 4,217 85.8 177.0 151.8 57.7 34.3 0.0 0.0 0.0 20.525 34.481 183.9 1.26 Mozambique MOZ 5.8 3.0 202 104 73.9 5.0 3.7 1.6 0.8 0.0 0.0 0.4 32.589 63.584 188.6 28.65 Namibia NAM 3.5 2.1 1,462 888 87.5 36.5 32.0 11.9 7.2 0.0 0.0 0.0 8.084 13.313 28.4 2.40 Niger NER 4.7 2.7 219 127 83.2 5.5 4.6 1.8 1.0 0.0 0.0 0.3 335.880 582.075 1,590.9 21.60 Nigeria NGA 82.9 55.3 435 290 96.1 10.9 10.4 3.5 2.4 0.3 0.3 2.6 203.839 305.790 16,908.1 190.87 Rwanda RWA 3.1 2.1 262 176 96.6 6.6 6.3 2.1 1.4 0.0 0.0 0.2 557.283 831.531 1,751.4 11.98 São Tomé and Príncipe STP 0.2 0.1 828 502 87.4 20.7 18.1 6.7 4.1 0.0 0.0 0.0 13.187 21.741 2.3 0.21 Senegal SEN 9.1 5.4 588 348 85.2 14.7 12.5 4.8 2.8 0.0 0.0 0.2 343.977 582.075 3,119.4 15.42 Seychelles SYC 0.9 0.6 8,918 5,895 95.3 222.8 212.3 72.6 48.0 0.0 0.0 0.0 9.022 13.648 7.8 0.10 Sierra Leone SLE 0.8 0.6 111 79 101.9 2.8 2.8 0.9 0.6 0.0 0.0 0.1 5,222.409 7,384.432 4,354.3 7.49 South Africa ZAF 112.1 61.4 1,966 1,076 78.9 49.1 38.8 16.0 8.8 0.4 0.3 0.8 7.299 13.334 818.1 57.01 Sudan SDN 13.2 4.5 325 111 49.1 8.1 4.0 2.6 0.9 0.0 0.0 0.6 6.858 20.130 90.9 40.78 48    Purchasing Power Parities and the Size of World Economies Table 2.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 22.5 15.5 411 283 99.1 10.3 10.2 3.4 2.3 0.1 0.1 0.8 1,532.051 2,228.858 34,444.3 54.66 Togo TGO 2.0 1.1 255 144 81.6 6.4 5.2 2.1 1.2 0.0 0.0 0.1 329.689 582.075 646.7 7.70 Uganda UGA 14.2 8.9 345 215 89.9 8.6 7.7 2.8 1.8 0.0 0.0 0.6 2,252.249 3,611.224 31,966.1 41.17 Zambia ZMB 16.7 9.9 992 588 85.4 24.8 21.2 8.1 4.8 0.1 0.0 0.2 5.643 9.520 94.4 16.85 Zimbabwe ZWE 3.3 2.1 232 149 92.6 5.8 5.4 1.9 1.2 0.0 0.0 0.2 0.643 1.000 2.1 14.24 Total (45) SSB 567.3 339.5 555 332 86.3 13.9 12.0 4.5 2.7 2.0 1.7 14.2 n.a. n.a n.a. 1,021.22 World (176) WLD 28,837.2 20,004.5 4,003 2,777 100.0 100.0 100.0 32.6 22.6 100.0 100.0 100.0 n.a. n.a. n.a. 7,203.60 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either the Latin America and the Caribbean or the world totals. ICP 2017 results 49 Table 2.6  Domestic absorption: ICP 2017 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 100.0 Expenditure level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 1,215.5 1,378.8 49,405 56,046 169.7 300.6 510.1 80.0 90.8 1.0 1.7 0.3 1.480 1.305 1,799.1 24.60 Brunei Darussalam BRN 22.1 10.4 51,467 24,293 70.6 313.1 221.1 83.3 39.3 0.0 0.0 0.0 0.652 1.381 14.4 0.43 Cambodia KHM 62.8 22.2 3,960 1,401 52.9 24.1 12.7 6.4 2.3 0.1 0.0 0.2 1,432.774 4,050.580 89,927.9 15.85 China CHN 19,117.4 11,932.7 13,789 8,607 93.4 83.9 78.3 22.3 13.9 16.1 15.1 19.2 4.219 6.759 80,650.5 1386.40 Fiji FJI 12.2 5.5 13,906 6,323 68.0 84.6 57.6 22.5 10.2 0.0 0.0 0.0 0.940 2.067 11.5 0.88 Hong Kong SAR, China HKG 434.3 338.0 58,753 45,724 116.4 357.4 416.2 95.1 74.0 0.4 0.4 0.1 6.065 7.793 2,633.9 7.39 Indonesia IDN 2,859.8 1,005.1 10,920 3,838 52.6 66.4 34.9 17.7 6.2 2.4 1.3 3.6 4,702.844 13,380.872 13,449,387.6 261.89 Japan JPN 5,085.3 4,814.5 40,134 37,998 141.6 244.2 345.9 65.0 61.5 4.3 6.1 1.8 106.194 112.166 540,025.7 126.71 Korea, Rep. KOR 1,993.0 1,546.8 38,804 30,116 116.1 236.1 274.1 62.8 48.8 1.7 2.0 0.7 877.332 1,130.425 1,748,548.6 51.36 Lao PDR LAO 51.5 17.3 7,461 2,505 50.2 45.4 22.8 12.1 4.1 0.0 0.0 0.1 2,804.389 8,351.526 144,385.0 6.90 Malaysia MYS 762.2 292.9 23,803 9,145 57.5 144.8 83.2 38.5 14.8 0.6 0.4 0.4 1.652 4.300 1,259.4 32.02 Mongolia MNG 34.4 11.2 10,937 3,543 48.5 66.5 32.2 17.7 5.7 0.0 0.0 0.0 790.306 2,439.777 27,216.7 3.15 Myanmar MMR 248.7 68.0 4,680 1,280 40.9 28.5 11.7 7.6 2.1 0.2 0.1 0.7 372.132 1,360.359 92,561.4 53.15 New Zealand NZL 190.1 198.4 39,339 41,065 156.2 239.3 373.8 63.7 66.5 0.2 0.3 0.1 1.469 1.407 279.3 4.83 Philippines PHL 890.2 344.5 8,485 3,283 57.9 51.6 29.9 13.7 5.3 0.8 0.4 1.5 19.506 50.404 17,364.5 104.92 Singapore SGP 367.5 253.1 65,480 45,099 103.0 398.4 410.5 106.0 73.0 0.3 0.3 0.1 0.951 1.381 349.5 5.61 Taiwan, China TWN 954.4 501.6 40,508 21,290 78.6 246.4 193.8 65.6 34.5 0.8 0.6 0.3 16.000 30.442 15,269.8 23.56 Thailand THA 1,040.2 392.3 15,375 5,799 56.4 93.5 52.8 24.9 9.4 0.9 0.5 0.9 12.801 33.940 13,315.0 67.65 Vietnam VNM 658.4 217.5 6,986 2,308 49.4 42.5 21.0 11.3 3.7 0.6 0.3 1.3 7,390.658 22,370.087 4,865,693.1 94.24 Total (19) EAB 35,999.9 23,351.0 15,848 10,280 97.0 96.4 93.6 25.7 16.6 30.4 29.5 31.5 n.a. n.a n.a. 2,271.55 Europe and Central Asia Albania ALB 42.5 15.0 14,795 5,230 52.9 90.0 47.6 24.0 8.5 0.0 0.0 0.0 41.980 118.748 1,784.7 2.87 Armenia ARM 39.3 12.9 13,191 4,340 49.2 80.3 39.5 21.4 7.0 0.0 0.0 0.0 158.817 482.720 6,241.8 2.98 Austria AUT 461.7 404.5 52,500 45,993 131.1 319.4 418.6 85.0 74.5 0.4 0.5 0.1 0.775 0.885 358.1 8.80 Azerbaijan AZE 133.7 38.1 13,738 3,917 42.7 83.6 35.7 22.2 6.3 0.1 0.0 0.1 0.491 1.721 65.6 9.73 Belarus BLR 175.2 54.6 18,450 5,751 46.6 112.2 52.3 29.9 9.3 0.1 0.1 0.1 0.602 1.932 105.5 9.50 Belgium BEL 566.9 497.2 49,837 43,712 131.2 303.2 397.9 80.7 70.8 0.5 0.6 0.2 0.776 0.885 440.1 11.38 Bosnia and Herzegovina BIH 53.2 21.1 15,877 6,291 59.3 96.6 57.3 25.7 10.2 0.0 0.0 0.0 0.686 1.731 36.5 3.35 Bulgaria BGR 149.8 56.5 21,164 7,989 56.5 128.8 72.7 34.3 12.9 0.1 0.1 0.1 0.654 1.731 97.9 7.08 Croatia HRV 111.0 55.1 26,883 13,346 74.3 163.6 121.5 43.5 21.6 0.1 0.1 0.1 3.280 6.607 364.2 4.13 Cyprus CYP 32.9 22.7 38,233 26,437 103.5 232.6 240.6 61.9 42.8 0.0 0.0 0.0 0.612 0.885 20.1 0.86 Czech Republic CZE 384.0 200.3 36,260 18,914 78.0 220.6 172.2 58.7 30.6 0.3 0.3 0.1 12.156 23.304 4,667.5 10.59 Denmark DNK 287.6 307.2 49,869 53,272 159.8 303.4 484.9 80.8 86.3 0.2 0.4 0.1 7.034 6.585 2,022.9 5.77 Estonia EST 43.1 25.7 32,745 19,542 89.3 199.2 177.9 53.0 31.6 0.0 0.0 0.0 0.528 0.885 22.8 1.32 Finland FIN 259.8 254.8 47,160 46,254 146.7 286.9 421.0 76.4 74.9 0.2 0.3 0.1 0.868 0.885 225.5 5.51 France FRA 3,022.0 2,620.2 45,062 39,070 129.7 274.2 355.6 73.0 63.3 2.6 3.3 0.9 0.767 0.885 2,319.4 67.06 50    Purchasing Power Parities and the Size of World Economies Table 2.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 100.0 Expenditure level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Georgia GEO 55.9 18.0 14,986 4,836 48.3 91.2 44.0 24.3 7.8 0.0 0.0 0.1 0.810 2.510 45.2 3.73 Germany DEU 4,028.7 3,405.5 48,739 41,201 126.5 296.5 375.0 78.9 66.7 3.4 4.3 1.1 0.748 0.885 3,014.5 82.66 Greece GRC 318.0 205.7 29,566 19,124 96.8 179.9 174.1 47.9 31.0 0.3 0.3 0.1 0.573 0.885 182.1 10.75 Hungary HUN 274.9 131.6 28,085 13,440 71.6 170.9 122.3 45.5 21.8 0.2 0.2 0.1 130.973 273.692 36,004.6 9.79 Iceland ISL 17.8 23.5 51,862 68,354 197.2 315.5 622.2 84.0 110.7 0.0 0.0 0.0 140.631 106.701 2,504.6 0.34 Ireland IRL 282.8 261.5 58,883 54,460 138.4 358.2 495.7 95.4 88.2 0.2 0.3 0.1 0.819 0.885 231.5 4.80 Italy ITA 2,451.5 1,903.4 40,496 31,442 116.2 246.4 286.2 65.6 50.9 2.1 2.4 0.8 0.687 0.885 1,684.8 60.54 Kazakhstan KAZ 423.7 153.5 23,489 8,511 54.2 142.9 77.5 38.0 13.8 0.4 0.2 0.3 118.115 326.000 50,044.8 18.04 Kyrgyz Republic KGZ 38.3 10.2 6,439 1,715 39.8 39.2 15.6 10.4 2.8 0.0 0.0 0.1 18.313 68.769 700.8 5.94 Latvia LVA 55.8 30.2 28,771 15,571 81.0 175.0 141.7 46.6 25.2 0.0 0.0 0.0 0.479 0.885 26.8 1.94 Lithuania LTU 94.9 46.6 33,555 16,481 73.5 204.1 150.0 54.3 26.7 0.1 0.1 0.0 0.435 0.885 41.3 2.83 Luxembourg LUX 40.4 41.6 67,728 69,708 154.0 412.0 634.5 109.7 112.9 0.0 0.1 0.0 0.911 0.885 36.8 0.60 Moldova MDA 37.9 11.9 10,678 3,365 47.1 65.0 30.6 17.3 5.4 0.0 0.0 0.0 5.827 18.490 220.8 3.55 Montenegro MNE 14.8 6.0 23,709 9,633 60.8 144.2 87.7 38.4 15.6 0.0 0.0 0.0 0.360 0.885 5.3 0.62 Netherlands NLD 829.9 744.2 48,444 43,442 134.2 294.7 395.4 78.4 70.3 0.7 0.9 0.2 0.794 0.885 658.8 17.13 North Macedonia MKD 36.6 12.9 17,622 6,223 52.8 107.2 56.6 28.5 10.1 0.0 0.0 0.0 19.250 54.505 703.7 2.07 Norway NOR 314.6 385.2 59,626 72,989 183.1 362.8 664.4 96.6 118.2 0.3 0.5 0.1 10.107 8.256 3,180.0 5.28 Poland POL 1,123.6 505.8 29,244 13,166 67.4 177.9 119.8 47.4 21.3 0.9 0.6 0.5 1.696 3.768 1,906.2 38.42 Portugal PRT 339.3 219.1 32,937 021,274 96.6 200.4 193.6 53.3 34.5 0.3 0.3 0.1 0.572 0.885 194.0 10.30 Romania ROU 554.6 216.6 28,307 11,057 58.4 172.2 100.6 45.8 17.9 0.5 0.3 0.3 1.580 4.044 876.1 19.59 Russian Federation RUS 3,688.5 1,494.3 25,119 10,176 60.6 152.8 92.6 40.7 16.5 3.1 1.9 2.0 23.635 58.343 87,180.0 146.84 Serbia SRB 124.2 47.2 17,693 6,720 56.8 107.6 61.2 28.7 10.9 0.1 0.1 0.1 40.795 107.406 5,067.7 7.02 Slovak Republic SVK 166.3 93.4 30,586 17,172 84.0 186.1 156.3 49.5 27.8 0.1 0.1 0.1 0.497 0.885 82.7 5.44 Slovenia SVN 69.7 44.3 33,716 21,424 95.1 205.1 195.0 54.6 34.7 0.1 0.1 0.0 0.562 0.885 39.2 2.07 Spain ESP 1,784.1 1,265.6 38,340 27,198 106.1 233.3 247.6 62.1 44.0 1.5 1.6 0.6 0.628 0.885 1,120.3 46.53 Sweden SWE 505.5 524.4 50,261 52,142 155.2 305.8 474.6 81.4 84.4 0.4 0.7 0.1 8.848 8.529 4,472.8 10.06 Switzerland CHE 488.1 608.6 57,753 72,002 186.5 351.4 655.4 93.5 116.6 0.4 0.8 0.1 1.227 0.984 598.9 8.45 Tajikistan TJK 32.5 9.0 3,675 1,014 41.3 22.4 9.2 6.0 1.6 0.0 0.0 0.1 2.359 8.550 76.6 8.84 Turkey TUR 2,379.4 891.1 29,627 11,096 56.0 180.2 101.0 48.0 18.0 2.0 1.1 1.1 1.366 3.648 3,251.0 80.31 Ukraine UKR 544.2 120.8 12,809 2,844 33.2 77.9 25.9 20.7 4.6 0.5 0.2 0.6 5.905 26.597 3,213.3 42.49 United Kingdom GBR 3,072.7 2,702.0 46,527 40,914 131.6 283.1 372.4 75.3 66.3 2.6 3.4 0.9 0.682 0.776 2,096.8 66.04 Total (46) ECB 29,951.7 20,719.8 34,273 23,709 103.5 208.5 215.8 55.5 38.4 25.3 26.2 12.1 n.a. n.a n.a. 873.93 Latin America and Caribbean Anguilla AIA 0.4 0.3 26,804 22,607 126.2 163.1 205.8 43.4 36.6 0.0 0.0 0.0 2.277 2.700 0.9 0.01 Antigua and Barbuda ATG 1.8 1.4 18,400 14,301 116.3 111.9 130.2 29.8 23.2 0.0 0.0 0.0 2.098 2.700 3.7 0.10 Argentina ARG 1,066.6 660.3 24,275 15,028 92.6 147.7 136.8 39.3 24.3 0.9 0.8 0.6 10.254 16.563 10,936.2 43.94 Aruba ABW 4.0 3.0 37,820 28,513 112.8 230.1 259.5 61.2 46.2 0.0 0.0 0.0 1.349 1.790 5.4 0.11 ICP 2017 results 51 Table 2.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 14.1 12.7 36,947 33,195 134.4 224.8 302.1 59.8 53.8 0.0 0.0 0.0 0.898 1.000 12.7 0.38 Barbados BRB 4.9 5.2 17,027 18,222 160.1 103.6 165.9 27.6 29.5 0.0 0.0 0.0 2.140 2.000 10.4 0.29 Belize BLZ 2.8 1.9 7,445 5,126 103.0 45.3 46.7 12.1 8.3 0.0 0.0 0.0 1.377 2.000 3.9 0.38 Bolivia BOL 98.6 39.8 8,813 3,556 60.4 53.6 32.4 14.3 5.8 0.1 0.1 0.2 2.809 6.960 277.1 11.19 d Bonaire BON … … … … … … … … … … … … … 1.000 … 0.03 Brazil BRA 2,991.1 2,048.0 14,392 9,854 102.4 87.6 89.7 23.3 16.0 2.5 2.6 2.9 2.185 3.191 6,536.0 207.83 Cayman Islands CYM 3.2 4.0 50,619 62,528 184.8 308.0 569.1 82.0 101.3 0.0 0.0 0.0 1.029 0.833 3.3 0.06 Chile CHL 432.1 273.9 23,330 14,788 94.8 141.9 134.6 37.8 23.9 0.4 0.3 0.3 411.271 648.834 177,722.7 18.52 Colombia COL 731.6 327.6 14,842 6,646 67.0 90.3 60.5 24.0 10.8 0.6 0.4 0.7 1,321.594 2,951.327 966,890.0 49.29 Costa Rica CRI 97.6 60.4 19,741 12,216 92.6 120.1 111.2 32.0 19.8 0.1 0.1 0.1 351.198 567.513 34,282.0 4.94 Curaçao CUW 4.9 3.8 30,552 23,408 114.6 185.9 213.1 49.5 37.9 0.0 0.0 0.0 1.371 1.790 6.8 0.16 Dominica DMA 0.9 0.6 12,840 8,356 97.4 78.1 76.1 20.8 13.5 0.0 0.0 0.0 1.757 2.700 1.6 0.07 Dominican Republic DOM 179.1 82.3 17,034 7,827 68.7 103.6 71.2 27.6 12.7 0.2 0.1 0.1 21.842 47.537 3,911.4 10.51 Ecuador ECU 195.5 105.1 11,644 6,260 80.4 70.8 57.0 18.9 10.1 0.2 0.1 0.2 0.538 1.000 105.1 16.79 El Salvador SLV 61.7 29.0 9,657 4,546 70.4 58.7 41.4 15.6 7.4 0.1 0.0 0.1 0.471 1.000 29.0 6.39 Grenada GRD 2.2 1.4 19,686 12,588 95.7 119.8 114.6 31.9 20.4 0.0 0.0 0.0 1.726 2.700 3.8 0.11 Guyana GUY 7.7 4.0 9,981 5,120 76.7 60.7 46.6 16.2 8.3 0.0 0.0 0.0 108.840 212.190 842.1 0.78 Haiti HTI 26.6 12.2 2,421 1,115 68.9 14.7 10.1 3.9 1.8 0.0 0.0 0.2 29.334 63.687 779.9 10.98 Honduras HND 59.1 26.5 6,263 2,813 67.2 38.1 25.6 10.1 4.6 0.0 0.0 0.1 10.594 23.588 625.7 9.43 Jamaica JAM 31.3 17.0 10,723 5,813 81.1 65.2 52.9 17.4 9.4 0.0 0.0 0.0 69.370 127.965 2,172.7 2.92 Mexico MEX 2,517.1 1,178.7 20,404 9,555 70.1 124.1 87.0 33.0 15.5 2.1 1.5 1.7 8.863 18.927 22,309.5 123.36 Montserrat MSR 0.1 0.1 26,641 18,292 102.7 162.1 166.5 43.1 29.6 0.0 0.0 0.0 1.854 2.700 0.2 0.00 Nicaragua NIC 42.2 15.7 6,611 2,463 55.8 40.2 22.4 10.7 4.0 0.0 0.0 0.1 11.199 30.051 472.7 6.38 Panama PAN 128.1 64.2 31,201 15,628 74.9 189.8 142.3 50.5 25.3 0.1 0.1 0.1 0.501 1.000 64.2 4.11 Paraguay PRY 82.4 37.8 11,996 5,504 68.6 73.0 50.1 19.4 8.9 0.1 0.0 0.1 2,552.236 5,562.276 210,244.3 6.87 Peru PER 383.6 207.0 12,199 6,582 80.7 74.2 59.9 19.8 10.7 0.3 0.3 0.4 1.759 3.260 674.7 31.44 Sint Maarten SXM 1.4 1.1 34,548 26,780 116.0 210.2 243.8 55.9 43.4 0.0 0.0 0.0 1.388 1.790 2.0 0.04 St. Kitts and Nevis KNA 1.4 1.1 27,849 21,100 113.4 169.4 192.1 45.1 34.2 0.0 0.0 0.0 2.046 2.700 3.0 0.05 St. Lucia LCA 1.7 1.2 9,306 6,853 110.2 56.6 62.4 15.1 11.1 0.0 0.0 0.0 1.988 2.700 3.3 0.18 St. Vincent and the VCT 1.7 1.0 15,135 9,132 90.3 92.1 83.1 24.5 14.8 0.0 0.0 0.0 1.629 2.700 2.7 0.11 Grenadines Suriname SUR 9.2 3.2 16,108 5,683 52.8 98.0 51.7 26.1 9.2 0.0 0.0 0.0 2.664 7.550 24.5 0.57 Trinidad and Tobago TTO 34.3 20.8 24,747 15,006 90.7 150.6 136.6 40.1 24.3 0.0 0.0 0.0 4.111 6.780 140.8 1.38 Turks and Caicos Islands TCA 0.7 0.8 19,920 20,733 155.7 121.2 188.7 32.3 33.6 0.0 0.0 0.0 1.041 1.000 0.8 0.04 Uruguay URY 70.6 57.7 20,548 16,786 122.2 125.0 152.8 33.3 27.2 0.1 0.1 0.0 23.426 28.676 1,654.3 3.44 Virgin Islands, British VGB 0.8 0.8 25,845 28,614 165.6 157.2 260.5 41.9 46.3 0.0 0.0 0.0 1.107 1.000 0.8 0.03 Total (39) LCB 9,293.0 5,311.7 16,213 9,267 85.5 98.6 84.3 26.3 15.0 7.8 6.7 8.0 n.a. n.a n.a. 573.20 52    Purchasing Power Parities and the Size of World Economies Table 2.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 100.0 Expenditure level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 519.8 185.7 12,558 4,488 53.5 76.4 40.8 20.3 7.3 0.4 0.2 0.6 39.654 110.973 20,611.5 41.39 Bahrain BHR 65.2 32.4 43,435 21,615 74.5 264.3 196.7 70.3 35.0 0.1 0.0 0.0 0.187 0.376 12.2 1.50 Djibouti DJI 5.5 3.2 5,852 3,403 87.0 35.6 31.0 9.5 5.5 0.0 0.0 0.0 103.348 177.720 571.0 0.94 Egypt, Arab Rep. EGY 1,318.3 259.6 13,906 2,739 29.5 84.6 24.9 22.5 4.4 1.1 0.3 1.3 3.515 17.847 4,633.2 94.80 Iran, Islamic Rep. IRN 1,267.1 498.6 15,629 6,150 58.9 95.1 56.0 25.3 10.0 1.1 0.6 1.1 13,074.531 33,226.298 16,566,404.5 81.07 Iraq IRQ 336.5 150.2 9,061 4,045 66.8 55.1 36.8 14.7 6.6 0.3 0.2 0.5 560.709 1,256.000 188,683.3 37.14 Israel ISR 332.0 349.1 38,119 40,087 157.3 231.9 364.9 61.7 64.9 0.3 0.4 0.1 3.785 3.600 1,256.8 8.71 Jordan JOR 116.7 49.7 11,610 4,939 63.6 70.6 45.0 18.8 8.0 0.1 0.1 0.1 0.301 0.708 35.2 10.05 Kuwait KWT 195.5 114.1 47,879 27,947 87.3 291.3 254.4 77.5 45.3 0.2 0.1 0.1 0.177 0.303 34.6 4.08 Malta MLT 15.6 10.1 33,216 21,470 96.7 202.1 195.4 53.8 34.8 0.0 0.0 0.0 0.572 0.885 8.9 0.47 Morocco MAR 288.5 120.2 8,276 3,449 62.3 50.4 31.4 13.4 5.6 0.2 0.2 0.5 4.038 9.691 1,164.9 34.85 Oman OMN 132.1 68.6 28,967 15,043 77.7 176.2 136.9 46.9 24.4 0.1 0.1 0.1 0.200 0.385 26.4 4.56 Qatar QAT 219.3 143.5 80,482 52,676 97.9 489.6 479.5 130.3 85.3 0.2 0.2 0.0 2.389 3.650 523.9 2.72 Saudi Arabia SAU 1,489.3 650.6 45,667 19,950 65.4 277.8 181.6 74.0 32.3 1.3 0.8 0.5 1.638 3.750 2,439.9 32.61 Tunisia TUN 132.7 44.8 11,609 3,922 50.5 70.6 35.7 18.8 6.4 0.1 0.1 0.2 0.817 2.419 108.5 11.43 United Arab Emirates ARE 453.5 284.4 48,736 30,571 93.8 296.5 278.3 78.9 49.5 0.4 0.4 0.1 2.304 3.673 1,044.6 9.30 West Bank and Gaza PSE 36.9 19.9 8,284 4,461 80.6 50.4 40.6 13.4 7.2 0.0 0.0 0.1 1.939 3.600 71.5 4.45 Total (17) MEB 6,924.4 2,984.9 18,217 7,853 64.5 110.8 71.5 29.5 12.7 5.8 3.8 5.3 n.a. n.a n.a. 380.10 North Africa Bermuda BMU 3.5 5.1 55,957 81,676 218.4 340.4 743.4 90.6 132.3 0.0 0.0 0.0 1.460 1.000 5.1 0.06 Canada CAN 1,815.3 1,687.1 49,681 46,170 139.0 302.3 420.2 80.5 74.8 1.5 2.1 0.5 1.206 1.298 2,189.4 36.54 United States USA 20,094.8 20,094.8 61,752 61,752 149.6 375.7 562.1 100.0 100.0 17.0 25.4 4.5 1.000 1.000 20,094.8 325.41 Total (3) NAB 21,913.6 21,787.0 60,533 60,183 148.7 368.3 547.8 98.0 97.5 18.5 27.5 5.0 n.a. n.a n.a. 362.01 South Asia Bangladesh BGD 755.1 281.2 4,667 1,738 55.7 28.4 15.8 7.6 2.8 0.6 0.4 2.2 29.957 80.438 22,620.8 161.80 Bhutan BTN 10.0 3.0 13,770 4,188 45.5 83.8 38.1 22.3 6.8 0.0 0.0 0.0 19.806 65.122 198.3 0.73 India IND 8,226.3 2,626.1 6,283 2,006 47.8 38.2 18.3 10.2 3.2 6.9 3.3 18.2 20.789 65.122 171,016.7 1309.20 Maldives MDV 9.0 4.8 18,247 9,732 79.8 111.0 88.6 29.5 15.8 0.0 0.0 0.0 8.206 15.387 73.6 0.49 Nepal NPL 106.9 33.4 3,709 1,159 46.8 22.6 10.6 6.0 1.9 0.1 0.0 0.4 32.668 104.512 3,493.5 28.83 Pakistan PAK 1,074.7 347.6 5,397 1,746 48.4 32.8 15.9 8.7 2.8 0.9 0.4 2.8 34.110 105.455 36,657.4 199.11 Sri Lanka LKA 285.8 93.6 13,328 4,367 49.0 81.1 39.7 21.6 7.1 0.2 0.1 0.3 49.946 152.446 14,274.6 21.44 Total (7) SAB 10,467.8 3,389.8 6,080 1,969 48.4 37.0 17.9 9.8 3.2 8.8 4.3 23.9 n.a. n.a n.a. 1,721.60 Sub-Saharan Africa Angola AGO 208.3 115.7 6,985 3,881 83.1 42.5 35.3 11.3 6.3 0.2 0.1 0.4 92.186 165.916 19,200.1 29.82 Benin BEN 28.9 11.0 2,590 983 56.8 15.8 8.9 4.2 1.6 0.0 0.0 0.2 220.967 582.075 6,394.9 11.18 Botswana BWA 36.0 16.4 16,304 7,438 68.3 99.2 67.7 26.4 12.0 0.0 0.0 0.0 4.720 10.347 169.7 2.21 ICP 2017 results 53 Table 2.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 36.2 13.2 1,888 689 54.6 11.5 6.3 3.1 1.1 0.0 0.0 0.3 212.365 582.075 7,696.2 19.19 Burundi BDI 9.9 3.8 919 354 57.7 5.6 3.2 1.5 0.6 0.0 0.0 0.2 666.758 1,729.055 6,632.4 10.83 Cabo Verde CPV 4.5 2.2 8,398 4,090 72.9 51.1 37.2 13.6 6.6 0.0 0.0 0.0 47.630 97.799 215.0 0.54 Cameroon CMR 90.0 36.2 3,665 1,475 60.2 22.3 13.4 5.9 2.4 0.1 0.0 0.3 234.290 582.075 21,094.7 24.57 Central African Republic CAF 5.3 2.6 1,162 563 72.5 7.1 5.1 1.9 0.9 0.0 0.0 0.1 282.192 582.075 1,507.5 4.60 Chad TCD 26.0 10.9 1,730 728 62.9 10.5 6.6 2.8 1.2 0.0 0.0 0.2 244.802 582.075 6,359.4 15.02 Comoros COM 2.9 1.3 3,601 1,570 65.2 21.9 14.3 5.8 2.5 0.0 0.0 0.0 190.290 436.571 557.8 0.81 Congo, Dem. Rep. COD 115.4 50.9 1,418 625 66.0 8.6 5.7 2.3 1.0 0.1 0.1 1.1 645.590 1,464.418 74,500.4 81.40 Congo, Rep. COG 22.9 11.8 4,489 2,313 77.1 27.3 21.1 7.3 3.7 0.0 0.0 0.1 299.907 582.075 6,880.4 5.11 Côte d’Ivoire CIV 85.1 37.2 3,481 1,521 65.4 21.2 13.8 5.6 2.5 0.1 0.0 0.3 254.355 582.075 21,640.1 24.44 Equatorial Guinea GNQ 24.2 10.2 19,199 8,053 62.8 116.8 73.3 31.1 13.0 0.0 0.0 0.0 244.161 582.075 5,915.8 1.26 Eswatini SWZ 11.0 5.1 9,759 4,517 69.3 59.4 41.1 15.8 7.3 0.0 0.0 0.0 6.172 13.334 67.7 1.12 Ethiopia ETH 200.9 73.6 1,888 692 54.8 11.5 6.3 3.1 1.1 0.2 0.1 1.5 8.741 23.866 1,756.4 106.40 Gabon GAB 23.8 11.4 11,543 5,523 71.6 70.2 50.3 18.7 8.9 0.0 0.0 0.0 278.524 582.075 6,638.4 2.06 Gambia, The GMB 5.0 1.7 2,278 775 50.9 13.9 7.1 3.7 1.3 0.0 0.0 0.0 15.849 46.608 79.9 2.21 Ghana GHA 149.5 60.9 5,133 2,092 61.0 31.2 19.0 8.3 3.4 0.1 0.1 0.4 1.773 4.351 265.0 29.12 Guinea GIN 34.7 12.4 2,877 1,028 53.5 17.5 9.4 4.7 1.7 0.0 0.0 0.2 3,262.076 9,125.743 113,237.6 12.07 Guinea-Bissau GNB 3.7 1.4 2,002 773 57.8 12.2 7.0 3.2 1.3 0.0 0.0 0.0 224.831 582.075 823.1 1.83 Kenya KEN 234.4 92.4 4,667 1,839 59.0 28.4 16.7 7.6 3.0 0.2 0.1 0.7 40.755 103.411 9,551.5 50.22 Lesotho LSO 8.8 3.7 4,186 1,752 62.6 25.5 15.9 6.8 2.8 0.0 0.0 0.0 5.580 13.334 48.9 2.09 Liberia LBR 7.6 3.5 1,610 739 68.7 9.8 6.7 2.6 1.2 0.0 0.0 0.1 51.726 112.707 391.6 4.70 Madagascar MDG 40.5 13.4 1,585 526 49.6 9.6 4.8 2.6 0.9 0.0 0.0 0.4 1,033.584 3,116.110 41,898.0 25.57 Malawi MWI 21.2 7.5 1,202 426 53.1 7.3 3.9 1.9 0.7 0.0 0.0 0.2 259.008 730.273 5,500.3 17.67 Mali MLI 47.4 17.9 2,562 965 56.4 15.6 8.8 4.1 1.6 0.0 0.0 0.3 219.235 582.075 10,396.9 18.51 Mauritania MRT 17.8 5.8 4,153 1,345 48.4 25.3 12.2 6.7 2.2 0.0 0.0 0.1 115.754 357.493 2,059.0 4.28 Mauritius MUS 35.0 17.0 27,685 13,430 72.6 168.4 122.2 44.8 21.7 0.0 0.0 0.0 16.727 34.481 585.6 1.26 Mozambique MOZ 46.7 17.4 1,629 608 55.8 9.9 5.5 2.6 1.0 0.0 0.0 0.4 23.717 63.584 1,106.7 28.65 Namibia NAM 28.3 14.7 11,760 6,112 77.8 71.5 55.6 19.0 9.9 0.0 0.0 0.0 6.919 13.313 195.5 2.40 Niger NER 21.3 9.4 985 437 66.4 6.0 4.0 1.6 0.7 0.0 0.0 0.3 258.494 582.075 5,499.4 21.60 Nigeria NGA 880.2 335.5 4,612 1,758 57.0 28.1 16.0 7.5 2.8 0.7 0.4 2.6 116.558 305.790 102,598.7 190.87 Rwanda RWA 24.6 9.8 2,055 816 59.4 12.5 7.4 3.3 1.3 0.0 0.0 0.2 330.139 831.531 8,129.6 11.98 São Tomé and Príncipe STP 1.0 0.5 4,979 2,269 68.2 30.3 20.7 8.1 3.7 0.0 0.0 0.0 9.909 21.741 10.2 0.21 Senegal SEN 56.0 23.8 3,629 1,545 63.7 22.1 14.1 5.9 2.5 0.0 0.0 0.2 247.845 582.075 13,869.7 15.42 Seychelles SYC 3.1 1.7 31,888 18,138 85.1 194.0 165.1 51.6 29.4 0.0 0.0 0.0 7.763 13.648 23.9 0.10 Sierra Leone SLE 14.6 4.7 1,950 625 47.9 11.9 5.7 3.2 1.0 0.0 0.0 0.1 2,365.205 7,384.432 34,542.3 7.49 South Africa ZAF 727.8 349.2 12,767 6,125 71.8 77.7 55.7 20.7 9.9 0.6 0.4 0.8 6.397 13.334 4,655.6 57.01 Sudan SDN 180.0 42.9 4,413 1,053 35.7 26.8 9.6 7.1 1.7 0.2 0.1 0.6 4.803 20.130 864.5 40.78 54    Purchasing Power Parities and the Size of World Economies Table 2.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 127.6 50.9 2,334 931 59.7 14.2 8.5 3.8 1.5 0.1 0.1 0.8 888.911 2,228.858 113,405.3 54.66 Togo TGO 13.1 5.4 1,702 706 62.1 10.4 6.4 2.8 1.1 0.0 0.0 0.1 241.413 582.075 3,163.3 7.70 Uganda UGA 93.8 33.4 2,277 813 53.4 13.9 7.4 3.7 1.3 0.1 0.0 0.6 1,288.420 3,611.224 120,792.5 41.17 Zambia ZMB 57.4 25.3 3,405 1,502 66.0 20.7 13.7 5.5 2.4 0.0 0.0 0.2 4.198 9.520 240.9 16.85 Zimbabwe ZWE 41.7 21.0 2,927 1,475 75.4 17.8 13.4 4.7 2.4 0.0 0.0 0.2 0.504 1.000 21.0 14.24 Total (45) SSB 3,854.1 1,596.8 3,774 1,564 62.0 23.0 14.2 6.1 2.5 3.3 2.0 14.2 n.a. n.a n.a. 1,021.22 World (176) WLD 118,404.6 79,140.9 16,437 10,986 100.0 100.0 100.0 26.6 17.8 100.0 100.0 100.0 n.a. n.a. n.a. 7,203.60 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either the Latin America and the Caribbean or the world totals. ICP 2017 results 55 Table 2.7  Gross domestic product (GDP) and individual consumption expenditure by households for nonparticipating economies: ICP 2017 results GROSS DOMESTIC PRODUCT Reference data INDIVIDUAL CONSUMPTION Expenditure Expenditure per capita EXPENDITURE BY (billion US$) (US$) Expenditure, HOUSEHOLDS Price level Market gross indexa exchange domestic Based Based Based Based (world = PPPsb ratesb product Population PPPsb Economy on PPPs on XRs on PPPs on XRs 100.0) (US$ = 1.000) (US$ = 1.000) (billion LCU) (millions) (US$ = 1.000) (00) (01) (02) (03) (04) (05) (13) (14) (15) (16) (13) Nonparticipating economies Afghanistan AFG 79.9 20.2 2,203 557 38.0 17.206 68.027 1,375.5 36.30 17.360 c Guatemala GTM 141.3 75.7 8,353 4,473 80.5 3.933 7.344 555.6 16.91 4.403 Kosovo KSV 18.9 7.2 10,302 3,958 57.7 0.340 0.885 6.4 1.83 0.357 Lebanon LBN 109.5 53.4 16,082 7,838 73.3 734.776 1,507.500 80,491.2 6.81 761.833 Libya LBY 87.1 37.9 13,665 5,942 65.4 0.606 1.394 52.8 6.37 0.638 c Macao SAR, China MAC 79.0 50.8 126,918 81,517 96.5 5.155 8.026 407.3 0.62 5.940 Puerto Rico PRI 115.2 104.3 34,634 31,353 136.1 0.905 1.000 104.3 3.33 0.977 Somalia SOM 12.7 4.5 858 306 53.5 8,229.531 23,097.987 104,148.3 14.74 7,861.360 South Sudan SSD 9.8 3.1 898 280 47.0 35.505 113.648 347.7 10.91 34.920 Timor-Leste TLS 3.9 1.6 3,166 1,295 61.5 0.409 1.000 1.6 1.24 0.423 Turkmenistan TKM 81.8 37.9 14,205 6,587 69.7 1.623 3.500 132.7 5.76 1.663 Uzbekistand UZB 211.1 60.5 6,519 1,869 43.1 1,432.907 4,999.020 302,536.8 32.39 1,521.475 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable. a. World totals used to calculate price level indexes (PLIs) in this table include nonparticipating economies. b. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. c. GDP and individual consumption expenditure by households PPPs for Guatemala and Macao SAR, China are based on a time-series estimation approach. d. Individual consumption expenditure by households PPP for Uzbekistan is based on an experimental participation approach; the ICP online database covers additional headings based on this approach. 56    Purchasing Power Parities and the Size of World Economies Table 2.8  ICP 2017 Individual consumption expenditure by households, survey framework ICP Global Public or Core List ICP Total Medium Bulk and Private semipublic Other kinds and Global outlets Large and small Street discount Specialized service service of trades regional Core List covered shops shops Markets outlets shops shops providers providers and outlets items items Geographic Economy coveragea # % % % % % % % % % # # East Asia and Pacific Australia AUS Urban only ... ... … ... ... ... ... ... ... ... 1,599 352 Brunei Darussalam BRN Urban only 213 4.69 4.23 2.35 0.00 0.00 53.05 28.64 7.04 0.00 610 307 Cambodia KHM Urban and Rural 1,244 3.62 21.14 45.18 5.47 0.16 0.48 21.22 2.57 0.16 590 276 China CHN Urban and Rural 39,587 10.35 10.79 3.03 12.29 0.41 16.34 18.29 10.84 17.65 901 437 Fiji FJI Urban only 878 13.44 27.33 6.83 0.11 0.23 9.45 8.09 33.71 0.80 455 227 Hong Kong SAR, China HKG Urban only 1,880 6.54 2.98 18.35 0.00 0.00 46.81 22.50 2.82 0.00 703 352 Indonesia IDN Urban and Rural 1,156 12.72 21.97 8.56 3.72 0.26 26.30 24.39 1.38 0.69 676 339 Japan JPN Capital-city only ... ... ... ... ... ... ... ... ... ... 1,224 278 Korea, Rep. KOR Urban only ... ... ... ... ... ... ... ... ... ... 1,478 318 Lao PDR LAO Urban and Rural 1,254 0.80 0.96 76.71 0.00 0.40 4.31 9.49 3.75 3.59 639 323 Malaysia MYS Urban and Rural 9,641 22.00 18.99 20.99 0.00 0.00 3.00 17.01 18.01 0.00 739 365 Mongolia MNG Urban and Rural 2,714 4.53 28.81 7.04 0.52 0.04 2.84 46.13 6.82 3.28 787 382 Myanmar MMR Urban and Rural 3,568 2.24 24.69 45.66 3.73 0.25 11.66 7.74 1.99 2.05 775 375 New Zealand NZL Capital-city only ... ... ... ... ... ... ... ... ... ... 1,267 276 Philippines PHL Urban and Rural 6,399 5.61 8.05 25.39 9.16 0.02 29.85 16.42 2.66 2.84 849 413 Singapore SGP Urban only 792 1.89 2.78 3.03 0.00 0.00 32.83 53.66 2.02 3.79 713 358 Taiwan, China TWN Urban only 596 2.52 3.36 13.26 0.00 0.00 48.83 25.67 5.03 1.34 711 345 Thailand THA Urban and Rural 3,534 4.90 10.16 13.92 1.50 0.96 35.51 23.66 8.89 0.51 653 321 Vietnam VNM Urban and Rural 983 7.32 24.31 14.65 8.34 0.20 13.33 23.80 8.04 0.00 757 369 Europe and Central Asia Albania ALB Urban only ... 34.06 0.94 0.70 0.00 0.00 45.91 16.42 0.01 1.92 1,605 347 Armenia ARM Urban only 955 2.62 5.13 2.30 1.36 0.00 38.74 46.07 1.88 1.88 1,548 489 Austria AUT Urban only ... 29.35 0.01 2.80 0.00 6.69 38.08 15.52 0.37 7.20 1,933 377 Azerbaijan AZE Urban only 3,347 7.59 25.90 2.42 0.00 0.00 4.72 40.39 18.97 0.00 1,460 461 Belarus BLR Urban only 4,484 4.82 8.65 10.97 0.83 0.76 27.54 28.68 9.14 8.61 1,473 470 Belgium BEL Urban only ... 61.19 1.50 0.10 0.00 2.59 19.31 12.21 0.22 2.84 1,797 349 Bosnia and Herzegovina BIH Urban only ... 49.94 0.86 1.90 0.00 0.00 26.52 12.41 2.26 6.09 1,566 351 Bulgaria BGR Capital-city only ... 39.52 0.47 1.70 0.00 0.00 38.65 11.49 0.26 7.94 1,968 397 Croatia HRV Urban only ... 39.42 7.75 3.80 0.00 0.52 30.15 14.79 0.76 2.76 1,967 392 Cyprus CYP Urban only ... 52.65 2.78 0.70 0.00 0.00 27.32 14.93 1.54 0.08 1,769 376 Czech Republic CZE Capital-city only ... 45.07 1.08 0.00 0.00 3.77 34.23 13.85 0.46 1.54 1,879 371 Denmark DNK Urban only ... 14.15 0.11 0.00 0.00 1.76 33.80 34.24 0.36 15.58 1,733 360 Estonia EST Urban only ... 60.07 1.31 0.50 0.00 0.03 20.25 11.69 1.67 4.47 1,752 360 Finland FIN Urban only ... 48.12 0.01 0.00 0.10 4.78 24.79 17.75 0.48 3.95 1,792 355 France FRA Capital-city only ... 51.72 3.29 2.60 0.00 4.56 20.33 14.82 0.00 2.68 1,961 383 Georgia GEO Capital-city only 800 2.50 2.13 4.50 0.00 0.00 35.63 52.63 1.38 1.25 1,381 324 Germany DEU Capital-city only ... 34.88 0.18 0.40 0.00 7.57 21.91 22.48 2.32 10.30 1,768 360 Greece GRC Urban only ... 45.57 0.43 3.20 0.00 3.58 32.95 14.08 0.12 0.10 1,890 386 ICP 2017 results 57 Table 2.8  (Continued) ICP Global Public or Core List ICP Total Medium Bulk and Private semipublic Other kinds and Global outlets Large and small Street discount Specialized service service of trades regional Core List covered shops shops Markets outlets shops shops providers providers and outlets items items Geographic Economy coveragea # % % % % % % % % % # # Hungary HUN Capital-city only ... 27.55 13.69 2.60 0.00 5.64 29.53 17.52 0.27 3.24 1,855 369 Iceland ISL Urban only ... 48.76 0.38 0.00 0.00 0.05 27.80 21.61 0.18 1.22 1,638 335 Ireland IRL Urban only ... 49.52 2.89 0.00 0.00 4.38 24.47 17.84 0.89 0.01 1,832 365 Italy ITA Capital-city only ... 50.07 0.23 1.10 0.00 9.37 23.10 15.05 0.19 0.88 1,964 392 Kazakhstan KAZ Urban only 4,983 7.39 11.34 4.01 0.80 0.00 21.15 39.07 5.02 11.22 1,720 524 Kyrgyzstan KGZ Capital city only 213 4.23 0.94 4.23 0.94 0.00 18.78 58.69 3.76 8.45 1,451 467 Latvia LVA Urban only ... 47.08 2.31 2.30 0.00 1.00 31.51 14.13 0.73 0.92 1,835 375 Lithuania LTU Capital-city only ... 45.78 5.89 2.20 0.00 2.05 26.80 15.03 0.13 2.07 1,887 382 Luxembourg LUX Urban only ... 62.14 0.51 0.00 0.00 4.23 19.41 13.20 0.19 0.32 1,932 379 Moldova MDA Urban only 297 7.74 27.95 4.04 1.01 0.00 34.01 15.49 7.74 2.02 1,541 483 Montenegro MNE Urban only ... 44.07 3.85 0.80 0.00 8.64 28.61 13.55 0.20 0.20 1,631 363 Netherlands NLD Urban only ... 28.64 0.03 0.80 0.10 1.50 41.19 16.12 0.38 11.20 1,902 375 North Macedonia MKD Urban only ... 43.50 5.43 2.70 0.00 0.00 29.82 16.24 0.29 2.04 1,616 350 Norway NOR Urban only ... 30.61 4.88 0.00 0.00 26.61 21.22 10.24 0.90 5.54 1,780 349 Poland POL Capital-city only ... 32.14 10.89 1.10 0.10 4.22 31.91 14.87 1.42 3.37 1,937 385 Portugal PRT Capital-city only ... 45.42 0.67 2.50 0.00 2.55 26.95 21.03 0.24 0.62 1,896 378 Romania ROU Capital-city only ... 45.27 0.75 1.20 0.00 1.72 27.76 16.74 0.07 6.47 1,834 370 Russian Federation RUS Capital-city only ... 6.38 3.72 1.77 1.33 1.51 23.74 2.21 25.78 33.57 1,368 331 Serbia SRB Urban only ... 56.64 7.21 3.50 0.00 0.00 17.63 11.62 0.58 2.80 1,859 377 Slovakia SVK Urban only ... 51.25 1.60 1.20 0.20 0.65 29.99 13.34 0.03 1.73 1,914 382 Slovenia SVN Urban only ... 57.84 0.82 0.00 0.00 5.58 22.44 9.74 0.47 3.11 1,905 383 Spain ESP Capital-city only ... 35.76 0.71 9.10 0.10 4.97 25.68 22.63 0.41 0.56 1,932 384 Sweden SWE Urban only ... 83.39 0.04 0.00 0.00 0.17 9.59 5.18 0.15 1.48 1,804 356 Switzerland CHE Capital-city only ... 60.17 0.18 0.00 0.00 11.09 14.57 9.46 0.54 3.98 1,835 361 Tajikistan TJK Capital city only 59 10.17 25.42 8.47 0.00 3.39 16.95 23.73 5.08 6.78 1,381 448 Turkey TUR Capital-city only ... 52.66 0.03 0.10 0.00 3.02 30.59 12.05 0.61 0.93 1,869 377 Ukraine UKR Capital-city only 2,219 6.89 14.38 0.36 0.90 0.00 43.35 28.26 0.90 4.96 1,352 342 United Kingdom GBR Capital-city only ... 47.54 5.39 0.30 0.00 4.22 18.26 21.23 0.18 2.89 1,873 374 Latin America and the Caribbean Anguilla AIA Urban and Rural ... ... ... ... ... ... ... ... ... ... 406 368 Antigua and Barbuda ATG Urban Only 80 0.00 100.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 250 231 Argentina ARG Capital city only 3,988 4.29 95.71 0.00 0.00 0.00 0.00 0.00 0.00 0.00 286 268 Aruba ABW Urban Only 45 100.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 404 364 Bahamas, The BHS ... ... ... ... ... ... ... ... ... ... ... 259 249 Barbados BRB Urban and Rural 70 0.00 100.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 279 256 Belize BLZ Urban only 161 0.00 100.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 261 239 Bolivia BOL Urban only … 0.50 7.92 0.00 47.25 0.00 22.88 14.57 0.09 6.80 222 207 Bonaire BON Urban only 80 0.00 100.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 177 168 58    Purchasing Power Parities and the Size of World Economies Table 2.8  (Continued) ICP Global Public or Core List ICP Total Medium Bulk and Private semipublic Other kinds and Global outlets Large and small Street discount Specialized service service of trades regional Core List covered shops shops Markets outlets shops shops providers providers and outlets items items Geographic Economy coveragea # % % % % % % % % % # # Brazil BRA Urban only 3,662 15.84 3.90 3.69 0.00 0.11 46.12 27.61 2.68 0.05 349 330 Cayman Islands CYM Capital city only 210 ... ... ... ... ... ... ... ... ... 422 389 Chile CHL Urban only ... ... ... ... ... ... ... ... ... ... 1,379 337 Colombia COL Urban only ... ... ... ... ... ... ... ... ... ... 1,048 298 Costa Rica CRI Urban only ... ... ... ... ... ... ... ... ... ... 1,034 268 Curaçao CUW Urban and Rural ... ... ... ... ... ... ... ... ... ... 392 373 Dominica DMA Urban and Rural 13 ... ... ... ... ... ... ... ... ... 294 269 Dominican Republic DOM Urban only 3,585 17.57 65.86 2.40 0.00 0.00 14.17 0.00 0.00 0.00 423 387 Ecuador ECU Urban only 811 4.44 5.67 1.60 1.11 0.00 49.08 35.64 2.47 0.00 285 266 El Salvador SLV Urban only 1,324 62.54 3.85 6.27 0.53 0.00 0.00 0.23 0.00 26.59 170 161 Grenada GRD Capital city only 6 ... ... ... ... ... ... ... ... ... 234 214 Guyana GUY Capital city only 97 11.34 69.07 5.15 0.00 10.31 0.00 4.12 0.00 0.00 368 336 Haiti HTI ... ... ... ... ... ... ... ... ... ... ... 203 195 Honduras HND ... ... ... ... ... ... ... ... ... ... ... 241 224 Jamaica JAM ... ... ... ... ... ... ... ... ... ... ... 174 160 Mexico MEX Urban only ... ... ... ... ... ... ... ... ... ... 1,481 342 Montserrat MSR Urban and Rural ... ... ... ... ... ... ... ... ... ... 215 196 Nicaragua NIC Urban only 1,086 ... ... ... ... ... ... ... ... ... 255 238 Panama PAN Urban only 132 9.85 21.97 1.52 0.00 0.00 24.24 30.30 0.00 12.12 203 197 Paraguay PRY Urban only 377 7.16 12.20 1.86 1.06 0.00 32.63 38.46 5.84 0.80 273 257 Peru PER Capital city only 607 6.92 13.01 7.74 2.31 0.00 22.73 45.47 0.66 1.15 444 404 Sint Maarten SXM Urban only 155 11.61 20.65 0.00 0.00 0.65 10.97 52.26 3.87 0.00 256 249 St. Kitts and Nevis KNA Capital city only 69 ... ... ... ... ... ... ... ... ... 402 371 St. Lucia LCA Urban and Rural 153 3.92 7.19 1.31 0.00 0.00 49.67 35.95 1.96 0.00 370 341 St. Vincent and the VCT Urban and Rural 91 14.29 0.00 3.30 0.00 0.00 25.27 52.75 4.40 0.00 356 321 Grenadines Suriname SUR Urban and Rural 383 26.37 8.88 1.83 2.09 0.78 26.37 30.03 3.66 0.00 414 384 Trinidad and Tobago TTO Urban only 532 14.10 23.87 1.32 0.75 0.19 38.53 20.68 0.56 0.00 432 398 Turks and Caicos Islands TCA ... ... ... ... ... ... ... ... ... ... ... 325 303 Uruguay URY Capital city only ... ... ... ... ... ... ... ... ... ... 284 267 Virgin Islands, British VGB Capital city only 122 ... ... ... ... ... ... ... ... ... 287 262 Middle East and North Africa Algeria DZA Urban and Rural 364 0.00 3.30 11.81 7.69 4.12 0.00 57.69 12.36 3.02 458 357 Bahrain BHR Urban only 287 2.44 4.18 2.09 0.00 0.35 62.02 27.53 1.39 0.00 554 392 Djibouti DJI Capital city only 97 5.66 28.30 1.89 3.77 0.00 28.30 28.30 3.77 0.00 451 358 Egypt, Arab Rep. EGY Urban and Rural 3,425 8.29 5.43 1.02 0.00 0.00 85.26 0.00 0.00 0.00 716 459 Iran, Islamic Rep. IRN Urban only 3,241 5.71 36.25 24.99 14.10 2.31 2.81 10.34 2.99 0.49 548 382 Iraq IRQ Urban only 102 6.86 24.51 0.00 0.00 0.00 0.00 19.61 24.51 24.51 648 449 ICP 2017 results 59 Table 2.8  (Continued) ICP Global Public or Core List ICP Total Medium Bulk and Private semipublic Other kinds and Global outlets Large and small Street discount Specialized service service of trades regional Core List covered shops shops Markets outlets shops shops providers providers and outlets items items Geographic Economy coveragea # % % % % % % % % % # # Israel ISR Urban only ... ... ... ... ... ... ... ... ... ... 1,673 358 Jordan JOR Urban only 1,812 4.25 13.19 11.20 1.21 0.33 33.39 34.44 1.60 0.39 647 445 Kuwait KWT Urban only 280 9.64 8.93 12.14 5.36 0.36 31.79 15.71 16.07 0.00 627 430 Malta MLT Urban only ... 34.62 6.73 0.50 0.00 2.79 34.55 20.06 0.43 0.35 1,830 376 Morocco MAR Urban and Rural 577 2.08 5.72 4.33 1.91 0.35 48.53 34.32 2.43 0.35 842 531 Oman OMN Urban only 62 17.74 0.00 82.26 0.00 0.00 0.00 0.00 0.00 0.00 607 409 Qatar QAT Urban only 450 ... ... ... ... ... ... ... ... ... 625 432 Saudi Arabia SAU Urban only 450 ... ... ... ... ... ... ... ... ... 641 440 Tunisia TUN Urban and Rural 969 15.69 18.16 22.29 1.03 0.31 26.93 12.07 0.31 3.20 478 371 United Arab Emirates ARE Urban only 654 12.20 26.60 8.90 4.30 2.30 17.90 18.70 4.30 4.90 642 445 West Bank and Gaza PSE Urban only 1,899 8.43 56.19 0.00 3.11 0.42 0.21 23.64 0.74 7.27 538 377 North America Bermuda BMU Urban only 41 0.00 29.27 0.00 0.00 0.00 53.66 7.32 9.76 0.00 155 149 Canada CAN Urban only ... ... ... ... ... ... ... ... ... ... 1,354 318 United States USA Urban only ... ... ... ... ... ... ... ... ... ... 1,304 324 South Asia Bangladesh BGD Urban and Rural 720 0.00 0.00 100.00 0.00 0.00 0.00 0.00 0.00 0.00 780 365 Bhutan BTN Urban and Rural 482 0.41 48.76 8.09 0.00 0.00 13.07 26.97 2.70 0.00 442 219 India IND Urban and Rural 897 ... ... ... ... ... ... ... ... ... 945 441 Maldives MDV Urban and Rural 241 0.41 20.75 0.41 0.00 0.00 44.40 27.80 3.32 2.90 359 182 Nepal NPL Urban and Rural 4,016 7.74 51.00 2.61 3.96 0.22 14.54 15.01 2.37 2.54 667 307 Pakistan PAK Urban and Rural 120 … … … … … … … … … 890 415 Sri Lanka LKA Urban and Rural 3,948 7.29 32.90 8.08 2.05 1.37 29.08 16.26 2.36 0.61 652 313 Sub-Saharan Africa Angola AGO Urban and Rural 402 7.46 21.64 8.46 0.00 0.00 31.34 29.60 1.49 0.00 217 177 Benin BEN Urban and Rural 1,769 5.71 8.88 12.21 16.05 6.05 37.82 11.25 1.87 0.17 547 420 Botswana BWA Urban and Rural 1,592 5.19 2.59 1.98 2.10 0.00 27.90 14.94 0.00 45.31 482 391 Burkina Faso BFA Urban and Rural 255 5.10 5.10 10.20 5.10 0.00 37.25 30.20 7.06 0.00 520 399 Burundi BDI Urban and Rural 185 5.41 29.73 9.19 3.24 0.00 34.59 16.76 1.08 0.00 468 359 Cabo Verde CPV Urban and Rural 280 5.38 8.60 10.75 3.23 0.00 45.16 21.51 5.38 0.00 489 383 Cameroon CMR Urban and Rural 924 21.84 10.34 5.75 4.60 0.00 25.29 29.89 2.30 0.00 548 420 Central African Republic CAF Urban and Rural 221 11.90 21.43 5.95 1.19 0.00 36.90 22.62 0.00 0.00 444 347 Chad TCD Capital city only 135 7.21 5.41 8.11 6.31 0.00 12.61 57.66 2.70 0.00 512 392 Comoros COM Urban only 56 7.14 25.00 7.14 3.57 0.00 17.86 35.71 3.57 0.00 388 313 Congo, Dem. Rep. COD Urban only 130 12.15 21.50 12.15 1.87 0.00 26.17 24.30 1.87 0.00 510 392 Congo, Rep. COG Urban only 602 10.53 13.16 2.63 2.63 0.00 38.16 30.26 2.63 0.00 562 428 Côte d’Ivoire CIV Urban and Rural 241 16.13 32.26 8.06 8.06 0.00 16.13 16.13 3.23 0.00 559 426 Equatorial Guinea GNQ Capital city only 81 12.20 21.95 2.44 4.88 0.00 24.39 29.27 4.88 0.00 548 418 60    Purchasing Power Parities and the Size of World Economies Table 2.8  (Continued) ICP Global Public or Core List ICP Total Medium Bulk and Private semipublic Other kinds and Global outlets Large and small Street discount Specialized service service of trades regional Core List covered shops shops Markets outlets shops shops providers providers and outlets items items Geographic Economy coveragea # % % % % % % % % % # # Eswatini SWZ Urban only 125 37.60 0.80 5.60 7.20 0.00 48.80 0.00 0.00 0.00 483 382 Ethiopia ETH Urban only 453 10.68 29.13 10.68 4.85 0.00 21.36 21.36 1.94 0.00 523 405 Gabon GAB Urban only 313 8.95 35.46 9.58 2.24 0.00 28.75 7.03 7.99 0.00 423 332 Gambia, The GMB Urban and Rural 460 4.78 12.61 8.26 9.35 0.00 15.87 38.91 10.22 0.00 533 404 Ghana GHA Urban only 328 20.73 14.33 8.54 1.52 0.00 33.23 21.04 0.61 0.00 526 401 Guinea GIN Urban and Rural 210 10.87 21.74 15.22 4.35 0.00 21.74 21.74 4.35 0.00 499 382 Guinea-Bissau GNB Capital city only 403 7.94 14.29 4.76 1.59 0.00 11.11 57.14 3.17 0.00 544 417 Kenya KEN Urban and Rural 1,484 11.81 23.62 11.81 3.94 0.00 23.62 23.62 1.57 0.00 507 392 Lesotho LSO Urban only 474 37.97 14.35 1.69 3.38 0.00 36.08 6.54 0.00 0.00 406 340 Liberia LBR Capital city only 150 10.67 12.00 11.33 11.33 0.00 15.33 33.33 6.00 0.00 475 370 Madagascar MDG Capital city only 519 4.24 37.76 6.55 3.47 0.00 22.54 24.86 0.58 0.00 461 364 Malawi MWI Urban and Rural 151 15.25 25.42 23.73 3.39 0.00 15.25 11.86 5.08 0.00 516 395 Mali MLI Urban and Rural 466 11.36 22.73 11.36 4.55 0.00 22.73 22.73 4.55 0.00 556 422 Mauritania MRT Urban and Rural 2,438 4.18 15.75 33.10 0.00 0.00 23.13 5.58 18.25 0.00 453 351 Mauritius MUS Urban and Rural 520 4.62 31.73 2.12 0.58 0.00 46.92 10.38 3.65 0.00 502 395 Mozambique MOZ Urban only 706 50.82 45.90 1.64 0.00 0.00 1.64 0.00 0.00 0.00 502 385 Namibia NAM Urban only 242 14.46 4.96 1.24 0.00 0.00 28.10 41.32 9.92 0.00 509 406 Niger NER Capital city only 210 9.05 11.90 7.14 8.10 0.00 7.14 49.52 7.14 0.00 525 404 Nigeria NGA Urban and Rural 1,004 6.87 14.94 11.45 8.96 0.00 20.12 29.88 7.77 0.00 546 417 Rwanda RWA Urban and Rural 184 7.30 29.60 11.00 6.00 0.00 33.10 12.00 1.00 0.00 489 384 São Tomé and Principe STP Capital city only 276 3.99 11.59 3.99 2.90 0.00 51.09 21.01 5.43 0.00 366 284 Senegal SEN Urban and Rural 254 12.66 25.32 6.33 2.53 0.00 25.32 25.32 2.53 0.00 544 415 Seychelles SYC Capital city only 53 50.94 11.32 1.89 0.00 0.00 32.08 1.89 1.89 0.00 477 384 Sierra Leone SLE Urban only 101 8.91 10.89 12.87 6.93 0.00 10.89 47.52 1.98 0.00 515 393 South Africa ZAF Urban and Rural 1,016 32.09 10.33 1.28 1.57 0.00 8.66 34.94 11.12 0.00 366 313 Sudan SDN Urban and Rural 3,165 18.70 14.63 2.53 1.80 9.51 23.44 6.41 7.58 15.39 602 407 Tanzania TZA Urban and Rural 1,134 5.49 13.50 9.70 9.92 0.00 22.15 37.76 1.48 0.00 540 410 Togo TGO Capital city only 209 5.26 26.32 5.26 5.26 0.00 26.32 26.32 5.26 0.00 315 247 Uganda UGA Urban and Rural 777 10.53 21.05 10.53 2.63 0.00 26.32 26.32 2.63 0.00 543 416 Zambia ZMB Urban only 378 25.13 5.56 0.26 2.12 2.38 39.42 15.34 9.79 0.00 488 385 Zimbabwe ZWE Urban and Rural 1,040 11.92 5.38 0.67 21.15 0.00 26.06 27.88 6.92 0.00 523 405 Note: ICP = International Comparison Program; … = information not available. a. ICP data requirements require that all average prices reported by participating economies and used in PPP calculations be nationally representative annual average prices, irrespective of the survey geographical coverage reported here. ­ ICP 2017 results 61 CHAPTER 3 Purchasing power parities and real expenditures Concepts and definitions comparisons of GDP can be made from the pro- duction side and from the expenditure side, but The ICP approach to GDP comparisons not from the income side. ICP comparisons are The International Comparison Program (ICP) made from the expenditure side. This approach comparisons of gross domestic product (GDP) allows comparison of the levels of the principal are based on the value of an individual item elements of final demand—that is, consump- equaling the product of its price and quantity tion and investment. It also avoids the difficul- (that is, the identity: value = price × quantity). ties encountered in organizing comparisons Once more than one item is involved, the iden- from the production side, which requires data tity can no longer be expressed in terms of price for both intermediate consumption and gross × quantity. Therefore, in ICP terms, it becomes output in order to effect double deflation. The value = price × volume. disadvantage of the expenditure approach is GDP is a measure of production within an that, unlike the production approach, it does economy, and it is commonly estimated as the not identify individual industries, and so pro- sum of the value of the outputs from produc- ductivity can be compared only at the level tion less the cost of the goods and services used of the whole economy. On the other hand, a in their production—the so-called production major advantage is that the estimates of final approach. It also can be estimated as the sum demand can be used in many different types of the final expenditures on goods and ser- of economic analysis, including forecasting and vices plus exports less imports of goods and poverty analysis. services, which is known as the expenditure Economies estimate their expenditures on side of national accounts and is the approach GDP at national price levels and in local currency used by the ICP. Yet another alternative is to units. But before these nominal expenditures estimate GDP as the sum of the incomes arising can be used to compare the volumes of goods from production (wages, profits, and so forth), and services produced by economies, differences which is referred to as the income approach. in national price levels have to be eliminated In theory, the three approaches yield the same and local currency units have to be converted to result. However, whereas values estimated from a common currency. Differences in price levels the production side and the expenditure side between economies can be removed either by can be split into meaningful price and volume observing volumes directly as the sum of their components, values estimated from the income underlying quantities or by deriving them indi- side cannot. In other words, price and volume rectly using a measure of relative prices to place 63 the expenditures of all economies on the same have to be traded internationally, and the sup- price level. Prices are easier to observe than ply and demand for currencies would have to be quantities, and direct measures of relative prices driven predominantly, if not solely, by the cur- usually have a smaller variability than direct rency requirements of international trade. But measures of relative quantities. In ICP compari- this is not the case. Many goods and services— sons, volumes (referred to as real expenditures) such as buildings, government services, and are mostly estimated indirectly using direct mea- most household market services—are not traded sures of relative prices—purchasing power pari- internationally, and the supply and demand for ties (PPPs)—to deflate nominal expenditures. In currencies are influenced primarily by factors addition to being spatial price deflators, PPPs are such as currency speculation, interest rates, currency converters. Thus PPP-deflated expendi- government intervention, and capital flows tures are expressed in a common currency unit between economies. Consequently, as equation and are also valued at the same price level. (B3.1.2) in box 3.1 indicates, GDP converted to a common currency using market exchange rates remains valued at national price levels. The Market exchange rates differences between the levels of GDP in two or Before PPPs became widely available, market more economies reflect both differences in the exchange rates were used to make international volumes of goods and services produced by the comparisons of GDP. Market exchange rates, economies and differences in the price levels of however, only convert GDP to a common cur- the economies. However, as equation (B3.1.4) rency. They do not provide GDP valued at a in box 3.1 shows, GDP converted with PPPs common price level because market exchange reflect only differences in the volumes produced rates do not reflect the relative purchasing by the economies. power of currencies in their national markets. Market exchange rate–converted GDP— For them to do so, all goods and services would that is, nominal GDP converted to a common Box 3.1  Using market exchange rates and PPPs to convert to a common currency 1.  The ratio of the GDPs of two economies when both are valued at national price levels and expressed in local currency units has three component ratios: GDP ratio = price level ratio × volume ratio × currency ratio. (B3.1.1) 2.  When converting the GDP ratio in equation (B3.1.1) to a common currency using the market exchange rate, the resulting GDPXR ratio has two component ratios: GDPXR ratio = price level ratio × volume ratio. (B3.1.2) The GDP ratio in equation (B3.1.2) is expressed in a common currency, but it reflects both the price level differences and the volume differences between the two economies. 3.  A PPP is defined as a spatial price deflator and currency converter. It is composed of two component ratios: PPP = price level ratio × currency ratio. (B3.1.3) 4.  When a PPP is used, the GDP ratio in equation (B3.1.1) is divided by equation (B3.1.3), and the resulting GDPPPP ratio has only one component ratio: GDPPPP ratio = volume ratio.  (B3.1.4) The GDP ratio in equation (B3.1.4) is expressed in a common currency, is valued at a com- mon price level, and reflects only differences in volume between the two economies. 64    Purchasing Power Parities and the Size of World Economies currency using market exchange rates—can be €1.00 spent on hamburgers in France, $0.83 highly misleading with regard to the relative size would have to be spent in the United States to of economies. Price levels are normally higher obtain the same quantity and quality—that is, in high-income economies than they are in the same volume—of hamburgers. Conversely, low-income economies; as a result, differences for every $1.00 spent on hamburgers in the in price levels between high-income econo- United States, €1.20 would have to be spent in mies and low-income economies are greater France to obtain the same volume of hamburg- for nontraded items than they are for traded ers. To compare the volumes of hamburgers items. Before the addition of tariffs, subsidies, purchased in the two economies, either the and trade costs, the prices of traded items are expenditure on hamburgers in France can be basically determined globally by the law of one expressed in dollars by dividing by 1.20, or the price, whereas the prices of nontraded items are expenditure on hamburgers in the United States determined by local circumstances, in particu- can be expressed in euros by dividing by 0.83. lar, by wages and salaries, which are generally PPPs are calculated in stages: first for item higher in high-income economies. If the larger groups, then for various aggregates, and finally differences in price level for nontraded items are for GDP. PPPs continue to be price relatives not taken into account when converting GDP whether they refer to an item group, to an to a common currency, the size of high-income aggregate, or to GDP. As one moves up the economies with high price levels will be over- aggregation hierarchy, the price relatives refer to stated and the size of low-income economies increasingly complex assortments of goods and with low price levels will be understated. This services. Therefore, if the PPP for GDP between is known as the Penn effect. No distinction is France and the United States is €0.95 to $1.00, made between traded items and nontraded it can be inferred that for every $1.00 spent on items when market exchange rates are used to GDP in the United States, €0.95 would have to convert GDP to a common currency—the rate be spent in France to purchase the same volume is the same for all items. PPP-converted GDP of goods and services. Purchasing the same vol- does not have this bias because, as explained in ume of goods and services does not mean that chapter 5, PPPs are calculated first for individual the baskets of goods and services purchased in items. They thus take into account the differ- both economies will be identical. The composi- ent price levels for traded items and nontraded tion of the baskets will vary between economies items. and reflect differences in taste, culture, climate, ICP PPPs are designed specifically for interna- price structure, item availability, and income tional comparisons of GDP. They are not designed level, but both baskets will, in principle, provide for comparisons of monetary flows or trade equivalent satisfaction or utility. flows. International comparisons of flows—such as development aid, foreign direct investment, Price level indexes migrants’ remittances, or imports and exports of goods and services—should be made with mar- PPPs are spatial price indexes. They show, with ket exchange rates, not with PPPs. reference to a base economy (or region), the price of a given basket of goods and services in each of the economies being compared. This Purchasing power parities index is similar to a temporal price index, which PPPs are price relatives that show the ratio of the shows, with reference to a base period, the price prices in local currency units of the same good of a given basket of goods and services at differ- or service in different economies. For example, if ent points in time. However, unlike a temporal the price of a hamburger is €4.80 in France and price index in which the indexes at the different $4.00 in the United States, the PPP for hamburg- points in time are expressed in the same cur- ers between the two economies is $0.83 to the rency unit so that changes in price over time €1.00 from France’s perspective (4.00/4.80) and are readily identifiable, the PPP index for each €1.20 to the dollar from the United States’ per- economy is expressed in the economy’s local spective (4.80/4.00). In other words, for every currency. It is thus not possible to say whether Purchasing power parities and real expenditures 65 one economy is more expensive or less expen- appear suddenly larger or smaller even though sive than another. For this type of comparison, there has been little or no change in the relative one would have to standardize the indexes by volume of goods and services produced. expressing them in a common unit of currency. The common currency used for the global com- Real expenditures parison is the US dollar, so each economy’s PPP has been standardized by dividing it by that Economies report aggregate and detailed nomi- economy’s dollar market exchange rate. The nal expenditures on GDP in local currency standardized indexes so obtained are called price units. Nominal expenditures are expenditures level indexes (PLIs). that are valued at national price levels. They Economies with PLIs greater than 100 have can be expressed in local currency units or, price levels that are higher than that of the base when converted with market exchange rates, economy. Economies with PLIs less than 100 in a common currency. In the latter, the con- have price levels that are lower than that of the verted expenditures remain nominal because, as base economy. So, returning to the hamburger explained earlier, market exchange rates do not example, if the market exchange rate is $1.00 to correct for differences in price levels between €0.79, the PLI for a hamburger with the United economies, and so the expenditures are still val- States as the base economy is 152 (1.20/0.79 × ued at national price levels. For the ICP, econo- 100). From this, it can be inferred that, given mies report their nominal expenditures in local the relative purchasing power of the dollar and currency units. the euro, hamburgers cost 52 percent more in PPPs are used to convert these nominal France than they do in the United States. In expenditures to real expenditures. Real expen- addition to items, PLIs can be calculated for GDP ditures are expenditures that are valued at a and its expenditure components. At the level of common price level. They reflect real or actual GDP, PLIs provide a measure of the differences differences in the volumes purchased in econo- in the general price levels of economies. Thus, if mies and provide the measures required for the PPP for GDP between France and the United international comparisons of volume: indexes States is €0.95 to $1.00, the PLI for GDP based of real expenditure and indexes of real expen- on the United States is 120 (0.95/0.79 × 100), diture per capita. It should be noted that the indicating that the general price level of France term “real” has a specific meaning when con- is 20 percent higher than that of the United sidering data in PPP terms and throughout this States. The PLIs of economies can be compared report. Confusion may arise when considering directly. For example, if the PLI of one economy the terms “real” and “nominal” in temporal is 120 while that of another economy is 80 and spatial contexts. While nominal expendi- (both with the United States as base), then it is tures, in both contexts, refer to expenditures valid to infer that the price level is 50 percent in current-year prices valued at national price (that is, 120/80) higher in the former than in levels and expressed in local currency units or the latter. in a common currency using market exchange It is worth remembering that PPPs evolve rates, the term “real expenditures” can take on slowly, whereas market exchange rates can different meanings in spatial and temporal con- change quickly. Sudden changes in PLIs are texts. In the case of the former—most relevant usually the result of fluctuations in market for this text—real expenditures (or expendi- exchange rates. When market exchange rates tures in real terms) refer to expenditures in change rapidly, a PLI for an economy could current-year prices converted to a common change rapidly as well, reflecting the fact that currency and valued at a uniform price level an economy that was relatively cheap has now with PPPs. Hence, the meaning of “real expen- become relatively expensive compared with the ditures” or “real GDP” throughout this text base economy. The volatility of market exchange should not be confused with its meaning in a rates is another reason they should not be used temporal context, where it is commonly used to to compare the size of economies. Fluctuations describe nominal expenditures or GDP adjusted in market exchange rates can make economies for inflation. 66    Purchasing Power Parities and the Size of World Economies GDP compared with gross national consumption expenditure of households does income not capture all goods and services consumed by households in all economies. However, AIC GDP measures the production by producers covers all such goods regardless of whether they who reside within an economy’s territory. The are purchased by households themselves or are income generated from such production is dis- provided as social transfers in kind by the gov- tributed mainly to residents of the economy, but ernment or NPISHs. some of the income may accrue to nonresidents The concept of actual individual consumption (such as the interest or dividends that have to dates back to the earliest years of the ICP, when be paid abroad or the cost of servicing foreign it was called the consumption expenditure of the debt). Similarly, some residents may receive population. Initially, the individual consumption income from nonresidents (such as interest or expenditure by NPISHs was not included. Later, dividends paid to residents from abroad). For however, the concept was expanded to include some types of analysis, these income flows the consumption expenditure of NPISHs, and it can be of interest, which leads to the concept was adopted by national accountants in the Sys- of gross national income (GNI). GNI measures tem of National Accounts (SNA) 1993 (UNSC the value of the incomes received by residents. 1993). In the ICP 2017, a separate PPP was It differs from GDP by the net amount of the calculated for individual consumption expen- income flows between an economy’s residents diture by households and for actual individual and the residents of other economies. consumption. In addition, PPPs belonging to the following analytical categories were calculated Actual individual consumption on the basis of actual individual consumption: health; education; housing; water, electricity, One aggregate below the level of GDP that has and other fuels; recreation and culture; and mis- particular significance in ICP comparisons is cellaneous goods and services. actual individual consumption (AIC), which measures the individual goods and services that households actually consume as opposed to what they actually purchase. AIC includes Use and applications of PPPs and the value of what households purchase (that is, real expenditures individual consumption expenditure of house- Use and limitations of PPPs and real holds) plus the value of services they receive expenditures from the government and nonprofit institutions serving households (NPISHs), such as chari- As explained in the previous section on con- ties and nongovernmental organizations. On cepts and definitions, the major use of PPPs is in a per capita basis, AIC is conceptually a better making intercountry comparisons of real GDP measure of average material well-being than and its expenditure components. GDP is the individual consumption expenditure of house- aggregate used most frequently to represent the holds alone when material well-being is defined size of an economy and, on a per capita basis, in terms of the goods and services consumed by the average income per person in that economy households to satisfy their individual needs. during a given year. Calculating PPPs is the first AIC is used because in some economies the step in the process of converting the level of government or NPISHs provide an important GDP and its major aggregates, expressed in local element of household services, such as health or currencies, into a common currency to enable education, and these expenditures are included these comparisons to be made. in the individual consumption expenditure of Anyone comparing economies by the size government or NPISHs. But in other econo- of their real GDP or their real GDP per capita mies, these same services are purchased by should do so with caution. Such comparisons households from market producers and are require that all of the economies employ the included in the individual consumption expen- same definition of GDP and that their measure- diture of households. It follows that individual ment of GDP be equally exhaustive. Although Purchasing power parities and real expenditures 67 the first requirement is broadly met because the considered significant. This margin of error can GDP estimates of most economies participating rise to plus or minus 15 percent for economies in ICP 2017 are compiled more or less in line that differ widely in their price and economic with SNA 2008 (UNSC 2009), the measure- structures. This margin of error should be kept ment of GDP is not sufficiently uniform over all in mind when using, for example, the PPPs of participants to satisfy the second requirement. Brazil, China, India, and the United States to In particular, the GDP of participants with large compare these economies not only with each nonobserved economies, such as a large infor- other but also with more disparate economies mal sector, could be underestimated. Bearing such as most of those in Africa. in mind that there may be errors in the popula- PPPs appear in international trade theory in tion data in addition to errors in the price and the context of equilibrium exchange rates (the expenditure data, small differences between underlying rates of exchange to which actual real GDP and real GDP per capita should not be market exchange rates are assumed to converge considered significant. in the long term). But ICP PPPs should not ICP 2017 includes economies ranging from be interpreted as equilibrium exchange rates. city-states, such as Singapore, and small islands, They have been calculated specifically to enable such as Grenada, to large and diverse econo- international comparisons of prices and real mies, such as Brazil, China, India, the Russian expenditures for GDP. They refer to the entire Federation, South Africa, and the United States. range of goods and services that make up GDP Because of wide differences in the price and and include many items that are not traded economic structure of economies and inherent internationally. Moreover, except for exports statistical variability in the methods used to cal- and imports, they are valued at domestic mar- culate PPPs, the following guidelines are recom- ket prices, and PPPs for GDP are calculated mended for analyses using the 2017 PPPs and using expenditure weights that reflect domestic real expenditures. demand. For the same reason, ICP PPPs do not indicate whether a currency is undervalued • Comparisons between economies that are or overvalued and should not be used for this similar are more precise than comparisons purpose. between economies that are dissimilar. For ICP comparisons are designed to compare the example, the PPP between Nigeria and South volumes of goods and services that enter GDP Africa is more precise than the PPP between at specific points in time. They are not designed either economy and Liberia or Zimbabwe. to measure the relative rates of growth in GDP Comparisons between economies in the between these points. Each ICP comparison same region are more precise than compari- produces indexes of real GDP that show the sons between economies in other regions. relative volume levels of GDP among partici- For example, the China-India comparison is pating economies for the reference year. When more precise than the comparison of either the indexes for consecutive reference years to the United States. are placed side by side, they appear to provide • PPPs based on the prices of goods are more points in a time series of relative volume levels precise than PPPs based on the prices of ser- of GDP over the intervening years. This appar- vices. Areas such as housing and health care ent time series of volume measures is actually a will have wider measures of error than areas time series of value indexes because the volume such as food. indexes for each reference year are calculated using the prices and expenditures for that year. • PPPs provide the overall price level of an Changes in the volume indexes between ref- economy, but they do not capture price dif- erence years are thus due to changes in the ferences within an economy. relative price levels as well as to changes in the Because of the sampling and statistical errors relative volume levels. As a result, the rates of arising from the calculation methods, differences relative growth derived from the indexes are in real GDP of less than 5 percent should not be not consistent with those obtained from times 68    Purchasing Power Parities and the Size of World Economies series of GDP volumes estimated by the econo- prices for the economy as a whole and not on mies themselves. The rates of growth estimated the prices faced by the poor in that economy. In by the economies should be used to determine response, some attempts have been made to use relative rates of growth in GDP. the consumption patterns of the poor to calcu- The PLIs for individual consumption expen- late poverty-specific PPPs. Most of these studies diture by households provide a measure of have concluded that these poverty-specific PPPs differences in the cost of living between econo- are not significantly different from the ICP PPPs mies—that is, they indicate whether the overall for individual consumption expenditures by price level for consumer goods and services households. Regarding the prices faced by the faced by the average household in one economy poor, if these were systematically different from is higher or lower than that faced by the aver- the average prices in a way that differed from age household in another economy. Even so, one economy to another—for example, if one people considering moving from one economy of the economies had extensive food subsidies to another should not use these PLIs to infer so that the poor pay lower prices—then the PPPs how the change of economy will affect their cost generated by the ICP are less suitable for mea- of living. For one thing, PLIs reflect the expendi- suring poverty. However, this approach has not ture pattern of the average household, which in yet been explored in detail, as studying it fully all likelihood is different from that of the person would likely require a separate price collection, contemplating the move. For another, PLIs are parallel to the ICP. national averages and do not reflect differences Box 3.2 summarizes the recommended uses in the cost of living between specific locations of PPPs, the uses of PPPs with limitations, and within an economy. the instances where the use of PPPs is not Global poverty numbers require a large and recommended. varied set of inputs from different data sources. Five unique data sources are required for the Main applications of PPPs and real World Bank’s calculation of global poverty num- expenditures bers: household income and expenditure sur- veys, population data, national accounts, con- PPPs, and the PLIs and real expenditures to sumer price indexes, and ICP PPPs for individual which they give rise, are used for research consumption expenditures by households. Each and analysis, for index compilation, for policy new ICP cycle brings revisions of the PPPs, making, and for administrative purposes at the and these revisions, like revisions of the other global, regional, and national levels. data sources, can have large effects on global, They are used across a range of themes under regional, and national poverty counts stemming the economic, environmental, and social devel- from a common international poverty line. ICP opment umbrellas. Users include international PPPs for individual consumption expenditures bodies such as the World Bank, the International by households are based on the patterns of Monetary Fund (IMF), the United Nations and aggregate household consumption provided by its affiliates, the Organisation for Economic Co- an economy’s national accounts. The use of operation and Development (OECD), the Euro- these PPPs for measuring global poverty has pean Commission, and regional organizations sometimes been criticized on the grounds that such as the African Development Bank (AfDB), people who live at or below the global poverty the Asian Development Bank (ADB), and the line have different patterns of consumption Interstate Statistical Committee of the Com- than those provided by national accounts aggre- monwealth of Independent States (CIS-STAT). gates. In particular, they spend a much larger Additionally, there has been a rapid growth in share of their budgets on food, and they spend their use by the media, with frequent articles very little on housing and essentially nothing mentioning PPPs, by the private sector, and by at all on air travel or on financial services indi- national governments. Universities and research rectly measured. A second common criticism is institutes have long applied PPPs and ICP data in that ICP PPPs are compiled based on average their academic analyses. Purchasing power parities and real expenditures 69 Box 3.2  Use of purchasing power parities Recommended uses 1.  To make spatial comparisons of Gross domestic product (GDP): relative size of economies •  GDP per hour worked: labor productivity •  GDP per capita: income per capita •  Actual individual consumption (AIC) per capita: a measure of average material •  well-being 2.  To make spatial comparisons of price levels 3.  To group economies by their Volume index of GDP or AIC per capita •  Price levels of GDP or AIC. •  Recommended uses with limitations 1.  To analyze changes over time in relative GDP per capita and relative prices 2.  To analyze price convergence 3.  To make spatial comparisons of the cost of living 4.  To use PPPs calculated for GDP and its expenditure components as deflators for other values—as, for example, household income. Uses not recommended 1.  As a precise measure to establish strict rankings of economies 2.  As a means of constructing national growth rates 3.  As a measure to generate output and productivity comparisons by industry 4.  As an indicator of the undervaluation or overvaluation of currencies 5.  As an equilibrium exchange rate. PPPs are used as inputs for economic research prosperity, economic growth, trade and com- and policy analysis that involve comparisons of petitiveness, sustainable development, human economies. In this context, PPPs are employed development, health, education, labor pro- either to generate measures of real expenditure ductivity and wages, the environment, energy, with which to compare the size of economies climate, waste, information and communica- and their levels of consumption, investment, tion technology, and peace and conflict. PPP- government expenditure, and overall produc- converted GDP is used to standardize other tivity or to generate price measures with which economic variables such as carbon emissions to compare price levels, price structures, price per unit of GDP, energy use per unit of GDP, convergence, and competitiveness. GDP per employee, or GDP per hour worked. GDP and GDP per capita measured in PPPs Multinational corporations, for example, use are used in many socioeconomic analyses PPPs to evaluate the cost of investment in dif- covering topics such as poverty and shared ferent economies. 70    Purchasing Power Parities and the Size of World Economies The United Nations’ 2030 Agenda for Sus- mothers who die in childbirth, and the modeled tainable Development covers many of the topics indicator used to monitor this is PPP-converted listed above, and the wide use of PPPs in many GDP. Target 3.8 looks at achieving universal of the agenda’s goals—the Sustainable Develop- health coverage, and analyses exploring this use ment Goals (SDGs)—reflects the importance PPPs to compare out-of-pocket expenditures and relevance of this indicator for monitoring on health in different countries as well as the progress. PPPs are used for monitoring how far number of people pushed below the poverty line the world has come in achieving no poverty by catastrophic expenditures. SDG 4 compares (SDG 1); zero hunger (SDG 2); good health and expenditures by both government and house- well-being (SDG 3); quality education (SDG 4); holds on education using PPPs. SDG 7 tracks affordable and clean energy (SDG 7); decent energy efficiency by measuring the amount of work and economic growth (SDG 8); better energy used to produce one dollar’s (in PPPs) industry, innovation, and infrastructure (SDG 9), worth of goods and services. SDG 8 uses PPP- and reduced inequalities (SDG 10). converted GDP per person employed to moni- One major use of PPPs is for poverty assess- tor economic productivity. In SDG 9, target 9.4 ment using the World Bank’s international monitors progress toward sustainable, efficient, poverty line of $1.90 per day per person, which and clean industry and measures carbon dioxide is used in SDG 1. National poverty assessments emissions per unit of PPP-converted GDP. Target differ because the purchasing power of local 9.5 encourages scientific innovation and moni- currency units differs from one economy to tors spending on research and development using another. Therefore, establishing an interna- PPPs. SDG 10 monitors growth in the income of tional poverty line requires equalizing purchas- the poorest citizens and uses PPPs to compare per ing power over economies. The current interna- capita consumption and income for the poorest tional poverty line of $1.90 per day is converted 40 percent against the national average. to national price levels by using the ICP 2011 The World Bank’s twin goals of ending pov- PPPs for individual consumption expenditure by erty and boosting shared prosperity mirror SDGs households. Data from household income and 1 and 10 and thus also rely on PPPs. expenditure surveys are then used to determine Beyond the SDGs, other notable uses include the number of people whose consumption per the United Nations Development Programme’s capita is below this poverty line. The interna- Human Development Index, which measures tional poverty line itself has typically been cal- average achievement in three basic dimensions culated as the average of the PPP equivalents of of human development—a long and healthy the national poverty lines of some the world’s life, knowledge, and a decent standard of living. poorest economies, using PPPs for individual The index uses PPPs in income, economy, pov- consumption expenditure by households. The erty, and environmental composite measures. PPPs thus enter the calculation at two stages: The World Economic Forum’s Global Com- first, in establishing the international poverty petitiveness Index uses GDP and the value of line; and second, in calculating the number of imports measured using PPPs in its 10th pillar people living below it in each economy—the on market size. poverty headcount. People living below the The World Bank also uses PPPs to facilitate $1.90 a day line represent the extreme poor. comparisons of public service pay and wage bill Other international poverty lines are based data across countries. Other examples of using on income and consumption levels in lower- PPPs as spatial price deflators include cross- middle-income ($3.20) and upper-middle- country comparisons of the value of unpaid care income ($5.50) economies measured using ICP work, minimum wages, user revenue for inter- 2011 PPPs. net providers, the cost of violence and natural SDG 2 focuses on agricultural productivity. disasters, the cost of disease and potential sav- PPPs are used to define the revenue of small-scale ings through reduced child mortality, and better producers as well as to measure output and indi- nutrition and other medical interventions. viduals’ income derived from farming. In SDG 3, PPPs are also used for statistical compilation. target 3.1 seeks to reduce the proportion of International organizations use PPPs to obtain Purchasing power parities and real expenditures 71 totals and averages for a group of economies weight of 40 percent to the economic weight, such as a region or income group. Real GDP which in turn provides a weight of 80 percent to and its components are aggregated across the the total, the remainder coming from a measure economies in a group to obtain totals for the of contributions to the International Develop- group. The shares of economies in these totals ment Association. are used as weights when economic indicators, In addition to these applications of PPPs and such as price indexes or growth rates, are com- other ICP indicators, the data collected by the bined to obtain averages for the group. Both ICP on prices and expenditures support various the IMF and the OECD use PPP-based GDP and analyses by policy makers and researchers from GDP aggregates to provide estimates of regional international, regional, and national agencies and world output and growth in their respec- as well as from academic and research institu- tive publications, World Economic Outlook and tions. Examples include analysis of the cost of Economic Outlook. nutritional food and recommended diets around Finally, the European Commission, the IMF, the world, the cost of living for foreign service and the World Bank employ PPPs for admin- staff living overseas, consumption patterns and istrative purposes. The European Commission income elasticities, the effect of prices on the uses the PPPs of its member states when allocat- share of expenditure on housing, the price ing the structural funds intended to reduce eco- of traditional goods and skill-intensive goods nomic disparities between and within member against GDP per capita, trade elasticity, and wage states. The principal indicator influencing the inequality indexes, to name but a few. Hence, allocation is PPP-deflated intracountry regional the detailed data sets generated by the ICP make GDP per capita. The IMF uses PPP-based GDP an important contribution to the overall value from the World Economic Outlook in its current of the program. The ICP Global Office has estab- quota formula. In the past, this measure often lished a set of rules governing access to unpub- helped to guide increases in members’ quotas. lished results and underlying data. The resulting Quota subscriptions determine the maximum data access and archive policy (described in financial resources that member economies appendix H) meets a long-standing objective of are obliged to provide the IMF, the amount of the ICP: that data derived from the ICP should financing that members can obtain from the be used to the maximum extent possible for sta- IMF, their share in a general allocation of Special tistical, research, and analytical purposes. Drawing Rights, and their voting power in IMF The applications of PPPs and underlying data decisions. PPP-based GDP has a weight of 20 continue to expand as the limitations of the percent in the current quota formula. Similarly, main alternative method of adjusting values to a the World Bank Group now incorporates PPPs common currency using market exchange rates into its dynamic formula for computing the become more widely recognized. As these data shareholding rights of the International Bank and indicators are produced more frequently for Reconstruction and Development member and for an expanding number of economies, countries, with PPP-based GDP contributing a their use is likely to accelerate. 72    Purchasing Power Parities and the Size of World Economies CHAPTER 4 Governance and organization Governance of ICP 2017 with ICP 1993, in which the regional compari- sons could not be combined to produce a global The International Comparison Program (ICP) comparison. The findings of the review were was established in the late 1960s on the rec- reported to the UNSC in 1999. Among the prin- ommendation of the United Nations Statistical cipal shortcomings identified were the lack of a Commission (UNSC). It began as a research formally defined governance structure and the project carried out jointly by the United Nations consequent poor coordination between regions. Statistical Office (UNSO) and the University of Methods, processes, and timetables were not Pennsylvania. It is now a permanent element uniform across regions; results were not consis- of the Global Statistical Programme, run under tent between regions; and there was no blue- the auspices of the UNSC, supported by a fed- print for linking the regional comparisons. erated governance structure, and coordinated As a result of the review, the World Bank and carried out by implementing agencies at put in place in 2002 a governance structure to the national, regional, and global levels. To ensure that each region produced results consis- date, nine comparisons have been conducted. tent with the results of other regions and that The first was in 1970 (covering 10 economies), each region’s results could be combined with the followed by 1973 (16 economies), 1975 (34 results of other regions in a global comparison. economies), 1980 (60 economies), 1985 (64 This goal was to be achieved by coordinating economies), 1993 (115 economies), 2005 (146 the work globally, establishing a single set of economies), 2011 (199 economies), and 2017 standards, providing centralized technical and (176 economies). After the 1975 comparison, practical guidance, and ruling on issues that had the ICP shifted from being a research project to the potential to be interpreted in different ways being a regular operational component of the in the regions. The structure had several tiers: UNSO work program. It was also regionalized, the UNSC, the Executive/Governing Board, the whereby comparisons were organized by region ICP Global Office, the Technical Advisory Group and then combined to obtain a global compari- (TAG), the regional implementing agencies, son. Details of the history of the ICP are given in and the national implementing agencies. This appendix A and on the ICP website.1 strengthened governance contributed signifi- The UNSC commissioned a major review cantly to the successful conclusion of the 2005 of the ICP in 1997, before agreeing to further and 2011 comparisons and the timely publica- cycles. This review was in response to problems tion of their results. 73 Figure 4.1  ICP governance structure UNITED NATIONS STATISTICAL COMMISSION ICP GOVERNING BOARD ICP Inter-Agency Coordination Group Global WORLD BANK Technical Implementing (ICP Global Office) IMF Agency Advisory Group and Regional task forces CIS- UN- UN- Eurostat Implementing AfDB ADB STAT ECLAC ESCWA and OECD Agencies National Asia Common- Latin wealth of America Western Eurostat- Implementing Africa and the Independent and the Asia OECD Agencies Pacific States Caribbean Note: AfDB = African Development Bank. ADB = Asian Development Bank. CIS-STAT = Interstate Statistical Committee of the Commonwealth of Independent States. UN-ECLAC = United Nations Economic Commission for Latin America and the Caribbean. UN-ESCWA = United Nations Economic and Social Commission for Western Asia. Eurostat = Statistical Office of the European Union. OECD = Organisation for Economic Co-operation and Development. IMF = International Monetary Fund. In November 2016, the ICP Governing Board Regional and national adopted an updated ICP governance framework. organization In place for the ICP 2017 cycle, this framework’s overall mandate was to ensure that the global, To calculate PPPs, the ICP conducts worldwide regional, and national efforts to produce reliable surveys at regular intervals to collect compa- purchasing power parity (PPP) estimates and rable price and expenditure data for the whole related measures of real expenditures adhere range of final goods and services that make up to approved policies, protocols, methodologies, the final expenditure on GDP: consumer goods and quality assurance standards, and that the and services, government services, and capital estimates are produced efficiently, in keeping goods. While the ICP global comparison is coor- with available resources. dinated through the Global Office at the World The framework outlines the current gov- Bank, the surveys are carried out by national ernance structure and the roles and responsi- implementing agencies, such as the national sta- bilities of the governance bodies. These include tistical office, and overseen by a regional imple- the UNSC; the Governing Board; the TAG; the menting agency. The intention is to produce ICP Global Office; the Inter-Agency Coordi- regional comparisons that can be combined into nation Group (IACG), comprising the World a single global comparison for a given reference Bank, the regional implementing agencies, and year. the International Monetary Fund (IMF); and Conducting the surveys on a regional basis the national implementing agencies. Figure ensures that the items to be priced are more 4.1 depicts the ICP governance structure. The homogeneous within regions, expenditure pat- governance bodies meet periodically to discuss terns are likely to be similar, and language issues and move the program forward. Details of obstacles are reduced. In addition, there are their activities are available on the ICP website.2 operational advantages in having the ICP car- More details on the governance framework and ried out by regional agencies that are in rela- its bodies are given in appendix B. tively close proximity to the economies they are 74    Purchasing Power Parities and the Size of World Economies coordinating. In 2017 the six regional programs Commission for Western Asia (UN-ESCWA). were as follows3: Africa region, coordinated by Member states and associated economies of the the African Development Bank (AfDB); Asia European Union and the Organisation for Eco- and the Pacific region, overseen by the Asian nomic Co-operation and Development (OECD) Development Bank (ADB); the Commonwealth are covered by the Eurostat-OECD PPP Pro- of Independent States region, run by the Inter- gramme. Georgia and Ukraine were included state Statistical Committee of the Common- in the Eurostat-OECD PPP Programme as spe- wealth of Independent States (CIS-STAT); Latin cial participants. The Islamic Republic of Iran America and the Caribbean region, overseen by was also included as a special participant in the the United Nations Economic Commission for global exercise, linked through the Western Asia Latin America and the Caribbean (UN-ECLAC) region. Uzbekistan participated on a limited and with support from the Caribbean Community experimental basis within the Commonwealth of (CARICOM); and Western Asia region, coordi- Independent States region. Box 4.1 lists all par- nated by the United Nations Economic and Social ticipating economies by region for the 2017 cycle. Box 4.1  ICP 2017 cycle: Participating economies, by region Africa: 50 economies Regional implementing agency: African Development Bank (AfDB) Algeria; Angola; Benin; Botswana; Burkina Faso; Burundi; Cameroon; Cabo Verde; Central African Republic; Chad; the Comoros; the Republic of Congo; the Democratic Republic of Congo; Côte d’Ivoire; Djibouti; Arab Republic of Egypt;a Equatorial Guinea; Eswatini; Ethiopia; Gabon; The Gambia; Ghana; Guinea; Guinea-Bissau; Kenya; Lesotho; Liberia; Madagascar; Malawi; Mali; Mauritania; Mauritius; Morocco;a Mozambique; Namibia; Niger; Nigeria; Rwanda; São Tomé and Príncipe; Senegal; the Seychelles; Sierra Leone; South Africa; Sudan;a Tanzania; Togo; Tunisia; Uganda; Zambia; Zimbabwe Asia and the Pacific: 22 economies Regional implementing agency: Asian Development Bank (ADB) Bangladesh; Bhutan; Brunei Darussalam; Cambodia; China; Fiji; Hong Kong SAR, China; India; Indonesia; Lao People’s Democratic Republic; Malaysia; the Maldives; Mongolia; Myanmar; Nepal; Pakistan; the Philippines; Singapore; Sri Lanka; Taiwan, China; Thailand; Vietnam Commonwealth of Independent States: 8 economies Regional implementing agency: Interstate Statistical Committee of the Commonwealth of Independent States (CIS-STAT) Armenia; Azerbaijan; Belarus; Kazakhstan; Kyrgyz Republic; Moldova; Russian Federation;a Tajikistan Latin America and the Caribbean: 36 economies Regional implementing agency: United Nations Economic Commission for Latin America and the Caribbean (UN-ECLAC) Argentina; Bolivia; Brazil; Dominican Republic; Ecuador; El Salvador; Guyana; Haiti; Honduras; Nicaragua; Panama; Paraguay; Peru; and Uruguay. Anguilla; Antigua and (continued) Governance and organization 75 Box 4.1  (Continued) Barbuda; Aruba; The Bahamas; Barbados; Belize; Bermuda; Bonaire; Cayman Islands; Curaçao; Dominica; Grenada; Jamaica; Montserrat; St. Kitts and Nevis; St. Lucia; St. Vincent and the Grenadines; Sint Maarten; Suriname; Trinidad and Tobago; Turks and Caicos Islands; British Virgin Islands Western Asia: 12 economies Regional implementing agency: United Nations Economic and Social Commission for Western Asia (UN-ESCWA) Bahrain; Arab Republic of Egypt;a Iraq; Jordan; Kuwait; Morocco;a Oman; Qatar; Saudi Arabia; Sudan;a United Arab Emirates; West Bank and Gaza Europe and Organisation for Economic Co-operation and Development (OECD): 49 economies Implementing agencies: Eurostat and OECD Albania; Australia; Austria; Belgium; Bosnia and Herzegovina; Bulgaria; Canada; Chile; Colombia; Costa Rica; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Hungary; Iceland; Ireland; Israel; Italy; Japan; the Republic of Korea; Latvia; Lithuania; Luxembourg; Malta; Mexico; Montenegro; the Netherlands; New Zealand; North Macedonia; Norway; Poland; Portugal; Romania; the Russian Federation;a Serbia; Slovak Republic; Slovenia; Spain; Sweden; Switzerland; Turkey; United Kingdom; United States Special participation: 3 economies Georgia; the Islamic Republic of Iran; Ukraine a. Dual-participation economies. Notes 1. See icp.worldbank.org/programs/icp#2. 2. See icp.worldbank.org/programs/icp#3. 3. See icp.worldbank.org/programs/icp#4. 76    Purchasing Power Parities and the Size of World Economies CHAPTER 5 Methodology The International Comparison Program (ICP) the methodology used to compute purchasing is a complex international statistical exercise, power parities (PPPs), first within regions for the and its methodology has evolved over several regional comparisons and then across regions decades. for the global comparison. The 2011 cycle of the ICP introduced sev- Each ICP comparison has a reference year, eral major methodological innovations, includ- such as 2005, 2011, and 2017. Each participat- ing a new approach for combining regional ing economy provides the following required results into a global set of results, a simplified data for the reference year: a set of prices for approach for comparing the construction and a selection of items chosen from a common civil engineering component of gross domestic basket of precisely defined goods and services, product (GDP), a wider application of produc- a detailed breakdown of the national accounts tivity adjustment to government labor, and expenditures in local currency units, accord- the implementation of enhanced data quality ing to a common classification, the economy’s assurance and computation procedures. The market exchange rates, and its resident popula- 2017 cycle maintained the same methods and tion. The prices and expenditures are used to procedures applied in the 2011 cycle, further calculate PPPs and real expenditures (or vol- strengthened data quality assurance approaches umes—that is, PPP-converted expenditures); using the latest technology, and introduced a the market exchange rates and PPPs are used to fully documented and more transparent process calculate price level indexes; and the population for producing results. totals and real expenditures are used to calculate Overall, the ICP methodology has three major real expenditures per capita. Prices and expen- components. The first is the System of National ditures are reported by participating economies Accounts (SNA) definition of final expenditures in their local currencies. Both cover the whole on GDP. The second is the basket of goods and range of final goods and services constituting services from which items are selected for pric- the GDP. ing: these items should be comparable across The ICP methodology is documented in Mea- economies and should represent an important suring the Real Size of the World Economy: The part of each economy’s final purchases. The Framework, Methodology, and Results of the Inter- national annual average prices or related data national Comparison Program (World Bank 2013); collected for these goods and services must in Operational Guidelines and Procedures for Mea- be consistent with the underlying values in suring the Real Size of the World Economy (World the national accounts. The third component is Bank 2015); and on the ICP website.1 A brief 77 overview of the ICP’s conceptual framework, relevant expenditure components identified in data requirements, and PPP computation meth- the ICP expenditure classification. odology follows. At the lowest level of the classification, the expenditure components are termed basic head- ings. The classification breaks down the expen- Conceptual framework diture on final goods and services into 155 basic headings that comply with the functional and The conceptual framework for an ICP com- product classifications of SNA 2008 and are the parison is determined by the definition of GDP. building blocks of the ICP comparison. They are The ICP 2017 cycle adopted the internationally the level at which expenditures are defined and agreed-on definition of GDP provided by SNA estimated, items are selected for pricing, and 2008 as its framework for the common ICP prices are collected. Basic headings are the level expenditure classification.2 The previous 2005 at which PPPs are first calculated. and 2011 cycles used the definition of GDP pro- In principle, a basic heading consists of a vided by SNA 1993.3 group of similar well-defined goods or services. The SNA defines GDP from the expendi- In practice, a basic heading is defined by the ture side as the sum of expenditures on final lowest level of final expenditure for which the consumption, gross capital formation, and net participating economies can estimate explicit exports. Final consumption is the total expen- expenditures. Consequently, basic headings can diture on the goods and services consumed by cover a broader range of goods or services than individual households or the community to is theoretically desirable. satisfy their individual or collective needs. Gross capital formation is the total expenditure on gross fixed capital formation, changes in inven- Expenditure data validation tories, and acquisitions less disposals of valu- National accounts data validation requires three ables. Net exports are the difference between stages: first, intracountry validation carried out the value of goods and services exported and by the individual participating economies; sec- the value of goods and services imported. ICP ond, intercountry validation carried out at the comparisons are based largely on PPPs calcu- regional level; and third, interregional valida- lated using prices collected for the expenditure tion carried out at the global level. components of final consumption and gross Before the national accounts expenditure fixed capital formation. Prices are not collected data are sent to the regional offices, basic edits for changes in inventories, the acquisition and are carried out by the national implementing disposal of valuables, or net exports because agencies. These include: they are deflated using reference PPPs. • Ensuring SNA compliance, including data completeness, applicability of positive and Expenditure data negative values, and additivity • Ensuring the correct estimation of financial The data on national expenditures in local cur- intermediation services indirectly measured rency provided by the participating economies (FISIM), net purchases abroad, and nonprofit are essential to the ICP comparison. First, they institutions serving households (NPISHs). are used as weights to aggregate PPPs through the various levels of aggregation up to GDP. Furthermore, an economic plausibility assess- Second, they are ultimately deflated by the PPPs ment, such as verifying per capita basic-heading and expressed as real expenditures. expenditures and basic-heading shares of GDP, is also advised. The validation edits carried out at the national Expenditure data compilation level are repeated at the regional level. The aim Economies are expected to estimate their GDP of the regional validation is to compare the con- for the reference year in line with SNA 2008 sistency of data from similar economies within and to disaggregate this GDP estimate into the a region. The regional implementing agency 78    Purchasing Power Parities and the Size of World Economies identifies clusters of economies based on their as brand specific and not brand specific—that economic similarities. GDP per capita in previ- is, generic—items with the same characteristics. ous years serves as a key indicator of the cluster The construction and civil engineering sur- to which an economy is allocated. vey is based on a list of common resources for The global comparison of real expenditures construction work, including materials, equip- (and their per capita equivalents) is achieved by ment hire rates, and labor costs. In addition, linking regional results to form a global set of respondents are required to provide information results. At the global level, the same intracoun- on resource mixes, typical markups, and profes- try validation processes as previously defined are sional fees. followed. The intercountry validation process is For each of these surveys there is a global also followed across economies and within and core list (GCL) of items, prepared in consultation between regions. with regional and national implementing agen- cies and based on previous ICP cycles to main- tain temporal comparability. In addition, each Price data region develops its own list of regional items for the regional comparison, which includes region- Economies participating in the ICP collect prices specific items representative of the consump- for a selection of the goods and services that tion pattern in the region, as well as GCL items make up final consumption expenditure and needed to facilitate linking the regional results gross capital formation. There are four main to form a global set of results. surveys: All prices reported are national annual aver- age prices, in local currency, for the reference • Household consumption year—that is, they should be the average of the • Government consumption prices collected at regular intervals throughout • Machinery and equipment the year. When price surveys are conducted • Construction and civil engineering. outside the reference year, prices are retropo- lated or extrapolated based on consumer price The household consumption survey covers index (CPI) data. the largest expenditure share, accounting for more than 60 percent of GDP in the majority of economies. It includes a wide assortment of Household consumption goods and services purchased by households Household consumption survey for individual consumption. This survey also This main survey collects prices for a wide range includes two additional surveys that are treated of goods and services for household consump- separately due to different data requirements; tion such as food, beverages, tobacco, cloth- these are the private education and housing ing, footwear, utilities, furniture, household surveys. appliances, pharmaceuticals, private health care The government consumption survey com- services, motor vehicles, transportation services, piles administrative or survey data on the com- electronic equipment, communication services, pensation of public employees in a variety of catering services, accommodation services, rec- collective services, public health services, and reational activities, personal hygiene, and other public education services. This selection of gov- goods and services. For this survey, each econ- ernment occupations represents the various omy classifies the items priced as important or education and skills levels that are commonly less important for the consumption patterns of found among employees working in these three its inhabitants. government sectors. The machinery and equipment survey is Private education survey based on a list of industrial, transportation, and This survey collects annual tuition prices for electronic items commonly used in a variety private education institutions at the primary, of industries for the production of goods and secondary, and tertiary levels as well as other services. The items on this list are often paired education services, such as foreign language and Methodology 79 private tutoring. The private education survey adjust the quantity measure when converting was not conducted by the Eurostat–Organisation it into a real expenditure (volume) measure. for Economic Co-operation and Development Therefore, for the dwelling stock approach, the (OECD) PPP Programme, which instead follows housing survey collects data on both the quan- an output approach for total education. tity and quality of the dwelling stock. Housing survey and related data Government consumption This survey collects annual rental prices or dwelling stock data for housing services. Four This survey collects prices for the compensation basic headings within the ICP expenditure clas- of government employees, which comprises the sification require data on rentals: basic salary or wage, allowances and cash pay- ments over and above the basic salary or wage, • Actual rentals for housing income in kind, and the employer’s actual and • Imputed rentals for housing imputed social security contribution. The sources • Housing under individual consumption of the data reported are the administrative expenditures by NPISHs government pay scales for each of the selected • Housing under individual consumption occupations or dedicated surveys on the com- expenditures by government. pensation of government employees. The GCL defines these occupations using job descriptions Since these last two basic headings use ref- taken from the International Labour Organiza- erence PPPs derived from the first two basic tion’s International Standard Classification of headings listed, it is sufficient to focus on how Occupations 2008. to compute PPPs for actual and imputed rent- als. Actual rents are the rents that tenants pay to the owner of the dwelling they are leasing. Gross fixed capital formation Imputed rents are estimates of the rents that Machinery and equipment owner-occupiers would have to pay for their This survey collects prices for machinery and dwelling were they renting rather than owning equipment typically used in a variety of indus- the dwelling. The SNA requires that households’ tries. The GCL includes one item identified by housing expenditures include both the actual brand and model and another generic item with expenditure on rents and an estimate of the rent the exact same characteristics, but not identi- that the owners would have to pay if they were fied by brand and model. For consistency with obliged to rent (imputed rents). national accounts, prices for equipment goods The PPPs for housing services can be cal- that are consistent with the valuation of those culated either directly, using the rental (price) goods as fixed capital assets in the national approach, or indirectly, using the dwelling stock accounts are required. Thus the prices must (volume) approach. The survey was designed to include the import duties and other taxes actu- collect data for both approaches. ally paid by the purchaser, the costs of transport- Under the rental approach, rental prices ing the asset to the place where it will be used, are collected for similar dwelling types in each and any charges for installing the asset so that economy. This method has been found to work it will be ready for use in production. Deducted well in economies in which the dwellings actu- from the price are the discounts generally avail- ally rented are representative of the stock of able to most purchasers. dwellings as a whole and where statistical agen- cies collect information on rents paid for the dif- Construction and civil engineering ferent kinds of dwellings that are rented in most This survey collects prices for inputs to con- parts of the economy. struction work, including materials, equipment Under the dwelling stock approach, it is nec- hire, and labor. The prices provided are those essary to calculate both a measure of relative paid by construction contractors to their sup- quantity and a measure of relative quality of pliers. For materials, these are typically the housing services. The quality measure is used to prices paid, after discounts, to manufacturers or 80    Purchasing Power Parities and the Size of World Economies intermediaries (agents or merchants), includ- unambiguously in the outlets they visit. Any ing all nonrecoverable taxes and excluding all difficulties arising with each price survey should recoverable taxes such as a value added tax. be documented and reflected in the design and For equipment, prices are the rental charges conduct of future surveys. paid to hire companies or internal hire rates. For labor, these reflect the cost to the contrac- tor of employing workers. In addition, resource PPP calculation and estimation weights for each input component (materials, equipment hire, labor) for typical residential, In general, price relatives are first computed at nonresidential, and civil engineering projects the individual item level within each basic head- are collected. ing for each pair of economies being compared. Suppose three economies—A, B, and C—price two kinds of rice under the rice basic heading. Price data validation For each kind of rice, there are three price rela- Validation procedures are an iterative process tives: PB/PA, PC/PA, and PC/PB. The basic-heading carried out at the national, regional, and global PPP for each pair of economies can be computed levels to ensure data quality and comparability directly by taking the geometric mean of the across all participating economies. price relatives between them for the two kinds The validation process comprises three dis- of rice. This is a bilateral comparison. The PPP tinct stages. The first is the intracountry or between economies B and A can be computed national validation stage, during which the indirectly: PPP C/A × PPP B/C = PPP B/A. The use prices collected by a single economy are edited of both direct and indirect PPPs is a multilateral and verified. The second is the intercountry comparison. This means that the PPPs between or regional validation stage, during which the any two economies are affected by their respec- prices collected by all economies participating in tive PPPs with other economies in the com- a regional comparison are edited and verified. parison. As a result, a change in the mix of The third is the interregional, or global, valida- economies included in the comparison will also tion stage, during which the prices that have change the PPPs between any two economies. been collected for global core items from the Different methods can be used to compute GCL and have already been edited and verified multilateral PPPs. The choice of method is within regions during the intercountry valida- based on two basic properties: transitivity and tion are edited and verified across all economies base country invariance. PPPs are transitive and all regions. when the PPP between any two economies is This process is repeated over several rounds, the same whether it is computed directly or since changes and revisions to price data from indirectly through a third economy. PPPs are one economy impact the PPPs calculated for base country invariant if the PPP between any all other economies. Once errors are found and two economies is the same regardless of the corrected, overall results need to be recalculated choice of base economy. These properties apply and a new validation round begins. The new for every computational step: computing basic- results, once cleared of major errors, may reveal heading PPPs between economies, aggregating mistakes that were not previously detected. This basic-heading PPPs to the within-region GDP process repeats itself until the final price data are PPPs, linking PPPs across regions, and finally deemed reliable. computing global PPPs. It should be stressed that validation proce- Another property underlying the compu- dures are complementary to good survey prac- tational steps to obtain PPPs is that econo- tices. Data quality depends to a large extent on mies are treated equally regardless of the size the design and management of each price sur- of their GDP. Weights based on basic-heading vey. Price collections must be planned carefully, expenditures are used in the methodology to carried out efficiently, and supervised properly. weight a group of basic headings to an aggregate Item specifications must be sufficiently detailed level. Therefore, PPPs are first weighted using to enable price collectors to identify items economy A’s weights (Laspeyres index) and Methodology 81 then weighted again using economy B’s weights known as the country product dummy (CPD) (Paasche index). Each index provides a weighted method, which directly estimates PPPs that are average of the PPP between economy A and transitive and base-country invariant in one economy B. To maintain symmetry, the geomet- step. The results obtained by both methods are ric mean is taken of the two aggregated PPPs for the same if every economy prices every item. every pair of economies in the comparison. The Both methods can be modified to include result is the Fisher index. For each pair of econo- weighting at the item level. As there are no mies, the multilateral PPP is the geometric mean expenditure weights below the basic-heading of the direct and indirect Fisher indexes. level, participating economies are asked to use This method, however, does not satisfy the their expert judgment to determine which items additivity requirement. Additivity occurs when would have the largest expenditure shares the sum of the real expenditures of the basic within each basic heading. For instance, if bas- headings constituting an aggregate equals the mati rice is deemed to be important within the real expenditures based on the PPPs for the rice basic heading, then basmati rice will have aggregate. Additive methods have the disadvan- a higher weight in the PPP calculation for that tage of giving more weight to the relative prices economy. This weighting at the item level is of the larger, more developed economies. As a only applied in the household consumption sur- result, the real expenditures of poor economies vey. The modified methods are simply known as become artificially larger and move closer to GEKS* and weighted CPD (CPD-W). However, the real expenditures of rich economies. This is the results provided by the two methods differ. known as the Gerschenkron effect. For the uses This is because these methods provide different of ICP PPPs, such as for poverty analysis, non- results in their unweighted form, and in addi- additive methods that avoid the Gerschenkron tion the GEKS* method assigns a weight of 1 to effect are preferred. the most important items and a weight of zero Fixity is yet another concept that determines to the least important items, while the CPD-W the methods used. The fixity concept means method assigns weights of 3 and 1, respectively. that the relative volume—the ratio of real expenditures—between any pair of economies in a region remains the same after the regional Reference PPPs results have been combined into a set of global For some basic headings, expenditure data exist, results including all economies. but price collection is considered too expensive or time-consuming or the price data are unreli- PPP estimation at the basic-heading level able. For these basic headings, reference PPPs are used, and they can be categorized as follows: The PPP estimation process begins with the par- ticipating economies collecting prices for items • Price-based reference PPPs, specific or neutral chosen from a common list of precisely defined • Market exchange rate reference PPPs. items. These common lists include both regional items, priced in a specific region, as well as Price-based reference PPPs form the majority global core items as set out in the GCL, priced in of all reference PPPs used. They are based on all ICP regions. These two sets of prices cover the the PPPs of other basic headings for which prices whole range of final goods and services included were collected. These PPPs are referred to as in GDP: household consumption expenditures, specific reference PPPs. They may be the PPPs for government consumption expenditures, and a single basic heading or an average of the PPPs gross capital formation expenditures. for several basic headings. In the latter case, Two basic methods are used in the ICP to they will be GEKS averages of the selected PPPs calculate basic-heading PPPs. The first approach weighted by expenditure shares. In other cases, is based on the Jevons index made transitive by reference PPPs are the PPPs of a large group of the Gini-Éltető-Köves-Szulc (GEKS) method, basic headings, such as all the basic headings which transforms bilateral PPPs into multilateral under gross capital formation for which prices PPPs. The other method uses a regression model have been collected. In this case, the purpose is 82    Purchasing Power Parities and the Size of World Economies to ensure that the use of a reference PPP will not artificially larger and move closer to the real change the PPP for that larger group. These are expenditures of high-income economies, per referred to as neutral reference PPPs because the the Gerschenkron effect. intention is for them to have no impact on the PPPs of the larger group of basic headings. Calculation of global PPPs Market exchange rate reference PPPs are used for the following four basic headings: net Standard linking approach purchases abroad, acquisitions less disposals of At the global level, regional PPPs are linked valuables, exports of goods and services, and to form a global set of PPPs and measures of imports of goods and services. For the calculation price and volume relatives. In order to link the of PPPs for exports and imports, it would be pro- regional basic-heading PPPs for each participat- hibitively expensive to collect prices in the same ing economy, the so-called interregional linking manner as for other items of final expenditure, factors are calculated based on the prices of and the use of market exchange rates can be global items from the GCL collected in all ICP justified on practical grounds. For net purchases regions. abroad, however, there may be better alterna- The GEKS aggregation method, with further tives to the use of market exchange rates. A full redistribution of regional volumes in accordance list of reference PPPs is provided in appendix D. with an economy’s regional volume shares (known as the country aggregation with redis- PPP aggregation above the basic headings tribution [CAR] procedure), is used to obtain real expenditures (hereafter referred to as vol- Once PPPs are computed for each basic heading umes) and aggregated PPPs with regional fix- for all participating economies within a region, ity. All economies in the standard ICP regions they are used as inputs for the higher levels participated simultaneously and equally in the of aggregation using the GEKS method. This global aggregation using the GEKS method. method consists of two steps: Linking at the basic-heading level involves • Step 1. Aggregate the basic-heading PPPs the following four steps: using the national accounts expenditure structures to obtain the bilateral PPPs for • Step A1. Calculate the regional basic-heading each pair of economies. Usually Fisher-type PPPs based on both the regional and GCL PPPs will be used, which require calculating items. The regional basic-heading PPPs must both Paasche-type and Laspeyres-type PPPs. follow the ICP classification in appendix C. The Fisher-type binary PPPs will simply be • Step A2. Convert all GCL item prices in local the geometric mean of the Laspeyres-type currency to a common regional currency by and Paasche-type PPPs. using the regional basic-heading PPPs from • Step 2. Average the Fisher-type PPPs obtained step A1. to arrive at the final vector of GEKS PPPs. The • Step A3. Calculate the interregional linking GEKS calculations are performed separately factors by applying the CPD-W method to the for each aggregation level and for each cat- GCL item prices from step A2.4 egory within a given aggregation level. • Step A4. Multiply each economy’s regional It is important to note that the GEKS method basic-heading PPP from step 1 by the inter- is not additive. Additivity occurs when the sum regional linking factor resulting from step A3. of the real expenditures of the basic headings The PPPs derived from this step are the global constituting an aggregate equals the real expen- basic-heading PPPs with regional fixity. ditures based on the PPPs for the aggregate. Linking at the above, the basic-heading level While this property may be desirable for some involves the following six steps: uses, additive methods have the disadvantage of giving more weight to the relative prices of • Step B1. Calculate the regional PPPs by apply- high-income economies. As a result, the real ing the GEKS aggregation to the regional expenditures of low-income economies become basic-heading PPPs from step A1 and the Methodology 83 national accounts basic-heading expenditures questionnaires. However, not all economies were in local currency units for each level of aggre- able to report rents and dwelling stock data, and gation up to GDP. some economies were only able to provide rents • Step B2. Obtain an economy’s volume shares for a limited subset of dwelling types or limited in the regional results for each level of aggre- dwelling stock data. Each regional coordinating gation up to GDP using data from step B1. agency decided on the best way to use the col- lected data for its region. • Step B3. Calculate an economy’s aggregated Rental data were used to link the Africa, PPPs in the global comparison by applying Latin America and the Caribbean, and Western the unrestricted GEKS aggregation to the Asia regions. The linking factors for these three global basic-heading PPPs derived from step regions were calculated using the CPD method. A4 and the national accounts basic-heading The Asia and the Pacific and the Eurostat-OECD expenditures in local currency for each level regions were linked to each other and to the rest of aggregation up to GDP. of the world using the dwelling stock approach. • Step B4. Obtain the regional volume totals in the global comparison by summing up the Government compensation total volumes for individual economies for The ICP approach for estimating PPPs for govern- each region derived from step B3 for each ment services is based on an input approach in level of aggregation up to GDP. which compensation data for selected govern- • Step B5. Distribute the regional volume totals ment occupations are collected across economies. from step B4 among the economies in the Given the differences in productivity, adjustment regions according to the economy shares in factors are applied to account for differences in the regional results derived from step B2 in capital per worker. These adjustment factors are order to uphold regional fixity for each level based on differences in countrywide levels of of aggregation up to GDP. capital per worker and their estimated contribu- • Step B6. Calculate the aggregated global PPPs tion to output using the aggregate share of capi- indirectly by dividing the economies’ nomi- tal income in GDP from the Penn World Tables.5 nal expenditures by the volumes derived Adjustments were made to the PPPs for from step B5 for each level of aggregation up government in the Africa, Asia and the Pacific, to GDP. Latin America and the Caribbean, and West- ern Asia regions. No productivity adjustments The resulting linked global PPPs maintain the were applied to the Eurostat-OECD and Com- fixity of the regional results. monwealth of Independent States (CIS) regions Nonstandard linking approaches because differences in labor productivity within While the standard linking approach is applica- each of those regions were considered to be rel- ble to most household consumption basic head- atively low. However, productivity adjustments ings for all regions, other basic headings require were made to all regions when the interregional different approaches due to the specific nature linking factors were estimated to maintain con- of their surveys. sistency in the global comparison. Housing Education and health All economies participating in ICP 2017 were For education and health, Eurostat-OECD fol- asked to collect annual average rents for a global lowed an output approach to calculating their list of dwelling types, as well as dwelling stock PPPs; thus it was necessary to link their PPPs to data: number of dwellings, usable surface area in those of other ICP regions that follow the input square meters, and information on three quality approach to calculating their PPPs for health and indicators—availability of electricity, water sup- education. ply, and an in-house toilet. National accounts For education, since Eurostat-OECD does not expenditure data on actual and imputed rent- collect expenditure weights at the basic-heading als were collected by means of expenditure level, a simplified weighting system was used, 84    Purchasing Power Parities and the Size of World Economies based on information on education expenditure which regional PPPs were not used to convert structures in the OECD–United Nations Edu- construction item prices in local currency. cational, Scientific, and Cultural Organization (UNESCO) database. Data on average compen- Special linking cases sation of employees in education in Eurostat- OECD economies were used to bridge their In tandem with the calculation of global results, output-based PPPs to those of other ICP regions special linking cases included the linking of CIS that follow the input approach. results with Eurostat-OECD results, the linking For health, since Eurostat-OECD does not of Caribbean economies with Latin American collect expenditure weights at the basic-heading economies, the treatment of dual-participation level, the System of Health Accounts (SHA) was economies in the Africa and Western Asia used, as it offers a breakdown with a significant regions, and the inclusion of the special partici- overlap with basic headings in the ICP. For com- pation economies Georgia, the Islamic Republic parison purposes, it was necessary to combine of Iran, and Ukraine. the basic headings for household, NPISHs, and government consumption for other ICP regions Linking CIS with Eurostat-OECD because the SHA does not distinguish between The Russian Federation participates in both these different types of expenditures. the CIS and the Eurostat-OECD comparison, and the CIS economies were linked with the Construction and civil engineering Eurostat-OECD results using Russia’s data at The standard regional approach for estimating the basic-heading level. At the aggregated construction and civil engineering PPPs covered level, however, the CIS economies were linked four steps: through a multilateral procedure that used data from all participating economies to link the CIS • Input prices collected for materials, labor, with Eurostat-OECD. and hire of equipment were allocated to the three construction basic headings (residential Linking the Caribbean with Latin America buildings, nonresidential buildings, and civil The method used to link the Caribbean econo- engineering works). mies with Latin America included three steps. • PPPs for the input groups (materials, equip- First, PPPs were produced for the full set of Latin ment hire, and labor) were calculated using American and Caribbean economies. Second, the CPD method, resulting in nine sets of separate subregional PPP aggregations were car- input-group PPPs. ried out, one for the Latin American economies • The input-group PPPs were aggregated using and another for the Caribbean economies. As resource mixes as weights, resulting in three a third and final step, the PPPs in the first step sets of basic-heading PPPs. were reindexed in accordance with results from the second step, in order to maintain fixity of • PPPs for the three basic headings were aggre- both Latin American and Caribbean PPPs. gated using national accounts expenditure data as weights, resulting in PPPs for the con- Linking dual-participation and single struction category. economies The Eurostat-OECD approach to estimating The Arab Republic of Egypt, Morocco, and construction and civil engineering PPPs dif- Sudan participated in both the Africa and West- fers from the ICP approach, and thus several ern Asia comparisons. Published global PPPs for economies in the Eurostat-OECD comparison these economies are geometric means of their conducted the ICP survey in tandem, which pro- respective global PPPs in the Africa and Western vided a link for construction between the Euro- Asia comparisons. Russia participated in the CIS stat-OECD economies and the rest of the world. and Eurostat-OECD comparisons, but only the A modified approach was used for linking, in Eurostat-OECD results for Russia are published. Methodology 85 The single economies, Georgia and Ukraine, calculated based on an approach in which basic- were included as guest participants in the heading PPPs were first interpolated between Eurostat-OECD comparison and followed the the reference years and subsequently aggre- Eurostat-OECD methodology, while the Islamic gated using the standard GEKS method. In Republic of Iran was linked through the West- addition, regional PPPs between the reference ern Asia comparison. years, where available,6 were incorporated using the CAR procedure. The resulting annual PPPs uphold the same properties of base-country PPPs for nonparticipating economies invariance and fixity as the PPPs from reference In the 2017 cycle, 176 economies participated in year comparisons.7 the ICP. Other economies did not participate in The data required to construct annual PPPs the comparison for a variety of reasons, includ- included global PPPs for the two reference years; ing civil unrest, lack of resources, or lack of regional PPPs between the reference years, capacity. Although these nonparticipating econ- where available; national accounts deflators omies account for a small share of the world and consumer price indexes; national accounts economy and world population, it is important expenditures at current prices in local currency that they be included in any comprehensive units; market exchange rates; and population. measurement of the size of the world economy or of global poverty. The method used for imputing PPPs for non- Notes participating economies uses two regression models, one based on the price level index (PLI) 1. See icp.worldbank.org/programs/icp#6. for GDP and the other based on the PLI for indi- 2. See https://unstats.un.org/unsd/national vidual consumption expenditure by households, account/docs/SNA2008.pdf. including NPISHs. The two regressions are esti- 3. S ee https://unstats.un.org/unsd/national mated jointly using the “seemingly unrelated account/docs/1993sna.pdf. regression” method. The required explanatory 4. CPD is used for selected basic headings variables are the following: GDP per capita in US under household consumption (housing and dollars based on market exchange rates, imports education) and for all nonhousehold con- as a share of GDP, exports as a share of GDP, sumption expenditure components. and the age dependency ratio. Dummy vari- 5. The Penn World Tables are a data set of ables are required for the Sub-Saharan African National Accounts developed and main- economies, the Eurostat-OECD PPP Programme tained by the University of California, Davis, participants, island economies, and landlocked and the University of Groningen to measure economies. Interaction terms of GDP per capita GDP across economies from 1950 to 2017. in US dollars based on market exchange rates 6. Regional PPPs between the reference-year and the dummy variables are also required. comparisons were available as follows: CIS (2014), Eurostat-OECD (2012–16), and Western Asia (2012–16). Interpolated annual PPPs 7. For further details on the approach to con- For the years between reference years 2011 structing annual PPPs, see Inklaar and Rao and 2017—namely, 2012 to 2016—PPPs were (2020). 86    Purchasing Power Parities and the Size of World Economies CHAPTER 6 Looking forward As we release the results of the 2017 cycle of the Additionally, web scraping of prices will help to ICP, the world is in crisis battling the COVID-19 collect data on hard-to-price items and the latest pandemic. In addition to its principal costs to consumer trends, such as consumer electron- human life and health, countries across the ics, clothing, flights, hotel rates, and housing globe face considerable economic costs that will rents items. Crowdsourcing, whereby contribu- influence the size and distribution of the global tors provide price data via an app, could lead economy in 2020 and beyond. Our response to to more granular prices being gathered and this pandemic will transform the way we col- facilitate pricing items for sale in noncentral and lect, process, and analyze data and information rural locations. Data from administrative records over the next decade, and timely and reliable could be extended beyond the current collection economic data will be critical and instrumental of government compensation data to encompass to how policy makers, economists, statisticians, the price of public utilities and public transport, data scientists, and the wider development com- among others. Machine learning could be used munity come together to assess the outcomes to analyze item specifications and item lists and and aftermath of this global crisis. to recognize, classify, and tag items through The International Comparison Program (ICP) imaging. will evolve and respond to this changing world With regard to the basket of goods and ser- as it launches its 2021 cycle.1 This cycle will vices that the ICP prices, the program will need be implemented following the established ICP to react quickly to changes in consumers’ pur- methodology, while incorporating updates to chasing patterns and how these are reflected in item lists to reflect consumption patterns in the System of National Accounts. E-commerce 2021. and online marketplaces have enabled trade in For the ICP to accurately reflect prices and goods that are not confined to a locality, econ- expenditures prevalent in its participating econo- omy, or region, disrupting the previous geo- mies and to produce high-quality, timely results, graphic boundaries of commerce. The sharing the program needs to embrace the advance of economy also has influenced purchasing habits new technologies, both in how the program and the choice of goods and services available to collects its data and in what items it prices. consumers. Both of these channels are growing In terms of the former, scanner data collected in size and will continue to widen consumer directly from the retailer’s own records will pro- choice and, in many instances, will replace tra- vide point-of-sale prices and accurate metadata. ditional models of exchange and commerce. 87 Furthermore, as the permanent ICP tran- Note sitions to being implemented on a three- year cycle, its research agenda (presented in Following the three-year cycle implementa- 1.  appendix G) will continue to move forward tion plan, ICP stakeholders had planned to under the guidance of the Technical Advisory conduct an ICP 2020 cycle. However, restric- Group and evolve to ensure that the program tions and lockdowns in response to Covid-19 meets its users’ needs and the challenges of the halted field collection of prices in 2020 in new decade. many economies. In consideration of this setback, the ICP Governing Board decided in April 2020 to conduct an ICP 2021 cycle in lieu of an ICP 2020 cycle. 88    Purchasing Power Parities and the Size of World Economies APPENDIX A History of the International Comparison Program This appendix summarizes the history of the index formula.2 Referred to as international International Comparison Program (ICP). The units, they measured the purchasing power of ICP website provides addtional details.1 Statisti- national currencies over the period 1925–34 cians have long recognized that using market based on average prices for the period. In the exchange rates to compare levels of economic second and third editions of his study, Clark activity across economies can lead to misleading increased the number of economies covered and results. In particular, the differences between refined the methodology applied. the size of high-income economies with high Clark’s pioneering studies stimulated further price levels and low-income economies with low research. In the 1950s, the Organisation for price levels will appear larger than they actually European Economic Cooperation (OEEC) 3 used are. This distortion can be avoided by using pur- purchasing power equivalents to compare the chasing power parities (PPPs) instead of market national products of France, Germany, Italy, the exchange rates to undertake such comparisons. United Kingdom, and the United States (Gilbert In his study The Conditions of Economic Progress, and Kravis 1954). The comparison was subse- the British economist Colin Clark was the first quently enlarged to include Belgium, Denmark, to use PPPs to estimate levels of real income. the Netherlands, and Norway (Gilbert and Asso- The first edition of his study was published in ciates 1958). All final expenditures, including 1940, followed by second and third editions government and capital expenditures, were in 1951 and 1957 (Clark 1940, 1951, 1957). covered in the comparison. In the 1960s, the The first edition covered the United States and Economic Commission for Latin America car- 52 other economies. Other economies were ried out PPP-based comparisons of real product linked through a series of bilateral compari- in 19 Latin American economies; the Council sons with the United States. The results were for Mutual Economic Assistance (COMECON) then used to quantify the intercountry spread conducted PPP-based comparisons of national in real income per capita and to provide an income between several Central and Eastern estimate of world income. Income was defined European centrally planned economies, and the as consumer expenditure and did not include Conference of European Statisticians approved government expenditure or capital expenditure. a project to undertake PPP-based comparisons For income per capita, total persons employed of consumption levels among a small group rather than total population was the denomi- of market economies and centrally planned nator. PPPs were calculated using Fisher’s ideal economies. 89 In 1965 the United Nations Statistical Com- and government to obtain an aggregate of total mission (UNSC) discussed the problems inher- individual consumption called the consump- ent in market exchange rate–based comparisons tion expenditure of the population (CEP). The and agreed that the United Nations Statistical objective in measuring the CEP was to minimize Office (UNSO)4 should develop a more suitable the effect on the volume comparisons of differ- methodology for making international compari- ences in institutional arrangements, particularly sons of gross domestic product (GDP). In 1968 regarding the extent to which the government the UNSC considered a report that outlined a and private sectors provided health and edu- research project to be run from 1968 to 1971 cation services in different economies. In this aimed at developing PPP-based comparisons. respect, the ICP was more than two decades The report proposed using a small group of ahead of the System of National Accounts 1993, economies representative of different income which set out the concept of actual individual levels, social systems, and geographic areas to consumption (defined almost identically to the test and assess methodology. The UNSC agreed CEP) as an official national accounts measure that the project should proceed, and, because (UNSC 1993). the UNSO had only limited resources, asked Up to and including 1993, the ICP was con- other international organizations and United ducted in phases. Phase I had two stages. The Nations member economies to assist with the first stage was a pilot study based on data col- project. At this stage, the research endorsed by lected for 1967 for six economies (Hungary, the UNSC was to cover GDP measured from India, Japan, Kenya, the United Kingdom, and both the expenditure and production sides of the United States). The second stage was run for national accounts. Even so, it was understood 1970 and included four additional economies that initial efforts would concentrate on the (Colombia, France, Germany, and Italy) that expenditure side—it was less difficult to imple- had not been able to report the necessary data ment in practice because a single set of expendi- for 1967. The outcome consisted of different tures was involved rather than both outputs and sets of estimates, including multilateral compari- inputs, which gave rise to the added complexity sons between all 10 economies for GDP and a of double deflation. range of expenditure components for 1970. The The International Comparison Project (ICP) results of phase I were published in 1975 in A was launched in 1968 as a joint undertak- System of International Comparisons of Gross Product ing between the UNSO and the University of and Purchasing Power (Kravis et al. 1975). The Pennsylvania, which established a special unit details presented in this publication included the funded by a grant from the Ford Foundation. overall results of the multilateral comparison for The World Bank became involved, providing 1970, a variety of bilateral comparisons for both financial assistance both directly and through a 1967 and 1970, and the outcomes of various grant from the Scandinavian economies that was experiments on important issues such as rents, channeled through the World Bank. The United motor vehicle prices, and the consistency of dif- States Agency for International Development ferent quantity comparisons. and the US-based Social Science Research Coun- Phase II included six more economies—Bel- cil assisted with monetary contributions. The gium, the Islamic Republic of Iran, the Republic United Kingdom offered in-kind statistical sup- of Korea, Malaysia, the Netherlands, and the port for the participating economies. The UNSO Philippines—initially to enable a broader com- director was responsible for supervising the proj- parison for 1970, but mainly to update the PPPs ect. An advisory board set up to provide techni- and associated price and volume measures to cal advice considered detailed proposals for the 1973. Results for the 16 economies were pub- project at a meeting held in October 1969. lished in 1978 in International Comparisons of Real One of the proposals discussed by the advi- Product (Kravis, Heston, and Summers 1978). sory board resulted in the ICP adopting a Thirty-four economies participated in phase concept of consumption that summed the indi- III, with 1975 as the reference year. In the ear- vidual consumption expenditures of households lier phases, the detailed characteristics of items 90    Purchasing Power Parities and the Size of World Economies in the US consumer price index were used as Development (OECD) to set up a PPP program the starting point for developing the ICP item for its member economies in conjunction with lists. Later, they were modified in consulta- the PPP program being run by the Statistical tion with some of the participating economies, Office of the European Union (Eurostat) for including India and the COMECON group, to economies in what is now the European Union. make the specifications of ICP items more gen- In addition to the Eurostat-OECD comparison, erally applicable—for example, by removing Africa, Asia, and Latin America participated in characteristics such as brand name that were phase IV as regions. The regions were linked specific to the United States. The greater diver- using the bridge economy approach, in which sity of economies in phase III meant that the selected economies priced a range of item speci- range of items to be priced had to be expanded fications from another region to provide a bridge further so that all participating economies could or link between their region and the other price a sufficient number of items representa- region. The reference year for phase IV was tive of their expenditures. At this point, the ICP 1980. considered the pros and cons of continuing with The reference year for phase V was 1985. a single global comparison or moving to regional It saw only a small increase in the number of comparisons that would be linked to produce participating economies, from 60 to 64, with worldwide results. The trade-off involved in some new economies replacing some that had regionalizing the project was improved com- been in phase IV but had then dropped out parisons between economies within a region of phase V. Once again, a regional approach but at the expense of comparisons between was adopted. The regions were Africa, Asia, economies in different regions because of the and the Caribbean, alongside the Eurostat- difficulties inherent in linking results between OECD comparison. In addition, three Central regions. In the end, however, phase III went and Eastern European economies were added ahead as a single global comparison, although to the Eurostat-OECD comparison, using Aus- some regional results were presented as having tria as a bridge. The bridge economy approach been calculated for the relevant economies from was used again to link the regions, but some the globally based results. The results of this of the links were problematic because several phase were published in 1982 in World Product bridge economies encountered difficulties col- and Income: International Comparisons of Real Gross lecting prices for a sufficiently broad range of Product and Purchasing Power (Kravis, Heston, items from the other region. and Summers 1982). In 1990 the exercise was renamed the Inter- Phase IV saw some major developments in national Comparison Program. Phase VI, con- the program. The first was that the number of ducted with 1993 as the reference year, was participating economies almost doubled, from the most ambitious phase to date, covering 115 34 to 60. The second was that the ICP shifted economies. From the outset, this phase was from being a research project to being a regular beset by difficulties. The lack of funding was operational part of the UNSO work program. the major problem, although the lack of overall With this development, the University of Penn- coordination also led to some major deficien- sylvania’s participation in the day-to-day run- cies in the final outcome. Regional comparisons ning of the project ended, although it continued were undertaken for Africa, Asia, Eurostat- to advise on methodological issues. The third OECD, and Western Asia, but not for Latin significant change was the regionalization of America. Moreover, there was no global com- the organization of the program. The principal parison because it proved virtually impossible to reason for regionalization was the large number link the regions. In response to these problems, of economies now involved worldwide, making in 1997 the UNSC commissioned a major review it no longer feasible to organize comparisons of the ICP before further phases were attempted. centrally. Another factor was the decision by the The report on the review was presented to Organisation for Economic Co-operation and the UNSC in 1999 (ECOSOC 1999). It concluded History of the International Comparison Program 91 that PPPs and PPP-related statistics were needed, an international governance arrangement and a but that the ICP was not producing these data on broad implementation plan. a timely and regular basis for a sufficient num- The new cycle was launched in 2003 and ber of economies, as required by potential users. ended in 2008. The reference year was 2005. Poor management and insufficient resources at Regional comparisons were organized by the all levels—central, regional, and national—were ICP regional coordinating agencies—the African identified as the principal reasons for the dif- Development Bank (AfDB); the Asian Develop- ficulties. Other important contributory factors ment Bank (ADB), assisted by the Australian were inadequate documentation, heavy data Bureau of Statistics; the Interstate Statistical requirements that did not take into account the Committee of the Commonwealth of Indepen- circumstances of individual economies, lack of dent States (CIS-STAT), with the State Sta- uniformity in the execution of activities across tistical Service of the Russian Federation; the regions, lack of confidence among economies United Nations Economic Commission for Latin that others were following guidelines and stan- America and the Caribbean (UN-ECLAC), with dards consistently, and failure to involve econo- Statistics Canada; and the United Nations Eco- mies in the editing and calculation stages of nomic and Social Commission for Western Asia the exercise. The report recommended that the (UN-ESCWA)—and by Eurostat and the OECD. UNSC not sanction a new cycle until at least The ICP Global Office was established at the the management and resource issues had been World Bank to provide overall coordination and resolved. to ensure technical and procedural uniformity The UNSC responded by asking the World across the regions. The Global Office was also Bank to consult with other interested parties responsible for organizing the ring comparison and propose a strategy to address the deficien- that, by comparing a small number of econo- cies identified by the review and to draw up mies from each region across regions, provided an implementation plan for a new cycle of the the means to link the regional comparisons in ICP. The plan involved mobilizing funds from a one global or worldwide comparison. The final variety of sources and establishing a governance results of the regional and global comparisons infrastructure to provide effective management were published at the end of 2007 and the and coordination between the global center and beginning of 2008. the regions and between the regions and the A review by the UNSC’s Friends of the Chair participating economies. It also involved provid- (FOC) group of the ICP 2005 cycle concluded ing complete and clearly written documentation that it was generally considered to be a success on the ICP’s technical and procedural guidelines (ECOSOC 2008). It produced estimates of the and standards. Such guidelines would allow relative price levels of GDP and its principal economies to participate in a full comparison aggregates for 146 economies—including the covering GDP or in a partial comparison cover- major emerging ones such as Brazil, China, ing actual individual consumption, using, as far India, Indonesia, the Russian Federation, and as possible, regular national statistical programs South Africa—and its results were published to obtain price and national accounts data for on a timely basis in 2008 in Global Purchas- the ICP and linking participation in the ICP to ing Power Parities and Real Expenditures: 2005 national statistical capacity building. International Comparison Program (World Bank The UNSC considered the implementation 2008). An important contributory factor was plan in 2000 and again in 2001. It was reluctant the governance structure that the World Bank to start another cycle of the ICP before adequate had put in place prior to the start of the exercise funding had been secured. However, after the to ensure that the ICP regional coordinating World Bank embarked on a successful major agencies would deliver, within a common time fund-raising exercise, the UNSC agreed, at its frame, regional results that would be consistent 33rd session, to a new cycle in 2002. At the across regions and that could be combined in same time, the UNSC reviewed and endorsed a a global comparison. The governance struc- new strategic framework for the ICP, including ture was retained after ICP 2005 to commence 92    Purchasing Power Parities and the Size of World Economies preparations for the next cycle of the ICP pro- and balanced representation of countries and posed for 2011. The proposal was approved by coordinating agencies in the governing bodies. the UNSC at its 39th session in 2009, and the The Global Office was established as a perma- UNSC requested that the World Bank host the nent unit at the World Bank, responsible for Global Office and coordinate the global program global coordination, data validation, calcula- for the 2011 cycle. tion of global results, and related day-to day The ICP 2011, with its considerably expanded organizational activities. With regard to the coverage of 199 economies, including 21 Pacific methodology of the ICP, the UNSC agreed that Island economies whose participation was lim- no major changes should be introduced and ited to individual household consumption, that a research agenda, to be developed by brought a broader acceptance compared to the TAG, should focus on methodological earlier exercises. Furthermore, the wide avail- improvements to be considered for future ability of reliable PPPs, referenced to 2011 and comparison cycles. published in 2014 in Purchasing Power Parities With the launch of the United Nations and the Real Size of World Economies: A Compre- 2030 Agenda for Sustainable Development,6 hensive Report of the 2011 International Comparison the UNSC also emphasized the need to link Program (World Bank 2014), increased their use the capacity-building activities of the ICP with in subject matter and across the globe. Notably, efforts to enhance the statistical capacity of the international poverty line was updated in countries for monitoring progress toward the 2015 to $1.90 a day, reflecting PPPs for 2011. Sustainable Development Goals. The UNSC also The major improvements in the program were suggested exploring a closer alignment of ICP documented by the FOC, which was asked by price surveys with national consumer price the UNSC at its 45th session, in March 2014, index compilation. to evaluate the 2011 cycle (ECOSOC 2016). Data collection for the ICP’s 2017 cycle began The FOC observed that the 2011 cycle had put in 2016 and continued through to the end of the program on a firm methodological basis by 2018. The number of participating economies introducing approaches such as the global core decreased slightly, to 176, with Fiji the only lists and applying major technical innovations. representative from the Pacific Islands. Argen- Specifically, the provision of technical assis- tina and Guyana joined the Latin America and tance to countries, the broad documentation of the Caribbean comparison, while Colombia metadata, and the further development of ICP and Costa Rica moved to the OECD exercise. operational guides and handbooks contributed Some other economies that participated in the significantly to the knowledge of staff conduct- 2011 cycle were affected by conflict or natural ing the work around the world. disasters and were not included in 2011. These The 47th session of the UNSC, held in March included Guatemala and the República Boli- 2016, discussed the future of the ICP in light of variana de Venezuela in Latin America and the the recommendations of the FOC in its evalu- Caribbean and the Republic of Yemen in West- ation of ICP 2011. As a result, the UNSC insti- ern Asia. The AfDB oversaw the work of the tuted the ICP as a permanent element of the 50 economies in Africa, with the Economic and global statistical work program to be conducted Statistical Observatory of Sub-Saharan Africa at more frequent intervals from the 2017 cycle (AFRISTAT) coordinating 30 of those and the onward. Common Market for Eastern and Southern At the same time, the UNSC also endorsed Africa (COMESA) coordinating the remaining the strengthening of the governance structure5 20. Three economies in this region also par- consisting of the ICP Governing Board, the ticipated in the Western Asia exercise (the Arab Inter-Agency Coordination Group (IACG), the Republic of Egypt, Morocco, and Sudan). The Technical Advisory Group (TAG), with its inter- ADB coordinated the work of its 22 participat- mittent task forces, and implementing agen- ing economies, while CIS-STAT oversaw its cies at the national, regional, and global levels. eight economies and an experimental participa- The structure ensures efficient functioning tion by Uzbekistan. UN-ECLAC coordinated the History of the International Comparison Program 93 work of its 36 economies, with support from Notes CARICOM for the 23 Caribbean islands. UN-ESCWA coordinated the 12 economies in 1. See icp.worldbank.org/programs/#2. Western Asia. Eurostat and OECD provided 2. Fisher’s ideal volume index is the geometric results for their joint total of 49 economies mean of the Laspeyres and Paasche volume and assisted with the special participation of indexes. See icp.worldbank.org/programs Georgia and Ukraine. The Islamic Republic of /icp#6. Iran participated through a special exercise 3. Now called the Organisation for Economic linked with Western Asia. To encourage and Co-operation and Development (OECD). prepare for future participation, several econo- 4. Now called the United Nations Statistics Divi- mies also benefited from ICP capacity-building sion (UNSD). efforts. These included Eritrea, Libya, Somalia, 5. See icp.worldbank.org/programs/icp#3. South Sudan, Turkmenistan, Uzbekistan, and 6. See https://www.un.org/sustainabledevelop the Republic of Yemen. ment/development-agenda/. 94    Purchasing Power Parities and the Size of World Economies APPENDIX B The ICP’s governance framework This appendix presents the elements of the and Development (OECD), and the national International Comparison Program’s (ICP) gov- im­plementing agencies carry out the various ernance framework, as approved by the ICP activities to coordinate and implement the Governing Board at its first meeting in Novem- program. ber 2016 (World Bank 2016b). It sets out the overall governance structure and the roles and responsibilities of its main bodies, based on the The roles and responsibilities of lessons learned from earlier ICP cycles. the ICP governance bodies United Nations Statistical Commission The ICP’s governance structure The UNSC, the ultimate stakeholder of the ICP, The overall mandate of the ICP governance • Decides on the frequency and operational framework is to ensure that the global, regional, modality of the program and national efforts to produce reliable pur- • Establishes the ICP Governing Board chasing power parity (PPP) estimates and related measures of real expenditures adhere • Ensures an adequate and balanced represen- to approved policies, protocols, methodologies, tation of economies and organizations and quality assurance standards and that the • Selects the global implementing agency estimates are produced efficiently, in keeping • Reviews and acts on issues raised in the with available resources. annual reports to the UNSC, prepared by the The ICP’s governance structure, outlined global implementing agency in figure B.1, comprises the United Nations Statistical Commission (UNSC), the Govern- • Reviews the functioning of the ICP gover- ing Board, the Inter-Agency Coordination nance structure and the membership of its Group (IACG), and the Technical Advisory governing bodies after a three-year period Group (TAG) and its task forces. Within this and introduces modifications, if needed scheme, the global implementing agency, the • Considers specific issues related to the ICP regional implementing agencies, the Statisti- governance structure or membership of its cal Office of the European Union (Eurostat), governance bodies, if raised in the annual the Organisation for Economic Co-operation reports to the UNSC. 95 Figure B.1  ICP governance structure UNITED NATIONS STATISTICAL COMMISSION ICP GOVERNING BOARD ICP Inter-Agency Coordination Group Global WORLD BANK Technical Implementing (ICP Global Office) IMF Agency Advisory Group and Regional task forces CIS- UN- UN- Eurostat Implementing AfDB ADB STAT ECLAC ESCWA and OECD Agencies National Asia Common- Latin wealth of America Western Eurostat- Implementing Africa and the Independent and the Asia OECD Agencies Pacific States Caribbean Note: AfDB = African Development Bank. ADB = Asian Development Bank. CIS-STAT = Interstate Statistical Committee of the Commonwealth of Independent States. UN-ECLAC = United Nations Economic Commission for Latin America and the Caribbean. UN-ESCWA = United Nations Economic and Social Commission for Western Asia. Eurostat = Statistical Office of the European Union. OECD = Organisation for Economic Co-operation and Development. IMF = International Monetary Fund. The Governing Board • Puts forth an ICP data access and archive policy that promotes further openness with The Governing Board, a strategic and policy- regard to access to data and metadata. making body, Members of the Governing Board include • Puts forth the policies and protocols that gov- chief statisticians or senior-level directors of sta- ern the production of regional and global PPP tistics from 11 national implementing agencies, estimates representing their respective ICP regions. The 11 • Forms the TAG board members are distributed geographically as • Approves the technical research agenda, follows: Africa (two), Asia (two), Pacific Islands methodology for producing PPPs, and any (one), Latin America (one), Caribbean (one), methodological improvement thereafter Western Asia (one), Commonwealth of Inde- • Ensures that regional and global ICP results pendent States (one), European Union (one), are produced following the agreed-on time- and non–European Union OECD (one). A rota- tables and in line with the agreed-on policies, tion system within each ICP region ensures a protocols, and methodology to secure the broad representation of economies on the board integrity of the estimates over time. The duration of each rotation is three years. • Sets up a sustainable funding model that cor- In addition to the 11 national implementing responds to the frequency and operational agencies, seven international and regional orga- modality of the program nizations serve as members of the Governing • Reaches out and demonstrates the value of Board, including the World Bank, International the ICP to policy makers in order to ensure Monetary Fund (IMF), United Nations Statistics that the program is included in the regu- Division, African Development Bank (AfDB), lar national statistical work and to increase and Asian Development Bank (ADB). The Euro- national funding for the ICP stat-OECD PPP Programme is represented by a • Ensures that the ICP responds to user needs seat on the Governing Board, and Eurostat and 96    Purchasing Power Parities and the Size of World Economies the OECD rotate on this seat. Another board established methods and procedures to improve seat is assigned to the smaller regional pro- the quality of the estimates. grams, with the United Nations Economic Com- The TAG is formed by the ICP Govern- mission for Latin America and the Caribbean ing Board, with the membership of prominent (UN-ECLAC), United Nations Economic and experts in the fields of index numbers, PPPs, price Social Commission for Western Asia (UN- statistics, and national accounts, with knowledge ESCWA), and Interstate Statistical Committee of national statistical systems and capacity-build- of the Commonwealth of Independent States ing challenges across the various regions. The (CIS-STAT) rotating in this seat. The duration of membership brings together a group of leading rotation is one year. Members of the IACG not academics, practitioners, former chief statisti- holding a seat during a given rotation period are cians, and prominent users. Members participate invited to attend Governing Board meetings as in their own independent capacity and do not observers. represent any specific region or institution. Governing Board members elect a chair or TAG members select a chair for the duration co-chairs for the duration of three years. The of three years. The chair convenes meetings of chair or co-chairs convene meetings of the Gov- the group with support from the ICP Global erning Board with support from the ICP Global Office, which serves as its secretariat. Office, which serves as the secretariat for the The TAG holds regular annual meetings to Governing Board. discuss methodological improvements under The Governing Board holds regular annual the technical research agenda and to review meetings, around the UNSC sessions in New the methodological soundness and overall qual- York, to discuss policies, protocols, and method- ity of the PPP estimates. Ad hoc meetings are ology governing the production of PPP estimates organized, if a need arises. The TAG forms task and ICP advocacy and funding aspects. Ad hoc forces on specific topics and invites recognized meetings may be organized, if need arises. experts on the practical application of index Governing Board decisions are made by con- numbers, PPPs, price statistics, and national sensus. If a consensus cannot be achieved, deci- accounts to take part in them, as needed, to sions are made by majority vote. develop concrete proposals to address items on the research agenda. The task forces meet as needed, physically or virtually. They may also The Technical Advisory Group and its join IACG meetings to discuss their proposals task forces and TAG meetings to present their findings and recommendations for consideration. The TAG, a technical body, • Assures the methodological soundness and The Inter-Agency Coordination Group and overall quality of the PPP estimates its agencies • Ensures the transparency of the PPP estima- The IACG, a coordinating body, tion process • Supports the establishment of a permanent • Collaborates on establishing timetables and and more frequent ICP. work plans for data collection, validation, calculation, and dissemination The TAG, in collaboration with the IACG, • Develops common standards and protocols sets forth a technical research agenda to inform to ensure comparability across regions and future ICP comparisons, for the Governing economies Board’s review and approval. In order to ensure the comparability of PPP • Provides the quality assurance standards that estimates, the short-term technical research national and regional data and metadata agenda focuses on methodological aspects must satisfy to be included in the global PPP related to compiling annual PPPs and fine-tuning estimates The ICP’s governance framework 97 • Develops a technical research agenda on the • Links the regional data and then calculates, methodological choices and implementation validates, and disseminates the global ICP arrangements, to inform future ICP compari- results as per the agreed-on timetables sons, together with the TAG • Implements the ICP results dissemination • Prepares and updates operational guidelines policy and manages relevant databases, and materials, including classifications, lists of ensuring that access to detailed ICP data and items, and survey forms metadata is granted per the ICP data access • Promotes and supports the integration of ICP and archive policy and consumer price index survey activities to • Prepares annual reports for submission to the decrease the burden on economies UNSC. • Takes stock of existing capacity-building The regional implementing agencies activities undertaken by the various agencies • Coordinate the regional ICP comparisons in the areas of prices and national accounts and facilitate data and information flow and plans and implements statistical capacity- between the ICP Global Office and participat- building activities related to the ICP. ing economies The IACG comprises the World Bank as the • Carry out day-to-day management of the global implementing agency, the regional imple- regional programs menting agencies, the OECD, Eurostat, and the • Plan and implement the regional ICP activi- IMF. It is chaired by the ICP Global Office, which ties in line with the agreed-on timetables also serves as its secretariat. • Participate in the preparation of operational As the global implementing agency, the guidelines and materials, as IACG members World Bank is responsible for establishing the ICP Global Office, which supports the ICP gov- • Ensure adequate national and regional data ernance framework and undertakes the global and metadata quality as per the agreed-on coordination and implementation of the ICP. standards The ICP Global Office • Carry out regional capacity-building activities and provide technical support to the econo- • Carries out day-to-day management of the mies on data and metadata collection and global program validation • Serves as the secretariat of the Governing • Prepare and disseminate regional ICP results Board and TAG as per the agreed-on timetables • Chairs the IACG and serves as its secretariat • Transmit national and regional data and • Drafts and implements common policies and metadata, including quality indicators, to the procedures for sharing data and metadata ICP Global Office as per the ICP data access between economies, regions, and the ICP and archive policy Global Office • Contribute to global ICP research initiatives • Drafts operational guidelines and materials to by identifying and undertaking research pri- support the conduct of the program orities relevant to their regions. • Assesses national and regional data and The following organizations are currently act- metadata submitted by the regions against ing as the regional implementing agencies: the quality assurance standards agreed to by • AfDB for the Africa region the IACG to determine their suitability for inclusion in the global PPP calculations • ADB for the Asia and the Pacific region • Provides technical support to the regions on • CIS-STAT for the Commonwealth of the implementation of standards, data valida- Independent States tion, analysis, and computation of regional • UN-ECLAC for the Latin America and the results Caribbean region 98    Purchasing Power Parities and the Size of World Economies • UN-ESCWA for the Western Asia region. CPI, PPI, and national accounts expendi- ture data used in the calculation of the ICP If additional organizations are selected to results. coordinate the program in other regional group- ings, such as the Pacific Islands, these regional The IACG holds regular biannual meetings implementing agencies will join the IACG as and ad hoc meetings, if need arises. The meet- members. ings mainly review the following: Reflecting existing arrangements of the long- standing Eurostat-OECD PPP Programme, Euro- • Progress of the regional and global compari- stat is responsible for the ICP activities for Euro- sons against the agreed-on timetables pean economies and OECD is responsible for • Operational and technical challenges in non-European OECD economies and other OECD implementing the ICP program in the regions accession economies. Eurostat and the OECD and needed improvements in standards, methods, and protocols • Coordinate and execute their own permanent comparison program, including determining • Operational guidelines and materials, includ- the program’s approaches and timetables ing classifications, lists of items, and survey forms • Participate in the preparation of operational guidelines and materials, as members of the • Prices, national accounts expenditures, and IACG other data and metadata underlying the regional and global comparisons • Transmit national and regional data and metadata, including quality indicators, to the • Preliminary and final regional and global PPP ICP Global Office as per the ICP data access estimates. and archive policy • Ensure the availability of data necessary to The national implementing agencies link the Eurostat and OECD economies to the Each participating economy designates a global comparison. national implementing agency, which is respon- The IMF is one of the leading agencies that sible for planning, coordinating, and imple- plan and deliver statistical capacity-building menting national ICP activities under the overall activities related to the consumer price index work program of the ICP region to which it (CPI), producer price index (PPI), and national belongs. National implementing agencies accounts. Moreover, the IMF compiles and • Collect and compile the data and metadata maintains, jointly with the OECD, a database of required for estimating PPPs following the detailed CPIs that can be used in the extrapola- agreed-on standards, protocols, and guide- tion and retropolation of data underlying the lines for ensuring cross-country comparability PPPs. In this role, the IMF • Ensure adequate national data and metadata • Supports the planning and conduct of quality as per the agreed-on quality assur- regional statistical capacity-building activi- ance standards ties to improve the quality and availability of • Facilitate the transmission of data and meta- CPI, PPI, and national accounts expenditure data to regional implementing agencies as per data the ICP data access and archive policy • Advances the agenda for integrating ICP and • Participate in regional workshops and activi- CPI survey activities ties to discuss operational guidelines and • Contributes to formulation of the framework materials, data and metadata quality, and and approaches for assessing the quality of preliminary and final regional results. The ICP’s governance framework 99 APPENDIX C ICP expenditure classification Economies participating in the International 63 expenditure groups, 126 expenditure classes, Comparison Program (ICP) are required to and 155 basic headings, as shown in table C.1 provide a detailed breakdown of their national In the outline of the expenditure classifica- accounts expenditures for the reference year tion that appears in table C.2, main aggregates according to a common classification. The break- are identified by a two-digit code, categories by down is used first in the regional comparison in a four-digit code, groups by a five-digit code, which the reporting economy is engaged and classes by a six-digit code, and basic headings by then in the global comparison. The classification a seven-digit code: of gross domestic product (GDP) expenditures used by the ICP adheres to the internationally 1100000  INDIVIDUAL CONSUMPTION agreed-on concepts, definitions, classifications, EXPENDITURE BY HOUSEHOLDS and accounting rules of the System of National (main aggregate) Accounts (SNA) 2008 (UNSC 2009). It is struc- 1101000  FOOD AND NONALCOHOLIC tured first by type of final expenditure—indi- BEVERAGES (category) vidual consumption expenditure, collective 1101100  FOOD (group) consumption expenditure, or capital expendi- 1101110  Bread and cereals (class) ture—and then, in the case of individual con- 1101111  Rice (basic heading). sumption expenditure, by purchaser—house- holds, nonprofit institutions serving households Of these aggregation levels, the basic-heading (NPISHs), and government. level is particularly important. At this level, This appendix provides an overview of the 2017 ICP expenditure classification. More details expenditures are defined and estimated, items are available on the ICP website,1 including a are selected for pricing, prices are collected and description of the full classification (see World validated, and purchasing power parities (PPPs) Bank 2016a). are first calculated. In principle, a basic head- ing consists of a group of similar well-defined goods or services. In practice, a basic heading is defined by the lowest level of final expenditure 2017 ICP expenditure for which explicit expenditures can be estimated classification structure by the participating economies. Consequently, GDP comprises six main aggregates, which are basic headings can cover a broader range of broken down into 28 expenditure categories, goods or services than is theoretically desirable. 101 Table C.1  Structure of the ICP expenditure classification, ICP 2017 Main aggregates Categories Groups Classes Basic headings 11. Individual consumption expenditure by households 13 44 91 110 Individual consumption expenditure by nonprofit institutions serving 12.  5 5 5 5 households (NPISHs) 13. Individual consumption expenditure by government 5 7 16 21 14. Collective consumption expenditure by government 1 1 5 5 15. Gross capital formation 3 5 8 12 16. Balance of exports and imports 1 1 1 2 GDP 26 63 126 155 Source: ICP. Main aggregates The individual consumption expenditures of NPISHs and government cover their expendi- Individual consumption by households is bro- tures on the services they provide to individual ken down by purpose, in line with the Clas- households as social transfers in kind—that is, sification of Individual Consumption by Pur- services related to housing, health care, recre- pose (COICOP) (see UNSD 2000a). Individual ation and culture, education, and social protec- consumption expenditure by NPISHs is broken tion. Combining these expenditures is necessary down by purpose, in line with the Classification because of the various ways in which individual of the Purposes of Non-Profit Institutions Serv- services are financed in different economies. If ing Households (COPNI) (see UNSD 2000b). the expenditures are not combined and only the And consumption expenditure by government individual consumption expenditures of house- is broken down into individual consumption holds are compared, households in economies expenditure and collective consumption expen- in which NPISHs or government provide indi- diture by purpose and by type of service, in line vidual services will appear to consume a smaller with the Classification of the Functions of Gov- volume of goods and services than households ernment (COFOG) (UNSD 2000c). Gross capital in economies in which households themselves formation consists of three categories: gross pay directly for these services. fixed capital formation, changes in inventories, To effect the merger, the individual con- and acquisitions less disposals of valuables. Of sumption expenditures of NPISHs and govern- these, gross fixed capital formation is broken ment are broken down so that they can be down by the type of product, in line with the added to their counterpart expenditures under Statistical Classification of Products by Activity household expenditure. The breakdowns are (CPA) in the European Economic Community structured so that the summation can be at (see Eurostat 2008). The balance of exports and the lowest level of aggregation feasible, which imports comprises exports of goods and services is generally at the level of the basic heading. and imports of goods and services. Many economies are unable to break down the individual consumption expenditures of NPISHs to the required level of detail. When Deriving actual individual this is the case, the expenditures of NPISHs are consumption reported in total. This total is subsequently dis- tributed over the relevant basic headings under Actual individual consumption is obtained by household expenditure in the same proportions summing the individual consumption expendi- as household expenditure is distributed across tures of households, NPISHs, and government. the basic headings. 102    Purchasing Power Parities and the Size of World Economies Facilitating the input price of nonresident households within the economic approach territory. Many economies, however, estimate the expenditures on these basic headings accord- The collective and individual services produced ing to the domestic concept—that is, irrespective by government are nonmarket services because of whether the household making the purchase they are either provided free or sold at prices is resident or not. For these economies, the clas- that are not economically significant. In the sification contains a global adjustment to rectify absence of economically significant prices, this difference. The adjustment is defined as the national accountants obtain the expenditure balance of the expenditures of residents abroad on nonmarket services by summing the costs of less the expenditures of nonresidents within the the inputs required to produce them. To main- economic territory or as net purchases abroad. tain consistency with the prices underlying the It is important to note that many economies estimated expenditure on nonmarket services base their estimates of individual consumption in the national accounts, the PPPs for nonmar- expenditure by households on household bud- ket services are based on input prices. This is get surveys, so the estimates are automatically the input price approach. To enable application on a national basis. For these economies, global of the input price approach, the classification adjustment is not required. breaks down the consumption expenditure by government on the production of collective services and the principal individual services— Updates introduced for the 2017 education and health—into the following com- ICP expenditure classification ponents: compensation of employees, inter- mediate consumption, gross operating surplus, The classification of expenditure on GDP used and net taxes on production (the sum of these for ICP 2005 and ICP 2011 has been updated four components is a measure of government (a) to reflect the lessons learned during the 2005 output). Receipts from sales (such as those and 2011 cycles; (b) to maintain consistency from statistical publications) are deducted from with the Eurostat expenditure classification, output to provide the estimate of consumption which has recently been revised; and (c) to expenditure by government. take account of the changes in the classification A distinction is made between the govern- introduced by SNA 2008. Gross capital formation ment’s expenditure on the health and educa- has been introduced as a main aggregate. It tion services it produces and the government’s replaces the former main aggregates gross fixed expenditure on the health and education ser- capital formation and changes in inventories and vices it purchases from market producers in the acquisitions less disposals of valuables, which are private sector under benefits and reimburse- now aggregates at the expenditure-category ments. This approach ensures that the input level. Three sets of balancing basic headings price approach is applied only to government were merged to become single basic headings expenditure on government-produced services. (net purchases abroad, changes in inventories, and acquisitions less disposals of valuables). Other changes concern rentals for housing and Adjusting household expenditure individual consumption expenditure by NPISHs. Pre- to the national concept viously, these were single basic headings, but the housing rentals category is now broken Expenditures on the basic headings constituting down into two basic headings, one for actual individual consumption expenditure by house- rentals and one for imputed rentals, while holds are defined according to the national NPISHs expenditures are divided across five concept—that is, they cover only expenditures basic headings that cover the individual services by resident households, including their expen- provided by NPISHs (housing, health, recreation ditures abroad, and exclude the expenditures and culture, education, social protection, and ICP expenditure classification 103 other services). ICP basic-heading code num- the classification of fixed assets relating to bers remain unchanged, except for the basic research and development, military weapons headings under gross capital formation and the systems and ammunition, computer software newly introduced basic headings. and databases, land improvements, and own- SNA 2008 does not differ fundamentally ership transfer costs on nonproduced assets from SNA 1993 (UNSC 1993), and the basic including land. structure of the classification stays the same. Within the basic structure, changes occur Note under gross fixed capital formation as a result of the changes that have been introduced in 1.  See icp.worldbank.org/programs/#6. Table C.2  Expenditure classification, ICP 2017 Code Name Expenditure level 1000000 GROSS DOMESTIC PRODUCT GDP 1100000 INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS Main aggregate 1101000 FOOD AND NONALCOHOLIC BEVERAGES Category 1101100 FOOD Group 1101110 Bread and cereals Class 1101111 Rice Basic heading 1101112 Other cereals, flour, and other cereal products Basic heading 1101113 Bread Basic heading 1101114 Other bakery products Basic heading 1101115 Pasta products and couscous Basic heading 1101120 Meat Class 1101121 Beef and veal Basic heading 1101122 Pork Basic heading 1101123 Lamb, mutton, and goat Basic heading 1101124 Poultry Basic heading 1101125 Other meats and meat preparations Basic heading 1101130 Fish and seafood Class 1101131 Fresh, chilled, or frozen fish and seafood Basic heading 1101132 Preserved or processed fish and seafood Basic heading 1101140 Milk, cheese, and eggs Class 1101141 Fresh milk Basic heading 1101142 Preserved milk and other milk products Basic heading 1101143 Cheese and curd Basic heading 1101144 Eggs and egg-based products Basic heading 1101150 Oils and fats Class 1101151 Butter and margarine Basic heading 1101153 Other edible oils and fats Basic heading 1101160 Fruit Class 1101161 Fresh or chilled fruit Basic heading 1101162 Frozen, preserved, or processed fruit and fruit-based products Basic heading 104    Purchasing Power Parities and the Size of World Economies Table C.2  (Continued) Code Name Expenditure level 1101170 Vegetables Class 1101171 Fresh or chilled vegetables, other than potatoes and other tuber vegetables Basic heading 1101172 Fresh or chilled potatoes and other tuber vegetables Basic heading 1101173 Frozen, preserved, or processed vegetables and vegetable-based products Basic heading 1101180 Sugar, jam, honey, chocolate, and confectionery Class 1101181 Sugar Basic heading 1101182 Jams, marmalades, and honey Basic heading 1101183 Confectionery, chocolate, and ice cream Basic heading 1101190 Food products n.e.c. Class 1101191 Food products n.e.c. Basic heading 1101200 NONALCOHOLIC BEVERAGES Group 1101210 Coffee, tea, and cocoa Class 1101211 Coffee, tea, and cocoa Basic heading 1101220 Mineral waters, soft drinks, and fruit and vegetable juices Class 1101221 Mineral waters, soft drinks, and fruit and vegetable juices Basic heading 1102000 ALCOHOLIC BEVERAGES, TOBACCO, AND NARCOTICS Category 1102100 ALCOHOLIC BEVERAGES Group 1102110 Spirits Class 1102111 Spirits Basic heading 1102120 Wine Class 1102121 Wine Basic heading 1102130 Beer Class 1102131 Beer Basic heading 1102200 TOBACCO Group 1102210 Tobacco Class 1102211 Tobacco Basic heading 1102300 NARCOTICS Group 1102310 Narcotics Class 1102311 Narcotics Basic heading 1103000 CLOTHING AND FOOTWEAR Category 1103100 CLOTHING Group 1103110 Clothing materials, other articles of clothing, and clothing accessories Class 1103111 Clothing materials, other articles of clothing, and clothing accessories Basic heading 1103120 Garments Class 1103121 Garments Basic heading 1103140 Cleaning, repair, and hire of clothing Class 1103141 Cleaning, repair, and hire of clothing Basic heading 1103200 FOOTWEAR Group 1103210 Shoes and other footwear Class 1103211 Shoes and other footwear Basic heading (continued) ICP expenditure classification 105 Table C.2  (Continued) Code Name Expenditure level 1103220 Repair and hire of footwear Class 1103221 Repair and hire of footwear Basic heading 1104000 HOUSING, WATER, ELECTRICITY, GAS, AND OTHER FUELS Category 1104100 ACTUAL RENTALS FOR HOUSING Group 1104110 Actual rentals for housing Class 1104111 Actual rentals for housing * Basic heading 1104200 IMPUTED RENTALS FOR HOUSING Group 1104210 Imputed rentals for housing Class 1104211 Imputed rentals for housing * Basic heading 1104300 MAINTENANCE AND REPAIR OF THE DWELLING Group 1104310 Maintenance and repair of the dwelling Class 1104311 Maintenance and repair of the dwelling Basic heading 1104400 WATER SUPPLY AND MISCELLANEOUS SERVICES RELATING TO THE DWELLING Group 1104410 Water supply Class 1104411 Water supply Basic heading 1104420 Miscellaneous services relating to the dwelling Class 1104421 Miscellaneous services relating to the dwelling Basic heading 1104500 ELECTRICITY, GAS, AND OTHER FUELS Group 1104510 Electricity Class 1104511 Electricity Basic heading 1104520 Gas Class 1104521 Gas Basic heading 1104530 Other fuels Class 1104531 Other fuels Basic heading 1105000 FURNISHINGS, HOUSEHOLD EQUIPMENT, AND ROUTINE HOUSEHOLD MAINTENANCE Category 1105100 FURNITURE AND FURNISHINGS, CARPETS, AND OTHER FLOOR COVERINGS Group 1105110 Furniture and furnishings Class 1105111 Furniture and furnishings Basic heading 1105120 Carpets and other floor coverings Class 1105121 Carpets and other floor coverings Basic heading 1105130 Repair of furniture, furnishings, and floor coverings Class 1105131 Repair of furniture, furnishings, and floor coverings Basic heading 1105200 HOUSEHOLD TEXTILES Group 1105210 Household textiles Class 1105211 Household textiles Basic heading 1105300 HOUSEHOLD APPLIANCES Group 1105310 Major household appliances whether electric or not Class 1105311 Major household appliances whether electric or not Basic heading 1105320 Small electric household appliances Class 1105321 Small electric household appliances Basic heading 106    Purchasing Power Parities and the Size of World Economies Table C.2  (Continued) Code Name Expenditure level 1105330 Repair of household appliances Class 1105331 Repair of household appliances Basic heading 1105400 GLASSWARE, TABLEWARE, AND HOUSEHOLD UTENSILS Group 1105410 Glassware, tableware, and household utensils Class 1105411 Glassware, tableware, and household utensils Basic heading 1105500 TOOLS AND EQUIPMENT FOR HOUSE AND GARDEN Group 1105510 Major tools and equipment Class 1105511 Major tools and equipment Basic heading 1105520 Small tools and miscellaneous accessories Class 1105521 Small tools and miscellaneous accessories Basic heading 1105600 GOODS AND SERVICES FOR ROUTINE HOUSEHOLD MAINTENANCE Group 1105610 Nondurable household goods Class 1105611 Nondurable household goods Basic heading 1105620 Domestic services and household services Class 1105621 Domestic services Basic heading 1105622 Household services Basic heading 1106000 HEALTH Category 1106100 MEDICAL PRODUCTS, APPLIANCES, AND EQUIPMENT Group 1106110 Pharmaceutical products Class 1106111 Pharmaceutical products Basic heading 1106120 Other medical products Class 1106121 Other medical products Basic heading 1106130 Therapeutic appliances and equipment Class 1106131 Therapeutic appliances and equipment Basic heading 1106200 OUTPATIENT SERVICES Group 1106210 Medical services Class 1106211 Medical services Basic heading 1106220 Dental services Class 1106221 Dental services Basic heading 1106230 Paramedical services Class 1106231 Paramedical services Basic heading 1106300 HOSPITAL SERVICES Group 1106310 Hospital services Class 1106311 Hospital services Basic heading 1107000 TRANSPORT Category 1107100 PURCHASE OF VEHICLES Group 1107110 Motor cars Class 1107111 Motor cars Basic heading 1107120 Motorcycles Class 1107121 Motorcycles Basic heading (continued) ICP expenditure classification 107 Table C.2  (Continued) Code Name Expenditure level 1107130 Bicycles Class 1107131 Bicycles Basic heading 1107140 Animal-drawn vehicles Class 1107141 Animal-drawn vehicles Basic heading 1107200 OPERATION OF PERSONAL TRANSPORT EQUIPMENT Group 1107220 Fuels and lubricants for personal transport equipment Class 1107221 Fuels and lubricants for personal transport equipment Basic heading 1107230 Maintenance and repair of personal transport equipment Class 1107231 Maintenance and repair of personal transport equipment Basic heading 1107240 Other services in respect of personal transport equipment Class 1107241 Other services in respect of personal transport equipment Basic heading 1107300 TRANSPORT SERVICES Group 1107310 Passenger transport by railway Class 1107311 Passenger transport by railway Basic heading 1107320 Passenger transport by road Class 1107321 Passenger transport by road Basic heading 1107330 Passenger transport by air Class 1107331 Passenger transport by air Basic heading 1107340 Passenger transport by sea and inland waterway Class 1107341 Passenger transport by sea and inland waterway Basic heading 1107350 Combined passenger transport Class 1107351 Combined passenger transport Basic heading 1107360 Other purchased transport services Class 1107361 Other purchased transport services Basic heading 1108000 COMMUNICATION Category 1108100 POSTAL SERVICES Group 1108110 Postal services Class 1108111 Postal services Basic heading 1108200 TELEPHONE AND TELEFAX EQUIPMENT Group 1108210 Telephone and telefax equipment Class 1108211 Telephone and telefax equipment Basic heading 1108300 TELEPHONE AND TELEFAX SERVICES Group 1108310 Telephone and telefax services Class 1108311 Telephone and telefax services Basic heading 1109000 RECREATION AND CULTURE Category 1109100 AUDIOVISUAL, PHOTOGRAPHIC, AND INFORMATION PROCESSING EQUIPMENT Group 1109110 Audiovisual, photographic, and information processing equipment Class 1109111 Audiovisual, photographic, and information processing equipment Basic heading 1109140 Recording media Class 1109141 Recording media Basic heading 108    Purchasing Power Parities and the Size of World Economies Table C.2  (Continued) Code Name Expenditure level 1109150 Repair of audiovisual, photographic, and information processing equipment Class 1109151 Repair of audiovisual, photographic, and information processing equipment Basic heading 1109200 OTHER MAJOR DURABLES FOR RECREATION AND CULTURE Group 1109210 Major durables for outdoor and indoor recreation Class 1109211 Major durables for outdoor and indoor recreation Basic heading 1109230 Maintenance and repair of other major durables for recreation and culture Class 1109231 Maintenance and repair of other major durables for recreation and culture Basic heading 1109300 OTHER RECREATIONAL ITEMS AND EQUIPMENT, GARDENS, AND PETS Group 1109310 Other recreational items and equipment Class 1109311 Other recreational items and equipment Basic heading 1109330 Gardens and pets Class 1109331 Gardens and pets Basic heading 1109350 Veterinary and other services for pets Class 1109351 Veterinary and other services for pets Basic heading 1109400 RECREATIONAL AND CULTURAL SERVICES Group 1109410 Recreational and sporting services Class 1109411 Recreational and sporting services Basic heading 1109420 Cultural services Class 1109421 Cultural services Basic heading 1109430 Games of chance Class 1109431 Games of chance Basic heading 1109500 NEWSPAPERS, BOOKS, AND STATIONERY Group 1109510 Newspapers, books, and stationery Class 1109511 Newspapers, books, and stationery Basic heading 1109600 PACKAGE HOLIDAYS Group 1109610 Package holidays Class 1109611 Package holidays Basic heading 1110000 EDUCATION Category 1110100 EDUCATION Group 1110110 Education Class 1110111 Education Basic heading 1111000 RESTAURANTS AND HOTELS Category 1111100 CATERING SERVICES Group 1111110 Catering services Class 1111111 Catering services Basic heading 1111200 ACCOMMODATION SERVICES Group 1111210 Accommodation services Class 1111211 Accommodation services Basic heading (continued) ICP expenditure classification 109 Table C.2  (Continued) Code Name Expenditure level 1112000 MISCELLANEOUS GOODS AND SERVICES Category 1112100 PERSONAL CARE Group 1112110 Hairdressing salons and personal grooming establishments Class 1112111 Hairdressing salons and personal grooming establishments Basic heading 1112120 Appliances, articles, and products for personal care Class 1112121 Appliances, articles, and products for personal care Basic heading 1112200 PROSTITUTION Group 1112210 Prostitution Class 1112211 Prostitution Basic heading 1112300 PERSONAL EFFECTS N.E.C. Group 1112310 Jewelry, clocks, and watches Class 1112311 Jewelry, clocks, and watches Basic heading 1112320 Other personal effects Class 1112321 Other personal effects Basic heading 1112400 SOCIAL PROTECTION Group 1112410 Social protection Class 1112411 Social protection Basic heading 1112500 INSURANCE Group 1112510 Insurance Class 1112511 Insurance Basic heading 1112600 FINANCIAL SERVICES N.E.C. Group 1112610 Financial intermediation services indirectly measured (FISIM) Class 1112611 Financial intermediation services indirectly measured (FISIM) Basic heading 1112620 Other financial services n.e.c. Class 1112621 Other financial services n.e.c. Basic heading 1112700 OTHER SERVICES N.E.C. Group 1112710 Other services n.e.c. Class 1112711 Other services n.e.c. Basic heading 1113000 NET PURCHASES ABROAD Category 1113100 NET PURCHASES ABROAD Group 1113110 Net purchases abroad Class 1113111 Net purchases abroad * Basic heading 1200000 INDIVIDUAL CONSUMPTION EXPENDITURE BY NPISHs Main aggregate 1201000 HOUSING Category 1201100 HOUSING Group 1201110 Housing Class 1201111 Housing * Basic heading 1202000 HEALTH Category 1202100 HEALTH Group 1202110 Health Class 110    Purchasing Power Parities and the Size of World Economies Table C.2  (Continued) Code Name Expenditure level 1202111 Health * Basic heading 1203000 RECREATION AND CULTURE Category 1203100 RECREATION AND CULTURE Group 1203110 Recreation and culture Class 1203111 Recreation and culture * Basic heading 1204000 EDUCATION Category 1204100 EDUCATION Group 1204110 Education Class 1204111 Education * Basic heading 1205000 SOCIAL PROTECTION AND OTHER SERVICES Category 1205100 SOCIAL PROTECTION AND OTHER SERVICES Group 1205110 Social protection and other services Class 1205111 Social protection and other services * Basic heading 1300000 INDIVIDUAL CONSUMPTION EXPENDITURE BY GOVERNMENT Main aggregate 1301000 HOUSING Category 1301100 HOUSING Group 1301110 Housing Class 1301111 Housing Basic heading 1302000 HEALTH Category 1302100 HEALTH BENEFITS AND REIMBURSEMENTS Group 1302110 Medical products, appliances, and equipment Class 1302111 Pharmaceutical products Basic heading 1302112 Other medical products Basic heading 1302113 Therapeutic appliances and equipment Basic heading 1302120 Health services Class 1302121 Outpatient medical services Basic heading 1302122 Outpatient dental services Basic heading 1302123 Outpatient paramedical services Basic heading 1302124 Hospital services Basic heading 1302200 PRODUCTION OF HEALTH SERVICES Group 1302210 Compensation of employees Class 1302211 Compensation of employees Basic heading 1302220 Intermediate consumption Class 1302221 Intermediate consumption Basic heading 1302230 Gross operating surplus Class 1302231 Gross operating surplus Basic heading 1302240 Net taxes on production Class 1302241 Net taxes on production Basic heading (continued) ICP expenditure classification 111 Table C.2  (Continued) Code Name Expenditure level 1302250 Receipts from sales Class 1302251 Receipts from sales Basic heading 1303000 RECREATION AND CULTURE Category 1303100 RECREATION AND CULTURE Group 1303110 Recreation and culture Class 1303111 Recreation and culture Basic heading 1304000 EDUCATION Category 1304100 EDUCATION BENEFITS AND REIMBURSEMENTS Group 1304110 Education benefits and reimbursements Class 1304111 Education benefits and reimbursements Basic heading 1304200 PRODUCTION OF EDUCATION SERVICES Group 1304210 Compensation of employees Class 1304211 Compensation of employees Basic heading 1304220 Intermediate consumption Class 1304221 Intermediate consumption Basic heading 1304230 Gross operating surplus Class 1304231 Gross operating surplus Basic heading 1304240 Net taxes on production Class 1304241 Net taxes on production Basic heading 1304250 Receipts from sales Class 1304251 Receipt from sales Basic heading 1305000 SOCIAL PROTECTION Category 1305100 SOCIAL PROTECTION Group 1305110 Social protection Class 1305111 Social protection Basic heading 1400000 COLLECTIVE CONSUMPTION EXPENDITURE BY GOVERNMENT Main aggregate 1401000 COLLECTIVE SERVICES Category 1401100 COLLECTIVE SERVICES Group 1401110 Compensation of employees Class 1401111 Compensation of employees Basic heading 1401120 Intermediate consumption Class 1401121 Intermediate consumption Basic heading 1401130 Gross operating surplus Class 1401131 Gross operating surplus Basic heading 1401140 Net taxes on production Class 1401141 Net taxes on production Basic heading 1401150 Receipts from sales Class 1401151 Receipts from sales Basic heading 112    Purchasing Power Parities and the Size of World Economies Table C.2  (Continued) Code Name Expenditure level 1500000 GROSS CAPITAL FORMATION Main aggregate 1501000 GROSS FIXED CAPITAL FORMATION Category 1501100 MACHINERY AND EQUIPMENT Group 1501110 Metal products and equipment Class 1501111 Fabricated metal products, except machinery and equipment Basic heading 1501112 Electrical and optical equipment Basic heading 1501115 General purpose machinery Basic heading 1501116 Special purpose machinery Basic heading 1501120 Transport equipment Class 1501121 Road transport equipment Basic heading 1501122 Other transport equipment Basic heading 1501200 CONSTRUCTION Group 1501210 Residential buildings Class 1501211 Residential buildings Basic heading 1501220 Nonresidential buildings Class 1501221 Nonresidential buildings Basic heading 1501230 Civil engineering works Class 1501231 Civil engineering works Basic heading 1501300 OTHER PRODUCTS Group 1501310 Other products Class 1501311 Other products Basic heading 1502000 CHANGES IN INVENTORIES Category 1502100 CHANGES IN INVENTORIES Group 1502110 Changes in inventories Class 1502111 Changes in inventories * Basic heading 1503000 ACQUISITIONS LESS DISPOSALS OF VALUABLES Category 1503100 ACQUISITIONS LESS DISPOSALS OF VALUABLES Group 1503110 Acquisitions less disposals of valuables Class 1503111 Acquisitions less disposals of valuables * Basic heading 1600000 BALANCE OF EXPORTS AND IMPORTS Main aggregate 1601000 BALANCE OF EXPORTS AND IMPORTS Category 1601100 BALANCE OF EXPORTS AND IMPORTS Group 1601110 Balance of exports and imports Class 1601111 Exports of goods and services Basic heading 1601112 Imports of goods and services Basic heading Source: ICP. Note: n.e.c. = not elsewhere classified. * = newly introduced basic headings. ICP expenditure classification 113 APPENDIX D Reference PPPs used in ICP 2017 The gross domestic product (GDP) expenditures In applying this procedure, basic headings with used for the 2017 International Comparison reference PPPs were not used to generate refer- Program (ICP) were classified into 155 basic ence PPPs for other basic headings for which no headings. However, prices for 55 basic head- prices were collected. ings were not collected in some ICP regions. The reference PPPs proposed for use in ICP For some of these basic headings, it was too dif- 2017 in all regions and the basic headings to ficult to specify comparable items that could be which they apply are listed in table D.1. In most priced across economies; for others, it was too cases, reference PPPs were based on the PPPs of expensive and time-consuming to collect prices. only a few basic headings considered similar to The basic headings for which prices were not the basic headings for which no prices were col- collected in some ICP regions are listed in table lected. For example, the reference PPP for hos- D.1. Some examples are narcotics (1102311), pital services (1106311) is based on the aggrega- prostitution (1112211), financial intermediation tion of the PPP for medical services (1106211), services indirectly measured (FISIM) (1112611), the PPP for dental services (1106221), and the and changes in inventories (1502111). PPP for paramedical services (1106231), where Without prices for those basic headings, the weights used in the aggregation are the aggregation at higher aggregate levels is not pos- expenditures on the constituent basic headings. sible because it is necessary to have a complete In a few cases, reference PPPs are based on the matrix of basic-heading purchasing power pari- PPPs of a large group of basic headings, the ties (PPPs). For that reason, reference PPPs were objective being to ensure that the use of a refer- used in ICP 2017 as proxies for PPPs of the basic ence PPP does not change the PPP of the larger headings for which no prices were collected. group to which the basic heading with a missing The use of reference PPPs has been standard PPP belongs. For example, the PPP for individ- practice in all ICP comparisons, and this appen- ual consumption expenditure by households is dix sets out the reference PPPs used in the ICP used as the reference PPP for the basic-heading 2017 cycle. Further information is available on FISIM (1112611), among others. the ICP website. The number of reference PPPs by ICP main In calculating reference PPPs, the weighted aggregate is the following: 21 under individ- Gini-Éltető-Köves-Szulc (GEKS) method was ual consumption expenditure by households, used. The weights were the expenditures on the 5 under individual consumption expenditure basic headings whose PPPs were being averaged. by nonprofit institutions serving households 115 (NPISHs), 19 under individual consumption regions were advised to apply the reference PPPs expenditure by government, 4 under collective listed in table D.1, it was ultimately up to each consumption expenditure by government, 4 region to decide the basic heading to which a under gross capital formation, and 2 under the reference PPP corresponds and what basic head- balance of exports and imports. Finally, while ings make up a given reference PPP. Table D.1  ICP 2017 Reference PPPs ICP main aggregate Basic heading Reference PPPs Individual 1102311 Narcotics PPP(s) for tobacco (1102211), pharmaceutical products (1106111) consumption 1104211 Imputed rentals for housing PPP(s) for actual rentals for housing (1104111) expenditure by households 1104421 Miscellaneous services relating to PPP(s) for maintenance and repair of the dwelling (1104311), water supply the dwelling (1104411) 1105131 Repair of furniture, furnishings, PPP(s) for maintenance and repair of the dwelling (1104311) and floor coverings 1105331 Repair of household appliances PPP(s) for maintenance and repair of the dwelling (1104311) 1106311 Hospital services PPP(s) for medical services (1106211), dental services (1106221), paramedical services (1106231) 1107141 Animal-drawn vehicles PPP(s) for bicycles (1107131) 1107341 Passenger transport by sea and PPP(s) for passenger transport by railway (1107311), passenger transport by inland waterway road (1107321), passenger transport by air (1107331) 1107351 Combined passenger transport PPP(s) for passenger transport by railway (1107311), passenger transport by road (1107321) 1107361 Other purchased transport PPP(s) for passenger transport by railway (1107311), passenger transport by services road (1107321) 1109211 Major durables for outdoor and PPP(s) for furniture and furnishings (1105111), carpets and other floor coverings indoor recreation (1105121), major household appliances whether electric or not (1105311), major tools and equipment (1105511), therapeutic appliances and equipment (1106131), motor cars (1107111), motor cycles (1107121), bicycles (1107131), telephone and telefax equipment (1108211), audiovisual, photographic, and information processing equipment (1109111), jewelry, clocks, and watches (1112311) 1109231 Maintenance and repair of other PPP(s) for maintenance and repair of personal transport equipment (1107231), major durables for recreation and repair of audiovisual, photographic, and information processing equipment culture (1109151) 1109431 Games of chance PPP(s) for recreational and sporting services (1109411) 1109611 Package holidays PPP(s) for passenger transport by railway (1107311), passenger transport by road (1107321), passenger transport by air (1107331), catering services (1111111), accommodation services (1111211) 1112211 Prostitution PPP(s) for individual consumption expenditure by households (110000), excluding health and education basic headings and basic headings with reference PPPs 1112411 Social protection—individual PPP(s) for compensation of employees—individual health government consumption expenditure by (1302211), intermediate consumption—individual health government (1302221), households gross operating surplus—individual health government (1302231), compensation of employees—individual education government (1304211), intermediate consumption—individual education government (1304221), gross operating surplus—individual education government (1304231) 1112511 Insurance PPP(s) for individual consumption expenditure by households (110000), excluding health and education basic headings and basic headings with reference PPPs 116    Purchasing Power Parities and the Size of World Economies Table D.1  (Continued) ICP main aggregate Basic heading Reference PPPs 1112611 Financial intermediation services PPP(s) for individual consumption expenditure by households (110000), indirectly measured (FISIM) excluding health and education basic headings and basic headings with reference PPPs 1112621 Other financial services n.e.c. PPP(s) for individual consumption expenditure by households (110000), excluding health and education basic headings and basic headings with reference PPPs 1112711 Other services n.e.c. PPP(s) for individual consumption expenditure by households (110000), excluding health and education basic headings and basic headings with reference PPPs 1113111 Net purchases abroad Market exchange rates Individual 1201111 Housing—NPISHs PPP(s) for actual rentals for housing (1104111) consumption 1202111 Health—NPISHs PPP(s) for compensation of employees—individual health government expenditure by (1302211), intermediate consumption—individual health government (1302221), nonprofit institutions gross operating surplus—individual health government (1302231) serving households (NPISHs) 1203111 Recreation and culture—NPISHs PPP(s) for recreational and sporting services (1109411), cultural services (1109421) 1204111 Education—NPISHs PPP(s) for compensation of employees—individual education government (1304211), intermediate consumption—individual education government (1304221), gross operating surplus—individual education government (1304231) 1205111 Social protection and other PPP(s) for compensation of employees—individual health government services—NPISHs (1302211), intermediate consumption—individual health government (1302221), gross operating surplus—individual health government (1302231), compensation of employees—individual education government (1304211), intermediate consumption—individual education government (1304221), gross operating surplus—individual education government (1304231) Individual 1301111 Housing PPP(s) for actual rentals for housing (1104111) consumption 1302111 Pharmaceutical products PPP(s) for pharmaceutical products (1106111) expenditure by government 1302112 Other medical products PPP(s) for other medical products (1106121) 1302113 Therapeutic appliances and PPP(s) for therapeutic appliances and equipment (1106131) equipment 1302121 Outpatient medical services PPP(s) for medical services (1106211) 1302122 Outpatient dental services PPP(s) for dental services (1106221) 1302123 Outpatient paramedical services PPP(s) for paramedical services (1106231) 1302124 Hospital services PPP(s) for hospital services (1106311) 1302221 Intermediate consumption PPP(s) for individual consumption expenditure by households (110000), excluding health and education basic headings and basic headings with reference PPPs 1302231 Gross operating surplus PPP(s) for fabricated metal products, except machinery and equipment (1501111), electrical and optical equipment (1501112), general-purpose machinery (1501115), special-purpose machinery (1501116), road transport equipment (1501121), residential buildings (1501211), nonresidential buildings (1501221), civil engineering works (1501231) 1302241 Net taxes on production— PPP(s) for compensation of employees—individual health government individual health government (1302211), intermediate consumption—individual health government (1302221), gross operating surplus—individual health government (1302231) 1302251 Receipts from sales—individual PPP(s) for compensation of employees—individual health government health government (1302211), intermediate consumption—individual health government (1302221), gross operating surplus—individual health government (1302231) (continued) Reference PPPs used in ICP 2017 117 Table D.1  (Continued) ICP main aggregate Basic heading Reference PPPs 1303111 Recreation and culture PPP(s) for recreational and sporting services (1109411), cultural services (1109421) 1304111 Education benefits and PPP(s) for education (1110111) reimbursements 1304221 Intermediate consumption— PPP(s) for individual consumption expenditure by households (110000), individual education government excluding health and education basic headings and basic headings with reference PPPs 1304231 Gross operating surplus— PPP(s) for fabricated metal products, except machinery and equipment individual education government (1501111), electrical and optical equipment (1501112), general-purpose machinery (1501115), special-purpose machinery (1501116), road transport equipment (1501121), residential buildings (1501211), nonresidential buildings (1501221), civil engineering works (1501231) 1304241 Net taxes on production— PPP(s) for compensation of employees—individual education government individual education government (1304211), intermediate consumption—individual education government (1304221), gross operating surplus—individual education government (1304231) 1304251 Receipt from sales—individual PPP(s) for compensation of employees—individual education government education government (1304211), intermediate consumption—individual education government (1304221), gross operating surplus—individual education government (1304231) 1305111 Social protection—individual PPP(s) for compensation of employees—individual health government consumption expenditure by (1302211), intermediate consumption—individual health government (1302221), government gross operating surplus—individual health government (1302231), compensation of employees—individual education government (1304211), intermediate consumption—individual education government (1304221), gross operating surplus—individual education government (1304231) Collective 1401121 Intermediate consumption— PPP(s) for individual consumption expenditure by households (110000), consumption collective government excluding health and education basic headings and basic headings with expenditure by reference PPPs government 1401131 Gross operating surplus— PPP(s) for fabricated metal products, except machinery and equipment collective government (1501111), electrical and optical equipment (1501112), general-purpose machinery (1501115), special-purpose machinery (1501116), road transport equipment (1501121), residential buildings (1501211), nonresidential buildings (1501221), civil engineering works (1501231) 1401141 Net taxes on production— PPP(s) for compensation of employees—collective government (1401111), collective government intermediate consumption—collective government (1401121), gross operating surplus—collective government (1401131) 1401151 Receipts from sales—collective PPP(s) for compensation of employees—collective government (1401111), government intermediate consumption—collective government (1401121), gross operating surplus—collective government (1401131) Gross capital 1501122 Other transport equipment PPP(s) for road transport equipment (1501121) formation 1501311 Other products PPP(s) for fabricated metal products, except machinery and equipment (1501111), electrical and optical equipment (1501112), general-purpose machinery (1501115), special-purpose machinery (1501116), road transport equipment (1501121) 1502111 Changes in inventories PPP(s) for all basic headings classified as containing predominantly goods (rather than goods and services), excluding basic headings with reference PPPs 1503111 Acquisitions less disposals of Market exchange rates valuables Balance of exports 1601111 Exports of goods and services Market exchange rates and imports 1601112 Imports of goods and services Market exchange rates Note: ICP = International Comparison Program. PPP = purchasing power parity. n.e.c. = not elsewhere classified. 118    Purchasing Power Parities and the Size of World Economies APPENDIX E Revised 2011 results and comparisons with original ICP 2011 results This appendix provides revised 2011 results for In addition, supplementary table E.7 provides the International Comparison Program (ICP) a limited set of results for selected economies and compares them with the original 2011 that did not participate in the 2011 cycle. The results published in 2014. approach for imputing the PPPs for these econo- Tables E.1 to E.6 present revised global 2011 mies is described in chapter 5. results using updated 2011 expenditures, regional Tables E.8 and E.9 compare revised 2011 purchasing power parities (PPPs), population, PPPs with original 2011 PPPs, as well as expen- and market exchange rate data. Subsequently, all ditures in current local currency units for both related indicators were revised. More detailed data sets for the following headings: data sets are available through online databases, • Table E.8 Gross domestic product (GDP) which are accessible through the ICP website1 and through the World Bank’s Databank2 and • Table E.9 Individual consumption expendi- Data Catalog.3 ture by households. In addition, users may acquire access to unpub- The comparison tables cover the following lished ICP data sets, as detailed in the ICP data indicators for each heading: access and archive policy (World Bank 2019a). Results presented in these tables are pro- • Column (00). Name of the economy and its duced by the ICP Global Office and regional International Organization for Standardiza- implementing agencies, based on data supplied tion (ISO) code by participating economies, and in accordance • Column (01). Revised 2011 PPPs with the US with the methodology recommended by the ICP dollar equal to 1 Technical Advisory Group and approved by the • Column (02). Original 2011 PPPs with the US ICP Governing Board. As such, these results are dollar equal to 1 not produced by participating economies as part of their national official statistics. • Column (03). Percentage difference between This appendix provides the main set of results columns (01) and (02) for the following headings: • Column (04). Revised 2011 expenditures in local currency units • Table E.1 Gross domestic product (GDP) • Column (05). Original 2011 expenditures in • Table E.2 Actual individual consumption (AIC) local currency units • Table E.3 Individual consumption expendi- • Column (06). Percentage difference between ture by households columns (04) and (05). • Table E.4 Consumption expenditure by government • Table E.5 Gross fixed capital formation (GFCF) Notes • Table E.6 Domestic absorption. 1.  See icp.worldbank.org/programs/icp#5. The table structure follows that of the 2017 2.  See data.worldbank.org. results (see chapter 2 for the details). 3.  See datacatalog.worldbank.org. 119 Table E.1  Gross domestic product (GDP): Revised ICP 2011 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 971.2 1,513.8 43,474 67,761 201.1 312.3 628.1 87.3 136.0 1.0 2.1 0.3 1.511 0.969 1,467.6 22.34 Brunei Darussalam BRN 33.0 18.5 84,005 47,095 72.3 603.5 436.5 168.6 94.5 0.0 0.0 0.0 0.705 1.258 23.3 0.39 Cambodia KHM 38.0 12.8 2,654 897 43.6 19.1 8.3 5.3 1.8 0.0 0.0 0.2 1,371.235 4,058.500 52,068.7 14.31 China CHN 13,883.0 7,572.6 10,329 5,634 70.4 74.2 52.2 20.7 11.3 14.8 10.4 20.0 3.524 6.461 48,930.1 1,344.13 Fiji FJI 7.7 4.1 9,047 4,786 68.3 65.0 44.4 18.2 9.6 0.0 0.0 0.0 0.949 1.793 7.3 0.85 Hong Kong SAR, China HKG 369.7 248.5 52,277 35,142 86.7 375.5 325.7 105.0 70.6 0.4 0.3 0.1 5.233 7.784 1,934.4 7.07 Indonesia IDN 2,229.5 893.0 9,213 3,690 51.7 66.2 34.2 18.5 7.4 2.4 1.2 3.6 3,512.754 8,770.433 7,831,726.0 241.99 Japan JPN 4,573.2 6,157.5 35,775 48,169 173.7 257.0 446.5 71.8 96.7 4.9 8.5 1.9 107.454 79.807 491,408.5 127.83 Korea, Rep. KOR 1,625.3 1,253.2 32,547 25,096 99.5 233.8 232.6 65.3 50.4 1.7 1.7 0.7 854.586 1,108.292 1,388,937.3 49.94 Lao PDR LAO 26.8 8.9 4,386 1,456 42.8 31.5 13.5 8.8 2.9 0.0 0.0 0.1 2,666.535 8,030.055 71,543.6 6.12 d Macao SAR, China MAC 66.3 36.7 120,358 66,644 71.4 864.6 617.7 241.6 133.8 0.1 0.1 0.0 4.440 8.018 294.3 0.55 Malaysia MYS 621.9 298.0 21,398 10,252 61.8 153.7 95.0 43.0 20.6 0.7 0.4 0.4 1.466 3.060 911.7 29.06 Mongolia MNG 24.7 10.4 8,862 3,736 54.4 63.7 34.6 17.8 7.5 0.0 0.0 0.0 533.527 1,265.516 13,173.8 2.79 Myanmar MMR 167.7 53.7 3,377 1,081 41.3 24.3 10.0 6.8 2.2 0.2 0.1 0.7 261.784 817.917 43,900.0 49.66 New Zealand NZL 142.2 166.9 32,370 37,999 151.5 232.5 352.2 65.0 76.3 0.2 0.2 0.1 1.486 1.266 211.3 4.39 Philippines PHL 536.4 224.1 5,696 2,380 53.9 40.9 22.1 11.4 4.8 0.6 0.3 1.4 18.098 43.313 9,708.3 94.18 Singapore SGP 415.0 279.4 80,052 53,891 86.9 575.1 499.5 160.7 108.2 0.4 0.4 0.1 0.847 1.258 351.4 5.18 Taiwan, China TWN 944.7 485.7 40,736 20,943 66.3 292.6 194.1 81.8 42.0 1.0 0.7 0.3 15.151 29.469 14,312.2 23.19 Thailand THA 912.8 370.8 13,785 5,600 52.4 99.0 51.9 27.7 11.2 1.0 0.5 1.0 12.387 30.492 11,306.9 66.21 Vietnam VNM 402.0 135.5 4,562 1,538 43.5 32.8 14.3 9.2 3.1 0.4 0.2 1.3 6,915.335 20,509.750 2,779,880.2 88.11 Total (20) EAB 27,991.0 19,744.1 12,850 9,064 91.0 92.3 84.0 25.8 18.2 29.9 27.2 32.3 n.a. n.a n.a. 2,178.31  Europe and Central Asia   Albania ALB 29.7 12.9 10,208 4,441 56.1 73.3 41.2 20.5 8.9 0.0 0.0 0.0 43.858 100.812 1,300.6 2.91 Armenia ARM 23.1 10.1 7,624 3,350 56.7 54.8 31.0 15.3 6.7 0.0 0.0 0.0 163.650 372.500 3,777.9 3.03 Austria AUT 373.0 431.7 44,469 51,463 149.3 319.5 477.0 89.3 103.3 0.4 0.6 0.1 0.831 0.718 310.1 8.39 Azerbaijan AZE 135.8 65.9 15,001 7,282 62.6 107.8 67.5 30.1 14.6 0.1 0.1 0.1 0.384 0.790 52.1 9.05 Belarus BLR 156.7 54.8 16,543 5,786 45.1 118.8 53.6 33.2 11.6 0.2 0.1 0.1 0.196 0.561 30.7 9.47 Belgium BEL 451.9 523.3 40,942 47,412 149.4 294.1 439.4 82.2 95.2 0.5 0.7 0.2 0.832 0.718 376.0 11.04 Bosnia and Herzegovina BIH 36.5 18.7 9,976 5,099 65.9 71.7 47.3 20.0 10.2 0.0 0.0 0.1 0.718 1.405 26.2 3.66 Bulgaria BGR 115.1 57.4 15,661 7,815 64.4 112.5 72.4 31.4 15.7 0.1 0.1 0.1 0.701 1.405 80.7 7.35 Croatia HRV 88.8 62.4 20,732 14,558 90.6 148.9 134.9 41.6 29.2 0.1 0.1 0.1 3.753 5.344 333.2 4.28 Cyprus CYP 28.3 27.6 33,314 32,397 125.5 239.3 300.3 66.9 65.0 0.0 0.0 0.0 0.699 0.718 19.8 0.85 Czech Republic CZE 302.3 228.3 28,796 21,754 97.5 206.9 201.6 57.8 43.7 0.3 0.3 0.2 13.345 17.665 4,033.8 10.50 Denmark DNK 247.4 345.0 44,408 61,948 180.0 319.0 574.2 89.2 124.4 0.3 0.5 0.1 7.466 5.352 1,846.9 5.57 Estonia EST 32.9 23.4 24,739 17,618 91.9 177.7 163.3 49.7 35.4 0.0 0.0 0.0 0.512 0.718 16.8 1.33 Finland FIN 220.5 275.6 40,917 51,150 161.3 293.9 474.1 82.1 102.7 0.2 0.4 0.1 0.898 0.718 198.0 5.39 120    Purchasing Power Parities and the Size of World Economies Table E.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) France FRA 2,446.5 2,865.2 37,448 43,858 151.1 269.0 406.5 75.2 88.0 2.6 3.9 1.0 0.841 0.718 2,058.4 65.33 Georgia GEO 31.4 15.1 8,360 4,022 62.1 60.1 37.3 16.8 8.1 0.0 0.0 0.1 0.811 1.686 25.5 3.76 Germany DEU 3,415.0 3,749.4 42,542 46,707 141.7 305.6 432.9 85.4 93.8 3.6 5.2 1.2 0.789 0.718 2,693.6 80.28 Greece GRC 290.3 288.2 26,141 25,951 128.1 187.8 240.5 52.5 52.1 0.3 0.4 0.2 0.713 0.718 207.0 11.11 Hungary HUN 228.3 141.4 22,894 14,176 79.9 164.5 131.4 46.0 28.5 0.2 0.2 0.1 124.272 200.697 28,370.8 9.97 Iceland ISL 13.0 15.2 40,769 47,515 150.4 292.9 440.4 81.8 95.4 0.0 0.0 0.0 135.152 115.963 1,757.7 0.32 Ireland IRL 205.4 237.8 44,870 51,936 149.3 322.3 481.4 90.1 104.3 0.2 0.3 0.1 0.832 0.718 170.8 4.58 Italy ITA 2,173.2 2,295.1 36,183 38,213 136.3 259.9 354.2 72.6 76.7 2.3 3.2 0.9 0.759 0.718 1,648.8 60.06 Kazakhstan KAZ 344.0 192.6 20,779 11,634 72.2 149.3 107.8 41.7 23.4 0.4 0.3 0.2 82.090 146.620 28,243.1 16.56 Kyrgyz Republic KGZ 18.2 6.2 3,457 1,178 44.0 24.8 10.9 6.9 2.4 0.0 0.0 0.1 15.728 46.144 286.0 5.26 Latvia LVA 40.6 28.1 19,700 13,670 89.5 141.5 126.7 39.5 27.4 0.0 0.0 0.0 0.499 0.718 20.2 2.06 Lithuania LTU 69.1 43.5 22,824 14,358 81.2 164.0 133.1 45.8 28.8 0.1 0.1 0.0 0.452 0.718 31.2 3.03 Luxembourg LUX 47.7 60.1 91,813 115,675 162.6 659.6 1,072.1 184.3 232.2 0.1 0.1 0.0 0.905 0.718 43.2 0.52 Moldova MDA 19.8 8.4 5,554 2,366 55.0 39.9 21.9 11.2 4.8 0.0 0.0 0.1 4.996 11.726 98.8 3.56 Montenegro MNE 9.0 4.5 14,473 7,329 65.3 104.0 67.9 29.1 14.7 0.0 0.0 0.0 0.364 0.718 3.3 0.62 Netherlands NLD 777.9 905.3 46,599 54,232 150.2 334.8 502.7 93.6 108.9 0.8 1.2 0.2 0.836 0.718 650.4 16.69 North Macedonia MKD 24.1 10.5 11,690 5,101 56.3 84.0 47.3 23.5 10.2 0.0 0.0 0.0 19.290 44.202 464.2 2.06 Norway NOR 307.5 498.8 62,078 100,708 209.3 445.9 933.4 124.6 202.2 0.3 0.7 0.1 9.083 5.599 2,792.7 4.95 Poland POL 869.8 529.3 22,576 13,739 78.5 162.2 127.3 45.3 27.6 0.9 0.7 0.6 1.801 2.960 1,566.8 38.53 Portugal PRT 282.6 245.1 26,769 23,218 111.9 192.3 215.2 53.7 46.6 0.3 0.3 0.2 0.623 0.718 176.1 10.56 Romania ROU 360.8 183.6 17,908 9,115 65.7 128.6 84.5 36.0 18.3 0.4 0.3 0.3 1.550 3.045 559.2 20.15 Russian Federation RUS 3,268.5 2,051.7 22,863 14,351 81.0 164.2 133.0 45.9 28.8 3.5 2.8 2.1 18.444 29.382 60,282.5 142.96 Serbia SRB 99.4 49.3 13,742 6,816 64.0 98.7 63.2 27.6 13.7 0.1 0.1 0.1 36.324 73.240 3,612.3 7.24 Slovak Republic SVK 140.6 99.1 26,051 18,364 91.0 187.1 170.2 52.3 36.9 0.1 0.1 0.1 0.506 0.718 71.2 5.40 Slovenia SVN 59.4 51.6 28,931 25,129 112.1 207.8 232.9 58.1 50.4 0.1 0.1 0.0 0.624 0.718 37.1 2.05 Spain ESP 1,486.4 1,477.6 31,803 31,615 128.3 228.5 293.0 63.8 63.5 1.6 2.0 0.7 0.714 0.718 1,061.5 46.74 Sweden SWE 420.5 573.3 44,504 60,675 175.9 319.7 562.4 89.3 121.8 0.4 0.8 0.1 8.844 6.487 3,719.1 9.45 Switzerland CHE 444.5 701.6 56,184 88,671 203.6 403.6 821.9 112.8 178.0 0.5 1.0 0.1 1.397 0.885 621.3 7.91 Tajikistan TJK 19.2 6.5 2,491 846 43.8 17.9 7.8 5.0 1.7 0.0 0.0 0.1 1.565 4.610 30.1 7.71 Turkey TUR 1,443.3 832.5 19,445 11,217 74.4 139.7 104.0 39.0 22.5 1.5 1.1 1.1 0.966 1.675 1,394.5 74.22 d Ukraine UKR 422.6 169.3 9,247 3,705 51.7 66.4 34.3 18.6 7.4 0.5 0.2 0.7 3.192 7.968 1,349.2 45.71 United Kingdom GBR 2,350.8 2,662.1 37,146 42,066 146.1 266.8 389.9 74.6 84.5 2.5 3.7 0.9 0.706 0.623 1,659.8 63.29 Total (46) ECB 24,371.3 23,135.5 28,490 27,046 122.5 204.7 250.7 57.2 54.3 26.0 31.8 12.7 n.a. n.a n.a. 855.42 Latin America and the Caribbean                            Anguilla AIA 0.4 0.3 28,940 21,336 95.1 207.9 197.8 58.1 42.8 0.0 0.0 0.0 1.990 2.700 0.8 0.01 Antigua and Barbuda ATG 1.8 1.1 20,426 12,796 80.8 146.7 118.6 41.0 25.7 0.0 0.0 0.0 1.691 2.700 3.1 0.09 Aruba ABW 3.6 2.6 34,794 25,326 93.9 249.9 234.7 69.9 50.8 0.0 0.0 0.0 1.303 1.790 4.6 0.10 (continued) Revised 2011 results and comparisons with original ICP 2011 results 121 Table E.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 11.2 10.1 31,168 28,006 115.9 223.9 259.6 62.6 56.2 0.0 0.0 0.0 0.899 1.000 10.1 0.36 Barbados BRB 4.6 4.7 16,316 16,470 130.2 117.2 152.7 32.8 33.1 0.0 0.0 0.0 2.019 2.000 9.3 0.28 Belize BLZ 2.6 1.5 7,821 4,502 74.3 56.2 41.7 15.7 9.0 0.0 0.0 0.0 1.151 2.000 3.0 0.33 Bolivia BOL 55.8 23.8 5,460 2,331 55.1 39.2 21.6 11.0 4.7 0.1 0.0 0.2 2.981 6.982 166.2 10.21 Bonairee BON … … … … … … … … … … … … … 1.000 … 0.02 Brazil BRA 2,970.6 2,616.2 15,040 13,245 113.6 108.0 122.8 30.2 26.6 3.2 3.6 2.9 1.473 1.673 4,376.4 197.51 Cayman Islands CYM 3.7 4.2 64,014 72,326 145.8 459.9 670.4 128.5 145.2 0.0 0.0 0.0 0.942 0.833 3.5 0.06 Chile CHL 350.6 252.3 20,303 14,609 92.8 145.8 135.4 40.8 29.3 0.4 0.3 0.3 348.017 483.668 122,006.1 17.27 Colombia COL 529.1 334.5 11,491 7,264 81.6 82.5 67.3 23.1 14.6 0.6 0.5 0.7 1,168.243 1,848.139 618,117.7 46.04 Costa Rica CRI 62.0 42.3 13,514 9,208 87.9 97.1 85.3 27.1 18.5 0.1 0.1 0.1 344.546 505.664 21,370.7 4.59 Curaçao CUW 4.1 3.0 26,959 19,950 95.5 193.7 184.9 54.1 40.1 0.0 0.0 0.0 1.325 1.790 5.4 0.15 Dominica DMA 0.7 0.5 10,199 7,065 89.4 73.3 65.5 20.5 14.2 0.0 0.0 0.0 1.870 2.700 1.4 0.07 Dominican Republic DOM 116.5 58.0 11,869 5,912 64.3 85.3 54.8 23.8 11.9 0.1 0.1 0.1 18.976 38.099 2,210.2 9.81 Ecuador ECU 150.3 79.3 9,858 5,201 68.1 70.8 48.2 19.8 10.4 0.2 0.1 0.2 0.528 1.000 79.3 15.24 El Salvador SLV 40.2 20.3 6,466 3,266 65.2 46.4 30.3 13.0 6.6 0.0 0.0 0.1 0.505 1.000 20.3 6.21 Grenada GRD 1.2 0.8 11,116 7,291 84.6 79.9 67.6 22.3 14.6 0.0 0.0 0.0 1.771 2.700 2.1 0.11 Guatemalad GTM 102.0 47.5 6,825 3,179 60.1 49.0 29.5 13.7 6.4 0.1 0.1 0.2 3.637 7.807 371.0 14.95 Haiti HTI 17.1 7.7 1,694 764 58.2 12.2 7.1 3.4 1.5 0.0 0.0 0.1 18.495 40.977 316.4 10.10 Honduras HND 33.3 17.6 3,928 2,074 68.1 28.2 19.2 7.9 4.2 0.0 0.0 0.1 10.057 19.048 335.0 8.48 Jamaica JAM 23.1 14.4 8,160 5,110 80.8 58.6 47.4 16.4 10.3 0.0 0.0 0.0 53.805 85.911 1,240.7 2.83 Mexico MEX 1,911.3 1,180.5 16,547 10,220 79.7 118.9 94.7 33.2 20.5 2.0 1.6 1.7 7.673 12.423 14,665.6 115.51 Montserrat MSR 0.1 0.1 20,405 12,915 81.7 146.6 119.7 41.0 25.9 0.0 0.0 0.0 1.709 2.700 0.2 0.00 Nicaragua NIC 25.2 9.8 4,263 1,656 50.1 30.6 15.3 8.6 3.3 0.0 0.0 0.1 8.710 22.424 219.2 5.90 Panama PAN 62.7 34.7 16,924 9,358 71.3 121.6 86.7 34.0 18.8 0.1 0.0 0.1 0.553 1.000 34.7 3.71 Paraguay PRY 66.4 33.8 10,491 5,334 65.6 75.4 49.4 21.1 10.7 0.1 0.0 0.1 2,126.670 4,183.127 141,315.8 6.33 Peru PER 306.6 171.8 10,477 5,869 72.3 75.3 54.4 21.0 11.8 0.3 0.2 0.4 1.543 2.754 473.0 29.26 Sint Maarten SXM 1.2 0.9 35,510 26,701 97.0 255.1 247.5 71.3 53.6 0.0 0.0 0.0 1.346 1.790 1.7 0.04 St. Kitts and Nevis KNA 1.1 0.8 22,768 16,538 93.7 163.6 153.3 45.7 33.2 0.0 0.0 0.0 1.961 2.700 2.2 0.05 St. Lucia LCA 2.1 1.4 12,141 8,227 87.4 87.2 76.3 24.4 16.5 0.0 0.0 0.0 1.830 2.700 3.9 0.18 St. Vincent and the VCT 1.2 0.7 10,634 6,443 78.2 76.4 59.7 21.3 12.9 0.0 0.0 0.0 1.636 2.700 1.9 0.11 Grenadines Suriname SUR 7.7 4.3 14,445 8,044 71.9 103.8 74.6 29.0 16.2 0.0 0.0 0.0 1.866 3.350 14.4 0.54 Trinidad and Tobago TTO 41.9 25.7 31,321 19,250 79.3 225.0 178.4 62.9 38.6 0.0 0.0 0.0 3.950 6.426 165.3 1.34 Turks and Caicos Islands TCA 0.7 0.7 21,232 21,835 132.7 152.5 202.4 42.6 43.8 0.0 0.0 0.0 1.028 1.000 0.7 0.03 Uruguay URY 60.7 48.0 18,003 14,237 102.0 129.3 132.0 36.1 28.6 0.1 0.1 0.1 15.274 19.314 926.4 3.37 Venezuela, RBd VEN 506.3 316.5 17,528 10,956 80.6 125.9 101.5 35.2 22.0 0.5 0.4 0.4 2.681 4.289 1,357.5 28.89 Virgin Islands, British VGB 0.9 0.9 31,464 32,331 132.6 226.0 299.7 63.2 64.9 0.0 0.0 0.0 1.028 1.000 0.9 0.03 Total (39) LCB 7,480.6 5,373.1 13,850 9,948 92.7 99.5 92.2 27.8 20.0 8.0 7.4 8.0 n.a. n.a n.a. 540.10 122    Purchasing Power Parities and the Size of World Economies Table E.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 494.9 200.0 13,500 5,456 52.1 97.0 50.6 27.1 11.0 0.5 0.3 0.5 29.476 72.938 14,589.0 36.66 Bahrain BHR 60.5 28.8 50,666 24,077 61.3 364.0 223.2 101.7 48.3 0.1 0.0 0.0 0.179 0.376 10.8 1.20 Djibouti DJI 4.2 2.2 4,916 2,588 67.9 35.3 24.0 9.9 5.2 0.0 0.0 0.0 93.572 177.721 392.7 0.85 Egypt, Arab Rep. EGY 905.5 255.0 11,245 3,166 36.3 80.8 29.3 22.6 6.4 1.0 0.4 1.2 1.675 5.947 1,516.4 80.53 Iran, Islamic Rep. IRN 1,584.8 710.4 21,089 9,453 57.8 151.5 87.6 42.3 19.0 1.7 1.0 1.1 4,758.870 10,616.307 7,542,036.5 75.15 Iraq IRQ 366.2 159.8 10,985 4,794 56.3 78.9 44.4 22.1 9.6 0.4 0.2 0.5 523.340 1,199.200 191,652.9 33.34 Israel ISR 237.2 261.5 30,551 33,681 142.2 219.5 312.2 61.3 67.6 0.3 0.4 0.1 3.945 3.578 935.6 7.76 Jordan JOR 70.5 29.0 10,077 4,141 53.0 72.4 38.4 20.2 8.3 0.1 0.0 0.1 0.291 0.708 20.5 6.99 Kuwait KWT 247.6 151.8 80,758 49,526 79.1 580.1 459.0 162.1 99.4 0.3 0.2 0.0 0.172 0.280 42.5 3.07 Malta MLT 11.9 9.5 28,586 22,846 103.1 205.4 211.8 57.4 45.9 0.0 0.0 0.0 0.574 0.718 6.8 0.42 Morocco MAR 223.3 101.9 6,855 3,127 58.9 49.2 29.0 13.8 6.3 0.2 0.1 0.5 3.672 8.049 820.1 32.58 Oman OMN 141.2 67.9 42,843 20,597 62.0 307.8 190.9 86.0 41.4 0.2 0.1 0.0 0.185 0.385 26.1 3.30 Qatar QAT 283.7 167.3 163,740 96,563 76.1 1,176.3 895.0 328.7 193.9 0.3 0.2 0.0 2.153 3.650 610.7 1.73 Saudi Arabia SAU 1,586.7 671.2 56,321 23,825 54.6 404.6 220.8 113.1 47.8 1.7 0.9 0.4 1.586 3.750 2,517.1 28.17 Tunisia TUN 108.2 45.8 10,069 4,265 54.7 72.3 39.5 20.2 8.6 0.1 0.1 0.2 0.596 1.408 64.5 10.74 United Arab Emirates ARE 605.6 350.7 69,831 40,437 74.7 501.6 374.8 140.2 81.2 0.6 0.5 0.1 2.127 3.673 1,287.8 8.67 West Bank and Gaza PSE 15.6 10.5 4,015 2,698 86.7 28.8 25.0 8.1 5.4 0.0 0.0 0.1 2.405 3.578 37.4 3.88 d Yemen, Rep. YEM 82.4 31.4 3,458 1,318 49.2 24.8 12.2 6.9 2.6 0.1 0.0 0.4 81.477 213.800 6,714.9 23.83 Total (17) MEB 7,030.1 3,254.7 19,589 9,069 59.7 140.7 84.1 39.3 18.2 7.5 4.5 5.3 n.a. n.a n.a. 358.87 North America   Bermuda BMU 4.0 5.6 61,692 86,171 180.2 443.2 798.7 123.9 173.0 0.0 0.0 0.0 1.397 1.000 5.6 0.07 Canada CAN 1,430.8 1,792.8 41,663 52,204 161.7 299.3 483.9 83.6 104.8 1.5 2.5 0.5 1.240 0.990 1,774.1 34.34 United States USA 15,542.6 15,542.6 49,811 49,811 129.0 357.8 461.7 100.0 100.0 16.6 21.4 4.6 1.000 1.000 15,542.6 312.03 Total (3) NAB 16,977.4 17,341.0 49,005 50,055 131.8 352.0 463.9 98.4 100.5 18.1 23.9 5.1 n.a. n.a n.a. 346.44 South Asia                                   Bangladesh BGD 421.0 132.9 2,812 888 40.7 20.2 8.2 5.6 1.8 0.4 0.2 2.2 23.410 74.152 9,855.2 149.70 Bhutan BTN 5.2 1.8 7,625 2,679 45.3 54.8 24.8 15.3 5.4 0.0 0.0 0.0 16.397 46.670 85.0 0.68 India IND 5,482.9 1,826.8 4,508 1,502 43.0 32.4 13.9 9.1 3.0 5.8 2.5 18.1 15.550 46.670 85,256.2 1,216.15 Maldives MDV 5.2 2.8 12,681 6,827 69.5 91.1 63.3 25.5 13.7 0.0 0.0 0.0 7.862 14.602 40.5 0.41 Nepal NPL 57.1 19.5 2,154 735 44.0 15.5 6.8 4.3 1.5 0.1 0.0 0.4 25.255 74.020 1,440.8 26.49 Pakistan PAK 767.6 221.9 4,334 1,253 37.3 31.1 11.6 8.7 2.5 0.8 0.3 2.6 24.962 86.343 19,161.5 177.10 Sri Lanka LKA 183.7 65.3 9,099 3,233 45.8 65.4 30.0 18.3 6.5 0.2 0.1 0.3 39.289 110.565 7,219.1 20.20 Total (7) SAB 6,922.6 2,270.9 4,352 1,428 42.3 31.3 13.2 8.7 2.9 7.4 3.1 23.6 n.a. n.a n.a. 1,590.72 Sub-Saharan Africa                            Angola AGO 164.0 112.8 6,772 4,658 88.7 48.6 43.2 13.6 9.4 0.2 0.2 0.4 64.606 93.935 10,597.0 24.22 Benin BEN 16.7 7.8 1,767 825 60.3 12.7 7.7 3.5 1.7 0.0 0.0 0.1 220.434 471.866 3,684.9 9.46 Botswana BWA 28.7 15.4 14,253 7,617 69.0 102.4 70.6 28.6 15.3 0.0 0.0 0.0 3.655 6.838 105.0 2.02 (continued) Revised 2011 results and comparisons with original ICP 2011 results 123 Table E.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 22.8 10.8 1,419 671 61.0 10.2 6.2 2.8 1.3 0.0 0.0 0.2 223.116 471.866 5,092.6 16.08 Burundi BDI 6.1 2.3 686 251 47.2 4.9 2.3 1.4 0.5 0.0 0.0 0.1 461.509 1,261.073 2,837.7 8.96 Cabo Verde CPV 3.0 1.9 5,966 3,738 80.8 42.9 34.6 12.0 7.5 0.0 0.0 0.0 49.695 79.323 147.9 0.50 Cameroon CMR 58.0 29.3 2,774 1,403 65.3 19.9 13.0 5.6 2.8 0.1 0.0 0.3 238.707 471.866 13,843.1 20.91 Central African Republic CAF 4.5 2.4 1,013 551 70.2 7.3 5.1 2.0 1.1 0.0 0.0 0.1 256.761 471.866 1,148.9 4.42 Chad TCD 22.8 12.5 1,846 1,010 70.6 13.3 9.4 3.7 2.0 0.0 0.0 0.2 258.131 471.866 5,891.4 12.36 Comoros COM 1.7 1.0 2,337 1,446 79.8 16.8 13.4 4.7 2.9 0.0 0.0 0.0 218.978 353.900 361.6 0.71 Congo, Dem. Rep. COD 58.7 34.0 879 509 74.7 6.3 4.7 1.8 1.0 0.1 0.0 1.0 532.063 919.491 31,230.5 66.76 Congo, Rep. COG 25.1 16.5 5,714 3,745 84.6 41.0 34.7 11.5 7.5 0.0 0.0 0.1 309.251 471.866 7,765.6 4.39 Côte d’Ivoire CIV 51.1 25.7 2,431 1,221 64.8 17.5 11.3 4.9 2.5 0.1 0.0 0.3 236.911 471.866 12,112.7 21.03 Equatorial Guinea GNQ 33.8 21.3 34,280 21,613 81.3 246.3 200.3 68.8 43.4 0.0 0.0 0.0 297.509 471.866 10,064.6 0.99 Eswatini SWZ 8.5 4.7 7,889 4,403 72.0 56.7 40.8 15.8 8.8 0.0 0.0 0.0 4.052 7.261 34.3 1.07 Ethiopia ETH 152.6 45.5 1,693 505 38.4 12.2 4.7 3.4 1.0 0.2 0.1 1.3 5.036 16.899 768.6 90.14 Gabon GAB 27.9 19.3 16,562 11,433 89.1 119.0 106.0 33.2 23.0 0.0 0.0 0.0 325.733 471.866 9,088.2 1.68 Gambia, The GMB 4.0 1.4 2,150 740 44.4 15.4 6.9 4.3 1.5 0.0 0.0 0.0 10.142 29.462 40.3 1.85 Ghana GHA 85.8 39.6 3,379 1,558 59.5 24.3 14.4 6.8 3.1 0.1 0.1 0.4 0.697 1.512 59.8 25.39 Guinea GIN 18.2 6.8 1,744 651 48.2 12.5 6.0 3.5 1.3 0.0 0.0 0.2 2,485.901 6,658.031 45,176.5 10.42 Guinea-Bissau GNB 2.2 1.1 1,439 703 63.0 10.3 6.5 2.9 1.4 0.0 0.0 0.0 230.392 471.866 518.3 1.56 Kenya KEN 105.3 42.0 2,439 972 51.4 17.5 9.0 4.9 2.0 0.1 0.1 0.6 35.396 88.811 3,727.4 43.18 Lesotho LSO 4.8 2.7 2,386 1,341 72.5 17.1 12.4 4.8 2.7 0.0 0.0 0.0 4.081 7.261 19.5 2.00 Liberia LBR 2.8 1.5 702 383 70.4 5.0 3.6 1.4 0.8 0.0 0.0 0.1 39.424 72.227 111.2 4.02 Madagascar MDG 33.7 11.6 1,549 532 44.3 11.1 4.9 3.1 1.1 0.0 0.0 0.3 694.863 2,025.118 23,404.5 21.74 Malawi MWI 15.9 8.0 1,063 535 64.9 7.6 5.0 2.1 1.1 0.0 0.0 0.2 78.769 156.515 1,253.2 14.96 Mali MLI 28.3 13.0 1,827 837 59.1 13.1 7.8 3.7 1.7 0.0 0.0 0.2 216.090 471.866 6,123.9 15.51 Mauritania MRT 12.1 5.2 3,372 1,436 54.9 24.2 13.3 6.8 2.9 0.0 0.0 0.1 119.682 281.118 1,452.4 3.60 Mauritius MUS 25.1 13.9 20,102 11,102 71.3 144.4 102.9 40.4 22.3 0.0 0.0 0.0 15.853 28.706 398.7 1.25 Mozambique MOZ 24.5 14.3 1,015 590 75.0 7.3 5.5 2.0 1.2 0.0 0.0 0.4 16.894 29.068 414.6 24.19 Namibia NAM 19.1 12.4 8,859 5,772 84.1 63.6 53.5 17.8 11.6 0.0 0.0 0.0 4.732 7.261 90.4 2.16 Niger NER 13.4 6.4 781 374 61.8 5.6 3.5 1.6 0.8 0.0 0.0 0.3 226.128 471.866 3,024.3 17.11 Nigeria NGA 798.9 409.0 4,907 2,512 66.1 35.2 23.3 9.9 5.0 0.9 0.6 2.4 78.777 153.862 62,931.7 162.81 Rwanda RWA 13.9 6.4 1,354 624 59.5 9.7 5.8 2.7 1.3 0.0 0.0 0.2 276.649 600.307 3,854.3 10.29 São Tomé and Príncipe STP 0.6 0.3 3,259 1,374 54.4 23.4 12.7 6.5 2.8 0.0 0.0 0.0 7.431 17.623 4.5 0.18 Senegal SEN 36.2 18.5 2,780 1,422 66.0 20.0 13.2 5.6 2.9 0.0 0.0 0.2 241.276 471.866 8,743.8 13.03 Seychelles SYC 1.9 1.1 20,739 11,531 71.7 149.0 106.9 41.6 23.1 0.0 0.0 0.0 6.884 12.381 13.1 0.09 Sierra Leone SLE 7.9 2.9 1,203 448 48.1 8.6 4.2 2.4 0.9 0.0 0.0 0.1 1,620.575 4,349.162 12,797.6 6.56 South Africa ZAF 639.2 420.5 12,291 8,086 84.9 88.3 74.9 24.7 16.2 0.7 0.6 0.8 4.777 7.261 3,053.2 52.00 Sudan SDN 147.9 50.2 4,354 1,477 43.8 31.3 13.7 8.7 3.0 0.2 0.1 0.5 1.231 3.630 182.2 33.98 124    Purchasing Power Parities and the Size of World Economies Table E.1  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange GROSS DOMESTIC PRODUCT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 101.6 35.3 2,224 773 44.8 16.0 7.2 4.5 1.6 0.1 0.0 0.7 546.073 1,572.116 55,469.0 45.67 Togo TGO 8.0 3.9 1,218 590 62.5 8.8 5.5 2.4 1.2 0.0 0.0 0.1 228.625 471.866 1,837.1 6.60 Uganda UGA 85.5 29.0 2,553 866 43.8 18.3 8.0 5.1 1.7 0.1 0.0 0.5 856.168 2,522.746 73,174.3 33.48 Zambia ZMB 50.6 25.5 3,607 1,816 64.9 25.9 16.8 7.2 3.6 0.1 0.0 0.2 2.446 4.861 123.8 14.02 Zimbabwe ZWE 23.3 12.1 1,803 938 67.1 13.0 8.7 3.6 1.9 0.0 0.0 0.2 0.520 1.000 12.1 12.89 Total (45) SSB 2,996.9 1,557.4 3,460 1,798 67.0 24.9 16.7 6.9 3.6 3.2 2.1 12.9 n.a. n.a n.a. 866.25 World (178) WLD 93,769.9 72,676.7 13,920 10,789 100.0 100.0 100.0 27.9 21.7 100.0 100.0 100.0 n.a. n.a. n.a. 6,736.12 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. National accounts expenditures for the revised ICP 2011 results are estimated by the ICP Global Office. e. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either Latin America and the Caribbean or the world totals. Revised 2011 results and comparisons with original ICP 2011 results 125 Table E.2  Actual individual consumption (AIC): Revised ICP 2011 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 635.3 986.4 28,439 44,152 195.0 320.7 625.2 76.6 118.9 1.1 2.1 0.3 1.505 0.969 956.2 22.34 Brunei Darussalam BRN 5.2 3.2 13,219 8,061 76.6 149.0 114.1 35.6 21.7 0.0 0.0 0.0 0.767 1.258 4.0 0.39 Cambodia KHM 33.1 10.8 2,311 756 41.1 26.1 10.7 6.2 2.0 0.1 0.0 0.2 1,327.047 4,058.500 43,880.6 14.31 China CHN 6,031.2 3,249.5 4,487 2,418 67.7 50.6 34.2 12.1 6.5 10.1 6.8 20.0 3.481 6.461 20,996.3 1,344.13 Fiji FJI 5.7 3.0 6,725 3,560 66.5 75.8 50.4 18.1 9.6 0.0 0.0 0.0 0.949 1.793 5.5 0.85 Hong Kong SAR, China HKG 241.7 165.7 34,177 23,426 86.1 385.3 331.7 92.0 63.1 0.4 0.3 0.1 5.335 7.784 1,289.5 7.07 Indonesia IDN 1,316.2 525.1 5,439 2,170 50.1 61.3 30.7 14.6 5.8 2.2 1.1 3.6 3,499.323 8,770.433 4,605,767.6 241.99 Japan JPN 3,154.7 4,312.6 24,678 33,737 171.7 278.3 477.7 66.4 90.8 5.3 9.1 1.9 109.100 79.807 344,176.3 127.83 Korea, Rep. KOR 941.1 721.5 18,845 14,449 96.3 212.5 204.6 50.7 38.9 1.6 1.5 0.7 849.741 1,108.292 799,652.0 49.94 Lao PDR LAO 16.5 5.6 2,698 912 42.4 30.4 12.9 7.3 2.5 0.0 0.0 0.1 2,713.182 8,030.055 44,775.1 6.12 Macao SAR, Chinad MAC 14.4 8.7 26,210 15,883 76.1 295.5 224.9 70.6 42.8 0.0 0.0 0.0 4.859 8.018 70.2 0.55 Malaysia MYS 339.5 162.3 11,682 5,586 60.1 131.7 79.1 31.4 15.0 0.6 0.3 0.4 1.463 3.060 496.8 29.06 Mongolia MNG 15.1 5.9 5,423 2,131 49.4 61.2 30.2 14.6 5.7 0.0 0.0 0.0 497.347 1,265.516 7,515.7 2.79 Myanmar MMR 108.1 32.9 2,177 663 38.3 24.5 9.4 5.9 1.8 0.2 0.1 0.7 249.138 817.917 26,938.9 49.66 New Zealand NZL 100.1 116.8 22,784 26,582 146.5 256.9 376.4 61.3 71.6 0.2 0.2 0.1 1.477 1.266 147.8 4.39 Philippines PHL 431.2 173.9 4,579 1,846 50.6 51.6 26.1 12.3 5.0 0.7 0.4 1.4 17.466 43.313 7,532.0 94.18 Singapore SGP 137.6 111.5 26,554 21,512 101.7 299.4 304.6 71.5 57.9 0.2 0.2 0.1 1.019 1.258 140.3 5.18 Taiwan, China TWN 588.2 301.7 25,366 13,010 64.4 286.0 184.2 68.3 35.0 1.0 0.6 0.3 15.114 29.469 8,891.0 23.19 Thailand THA 593.9 229.8 8,970 3,470 48.6 101.1 49.1 24.1 9.3 1.0 0.5 1.0 11.797 30.492 7,006.7 66.21 Vietnam VNM 264.2 86.0 2,998 975 40.9 33.8 13.8 8.1 2.6 0.4 0.2 1.3 6,673.613 20,509.750 1,762,838.5 88.11 Total (20) EAB 14,973.1 11,212.9 6,874 5,148 94.0 77.5 72.9 18.5 13.9 25.1 23.6 32.3 n.a. n.a n.a. 2,178.31 Europe and Central Asia Albania ALB 23.7 10.8 8,174 3,711 57.0 92.2 52.5 22.0 10.0 0.0 0.0 0.0 45.770 100.812 1,086.9 2.91 Armenia ARM 22.7 9.0 7,486 2,976 49.9 84.4 42.1 20.2 8.0 0.0 0.0 0.0 148.074 372.500 3,356.4 3.03 Austria AUT 238.3 282.9 28,409 33,723 149.1 320.3 477.5 76.5 90.8 0.4 0.6 0.1 0.853 0.718 203.2 8.39 Azerbaijan AZE 73.4 27.1 8,105 2,988 46.3 91.4 42.3 21.8 8.0 0.1 0.1 0.1 0.291 0.790 21.4 9.05 Belarus BLR 108.8 31.3 11,483 3,300 36.1 129.5 46.7 30.9 8.9 0.2 0.1 0.1 0.161 0.561 17.5 9.47 Belgium BEL 288.5 349.7 26,140 31,683 152.2 294.7 448.6 70.4 85.3 0.5 0.7 0.2 0.871 0.718 251.2 11.04 Bosnia and Herzegovina BIH 32.7 17.9 8,941 4,877 68.5 100.8 69.1 24.1 13.1 0.1 0.0 0.1 0.766 1.405 25.1 3.66 Bulgaria BGR 82.2 40.3 11,185 5,488 61.6 126.1 77.7 30.1 14.8 0.1 0.1 0.1 0.689 1.405 56.7 7.35 Croatia HRV 60.7 44.6 14,182 10,415 92.2 159.9 147.5 38.2 28.0 0.1 0.1 0.1 3.925 5.344 238.4 4.28 Cyprus CYP 19.8 20.4 23,254 24,020 129.7 262.2 340.1 62.6 64.7 0.0 0.0 0.0 0.742 0.718 14.7 0.85 Czech Republic CZE 183.2 136.2 17,451 12,972 93.4 196.8 183.7 47.0 34.9 0.3 0.3 0.2 13.131 17.665 2,405.3 10.50 Denmark DNK 152.3 229.6 27,336 41,228 189.4 308.2 583.8 73.6 111.0 0.3 0.5 0.1 8.073 5.352 1,229.1 5.57 Estonia EST 19.6 14.2 14,706 10,662 91.1 165.8 151.0 39.6 28.7 0.0 0.0 0.0 0.521 0.718 10.2 1.33 Finland FIN 143.9 188.6 26,701 35,007 164.6 301.1 495.7 71.9 94.2 0.2 0.4 0.1 0.942 0.718 135.5 5.39 126    Purchasing Power Parities and the Size of World Economies Table E.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) France FRA 1,704.9 2,015.8 26,097 30,856 148.5 294.2 436.9 70.3 83.1 2.9 4.2 1.0 0.849 0.718 1,448.2 65.33 Georgia GEO 29.2 13.0 7,781 3,469 56.0 87.7 49.1 20.9 9.3 0.0 0.0 0.1 0.752 1.686 22.0 3.76 Germany DEU 2,260.3 2,491.8 28,157 31,041 138.4 317.5 439.5 75.8 83.6 3.8 5.2 1.2 0.792 0.718 1,790.1 80.28 Greece GRC 227.5 232.8 20,483 20,960 128.5 230.9 296.8 55.1 56.4 0.4 0.5 0.2 0.735 0.718 167.2 11.11 Hungary HUN 147.5 89.6 14,787 8,986 76.3 166.7 127.2 39.8 24.2 0.2 0.2 0.1 121.962 200.697 17,983.8 9.97 Iceland ISL 8.6 10.2 27,020 31,925 148.4 304.7 452.0 72.7 85.9 0.0 0.0 0.0 137.011 115.963 1,181.0 0.32 Ireland IRL 105.2 139.1 22,986 30,377 166.0 259.2 430.1 61.9 81.8 0.2 0.3 0.1 0.949 0.718 99.9 4.58 Italy ITA 1,517.8 1,661.4 25,272 27,662 137.5 284.9 391.7 68.0 74.5 2.5 3.5 0.9 0.786 0.718 1,193.5 60.06 Kazakhstan KAZ 189.6 90.7 11,452 5,475 60.0 129.1 77.5 30.8 14.7 0.3 0.2 0.2 70.097 146.620 13,291.4 16.56 Kyrgyz Republic KGZ 18.8 5.8 3,568 1,103 38.8 40.2 15.6 9.6 3.0 0.0 0.0 0.1 14.269 46.144 267.8 5.26 Latvia LVA 27.6 19.6 13,408 9,514 89.1 151.2 134.7 36.1 25.6 0.0 0.0 0.0 0.510 0.718 14.1 2.06 Lithuania LTU 50.5 31.8 16,678 10,492 79.0 188.0 148.6 44.9 28.2 0.1 0.1 0.0 0.452 0.718 22.8 3.03 Luxembourg LUX 16.9 24.8 32,593 47,805 184.2 367.5 676.9 87.7 128.7 0.0 0.1 0.0 1.054 0.718 17.8 0.52 Moldova MDA 21.6 8.9 6,080 2,495 51.5 68.6 35.3 16.4 6.7 0.0 0.0 0.1 4.811 11.726 104.1 3.56 Montenegro MNE 7.8 4.1 12,534 6,659 66.7 141.3 94.3 33.7 17.9 0.0 0.0 0.0 0.382 0.718 3.0 0.62 Netherlands NLD 470.9 572.2 28,210 34,278 152.6 318.1 485.4 75.9 92.3 0.8 1.2 0.2 0.873 0.718 411.1 16.69 North Macedonia MKD 18.7 8.6 9,087 4,184 57.8 102.5 59.2 24.5 11.3 0.0 0.0 0.0 20.350 44.202 380.7 2.06 Norway NOR 152.4 271.6 30,765 54,841 223.9 346.9 776.5 82.8 147.6 0.3 0.6 0.1 9.980 5.599 1,520.8 4.95 Poland POL 651.0 377.1 16,899 9,788 72.7 190.5 138.6 45.5 26.3 1.1 0.8 0.6 1.715 2.960 1,116.3 38.53 Portugal PRT 203.8 187.3 19,300 17,743 115.5 217.6 251.2 52.0 47.8 0.3 0.4 0.2 0.660 0.718 134.6 10.56 Romania ROU 251.1 129.1 12,465 6,407 64.6 140.5 90.7 33.6 17.2 0.4 0.3 0.3 1.565 3.045 393.1 20.15 Russian Federation RUS 2,095.0 1,193.6 14,654 8,349 71.5 165.2 118.2 39.5 22.5 3.5 2.5 2.1 16.740 29.382 35,069.5 142.96 Serbia SRB 81.9 42.4 11,319 5,863 65.0 127.6 83.0 30.5 15.8 0.1 0.1 0.1 37.935 73.240 3,107.3 7.24 Slovak Repubic SVK 93.0 63.6 17,221 11,782 85.9 194.2 166.8 46.4 31.7 0.2 0.1 0.1 0.491 0.718 45.7 5.40 Slovenia SVN 39.3 35.5 19,148 17,282 113.3 215.9 244.7 51.5 46.5 0.1 0.1 0.0 0.648 0.718 25.5 2.05 Spain ESP 979.2 1,040.3 20,952 22,258 133.4 236.2 315.2 56.4 59.9 1.6 2.2 0.7 0.763 0.718 747.3 46.74 Sweden SWE 259.9 369.2 27,504 39,071 178.4 310.1 553.2 74.0 105.2 0.4 0.8 0.1 9.215 6.487 2,394.9 9.45 Switzerland CHE 236.6 412.4 29,897 52,121 218.9 337.1 738.0 80.5 140.3 0.4 0.9 0.1 1.544 0.885 365.2 7.91 Tajikistan TJK 22.5 7.5 2,922 973 41.8 32.9 13.8 7.9 2.6 0.0 0.0 0.1 1.535 4.610 34.6 7.71 Turkey TUR 984.8 582.9 13,268 7,854 74.3 149.6 111.2 35.7 21.1 1.6 1.2 1.1 0.991 1.675 976.4 74.22 Ukrained UKR 372.8 134.0 8,156 2,932 45.2 92.0 41.5 22.0 7.9 0.6 0.3 0.7 2.865 7.968 1,067.9 45.71 United Kingdom GBR 1,718.7 2,062.9 27,159 32,597 150.7 306.2 461.6 73.1 87.8 2.9 4.3 0.9 0.748 0.623 1,286.2 63.29 Total (46) ECB 16,415.3 15,732.2 19,190 18,391 120.4 216.4 260.4 51.7 49.5 27.5 33.1 12.7 n.a. n.a n.a. 855.42 Latin America and the Caribbean Anguilla AIA 0.3 0.3 23,295 19,314 104.1 262.7 273.5 62.7 52.0 0.0 0.0 0.0 2.239 2.700 0.7 0.01 Antigua and Barbuda ATG 1.1 0.8 12,426 8,822 89.2 140.1 124.9 33.5 23.8 0.0 0.0 0.0 1.917 2.700 2.1 0.09 Aruba ABW 2.4 2.0 23,418 19,794 106.1 264.0 280.3 63.0 53.3 0.0 0.0 0.0 1.513 1.790 3.6 0.10 (continued) Revised 2011 results and comparisons with original ICP 2011 results 127 Table E.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 6.9 7.1 19,257 19,769 128.9 217.1 279.9 51.8 53.2 0.0 0.0 0.0 1.027 1.000 7.1 0.36 Barbados BRB 3.3 3.7 11,676 13,063 140.5 131.6 185.0 31.4 35.2 0.0 0.0 0.0 2.238 2.000 7.4 0.28 Belize BLZ 2.0 1.1 6,200 3,364 68.1 69.9 47.6 16.7 9.1 0.0 0.0 0.0 1.085 2.000 2.2 0.33 Bolivia BOL 37.8 14.8 3,700 1,454 49.3 41.7 20.6 10.0 3.9 0.1 0.0 0.2 2.743 6.982 103.6 10.21 Bonairee BON … … … … … … … … … … … … … 1.000 … 0.02 Brazil BRA 2,022.8 1,778.5 10,241 9,005 110.4 115.5 127.5 27.6 24.2 3.4 3.7 2.9 1.471 1.673 2,975.2 197.51 Cayman Islands CYM 1.9 2.4 32,643 41,039 157.9 368.1 581.1 87.9 110.5 0.0 0.0 0.0 1.048 0.833 2.0 0.06 Chile CHL 233.6 170.6 13,528 9,881 91.7 152.5 139.9 36.4 26.6 0.4 0.4 0.3 353.270 483.668 82,521.1 17.27 Colombia COL 377.1 231.6 8,189 5,030 77.1 92.3 71.2 22.0 13.5 0.6 0.5 0.7 1,135.228 1,848.139 428,058.2 46.04 Costa Rica CRI 49.7 33.1 10,827 7,211 83.6 122.1 102.1 29.1 19.4 0.1 0.1 0.1 336.767 505.664 16,734.4 4.59 Curaçao CUW 3.0 2.3 19,915 14,921 94.1 224.5 211.3 53.6 40.2 0.0 0.0 0.0 1.341 1.790 4.1 0.15 Dominica DMA 0.7 0.5 9,200 6,463 88.2 103.7 91.5 24.8 17.4 0.0 0.0 0.0 1.897 2.700 1.2 0.07 Dominican Republic DOM 94.3 46.2 9,613 4,712 61.6 108.4 66.7 25.9 12.7 0.2 0.1 0.1 18.676 38.099 1,761.8 9.81 Ecuador ECU 105.2 53.5 6,899 3,511 63.9 77.8 49.7 18.6 9.5 0.2 0.1 0.2 0.509 1.000 53.5 15.24 El Salvador SLV 38.8 19.1 6,242 3,079 61.9 70.4 43.6 16.8 8.3 0.1 0.0 0.1 0.493 1.000 19.1 6.21 Grenada GRD 1.1 0.8 10,078 7,132 88.9 113.6 101.0 27.1 19.2 0.0 0.0 0.0 1.911 2.700 2.1 0.11 Guatemalad GTM 92.6 42.8 6,193 2,863 58.1 69.8 40.5 16.7 7.7 0.2 0.1 0.2 3.609 7.807 334.1 14.95 Haiti HTI 18.8 8.8 1,866 872 58.7 21.0 12.3 5.0 2.3 0.0 0.0 0.1 19.149 40.977 360.8 10.10 Honduras HND 29.4 15.1 3,463 1,782 64.6 39.1 25.2 9.3 4.8 0.0 0.0 0.1 9.803 19.048 287.9 8.48 Jamaica JAM 20.3 13.5 7,173 4,761 83.3 80.9 67.4 19.3 12.8 0.0 0.0 0.0 57.018 85.911 1,155.8 2.83 Mexico MEX 1,354.7 838.8 11,728 7,262 77.8 132.2 102.8 31.6 19.5 2.3 1.8 1.7 7.692 12.423 10,420.9 115.51 Montserrat MSR 0.1 0.1 15,549 11,289 91.2 175.3 159.9 41.9 30.4 0.0 0.0 0.0 1.960 2.700 0.1 0.00 Nicaragua NIC 21.9 8.1 3,703 1,380 46.8 41.7 19.5 10.0 3.7 0.0 0.0 0.1 8.359 22.424 182.7 5.90 Panama PAN 41.1 21.1 11,087 5,685 64.4 125.0 80.5 29.8 15.3 0.1 0.0 0.1 0.513 1.000 21.1 3.71 Paraguay PRY 47.2 23.0 7,449 3,629 61.2 84.0 51.4 20.1 9.8 0.1 0.0 0.1 2,037.699 4,183.127 96,145.6 6.33 Peru PER 208.4 110.3 7,122 3,768 66.4 80.3 53.4 19.2 10.1 0.3 0.2 0.4 1.457 2.754 303.7 29.26 Sint Maarten SXM 0.8 0.7 23,633 19,035 101.2 266.5 269.5 63.6 51.2 0.0 0.0 0.0 1.442 1.790 1.2 0.04 St. Kitts and Nevis KNA 0.8 0.6 16,678 12,381 93.2 188.0 175.3 44.9 33.3 0.0 0.0 0.0 2.004 2.700 1.7 0.05 St. Lucia LCA 1.7 1.2 9,807 6,921 88.6 110.6 98.0 26.4 18.6 0.0 0.0 0.0 1.905 2.700 3.3 0.18 St. Vincent and the VCT 1.0 0.6 8,936 5,917 83.1 100.8 83.8 24.1 15.9 0.0 0.0 0.0 1.788 2.700 1.7 0.11 Grenadines Suriname SUR 3.2 1.6 6,047 3,073 63.8 68.2 43.5 16.3 8.3 0.0 0.0 0.0 1.703 3.350 5.5 0.54 Trinidad and Tobago TTO 21.7 13.9 16,264 10,394 80.3 183.4 147.2 43.8 28.0 0.0 0.0 0.0 4.107 6.426 89.2 1.34 Turks and Caicos Islands TCA 0.3 0.3 8,147 9,366 144.4 91.9 132.6 21.9 25.2 0.0 0.0 0.0 1.150 1.000 0.3 0.03 Uruguay URY 44.4 35.5 13,178 10,551 100.5 148.6 149.4 35.5 28.4 0.1 0.1 0.1 15.463 19.314 686.5 3.37 d Venezuela, RB VEN 309.0 192.1 10,695 6,649 78.1 120.6 94.1 28.8 17.9 0.5 0.4 0.4 2.666 4.289 823.8 28.89 Virgin Islands, British VGB 0.3 0.3 10,736 12,000 140.4 121.0 169.9 28.9 32.3 0.0 0.0 0.0 1.118 1.000 0.3 0.03 Total (39) LCB 5,199.6 3,696.9 9,627 6,845 89.3 108.5 96.9 25.9 18.4 8.7 7.8 8.0 n.a. n.a n.a. 540.10 128    Purchasing Power Parities and the Size of World Economies Table E.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 235.4 86.5 6,422 2,361 46.2 72.4 33.4 17.3 6.4 0.4 0.2 0.5 26.814 72.938 6,312.7 36.66 Bahrain BHR 28.2 12.8 23,585 10,750 57.2 265.9 152.2 63.5 28.9 0.0 0.0 0.0 0.171 0.376 4.8 1.20 Djibouti DJI 2.7 1.4 3,135 1,650 66.1 35.3 23.4 8.4 4.4 0.0 0.0 0.0 93.533 177.721 250.3 0.85 Egypt, Arab Rep. EGY 807.1 212.2 10,023 2,636 33.0 113.0 37.3 27.0 7.1 1.4 0.4 1.2 1.564 5.947 1,262.2 80.53 Iran, Islamic Rep. IRN 918.9 393.4 12,227 5,235 53.8 137.9 74.1 32.9 14.1 1.5 0.8 1.1 4,545.742 10,616.307 4,176,900.0 75.15 Iraq IRQ 197.7 75.2 5,929 2,255 47.8 66.9 31.9 16.0 6.1 0.3 0.2 0.5 456.052 1,199.200 90,152.8 33.34 Israel ISR 158.8 179.3 20,460 23,092 141.7 230.7 327.0 55.1 62.2 0.3 0.4 0.1 4.038 3.578 641.4 7.76 Jordan JOR 59.3 24.9 8,483 3,562 52.7 95.6 50.4 22.8 9.6 0.1 0.1 0.1 0.297 0.708 17.6 6.99 Kuwait KWT 71.7 47.3 23,379 15,444 83.0 263.6 218.7 62.9 41.6 0.1 0.1 0.0 0.185 0.280 13.3 3.07 Malta MLT 7.8 6.6 18,822 15,822 105.6 212.2 224.0 50.7 42.6 0.0 0.0 0.0 0.604 0.718 4.7 0.42 Morocco MAR 146.1 68.9 4,485 2,116 59.2 50.6 30.0 12.1 5.7 0.2 0.1 0.5 3.797 8.049 554.8 32.58 Oman OMN 50.1 25.2 15,188 7,638 63.2 171.3 108.1 40.9 20.6 0.1 0.1 0.0 0.193 0.385 9.7 3.30 Qatar QAT 36.7 28.2 21,189 16,260 96.4 238.9 230.2 57.0 43.8 0.1 0.1 0.0 2.801 3.650 102.8 1.73 Saudi Arabia SAU 622.0 245.9 22,078 8,730 49.7 248.9 123.6 59.4 23.5 1.0 0.5 0.4 1.483 3.750 922.3 28.17 Tunisia TUN 77.2 34.1 7,184 3,174 55.5 81.0 44.9 19.3 8.5 0.1 0.1 0.2 0.622 1.408 48.0 10.74 United Arab Emirates ARE 249.1 159.3 28,728 18,367 80.3 323.9 260.1 77.3 49.4 0.4 0.3 0.1 2.348 3.673 584.9 8.67 West Bank and Gaza PSE 16.2 10.3 4,176 2,648 79.6 47.1 37.5 11.2 7.1 0.0 0.0 0.1 2.269 3.578 36.7 3.88 Yemen, Rep.d YEM 67.2 22.9 2,822 963 42.8 31.8 13.6 7.6 2.6 0.1 0.0 0.4 72.934 213.800 4,904.7 23.83 Total (17) MEB 3,752.2 1,634.6 10,456 4,555 54.7 117.9 64.5 28.1 12.3 6.3 3.4 5.3 n.a. n.a n.a. 358.87 North America Bermuda BMU 2.1 3.6 32,682 54,995 211.3 368.5 778.7 88.0 148.0 0.0 0.0 0.0 1.683 1.000 3.6 0.07 Canada CAN 952.1 1,223.3 27,723 35,622 161.4 312.6 504.4 74.6 95.9 1.6 2.6 0.5 1.271 0.990 1,210.5 34.34 United States USA 11,590.9 11,590.9 37,146 37,146 125.6 418.8 526.0 100.0 100.0 19.4 24.4 4.6 1.000 1.000 11,590.9 312.03 Total (3) NAB 12,545.1 12,817.8 36,211 36,998 128.3 408.3 523.9 97.5 99.6 21.0 26.9 5.1 n.a. n.a n.a. 346.44 South Asia Bangladesh BGD 330.2 100.2 2,206 670 38.1 24.9 9.5 5.9 1.8 0.6 0.2 2.2 22.508 74.152 7,432.8 149.70 Bhutan BTN 2.7 0.9 4,021 1,326 41.4 45.3 18.8 10.8 3.6 0.0 0.0 0.0 15.388 46.670 42.0 0.68 India IND 3,546.3 1,078.2 2,916 887 38.2 32.9 12.6 7.9 2.4 5.9 2.3 18.1 14.190 46.670 50,322.0 1,216.15 Maldives MDV 1.9 1.0 4,651 2,555 69.0 52.4 36.2 12.5 6.9 0.0 0.0 0.0 8.021 14.602 15.2 0.41 Nepal NPL 48.5 15.5 1,832 586 40.2 20.7 8.3 4.9 1.6 0.1 0.0 0.4 23.676 74.020 1,148.8 26.49 Pakistan PAK 694.5 188.4 3,921 1,064 34.1 44.2 15.1 10.6 2.9 1.2 0.4 2.6 23.419 86.343 16,264.1 177.10 Sri Lanka LKA 145.3 49.1 7,196 2,433 42.5 81.1 34.5 19.4 6.6 0.2 0.1 0.3 37.384 110.565 5,433.1 20.20 Total (7) SAB 4,769.5 1,433.4 2,998 901 37.7 33.8 12.8 8.1 2.4 8.0 3.0 23.6 n.a. n.a n.a. 1,590.72 Sub-Saharan Africa Angola AGO 58.0 45.9 2,393 1,895 99.4 27.0 26.8 6.4 5.1 0.1 0.1 0.4 74.381 93.935 4,311.0 24.22 Benin BEN 13.9 6.1 1,465 648 55.6 16.5 9.2 3.9 1.7 0.0 0.0 0.1 208.779 471.866 2,893.2 9.46 Botswana BWA 14.5 8.2 7,185 4,051 70.8 81.0 57.4 19.3 10.9 0.0 0.0 0.0 3.855 6.838 55.8 2.02 (continued) Revised 2011 results and comparisons with original ICP 2011 results 129 Table E.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 16.1 7.0 1,004 438 54.8 11.3 6.2 2.7 1.2 0.0 0.0 0.2 205.922 471.866 3,325.4 16.08 Burundi BDI 6.1 2.2 683 244 44.9 7.7 3.5 1.8 0.7 0.0 0.0 0.1 450.615 1,261.073 2,757.3 8.96 Cabo Verde CPV 2.4 1.3 4,734 2,657 70.5 53.4 37.6 12.7 7.2 0.0 0.0 0.0 44.526 79.323 105.1 0.50 Cameroon CMR 44.6 21.0 2,131 1,005 59.2 24.0 14.2 5.7 2.7 0.1 0.0 0.3 222.431 471.866 9,910.4 20.91 Central African Republic CAF 4.1 2.1 937 477 64.0 10.6 6.8 2.5 1.3 0.0 0.0 0.1 240.351 471.866 995.0 4.42 Chad TCD 15.5 7.6 1,253 611 61.2 14.1 8.6 3.4 1.6 0.0 0.0 0.2 230.002 471.866 3,562.8 12.36 Comoros COM 1.6 1.0 2,312 1,393 75.6 26.1 19.7 6.2 3.7 0.0 0.0 0.0 213.162 353.900 348.2 0.71 Congo, Dem. Rep. COD 38.9 20.7 582 310 66.8 6.6 4.4 1.6 0.8 0.1 0.0 1.0 489.288 919.491 19,021.3 66.76 Congo, Rep. COG 7.9 4.7 1,786 1,059 74.4 20.1 15.0 4.8 2.9 0.0 0.0 0.1 279.715 471.866 2,196.1 4.39 Côte d’Ivoire CIV 38.6 18.5 1,838 880 60.1 20.7 12.5 4.9 2.4 0.1 0.0 0.3 225.960 471.866 8,732.4 21.03 Equatorial Guinea GNQ 8.2 5.3 8,311 5,380 81.3 93.7 76.2 22.4 14.5 0.0 0.0 0.0 305.437 471.866 2,505.2 0.99 Eswatini SWZ 7.7 4.1 7,170 3,861 67.6 80.8 54.7 19.3 10.4 0.0 0.0 0.0 3.911 7.261 30.1 1.07 Ethiopia ETH 114.3 33.4 1,268 371 36.7 14.3 5.3 3.4 1.0 0.2 0.1 1.3 4.942 16.899 565.0 90.14 Gabon GAB 8.3 5.8 4,911 3,468 88.7 55.4 49.1 13.2 9.3 0.0 0.0 0.0 333.273 471.866 2,757.0 1.68 Gambia, The GMB 3.6 1.2 1,971 663 42.2 22.2 9.4 5.3 1.8 0.0 0.0 0.0 9.910 29.462 36.1 1.85 Ghana GHA 72.0 33.5 2,835 1,321 58.5 32.0 18.7 7.6 3.6 0.1 0.1 0.4 0.704 1.512 50.7 25.39 Guinea GIN 16.2 5.7 1,559 546 44.0 17.6 7.7 4.2 1.5 0.0 0.0 0.2 2,331.030 6,658.031 37,870.5 10.42 Guinea-Bissau GNB 2.0 1.0 1,255 608 60.9 14.1 8.6 3.4 1.6 0.0 0.0 0.0 228.728 471.866 448.5 1.56 Kenya KEN 98.4 37.2 2,280 862 47.5 25.7 12.2 6.1 2.3 0.2 0.1 0.6 33.562 88.811 3,303.9 43.18 Lesotho LSO 5.5 2.8 2,736 1,399 64.2 30.9 19.8 7.4 3.8 0.0 0.0 0.0 3.712 7.261 20.4 2.00 Liberia LBR 2.6 1.4 635 345 68.2 7.2 4.9 1.7 0.9 0.0 0.0 0.1 39.202 72.227 100.0 4.02 Madagascar MDG 28.2 8.9 1,298 408 39.5 14.6 5.8 3.5 1.1 0.0 0.0 0.3 637.466 2,025.118 17,986.0 21.74 Malawi MWI 15.0 7.1 1,001 472 59.2 11.3 6.7 2.7 1.3 0.0 0.0 0.2 73.830 156.515 1,105.5 14.96 Mali MLI 22.6 9.8 1,454 632 54.6 16.4 8.9 3.9 1.7 0.0 0.0 0.2 204.987 471.866 4,624.7 15.51 Mauritania MRT 7.1 2.6 1,961 729 46.7 22.1 10.3 5.3 2.0 0.0 0.0 0.1 104.505 281.118 737.3 3.60 Mauritius MUS 15.1 8.9 12,052 7,116 74.2 135.9 100.8 32.4 19.2 0.0 0.0 0.0 16.950 28.706 255.6 1.25 Mozambique MOZ 21.3 11.2 879 462 66.0 9.9 6.5 2.4 1.2 0.0 0.0 0.4 15.272 29.068 324.7 24.19 Namibia NAM 14.0 9.2 6,506 4,286 82.7 73.4 60.7 17.5 11.5 0.0 0.0 0.0 4.783 7.261 67.1 2.16 Niger NER 11.0 4.9 642 287 56.2 7.2 4.1 1.7 0.8 0.0 0.0 0.3 211.097 471.866 2,318.0 17.11 Nigeria NGA 552.2 274.5 3,392 1,686 62.4 38.2 23.9 9.1 4.5 0.9 0.6 2.4 76.499 153.862 42,241.1 162.81 Rwanda RWA 13.3 5.3 1,288 516 50.3 14.5 7.3 3.5 1.4 0.0 0.0 0.2 240.593 600.307 3,188.5 10.29 São Tomé and Príncipe STP 0.5 0.2 2,719 1,307 60.4 30.7 18.5 7.3 3.5 0.0 0.0 0.0 8.471 17.623 4.3 0.18 Senegal SEN 31.7 15.5 2,436 1,187 61.2 27.5 16.8 6.6 3.2 0.1 0.0 0.2 230.011 471.866 7,302.7 13.03 Seychelles SYC 1.1 0.6 12,234 7,074 72.6 137.9 100.2 32.9 19.0 0.0 0.0 0.0 7.159 12.381 8.0 0.09 Sierra Leone SLE 7.6 2.9 1,156 441 47.9 13.0 6.2 3.1 1.2 0.0 0.0 0.1 1,657.769 4,349.162 12,580.1 6.56 South Africa ZAF 446.6 292.0 8,588 5,615 82.1 96.8 79.5 23.1 15.1 0.7 0.6 0.8 4.748 7.261 2,120.4 52.00 Sudan SDN 99.4 36.1 2,927 1,062 45.6 33.0 15.0 7.9 2.9 0.2 0.1 0.5 1.318 3.630 131.0 33.98 130    Purchasing Power Parities and the Size of World Economies Table E.2  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market ACTUAL INDIVIDUAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange CONSUMPTION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 76.7 26.4 1,680 578 43.2 18.9 8.2 4.5 1.6 0.1 0.1 0.7 540.694 1,572.116 41,486.7 45.67 Togo TGO 7.2 3.2 1,086 492 56.9 12.2 7.0 2.9 1.3 0.0 0.0 0.1 213.798 471.866 1,531.7 6.60 Uganda UGA 67.0 22.9 2,001 684 42.9 22.6 9.7 5.4 1.8 0.1 0.0 0.5 861.869 2,522.746 57,732.7 33.48 Zambia ZMB 27.7 13.8 1,975 988 62.8 22.3 14.0 5.3 2.7 0.0 0.0 0.2 2.431 4.861 67.3 14.02 Zimbabwe ZWE 22.2 11.0 1,723 852 62.1 19.4 12.1 4.6 2.3 0.0 0.0 0.2 0.495 1.000 11.0 12.89 Total (45) SSB 2,088.3 1,044.9 2,411 1,206 62.8 27.2 17.1 6.5 3.2 3.5 2.2 12.9 n.a. n.a n.a. 866.25 World (178) WLD 59,743.2 47,572.8 8,869 7,062 100.0 100.0 100.0 23.9 19.0 100.0 100.0 100.0 n.a. n.a. n.a. 6,736.12 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. National accounts expenditures for the revised ICP 2011 results are estimated by the ICP Global Office. e. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either Latin America and the Caribbean or the world totals. Revised 2011 results and comparisons with original ICP 2011 results 131 Table E.3  Individual consumption expenditure by households: Revised ICP 2011 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 522.8 822.8 23,402 36,832 189.0 319.4 603.9 68.6 108.0 1.1 2.0 0.3 1.526 0.969 797.7 22.34 Brunei Darussalam BRN 3.6 2.4 9,101 6,019 79.4 124.2 98.7 26.7 17.6 0.0 0.0 0.0 0.832 1.258 3.0 0.39 Cambodia KHM 27.7 10.2 1,939 714 44.2 26.5 11.7 5.7 2.1 0.1 0.0 0.2 1,493.254 4,058.500 41,431.0 14.31 China CHN 4,546.6 2,601.8 3,383 1,936 68.7 46.2 31.7 9.9 5.7 9.2 6.3 20.0 3.698 6.461 16,811.1 1,344.13 Fiji FJI 4.9 2.8 5,782 3,277 68.1 78.9 53.7 17.0 9.6 0.0 0.0 0.0 1.016 1.793 5.0 0.85 Hong Kong SAR, China HKG 216.8 157.3 30,661 22,244 87.1 418.5 364.7 89.9 65.2 0.4 0.4 0.1 5.647 7.784 1,224.4 7.07 Indonesia IDN 1,115.2 494.9 4,608 2,045 53.3 62.9 33.5 13.5 6.0 2.3 1.2 3.6 3,892.218 8,770.433 4,340,605.4 241.99 Japan JPN 2,485.3 3,586.8 19,442 28,059 173.3 265.4 460.0 57.0 82.3 5.0 8.7 1.9 115.178 79.807 286,254.9 127.83 Korea, Rep. KOR 787.3 641.6 15,765 12,849 97.9 215.2 210.7 46.2 37.7 1.6 1.6 0.7 903.294 1,108.292 711,118.8 49.94 Lao PDR LAO 13.9 5.4 2,280 887 46.7 31.1 14.5 6.7 2.6 0.0 0.0 0.1 3,124.075 8,030.055 43,566.6 6.12 d Macao SAR, China MAC 12.0 7.7 21,788 14,032 77.4 297.4 230.1 63.9 41.1 0.0 0.0 0.0 5.164 8.018 62.0 0.55 Malaysia MYS 275.7 142.9 9,486 4,918 62.3 129.5 80.6 27.8 14.4 0.6 0.3 0.4 1.586 3.060 437.3 29.06 Mongolia MNG 11.7 5.4 4,192 1,924 55.1 57.2 31.5 12.3 5.6 0.0 0.0 0.0 580.638 1,265.516 6,782.7 2.79 Myanmar MMR 95.3 32.4 1,919 653 40.9 26.2 10.7 5.6 1.9 0.2 0.1 0.7 278.394 817.917 26,528.1 49.66 New Zealand NZL 78.1 97.4 17,770 22,161 149.8 242.6 363.3 52.1 65.0 0.2 0.2 0.1 1.579 1.266 123.2 4.39 Philippines PHL 380.0 164.7 4,034 1,748 52.1 55.1 28.7 11.8 5.1 0.8 0.4 1.4 18.772 43.313 7,132.6 94.18 Singapore SGP 117.7 102.2 22,699 19,713 104.3 309.9 323.2 66.6 57.8 0.2 0.2 0.1 1.092 1.258 128.5 5.18 Taiwan, China TWN 483.3 264.7 20,842 11,412 65.8 284.5 187.1 61.1 33.5 1.0 0.6 0.3 16.136 29.469 7,799.0 23.19 Thailand THA 479.5 200.6 7,241 3,030 50.3 98.8 49.7 21.2 8.9 1.0 0.5 1.0 12.759 30.492 6,117.6 66.21 Vietnam VNM 217.6 79.9 2,470 907 44.1 33.7 14.9 7.2 2.7 0.4 0.2 1.3 7,528.385 20,509.750 1,638,345.5 88.11 Total (20) EAB 11,875.0 9,423.9 5,451 4,326 95.3 74.4 70.9 16.0 12.7 24.1 22.9 32.3 n.a. n.a n.a. 2,178.31 Europe and Central Asia Albania ALB 18.6 10.1 6,414 3,477 65.1 87.6 57.0 18.8 10.2 0.0 0.0 0.0 54.653 100.812 1,018.4 2.91 Armenia ARM 19.1 8.5 6,303 2,803 53.4 86.0 45.9 18.5 8.2 0.0 0.0 0.0 165.629 372.500 3,161.0 3.03 Austria AUT 194.4 230.4 23,178 27,471 142.4 316.4 450.4 68.0 80.6 0.4 0.6 0.1 0.851 0.718 165.5 8.39 Azerbaijan AZE 60.0 24.6 6,627 2,713 49.2 90.5 44.5 19.4 8.0 0.1 0.1 0.1 0.323 0.790 19.4 9.05 Belarus BLR 80.8 26.7 8,527 2,818 39.7 116.4 46.2 25.0 8.3 0.2 0.1 0.1 0.185 0.561 15.0 9.47 Belgium BEL 220.8 269.7 20,001 24,437 146.8 273.0 400.7 58.6 71.7 0.4 0.7 0.2 0.878 0.718 193.8 11.04 Bosnia and Herzegovina BIH 25.9 15.7 7,066 4,297 73.0 96.5 70.5 20.7 12.6 0.1 0.0 0.1 0.854 1.405 22.1 3.66 Bulgaria BGR 63.2 35.7 8,604 4,861 67.9 117.4 79.7 25.2 14.3 0.1 0.1 0.1 0.794 1.405 50.2 7.35 Croatia HRV 48.3 38.2 11,273 8,912 95.0 153.9 146.1 33.1 26.1 0.1 0.1 0.1 4.225 5.344 204.0 4.28 Cyprus CYP 17.2 18.1 20,186 21,321 126.9 275.5 349.6 59.2 62.5 0.0 0.0 0.0 0.759 0.718 13.0 0.85 Czech Republic CZE 137.0 112.0 13,056 10,671 98.2 178.2 175.0 38.3 31.3 0.3 0.3 0.2 14.439 17.665 1,978.7 10.50 Denmark DNK 106.1 165.3 19,054 29,682 187.1 260.1 486.6 55.9 87.0 0.2 0.4 0.1 8.338 5.352 884.9 5.57 Estonia EST 14.5 11.7 10,922 8,819 97.0 149.1 144.6 32.0 25.9 0.0 0.0 0.0 0.580 0.718 8.4 1.33 Finland FIN 108.2 146.5 20,079 27,193 162.7 274.1 445.8 58.9 79.7 0.2 0.4 0.1 0.973 0.718 105.3 5.39 132    Purchasing Power Parities and the Size of World Economies Table E.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) France FRA 1,286.4 1,575.4 19,690 24,114 147.1 268.8 395.4 57.7 70.7 2.6 3.8 1.0 0.880 0.718 1,131.7 65.33 Georgia GEO 25.1 12.4 6,679 3,308 59.5 91.2 54.2 19.6 9.7 0.1 0.0 0.1 0.835 1.686 21.0 3.76 Germany DEU 1,771.2 2,039.2 22,065 25,403 138.3 301.2 416.5 64.7 74.5 3.6 5.0 1.2 0.827 0.718 1,464.9 80.28 Greece GRC 188.4 201.4 16,962 18,135 128.4 231.5 297.3 49.7 53.2 0.4 0.5 0.2 0.768 0.718 144.7 11.11 Hungary HUN 109.2 74.6 10,946 7,482 82.1 149.4 122.7 32.1 21.9 0.2 0.2 0.1 137.179 200.697 14,973.8 9.97 Iceland ISL 6.5 7.9 20,408 24,781 145.8 278.6 406.3 59.8 72.7 0.0 0.0 0.0 140.808 115.963 916.7 0.32 Ireland IRL 82.7 110.3 18,072 24,095 160.1 246.7 395.0 53.0 70.7 0.2 0.3 0.1 0.958 0.718 79.3 4.58 Italy ITA 1,236.8 1,402.7 20,592 23,354 136.2 281.1 382.9 60.4 68.5 2.5 3.4 0.9 0.815 0.718 1,007.7 60.06 Kazakhstan KAZ 150.4 81.3 9,085 4,909 64.9 124.0 80.5 26.6 14.4 0.3 0.2 0.2 79.222 146.620 11,916.1 16.56 Kyrgyz Republic KGZ 14.6 5.2 2,783 983 42.4 38.0 16.1 8.2 2.9 0.0 0.0 0.1 16.296 46.144 238.5 5.26 Latvia LVA 21.9 17.3 10,630 8,387 94.8 145.1 137.5 31.2 24.6 0.0 0.0 0.0 0.567 0.718 12.4 2.06 Lithuania LTU 38.2 27.1 12,603 8,959 85.4 172.0 146.9 37.0 26.3 0.1 0.1 0.0 0.511 0.718 19.5 3.03 Luxembourg LUX 13.8 18.8 26,580 36,245 163.8 362.8 594.2 77.9 106.3 0.0 0.0 0.0 0.980 0.718 13.5 0.52 Moldova MDA 17.0 7.8 4,766 2,199 55.4 65.1 36.0 14.0 6.4 0.0 0.0 0.1 5.410 11.726 91.8 3.56 Montenegro MNE 6.0 3.7 9,736 5,978 73.8 132.9 98.0 28.5 17.5 0.0 0.0 0.0 0.441 0.718 2.7 0.62 Netherlands NLD 339.3 413.2 20,326 24,751 146.3 277.5 405.8 59.6 72.6 0.7 1.0 0.2 0.875 0.718 296.8 16.69 North Macedonia MKD 14.5 7.8 7,060 3,770 64.1 96.4 61.8 20.7 11.1 0.0 0.0 0.0 23.608 44.202 343.1 2.06 Norway NOR 114.6 201.0 23,143 40,576 210.6 315.9 665.3 67.9 119.0 0.2 0.5 0.1 9.816 5.599 1,125.2 4.95 Poland POL 508.3 325.3 13,194 8,445 76.9 180.1 138.5 38.7 24.8 1.0 0.8 0.6 1.895 2.960 963.1 38.53 Portugal PRT 168.1 161.5 15,919 15,298 115.4 217.3 250.8 46.7 44.9 0.3 0.4 0.2 0.690 0.718 116.0 10.56 Romania ROU 196.0 116.5 9,726 5,782 71.4 132.8 94.8 28.5 17.0 0.4 0.3 0.3 1.810 3.045 354.8 20.15 Russian Federation RUS 1,617.0 1,026.6 11,311 7,181 76.3 154.4 117.7 33.2 21.1 3.3 2.5 2.1 18.655 29.382 30,164.8 142.96 Serbia SRB 62.5 37.3 8,642 5,148 71.5 118.0 84.4 25.3 15.1 0.1 0.1 0.1 43.629 73.240 2,728.5 7.24 Slovak Republic SVK 71.4 55.2 13,226 10,231 92.9 180.5 167.7 38.8 30.0 0.1 0.1 0.1 0.556 0.718 39.7 5.40 Slovenia SVN 30.9 29.2 15,063 14,206 113.3 205.6 232.9 44.2 41.7 0.1 0.1 0.0 0.677 0.718 20.9 2.05 Spain ESP 789.2 865.9 16,886 18,528 131.8 230.5 303.8 49.5 54.3 1.6 2.1 0.7 0.788 0.718 622.1 46.74 Sweden SWE 191.5 266.4 20,270 28,188 167.0 276.7 462.1 59.4 82.7 0.4 0.6 0.1 9.021 6.487 1,727.8 9.45 Switzerland CHE 214.5 372.9 27,103 47,127 208.8 370.0 772.7 79.5 138.2 0.4 0.9 0.1 1.540 0.885 330.2 7.91 Tajikistan TJK 18.0 7.0 2,332 904 46.5 31.8 14.8 6.8 2.7 0.0 0.0 0.1 1.786 4.610 32.1 7.71 Turkey TUR 776.3 525.9 10,459 7,085 81.4 142.8 116.2 30.7 20.8 1.6 1.3 1.1 1.135 1.675 880.9 74.22 Ukrained UKR 285.1 113.9 6,239 2,491 48.0 85.2 40.8 18.3 7.3 0.6 0.3 0.7 3.182 7.968 907.2 45.71 United Kingdom GBR 1,374.3 1,711.2 21,716 27,040 149.6 296.4 443.3 63.7 79.3 2.8 4.2 0.9 0.776 0.623 1,066.9 63.29 Total (46) ECB 12,853.8 12,935.1 15,026 15,121 120.9 205.1 247.9 44.1 44.3 26.0 31.5 12.7 n.a. n.a n.a. 855.42 Latin America and the Caribbean Anguilla AIA 0.3 0.2 19,569 18,133 111.3 267.1 297.3 57.4 53.2 0.0 0.0 0.0 2.502 2.700 0.7 0.01 Antigua and Barbuda ATG 0.9 0.7 9,742 7,945 98.0 133.0 130.3 28.6 23.3 0.0 0.0 0.0 2.202 2.700 1.9 0.09 Aruba ABW 1.8 1.6 17,177 15,716 109.9 234.5 257.7 50.4 46.1 0.0 0.0 0.0 1.638 1.790 2.9 0.10 (continued) Revised 2011 results and comparisons with original ICP 2011 results 133 Table E.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 5.6 6.3 15,574 17,525 135.2 212.6 287.3 45.7 51.4 0.0 0.0 0.0 1.125 1.000 6.3 0.36 Barbados BRB 2.8 3.3 9,832 11,764 143.7 134.2 192.9 28.8 34.5 0.0 0.0 0.0 2.393 2.000 6.7 0.28 Belize BLZ 1.8 1.0 5,394 3,167 70.5 73.6 51.9 15.8 9.3 0.0 0.0 0.0 1.174 2.000 2.1 0.33 Bolivia BOL 34.9 14.5 3,418 1,415 49.7 46.7 23.2 10.0 4.1 0.1 0.0 0.2 2.891 6.982 100.9 10.21 e Bonaire BON 0.2 0.2 8,735 8,015 110.0 119.8 131.7 25.6 23.5 0.0 0.0 0.0 0.918 1.000 0.2 0.02 Brazil BRA 1,597.5 1,576.9 8,088 7,984 118.6 110.4 130.9 23.7 23.4 3.2 3.8 2.9 1.651 1.673 2,637.8 197.51 Cayman Islands CYM 1.7 2.3 28,808 39,060 162.9 393.2 640.4 84.5 114.5 0.0 0.0 0.0 1.130 0.833 1.9 0.06 Chile CHL 189.6 151.7 10,983 8,784 96.1 149.9 144.0 32.2 25.8 0.4 0.4 0.3 386.817 483.668 73,356.8 17.27 Colombia COL 333.4 218.5 7,241 4,745 78.7 98.8 77.8 21.2 13.9 0.7 0.5 0.7 1,210.993 1,848.139 403,766.7 46.04 Costa Rica CRI 40.8 28.2 8,887 6,140 83.0 121.3 100.7 26.1 18.0 0.1 0.1 0.1 349.407 505.664 14,250.9 4.59 Curaçao CUW 2.5 2.0 16,419 13,412 98.1 224.1 219.9 48.1 39.3 0.0 0.0 0.0 1.462 1.790 3.7 0.15 Dominica DMA 0.6 0.4 7,975 6,012 90.5 108.9 98.6 23.4 17.6 0.0 0.0 0.0 2.035 2.700 1.2 0.07 Dominican Republic DOM 81.2 44.2 8,272 4,509 65.5 112.9 73.9 24.3 13.2 0.2 0.1 0.1 20.765 38.099 1,685.7 9.81 Ecuador ECU 88.8 48.7 5,827 3,192 65.8 79.5 52.3 17.1 9.4 0.2 0.1 0.2 0.548 1.000 48.7 15.24 El Salvador SLV 33.1 17.8 5,336 2,866 64.5 72.8 47.0 15.6 8.4 0.1 0.0 0.1 0.537 1.000 17.8 6.21 Grenada GRD 0.9 0.7 8,455 6,595 93.7 115.4 108.1 24.8 19.3 0.0 0.0 0.0 2.106 2.700 1.9 0.11 d Guatemala GTM 81.3 40.5 5,440 2,712 59.9 74.3 44.5 16.0 8.0 0.2 0.1 0.2 3.892 7.807 316.5 14.95 Haiti HTI 16.0 8.1 1,587 807 61.1 21.7 13.2 4.7 2.4 0.0 0.0 0.1 20.833 40.977 333.9 10.10 Honduras HND 25.3 13.7 2,988 1,610 64.7 40.8 26.4 8.8 4.7 0.1 0.0 0.1 10.264 19.048 260.1 8.48 Jamaica JAM 16.9 12.4 5,994 4,387 87.9 81.8 71.9 17.6 12.9 0.0 0.0 0.0 62.876 85.911 1,065.1 2.83 Mexico MEX 1,069.6 765.0 9,259 6,623 85.9 126.4 108.6 27.2 19.4 2.2 1.9 1.7 8.886 12.423 9,504.3 115.51 Montserrat MSR 0.1 0.0 11,606 9,566 99.0 158.4 156.8 34.0 28.1 0.0 0.0 0.0 2.225 2.700 0.1 0.00 Nicaragua NIC 18.3 7.5 3,099 1,278 49.5 42.3 21.0 9.1 3.7 0.0 0.0 0.1 9.251 22.424 169.2 5.90 Panama PAN 34.8 19.3 9,392 5,196 66.4 128.2 85.2 27.5 15.2 0.1 0.0 0.1 0.553 1.000 19.3 3.71 Paraguay PRY 40.1 21.5 6,333 3,394 64.4 86.4 55.6 18.6 10.0 0.1 0.1 0.1 2,242.096 4,183.127 89,930.6 6.33 Peru PER 181.0 103.8 6,185 3,546 68.9 84.4 58.1 18.1 10.4 0.4 0.3 0.4 1.579 2.754 285.8 29.26 Sint Maarten SXM 0.7 0.6 19,678 17,923 109.4 268.6 293.9 57.7 52.6 0.0 0.0 0.0 1.630 1.790 1.1 0.04 St. Kitts and Nevis KNA 0.7 0.6 13,690 11,322 99.3 186.9 185.6 40.1 33.2 0.0 0.0 0.0 2.233 2.700 1.5 0.05 St. Lucia LCA 1.5 1.1 8,435 6,511 92.7 115.1 106.7 24.7 19.1 0.0 0.0 0.0 2.084 2.700 3.1 0.18 St. Vincent and the VCT 0.8 0.6 7,089 5,246 88.9 96.8 86.0 20.8 15.4 0.0 0.0 0.0 1.998 2.700 1.5 0.11 Grenadines Suriname SUR 2.7 1.5 5,101 2,893 68.1 69.6 47.4 15.0 8.5 0.0 0.0 0.0 1.900 3.350 5.2 0.54 Trinidad and Tobago TTO 16.8 11.8 12,583 8,852 84.5 171.8 145.1 36.9 26.0 0.0 0.0 0.0 4.520 6.426 76.0 1.34 Turks and Caicos Islands TCA 0.2 0.3 6,823 8,596 151.3 93.1 140.9 20.0 25.2 0.0 0.0 0.0 1.260 1.000 0.3 0.03 Uruguay URY 37.2 32.0 11,053 9,504 103.3 150.9 155.8 32.4 27.9 0.1 0.1 0.1 16.608 19.314 618.4 3.37 Venezuela, RBd VEN 254.4 174.6 8,806 6,043 82.4 120.2 99.1 25.8 17.7 0.5 0.4 0.4 2.944 4.289 748.8 28.89 Virgin Islands, British VGB 0.3 0.3 9,429 11,349 144.6 128.7 186.1 27.6 33.3 0.0 0.0 0.0 1.204 1.000 0.3 0.03 Total (39) LCB 4,216.8 3,334.4 7,807 6,174 95.0 106.6 101.2 22.9 18.1 8.5 8.1 8.0 n.a. n.a n.a. 540.10 134    Purchasing Power Parities and the Size of World Economies Table E.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 145.1 62.7 3,957 1,710 51.9 54.0 28.0 11.6 5.0 0.3 0.2 0.5 31.518 72.938 4,571.9 36.66 Bahrain BHR 23.7 11.2 19,805 9,409 57.1 270.3 154.3 58.1 27.6 0.0 0.0 0.0 0.179 0.376 4.2 1.20 Djibouti DJI 2.3 1.3 2,731 1,546 68.0 37.3 25.3 8.0 4.5 0.0 0.0 0.0 100.624 177.721 234.6 0.85 Egypt, Arab Rep. EGY 700.2 201.9 8,695 2,507 34.6 118.7 41.1 25.5 7.4 1.4 0.5 1.2 1.715 5.947 1,200.6 80.53 Iran, Islamic Rep. IRN 763.7 382.9 10,162 5,096 60.2 138.7 83.5 29.8 14.9 1.5 0.9 1.1 5,323.442 10,616.307 4,065,433.1 75.15 Iraq IRQ 159.7 63.6 4,790 1,907 47.8 65.4 31.3 14.0 5.6 0.3 0.2 0.5 477.559 1,199.200 76,260.3 33.34 Israel ISR 124.6 148.1 16,046 19,076 142.8 219.0 312.8 47.1 55.9 0.3 0.4 0.1 4.254 3.578 529.9 7.76 Jordan JOR 51.1 23.5 7,308 3,355 55.1 99.8 55.0 21.4 9.8 0.1 0.1 0.1 0.325 0.708 16.6 6.99 Kuwait KWT 57.9 36.8 18,872 12,008 76.4 257.6 196.9 55.3 35.2 0.1 0.1 0.0 0.178 0.280 10.3 3.07 Malta MLT 6.3 5.6 15,215 13,405 105.8 207.7 219.8 44.6 39.3 0.0 0.0 0.0 0.633 0.718 4.0 0.42 Morocco MAR 118.4 60.7 3,634 1,862 61.6 49.6 30.5 10.7 5.5 0.2 0.1 0.5 4.125 8.049 488.3 32.58 Oman OMN 39.3 20.9 11,932 6,355 64.0 162.9 104.2 35.0 18.6 0.1 0.1 0.0 0.205 0.385 8.1 3.30 Qatar QAT 27.4 22.4 15,798 12,950 98.5 215.6 212.3 46.3 38.0 0.1 0.1 0.0 2.992 3.650 81.9 1.73 Saudi Arabia SAU 451.1 183.5 16,011 6,512 48.8 218.6 106.8 46.9 19.1 0.9 0.4 0.4 1.525 3.750 687.9 28.17 Tunisia TUN 61.4 30.4 5,717 2,830 59.5 78.0 46.4 16.8 8.3 0.1 0.1 0.2 0.697 1.408 42.8 10.74 United Arab Emirates ARE 206.2 134.5 23,775 15,515 78.4 324.5 254.4 69.7 45.5 0.4 0.3 0.1 2.397 3.673 494.1 8.67 West Bank and Gaza PSE 14.1 9.6 3,646 2,484 81.8 49.8 40.7 10.7 7.3 0.0 0.0 0.1 2.438 3.578 34.5 3.88 Yemen, Rep.d YEM 59.6 21.4 2,500 898 43.1 34.1 14.7 7.3 2.6 0.1 0.1 0.4 76.766 213.800 4,573.2 23.83 Total (17) MEB 3,011.9 1,421.1 8,393 3,960 56.7 114.6 64.9 24.6 11.6 6.1 3.5 5.3 n.a. n.a n.a. 358.87 North America Bermuda BMU 1.7 3.1 26,123 47,706 219.3 356.6 782.2 76.6 139.9 0.0 0.0 0.0 1.826 1.000 3.1 0.07 Canada CAN 773.4 1,002.2 22,520 29,183 155.7 307.4 478.5 66.0 85.6 1.6 2.4 0.5 1.282 0.990 991.8 34.34 United States USA 10,641.1 10,641.1 34,103 34,103 120.1 465.5 559.1 100.0 100.0 21.6 25.9 4.6 1.000 1.000 10,641.1 312.03 Total (3) NAB 11,416.2 11,646.5 32,953 33,617 122.5 449.8 551.2 96.6 98.6 23.1 28.3 5.1 n.a. n.a n.a. 346.44 South Asia Bangladesh BGD 294.8 98.3 1,969 657 40.1 26.9 10.8 5.8 1.9 0.6 0.2 2.2 24.732 74.152 7,291.8 149.70 Bhutan BTN 2.1 0.8 3,049 1,113 43.9 41.6 18.3 8.9 3.3 0.0 0.0 0.0 17.044 46.670 35.3 0.68 India IND 3,112.4 1,019.2 2,559 838 39.3 34.9 13.7 7.5 2.5 6.3 2.5 18.1 15.283 46.670 47,565.7 1,216.15 Maldives MDV 1.5 0.9 3,737 2,254 72.5 51.0 37.0 11.0 6.6 0.0 0.0 0.0 8.810 14.602 13.4 0.41 Nepal NPL 42.8 14.9 1,615 562 41.8 22.1 9.2 4.7 1.6 0.1 0.0 0.4 25.743 74.020 1,101.6 26.49 Pakistan PAK 615.0 181.6 3,473 1,025 35.5 47.4 16.8 10.2 3.0 1.2 0.4 2.6 25.496 86.343 15,679.6 177.10 Sri Lanka LKA 119.7 46.5 5,925 2,304 46.7 80.9 37.8 17.4 6.8 0.2 0.1 0.3 42.988 110.565 5,143.7 20.20 Total (7) SAB 4,188.2 1,362.2 2,633 856 39.1 35.9 14.0 7.7 2.5 8.5 3.3 23.6 n.a. n.a n.a. 1,590.72 Sub-Saharan Africa Angola AGO 45.3 39.0 1,869 1,611 103.5 25.5 26.4 5.5 4.7 0.1 0.1 0.4 80.932 93.935 3,664.5 24.22 Benin BEN 11.8 5.6 1,250 597 57.4 17.1 9.8 3.7 1.8 0.0 0.0 0.1 225.412 471.866 2,665.7 9.46 Botswana BWA 11.4 7.1 5,661 3,528 74.9 77.3 57.9 16.6 10.3 0.0 0.0 0.0 4.262 6.838 48.6 2.02 (continued) Revised 2011 results and comparisons with original ICP 2011 results 135 Table E.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 13.6 6.4 847 400 56.8 11.6 6.6 2.5 1.2 0.0 0.0 0.2 223.073 471.866 3,037.2 16.08 Burundi BDI 5.2 2.0 579 228 47.3 7.9 3.7 1.7 0.7 0.0 0.0 0.1 496.117 1,261.073 2,573.5 8.96 Cabo Verde CPV 1.9 1.2 3,873 2,346 72.8 52.9 38.5 11.4 6.9 0.0 0.0 0.0 48.057 79.323 92.8 0.50 Cameroon CMR 39.3 20.2 1,878 966 61.8 25.6 15.8 5.5 2.8 0.1 0.0 0.3 242.678 471.866 9,526.5 20.91 Central African Republic CAF 3.6 2.0 823 463 67.6 11.2 7.6 2.4 1.4 0.0 0.0 0.1 265.661 471.866 965.9 4.42 Chad TCD 13.3 7.1 1,076 571 63.7 14.7 9.4 3.2 1.7 0.0 0.0 0.2 250.251 471.866 3,328.6 12.36 Comoros COM 1.4 1.0 2,025 1,348 80.0 27.6 22.1 5.9 4.0 0.0 0.0 0.0 235.604 353.900 337.1 0.71 Congo, Dem. Rep. COD 33.5 19.9 501 298 71.4 6.8 4.9 1.5 0.9 0.1 0.0 1.0 546.732 919.491 18,298.8 66.76 Congo, Rep. COG 6.6 4.3 1,506 969 77.3 20.6 15.9 4.4 2.8 0.0 0.0 0.1 303.724 471.866 2,009.9 4.39 Côte d’Ivoire CIV 34.1 17.6 1,621 836 62.0 22.1 13.7 4.8 2.5 0.1 0.0 0.3 243.461 471.866 8,298.4 21.03 Equatorial Guinea GNQ 6.2 4.3 6,328 4,400 83.5 86.4 72.1 18.6 12.9 0.0 0.0 0.0 328.091 471.866 2,048.8 0.99 Eswatini SWZ 6.6 3.8 6,187 3,504 68.0 84.5 57.4 18.1 10.3 0.0 0.0 0.0 4.112 7.261 27.3 1.07 Ethiopia ETH 97.0 32.0 1,076 355 39.6 14.7 5.8 3.2 1.0 0.2 0.1 1.3 5.575 16.899 540.5 90.14 Gabon GAB 7.0 5.3 4,168 3,174 91.5 56.9 52.0 12.2 9.3 0.0 0.0 0.0 359.344 471.866 2,523.1 1.68 Gambia, The GMB 3.2 1.2 1,717 636 44.5 23.4 10.4 5.0 1.9 0.0 0.0 0.0 10.912 29.462 34.6 1.85 Ghana GHA 62.0 31.9 2,442 1,258 61.9 33.3 20.6 7.2 3.7 0.1 0.1 0.4 0.779 1.512 48.3 25.39 Guinea GIN 14.2 5.5 1,363 532 46.9 18.6 8.7 4.0 1.6 0.0 0.0 0.2 2,599.891 6,658.031 36,919.5 10.42 Guinea-Bissau GNB 1.7 0.9 1,072 587 65.8 14.6 9.6 3.1 1.7 0.0 0.0 0.0 258.323 471.866 432.9 1.56 Kenya KEN 84.2 33.8 1,949 782 48.2 26.6 12.8 5.7 2.3 0.2 0.1 0.6 35.621 88.811 2,997.9 43.18 Lesotho LSO 4.6 2.5 2,293 1,239 64.9 31.3 20.3 6.7 3.6 0.0 0.0 0.0 3.926 7.261 18.0 2.00 Liberia LBR 2.0 1.2 507 303 71.9 6.9 5.0 1.5 0.9 0.0 0.0 0.1 43.207 72.227 88.0 4.02 Madagascar MDG 24.7 8.6 1,138 393 41.5 15.5 6.4 3.3 1.2 0.1 0.0 0.3 700.228 2,025.118 17,322.0 21.74 Malawi MWI 13.4 6.7 895 450 60.4 12.2 7.4 2.6 1.3 0.0 0.0 0.2 78.703 156.515 1,053.6 14.96 Mali MLI 19.6 9.3 1,262 600 57.1 17.2 9.8 3.7 1.8 0.0 0.0 0.2 224.357 471.866 4,394.5 15.51 Mauritania MRT 5.8 2.3 1,603 643 48.2 21.9 10.5 4.7 1.9 0.0 0.0 0.1 112.849 281.118 650.8 3.60 Mauritius MUS 12.9 8.3 10,315 6,668 77.6 140.8 109.3 30.2 19.6 0.0 0.0 0.0 18.555 28.706 239.5 1.25 Mozambique MOZ 18.3 10.0 756 412 65.4 10.3 6.8 2.2 1.2 0.0 0.0 0.4 15.826 29.068 289.6 24.19 Namibia NAM 11.4 8.2 5,289 3,820 86.7 72.2 62.6 15.5 11.2 0.0 0.0 0.0 5.244 7.261 59.8 2.16 Niger NER 9.5 4.6 556 272 58.7 7.6 4.5 1.6 0.8 0.0 0.0 0.3 230.417 471.866 2,192.8 17.11 Nigeria NGA 489.4 265.9 3,006 1,633 65.2 41.0 26.8 8.8 4.8 1.0 0.6 2.4 83.583 153.862 40,904.9 162.81 Rwanda RWA 12.1 5.1 1,174 492 50.3 16.0 8.1 3.4 1.4 0.0 0.0 0.2 251.305 600.307 3,038.1 10.29 São Tomé and Príncipe STP 0.4 0.2 1,934 1,151 71.5 26.4 18.9 5.7 3.4 0.0 0.0 0.0 10.487 17.623 3.7 0.18 Senegal SEN 27.1 14.3 2,080 1,099 63.5 28.4 18.0 6.1 3.2 0.1 0.0 0.2 249.278 471.866 6,756.4 13.03 Seychelles SYC 0.9 0.6 9,277 6,169 79.9 126.6 101.1 27.2 18.1 0.0 0.0 0.0 8.233 12.381 7.0 0.09 Sierra Leone SLE 6.7 2.8 1,026 431 50.4 14.0 7.1 3.0 1.3 0.0 0.0 0.1 1,825.528 4,349.162 12,295.1 6.56 South Africa ZAF 364.1 252.3 7,001 4,851 83.2 95.6 79.5 20.5 14.2 0.7 0.6 0.8 5.031 7.261 1,831.8 52.00 Sudan SDN 86.8 35.0 2,556 1,031 48.5 34.9 16.9 7.5 3.0 0.2 0.1 0.5 1.465 3.630 127.2 33.98 136    Purchasing Power Parities and the Size of World Economies Table E.3  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market INDIVIDUAL CONSUMPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange EXPENDITURE BY HOUSEHOLDS index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 66.3 24.8 1,452 544 45.0 19.8 8.9 4.3 1.6 0.1 0.1 0.7 588.785 1,572.116 39,059.9 45.67 Togo TGO 6.0 3.0 912 457 60.2 12.4 7.5 2.7 1.3 0.0 0.0 0.1 236.587 471.866 1,422.5 6.60 Uganda UGA 57.5 21.5 1,717 643 45.0 23.4 10.5 5.0 1.9 0.1 0.1 0.5 944.256 2,522.746 54,266.8 33.48 Zambia ZMB 24.3 13.1 1,736 933 64.5 23.7 15.3 5.1 2.7 0.0 0.0 0.2 2.611 4.861 63.6 14.02 Zimbabwe ZWE 18.3 9.8 1,419 760 64.3 19.4 12.5 4.2 2.2 0.0 0.0 0.2 0.535 1.000 9.8 12.89 Total (45) SSB 1,785.3 962.4 2,061 1,111 64.7 28.1 18.2 6.0 3.3 3.6 2.3 12.9 n.a. n.a n.a. 866.25 World (178) WLD 49,347.2 41,085.5 7,326 6,099 100.0 100.0 100.0 21.5 17.9 100.0 100.0 100.0 n.a. n.a. n.a. 6,736.12 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. National accounts expenditures for the revised ICP 2011 results are estimated by the ICP Global Office. e. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either Latin America and the Caribbean or the world totals. Revised 2011 results and comparisons with original ICP 2011 results 137 Table E.4  Consumption expenditure by government: Revised ICP 2011 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 199.0 271.6 8,907 12,155 217.8 300.4 654.3 110.6 151.0 1.0 2.2 0.3 1.323 0.969 263.3 22.34 Brunei Darussalam BRN 10.8 3.5 27,483 8,820 51.2 926.9 474.8 341.4 109.6 0.1 0.0 0.0 0.404 1.258 4.4 0.39 Cambodia KHM 6.1 1.1 429 75 28.1 14.5 4.1 5.3 0.9 0.0 0.0 0.2 713.781 4,058.500 4,380.9 14.31 China CHN 2,645.5 1,121.2 1,968 834 67.6 66.4 44.9 24.5 10.4 13.2 9.0 20.0 2.738 6.461 7,244.8 1,344.13 Fiji FJI 1.6 0.7 1,917 765 63.7 64.6 41.2 23.8 9.5 0.0 0.0 0.0 0.716 1.793 1.2 0.85 Hong Kong SAR, China HKG 37.3 21.6 5,280 3,061 92.6 178.1 164.8 65.6 38.0 0.2 0.2 0.1 4.513 7.784 168.5 7.07 Indonesia IDN 352.6 80.9 1,457 334 36.6 49.1 18.0 18.1 4.2 1.8 0.6 3.6 2,011.816 8,770.433 709,450.8 241.99 Japan JPN 1,204.2 1,243.1 9,421 9,724 164.8 317.7 523.5 117.0 120.8 6.0 9.9 1.9 82.380 79.807 99,204.5 127.83 Korea, Rep. KOR 315.3 180.1 6,315 3,607 91.2 213.0 194.2 78.4 44.8 1.6 1.4 0.7 633.057 1,108.292 199,627.2 49.94 Lao PDR LAO 6.2 0.8 1,019 127 19.9 34.4 6.9 12.7 1.6 0.0 0.0 0.1 1,003.569 8,030.055 6,258.4 6.12 Macao SAR, Chinad MAC 5.3 2.6 9,682 4,743 78.2 326.5 255.3 120.3 58.9 0.0 0.0 0.0 3.928 8.018 21.0 0.55 Malaysia MYS 121.1 39.5 4,168 1,361 52.1 140.6 73.2 51.8 16.9 0.6 0.3 0.4 0.999 3.060 121.0 29.06 Mongolia MNG 7.4 1.3 2,667 458 27.4 89.9 24.6 33.1 5.7 0.0 0.0 0.0 217.279 1,265.516 1,614.5 2.79 Myanmar MMR 37.8 6.4 761 130 27.2 25.7 7.0 9.5 1.6 0.2 0.1 0.7 139.197 817.917 5,262.1 49.66 New Zealand NZL 38.5 32.8 8,768 7,470 136.0 295.7 402.1 108.9 92.8 0.2 0.3 0.1 1.079 1.266 41.5 4.39 Philippines PHL 61.3 21.7 651 231 56.6 21.9 12.4 8.1 2.9 0.3 0.2 1.4 15.367 43.313 941.8 94.18 Singapore SGP 47.0 25.8 9,076 4,973 87.5 306.1 267.7 112.8 61.8 0.2 0.2 0.1 0.689 1.258 32.4 5.18 Taiwan, China TWN 191.7 73.6 8,264 3,172 61.3 278.7 170.7 102.7 39.4 1.0 0.6 0.3 11.310 29.469 2,167.6 23.19 Thailand THA 205.4 61.1 3,102 924 47.5 104.6 49.7 38.5 11.5 1.0 0.5 1.0 9.077 30.492 1,864.6 66.21 Vietnam VNM 86.4 14.1 981 160 26.0 33.1 8.6 12.2 2.0 0.4 0.1 1.3 3,341.661 20,509.750 288,815.9 88.11 Total (20) EAB 5,580.9 3,203.5 2,562 1,471 91.6 86.4 79.2 31.8 18.3 27.9 25.6 32.3 n.a. n.a n.a. 2,178.31 Europe and Central Asia Albania ALB 8.3 1.4 2,845 487 27.3 95.9 26.2 35.3 6.1 0.0 0.0 0.0 17.270 100.812 142.7 2.91 Armenia ARM 6.7 1.3 2,204 433 31.4 74.3 23.3 27.4 5.4 0.0 0.0 0.0 73.177 372.500 488.4 3.03 Austria AUT 78.4 85.9 9,344 10,239 174.9 315.1 551.2 116.1 127.2 0.4 0.7 0.1 0.787 0.718 61.7 8.39 Azerbaijan AZE 32.0 6.7 3,538 738 33.3 119.3 39.7 44.0 9.2 0.2 0.1 0.1 0.165 0.790 5.3 9.05 Belarus BLR 50.3 7.4 5,308 778 23.4 179.0 41.9 65.9 9.7 0.3 0.1 0.1 0.082 0.561 4.1 9.47 Belgium BEL 114.2 125.9 10,348 11,402 175.9 349.0 613.8 128.6 141.6 0.6 1.0 0.2 0.792 0.718 90.4 11.04 Bosnia and Herzegovina BIH 13.7 4.3 3,738 1,177 50.3 126.1 63.4 46.4 14.6 0.1 0.0 0.1 0.443 1.405 6.1 3.66 Bulgaria BGR 37.8 9.2 5,148 1,245 38.6 173.6 67.0 64.0 15.5 0.2 0.1 0.1 0.340 1.405 12.9 7.35 Croatia HRV 28.1 12.9 6,570 3,008 73.1 221.6 161.9 81.6 37.4 0.1 0.1 0.1 2.447 5.344 68.9 4.28 Cyprus CYP 6.2 5.3 7,285 6,184 135.5 245.7 332.9 90.5 76.8 0.0 0.0 0.0 0.610 0.718 3.8 0.85 Czech Republic CZE 96.4 46.0 9,184 4,385 76.2 309.7 236.1 114.1 54.5 0.5 0.4 0.2 8.435 17.665 813.2 10.50 Denmark DNK 74.9 91.7 13,449 16,456 195.3 453.6 885.9 167.1 204.4 0.4 0.7 0.1 6.549 5.352 490.6 5.57 Estonia EST 10.4 4.4 7,811 3,301 67.4 263.4 177.7 97.0 41.0 0.1 0.0 0.0 0.304 0.718 3.2 1.33 Finland FIN 61.7 64.4 11,445 11,949 166.6 386.0 643.2 142.2 148.4 0.3 0.5 0.1 0.750 0.718 46.3 5.39 138    Purchasing Power Parities and the Size of World Economies Table E.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) France FRA 686.2 680.3 10,503 10,414 158.3 354.2 560.6 130.5 129.4 3.4 5.4 1.0 0.712 0.718 488.8 65.33 Georgia GEO 8.8 2.1 2,347 552 37.5 79.1 29.7 29.2 6.9 0.0 0.0 0.1 0.397 1.686 3.5 3.76 Germany DEU 797.9 715.0 9,939 8,907 143.0 335.2 479.5 123.5 110.7 4.0 5.7 1.2 0.644 0.718 513.7 80.28 Greece GRC 84.2 62.8 7,580 5,654 119.0 255.6 304.3 94.2 70.2 0.4 0.5 0.2 0.536 0.718 45.1 11.11 Hungary HUN 82.0 29.3 8,223 2,937 57.0 277.3 158.1 102.1 36.5 0.4 0.2 0.1 71.690 200.697 5,878.1 9.97 Iceland ISL 4.1 3.7 12,774 11,717 146.4 430.8 630.7 158.7 145.6 0.0 0.0 0.0 106.365 115.963 433.4 0.32 Ireland IRL 39.5 43.6 8,625 9,524 176.2 290.9 512.7 107.1 118.3 0.2 0.3 0.1 0.793 0.718 31.3 4.58 Italy ITA 490.6 454.8 8,168 7,572 148.0 275.5 407.6 101.5 94.1 2.5 3.6 0.9 0.666 0.718 326.7 60.06 Kazakhstan KAZ 80.6 20.2 4,869 1,219 40.0 164.2 65.6 60.5 15.1 0.4 0.2 0.2 36.699 146.620 2,958.7 16.56 Kyrgyzstan KGZ 7.6 1.1 1,453 215 23.6 49.0 11.6 18.1 2.7 0.0 0.0 0.1 6.819 46.144 52.1 5.26 Latvia LVA 13.4 5.1 6,509 2,493 61.1 219.5 134.2 80.9 31.0 0.1 0.0 0.0 0.275 0.718 3.7 2.06 Lithuania LTU 23.4 8.0 7,725 2,637 54.5 260.5 142.0 96.0 32.8 0.1 0.1 0.0 0.245 0.718 5.7 3.03 Luxembourg LUX 6.6 10.0 12,728 19,308 242.1 429.2 1,039.3 158.1 239.9 0.0 0.1 0.0 1.090 0.718 7.2 0.52 Moldova MDA 7.4 1.4 2,084 392 30.0 70.3 21.1 25.9 4.9 0.0 0.0 0.1 2.204 11.726 16.4 3.56 Montenegro MNE 3.9 1.0 6,219 1,544 39.6 209.7 83.1 77.3 19.2 0.0 0.0 0.0 0.178 0.718 0.7 0.62 Netherlands NLD 221.8 233.4 13,284 13,985 168.0 448.0 752.8 165.0 173.7 1.1 1.9 0.2 0.756 0.718 167.7 16.69 North Macedonia MKD 9.1 1.9 4,401 924 33.5 148.4 49.8 54.7 11.5 0.0 0.0 0.0 9.284 44.202 84.1 2.06 Norway NOR 63.9 104.3 12,896 21,067 260.8 434.9 1,134.1 160.2 261.7 0.3 0.8 0.1 9.146 5.599 584.2 4.95 Poland POL 265.3 95.5 6,886 2,480 57.5 232.2 133.5 85.5 30.8 1.3 0.8 0.6 1.066 2.960 282.8 38.53 Portugal PRT 69.5 48.3 6,586 4,575 110.9 222.1 246.3 81.8 56.8 0.3 0.4 0.2 0.499 0.718 34.7 10.56 Romania ROU 108.9 26.2 5,404 1,300 38.4 182.3 70.0 67.1 16.1 0.5 0.2 0.3 0.732 3.045 79.7 20.15 Russian Federation RUS 1,087.5 358.3 7,607 2,506 52.6 256.6 134.9 94.5 31.1 5.4 2.9 2.1 9.680 29.382 10,527.4 142.96 Serbia SRB 38.0 9.3 5,252 1,291 39.2 177.1 69.5 65.2 16.0 0.2 0.1 0.1 18.004 73.240 684.2 7.24 Slovak Republic SVK 47.3 18.2 8,754 3,367 61.4 295.2 181.3 108.8 41.8 0.2 0.1 0.1 0.276 0.718 13.1 5.40 Slovenia SVN 16.1 10.6 7,849 5,167 105.1 264.7 278.2 97.5 64.2 0.1 0.1 0.0 0.473 0.718 7.6 2.05 Spain ESP 373.0 306.1 7,980 6,549 131.0 269.1 352.6 99.1 81.4 1.9 2.4 0.7 0.590 0.718 219.9 46.74 Sweden SWE 115.1 143.3 12,179 15,166 198.8 410.8 816.4 151.3 188.4 0.6 1.1 0.1 8.078 6.487 929.6 9.45 Switzerland CHE 49.4 82.0 6,250 10,358 264.5 210.8 557.6 77.6 128.7 0.2 0.7 0.1 1.468 0.885 72.6 7.91 Tajikistan TJK 7.2 0.9 937 113 19.3 31.6 6.1 11.6 1.4 0.0 0.0 0.1 0.558 4.610 4.0 7.71 Turkey TUR 372.6 114.1 5,020 1,537 48.9 169.3 82.7 62.4 19.1 1.9 0.9 1.1 0.513 1.675 191.1 74.22 Ukrained UKR 156.9 30.9 3,432 676 31.4 115.8 36.4 42.6 8.4 0.8 0.2 0.7 1.568 7.968 246.0 45.71 United Kingdom GBR 600.8 558.2 9,494 8,821 148.3 320.2 474.8 117.9 109.6 3.0 4.5 0.9 0.579 0.623 348.0 63.29 Total (46) ECB 6,557.5 4,646.6 7,666 5,432 113.1 258.5 292.4 95.2 67.5 32.8 37.1 12.7 n.a. n.a n.a. 855.42 Latin America and the Caribbean Anguilla AIA 0.1 0.1 9,189 3,708 64.4 309.9 199.6 114.2 46.1 0.0 0.0 0.0 1.090 2.700 0.1 0.01 Antigua and Barbuda ATG 1.0 0.3 10,805 3,193 47.2 364.4 171.9 134.2 39.7 0.0 0.0 0.0 0.798 2.700 0.8 0.09 Aruba ABW 1.4 0.7 13,481 6,490 76.8 454.7 349.4 167.5 80.6 0.0 0.0 0.0 0.862 1.790 1.2 0.10 (continued) Revised 2011 results and comparisons with original ICP 2011 results 139 Table E.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 4.3 2.1 12,073 5,815 76.9 407.2 313.0 150.0 72.2 0.0 0.0 0.0 0.482 1.000 2.1 0.36 Barbados BRB 1.4 0.9 4,945 3,114 100.5 166.8 167.7 61.4 38.7 0.0 0.0 0.0 1.260 2.000 1.8 0.28 Belize BLZ 0.6 0.2 1,793 695 61.8 60.5 37.4 22.3 8.6 0.0 0.0 0.0 0.775 2.000 0.5 0.33 Bolivia BOL 7.4 3.3 728 321 70.4 24.6 17.3 9.0 4.0 0.0 0.0 0.2 3.080 6.982 22.9 10.21 e Bonaire BON … … … … … … … … … … … … … 1.000 … 0.02 Brazil BRA 732.3 488.4 3,708 2,473 106.4 125.0 133.1 46.1 30.7 3.7 3.9 2.9 1.116 1.673 817.0 197.51 Cayman Islands CYM 0.4 0.4 7,372 6,733 145.8 248.6 362.4 91.6 83.6 0.0 0.0 0.0 0.761 0.833 0.3 0.06 Chile CHL 68.8 30.1 3,983 1,740 69.7 134.3 93.7 49.5 21.6 0.3 0.2 0.3 211.358 483.668 14,535.2 17.27 Colombia COL 92.8 44.7 2,015 971 76.9 67.9 52.3 25.0 12.1 0.5 0.4 0.7 890.769 1,848.139 82,635.0 46.04 Costa Rica CRI 12.3 7.3 2,688 1,581 93.9 90.6 85.1 33.4 19.6 0.1 0.1 0.1 297.366 505.664 3,668.1 4.59 Curaçao CUW 1.0 0.5 6,297 2,960 75.0 212.4 159.3 78.2 36.8 0.0 0.0 0.0 0.841 1.790 0.8 0.15 Dominica DMA 0.2 0.1 2,310 1,227 84.8 77.9 66.0 28.7 15.2 0.0 0.0 0.0 1.434 2.700 0.2 0.07 Dominican Republic DOM 21.9 5.4 2,230 551 39.4 75.2 29.7 27.7 6.8 0.1 0.0 0.1 9.415 38.099 206.0 9.81 Ecuador ECU 24.4 10.1 1,599 662 66.1 53.9 35.6 19.9 8.2 0.1 0.1 0.2 0.414 1.000 10.1 15.24 El Salvador SLV 9.3 3.2 1,504 515 54.6 50.7 27.7 18.7 6.4 0.0 0.0 0.1 0.342 1.000 3.2 6.21 Grenada GRD 0.3 0.1 2,958 1,156 62.4 99.8 62.2 36.8 14.4 0.0 0.0 0.0 1.055 2.700 0.3 0.11 Guatemalad GTM 13.4 4.8 900 324 57.5 30.3 17.4 11.2 4.0 0.1 0.0 0.2 2.811 7.807 37.8 14.95 Haiti HTI 2.2 0.7 217 71 52.5 7.3 3.8 2.7 0.9 0.0 0.0 0.1 13.483 40.977 29.6 10.10 Honduras HND 5.8 2.8 680 333 78.2 22.9 17.9 8.5 4.1 0.0 0.0 0.1 9.327 19.048 53.8 8.48 Jamaica JAM 6.1 2.3 2,148 808 60.0 72.4 43.5 26.7 10.0 0.0 0.0 0.0 32.308 85.911 196.1 2.83 Mexico MEX 458.3 139.0 3,967 1,204 48.4 133.8 64.8 49.3 15.0 2.3 1.1 1.7 3.769 12.423 1,727.2 115.51 Montserrat MSR 0.1 0.0 17,239 5,640 52.2 581.4 303.6 214.2 70.1 0.0 0.0 0.0 0.883 2.700 0.1 0.00 Nicaragua NIC 6.0 1.3 1,009 225 35.6 34.0 12.1 12.5 2.8 0.0 0.0 0.1 5.006 22.424 29.8 5.90 Panama PAN 10.7 4.1 2,893 1,110 61.3 97.6 59.8 35.9 13.8 0.1 0.0 0.1 0.384 1.000 4.1 3.71 Paraguay PRY 10.1 3.3 1,595 523 52.4 53.8 28.2 19.8 6.5 0.1 0.0 0.1 1,372.133 4,183.127 13,860.5 6.33 Peru PER 41.5 17.8 1,417 608 68.5 47.8 32.7 17.6 7.6 0.2 0.1 0.4 1.182 2.754 49.0 29.26 Sint Maarten SXM 0.4 0.2 12,208 4,887 63.9 411.7 263.0 151.7 60.7 0.0 0.0 0.0 0.717 1.790 0.3 0.04 St. Kitts and Nevis KNA 0.4 0.1 7,210 2,835 62.8 243.2 152.6 89.6 35.2 0.0 0.0 0.0 1.062 2.700 0.4 0.05 St. Lucia LCA 0.4 0.2 2,500 1,034 66.0 84.3 55.7 31.1 12.8 0.0 0.0 0.0 1.117 2.700 0.5 0.18 St. Vincent and the VCT 0.5 0.1 4,208 1,358 51.5 141.9 73.1 52.3 16.9 0.0 0.0 0.0 0.871 2.700 0.4 0.11 Grenadines Suriname SUR 1.8 0.6 3,365 1,098 52.1 113.5 59.1 41.8 13.6 0.0 0.0 0.0 1.093 3.350 2.0 0.54 Trinidad and Tobago TTO 7.0 2.3 5,239 1,749 53.3 176.7 94.1 65.1 21.7 0.0 0.0 0.0 2.145 6.426 15.0 1.34 Turks and Caicos Islands TCA 0.3 0.2 9,587 4,878 81.2 323.3 262.6 119.1 60.6 0.0 0.0 0.0 0.509 1.000 0.2 0.03 Uruguay URY 10.2 6.1 3,028 1,817 95.7 102.1 97.8 37.6 22.6 0.1 0.0 0.1 11.586 19.314 118.2 3.37 Venezuela, RBd VEN 103.2 36.5 3,572 1,262 56.4 120.5 67.9 44.4 15.7 0.5 0.3 0.4 1.515 4.289 156.4 28.89 Virgin Islands, British VGB 0.1 0.1 4,926 2,742 88.8 166.1 147.6 61.2 34.1 0.0 0.0 0.0 0.557 1.000 0.1 0.03 Total (39) LCB 1,658.3 820.3 3,070 1,519 79.0 103.6 81.8 38.1 18.9 8.3 6.6 8.0 n.a. n.a n.a. 540.10 140    Purchasing Power Parities and the Size of World Economies Table E.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 225.3 41.0 6,145 1,119 29.1 207.2 60.2 76.3 13.9 1.1 0.3 0.5 13.280 72.938 2,991.5 36.66 Bahrain BHR 10.9 4.0 9,108 3,330 58.4 307.2 179.3 113.1 41.4 0.1 0.0 0.0 0.137 0.376 1.5 1.20 Djibouti DJI 0.5 0.2 610 239 62.5 20.6 12.9 7.6 3.0 0.0 0.0 0.0 69.637 177.721 36.3 0.85 Egypt, Arab Rep. EGY 187.9 27.7 2,333 344 23.5 78.7 18.5 29.0 4.3 0.9 0.2 1.2 0.876 5.947 164.6 80.53 Iran, Islamic Rep. IRN 410.1 64.6 5,457 860 25.2 184.0 46.3 67.8 10.7 2.1 0.5 1.1 1,673.585 10,616.307 686,332.2 75.15 Iraq IRQ 115.4 35.7 3,460 1,069 49.3 116.7 57.6 43.0 13.3 0.6 0.3 0.5 370.620 1,199.200 42,754.8 33.34 Israel ISR 70.7 58.7 9,110 7,566 132.6 307.2 407.3 113.2 94.0 0.4 0.5 0.1 2.972 3.578 210.2 7.76 Jordan JOR 21.7 5.3 3,098 754 38.9 104.5 40.6 38.5 9.4 0.1 0.0 0.1 0.172 0.708 3.7 6.99 Kuwait KWT 33.9 22.6 11,066 7,371 106.3 373.2 396.8 137.5 91.6 0.2 0.2 0.0 0.186 0.280 6.3 3.07 Malta MLT 3.3 1.9 7,990 4,497 89.8 269.5 242.1 99.3 55.9 0.0 0.0 0.0 0.404 0.718 1.3 0.42 Morocco MAR 57.2 19.1 1,756 585 53.2 59.2 31.5 21.8 7.3 0.3 0.2 0.5 2.681 8.049 153.4 32.58 Oman OMN 34.1 12.3 10,336 3,720 57.4 348.6 200.3 128.4 46.2 0.2 0.1 0.0 0.138 0.385 4.7 3.30 Qatar QAT 35.6 18.5 20,548 10,660 82.8 693.0 573.8 255.3 132.4 0.2 0.1 0.0 1.894 3.650 67.4 1.73 Saudi Arabia SAU 428.8 128.5 15,221 4,561 47.8 513.3 245.5 189.1 56.7 2.1 1.0 0.4 1.124 3.750 481.9 28.17 Tunisia TUN 34.9 8.3 3,252 769 37.7 109.7 41.4 40.4 9.6 0.2 0.1 0.2 0.333 1.408 11.6 10.74 United Arab Emirates ARE 64.4 34.9 7,424 4,025 86.5 250.4 216.7 92.2 50.0 0.3 0.3 0.1 1.991 3.673 128.2 8.67 West Bank and Gaza PSE 5.9 2.9 1,528 746 77.9 51.5 40.1 19.0 9.3 0.0 0.0 0.1 1.747 3.578 10.3 3.88 d Yemen, Rep. YEM 15.3 4.4 641 186 46.2 21.6 10.0 8.0 2.3 0.1 0.0 0.4 61.864 213.800 945.5 23.83 Total (17) MEB 1,755.8 490.4 4,893 1,367 44.6 165.0 73.6 60.8 17.0 8.8 3.9 5.3 n.a. n.a n.a. 358.87 North America Bermuda BMU 0.8 0.8 12,193 12,584 164.7 411.2 677.4 151.5 156.3 0.0 0.0 0.0 1.032 1.000 0.8 0.07 Canada CAN 333.7 379.1 9,718 11,039 181.3 327.7 594.2 120.7 137.1 1.7 3.0 0.5 1.124 0.990 375.1 34.34 United States USA 2,511.8 2,511.8 8,050 8,050 159.6 271.5 433.3 100.0 100.0 12.6 20.1 4.6 1.000 1.000 2,511.8 312.03 Total (3) NAB 2,846.3 2,891.7 8,216 8,347 162.2 277.1 449.3 102.1 103.7 14.3 23.1 5.1 n.a. n.a n.a. 346.44 South Asia Bangladesh BGD 33.2 6.7 222 45 32.4 7.5 2.4 2.8 0.6 0.2 0.1 2.2 15.053 74.152 499.3 149.70 Bhutan BTN 2.1 0.4 3,110 538 27.6 104.9 28.9 38.6 6.7 0.0 0.0 0.0 8.066 46.670 17.0 0.68 India IND 792.5 202.8 652 167 40.8 22.0 9.0 8.1 2.1 4.0 1.6 18.1 11.944 46.670 9,465.4 1,216.15 Maldives MDV 1.9 0.6 4,598 1,462 50.7 155.1 78.7 57.1 18.2 0.0 0.0 0.0 4.642 14.602 8.7 0.41 Nepal NPL 6.8 1.9 255 70 44.0 8.6 3.8 3.2 0.9 0.0 0.0 0.4 20.417 74.020 138.0 26.49 Pakistan PAK 117.0 22.5 661 127 30.7 22.3 6.8 8.2 1.6 0.6 0.2 2.6 16.583 86.343 1,941.0 177.10 Sri Lanka LKA 39.2 5.6 1,941 277 22.7 65.5 14.9 24.1 3.4 0.2 0.0 0.3 15.754 110.565 617.7 20.20 Total (7) SAB 992.6 240.4 624 151 38.7 21.0 8.1 7.8 1.9 5.0 1.9 23.6 n.a. n.a n.a. 1,590.72 Sub-Saharan Africa Angola AGO 40.1 20.4 1,656 842 81.1 55.8 45.3 20.6 10.5 0.2 0.2 0.4 47.756 93.935 1,914.9 24.22 Benin BEN 4.3 1.3 458 136 47.3 15.4 7.3 5.7 1.7 0.0 0.0 0.1 139.916 471.866 605.9 9.46 Botswana BWA 8.3 2.8 4,118 1,408 54.6 138.9 75.8 51.2 17.5 0.0 0.0 0.0 2.339 6.838 19.4 2.02 (continued) Revised 2011 results and comparisons with original ICP 2011 results 141 Table E.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 6.6 2.2 407 139 54.3 13.7 7.5 5.1 1.7 0.0 0.0 0.2 160.599 471.866 1,052.4 16.08 Burundi BDI 1.8 0.4 199 46 37.0 6.7 2.5 2.5 0.6 0.0 0.0 0.1 292.235 1,261.073 521.1 8.96 Cabo Verde CPV 0.8 0.3 1,647 692 67.1 55.6 37.3 20.5 8.6 0.0 0.0 0.0 33.346 79.323 27.4 0.50 Cameroon CMR 10.6 3.6 507 170 53.5 17.1 9.1 6.3 2.1 0.1 0.0 0.3 158.288 471.866 1,676.6 20.91 Central African Republic CAF 0.8 0.3 170 57 54.1 5.7 3.1 2.1 0.7 0.0 0.0 0.1 159.791 471.866 119.9 4.42 Chad TCD 4.0 1.5 328 122 59.4 11.0 6.6 4.1 1.5 0.0 0.0 0.2 175.462 471.866 710.4 12.36 Comoros COM 0.3 0.1 420 154 58.6 14.2 8.3 5.2 1.9 0.0 0.0 0.0 129.901 353.900 38.5 0.71 Congo, Dem. Rep. COD 11.6 3.7 173 55 51.1 5.8 3.0 2.2 0.7 0.1 0.0 1.0 294.368 919.491 3,405.6 66.76 Congo, Rep. COG 4.4 2.2 1,009 495 78.3 34.0 26.6 12.5 6.1 0.0 0.0 0.1 231.502 471.866 1,026.3 4.39 Côte d’Ivoire CIV 7.8 2.9 370 136 58.5 12.5 7.3 4.6 1.7 0.0 0.0 0.3 172.992 471.866 1,346.9 21.03 Equatorial Guinea GNQ 4.7 2.7 4,797 2,749 91.5 161.8 148.0 59.6 34.2 0.0 0.0 0.0 270.399 471.866 1,280.1 0.99 Eswatini SWZ 1.9 1.0 1,804 887 78.5 60.8 47.7 22.4 11.0 0.0 0.0 0.0 3.570 7.261 6.9 1.07 Ethiopia ETH 21.2 3.2 235 36 24.5 7.9 1.9 2.9 0.4 0.1 0.0 1.3 2.590 16.899 54.9 90.14 Gabon GAB 6.2 2.8 3,674 1,655 71.9 123.9 89.1 45.6 20.6 0.0 0.0 0.0 212.527 471.866 1,315.3 1.68 Gambia, The GMB 0.8 0.1 412 79 30.5 13.9 4.2 5.1 1.0 0.0 0.0 0.0 5.629 29.462 4.3 1.85 Ghana GHA 25.6 7.4 1,009 292 46.2 34.0 15.7 12.5 3.6 0.1 0.1 0.4 0.437 1.512 11.2 25.39 Guinea GIN 5.1 1.0 490 98 31.8 16.5 5.2 6.1 1.2 0.0 0.0 0.2 1,325.512 6,658.031 6,765.0 10.42 Guinea-Bissau GNB 0.8 0.2 522 130 39.8 17.6 7.0 6.5 1.6 0.0 0.0 0.0 117.740 471.866 96.0 1.56 Kenya KEN 17.5 5.9 404 136 53.6 13.6 7.3 5.0 1.7 0.1 0.0 0.6 29.839 88.811 520.9 43.18 Lesotho LSO 2.2 1.0 1,083 486 71.6 36.5 26.1 13.5 6.0 0.0 0.0 0.0 3.255 7.261 7.1 2.00 Liberia LBR 1.1 0.4 272 93 54.6 9.2 5.0 3.4 1.2 0.0 0.0 0.1 24.721 72.227 27.0 4.02 Madagascar MDG 6.6 1.6 302 73 38.5 10.2 3.9 3.7 0.9 0.0 0.0 0.3 488.473 2,025.118 3,203.3 21.74 Malawi MWI 1.8 0.7 122 50 64.7 4.1 2.7 1.5 0.6 0.0 0.0 0.2 63.489 156.515 116.1 14.96 Mali MLI 7.4 2.2 476 142 47.6 16.1 7.6 5.9 1.8 0.0 0.0 0.2 140.672 471.866 1,039.7 15.51 Mauritania MRT 3.3 0.9 912 260 45.5 30.7 14.0 11.3 3.2 0.0 0.0 0.1 80.207 281.118 263.1 3.60 Mauritius MUS 4.1 1.3 3,295 1,040 50.4 111.1 56.0 40.9 12.9 0.0 0.0 0.0 9.058 28.706 37.3 1.25 Mozambique MOZ 4.9 2.6 204 108 84.7 6.9 5.8 2.5 1.3 0.0 0.0 0.4 15.419 29.068 76.1 24.19 Namibia NAM 6.7 2.9 3,093 1,334 68.9 104.3 71.8 38.4 16.6 0.0 0.0 0.0 3.132 7.261 20.9 2.16 Niger NER 2.9 1.0 168 59 55.5 5.7 3.2 2.1 0.7 0.0 0.0 0.3 164.022 471.866 473.0 17.11 Nigeria NGA 109.1 35.2 670 216 51.4 22.6 11.6 8.3 2.7 0.5 0.3 2.4 49.595 153.862 5,412.0 162.81 Rwanda RWA 1.8 0.9 177 85 76.7 6.0 4.6 2.2 1.1 0.0 0.0 0.2 288.376 600.307 524.2 10.29 São Tomé and Príncipe STP 0.4 0.1 2,175 445 32.6 73.3 23.9 27.0 5.5 0.0 0.0 0.0 3.605 17.623 1.4 0.18 Senegal SEN 7.6 2.6 586 203 55.3 19.8 10.9 7.3 2.5 0.0 0.0 0.2 163.400 471.866 1,247.5 13.03 Seychelles SYC 1.1 0.3 12,479 3,171 40.6 420.9 170.7 155.0 39.4 0.0 0.0 0.0 3.146 12.381 3.6 0.09 Sierra Leone SLE 1.3 0.3 201 45 35.9 6.8 2.4 2.5 0.6 0.0 0.0 0.1 978.764 4,349.162 1,289.1 6.56 South Africa ZAF 160.1 82.7 3,079 1,590 82.5 103.8 85.6 38.2 19.8 0.8 0.7 0.8 3.751 7.261 600.6 52.00 Sudan SDN 24.9 3.6 733 106 23.1 24.7 5.7 9.1 1.3 0.1 0.0 0.5 0.525 3.630 13.1 33.98 142    Purchasing Power Parities and the Size of World Economies Table E.4  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market CONSUMPTION EXPENDITURE (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange BY GOVERNMENT index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 16.2 4.6 355 102 45.6 12.0 5.5 4.4 1.3 0.1 0.0 0.7 449.517 1,572.116 7,294.0 45.67 Togo TGO 2.1 0.7 326 101 49.4 11.0 5.4 4.0 1.3 0.0 0.0 0.1 146.117 471.866 313.9 6.60 Uganda UGA 16.6 3.8 495 113 36.3 16.7 6.1 6.2 1.4 0.1 0.0 0.5 573.563 2,522.746 9,506.1 33.48 Zambia ZMB 6.7 2.6 477 184 61.4 16.1 9.9 5.9 2.3 0.0 0.0 0.2 1.869 4.861 12.5 14.02 Zimbabwe ZWE 7.6 2.6 586 205 55.9 19.8 11.1 7.3 2.6 0.0 0.0 0.2 0.350 1.000 2.6 12.89 Total (45) SSB 581.7 220.6 672 255 60.5 22.6 13.7 8.3 3.2 2.9 1.8 12.9 n.a. n.a n.a. 866.25 World (178) WLD 19,973.3 12,513.5 2,965 1,858 100.0 100.0 100.0 36.8 23.1 100.0 100.0 100.0 n.a. n.a. n.a. 6,736.12 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. National accounts expenditures for the revised ICP 2011 results are estimated by the ICP Global Office. e. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either Latin America and the Caribbean or the world totals. Revised 2011 results and comparisons with original ICP 2011 results 143 Table E.5  Gross fixed capital formation (GFCF): Revised ICP 2011 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 100.0 Expenditure level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 228.8 400.5 10,241 17,927 223.4 310.3 693.1 109.3 191.4 1.0 2.3 0.3 1.697 0.969 388.3 22.34 Brunei Darussalam BRN 8.3 5.7 21,157 14,364 86.6 641.0 555.4 225.9 153.3 0.0 0.0 0.0 0.854 1.258 7.1 0.39 Cambodia KHM 3.6 1.5 255 104 52.0 7.7 4.0 2.7 1.1 0.0 0.0 0.2 1,654.904 4,058.500 6,035.3 14.31 China CHN 5,766.0 3,452.3 4,290 2,568 76.4 130.0 99.3 45.8 27.4 25.9 19.8 20.0 3.869 6.461 22,306.6 1,344.13 Fiji FJI 1.4 0.7 1,595 876 70.1 48.3 33.9 17.0 9.4 0.0 0.0 0.0 0.985 1.793 1.3 0.85 Hong Kong SAR, China HKG 82.3 58.5 11,640 8,271 90.7 352.7 319.8 124.3 88.3 0.4 0.3 0.1 5.531 7.784 455.3 7.07 Indonesia IDN 636.7 279.6 2,631 1,155 56.0 79.7 44.7 28.1 12.3 2.9 1.6 3.6 3,850.688 8,770.433 2,451,914.0 241.99 Japan JPN 975.1 1,348.7 7,628 10,551 176.5 231.1 407.9 81.4 112.6 4.4 7.7 1.9 110.387 79.807 107,637.5 127.83 Korea, Rep. KOR 468.8 377.9 9,388 7,568 102.9 284.4 292.6 100.2 80.8 2.1 2.2 0.7 893.384 1,108.292 418,824.8 49.94 Lao PDR LAO 7.4 2.9 1,203 470 49.9 36.4 18.2 12.8 5.0 0.0 0.0 0.1 3,140.557 8,030.055 23,103.7 6.12 d Macao SAR, China MAC 7.2 4.6 13,116 8,315 80.9 397.4 321.5 140.0 88.8 0.0 0.0 0.0 5.083 8.018 36.7 0.55 Malaysia MYS 122.6 65.8 4,218 2,264 68.5 127.8 87.5 45.0 24.2 0.6 0.4 0.4 1.642 3.060 201.3 29.06 Mongolia MNG 9.2 5.0 3,285 1,809 70.3 99.5 69.9 35.1 19.3 0.0 0.0 0.0 696.773 1,265.516 6,377.7 2.79 Myanmar MMR 41.7 16.8 840 337 51.2 25.5 13.0 9.0 3.6 0.2 0.1 0.7 328.456 817.917 13,705.0 49.66 New Zealand NZL 24.6 32.9 5,603 7,486 170.5 169.7 289.4 59.8 79.9 0.1 0.2 0.1 1.691 1.266 41.6 4.39 Philippines PHL 89.5 42.0 950 446 59.9 28.8 17.2 10.1 4.8 0.4 0.2 1.4 20.331 43.313 1,819.3 94.18 Singapore SGP 109.9 70.5 21,204 13,602 81.9 642.4 525.9 226.4 145.2 0.5 0.4 0.1 0.807 1.258 88.7 5.18 Taiwan, China TWN 202.5 113.6 8,734 4,898 71.6 264.6 189.4 93.2 52.3 0.9 0.7 0.3 16.525 29.469 3,346.9 23.19 Thailand THA 210.8 97.8 3,184 1,477 59.2 96.5 57.1 34.0 15.8 0.9 0.6 1.0 14.146 30.492 2,982.1 66.21 Vietnam VNM 95.7 40.3 1,086 458 53.8 32.9 17.7 11.6 4.9 0.4 0.2 1.3 8,642.484 20,509.750 827,032.2 88.11 Total (20) EAB 9,092.2 6,417.4 4,174 2,946 90.1 126.5 113.9 44.6 31.5 40.9 36.8 32.3 n.a. n.a n.a. 2,178.31 Europe and Central Asia Albania ALB 6.8 3.8 2,354 1,304 70.7 71.3 50.4 25.1 13.9 0.0 0.0 0.0 55.843 100.812 381.9 2.91 Armenia ARM 2.5 2.6 827 871 134.5 25.1 33.7 8.8 9.3 0.0 0.0 0.0 392.534 372.500 982.7 3.03 Austria AUT 87.4 97.0 10,419 11,565 141.7 315.7 447.1 111.2 123.5 0.4 0.6 0.1 0.797 0.718 69.7 8.39 Azerbaijan AZE 13.5 13.3 1,490 1,469 125.8 45.2 56.8 15.9 15.7 0.1 0.1 0.1 0.779 0.790 10.5 9.05 Belarus BLR 28.5 20.5 3,004 2,163 91.9 91.0 83.6 32.1 23.1 0.1 0.1 0.1 0.404 0.561 11.5 9.47 Belgium BEL 121.3 120.4 10,991 10,910 126.7 333.0 421.8 117.3 116.5 0.5 0.7 0.2 0.713 0.718 86.5 11.04 Bosnia and Herzegovina BIH 6.0 3.5 1,630 944 73.9 49.4 36.5 17.4 10.1 0.0 0.0 0.1 0.814 1.405 4.9 3.66 Bulgaria BGR 19.0 12.0 2,588 1,637 80.7 78.4 63.3 27.6 17.5 0.1 0.1 0.1 0.889 1.405 16.9 7.35 Croatia HRV 18.0 12.6 4,191 2,948 89.8 127.0 114.0 44.7 31.5 0.1 0.1 0.1 3.759 5.344 67.5 4.28 Cyprus CYP 6.2 5.2 7,312 6,167 107.6 221.5 238.5 78.1 65.8 0.0 0.0 0.0 0.606 0.718 3.8 0.85 Czech Republic CZE 70.1 60.4 6,676 5,754 110.0 202.3 222.5 71.3 61.4 0.3 0.3 0.2 15.227 17.665 1,067.0 10.50 Denmark DNK 51.6 62.7 9,267 11,249 154.9 280.8 434.9 98.9 120.1 0.2 0.4 0.1 6.497 5.352 335.4 5.57 Estonia EST 8.1 6.1 6,061 4,619 97.3 183.6 178.6 64.7 49.3 0.0 0.0 0.0 0.547 0.718 4.4 1.33 Finland FIN 54.6 62.3 10,140 11,568 145.6 307.2 447.3 108.2 123.5 0.2 0.4 0.1 0.820 0.718 44.8 5.39 144    Purchasing Power Parities and the Size of World Economies Table E.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 100.0 Expenditure level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) France FRA 562.9 642.5 8,616 9,835 145.7 261.0 380.3 92.0 105.0 2.5 3.7 1.0 0.820 0.718 461.6 65.33 Georgia GEO 3.2 3.1 854 817 122.0 25.9 31.6 9.1 8.7 0.0 0.0 0.1 1.613 1.686 5.2 3.76 Germany DEU 660.2 763.8 8,224 9,515 147.7 249.2 367.9 87.8 101.6 3.0 4.4 1.2 0.831 0.718 548.7 80.28 Greece GRC 43.5 44.0 3,920 3,962 129.0 118.8 153.2 41.9 42.3 0.2 0.3 0.2 0.726 0.718 31.6 11.11 Hungary HUN 38.5 27.8 3,865 2,786 92.0 117.1 107.7 41.3 29.7 0.2 0.2 0.1 144.665 200.697 5,575.6 9.97 Iceland ISL 1.7 2.3 5,463 7,316 170.9 165.5 282.9 58.3 78.1 0.0 0.0 0.0 155.307 115.963 270.7 0.32 Ireland IRL 45.1 39.5 9,848 8,622 111.7 298.4 333.4 105.1 92.0 0.2 0.2 0.1 0.629 0.718 28.4 4.58 Italy ITA 487.2 452.4 8,111 7,533 118.5 245.8 291.3 86.6 80.4 2.2 2.6 0.9 0.667 0.718 325.0 60.06 Kazakhstan KAZ 43.8 41.3 2,647 2,497 120.4 80.2 96.6 28.3 26.7 0.2 0.2 0.2 138.299 146.620 6,062.3 16.56 Kyrgyz Republic KGZ 1.5 1.5 285 279 124.8 8.6 10.8 3.0 3.0 0.0 0.0 0.1 45.132 46.144 67.8 5.26 Latvia LVA 7.8 6.2 3,790 3,009 101.3 114.8 116.4 40.5 32.1 0.0 0.0 0.0 0.570 0.718 4.5 2.06 Lithuania LTU 10.6 8.0 3,493 2,658 97.1 105.8 102.8 37.3 28.4 0.0 0.0 0.0 0.547 0.718 5.8 3.03 Luxembourg LUX 11.4 11.5 22,036 22,185 128.5 667.6 857.8 235.2 236.8 0.1 0.1 0.0 0.723 0.718 8.3 0.52 Moldova MDA 2.0 2.0 554 548 126.3 16.8 21.2 5.9 5.9 0.0 0.0 0.1 11.602 11.726 22.9 3.56 Montenegro MNE 1.3 0.9 2,073 1,430 88.0 62.8 55.3 22.1 15.3 0.0 0.0 0.0 0.495 0.718 0.6 0.62 Netherlands NLD 164.4 182.3 9,849 10,921 141.5 298.4 422.3 105.1 116.6 0.7 1.0 0.2 0.797 0.718 131.0 16.69 North Macedonia MKD 4.5 2.5 2,207 1,200 69.4 66.9 46.4 23.6 12.8 0.0 0.0 0.0 24.041 44.202 109.2 2.06 Norway NOR 67.5 107.3 13,637 21,666 202.8 413.2 837.7 145.6 231.3 0.3 0.6 0.1 8.895 5.599 600.8 4.95 Poland POL 133.3 109.5 3,461 2,842 104.8 104.9 109.9 37.0 30.3 0.6 0.6 0.6 2.430 2.960 324.1 38.53 Portugal PRT 59.6 45.2 5,643 4,277 96.7 171.0 165.4 60.2 45.7 0.3 0.3 0.2 0.544 0.718 32.4 10.56 Romania ROU 81.0 50.0 4,018 2,482 78.8 121.7 96.0 42.9 26.5 0.4 0.3 0.3 1.881 3.045 152.3 20.15 Russian Federation RUS 445.0 424.4 3,112 2,969 121.7 94.3 114.8 33.2 31.7 2.0 2.4 2.1 28.027 29.382 12,470.7 142.96 Serbia SRB 13.8 8.6 1,912 1,193 79.6 57.9 46.1 20.4 12.7 0.1 0.0 0.1 45.697 73.240 632.4 7.24 Slovak Republic SVK 25.5 23.1 4,730 4,279 115.4 143.3 165.4 50.5 45.7 0.1 0.1 0.1 0.650 0.718 16.6 5.40 Slovenia SVN 12.0 10.3 5,857 5,012 109.2 177.4 193.8 62.5 53.5 0.1 0.1 0.0 0.615 0.718 7.4 2.05 Spain ESP 341.1 296.5 7,299 6,344 110.9 221.1 245.3 77.9 67.7 1.5 1.7 0.7 0.624 0.718 213.0 46.74 Sweden SWE 95.3 132.9 10,083 14,064 178.0 305.5 543.8 107.6 150.1 0.4 0.8 0.1 9.048 6.487 862.1 9.45 Switzerland CHE 113.1 164.2 14,294 20,755 185.3 433.1 802.5 152.6 221.6 0.5 0.9 0.1 1.286 0.885 145.4 7.91 Tajikistan TJK 2.2 2.1 284 274 123.2 8.6 10.6 3.0 2.9 0.0 0.0 0.1 4.449 4.610 9.7 7.71 Turkey TUR 364.2 233.7 4,906 3,148 81.9 148.6 121.7 52.4 33.6 1.6 1.3 1.1 1.075 1.675 391.4 74.22 d Ukraine UKR 36.4 31.4 797 688 110.1 24.2 26.6 8.5 7.3 0.2 0.2 0.7 6.876 7.968 250.5 45.71 United Kingdom GBR 414.9 410.3 6,556 6,484 126.2 198.6 250.7 70.0 69.2 1.9 2.4 0.9 0.617 0.623 255.8 63.29 Total (46) ECB 4,788.2 4,763.7 5,597 5,569 127.0 169.6 215.3 59.8 59.4 21.5 27.3 12.7 n.a. n.a n.a. 855.42 Latin America and the Caribbean Anguilla AIA 0.1 0.0 5,337 3,308 79.1 161.7 127.9 57.0 35.3 0.0 0.0 0.0 1.674 2.700 0.1 0.01 Antigua and Barbuda ATG 0.4 0.2 4,310 2,662 78.8 130.6 102.9 46.0 28.4 0.0 0.0 0.0 1.667 2.700 0.6 0.09 Aruba ABW 1.2 0.7 12,073 6,685 70.7 365.8 258.5 128.9 71.4 0.0 0.0 0.0 0.991 1.790 1.2 0.10 (continued) Revised 2011 results and comparisons with original ICP 2011 results 145 Table E.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 3.6 2.9 10,066 7,928 100.5 305.0 306.6 107.5 84.6 0.0 0.0 0.0 0.788 1.000 2.9 0.36 Barbados BRB 0.9 0.8 3,276 2,762 107.6 99.2 106.8 35.0 29.5 0.0 0.0 0.0 1.686 2.000 1.6 0.28 Belize BLZ 0.2 0.2 708 686 123.7 21.4 26.5 7.6 7.3 0.0 0.0 0.0 1.938 2.000 0.5 0.33 Bolivia BOL 8.5 4.5 830 442 68.0 25.2 17.1 8.9 4.7 0.0 0.0 0.2 3.718 6.982 31.5 10.21 e Bonaire BON … … … … … … … … … … … … … 1.000 … 0.02 Brazil BRA 682.0 539.2 3,453 2,730 100.9 104.6 105.5 36.9 29.1 3.1 3.1 2.9 1.322 1.673 901.9 197.51 Cayman Islands CYM 0.6 0.6 9,675 9,892 130.5 293.1 382.5 103.3 105.6 0.0 0.0 0.0 0.852 0.833 0.5 0.06 Chile CHL 75.8 58.3 4,390 3,377 98.2 133.0 130.6 46.9 36.1 0.3 0.3 0.3 372.146 483.668 28,207.4 17.27 Colombia COL 95.1 71.5 2,065 1,552 95.9 62.6 60.0 22.0 16.6 0.4 0.4 0.7 1,389.490 1,848.139 132,090.0 46.04 Costa Rica CRI 10.7 8.3 2,335 1,811 99.0 70.7 70.0 24.9 19.3 0.0 0.0 0.1 392.116 505.664 4,201.9 4.59 Curaçao CUW 0.9 0.8 5,968 5,182 110.8 180.8 200.4 63.7 55.3 0.0 0.0 0.0 1.554 1.790 1.4 0.15 Dominica DMA 0.1 0.1 1,468 1,172 101.9 44.5 45.3 15.7 12.5 0.0 0.0 0.0 2.155 2.700 0.2 0.07 Dominican Republic DOM 21.5 14.4 2,193 1,463 85.1 66.4 56.5 23.4 15.6 0.1 0.1 0.1 25.412 38.099 546.8 9.81 Ecuador ECU 32.8 20.5 2,150 1,343 79.7 65.1 51.9 22.9 14.3 0.1 0.1 0.2 0.625 1.000 20.5 15.24 El Salvador SLV 5.0 3.3 806 532 84.2 24.4 20.6 8.6 5.7 0.0 0.0 0.1 0.660 1.000 3.3 6.21 Grenada GRD 0.2 0.2 2,088 1,457 89.1 63.3 56.3 22.3 15.6 0.0 0.0 0.0 1.884 2.700 0.4 0.11 Guatemalad GTM 12.9 7.0 866 471 69.3 26.2 18.2 9.2 5.0 0.1 0.0 0.2 4.241 7.807 54.9 14.95 Haiti HTI 3.8 2.0 375 194 65.9 11.4 7.5 4.0 2.1 0.0 0.0 0.1 21.146 40.977 80.1 10.10 Honduras HND 6.9 4.3 811 507 79.7 24.6 19.6 8.7 5.4 0.0 0.0 0.1 11.899 19.048 81.9 8.48 Jamaica JAM 4.2 3.0 1,484 1,070 92.0 45.0 41.4 15.8 11.4 0.0 0.0 0.0 61.956 85.911 259.8 2.83 Mexico MEX 351.6 262.9 3,044 2,276 95.4 92.2 88.0 32.5 24.3 1.6 1.5 1.7 9.290 12.423 3,266.6 115.51 Montserrat MSR 0.0 0.0 5,016 3,410 86.8 152.0 131.8 53.5 36.4 0.0 0.0 0.0 1.836 2.700 0.0 0.00 Nicaragua NIC 3.9 2.4 658 408 79.1 19.9 15.8 7.0 4.4 0.0 0.0 0.1 13.895 22.424 53.9 5.90 Panama PAN 14.2 10.8 3,828 2,914 97.1 116.0 112.7 40.9 31.1 0.1 0.1 0.1 0.761 1.000 10.8 3.71 Paraguay PRY 11.0 7.1 1,742 1,119 82.0 52.8 43.3 18.6 11.9 0.0 0.0 0.1 2,686.447 4,183.127 29,638.3 6.33 Peru PER 57.1 40.1 1,950 1,370 89.7 59.1 53.0 20.8 14.6 0.3 0.2 0.4 1.935 2.754 110.5 29.26 Sint Maarten SXM 0.1 0.1 3,157 2,204 89.1 95.6 85.2 33.7 23.5 0.0 0.0 0.0 1.250 1.790 0.1 0.04 St. Kitts and Nevis KNA 0.3 0.3 5,879 5,114 111.0 178.1 197.7 62.8 54.6 0.0 0.0 0.0 2.349 2.700 0.7 0.05 St. Lucia LCA 0.5 0.4 2,614 2,069 101.0 79.2 80.0 27.9 22.1 0.0 0.0 0.0 2.138 2.700 1.0 0.18 St. Vincent and the VCT 0.2 0.2 2,307 1,588 87.8 69.9 61.4 24.6 16.9 0.0 0.0 0.0 1.858 2.700 0.5 0.11 Grenadines Suriname SUR 2.3 1.6 4,335 2,982 87.8 131.3 115.3 46.3 31.8 0.0 0.0 0.0 2.305 3.350 5.3 0.54 Trinidad and Tobago TTO 6.8 3.9 5,061 2,919 73.6 153.3 112.9 54.0 31.2 0.0 0.0 0.0 3.706 6.426 25.1 1.34 Turks and Caicos Islands TCA 0.1 0.1 2,530 3,132 158.0 76.6 121.1 27.0 33.4 0.0 0.0 0.0 1.238 1.000 0.1 0.03 Uruguay URY 11.6 9.2 3,450 2,722 100.7 104.5 105.2 36.8 29.1 0.1 0.1 0.1 15.236 19.314 177.1 3.37 Venezuela, RBd VEN 83.6 56.1 2,894 1,942 85.7 87.7 75.1 30.9 20.7 0.4 0.3 0.4 2.879 4.289 240.7 28.89 Virgin Islands, British VGB 0.2 0.2 6,484 7,730 152.2 196.4 298.9 69.2 82.5 0.0 0.0 0.0 1.192 1.000 0.2 0.03 Total (39) LCB 1,510.9 1,138.0 2,797 2,107 96.1 84.8 81.5 29.9 22.5 6.8 6.5 8.0 n.a. n.a n.a. 540.10 146    Purchasing Power Parities and the Size of World Economies Table E.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 107.9 63.3 2,943 1,728 74.9 89.2 66.8 31.4 18.4 0.5 0.4 0.5 42.825 72.938 4,620.3 36.66 Bahrain BHR 12.1 6.1 10,101 5,073 64.1 306.0 196.1 107.8 54.2 0.1 0.0 0.0 0.189 0.376 2.3 1.20 Djibouti DJI 1.7 0.9 1,955 1,084 70.8 59.2 41.9 20.9 11.6 0.0 0.0 0.0 98.556 177.721 164.5 0.85 Egypt, Arab Rep. EGY 80.4 38.0 999 472 60.3 30.3 18.2 10.7 5.0 0.4 0.2 1.2 2.808 5.947 225.9 80.53 Iran, Islamic Rep. IRN 255.3 161.3 3,398 2,146 80.6 102.9 83.0 36.3 22.9 1.1 0.9 1.1 6,705.487 10,616.307 1,712,186.3 75.15 Iraq IRQ 52.7 31.1 1,581 932 75.2 47.9 36.0 16.9 9.9 0.2 0.2 0.5 706.775 1,199.200 37,255.3 33.34 Israel ISR 47.9 53.3 6,173 6,870 142.0 187.0 265.6 65.9 73.3 0.2 0.3 0.1 3.982 3.578 190.8 7.76 Jordan JOR 15.9 7.3 2,272 1,050 59.0 68.8 40.6 24.3 11.2 0.1 0.0 0.1 0.327 0.708 5.2 6.99 Kuwait KWT 31.7 19.6 10,338 6,402 79.0 313.2 247.5 110.4 68.3 0.1 0.1 0.0 0.173 0.280 5.5 3.07 Malta MLT 2.1 1.7 5,098 4,098 102.6 154.5 158.5 54.4 43.8 0.0 0.0 0.0 0.578 0.718 1.2 0.42 Morocco MAR 71.9 32.1 2,207 985 57.0 66.9 38.1 23.6 10.5 0.3 0.2 0.5 3.592 8.049 258.3 32.58 Oman OMN 36.4 15.8 11,058 4,793 55.3 335.0 185.3 118.0 51.2 0.2 0.1 0.0 0.167 0.385 6.1 3.30 Qatar QAT 103.7 48.6 59,871 28,034 59.8 1,813.9 1,083.9 639.1 299.3 0.5 0.3 0.0 1.709 3.650 177.3 1.73 Saudi Arabia SAU 346.0 151.7 12,280 5,384 55.9 372.1 208.2 131.1 57.5 1.6 0.9 0.4 1.644 3.750 568.8 28.17 Tunisia TUN 22.4 10.0 2,082 932 57.1 63.1 36.0 22.2 10.0 0.1 0.1 0.2 0.630 1.408 14.1 10.74 United Arab Emirates ARE 142.1 75.3 16,391 8,680 67.6 496.6 335.6 175.0 92.7 0.6 0.4 0.1 1.945 3.673 276.4 8.67 West Bank and Gaza PSE 3.5 2.4 892 608 87.0 27.0 23.5 9.5 6.5 0.0 0.0 0.1 2.439 3.578 8.4 3.88 Yemen, Rep.d YEM 7.9 4.1 330 174 67.4 10.0 6.7 3.5 1.9 0.0 0.0 0.4 112.837 213.800 886.4 23.83 Total (17) MEB 1,341.6 722.6 3,738 2,014 68.7 113.3 77.9 39.9 21.5 6.0 4.1 5.3 n.a. n.a n.a. 358.87 North America Bermuda BMU 0.7 0.7 10,588 10,792 130.1 320.8 417.3 113.0 115.2 0.0 0.0 0.0 1.019 1.000 0.7 0.07 Canada CAN 349.9 421.5 10,188 12,273 153.7 308.7 474.5 108.8 131.0 1.6 2.4 0.5 1.192 0.990 417.1 34.34 United States USA 2,922.9 2,922.9 9,367 9,367 127.6 283.8 362.2 100.0 100.0 13.1 16.8 4.6 1.000 1.000 2,922.9 312.03 Total (3) NAB 3,273.5 3,345.1 9,449 9,656 130.4 286.3 373.3 100.9 103.1 14.7 19.2 5.1 n.a. n.a n.a. 346.44 South Asia Bangladesh BGD 95.7 37.0 639 247 49.4 19.4 9.6 6.8 2.6 0.4 0.2 2.2 28.711 74.152 2,746.8 149.70 Bhutan BTN 2.5 1.2 3,733 1,820 62.2 113.1 70.4 39.9 19.4 0.0 0.0 0.0 22.746 46.670 57.7 0.68 India IND 1,425.0 604.9 1,172 497 54.2 35.5 19.2 12.5 5.3 6.4 3.5 18.1 19.811 46.670 28,230.8 1,216.15 Maldives MDV 1.5 0.9 3,674 2,289 79.5 111.3 88.5 39.2 24.4 0.0 0.0 0.0 9.099 14.602 13.6 0.41 Nepal NPL 9.2 4.2 346 157 58.1 10.5 6.1 3.7 1.7 0.0 0.0 0.4 33.706 74.020 308.5 26.49 Pakistan PAK 70.4 28.9 398 163 52.4 12.0 6.3 4.2 1.7 0.3 0.2 2.6 35.439 86.343 2,494.9 177.10 Sri Lanka LKA 34.8 17.2 1,725 850 62.9 52.3 32.9 18.4 9.1 0.2 0.1 0.3 54.471 110.565 1,897.7 20.20 Total (7) SAB 1,639.1 694.3 1,030 436 54.1 31.2 16.9 11.0 4.7 7.4 4.0 23.6 n.a. n.a n.a. 1,590.72 Sub-Saharan Africa Angola AGO 70.8 44.2 2,922 1,825 79.7 88.5 70.6 31.2 19.5 0.3 0.3 0.4 58.671 93.935 4,151.7 24.22 Benin BEN 2.8 1.9 301 196 83.0 9.1 7.6 3.2 2.1 0.0 0.0 0.1 306.835 471.866 873.3 9.46 Botswana BWA 9.9 4.9 4,904 2,441 63.5 148.6 94.4 52.4 26.1 0.0 0.0 0.0 3.404 6.838 33.6 2.02 (continued) Revised 2011 results and comparisons with original ICP 2011 results 147 Table E.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 4.6 2.8 288 176 78.1 8.7 6.8 3.1 1.9 0.0 0.0 0.2 288.820 471.866 1,336.6 16.08 Burundi BDI 0.6 0.3 68 39 71.8 2.1 1.5 0.7 0.4 0.0 0.0 0.1 709.607 1,261.073 435.1 8.96 Cabo Verde CPV 1.2 0.9 2,309 1,747 96.5 70.0 67.5 24.7 18.6 0.0 0.0 0.0 60.010 79.323 69.1 0.50 Cameroon CMR 10.8 7.1 516 339 83.9 15.6 13.1 5.5 3.6 0.0 0.0 0.3 310.323 471.866 3,348.4 20.91 Central African Republic CAF 0.5 0.3 103 74 91.6 3.1 2.9 1.1 0.8 0.0 0.0 0.1 338.650 471.866 154.2 4.42 Chad TCD 4.6 3.4 371 278 95.7 11.2 10.8 4.0 3.0 0.0 0.0 0.2 353.817 471.866 1,622.9 12.36 Comoros COM 0.3 0.2 491 327 84.8 14.9 12.6 5.2 3.5 0.0 0.0 0.0 235.215 353.900 81.7 0.71 Congo, Dem. Rep. COD 15.8 12.0 237 179 96.4 7.2 6.9 2.5 1.9 0.1 0.1 1.0 694.904 919.491 10,992.8 66.76 Congo, Rep. COG 7.1 6.0 1,615 1,362 107.6 48.9 52.7 17.2 14.5 0.0 0.0 0.1 397.846 471.866 2,824.0 4.39 Côte d’Ivoire CIV 2.8 1.7 131 81 78.7 4.0 3.1 1.4 0.9 0.0 0.0 0.3 291.121 471.866 803.6 21.03 Equatorial Guinea GNQ 13.6 8.1 13,748 8,248 76.6 416.5 318.9 146.8 88.0 0.1 0.0 0.0 283.083 471.866 3,840.7 0.99 Eswatini SWZ 0.9 0.5 874 455 66.4 26.5 17.6 9.3 4.9 0.0 0.0 0.0 3.780 7.261 3.5 1.07 Ethiopia ETH 33.4 13.8 371 153 52.6 11.2 5.9 4.0 1.6 0.2 0.1 1.3 6.964 16.899 232.8 90.14 Gabon GAB 6.9 5.6 4,098 3,312 103.1 124.1 128.0 43.7 35.4 0.0 0.0 0.0 381.355 471.866 2,632.4 1.68 Gambia, The GMB 0.6 0.3 346 188 69.2 10.5 7.3 3.7 2.0 0.0 0.0 0.0 15.968 29.462 10.2 1.85 Ghana GHA 14.0 6.9 550 271 62.9 16.7 10.5 5.9 2.9 0.1 0.0 0.4 0.745 1.512 10.4 25.39 Guinea GIN 2.9 1.8 276 173 80.1 8.4 6.7 2.9 1.8 0.0 0.0 0.2 4,179.494 6,658.031 12,012.5 10.42 Guinea-Bissau GNB 0.1 0.1 77 47 78.8 2.3 1.8 0.8 0.5 0.0 0.0 0.0 291.289 471.866 35.0 1.56 Kenya KEN 16.3 8.5 378 197 66.3 11.5 7.6 4.0 2.1 0.1 0.0 0.6 46.153 88.811 754.2 43.18 Lesotho LSO 1.1 0.7 554 350 80.6 16.8 13.5 5.9 3.7 0.0 0.0 0.0 4.587 7.261 5.1 2.00 Liberia LBR 1.0 0.6 250 142 72.3 7.6 5.5 2.7 1.5 0.0 0.0 0.1 40.943 72.227 41.2 4.02 Madagascar MDG 5.4 2.9 247 131 67.9 7.5 5.1 2.6 1.4 0.0 0.0 0.3 1,076.806 2,025.118 5,775.0 21.74 Malawi MWI 1.6 1.0 110 68 78.8 3.3 2.6 1.2 0.7 0.0 0.0 0.2 96.643 156.515 158.5 14.96 Mali MLI 4.0 2.4 258 156 77.1 7.8 6.0 2.8 1.7 0.0 0.0 0.2 285.083 471.866 1,142.5 15.51 Mauritania MRT 3.1 2.0 865 542 80.0 26.2 21.0 9.2 5.8 0.0 0.0 0.1 176.184 281.118 548.3 3.60 Mauritius MUS 10.4 5.7 8,301 4,581 70.4 251.5 177.1 88.6 48.9 0.0 0.0 0.0 15.841 28.706 164.5 1.25 Mozambique MOZ 4.5 3.1 185 126 87.1 5.6 4.9 2.0 1.3 0.0 0.0 0.4 19.844 29.068 88.8 24.19 Namibia NAM 4.8 2.8 2,219 1,306 75.1 67.2 50.5 23.7 13.9 0.0 0.0 0.0 4.273 7.261 20.5 2.16 Niger NER 4.1 2.5 241 145 76.8 7.3 5.6 2.6 1.5 0.0 0.0 0.3 284.069 471.866 1,169.5 17.11 Nigeria NGA 104.9 64.3 644 395 78.3 19.5 15.3 6.9 4.2 0.5 0.4 2.4 94.366 153.862 9,897.2 162.81 Rwanda RWA 2.3 1.5 227 142 80.0 6.9 5.5 2.4 1.5 0.0 0.0 0.2 376.454 600.307 879.1 10.29 São Tomé and Príncipe STP 0.1 0.1 805 410 65.0 24.4 15.8 8.6 4.4 0.0 0.0 0.0 8.976 17.623 1.3 0.18 Senegal SEN 5.9 3.7 455 287 80.4 13.8 11.1 4.9 3.1 0.0 0.0 0.2 297.359 471.866 1,764.3 13.03 Seychelles SYC 0.6 0.4 6,688 4,653 88.8 202.6 179.9 71.4 49.7 0.0 0.0 0.0 8.614 12.381 5.3 0.09 Sierra Leone SLE 2.5 1.2 375 186 63.4 11.4 7.2 4.0 2.0 0.0 0.0 0.1 2,158.937 4,349.162 5,315.9 6.56 South Africa ZAF 116.9 75.4 2,247 1,450 82.4 68.1 56.1 24.0 15.5 0.5 0.4 0.8 4.686 7.261 547.6 52.00 Sudan SDN 33.9 12.2 998 359 45.9 30.2 13.9 10.7 3.8 0.2 0.1 0.5 1.305 3.630 44.2 33.98 148    Purchasing Power Parities and the Size of World Economies Table E.5  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market GROSS FIXED CAPITAL (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange FORMATION index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 26.6 10.2 582 224 49.1 17.6 8.7 6.2 2.4 0.1 0.1 0.7 605.344 1,572.116 16,078.2 45.67 Togo TGO 1.7 1.1 263 167 80.9 8.0 6.5 2.8 1.8 0.0 0.0 0.1 299.272 471.866 519.3 6.60 Uganda UGA 15.8 6.6 472 197 53.2 14.3 7.6 5.0 2.1 0.1 0.0 0.5 1,051.369 2,522.746 16,621.3 33.48 Zambia ZMB 12.5 6.6 888 468 67.3 26.9 18.1 9.5 5.0 0.1 0.0 0.2 2.562 4.861 31.9 14.02 Zimbabwe ZWE 3.7 2.4 287 189 84.2 8.7 7.3 3.1 2.0 0.0 0.0 0.2 0.660 1.000 2.4 12.89 Total (45) SSB 587.9 340.7 679 393 74.0 20.6 15.2 7.2 4.2 2.6 2.0 12.9 n.a. n.a n.a. 866.25 World (178) WLD 22,233.5 17,421.8 3,301 2,586 100.0 100.0 100.0 35.2 27.6 100.0 100.0 100.0 n.a. n.a. n.a. 6,736.12 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. National accounts expenditures for the revised ICP 2011 results are estimated by the ICP Global Office. e. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either Latin America and the Caribbean or the world totals. Revised 2011 results and comparisons with original ICP 2011 results 149 Table E.6  Domestic absorption: Revised ICP 2011 results Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) East Asia and Pacific Australia AUS 954.3 1,502.4 42,715 67,253 202.7 310.4 629.1 82.7 130.2 1.0 2.1 0.3 1.526 0.969 1,456.6 22.34 Brunei Darussalam BRN 19.0 11.2 48,371 28,505 75.9 351.5 266.6 93.6 55.2 0.0 0.0 0.0 0.741 1.258 14.1 0.39 Cambodia KHM 38.2 12.8 2,673 898 43.2 19.4 8.4 5.2 1.7 0.0 0.0 0.2 1,362.864 4,058.500 52,125.2 14.31 China CHN 13,449.7 7,377.9 10,006 5,489 70.6 72.7 51.3 19.4 10.6 14.5 10.2 20.0 3.544 6.461 47,672.1 1,344.13 Fiji FJI 8.2 4.3 9,573 5,048 67.9 69.6 47.2 18.5 9.8 0.0 0.0 0.0 0.946 1.793 7.7 0.85 Hong Kong SAR, China HKG 349.9 238.9 49,485 33,789 87.9 359.5 316.1 95.8 65.4 0.4 0.3 0.1 5.315 7.784 1,860.0 7.07 Indonesia IDN 2,189.5 870.9 9,048 3,599 51.2 65.7 33.7 17.5 7.0 2.4 1.2 3.6 3,488.424 8,770.433 7,637,914.8 241.99 Japan JPN 4,619.5 6,190.9 36,137 48,430 172.5 262.6 453.0 69.9 93.7 5.0 8.6 1.9 106.955 79.807 494,076.9 127.83 Korea, Rep. KOR 1,629.2 1,239.3 32,625 24,818 97.9 237.0 232.1 63.1 48.0 1.8 1.7 0.7 843.079 1,108.292 1,373,531.9 49.94 Lao PDR LAO 27.8 9.2 4,547 1,504 42.6 33.0 14.1 8.8 2.9 0.0 0.0 0.1 2,656.649 8,030.055 73,889.7 6.12 d Macao SAR, China MAC 25.2 15.4 45,818 27,988 78.6 332.9 261.8 88.7 54.2 0.0 0.0 0.0 4.898 8.018 123.6 0.55 Malaysia MYS 521.7 251.6 17,952 8,656 62.1 130.4 81.0 34.7 16.8 0.6 0.3 0.4 1.475 3.060 769.7 29.06 Mongolia MNG 29.9 12.7 10,720 4,554 54.7 77.9 42.6 20.7 8.8 0.0 0.0 0.0 537.603 1,265.516 16,057.8 2.79 Myanmar MMR 174.6 55.7 3,515 1,121 41.1 25.5 10.5 6.8 2.2 0.2 0.1 0.7 260.897 817.917 45,541.9 49.66 New Zealand NZL 139.2 163.5 31,693 37,211 151.1 230.3 348.1 61.3 72.0 0.2 0.2 0.1 1.486 1.266 206.9 4.39 Philippines PHL 556.7 232.3 5,911 2,466 53.7 42.9 23.1 11.4 4.8 0.6 0.3 1.4 18.072 43.313 10,061.3 94.18 Singapore SGP 279.4 202.5 53,898 39,056 93.3 391.6 365.3 104.3 75.6 0.3 0.3 0.1 0.911 1.258 254.6 5.18 Taiwan, China TWN 876.8 453.0 37,811 19,534 66.5 274.7 182.7 73.2 37.8 0.9 0.6 0.3 15.225 29.469 13,349.4 23.19 Thailand THA 898.1 363.3 13,564 5,486 52.1 98.6 51.3 26.3 10.6 1.0 0.5 1.0 12.333 30.492 11,076.9 66.21 Vietnam VNM 419.0 141.1 4,756 1,602 43.4 34.6 15.0 9.2 3.1 0.5 0.2 1.3 6,908.460 20,509.750 2,894,767.7 88.11 Total (20) EAB 27,206.0 19,348.9 12,490 8,883 91.6 90.7 83.1 24.2 17.2 29.3 26.9 32.3 n.a. n.a n.a. 2,178.31 Europe and Central Asia Albania ALB 34.8 15.8 11,986 5,450 58.5 87.1 51.0 23.2 10.5 0.0 0.0 0.0 45.844 100.812 1,596.3 2.91 Armenia ARM 27.5 12.5 9,074 4,140 58.7 65.9 38.7 17.6 8.0 0.0 0.0 0.0 169.943 372.500 4,669.4 3.03 Austria AUT 362.5 419.6 43,218 50,025 149.0 314.0 467.9 83.6 96.8 0.4 0.6 0.1 0.832 0.718 301.5 8.39 Azerbaijan AZE 100.9 44.6 11,140 4,927 56.9 80.9 46.1 21.6 9.5 0.1 0.1 0.1 0.349 0.790 35.2 9.05 Belarus BLR 159.6 55.4 16,843 5,846 44.7 122.4 54.7 32.6 11.3 0.2 0.1 0.1 0.195 0.561 31.0 9.47 Belgium BEL 453.4 523.9 41,074 47,459 148.7 298.4 443.9 79.5 91.9 0.5 0.7 0.2 0.830 0.718 376.3 11.04 Bosnia and Herzegovina BIH 43.7 23.1 11,943 6,311 68.0 86.8 59.0 23.1 12.2 0.0 0.0 0.1 0.742 1.405 32.5 3.66 Bulgaria BGR 116.2 57.2 15,815 7,785 63.4 114.9 72.8 30.6 15.1 0.1 0.1 0.1 0.692 1.405 80.4 7.35 Croatia HRV 91.8 63.6 21,444 14,850 89.1 155.8 138.9 41.5 28.7 0.1 0.1 0.1 3.701 5.344 339.9 4.28 Cyprus CYP 29.6 28.6 34,827 33,637 124.3 253.0 314.6 67.4 65.1 0.0 0.0 0.0 0.694 0.718 20.6 0.85 Czech Republic CZE 293.8 219.6 27,994 20,921 96.2 203.4 195.7 54.2 40.5 0.3 0.3 0.2 13.202 17.665 3,879.3 10.50 Denmark DNK 227.3 323.0 40,808 57,986 182.9 296.5 542.4 79.0 112.2 0.2 0.4 0.1 7.606 5.352 1,728.8 5.57 Estonia EST 31.5 22.1 23,691 16,602 90.2 172.1 155.3 45.9 32.1 0.0 0.0 0.0 0.503 0.718 15.9 1.33 Finland FIN 223.0 277.8 41,395 51,549 160.3 300.8 482.2 80.1 99.8 0.2 0.4 0.1 0.895 0.718 199.5 5.39 150    Purchasing Power Parities and the Size of World Economies Table E.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) France FRA 2,508.5 2,921.1 38,397 44,712 149.9 279.0 418.2 74.3 86.5 2.7 4.1 1.0 0.837 0.718 2,098.5 65.33 Georgia GEO 36.3 17.9 9,664 4,753 63.3 70.2 44.5 18.7 9.2 0.0 0.0 0.1 0.829 1.686 30.1 3.76 Germany DEU 3,241.7 3,565.4 40,383 44,415 141.6 293.4 415.4 78.2 86.0 3.5 5.0 1.2 0.790 0.718 2,561.4 80.28 Greece GRC 312.6 307.7 28,150 27,709 126.7 204.5 259.2 54.5 53.6 0.3 0.4 0.2 0.707 0.718 221.1 11.11 Hungary HUN 219.0 132.7 21,960 13,309 78.0 159.6 124.5 42.5 25.8 0.2 0.2 0.1 121.633 200.697 26,635.3 9.97 Iceland ISL 11.9 14.0 37,285 43,855 151.4 270.9 410.2 72.2 84.9 0.0 0.0 0.0 136.395 115.963 1,622.3 0.32 Ireland IRL 163.1 193.0 35,622 42,158 152.4 258.8 394.3 68.9 81.6 0.2 0.3 0.1 0.850 0.718 138.7 4.58 Italy ITA 2,214.5 2,327.2 36,871 38,748 135.3 267.9 362.4 71.4 75.0 2.4 3.2 0.9 0.755 0.718 1,671.8 60.06 Kazakhstan KAZ 289.2 154.5 17,465 9,329 68.8 126.9 87.3 33.8 18.1 0.3 0.2 0.2 78.318 146.620 22,647.7 16.56 Kyrgyz Republic KGZ 21.7 7.9 4,125 1,498 46.7 30.0 14.0 8.0 2.9 0.0 0.0 0.1 16.754 46.144 363.5 5.26 Latvia LVA 43.0 29.5 20,863 14,350 88.5 151.6 134.2 40.4 27.8 0.0 0.0 0.0 0.494 0.718 21.2 2.06 Lithuania LTU 71.5 44.6 23,615 14,744 80.4 171.6 137.9 45.7 28.5 0.1 0.1 0.0 0.449 0.718 32.1 3.03 Luxembourg LUX 30.6 40.5 58,973 78,047 170.4 428.5 730.0 114.1 151.1 0.0 0.1 0.0 0.951 0.718 29.1 0.52 Moldova MDA 25.0 11.2 7,013 3,160 58.0 51.0 29.6 13.6 6.1 0.0 0.0 0.1 5.283 11.726 131.9 3.56 Montenegro MNE 10.6 5.5 17,093 8,939 67.3 124.2 83.6 33.1 17.3 0.0 0.0 0.0 0.376 0.718 4.0 0.62 Netherlands NLD 704.4 828.0 42,195 49,604 151.3 306.6 464.0 81.7 96.0 0.8 1.1 0.2 0.845 0.718 594.9 16.69 North Macedonia MKD 27.7 12.5 13,456 6,068 58.1 97.8 56.8 26.0 11.7 0.0 0.0 0.0 19.933 44.202 552.1 2.06 Norway NOR 254.4 434.6 51,355 87,743 219.9 373.1 820.7 99.4 169.8 0.3 0.6 0.1 9.566 5.599 2,433.1 4.95 Poland POL 894.4 539.7 23,216 14,007 77.7 168.7 131.0 44.9 27.1 1.0 0.7 0.6 1.786 2.960 1,597.5 38.53 Portugal PRT 296.4 255.4 28,073 24,191 110.9 204.0 226.3 54.3 46.8 0.3 0.4 0.2 0.619 0.718 183.5 10.56 Romania ROU 380.2 194.3 18,873 9,644 65.8 137.1 90.2 36.5 18.7 0.4 0.3 0.3 1.556 3.045 591.7 20.15 Russian Federation RUS 3,081.8 1,886.4 21,557 13,196 78.8 156.6 123.4 41.7 25.5 3.3 2.6 2.1 17.986 29.382 55,428.1 142.96 Serbia SRB 110.3 55.6 15,244 7,688 64.9 110.8 71.9 29.5 14.9 0.1 0.1 0.1 36.940 73.240 4,074.8 7.24 Slovak Republic SVK 140.7 98.4 26,068 18,234 90.0 189.4 170.6 50.5 35.3 0.2 0.1 0.1 0.503 0.718 70.7 5.40 Slovenia SVN 59.1 51.0 28,803 24,823 110.9 209.3 232.2 55.7 48.0 0.1 0.1 0.0 0.619 0.718 36.6 2.05 Spain ESP 1,489.3 1,473.5 31,866 31,527 127.4 231.5 294.9 61.7 61.0 1.6 2.0 0.7 0.711 0.718 1,058.5 46.74 Sweden SWE 397.9 548.0 42,104 57,990 177.3 305.9 542.4 81.5 112.2 0.4 0.8 0.1 8.934 6.487 3,554.6 9.45 Switzerland CHE 396.7 642.4 50,142 81,191 208.5 364.3 759.4 97.0 157.1 0.4 0.9 0.1 1.434 0.885 568.9 7.91 Tajikistan TJK 26.5 10.2 3,442 1,322 49.5 25.0 12.4 6.7 2.6 0.0 0.0 0.1 1.771 4.610 47.0 7.71 Turkey TUR 1,545.3 900.3 20,820 12,129 75.0 151.3 113.5 40.3 23.5 1.7 1.3 1.1 0.976 1.675 1,508.0 74.22 Ukrained UKR 447.3 179.9 9,787 3,935 51.8 71.1 36.8 18.9 7.6 0.5 0.2 0.7 3.203 7.968 1,433.1 45.71 United Kingdom GBR 2,382.3 2,686.2 37,644 42,447 145.2 273.5 397.0 72.9 82.2 2.6 3.7 0.9 0.703 0.623 1,674.8 63.29 Total (46) ECB 24,029.7 22,656.0 28,091 26,485 121.4 204.1 247.7 54.4 51.3 25.9 31.5 12.7 n.a. n.a n.a. 855.42 Latin America and the Caribbean Anguilla AIA 0.5 0.3 33,536 24,788 95.2 243.7 231.9 64.9 48.0 0.0 0.0 0.0 1.996 2.700 0.9 0.01 Antigua and Barbuda ATG 2.0 1.2 22,001 13,932 81.5 159.9 130.3 42.6 27.0 0.0 0.0 0.0 1.710 2.700 3.4 0.09 Aruba ABW 4.1 3.0 40,142 29,294 93.9 291.7 274.0 77.7 56.7 0.0 0.0 0.0 1.306 1.790 5.4 0.10 (continued) Revised 2011 results and comparisons with original ICP 2011 results 151 Table E.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Bahamas, The BHS 12.9 11.4 35,887 31,777 114.0 260.7 297.2 69.5 61.5 0.0 0.0 0.0 0.885 1.000 11.4 0.36 Barbados BRB 5.2 5.2 18,546 18,236 126.6 134.8 170.6 35.9 35.3 0.0 0.0 0.0 1.967 2.000 10.3 0.28 Belize BLZ 2.6 1.5 7,930 4,577 74.3 57.6 42.8 15.3 8.9 0.0 0.0 0.0 1.154 2.000 3.0 0.33 Bolivia BOL 52.3 22.5 5,117 2,198 55.3 37.2 20.6 9.9 4.3 0.1 0.0 0.2 2.999 6.982 156.8 10.21 e Bonaire BON … … … … … … … … … … … … … 1.000 … 0.02 Brazil BRA 3,014.0 2,636.3 15,260 13,347 112.6 110.9 124.8 29.5 25.8 3.3 3.7 2.9 1.463 1.673 4,410.1 197.51 Cayman Islands CYM 2.7 3.2 47,389 55,748 151.4 344.3 521.5 91.7 107.9 0.0 0.0 0.0 0.980 0.833 2.7 0.06 Chile CHL 343.7 243.9 19,905 14,124 91.3 144.6 132.1 38.5 27.3 0.4 0.3 0.3 343.188 483.668 117,957.6 17.27 Colombia COL 533.2 337.5 11,580 7,330 81.5 84.1 68.6 22.4 14.2 0.6 0.5 0.7 1,169.914 1,848.139 623,796.8 46.04 Costa Rica CRI 64.6 43.8 14,066 9,552 87.4 102.2 89.4 27.2 18.5 0.1 0.1 0.1 343.394 505.664 22,169.5 4.59 Curaçao CUW 5.1 3.8 33,598 24,996 95.8 244.1 233.8 65.0 48.4 0.0 0.0 0.0 1.332 1.790 6.8 0.15 Dominica DMA 0.8 0.6 11,634 8,115 89.8 84.5 75.9 22.5 15.7 0.0 0.0 0.0 1.883 2.700 1.6 0.07 Dominican Republic DOM 126.9 64.2 12,931 6,539 65.1 94.0 61.2 25.0 12.7 0.1 0.1 0.1 19.267 38.099 2,444.8 9.81 Ecuador ECU 152.6 81.1 10,009 5,317 68.4 72.7 49.7 19.4 10.3 0.2 0.1 0.2 0.531 1.000 81.1 15.24 El Salvador SLV 47.8 24.6 7,699 3,962 66.3 55.9 37.1 14.9 7.7 0.1 0.0 0.1 0.515 1.000 24.6 6.21 Grenada GRD 1.5 1.0 13,680 9,157 86.2 99.4 85.7 26.5 17.7 0.0 0.0 0.0 1.807 2.700 2.6 0.11 Guatemalad GTM 110.8 52.6 7,411 3,520 61.2 53.8 32.9 14.3 6.8 0.1 0.1 0.2 3.709 7.807 410.8 14.95 Haiti HTI 22.8 10.8 2,260 1,072 61.1 16.4 10.0 4.4 2.1 0.0 0.0 0.1 19.436 40.977 443.7 10.10 Honduras HND 39.3 21.1 4,634 2,483 69.0 33.7 23.2 9.0 4.8 0.0 0.0 0.1 10.204 19.048 401.0 8.48 Jamaica JAM 27.8 17.8 9,834 6,290 82.3 71.5 58.8 19.0 12.2 0.0 0.0 0.0 54.952 85.911 1,527.1 2.83 Mexico MEX 1,938.8 1,197.0 16,784 10,362 79.5 122.0 96.9 32.5 20.1 2.1 1.7 1.7 7.670 12.423 14,870.3 115.51 Montserrat MSR 0.1 0.1 28,258 18,616 84.8 205.3 174.1 54.7 36.0 0.0 0.0 0.0 1.779 2.700 0.2 0.00 Nicaragua NIC 29.2 11.9 4,947 2,017 52.5 35.9 18.9 9.6 3.9 0.0 0.0 0.1 9.142 22.424 266.9 5.90 Panama PAN 66.1 36.8 17,835 9,922 71.6 129.6 92.8 34.5 19.2 0.1 0.1 0.1 0.556 1.000 36.8 3.71 Paraguay PRY 64.7 33.1 10,215 5,228 65.9 74.2 48.9 19.8 10.1 0.1 0.0 0.1 2,140.926 4,183.127 138,522.3 6.33 Peru PER 289.8 163.1 9,904 5,575 72.5 72.0 52.1 19.2 10.8 0.3 0.2 0.4 1.550 2.754 449.3 29.26 Sint Maarten SXM 1.2 0.9 33,498 25,014 96.1 243.4 234.0 64.8 48.4 0.0 0.0 0.0 1.337 1.790 1.6 0.04 St. Kitts and Nevis KNA 1.3 1.0 26,419 19,274 93.9 192.0 180.3 51.1 37.3 0.0 0.0 0.0 1.970 2.700 2.6 0.05 St. Lucia LCA 2.5 1.7 14,056 9,614 88.1 102.1 89.9 27.2 18.6 0.0 0.0 0.0 1.847 2.700 4.6 0.18 St. Vincent and the VCT 1.4 0.9 13,135 8,207 80.4 95.4 76.8 25.4 15.9 0.0 0.0 0.0 1.687 2.700 2.4 0.11 Grenadines Suriname SUR 7.3 4.0 13,584 7,534 71.4 98.7 70.5 26.3 14.6 0.0 0.0 0.0 1.858 3.350 13.5 0.54 Trinidad and Tobago TTO 31.6 18.6 23,650 13,927 75.8 171.8 130.3 45.8 27.0 0.0 0.0 0.0 3.784 6.426 119.6 1.34 Turks and Caicos Islands TCA 0.5 0.6 15,907 16,639 134.7 115.6 155.6 30.8 32.2 0.0 0.0 0.0 1.046 1.000 0.6 0.03 Uruguay URY 61.1 48.2 18,144 14,294 101.4 131.8 133.7 35.1 27.7 0.1 0.1 0.1 15.216 19.314 930.1 3.37 d Venezuela, RB VEN 456.8 284.0 15,812 9,833 80.1 114.9 92.0 30.6 19.0 0.5 0.4 0.4 2.667 4.289 1,218.4 28.89 Virgin Islands, British VGB 0.6 0.6 20,116 21,198 135.7 146.2 198.3 38.9 41.0 0.0 0.0 0.0 1.054 1.000 0.6 0.03 Total (39) LCB 7,526.1 5,389.8 13,935 9,979 92.2 101.2 93.3 27.0 19.3 8.1 7.5 8.0 n.a. n.a n.a. 540.10 152    Purchasing Power Parities and the Size of World Economies Table E.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Middle East and North Africa Algeria DZA 450.2 179.8 12,280 4,905 51.4 89.2 45.9 23.8 9.5 0.5 0.2 0.5 29.131 72.938 13,115.2 36.66 Bahrain BHR 47.2 21.7 39,496 18,134 59.1 287.0 169.6 76.4 35.1 0.1 0.0 0.0 0.173 0.376 8.1 1.20 Djibouti DJI 4.7 2.4 5,486 2,864 67.2 39.9 26.8 10.6 5.5 0.0 0.0 0.0 92.781 177.721 434.5 0.85 Egypt, Arab Rep. EGY 952.5 269.6 11,828 3,348 36.4 85.9 31.3 22.9 6.5 1.0 0.4 1.2 1.684 5.947 1,603.6 80.53 Iran, Islamic Rep. IRN 1,464.3 661.8 19,485 8,806 58.2 141.6 82.4 37.7 17.0 1.6 0.9 1.1 4,797.945 10,616.307 7,025,557.5 75.15 Iraq IRQ 308.0 129.6 9,239 3,888 54.2 67.1 36.4 17.9 7.5 0.3 0.2 0.5 504.623 1,199.200 155,438.1 33.34 Israel ISR 239.4 262.0 30,834 33,748 140.9 224.0 315.7 59.7 65.3 0.3 0.4 0.1 3.916 3.578 937.4 7.76 Jordan JOR 89.2 36.5 12,758 5,224 52.7 92.7 48.9 24.7 10.1 0.1 0.1 0.1 0.290 0.708 25.9 6.99 Kuwait KWT 123.9 80.0 40,417 26,090 83.1 293.7 244.0 78.2 50.5 0.1 0.1 0.0 0.181 0.280 22.4 3.07 Malta MLT 11.7 9.3 28,207 22,332 101.9 204.9 208.9 54.6 43.2 0.0 0.0 0.0 0.569 0.718 6.7 0.42 Morocco MAR 253.5 116.2 7,781 3,566 59.0 56.5 33.4 15.1 6.9 0.3 0.2 0.5 3.689 8.049 935.1 32.58 Oman OMN 102.0 47.7 30,968 14,472 60.2 225.0 135.4 59.9 28.0 0.1 0.1 0.0 0.180 0.385 18.3 3.30 Qatar QAT 147.7 89.5 85,219 51,644 78.0 619.2 483.1 164.9 100.0 0.2 0.1 0.0 2.212 3.650 326.6 1.73 Saudi Arabia SAU 1,237.8 493.0 43,935 17,499 51.3 319.2 163.7 85.0 33.9 1.3 0.7 0.4 1.494 3.750 1,848.7 28.17 Tunisia TUN 115.6 49.2 10,761 4,584 54.8 78.2 42.9 20.8 8.9 0.1 0.1 0.2 0.600 1.408 69.3 10.74 United Arab Emirates ARE 427.2 250.8 49,258 28,917 75.6 357.9 270.5 95.3 56.0 0.5 0.3 0.1 2.156 3.673 921.0 8.67 West Bank and Gaza PSE 22.7 14.4 5,853 3,710 81.6 42.5 34.7 11.3 7.2 0.0 0.0 0.1 2.268 3.578 51.5 3.88 d Yemen, Rep. YEM 85.5 31.7 3,590 1,331 47.8 26.1 12.5 6.9 2.6 0.1 0.0 0.4 79.303 213.800 6,784.1 23.83 Total (17) MEB 6,083.2 2,745.2 16,951 7,650 58.1 123.2 71.6 32.8 14.8 6.6 3.8 5.3 n.a. n.a n.a. 358.87 North America Bermuda BMU 3.0 4.4 46,166 68,210 190.2 335.4 638.0 89.4 132.0 0.0 0.0 0.0 1.478 1.000 4.4 0.07 Canada CAN 1,453.3 1,813.3 42,316 52,800 160.6 307.5 493.9 81.9 102.2 1.6 2.5 0.5 1.235 0.990 1,794.3 34.34 United States USA 16,122.0 16,122.0 51,668 51,668 128.7 375.4 483.3 100.0 100.0 17.4 22.4 4.6 1.000 1.000 16,122.0 312.03 Total (3) NAB 17,578.3 17,939.8 50,740 51,783 131.4 368.7 484.4 98.2 100.2 19.0 24.9 5.1 n.a. n.a n.a. 346.44 South Asia Bangladesh BGD 451.0 143.1 3,013 956 40.9 21.9 8.9 5.8 1.9 0.5 0.2 2.2 23.530 74.152 10,613.0 149.70 Bhutan BTN 6.6 2.4 9,649 3,463 46.2 70.1 32.4 18.7 6.7 0.0 0.0 0.0 16.750 46.670 109.8 0.68 India IND 5,764.7 1,928.0 4,740 1,585 43.1 34.4 14.8 9.2 3.1 6.2 2.7 18.1 15.609 46.670 89,983.0 1,216.15 Maldives MDV 4.5 2.5 11,063 6,040 70.3 80.4 56.5 21.4 11.7 0.0 0.0 0.0 7.972 14.602 35.8 0.41 Nepal NPL 69.1 24.1 2,608 911 45.0 19.0 8.5 5.0 1.8 0.1 0.0 0.4 25.860 74.020 1,786.9 26.49 Pakistan PAK 814.0 236.5 4,596 1,336 37.4 33.4 12.5 8.9 2.6 0.9 0.3 2.6 25.087 86.343 20,422.1 177.10 Sri Lanka LKA 206.3 73.9 10,214 3,660 46.1 74.2 34.2 19.8 7.1 0.2 0.1 0.3 39.615 110.565 8,171.4 20.20 Total (7) SAB 7,316.2 2,410.5 4,599 1,515 42.4 33.4 14.2 8.9 2.9 7.9 3.3 23.6 n.a. n.a n.a. 1,590.72 Sub-Saharan Africa Angola AGO 127.8 88.9 5,276 3,672 89.6 38.3 34.3 10.2 7.1 0.1 0.1 0.4 65.376 93.935 8,354.3 24.22 Benin BEN 18.8 8.8 1,986 931 60.4 14.4 8.7 3.8 1.8 0.0 0.0 0.1 221.291 471.866 4,157.4 9.46 Botswana BWA 30.1 15.9 14,934 7,895 68.1 108.5 73.8 28.9 15.3 0.0 0.0 0.0 3.615 6.838 108.8 2.02 (continued) Revised 2011 results and comparisons with original ICP 2011 results 153 Table E.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Burkina Faso BFA 24.6 11.7 1,531 725 61.0 11.1 6.8 3.0 1.4 0.0 0.0 0.2 223.551 471.866 5,504.8 16.08 Burundi BDI 7.4 2.8 823 315 49.2 6.0 2.9 1.6 0.6 0.0 0.0 0.1 481.961 1,261.073 3,555.2 8.96 Cabo Verde CPV 4.0 2.4 7,998 4,815 77.5 58.1 45.0 15.5 9.3 0.0 0.0 0.0 47.751 79.323 190.5 0.50 Cameroon CMR 61.2 30.8 2,926 1,474 64.9 21.3 13.8 5.7 2.9 0.1 0.0 0.3 237.811 471.866 14,545.3 20.91 Central African Republic CAF 4.9 2.6 1,106 596 69.4 8.0 5.6 2.1 1.2 0.0 0.0 0.1 254.507 471.866 1,243.3 4.42 Chad TCD 24.4 13.2 1,972 1,070 69.8 14.3 10.0 3.8 2.1 0.0 0.0 0.2 255.978 471.866 6,238.1 12.36 Comoros COM 2.1 1.2 2,903 1,744 77.4 21.1 16.3 5.6 3.4 0.0 0.0 0.0 212.659 353.900 436.1 0.71 Congo, Dem. Rep. COD 62.2 35.6 931 533 73.6 6.8 5.0 1.8 1.0 0.1 0.0 1.0 525.931 919.491 32,695.5 66.76 Congo, Rep. COG 19.3 12.9 4,381 2,940 86.4 31.8 27.5 8.5 5.7 0.0 0.0 0.1 316.579 471.866 6,096.0 4.39 Côte d’Ivoire CIV 43.1 21.5 2,049 1,021 64.2 14.9 9.6 4.0 2.0 0.0 0.0 0.3 235.239 471.866 10,134.6 21.03 Equatorial Guinea GNQ 21.6 13.7 21,899 13,873 81.6 159.1 129.8 42.4 26.9 0.0 0.0 0.0 298.922 471.866 6,460.1 0.99 Eswatini SWZ 9.7 5.3 9,055 4,974 70.7 65.8 46.5 17.5 9.6 0.0 0.0 0.0 3.989 7.261 38.7 1.07 Ethiopia ETH 160.6 50.0 1,782 555 40.1 12.9 5.2 3.4 1.1 0.2 0.1 1.3 5.261 16.899 845.1 90.14 Gabon GAB 19.8 14.1 11,782 8,352 91.3 85.6 78.1 22.8 16.2 0.0 0.0 0.0 334.469 471.866 6,638.9 1.68 Gambia, The GMB 4.6 1.7 2,503 902 46.4 18.2 8.4 4.8 1.7 0.0 0.0 0.0 10.622 29.462 49.1 1.85 Ghana GHA 100.8 46.7 3,969 1,838 59.6 28.8 17.2 7.7 3.6 0.1 0.1 0.4 0.700 1.512 70.5 25.39 Guinea GIN 21.2 8.2 2,031 786 49.8 14.8 7.4 3.9 1.5 0.0 0.0 0.2 2,578.046 6,658.031 54,550.5 10.42 Guinea-Bissau GNB 2.4 1.2 1,515 738 62.7 11.0 6.9 2.9 1.4 0.0 0.0 0.0 229.778 471.866 544.1 1.56 Kenya KEN 119.5 48.7 2,768 1,127 52.4 20.1 10.5 5.4 2.2 0.1 0.1 0.6 36.157 88.811 4,321.9 43.18 Lesotho LSO 7.5 4.1 3,751 2,040 70.0 27.3 19.1 7.3 3.9 0.0 0.0 0.0 3.950 7.261 29.7 2.00 Liberia LBR 4.0 2.2 1,003 538 69.0 7.3 5.0 1.9 1.0 0.0 0.0 0.1 38.731 72.227 156.1 4.02 Madagascar MDG 36.2 12.8 1,664 590 45.7 12.1 5.5 3.2 1.1 0.0 0.0 0.3 718.131 2,025.118 25,988.0 21.74 Malawi MWI 18.5 9.3 1,237 620 64.6 9.0 5.8 2.4 1.2 0.0 0.0 0.2 78.498 156.515 1,452.8 14.96 Mali MLI 30.6 14.1 1,973 907 59.2 14.3 8.5 3.8 1.8 0.0 0.0 0.2 217.017 471.866 6,642.1 15.51 Mauritania MRT 12.8 5.5 3,551 1,527 55.3 25.8 14.3 6.9 3.0 0.0 0.0 0.1 120.867 281.118 1,544.6 3.60 Mauritius MUS 28.1 15.3 22,493 12,267 70.2 163.4 114.7 43.5 23.7 0.0 0.0 0.0 15.655 28.706 440.5 1.25 Mozambique MOZ 30.0 17.1 1,239 706 73.4 9.0 6.6 2.4 1.4 0.0 0.0 0.4 16.577 29.068 496.6 24.19 Namibia NAM 22.0 13.9 10,204 6,460 81.5 74.1 60.4 19.7 12.5 0.0 0.0 0.0 4.597 7.261 101.2 2.16 Niger NER 16.8 8.1 984 475 62.1 7.2 4.4 1.9 0.9 0.0 0.0 0.3 227.749 471.866 3,837.3 17.11 Nigeria NGA 721.4 368.2 4,431 2,261 65.7 32.2 21.2 8.6 4.4 0.8 0.5 2.4 78.519 153.862 56,646.1 162.81 Rwanda RWA 16.0 7.4 1,555 723 59.8 11.3 6.8 3.0 1.4 0.0 0.0 0.2 279.059 600.307 4,467.7 10.29 São Tomé and Príncipe STP 0.9 0.4 4,610 2,020 56.4 33.5 18.9 8.9 3.9 0.0 0.0 0.0 7.721 17.623 6.6 0.18 Senegal SEN 41.6 21.2 3,192 1,624 65.5 23.2 15.2 6.2 3.1 0.0 0.0 0.2 240.031 471.866 9,986.0 13.03 Seychelles SYC 2.3 1.3 25,314 13,925 70.8 183.9 130.2 49.0 27.0 0.0 0.0 0.0 6.811 12.381 15.8 0.09 Sierra Leone SLE 11.1 4.4 1,684 664 50.8 12.2 6.2 3.3 1.3 0.0 0.0 0.1 1,715.919 4,349.162 18,964.0 6.56 South Africa ZAF 643.1 417.1 12,366 8,021 83.5 89.8 75.0 23.9 15.5 0.7 0.6 0.8 4.710 7.261 3,028.7 52.00 Sudan SDN 152.5 51.7 4,489 1,520 43.6 32.6 14.2 8.7 2.9 0.2 0.1 0.5 1.229 3.630 187.5 33.98 154    Purchasing Power Parities and the Size of World Economies Table E.6  (Continued) Expenditure per capita indexesb Share (world = 100%)b Reference data Expenditure Expenditure per United States = Price Market DOMESTIC ABSORPTION (billion US$) capita (US$) World = 100.0 Expenditure 100.0 level exchange index Based Based Based Based Based PPPsc ratesc Popula- Based Based Based Based (world = on on on on on Based Popula- (US$ = (US$ = Expenditure tion Economy on PPPs on XRs on PPPs on XRs 100.0)a PPPs XRs PPPs XRs PPPs on XRs tion 1.000) 1.000) (billion LCU) (millions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) (13) (14) (15) (16) Tanzania TZA 105.1 37.3 2,302 817 45.7 16.7 7.6 4.5 1.6 0.1 0.1 0.7 557.688 1,572.116 58,631.0 45.67 Togo TGO 9.7 4.7 1,468 712 62.5 10.7 6.7 2.8 1.4 0.0 0.0 0.1 228.944 471.866 2,217.3 6.60 Uganda UGA 94.1 33.1 2,812 988 45.2 20.4 9.2 5.4 1.9 0.1 0.0 0.5 886.618 2,522.746 83,454.3 33.48 Zambia ZMB 47.1 23.5 3,360 1,679 64.3 24.4 15.7 6.5 3.3 0.1 0.0 0.2 2.429 4.861 114.5 14.02 Zimbabwe ZWE 28.8 14.9 2,235 1,156 66.6 16.2 10.8 4.3 2.2 0.0 0.0 0.2 0.517 1.000 14.9 12.89 Total (45) SSB 2,970.2 1,525.4 3,429 1,761 66.1 24.9 16.5 6.6 3.4 3.2 2.1 12.9 n.a. n.a n.a. 866.25 World (178) WLD 92,709.8 72,015.6 13,763 10,691 100.0 100.0 100.0 26.6 20.7 100.0 100.0 100.0 n.a. n.a. n.a. 6,736.12 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. World totals used to calculate price level indexes (PLIs) in this table exclude nonparticipating economies. b. Indexes and shares are rounded to one decimal place for presentation in this table. c. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. d. National accounts expenditures for the revised ICP 2011 results are estimated by the ICP Global Office. e. Bonaire’s results are provided only for individual consumption expenditure by households. Therefore, to ensure consistency across tables, Bonaire is not included in either Latin America and the Caribbean or the world totals. Revised 2011 results and comparisons with original ICP 2011 results 155 Table E.7  Gross domestic product (GDP) and individual consumption expenditure for nonparticipating economies: Revised ICP 2011 results GROSS DOMESTIC PRODUCT Reference data INDIVIDUAL CONSUMPTION Expenditure Expenditure per capita EXPENDITURE BY (billion US$) (US$) Expenditure, HOUSEHOLDS Price level Market gross indexa exchange domestic Based Based Based Based (world = PPPsb ratesb product Population PPPsb Economy on PPPs on XRs on PPPs on XRs 100.0) (US$ = 1.000) (US$ = 1.000) (billion LCU) (millions) (US$ = 1.000) (00) (01) (02) (03) (04) (05) (13) (14) (15) (16) (13) Nonparticipating economies               Afghanistan AFG 51.2 18.2 1,699 604 46.0 16.613 46.747 850.3 30.12 16.788 Argentinac ARG 797.3 528.0 19,295 12,779 85.7 2.733 4.127 2,179.0 41.32 3.161 Eritrea ERI 6.6 2.6 1,475 583 51.2 6.077 15.375 40.1 4.47 6.440 Guyanac GUY 5.2 2.6 6,971 3,426 63.6 100.269 204.018 525.7 0.75 120.832 Lebanon LBN 76.6 40.1 14,723 7,703 67.7 788.752 1,507.500 60,414.1 5.20 830.624 Libya LBY 71.7 34.7 11,582 5,603 62.6 0.592 1.224 42.5 6.19 0.622 Puerto Rico PRI 117.1 100.4 31,824 27,279 111.0 0.857 1.000 100.4 3.68 0.962 South Sudan SSD 32.4 17.3 3,296 1,757 69.0 1.593 2.989 51.6 9.83 1.624 Timor-Leste TLS 2.3 1.1 2,085 948 58.8 0.455 1.000 5.7 1.11 0.502 Turkmenistan TKM 58.4 29.2 11,295 5,650 64.7 1.426 2.850 83.3 5.17 1.462 Uzbekistan UZB 161.0 56.5 5,489 1,926 45.4 601.998 1,715.430 96,949.6 29.34 630.993 Note: PPP = purchasing power parity; XR = market exchange rate; LCU = local currency unit; n.a. = not applicable. a. World totals used to calculate price level indexes (PLIs) in this table include nonparticipating economies. b. PPPs and market exchange rates are rounded to three decimal places for presentation in this table. c. GDP and individual consumption expenditure by households PPPs for Argentina and Guyana are based on a time-series estimation approach. 156    Purchasing Power Parities and the Size of World Economies Table E.8  Gross domestic product: Comparison of revised ICP 2011 results with original ICP 2011 results PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c East Asia and Pacific Australia AUS 1.511 1.511 0.0 1,467.6 1,444.5 1.6 Brunei Darussalam BRN 0.705 0.717 –1.7 23.3 21.0 11.0 Cambodia KHM 1,371.235 1,347.115 1.8 52,068.7 52,068.7 0.0 China CHN 3.524 3.506 0.5 48,930.1 47,310.4 3.4 Fiji FJI 0.949 1.042 –9.0 7.3 6.7 8.9 Hong Kong SAR, China HKG 5.233 5.462 –4.2 1,934.4 1,936.1 –0.1 Indonesia IDN 3,512.754 3,606.566 –2.6 7,831,726.0 7,422,781.2 5.5 Japan JPN 107.454 107.454 0.0 491,408.5 470,623.2 4.4 Korea, Rep. KOR 854.586 854.586 0.0 1,388,937.3 1,235,160.5 12.4 Lao PDR LAO 2,666.535 2,467.753 8.1 71,543.6 64,727.1 10.5 Macao SAR, China MAC 4.440 4.589 –3.2 294.3 295.0 –0.2 Malaysia MYS 1.466 1.459 0.5 911.7 884.5 3.1 Mongolia MNG 533.527 537.127 –0.7 13,173.8 12,546.8 5.0 Myanmar MMR 261.784 234.974 11.4 43,900.0 45,128.0 –2.7 New Zealand NZL 1.486 1.486 0.0 211.3 204.5 3.3 Philippines PHL 18.098 17.854 1.4 9,708.3 9,706.3 0.0 Singapore SGP 0.847 0.891 –5.0 351.4 334.1 5.2 Taiwan, China TWN 15.151 15.112 0.3 14,312.2 13,709.1 4.4 Thailand THA 12.387 12.370 0.1 11,306.9 11,120.5 1.7 Vietnam VNM 6,915.335 6,709.192 3.1 2,779,880.2 2,779,880.2 0.0 Total (20) EAB n.a. n.a. 0.2 n.a. n.a. 4.1 Europe and Central Asia Albania ALB 43.858 45.452 –3.5 1,300.6 1,282.3 1.4 Armenia ARM 163.650 187.095 –12.5 3,777.9 3,777.9 0.0 Austria AUT 0.831 0.830 0.2 310.1 299.2 3.6 Azerbaijan AZE 0.384 0.360 6.4 52.1 52.1 0.0 e Belarus BLR 0.196 0.189 3.8 30.7 29.7 3.4 Belgium BEL 0.832 0.839 –0.8 376.0 369.3 1.8 Bosnia and Herzegovina BIH 0.718 0.724 –0.8 26.2 26.8 –2.0 Bulgaria BGR 0.701 0.660 6.2 80.7 75.3 7.1 Croatia HRV 3.753 3.802 –1.3 333.2 330.2 0.9 Cyprus CYP 0.699 0.673 3.8 19.8 17.9 10.8 Czech Republic CZE 13.345 13.468 –0.9 4,033.8 3,823.4 5.5 Denmark DNK 7.466 7.689 –2.9 1,846.9 1,791.8 3.1 Estonia EST 0.512 0.524 –2.4 16.8 16.2 3.8 Finland FIN 0.898 0.907 –1.0 198.0 188.7 4.9 France FRA 0.841 0.845 –0.4 2,058.4 2,001.4 2.8 Georgia GEO 0.811 0.859 –5.5 25.5 24.3 4.7 Germany DEU 0.789 0.779 1.3 2,693.6 2,609.9 3.2 Greece GRC 0.713 0.693 2.9 207.0 208.5 –0.7 (continued) Revised 2011 results and comparisons with original ICP 2011 results 157 Table E.8  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c Hungary HUN 124.272 123.650 0.5 28,370.8 27,635.4 2.7 Iceland ISL 135.152 133.563 1.2 1,757.7 1,628.7 7.9 Ireland IRL 0.832 0.827 0.5 170.8 162.6 5.1 Italy ITA 0.759 0.768 –1.3 1,648.8 1,580.4 4.3 Kazakhstan KAZ 82.090 80.171 2.4 28,243.1 27,571.9 2.4 Kyrgyz Republic KGZ 15.728 17.757 –11.4 286.0 286.0 0.0 e Latvia LVA 0.499 0.491 1.4 20.2 20.2 0.0 Lithuaniae LTU 0.452 0.454 –0.4 31.2 31.0 0.9 Luxembourg LUX 0.905 0.906 –0.1 43.2 41.7 3.4 Moldova MDA 4.996 5.535 –9.7 98.8 82.3 19.9 Montenegro MNE 0.364 0.369 –1.4 3.3 3.2 1.0 Netherlands NLD 0.836 0.832 0.5 650.4 599.0 8.6 North Macedonia MKD 19.290 18.680 3.3 464.2 459.8 1.0 Norway NOR 9.083 8.973 1.2 2,792.7 2,750.0 1.6 Poland POL 1.801 1.823 –1.2 1,566.8 1,528.1 2.5 Portugal PRT 0.623 0.628 –0.7 176.1 171.1 2.9 Romania ROU 1.550 1.615 –4.0 559.2 556.7 0.5 Russian Federation RUS 18.444 17.346 6.3 60,282.5 55,799.6 8.0 Serbia SRB 36.324 37.288 –2.6 3,612.3 3,208.6 12.6 Slovakia SVK 0.506 0.508 –0.4 71.2 69.0 3.2 Slovak Republc SVN 0.624 0.625 –0.2 37.1 36.1 2.5 Spain ESP 0.714 0.705 1.2 1,061.5 1,046.3 1.4 Sweden SWE 8.844 8.820 0.3 3,719.1 3,480.5 6.9 Switzerland CHE 1.397 1.441 –3.0 621.3 585.1 6.2 Tajikistan TJK 1.565 1.740 –10.0 30.1 30.1 0.0 Turkey TUR 0.966 0.987 –2.1 1,394.5 1,297.7 7.5 Ukraine UKR 3.192 3.434 –7.0 1,349.2 1,302.1 3.6 United Kingdom GBR 0.706 0.698 1.1 1,659.8 1,536.9 8.0 Total (46) ECB n.a. n.a. 0.6 n.a. n.a. 4.5 Latin America and the Caribbean Anguilla AIA 1.990 2.077 –4.2 0.8 0.8 –0.8 Antigua and Barbuda ATG 1.691 1.731 –2.3 3.1 3.0 1.3 Aruba ABW 1.303 1.260 3.4 4.6 4.6 0.0 Bahamas, The BHS 0.899 0.949 –5.3 10.1 7.9 27.9 Barbados BRB 2.019 2.017 0.1 9.3 8.7 6.8 Belize BLZ 1.151 1.150 0.1 3.0 3.0 –0.4 Bolivia BOL 2.981 2.946 1.2 166.2 166.1 0.1 Bonaired BON ... ... ... ... ... ... Brazil BRA 1.473 1.471 0.1 4,376.4 4,143.0 5.6 Cayman Islands CYM 0.942 0.959 –1.8 3.5 2.7 29.4 Chile CHL 348.017 348.017 0.0 122,006.1 121,492.7 0.4 Colombia COL 1,168.243 1,161.910 0.5 618,117.7 621,615.0 –0.6 158    Purchasing Power Parities and the Size of World Economies Table E.8  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c Costa Rica CRI 344.546 346.738 –0.6 21,370.7 20,748.0 3.0 Curaçao CUW 1.325 1.292 2.5 5.4 5.4 0.0 Dominica DMA 1.870 1.861 0.5 1.4 1.3 2.0 Dominican Republic DOM 18.976 19.449 –2.4 2,210.2 2,119.3 4.3 Ecuador ECU 0.528 0.526 0.3 79.3 79.8 –0.6 El Salvador SLV 0.505 0.503 0.4 20.3 23.1 –12.3 Grenada GRD 1.771 1.783 –0.7 2.1 2.1 0.0 Guatemala GTM 3.637 3.626 0.3 371.0 371.3 –0.1 Haiti HTI 18.495 19.108 –3.2 316.4 297.7 6.3 Honduras HND 10.057 9.915 1.4 335.0 335.0 0.0 Jamaica JAM 53.805 54.122 –0.6 1,240.7 1,241.8 –0.1 Mexico MEX 7.673 7.673 0.0 14,665.6 14,536.9 0.9 Montserrat MSR 1.709 1.943 –12.0 0.2 0.2 8.9 Nicaragua NIC 8.710 8.919 –2.3 219.2 216.1 1.4 Panama PAN 0.553 0.547 1.0 34.7 31.3 10.7 Paraguay PRY 2,126.670 2,227.340 –4.5 141,315.8 105,203.2 34.3 Peru PER 1.543 1.521 1.4 473.0 497.8 –5.0 Sint Maarten SXM 1.346 1.379 –2.4 1.7 1.7 –1.5 St. Kitts and Nevis KNA 1.961 1.803 8.8 2.2 2.0 12.3 St. Lucia LCA 1.830 1.844 –0.8 3.9 3.3 19.3 St. Vincent and the Grenadines VCT 1.636 1.691 –3.3 1.9 1.8 3.1 Suriname SUR 1.866 1.826 2.2 14.4 14.3 1.1 Trinidad and Tobago TTO 3.950 3.938 0.3 165.3 150.9 9.5 Turks and Caicos Islands TCA 1.028 1.100 –6.5 0.7 0.7 0.0 Uruguay URY 15.274 15.282 –0.1 926.4 896.8 3.3 Venezuela, RB VEN 2.681 2.713 –1.2 1,357.5 1,357.5 0.0 Virgin Islands, British VGB 1.028 1.076 –4.5 0.9 0.9 0.0 Total (39) LCB n.a. n.a. 0.5 n.a. n.a. 3.1 Middle East and North Africa Algeria DZA 29.476 30.502 –3.4 14,589.0 14,481.0 0.7 Bahrain BHR 0.179 0.211 –15.2 10.8 10.9 –0.9 Djibouti DJI 93.572 94.003 –0.5 392.7 205.3 91.3 Egypt, Arab Rep. EGY 1.675 1.625 3.1 1,516.4 1,371.1 10.6 Iran, Islamic Rep. IRN 4,758.870 4,657.463 2.2 7,542,036.5 6,121,004.0 23.2 Iraq IRQ 523.340 516.521 1.3 191,652.9 191,652.9 0.0 Israel ISR 3.945 3.945 0.0 935.6 923.9 1.3 Jordan JOR 0.291 0.293 –0.8 20.5 20.5 0.1 Kuwait KWT 0.172 0.172 –0.2 42.5 44.3 –4.1 Malta MLT 0.574 0.558 2.8 6.8 6.6 3.1 Morocco MAR 3.672 3.677 –0.1 820.1 802.6 2.2 Oman OMN 0.185 0.192 –3.5 26.1 26.9 –3.0 Qatar QAT 2.153 2.419 –11.0 610.7 624.2 –2.2 (continued) Revised 2011 results and comparisons with original ICP 2011 results 159 Table E.8  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c Saudi Arabia SAU 1.586 1.837 –13.6 2,517.1 2,510.6 0.3 Tunisia TUN 0.596 0.592 0.7 64.5 64.7 –0.4 United Arab Emirates ARE 2.127 2.544 –16.4 1,287.8 1,280.2 0.6 West Bank and Gaza PSE 2.405 2.189 9.9 37.4 35.0 7.1 Yemen, Rep. YEM 81.477 75.818 7.5 6,714.9 6,714.9 0.0 Total (18) MEB n.a. n.a. –5.3 n.a. n.a. 5.1 North America Bermuda BMU 1.397 1.564 –10.7 5.6 5.6 0.9 Canada CAN 1.240 1.243 –0.2 1,774.1 1,759.7 0.8 United States USA 1.000 1.000 0.0 15,542.6 15,533.8 0.1 Total (3) NAB n.a. n.a. 0.0 n.a. n.a. 0.1 South Asia Bangladesh BGD 23.410 23.145 1.1 9,855.2 9,702.9 1.6 Bhutan BTN 16.397 16.856 –2.7 85.0 85.9 –1.2 India IND 15.550 15.109 2.9 85,256.2 86,993.1 –2.0 Maldives MDV 7.862 8.527 –7.8 40.5 31.6 28.3 Nepal NPL 25.255 24.628 2.5 1,440.8 1,449.5 –0.6 Pakistan PAK 24.962 24.346 2.5 19,161.5 19,187.9 –0.1 Sri Lanka LKA 39.289 38.654 1.6 7,219.1 6,542.7 10.3 Total (7) SAB n.a. n.a. 2.7 n.a. n.a. –1.3 Sub-Saharan Africa               Angola AGO 64.606 68.315 –5.4 10,597.0 9,767.6 8.5 Benin BEN 220.434 214.035 3.0 3,684.9 3,439.8 7.1 Botswana BWA 3.655 3.764 –2.9 105.0 102.5 2.4 Burkina Faso BFA 223.116 213.659 4.4 5,092.6 4,868.5 4.6 Burundi BDI 461.509 425.768 8.4 2,837.7 2,599.9 9.1 Cabo Verde CPV 49.695 48.592 2.3 147.9 149.0 –0.7 Cameroon CMR 238.707 227.212 5.1 13,843.1 12,545.7 10.3 Central African Republic CAF 256.761 255.862 0.4 1,148.9 1,029.7 11.6 Chad TCD 258.131 250.443 3.1 5,891.4 5,725.3 2.9 Comoros COM 218.978 207.584 5.5 361.6 95.4 278.9 Congo, Dem. Rep. COD 532.063 521.870 2.0 31,230.5 23,146.1 34.9 Congo, Rep. COG 309.251 289.299 6.9 7,765.6 6,982.5 11.2 Côte d’Ivoire CIV 236.911 228.228 3.8 12,112.7 12,275.5 –1.3 Equatorial Guinea GNQ 297.509 294.572 1.0 10,064.6 8,367.3 20.3 Eswatini SWZ 4.052 3.900 3.9 34.3 29.7 15.4 Ethiopia ETH 5.036 4.919 2.4 768.6 506.1 51.9 Gabon GAB 325.733 318.156 2.4 9,088.2 8,046.1 13.0 Gambia, The GMB 10.142 9.939 2.0 40.3 26.6 51.5 Ghana GHA 0.697 0.699 –0.3 59.8 59.8 0.0 Guinea GIN 2,485.901 2,518.386 –1.3 45,176.5 33,128.3 36.4 Guinea-Bissau GNB 230.392 220.085 4.7 518.3 464.7 11.5 160    Purchasing Power Parities and the Size of World Economies Table E.8  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c Kenya KEN 35.396 34.298 3.2 3,727.4 3,048.9 22.3 Lesotho LSO 4.081 3.923 4.0 19.5 18.3 6.4 e Liberia LBR 39.424 37.345 5.6 111.2 82.9 34.1 Madagascar MDG 694.863 673.730 3.1 23,404.5 20,276.4 15.4 Malawi MWI 78.769 76.259 3.3 1,253.2 1,140.8 9.8 Mali MLI 216.090 210.193 2.8 6,123.9 5,024.5 21.9 Mauritania MRT 119.682 115.855 3.3 1,452.4 1,309.4 10.9 Mauritius MUS 15.853 15.941 –0.5 398.7 323.0 23.5 Mozambique MOZ 16.894 16.030 5.4 414.6 364.7 13.7 Namibia NAM 4.732 4.663 1.5 90.4 90.6 –0.2 Niger NER 226.128 221.087 2.3 3,024.3 3,025.5 0.0 Nigeria NGA 78.777 74.378 5.9 62,931.7 38,017.0 65.5 Rwanda RWA 276.649 260.751 6.1 3,854.3 3,814.4 1.0 São Tomé and Príncipee STP 7.431 8.527 –12.9 4.5 4.4 2.1 Senegal SEN 241.276 236.287 2.1 8,743.8 6,766.8 29.2 Seychelles SYC 6.884 6.690 2.9 13.1 13.1 0.0 Sierra Leone SLE 1,620.575 1,553.139 4.3 12,797.6 12,754.9 0.3 South Africa ZAF 4.777 4.774 0.1 3,053.2 2,917.5 4.6 Sudan SDN 1.231 1.224 0.6 182.2 186.6 –2.4 Tanzania TZA 546.073 522.483 4.5 55,469.0 37,533.0 47.8 Togo TGO 228.625 215.060 6.3 1,837.1 1,739.2 5.6 Uganda UGA 856.168 833.540 2.7 73,174.3 45,944.1 59.3 Zambiae ZMB 2.446 2.378 2.9 123.8 101.1 22.4 Zimbabwe ZWE 0.520 0.504 3.2 12.1 8.9 36.5 Total (45) SSB n.a. n.a. 0.4 n.a. n.a. 22.0 World (178) WLD n.a. n.a. –0.1 n.a. n.a. 3.4 Note: PPP = purchasing power parity; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. Data source: ICP 2011. b. Totals for the regions and the world show average percentage change of PPPs, weighted by the size of expenditures converted by PPPs. c. Totals for the regions and the world show average percentage change of expenditures, weighted by the size of expenditures converted by market exchange rate. d. Bonaire’s results are provided only for individual consumption expenditure by households. e. Original ICP 2011 data were released in a different currency unit and were converted to the same currency as ICP 2017 in this table for comparison purposes. Revised 2011 results and comparisons with original ICP 2011 results 161 Table E.9  Individual consumption expenditure by households: Comparison of revised ICP 2011 results with original ICP 2011 results PPP (US$ = 1.000) Expenditure in local currency units (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c East Asia and Pacific Australia AUS 1.526 1.527 –0.1 797.7 774.5 3.0 Brunei Darussalam BRN 0.832 0.853 –2.4 3.0 4.1 –27.2 Cambodia KHM 1,493.254 1,527.558 –2.2 41,431.0 41,431.0 0.0 China CHN 3.698 3.696 0.0 16,811.1 16,254.7 3.4 Fiji FJI 1.016 1.217 –16.5 5.0 4.8 4.8 Hong Kong SAR, China HKG 5.647 5.753 –1.9 1,224.4 1,224.8 0.0 Indonesia IDN 3,892.218 4,091.939 –4.9 4,340,605.4 4,053,363.6 7.1 Japan JPN 115.178 116.103 –0.8 286,254.9 284,784.3 0.5 Korea, Rep. KOR 903.294 912.021 –1.0 711,118.8 655,386.6 8.5 Lao PDR LAO 3,124.075 2,914.847 7.2 43,566.6 36,750.1 18.5 Macao SAR, China MAC 5.164 5.462 –5.5 62.0 60.5 2.4 Malaysia MYS 1.586 1.586 0.0 437.3 418.3 4.6 Mongolia MNG 580.638 590.330 –1.6 6,782.7 6,885.5 –1.5 Myanmar MMR 278.394 275.828 0.9 26,528.1 28,760.0 –7.8 New Zealand NZL 1.579 1.589 –0.7 123.2 122.2 0.8 Philippines PHL 18.772 18.873 –0.5 7,132.6 7,132.6 0.0 Singapore SGP 1.092 1.171 –6.7 128.5 130.2 –1.3 Taiwan, China TWN 16.136 15.995 0.9 7,799.0 8,235.4 –5.3 Thailand THA 12.759 12.844 –0.7 6,117.6 6,076.1 0.7 Vietnam VNM 7,528.385 7,624.973 –1.3 1,638,345.5 1,638,345.5 0.0 Total (20) EAB n.a. n.a. –1.1 n.a. n.a. 2.2 Europe and Central Asia Albania ALB 54.653 58.168 –6.0 1,018.4 1,029.6 –1.1 Armenia ARM 165.629 183.780 –9.9 3,161.0 3,161.0 0.0 Austria AUT 0.851 0.848 0.5 165.5 163.9 1.0 Azerbaijan AZE 0.323 0.329 –1.8 19.4 19.4 0.0 Belarusd BLR 0.185 0.183 1.1 15.0 14.2 5.6 Belgium BEL 0.878 0.879 –0.1 193.8 194.7 –0.5 Bosnia and Herzegovina BIH 0.854 0.867 –1.4 22.1 22.2 –0.4 Bulgaria BGR 0.794 0.765 3.8 50.2 47.0 6.8 Croatia HRV 4.225 4.359 –3.1 204.0 197.8 3.1 Cyprus CYP 0.759 0.712 6.6 13.0 12.1 7.6 Czech Republic CZE 14.439 14.901 –3.1 1,978.7 1,935.2 2.2 Denmark DNK 8.338 8.524 –2.2 884.9 872.4 1.4 Estonia EST 0.580 0.609 –4.7 8.4 8.2 2.8 Finland FIN 0.973 0.980 –0.7 105.3 105.2 0.1 France FRA 0.880 0.880 0.0 1,131.7 1,155.3 –2.0 Georgia GEO 0.835 0.842 –0.8 21.0 18.0 16.3 Germany DEU 0.827 0.818 1.1 1,464.9 1,498.4 –2.2 Greece GRC 0.768 0.758 1.3 144.7 155.6 –7.0 162    Purchasing Power Parities and the Size of World Economies Table E.9  (Continued) PPP (US$ = 1.000) Expenditure in local currency units (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c Hungary HUN 137.179 137.883 –0.5 14,973.8 14,725.9 1.7 Iceland ISL 140.808 138.895 1.4 916.7 844.8 8.5 Ireland IRL 0.958 0.952 0.6 79.3 78.2 1.4 Italy ITA 0.815 0.825 –1.3 1,007.7 967.9 4.1 Kazakhstan KAZ 79.222 83.612 –5.3 11,916.1 11,791.9 1.1 Kyrgyz Republic KGZ 16.296 17.538 –7.1 238.5 238.5 0.0 d Latvia LVA 0.567 0.571 –0.7 12.4 12.6 –1.3 Lithuaniad LTU 0.511 0.517 –1.3 19.5 19.4 0.2 Luxembourg LUX 0.980 0.989 –1.0 13.5 13.3 2.0 Moldova MDA 5.410 5.451 –0.8 91.8 79.5 15.4 Montenegro MNE 0.441 0.449 –1.8 2.7 2.7 –0.2 Netherlands NLD 0.875 0.869 0.7 296.8 271.8 9.2 North Macedonia MKD 23.608 22.936 2.9 343.1 345.3 –0.6 Norway NOR 9.816 9.797 0.2 1,125.2 1,131.7 –0.6 Poland POL 1.895 1.936 –2.2 963.1 933.9 3.1 Portugal PRT 0.690 0.704 –1.9 116.0 113.0 2.7 Romania ROU 1.810 2.001 –9.5 354.8 353.5 0.4 Russian Federation RUS 18.655 16.769 11.2 30,164.8 27,398.6 10.1 Serbia SRB 43.629 45.370 –3.8 2,728.5 2,469.4 10.5 Slovak Republic SVK 0.556 0.567 –2.0 39.7 39.7 –0.1 Slovenia SVN 0.677 0.681 –0.6 20.9 20.8 0.8 Spain ESP 0.788 0.777 1.5 622.1 612.8 1.5 Sweden SWE 9.021 9.105 –0.9 1,727.8 1,671.2 3.4 Switzerland CHE 1.540 1.613 –4.6 330.2 335.4 –1.6 Tajikistan TJK 1.786 1.883 –5.1 32.1 32.1 0.0 Turkey TUR 1.135 1.164 –2.5 880.9 923.8 –4.7 Ukraine UKR 3.182 3.311 –3.9 907.2 875.6 3.6 United Kingdom GBR 0.776 0.756 2.6 1,066.9 992.3 7.5 Total (46) ECB n.a. n.a. 0.6 n.a. n.a. 1.9 Latin America and the Caribbean Anguilla AIA 2.502 2.591 –3.4 0.7 0.7 0.1 Antigua and Barbuda ATG 2.202 2.200 0.1 1.9 1.8 4.8 Aruba ABW 1.638 1.653 –0.9 2.9 2.9 0.0 Bahamas, The BHS 1.125 1.151 –2.2 6.3 5.6 12.8 Barbados BRB 2.393 2.413 –0.8 6.7 7.1 –6.3 Belize BLZ 1.174 1.183 –0.7 2.1 2.1 –2.2 Bolivia BOL 2.891 2.906 –0.5 100.9 101.3 –0.4 Bonaire BON 0.918 0.919 0.0 0.2 0.2 0.0 Brazil BRA 1.651 1.659 –0.5 2,637.8 2,499.5 5.5 Cayman Islands CYM 1.130 1.136 –0.5 1.9 1.9 –0.6 Chile CHL 386.817 391.644 –1.2 73,356.8 74,405.2 –1.4 Colombia COL 1,210.993 1,196.955 1.2 403,766.7 381,323.0 5.9 (continued) Revised 2011 results and comparisons with original ICP 2011 results 163 Table E.9  (Continued) PPP (US$ = 1.000) Expenditure in local currency units (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c Costa Rica CRI 349.407 343.786 1.6 14,250.9 13,555.4 5.1 Curaçao CUW 1.462 1.429 2.3 3.7 3.8 –2.7 Dominica DMA 2.035 2.069 –1.6 1.2 1.1 6.1 Dominican Republic DOM 20.765 20.741 0.1 1,685.7 1,833.7 –8.1 Ecuador ECU 0.548 0.547 0.1 48.7 48.7 –0.1 El Salvador SLV 0.537 0.531 1.2 17.8 21.6 –17.5 Grenada GRD 2.106 2.092 0.7 1.9 1.9 0.6 Guatemala GTM 3.892 3.873 0.5 316.5 316.6 0.0 Haiti HTI 20.833 20.706 0.6 333.9 334.0 0.0 Honduras HND 10.264 10.080 1.8 260.1 260.1 0.0 Jamaica JAM 62.876 63.354 –0.8 1,065.1 1,063.5 0.1 Mexico MEX 8.886 8.940 –0.6 9,504.3 9,640.8 –1.4 Montserrat MSR 2.225 2.336 –4.7 0.1 0.1 –0.1 Nicaragua NIC 9.251 9.160 1.0 169.2 168.1 0.7 Panama PAN 0.553 0.553 0.0 19.3 18.9 2.1 Paraguay PRY 2,242.096 2,309.430 –2.9 89,930.6 73,739.5 22.0 Peru PER 1.579 1.569 0.7 285.8 296.0 –3.4 Sint Maarten SXM 1.630 1.678 –2.8 1.1 1.0 9.4 St. Kitts and Nevis KNA 2.233 2.221 0.6 1.5 1.3 12.3 St. Lucia LCA 2.084 2.139 –2.6 3.1 2.4 27.7 St. Vincent and the Grenadines VCT 1.998 2.039 –2.0 1.5 1.5 2.3 Suriname SUR 1.900 1.885 0.8 5.2 5.3 –2.7 Trinidad and Tobago TTO 4.520 4.619 –2.1 76.0 69.1 10.0 Turks and Caicos Islands TCA 1.260 1.282 –1.8 0.3 0.3 9.8 Uruguay URY 16.608 16.424 1.1 618.4 609.2 1.5 Venezuela, RB VEN 2.944 2.915 1.0 748.8 748.8 0.0 Virgin Islands, British VGB 1.204 1.250 –3.7 0.3 0.3 0.0 Total (39) LCB n.a. n.a. 0.4 n.a. n.a. 2.4 Middle East and North Africa Algeria DZA 31.518 31.772 –0.8 4,571.9 4,552.7 0.4 Bahrain BHR 0.179 0.215 –17.1 4.2 4.2 0.0 Djibouti DJI 100.624 101.481 –0.8 234.6 136.2 72.3 Egypt, Arab Rep. EGY 1.715 1.803 –4.9 1,200.6 1,036.1 15.9 Iran, Islamic Rep. IRN 5,323.442 5,001.363 6.4 4,065,433.1 2,557,440.1 59.0 Iraq IRQ 477.559 573.418 –16.7 76,260.3 76,260.3 0.0 Israel ISR 4.254 4.270 –0.4 529.9 529.2 0.1 Jordan JOR 0.325 0.319 1.8 16.6 14.6 13.6 Kuwait KWT 0.178 0.180 –1.3 10.3 10.3 –0.1 Malta MLT 0.633 0.629 0.7 4.0 4.0 –0.5 Morocco MAR 4.125 4.193 –1.6 488.3 472.9 3.3 Oman OMN 0.205 0.200 2.4 8.1 8.1 –0.3 Qatar QAT 2.992 2.640 13.3 81.9 79.7 2.8 164    Purchasing Power Parities and the Size of World Economies Table E.9  (Continued) PPP (US$ = 1.000) Expenditure in local currency units (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c Saudi Arabia SAU 1.525 1.785 –14.6 687.9 681.8 0.9 Tunisia TUN 0.697 0.697 0.0 42.8 42.5 0.7 United Arab Emirates ARE 2.397 2.718 –11.8 494.1 661.8 –25.3 West Bank and Gaza PSE 2.438 2.523 –3.4 34.5 33.7 2.1 Yemen, Rep. YEM 76.766 82.094 –6.5 4,573.2 4,573.2 0.0 Total (18) MEB n.a. n.a. –6.4 n.a. n.a. 10.3 North America Bermuda BMU 1.826 1.900 –3.9 3.1 3.7 –16.8 Canada CAN 1.282 1.285 –0.2 991.8 980.1 1.2 United States USA 1.000 1.000 0.0 10,641.1 10,711.8 –0.7 Total (3) NAB n.a. n.a. 0.0 n.a. n.a. –0.5 South Asia Bangladesh BGD 24.732 24.849 –0.5 7,291.8 7,154.3 1.9 Bhutan BTN 17.044 16.963 0.5 35.3 37.6 –6.0 India IND 15.283 14.975 2.1 47,565.7 48,648.2 –2.2 Maldives MDV 8.810 10.676 –17.5 13.4 10.2 31.3 Nepal NPL 25.743 25.759 –0.1 1,101.6 1,114.6 –1.2 Pakistan PAK 25.496 25.414 0.3 15,679.6 15,712.2 –0.2 Sri Lanka LKA 42.988 42.219 1.8 5,143.7 4,568.4 12.6 Total (7) SAB n.a. n.a. 1.7 n.a. n.a. –1.2 Sub-Saharan Africa Angola AGO 80.932 73.833 9.6 3,664.5 4,957.5 –26.1 Benin BEN 225.412 224.917 0.2 2,665.7 2,631.4 1.3 Botswana BWA 4.262 4.438 –4.0 48.6 48.6 0.0 Burkina Faso BFA 223.073 222.242 0.4 3,037.2 3,169.0 –4.2 Burundi BDI 496.117 487.327 1.8 2,573.5 2,244.6 14.7 Cabo Verde CPV 48.057 47.565 1.0 92.8 93.0 –0.2 Cameroon CMR 242.678 230.375 5.3 9,526.5 9,519.1 0.1 Central African Republic CAF 265.661 267.869 –0.8 965.9 925.6 4.4 Chad TCD 250.251 251.296 –0.4 3,328.6 3,811.5 –12.7 Comoros COM 235.604 220.572 6.8 337.1 93.6 260.1 Congo, Dem. Rep. COD 546.732 537.732 1.7 18,298.8 14,337.3 27.6 Congo, Rep. COG 303.724 296.500 2.4 2,009.9 1,552.7 29.4 Côte d’Ivoire CIV 243.461 235.688 3.3 8,298.4 8,294.8 0.0 Equatorial Guinea GNQ 328.091 321.354 2.1 2,048.8 1,004.4 104.0 Eswatini SWZ 4.112 4.049 1.6 27.3 25.1 8.6 Ethiopia ETH 5.575 5.439 2.5 540.5 397.6 35.9 Gabon GAB 359.344 359.219 0.0 2,523.1 2,813.0 –10.3 Gambia, The GMB 10.912 10.826 0.8 34.6 20.2 71.4 Ghana GHA 0.779 0.788 –1.2 48.3 36.8 31.4 Guinea GIN 2,599.891 2,572.343 1.1 36,919.5 18,424.7 100.4 Guinea-Bissau GNB 258.323 248.236 4.1 432.9 311.0 39.2 (continued) Revised 2011 results and comparisons with original ICP 2011 results 165 Table E.9  (Continued) PPP (US$ = 1.000) Expenditure in local currency units (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS Percentage Percentage Economy Revised 2011 Original 2011 difference Revised 2011 Original 2011 difference (00) (01) (02)a (03)b (04) (05)a (06)c Kenya KEN 35.621 35.430 0.5 2,997.9 2,304.9 30.1 Lesotho LSO 3.926 3.864 1.6 18.0 17.8 1.4 Liberiad LBR 43.207 41.005 5.4 88.0 93.3 –5.7 Madagascar MDG 700.228 704.913 –0.7 17,322.0 17,830.7 –2.9 Malawi MWI 78.703 78.017 0.9 1,053.6 1,062.3 –0.8 Mali MLI 224.357 221.868 1.1 4,394.5 3,180.8 38.2 Mauritania MRT 112.849 112.807 0.0 650.8 678.7 –4.1 Mauritius MUS 18.555 18.285 1.5 239.5 237.2 1.0 Mozambique MOZ 15.826 15.527 1.9 289.6 290.6 –0.4 Namibia NAM 5.244 5.131 2.2 59.8 55.9 7.0 Niger NER 230.417 228.753 0.7 2,192.8 2,342.3 –6.4 Nigeria NGA 83.583 79.531 5.1 40,904.9 22,840.8 79.1 Rwanda RWA 251.305 246.834 1.8 3,038.1 3,181.4 –4.5 São Tomé and Prínciped STP 10.487 10.195 2.9 3.7 4.9 –23.9 Senegal SEN 249.278 246.107 1.3 6,756.4 5,312.1 27.2 Seychelles SYC 8.233 7.895 4.3 7.0 6.9 1.3 Sierra Leone SLE 1,825.528 1,767.190 3.3 12,295.1 11,163.1 10.1 South Africa ZAF 5.031 5.068 –0.7 1,831.8 1,731.7 5.8 Sudan SDN 1.465 1.486 –1.4 127.2 129.9 –2.1 Tanzania TZA 588.785 585.520 0.6 39,059.9 24,815.7 57.4 Togo TGO 236.587 232.215 1.9 1,422.5 1,474.2 –3.5 Uganda UGA 944.256 946.890 –0.3 54,266.8 37,758.9 43.7 d Zambia ZMB 2.611 2.505 4.2 63.6 52.5 21.2 Zimbabwe ZWE 0.535 0.536 –0.1 9.8 7.8 26.4 Total (45) SSB n.a. n.a. –0.4 n.a. n.a. 22.4 World (178) WLD n.a. n.a. –0.7 n.a. n.a. 1.9 Note: PPP = purchasing power parity; LCU = local currency unit; n.a. = not applicable; ... = data suppressed due to unavailability. a. Data source: ICP 2011. b. Totals for the regions and the world show average percentage change of PPPs, weighted by the size of expenditures converted by PPPs. c. Totals for the regions and the world show average percentage change of expenditures, weighted by the size of expenditures converted by market exchange rate. d. Original ICP 2011 data were released in a different currency unit and were converted to the same currency as ICP 2017 in this table for comparison purposes. 166    Purchasing Power Parities and the Size of World Economies APPENDIX F Comparison of ICP 2017 results with World Development Indicators data This appendix compares the purchasing power Tables F.1 and F.2 compare ICP 2017 PPPs parities (PPPs) produced by the International with WDI’s 2017 PPPs extrapolated from ICP Comparison Program (ICP) 2017 cycle with PPP 2011 PPPs, and compare ICP 2017 expenditures estimates published in the World Bank’s World in current local currency units with WDI 2017 Development Indicators (WDI) database based expenditures, for the following headings: on extrapolations from the original 2011 ICP • Table F.1 Gross domestic product (GDP) PPPs. It also compares the expenditures used in ICP 2017 with WDI 2017 expenditures. • Table F.2 Individual consumption expendi- These extrapolated 2017 PPPs were published ture by households. in the WDI database released in February 2020, The comparison tables cover the following prior to the release of the ICP 2017 results. To indicators for each heading: extrapolate to a given year, the WDI takes the difference between the rate of inflation observed • Column (00). Name of the economy and its in each economy over each period from or to International Organization for Standardiza- 2011 and the rate of inflation in the United tion (ISO) code States (the base economy for PPPs) over the • Column (01). ICP 2017 PPPs with the US dollar same period and applies it to the 2011 PPP to equal to 1 estimate the economy’s PPP for a given year. • Column (02). WDI 2017 PPPs (as of February Extrapolation for the gross domestic product 2020) with the US dollar equal to 1, extrapo- (GDP) PPPs uses the change in the GDP implicit lated from ICP 2011 PPPs deflator, while extrapolation for the individual • Column (03). Percentage difference between consumption expenditure by households PPPs columns (01) and (02) uses the change in the consumer price index. • Column (04). ICP 2017 expenditures in local For the economies participating in the Statistical currency units Office of the European Union (Eurostat)–Organ- isation for Economic Co-operation and Devel- • Column (05). WDI 2017 expenditures in local opment (OECD) PPP Programme, WDI obtained currency units (as of February 2020) annual PPP estimates by Eurostat-OECD, and • Column (06). Percentage difference between thus the data for those economies are not based columns (04) and (05). on the WDI extrapolation method. 167 Table F.1  Gross domestic product (GDP): Comparison of ICP 2017 results with data in World Development Indicators PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c East Asia and Pacific Australiag AUS 1.466 1.444 1.5 1,808.6 1,763.6 2.6 Brunei Darussalam BRN 0.647 0.494 30.8 16.7 16.7 0.0 Cambodia KHM 1,428.354 1,395.909 2.3 89,830.5 89,830.5 0.0 China CHN 4.184 3.528 18.6 82,075.4 82,075.4 0.0 Fiji FJI 0.939 1.221 –23.1 11.1 11.1 0.0 Hong Kong SAR, China HKG 6.011 5.837 3.0 2,662.8 2,662.8 0.0 Indonesia IDN 4,695.659 4,181.150 12.3 13,587,212.6 13,587,212.6 0.0 Japan JPN 105.379 102.470 2.8 545,121.9 545,121.9 0.0 Korea, Rep. KOR 871.696 866.009 0.7 1,835,698.2 1,730,398.5 6.1 Lao PDR LAO 2,789.109 2,915.892 –4.3 140,697.7 140,749.0 0.0 Malaysia MYS 1.655 1.469 12.7 1,353.4 1,371.6 –1.3 Mongolia MNG 791.436 699.879 13.1 27,876.3 27,876.3 0.0 g Myanmar MMR 366.713 274.511 33.6 85,980.8 90,450.9 –4.9 New Zealand NZL 1.453 1.471 –1.2 282.7 285.1 –0.8 Philippines PHL 19.385 18.021 7.6 15,807.6 15,807.6 0.0 Singapore SGP 0.886 0.862 2.7 467.3 467.3 0.0 Taiwan, China TWN 15.730 ... ... 17,501.2 ... ... Thailand THA 12.845 12.461 3.1 15,452.0 15,452.0 0.0 Vietnam VNM 7,395.338 7,716.431 –4.2 5,005,975.5 5,005,975.0 0.0 Total (19) EAB n.a. n.a. n.a. n.a. n.a. n.a. Europe and Central Asia Albania ALB 41.231 41.753 –1.2 1,551.3 1,551.3 0.0 Armenia ARM 155.971 196.407 –20.6 5,564.5 5,564.5 0.0 Austria AUT 0.770 0.780 –1.3 370.3 370.3 0.0 Azerbaijan AZE 0.505 0.407 24.1 70.3 70.3 0.0 Belarus BLR 0.609 0.589 3.5 105.7 105.7 0.0 Belgium BEL 0.773 0.781 –1.1 446.4 446.4 0.0 Bosnia and Herzegovina BIH 0.676 0.682 –0.8 31.4 31.4 0.0 Bulgaria BGR 0.674 0.682 –1.1 102.3 101.0 1.3 Croatia HRV 3.327 3.371 –1.3 366.4 366.4 0.0 Cyprus CYP 0.615 0.632 –2.7 20.0 20.0 0.0 Czech Republic CZE 12.378 12.531 –1.2 5,047.3 5,047.3 0.0 Denmark DNK 6.852 6.951 –1.4 2,175.1 2,175.1 0.0 Estonia EST 0.534 0.536 –0.4 23.8 23.8 0.0 Finland FIN 0.863 0.877 –1.5 225.8 225.8 0.0 France FRA 0.766 0.776 –1.2 2,295.1 2,295.1 0.0 Georgia GEO 0.805 0.977 –17.6 40.8 40.8 0.0 Germany DEU 0.741 0.754 –1.8 3,245.0 3,245.0 0.0 Greece GRC 0.576 0.586 –1.8 180.2 180.2 0.0 Hungary HUN 134.363 136.069 –1.3 38,835.2 38,835.2 0.0 168    Purchasing Power Parities and the Size of World Economies Table F.1  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c Iceland ISL 137.122 137.725 –0.4 2,613.0 2,616.4 –0.1 Ireland IRL 0.791 0.797 –0.7 297.1 297.1 0.0 Italy ITA 0.687 0.696 –1.4 1,736.6 1,736.6 0.0 Kazakhstan KAZ 121.253 113.802 6.5 54,378.9 54,378.9 0.0 Kyrgyz Republic KGZ 16.959 22.923 –26.0 530.5 530.5 0.0 Latvia LVA 0.484 0.491 –1.3 26.8 26.8 0.0 Lithuania LTU 0.442 0.449 –1.5 42.3 42.3 0.0 Luxembourg LUX 0.844 0.861 –2.0 56.8 56.8 0.0 Moldova MDA 5.572 7.348 –24.2 178.9 178.9 0.0 Montenegro MNE 0.351 0.357 –1.8 4.3 4.3 0.0 Netherlands NLD 0.778 0.791 –1.5 738.1 738.1 0.0 North Macedonia MKD 19.043 19.358 –1.6 618.1 616.6 0.2 Norway NOR 9.922 10.070 –1.5 3,295.4 3,295.4 0.0 Poland POL 1.737 1.750 –0.7 1,989.4 1,988.7 0.0 Portugal PRT 0.575 0.580 –0.9 195.9 195.9 0.0 Romania ROU 1.604 1.645 –2.4 857.9 857.9 0.0 Russian Federation RUS 24.050 24.342 –1.2 92,101.3 92,101.3 0.0 Serbia SRB 40.795 41.207 –1.0 4,754.4 4,754.4 0.0 Slovak Republic SVK 0.503 0.482 4.3 84.5 84.5 0.0 Slovenia SVN 0.568 0.576 –1.4 43.0 43.0 0.0 Spain ESP 0.630 0.641 –1.7 1,161.9 1,161.9 0.0 Sweden SWE 8.719 8.856 –1.5 4,621.0 4,621.0 0.0 Switzerland CHE 1.180 1.193 –1.1 669.5 669.5 0.0 Tajikistan TJK 2.231 2.142 4.1 61.2 61.2 0.0 Turkey TUR 1.373 1.374 –0.1 3,110.7 3,110.7 0.0 Ukraine UKR 5.916 8.079 –26.8 2,983.9 2,983.9 0.0 United Kingdom GBR 0.682 0.691 –1.3 2,071.7 2,071.7 0.0 Total (46) ECB n.a. n.a. n.a. n.a. n.a. n.a. Latin America and the Caribbean Anguilla AIA 2.295 ... ... 0.8 ... ... Antigua and Barbuda ATG 2.094 1.685 24.2 4.1 4.0 3.3 Argentinae ARG 10.257 11.595 –11.5 10,644.8 10,644.8 0.0 Aruba ABW 1.351 1.163 16.2 5.5 4.8 ... Bahamas, The BHS 0.901 1.022 –11.8 12.2 12.2 0.0 Barbados BRB 2.203 1.912 15.2 9.4 10.0 –5.6 Belize BLZ 1.375 1.170 17.5 3.7 3.7 1.4 Bolivia BOL 2.749 3.096 –11.2 259.2 259.2 0.0 d Bonaire BON ... ... ... ... ... ... Brazil BRA 2.182 2.013 8.4 6,583.3 6,553.8 0.4 Cayman Islands CYM 0.974 0.931 4.6 4.3 4.3 0.0 Chile CHL 411.264 402.359 2.2 180,211.3 180,211.3 0.0 Colombia COL 1,314.787 1,297.107 1.4 920,194.0 920,194.0 0.0 (continued) Comparison of ICP 2017 results with World Development Indicators data 169 Table F.1  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c Costa Rica CRI 350.817 392.887 –10.7 34,386.7 33,014.8 4.2 Curaçao CUW 1.367 1.261 8.4 5.6 5.6 0.0 Dominica DMA 1.738 1.844 –5.8 1.4 1.4 0.0 Dominican Republic DOM 21.613 22.094 –2.2 3,802.7 3,802.7 0.0 Ecuador ECU 0.535 0.540 –1.0 104.3 104.3 0.0 El Salvador SLV 0.463 0.489 –5.5 24.9 24.9 0.0 Grenada GRD 1.690 1.873 –9.7 3.0 3.0 0.0 Guyanae GUY 105.353 116.305 –9.4 734.2 734.2 0.0 Haitig HTI 28.498 27.637 3.1 587.5 552.0 6.4 Honduras HND 10.362 11.703 –11.5 543.4 542.6 0.2 Jamaica JAM 67.582 72.281 –6.5 1,898.8 1,894.7 0.2 Mexico MEX 8.871 9.041 –1.9 21,911.9 21,911.9 0.0 Montserrat MSR 1.790 ... ... 0.2 ... ... Nicaragua NIC 10.807 11.457 –5.7 416.0 416.0 0.0 Panama PAN 0.497 0.620 –19.7 62.3 62.3 0.0 Paraguay PRY 2,534.377 2,460.652 3.0 219,188.4 219,188.4 0.0 Peru PER 1.749 1.589 10.1 688.0 688.0 0.0 Sint Maarten SXM 1.387 1.408 –1.5 1.8 1.8 ... St. Kitts and Nevis KNA 2.040 1.791 13.9 2.5 2.7 –5.5 St. Lucia LCA 1.996 2.007 –0.6 4.6 4.9 –6.2 St. Vincent and the Grenadines VCT 1.590 1.653 –3.8 2.3 2.1 6.8 Suriname SUR 2.578 2.685 –4.0 24.0 23.0 4.6 Trinidad and Tobago TTO 4.162 3.499 19.0 154.4 152.4 1.4 Turks and Caicos Islands TCA 1.018 1.086 –6.3 1.0 1.0 2.0 Uruguay URY 23.294 21.856 6.6 1,707.1 1,707.1 0.0 Virgin Islands, British VGB 1.069 ... ... 1.3 ... ... Total (39) LCB n.a. n.a. n.a. n.a. n.a. n.a. Middle East and North Africa Algeria DZA 38.856 29.513 31.7 18,591.7 18,575.8 0.1 Bahrain BHR 0.187 0.187 0.0 13.3 13.3 –0.4 Djibouti DJI 106.023 ... ... 520.2 491.7 5.8 Egypt, Arab Rep.g EGY 3.267 3.064 6.6 4,127.1 3,470.0 18.9 Iran, Islamic Rep.g IRN 13,061.295 9,035.962 44.5 16,954,811.5 15,316,530.0 10.7 Iraq IRQ 560.761 351.198 59.7 206,530.1 231,049.1 –10.6 Israel ISR 3.745 3.755 –0.3 1,271.6 1,271.6 0.0 Jordan JOR 0.300 0.320 –6.1 29.0 28.9 0.4 Kuwait KWT 0.177 0.126 41.0 35.5 36.6 –3.2 Malta MLT 0.578 0.582 –0.7 11.3 11.3 0.0 Morocco MAR 4.023 3.560 13.0 1,063.4 1,063.4 0.0 Oman OMN 0.200 0.140 42.9 27.1 27.1 0.0 Qatar QAT 2.346 1.790 31.1 607.6 607.6 0.0 Saudi Arabia SAU 1.649 1.453 13.5 2,582.2 2,582.2 0.0 170    Purchasing Power Parities and the Size of World Economies Table F.1  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c Tunisia TUN 0.794 0.699 13.6 96.6 96.3 0.3 United Arab Emirates ARE 2.222 1.999 11.1 1,387.1 1,387.1 0.0 West Bank and Gaza PSE 2.036 2.289 –11.1 52.2 ... ... Total (17) MEB n.a. n.a. n.a. n.a. n.a. n.a. North America Bermuda BMU 1.366 ... ... 6.2 ... ... Canada CAN 1.205 1.252 –3.8 2,142.0 2,137.5 0.2 United States USA 1.000 1.000 0.0 19,519.4 19,485.4 0.2 Total (3) NAB n.a. n.a. n.a. n.a. n.a. n.a. South Asia Bangladeshg BGD 29.738 30.948 –3.9 21,131.5 19,758.2 7.0 Bhutan BTN 19.208 21.705 –11.5 164.6 159.6 3.2 Indiag IND 20.648 17.813 15.9 166,225.6 170,950.0 –2.8 Maldives MDV 8.161 10.108 –19.3 74.9 72.9 2.7 Nepalg NPL 31.235 33.672 –7.2 2,611.2 2,674.5 –2.4 Pakistang PAK 33.589 29.292 14.7 33,270.4 31,922.3 4.2 Sri Lanka LKA 49.390 48.587 1.7 13,317.3 13,418.3 –0.8 Total (7) SAB n.a. n.a. n.a. n.a. n.a. n.a. Sub-Saharan Africa Angola AGO 92.952 102.181 –9.0 20,365.4 20,262.3 0.5 Benin BEN 216.774 211.563 2.5 5,450.9 5,382.5 1.3 Botswana BWA 4.734 4.592 3.1 180.3 180.1 0.1 Burkina Faso BFA 208.757 200.349 4.2 7,263.3 7,177.4 1.2 Burundi BDI 654.896 686.482 –4.6 5,562.4 5,485.1 1.4 Cabo Verde CPV 48.477 45.967 5.5 172.4 173.1 –0.4 Cameroon CMR 232.801 227.035 2.5 20,277.0 20,328.4 –0.3 Central African Republic CAF 286.829 318.818 –10.0 1,235.2 1,203.3 2.7 Chad TCD 243.655 200.411 21.6 5,936.3 5,806.8 2.2 Comoros COM 190.126 205.015 –7.3 479.8 469.2 2.3 Congo, Dem. Rep. COD 645.391 769.674 –16.1 72,390.1 55,676.1 30.0 Congo, Rep. COG 297.674 176.521 68.6 7,827.5 5,065.0 54.5 Côte d’Ivoire CIV 253.746 231.131 9.8 22,150.8 22,150.8 0.0 Equatorial Guinea GNQ 248.934 231.055 7.7 7,153.6 7,153.6 0.0 Eswatini SWZ 6.206 5.143 20.7 60.8 59.3 2.6 g Ethiopia ETH 8.521 9.078 –6.1 1,466.0 1,832.6 –20.0 Gabon GAB 279.766 236.363 18.4 7,296.5 8,668.9 –15.8 Gambia, The GMB 15.286 12.854 18.9 66.7 70.1 –4.9 Ghana GHA 1.764 1.977 –10.8 256.7 256.7 0.0 Guinea GIN 3,216.035 3,281.563 –2.0 110,474.2 93,833.9 17.7 Guinea-Bissau GNB 222.749 247.213 –9.9 784.0 784.0 0.0 Kenya KEN 40.185 49.773 –19.3 8,196.7 8,144.4 0.6 Lesotho LSO 5.506 5.247 4.9 34.5 34.4 0.4 (continued) Comparison of ICP 2017 results with World Development Indicators data 171 Table F.1  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) GROSS DOMESTIC PRODUCT 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c Liberiaf LBR 51.957 60.884 –14.7 311.4 370.3 –15.9 Madagascar MDG 1,013.435 885.412 14.5 40,445.3 41,058.8 –1.5 Malawi MWI 251.074 205.176 22.4 4,635.6 4,603.1 0.7 Mali MLI 214.509 217.068 –1.2 8,931.3 8,928.0 0.0 Mauritaniaf MRT 111.258 101.928 9.2 1,760.7 1,756.3 0.2 Mauritius MUS 16.882 16.172 4.4 534.8 457.2 17.0 Mozambique MOZ 22.856 20.683 10.5 804.5 840.5 –4.3 Namibia NAM 7.021 6.769 3.7 179.0 180.6 –0.9 Niger NER 258.460 216.014 19.6 4,727.1 4,726.4 0.0 Nigeria NGA 115.978 102.243 13.4 102,593.5 114,899.2 –10.7 Rwanda RWA 325.126 305.275 6.5 7,025.7 7,600.4 –7.6 São Tomé and Príncipe STP 10.055 11.885 –15.4 6.8 8.2 –16.9 Senegal SEN 246.787 223.796 10.3 12,158.0 12,271.5 –0.9 Seychelles SYC 7.969 7.365 8.2 21.4 20.5 4.1 Sierra Leone SLE 2,244.995 2,387.706 –6.0 27,610.8 27,614.7 0.0 South Africa ZAF 6.427 6.075 5.8 4,715.2 4,653.6 1.3 Sudan SDN 4.619 4.129 11.9 815.9 822.4 –0.8 Tanzania TZA 885.083 724.689 22.1 110,651.1 118,844.1 –6.9 Togo TGO 239.722 214.920 11.5 2,689.4 2,798.7 –3.9 Ugandag UGA 1,270.608 1,145.394 10.9 116,251.5 91,718.3 26.7 Zambia ZMB 4.193 3.572 17.4 237.0 246.3 –3.8 Zimbabwe ZWE 0.511 0.567 –9.8 18.6 22.8 –18.3 Total (45) SSB n.a. n.a. n.a. n.a. n.a. n.a. World (176) WLD n.a. n.a. n.a. n.a. n.a. n.a. Note: PPP = purchasing power parity; WDI = World Development Indicators; n.a. = not applicable; ... = data suppressed due to unavailability. a. Data source: WDI (World Bank) [data as of February 2020]. b. WDI obtains PPP data from the Eurostat-Organisation for the Economic Co-operation and Development (OECD) PPP programme directly. Hence, data for economies participating in that programme are not based on the WDI extrapolation method. ­ c. Totals for the regions and the world are not provided due to differences in the availability of data for economies between the ICP and WDI. d. Bonaire’s results are provided only for individual consumption expenditure by households. e. Argentina and Guyana did not participate in ICP 2011. WDI’s extrapolation is based on imputed PPPs for 2011. f. WDI data were released in a different currency unit and were converted to the same currency unit as ICP 2017 in this table for comparison purposes. g. For WDI the economy reports national accounts data for its fiscal year. 172    Purchasing Power Parities and the Size of World Economies Table F.2  Individual consumption expenditure by households: Comparison of ICP 2017 results with data in World Development Indicators PPP (US$ = 1.000) Expenditure in local currency unit (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLS 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c East Asia and Pacific Australiaf AUS 1.529 1.538 –0.6 1,020.8 1,000.2 2.1 Brunei Darussalam BRN 0.697 0.769 –9.4 3.4 3.4 0.0 Cambodia KHM 1,488.798 1,655.539 –10.1 72,193.8 65,927.9 9.5 China CHN 4.147 3.827 8.4 30,964.1 31,796.4 –2.6 Fiji FJI 0.986 1.300 –24.1 7.5 ... ... Hong Kong SAR, China HKG 6.242 6.408 –2.6 1,785.5 1,785.5 0.0 Indonesia IDN 5,089.686 5,067.604 0.4 7,788,168.4 7,788,168.4 0.0 Japan JPN 113.023 108.572 4.1 302,490.5 302,490.5 0.0 Korea, Rep. KOR 974.206 962.003 1.3 872,791.4 832,234.7 4.9 Lao PDR LAO 3,133.812 3,204.507 –2.2 76,447.5 ... ... Malaysia MYS 1.727 1.687 2.4 748.9 759.7 –1.4 Mongolia MNG 873.542 853.487 2.3 14,922.2 14,922.2 0.0 Myanmarf MMR 389.843 348.525 11.9 48,963.3 ... ... New Zealand NZL 1.573 1.605 –2.0 162.7 164.1 –0.9 Philippines PHL 19.393 19.882 –2.5 11,614.1 11,614.1 0.0 Singapore SGP 1.080 1.156 –6.6 167.8 166.5 0.8 Taiwan, China TWN 16.598 ... ... 9,265.1 ... ... Thailand THA 13.287 12.636 5.2 7,378.1 7,529.4 –2.0 Vietnam VNM 7,807.612 9,186.042 –15.0 2,957,279.8 3,405,750.0 –13.2 Total (19) EAB n.a. n.a. n.a. n.a. n.a. n.a. Europe and Central Asia Albania ALB 50.357 51.847 –2.9 1,237.1 1,237.1 0.0 Armenia ARM 167.312 194.589 –14.0 4,453.3 4,453.3 0.0 Austria AUT 0.831 0.840 –1.1 193.3 193.3 0.0 Azerbaijan AZE 0.487 0.419 16.2 40.5 40.5 0.0 Belarus BLR 0.617 0.504 22.4 57.6 57.6 0.0 Belgium BEL 0.845 0.857 –1.4 229.5 229.5 0.0 Bosnia and Herzegovina BIH 0.782 0.789 –0.9 24.7 24.5 0.8 Bulgaria BGR 0.735 0.752 –2.2 61.5 61.5 0.0 Croatia HRV 3.815 3.902 –2.2 212.8 212.8 0.0 Cyprus CYP 0.668 0.694 –3.7 13.1 13.1 0.0 Czech Republic CZE 13.651 13.892 –1.7 2,393.2 2,393.2 0.0 Denmark DNK 7.891 7.990 –1.2 1,012.1 1,012.1 0.0 Estonia EST 0.596 0.604 –1.3 12.0 12.0 0.0 Finland FIN 0.933 0.947 –1.4 120.2 120.2 0.0 France FRA 0.835 0.847 –1.3 1,239.5 1,239.5 0.0 Georgia GEO 0.925 0.884 4.6 28.5 28.5 0.0 Germany DEU 0.787 0.805 –2.2 1,697.0 1,697.0 0.0 Greece GRC 0.646 0.661 –2.2 123.8 123.8 0.0 Hungary HUN 147.377 150.736 –2.2 19,232.5 19,232.5 0.0 (continued) Comparison of ICP 2017 results with World Development Indicators data 173 Table F.2  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLS 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c Iceland ISL 155.648 154.881 0.5 1,317.5 1,317.5 0.0 Ireland IRL 0.971 0.984 –1.3 95.6 95.6 0.0 Italy ITA 0.767 0.780 –1.7 1,046.8 1,046.8 0.0 Kazakhstan KAZ 125.263 119.764 4.6 28,596.7 27,584.3 3.7 Kyrgyz Republic KGZ 19.373 20.917 –7.4 435.4 435.4 0.0 Latvia LVA 0.554 0.564 –1.9 16.0 16.0 0.0 Lithuania LTU 0.488 0.500 –2.4 26.3 26.3 0.0 Luxembourg LUX 0.966 0.974 –0.8 16.9 16.9 0.0 Moldova MDA 6.383 7.147 –10.7 153.2 153.2 0.0 Montenegro MNE 0.419 0.431 –2.9 3.2 3.2 0.0 Netherlands NLD 0.850 0.867 –2.0 327.3 327.3 0.0 North Macedonia MKD 22.167 22.861 –3.0 412.0 406.3 1.4 Norway NOR 10.743 10.784 –0.4 1,471.7 1,471.7 0.0 Poland POL 1.842 1.866 –1.2 1,160.2 1,160.2 0.0 Portugal PRT 0.657 0.665 –1.1 126.5 126.5 0.0 Romania ROU 1.805 1.864 –3.2 540.4 540.4 0.0 Russian Federation RUS 25.218 26.183 –3.7 48,516.2 48,516.3 0.0 Serbia SRB 47.992 48.851 –1.8 3,367.5 3,367.5 0.0 Slovak Republic SVK 0.579 0.540 7.3 47.2 47.2 0.0 Slovenia SVN 0.639 0.648 –1.4 22.6 22.6 0.0 Spain ESP 0.703 0.715 –1.7 678.2 678.2 0.0 Sweden SWE 9.223 9.353 –1.4 2,077.2 2,077.2 0.0 Switzerland CHE 1.359 1.375 –1.2 359.6 359.6 0.0 Tajikistan TJK 2.595 ... ... 47.5 50.4 –5.8 Turkey TUR 1.647 1.681 –2.0 1,836.2 1,836.2 0.0 Ukraine UKR 7.006 6.623 5.8 2,001.5 2,001.5 0.0 United Kingdom GBR 0.780 0.789 –1.2 1,346.9 1,346.9 0.0 Total (46) ECB n.a. n.a. n.a. n.a. n.a. n.a. Latin America and the Caribbean Anguilla AIA 2.595 ... ... 0.6 ... ... Antigua and Barbuda ATG 2.468 2.194 12.5 1.7 ... ... Argentinae ARG 10.808 ... ... 7,295.3 7,059.0 3.3 Aruba ABW 1.480 1.483 –0.2 3.3 2.7 ... Bahamas, The BHS 1.103 1.135 –2.8 7.7 8.2 –6.1 Barbados BRB 2.371 2.514 –5.7 6.7 6.3 7.5 Belize BLZ 1.477 ... ... 2.6 2.6 1.2 Bolivia BOL 2.612 3.456 –24.4 175.3 175.3 0.0 Bonaire BON 0.812 ... ... 0.2 ... ... Brazil BRA 2.327 2.222 4.7 4,245.1 4,193.9 1.2 Cayman Islands CYM 1.150 ... ... 2.3 ... ... Chile CHL 478.996 461.246 3.8 113,565.7 113,565.7 0.0 Colombia COL 1,419.374 1,400.684 1.3 630,818.0 630,818.0 0.0 174    Purchasing Power Parities and the Size of World Economies Table F.2  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLS 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c Costa Rica CRI 372.669 371.372 0.3 22,319.8 21,079.1 5.9 Curaçao CUW 1.483 1.407 5.4 3.5 ... ... Dominica DMA 1.876 1.931 –2.8 1.2 ... ... Dominican Republic DOM 24.391 22.552 8.2 2,641.0 2,641.0 0.0 Ecuador ECU 0.575 0.596 –3.7 62.5 62.5 0.0 El Salvador SLV 0.515 0.509 1.1 20.8 20.8 0.0 Grenada GRD 1.800 1.985 –9.4 2.7 ... ... Guyanad GUY 115.626 130.906 –11.7 469.7 498.5 –5.8 Haitif HTI 31.103 28.483 9.2 561.6 526.9 6.6 Honduras HND 10.839 11.962 –9.4 417.4 416.0 0.3 Jamaica JAM 70.392 81.506 –13.6 1,490.0 1,483.5 0.4 Mexico MEX 9.861 10.172 –3.0 14,301.2 14,301.2 0.0 Montserrat MSR 2.118 ... ... 0.1 ... ... Nicaragua NIC 11.528 11.445 0.7 294.9 294.9 0.0 Panama PAN 0.508 0.583 –12.9 31.3 31.3 0.0 Paraguay PRY 2,539.985 2,635.282 –3.6 140,077.6 140,077.6 0.0 Peru PER 1.894 1.747 8.4 441.3 441.3 0.0 Sint Maarten SXM 1.488 1.717 –13.3 1.3 ... ... St. Kitts and Nevis KNA 2.547 2.034 25.2 1.7 ... ... St. Lucia LCA 2.079 2.064 0.8 1.6 ... ... St. Vincent and the Grenadines VCT 1.807 1.944 –7.0 1.7 1.7 0.0 Suriname SUR 2.934 3.879 –24.3 12.4 ... ... Trinidad and Tobago TTO 4.212 5.659 –25.6 98.1 ... ... Turks and Caicos Islands TCA 1.246 ... ... 0.4 ... ... Uruguay URY 24.854 24.373 2.0 1,147.3 1,147.3 0.0 Virgin Islands, British VGB 1.096 ... ... 0.5 ... ... Total (39) LCB n.a. n.a. n.a. n.a. n.a. n.a. Middle East and North Africa Algeria DZA 38.210 39.717 –3.8 8,071.9 8,034.2 0.5 Bahrain BHR 0.204 0.229 –10.7 5.6 5.6 0.0 Djibouti DJI 104.737 103.006 1.7 334.8 306.3 9.3 Egypt, Arab Rep.f EGY 3.408 3.474 –1.9 3,623.5 3,057.9 18.5 Iran, Islamic Rep.f IRN 13,944.904 12,800.390 8.9 8,104,686.7 7,294,401.0 11.1 Iraq IRQ 555.391 593.934 –6.5 114,058.4 136,377.3 –16.4 Israel ISR 4.207 4.237 –0.7 695.0 695.0 0.0 Jordan JOR 0.329 0.336 –1.9 24.9 25.0 –0.4 Kuwait KWT 0.187 0.197 –4.7 15.0 15.9 –5.7 Malta MLT 0.628 0.633 –0.8 5.0 5.0 0.0 Morocco MAR 4.291 4.148 3.4 615.9 615.9 0.0 Oman OMN 0.212 0.198 6.7 11.3 11.9 –5.1 Qatar QAT 2.893 2.776 4.2 149.4 149.5 –0.1 Saudi Arabia SAU 1.724 1.827 –5.7 1,070.8 1,063.6 0.7 (continued) Comparison of ICP 2017 results with World Development Indicators data 175 Table F.2  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLS 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c Tunisia TUN 0.742 0.840 –11.6 69.6 69.5 0.1 United Arab Emirates ARE 2.835 2.802 1.2 513.4 513.4 0.0 West Bank and Gaza PSE 2.066 2.497 –17.3 45.9 ... ... Total (17) MEB n.a. n.a. n.a. n.a. n.a. n.a. North America               Bermuda BMU 1.576 ... ... 3.3 ... ... Canada CAN 1.287 1.340 –4.0 1,221.6 1,240.4 –1.5 United States USA 1.000 1.000 0.0 13,312.1 13,312.1 0.0 Total (3) NAB n.a. n.a. n.a. n.a. n.a. n.a. South Asia Bangladeshf BGD 29.514 33.004 –10.6 14,751.8 13,568.9 8.7 Bhutan BTN 20.474 22.657 –9.6 86.9 86.0 1.0 Indiaf IND 19.469 20.177 –3.5 97,813.2 100,831.2 –3.0 Maldives MDV 9.794 12.013 –18.5 29.8 ... ... Nepalf NPL 30.513 ... ... 2,002.9 2,015.4 –0.6 Pakistanf PAK 33.251 32.698 1.7 27,355.3 26,148.6 4.6 Sri Lanka LKA 55.501 53.400 3.9 8,262.7 9,382.5 –11.9 Total (7) SAB n.a. n.a. n.a. n.a. n.a. n.a. Sub-Saharan Africa Angola AGO 107.270 167.629 –36.0 11,898.4 11,586.5 2.7 Benin BEN 219.476 218.948 0.2 3,964.4 4,096.3 –3.2 Botswana BWA 5.009 5.300 –5.5 88.8 88.7 0.1 Burkina Faso BFA 199.741 214.588 –6.9 4,173.7 3,952.8 5.6 Burundi BDI 654.422 769.945 –15.0 4,781.8 4,184.8 14.3 Cabo Verde CPV 47.612 45.095 5.6 109.2 112.9 –3.3 Cameroon CMR 236.912 235.321 0.7 14,169.0 14,220.3 –0.4 Central African Republic CAF 306.808 ... ... 1,113.8 998.2 11.6 Chad TCD 237.656 ... ... 4,484.7 4,654.9 –3.7 Comoros COM 213.518 ... ... 434.7 432.2 0.6 Congo, Dem. Rep. COD 630.606 ... ... 46,322.8 40,491.2 14.4 Congo, Rep. COG 285.969 322.619 –11.4 3,022.7 1,870.9 61.6 Côte d’Ivoire CIV 247.134 231.827 6.6 14,550.6 14,550.6 0.0 Equatorial Guinea GNQ 304.287 340.998 –10.8 3,326.9 3,326.9 0.0 Eswatini SWZ 6.118 5.432 12.6 46.3 38.8 19.2 Ethiopiaf ETH 8.496 9.330 –8.9 1,058.1 1,219.4 –13.2 Gabon GAB 319.160 371.897 –14.2 3,211.8 3,464.9 –7.3 Gambia, The GMB 15.114 14.352 5.3 60.0 61.4 –2.3 Ghana GHA 1.751 1.545 13.4 186.6 180.2 3.6 Guinea GIN 3,213.984 4,254.455 –24.5 82,442.7 69,410.5 18.8 Guinea-Bissau GNB 232.199 242.123 –4.1 654.9 682.1 –4.0 Kenya KEN 41.635 49.167 –15.3 6,196.5 6,645.2 –6.8 Lesotho LSO 5.244 4.819 8.8 28.0 27.1 3.0 176    Purchasing Power Parities and the Size of World Economies Table F.2  (Continued) PPP (US$ = 1.000) Expenditure in local currency unit (billions) INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLS 2017 (WDI Percentage Percentage Economy 2017 extrapolation) difference 2017 2017 (WDI) difference (00) (01) (02)a, b (03)c (04) (05)a, b (06)c Liberiae LBR 47.996 97.738 –14.7 192.1 510.0 –15.9 Madagascar MDG 962.960 949.475 1.4 28,886.2 29,401.9 –1.8 Malawi MWI 241.931 226.339 6.9 3,989.0 3,687.7 8.2 Mali MLI 205.273 217.986 –5.8 6,986.4 6,666.1 4.8 Mauritaniae MRT 124.453 125.430 –0.8 988.6 1,035.1 –4.5 Mauritius MUS 18.009 19.747 –8.8 349.2 342.1 2.0 Mozambique MOZ 21.988 ... ... 572.3 544.0 5.2 Namibia NAM 6.898 6.548 5.4 124.4 124.4 0.0 Niger NER 245.160 222.036 10.4 3,129.6 3,158.5 –0.9 Nigeria NGA 112.098 141.063 –20.5 79,505.3 92,065.1 –13.6 Rwanda RWA 293.705 322.184 –8.8 5,195.5 5,737.3 –9.4 São Tomé and Príncipe STP 10.757 14.041 –23.4 6.7 ... ... Senegal SEN 238.578 233.419 2.2 8,550.5 8,843.2 –3.3 Seychelles SYC 9.027 8.696 3.8 12.0 12.0 0.0 Sierra Leone SLE 2,128.519 2,669.458 –20.3 27,172.5 25,703.9 5.7 South Africa ZAF 6.549 6.467 1.3 2,812.5 2,756.5 2.0 Sudan SDN 5.377 ... ... 715.4 603.0 18.6 Tanzania TZA 754.621 834.588 –9.6 71,675.1 70,646.7 1.5 Togo TGO 246.596 229.434 7.5 1,929.5 1,904.7 1.3 Ugandaf UGA 1,221.088 1,243.113 –1.8 82,956.1 68,364.0 21.3 Zambia ZMB 4.224 3.909 8.1 115.7 ... ... Zimbabwe ZWE 0.485 0.502 –3.3 14.1 17.5 –19.4 Total (45) SSB n.a. n.a. n.a. n.a. n.a. n.a. World (176) WLD n.a. n.a. n.a. n.a. n.a. n.a. Note: PPP = purchasing power parity; WDI = World Development Indicators; n.a. = not applicable; ... = data suppressed due to unavailability. a. Data source: WDI (World Bank) [data as of February 2020]. b. WDI obtains PPP data from the Eurostat-Organisation for the Economic Co-operation and Development (OECD) PPP programme directly. Hence, data for economies participating in that programme are not based on the WDI extrapolation method. ­ c. Totals for the regions and the world are not provided due to differences in the availability of data for economies between the ICP and WDI. d. Argentina and Guyana did not participate in ICP 2011. WDI’s extrapolation is based on imputed PPPs for 2011. e. WDI data were released in a different currency unit and were converted to the same currency unit as ICP 2017 in this table for comparison purposes. f. For WDI the economy reports national accounts data for its fiscal year. Comparison of ICP 2017 results with World Development Indicators data 177 APPENDIX G ICP research agenda Over the last 50 years, the International Com- Component 3: Compiling annual PPPs for parison Program (ICP) has recorded many sig- the interim period nificant achievements, including establishing an   2.  PPPs and real expenditures for dwelling effective partnership and an efficient governance services structure for the ICP; designing survey instru- ments for price collection; developing methods   3.  Productivity adjustment for government dealing with comparison-resistant services, such and construction labor as housing, health, and education; and identify-   4.  Fine-tuning global linking procedures ing multilateral index number methods suitable for international comparisons of prices and real   5.  Quality and reliability of PPPs expenditures. Notwithstanding the impressive Component 1: Quality of data progress made, the ICP continues to strive for improvement and refinements in its approach, Component 2: Reliability measures for PPPs with the goal of providing reliable and timely   6.  Uses of PPPs for national and international estimates of purchasing power parities (PPPs) policy making and real expenditures. This appendix lists the main components of   7.  Consumer price index (CPI)–ICP synergies the ICP research agenda (World Bank 2017) and subnational PPPs which was proposed by the ICP’s Technical Advi-   8.  PPPs for exports and imports sory Group (TAG) in May 2017 and subsequently adopted by the ICP’s Governing Board in Sep-  9.  PPPs for construction tember 2017. The agenda comprises 13 research 10.  PPPs for health and education items and focuses on improving the methodology and approaches underlying the ICP: 11.  ICP PPPs and global poverty measurement   1.  Compilation of annual PPPs and the rolling 12.  Exploring innovations in technology and survey approach data sources for PPP measurement Component 1: Moving toward rolling price 13.  Accounting for item quality differences in surveys PPP measurement. Component 2: Linking interim regional  Throughout the ICP 2017 cycle, research has updates into a global comparison been carried out on moving toward the use of 179 rolling price surveys; linking interim regional as well as PPPs and real expenditures for dwell- updates into a global comparison; compiling ing services. Experts will also investigate and annual PPPs for the interim period; constructing make recommendations on the use of PPPs in PPPs and real expenditures for dwelling services; global poverty measurement and, more broadly, addressing productivity adjustment for govern- in national and international policy making. ment and construction labor; fine-tuning global Other research agenda items, such as PPPs for linking procedures; assessing the quality of data exports and imports and exploring innovations and results; and providing guidance on CPI-ICP in technology and data sources for PPP measure- synergies and subnational PPPs. ment, will be taken forward starting in ICP 2021. Further research in the immediate future will continue to examine global linking procedures 180    Purchasing Power Parities and the Size of World Economies APPENDIX H ICP data access and archive policy This appendix outlines the objectives, guiding was clear that the user community was pressing principles, and procedures for accessing and for greater access to more detailed data in sub- archiving International Comparison Program sequent ICP cycles. (ICP) data. The enhanced ICP data access and A total of 26 headings were published for archive policy (World Bank 2019a) was endorsed the ICP 2011 cycle.3 In response to mounting by the ICP Governing Board in December 2019 user demands for more detailed data, the ICP and provides full details of the data and meta- Executive Board endorsed the 2011 ICP data data covered by this policy and the relevant access and archive policy (World Bank 2012), access and archive processes. which improved access to include national aver- age prices at the item level for all participating economies, while respecting confidentiality con- straints and data-quality limitations. To improve Background the quality and increase the utility of the data The ICP entails a large price data collection collected, the ICP 2011 cycle also focused on and detailed national accounts expenditure collecting, archiving, and providing access to data compilation for participating economies. metadata. Moreover, throughout the course Its main outputs are indicators on purchasing of the ICP 2011 cycle, calls for greater govern- power parities (PPPs), price level indexes (PLIs), ment transparency and accountability through and real and per capita real expenditures in the open-data movement gained traction. These international dollars for various headings under open-data initiatives aimed to improve the avail- the ICP classification of final expenditure on ability and reuse of data. gross domestic product (GDP).1 Furthermore, the Statistical Office of the The published data for the ICP 2005 cycle2 European Union (Eurostat)4 and the Organisa- was restricted to main aggregates and catego- tion for Economic Co-operation and Develop- ries, with some additional aggregates—a total ment (OECD)5 publish their respective results of 24 headings. The 2005 ICP data access and at a finer level of detail than the ICP, covering archive policy (World Bank 2008b) strongly 61 and 50 headings, respectively. The Com- limited access to unpublished detailed price monwealth of Independent States (CIS)6 has and expenditure data: users were able to access published its 2014 results at a similar level of basic-heading level data and a limited set of detail as the OECD. national average prices at the item level for the Recognizing that inadequate access to 18 economies that participated in the global under­­lying ICP data inhibits research and pol- linking exercise. By the end of the 2005 cycle, it icy development and restricts feedback about 181 quality, the United Nations Statistical Commis-  2.  PPPs, PLIs, and expenditure data at various sion Friends of the Chair (FOC) evaluation of levels of detail below the publication level the 2011 ICP (ECOSOC 2016) noted the need for all economies, with supporting meta- “to reach out and demonstrate the value of data, are available to users through a formal ICP data to policy makers and other important application. users and donors, in particular showcasing to  3.  National average price data at the item level donors that the ICP generally responds to user for items on the global core lists for all econo- needs and strives for further openness with mies, with supporting metadata and mea- regard to access to data and metadata.” The sures of quality, are available to users through evaluation concluded by recommending that a formal application, except when the confi- “the Governing Board establish policies that dentiality of respondents is jeopardized. improve openness with regard to access to ICP data and metadata.”  4.  National average price data at the item level for regional items not on the global core lists for all economies, with supporting metadata Data access objectives and measures of quality, are available to The long-standing objective of the ICP data users through a formal application, except access and archive policy is as follows: Data when the confidentiality of respondents is derived from the ICP should be utilized to the maxi- jeopardized. mum extent possible for statistical, research, and ana- Individual price observations and subnational8  5.  lytical purposes. To enhance data access per the average prices with supporting metadata are FOC’s recommendation, the current policy has available to users where permitted by the two overall objectives: laws of individual economies, as long as the • Objective 1. To provide users with more confidentiality of respondents is protected.9 detailed results beyond what was published through the 2005 and 2011 ICP, the number of published headings such as groups and Guiding principles classes will be increased where feasible to a The following principles guide the management level agreed-on by the ICP Global Office and of ICP data and support the objective of enhanc- regional implementing agencies, as delegated ing data access: by the ICP Governing Board, taking into con- sideration the quality, availability, and confi-  1.  Appropriate use. ICP data should be made dentiality of data.7 available for analytical, research, and statis- tical purposes. Users should not misuse the • Objective 2. To enable in-depth policy analyses data by attempting to deduce underlying on specific fields of studies, user access to confidential data. unpublished data at a finer level of detail will be expanded, where feasible. To this latter  2.  Equality of access. ICP data are global public point, national implementing agencies may goods and should be made available on an voluntarily provide access to subnational equal basis to anyone who wants to use average prices and individual price observa- them, in the same way that most national tions, where applicable and permitted by statistical offices make data available to users. national law.  3.  Preservation of respondent confidentiality. Provi- The policy also has five detailed objectives, sion of ICP data should be consistent with reflecting enhanced publication and access: legal and other necessary arrangements that ensure the confidentiality of respondents.  1.  PPPs, PLIs, and expenditure data for all economies are disseminated in ICP publica-   4.  Transparency. The principles and procedures tions and through an ICP-dedicated online for access to ICP data, as well as the applica- database at the agreed-on publication level, tions of these data, should be transparent with supporting metadata. and publicly available. 182    Purchasing Power Parities and the Size of World Economies   5.  Consistency. The principles and procedures Procedures for archiving data for data access should strive to be consistent across all regions and economies to promote This section describes the procedures for equality in the treatment of all economies. archiving ICP data and metadata.   6.  Reciprocity. Reciprocity between participat-   1.  PPPs, PLIs, and expenditure data for all econo- ing economies should be established to the mies are disseminated at the agreed-on publica- maximum extent possible. All ICP national tion level, with supporting metadata. They are implementing agencies are automatically archived by the ICP Global Office and by the considered approved users of ICP data. Non- relevant regional implementing agencies. participating economies are not considered   2.  PPPs, PLIs, and expenditure data at various approved users of ICP data but may apply levels of detail below the publication level for all for access to these data following the proce- economies, with supporting metadata, are dures stipulated later in this appendix. archived by the ICP Global Office and by the   7. Reliability. Releases of ICP data should be relevant regional implementing agencies. accompanied by appropriate metadata,   3.  National and subnational average price data at including metadata describing the quality the item level for items on the global core lists for limitations of the data. all economies, with supporting metadata   8.  Quality limitations. Users of ICP data should and measures of quality, are archived by be informed of the data’s quality limitations, the ICP Global Office and by the relevant and they should agree that the data are still regional implementing agencies. useful for their purposes.   4.  National and subnational average price data at   9.  Serviceability. The ICP data should be archived the item level for regional items not on the global to ensure that they can be used to service core lists for all economies, with support- future approved requests for access to data, ing metadata and measures of quality, are that they are available for possible use in archived by the ICP Global Office and by the future ICP comparisons, and that they are relevant regional implementing agencies. available as a backup in case these data are lost through disaster or other reasons by a   5.  Individual price observations and subnational region or an economy. average price data, with supporting meta- data, are archived by national implementing 10.  Disclosure limitations. Users accessing unpub- agencies. However, some national imple- lished ICP data should not disseminate menting agencies may request that the ICP these data. Global Office or relevant regional imple- 11.  Promotion of uses. To promote the use of menting agency archive the individual price ICP data, users are required to share their observations and subnational average price research findings with the ICP Global Office, because they do not have their own facilities consistent with the disclosure limitations in to archive these data. If an economy asks the this policy. The ICP Global Office will, in ICP Global Office or relevant regional imple- turn, share these research findings with ICP menting agency to archive these data, the stakeholders. economy in question can choose to have the data encrypted and hold the encryption key. 12.  Limitations on users’ findings. Indicators com- puted by users based on ICP data are not The unpublished data archived by the ICP considered part of the official results of the Global Office will be treated with confidentiality. ICP. The data will be archived in a secure database 13.  Ease of access. Data access procedures should with limited access rights and administered by a ensure a simple and expedited process for designated data custodian. Access to the data (or accessing ICP data, while safeguarding the any portions of the data) will be subject to the confidentiality of unpublished data. procedures specified next. ICP data access and archive policy 183 Procedures for accessing data laws of individual economies, as long as the confidentiality of respondents is protected. This section describes the procedures for access- Users may submit a formal application of ing ICP data and metadata: access to these data to the national imple- 1.  PPPs, PLIs, and expenditure data for all economies menting agency, either directly or through at the agreed-on publication level, with support- the ICP Global Office or relevant regional ing metadata, will be disseminated in ICP implementing agency. publications and through an ICP-dedicated online database. Users apply for access to the ICP data sets by submitting a formal application and a signed 2.  PPPs, PLIs, and expenditure data at various declaration of use addressed to the ICP Global levels of detail below the publication level for Office.10 The ICP Global Office decides whether all economies, with supporting metadata, to approve requests, in line with the access pol- can be accessed by users through a for- icy approved by the ICP Governing Board and mal online application addressed to the ICP outlined in this document. Once the ICP Global Global Office. Office approves the formal data access request, it 3.  National average price data at the item level for notifies the requesting user(s) and grants secure items on the global core lists for all economies, online access to a custom confidential data with supporting metadata and measures of set containing the data requested. Such access quality, can be accessed by users through requires two-factor authentication, an approach a formal application addressed to the ICP that provides an additional layer of security. Global Office, consistent with the confiden- Alternatively, users may approach relevant tiality laws and processes of participating regional implementing agencies for access to economies. National implementing agencies regional data sets or relevant national imple- should inform the relevant regional imple- menting agencies for access to national data sets. menting agencies, which, in turn, will inform In these cases, regional and national implement- the ICP Global Office, which information is ing agencies will follow the access policy agreed considered confidential and hence cannot be by the ICP Governing Board. Access to regional shared. Item brands and models will be ano- and national data sets does not require clearance nymized before sharing with users. from the ICP Global Office. 4.  National average price data at the item level for regional items not on the global core lists for all Notes economies, with supporting metadata and  1. See icp.worldbank.org/programs/icp#6. measures of quality, can be accessed by users  2. See icp.worldbank.org/en/programs/icp#5. through a formal application addressed to the  3. See icp.worldbank.org/en/programs/icp#5. ICP Global Office, consistent with the confi-  4. S ee https://ec.europa.eu/eurostat/web dentiality laws and processes of participating /purchasing-power-parities/data/database. economies. National implementing agencies   5. See http://www.oecd.org/sdd/prices-ppp/. should inform the relevant regional imple-  6. See http://www.cisstat.org/icp/. menting agencies, which, in turn, will inform  7. The headings included in each published the ICP Global Office, which information is ICP data set will be listed on the ICP website. considered confidential and hence cannot be Capital city or first-level administrative divi-   8.  shared. Item brands and models will be ano- sions within an economy (for example, nymized before sharing with users. states, provinces). 5.  Individual price observations and subnational  9. For example, through data anonymization average price data, with supporting metadata, techniques. are available to users where permitted by the 10. See Annex 4 of World Bank (2019a). 184    Purchasing Power Parities and the Size of World Economies APPENDIX I ICP revision policy This appendix describes the International Com- the World Bank’s Databank3 and Data Catalog;4 parison Program (ICP) revision policy (World indicators using ICP data are included in World Bank 2019b) endorsed by the ICP Governing Development Indicators.5 Additional unpub- Board in December 2019. It sets out the trig- lished results and data are available to users gers and procedures for revising previously upon application to the ICP Global Office.6 published and unpublished results from the ICP to ensure that the program’s outputs reflect the latest available information and methodologies, Triggers for revising ICP indicators are of the highest quality, and remain relevant to users. It describes the timing of revisions and The triggers prompting revisions of ICP data the steps to be taken to communicate these revi- include revisions or changes in input data and sions to users. changes in methodology. Revisions and changes in input data Background • Revisions in the GDP estimate trigger a The ICP’s main outputs are indicators on pur- revision of real and per capita real expendi- chasing power parities (PPPs), price level indexes tures and nominal and per capita nominal (PLIs), and real and per capita real expenditures expenditures. in international dollars for various headings • Revisions in the national accounts expendi- under the ICP classification of final expenditure ture components (that is, national accounts on gross domestic product (GDP).1 structure) trigger a revision of real and per The ICP publishes full data sets for reference capita real expenditures and nominal and per years, such as 2011 and 2017. Annual PPPs capita nominal expenditures. They may also for nonreference years are estimated through trigger a revision of PPPs and PLIs. retropolation, interpolation, and extrapolation using consumer price index (CPI) and national • Revisions in population figures trigger a revi- accounts deflator time series. The ICP classifica- sion of per capita real expenditures and per tion level at which these results are published is capita nominal expenditures. determined by the ICP data access and archive • Revisions to CPI and national accounts defla- policy, described in appendix H. tor time series trigger a revision of annual ICP-published results are available through PPPs and PLIs and of real and per capita real various portals, including the ICP website2 and expenditures. 185 • Changes in economies’ currency units trigger • Historical revisions based on new methodolo- a revision of real and per capita real expendi- gies are subject to the feasibility of introduc- tures, PPPs, PLIs, and nominal and per capita ing the new methodology retrospectively, nominal expenditures. based on the availability and limitations of • Correction of errors in source data or results input data. may trigger a revision of PPPs and PLIs, real and per capita real expenditures, and nomi- Geographic scope nal and per capita nominal expenditures. • Revisions of regional data should precede revisions of global data in order to preserve New methodology the consistency between regional and global • Significantly improved PPP computation and data sets. aggregation methods trigger a revision of real • Regional implementing agencies are respon- and per capita real expenditures, PPPs, and sible for revising reference-year indicators PLIs. and associated interpolated annual indicators • A significantly improved global linking at the regional level, and the ICP Global Office approach triggers a revision of real and per is responsible for revising reference-year indi- capita real expenditures, PPPs, and PLIs. cators and interpolated annual indicators at • A significantly improved retropolation, inter- the global level (that is, denominated in the polation, and extrapolation method triggers a global numeraire). revision of annual PPPs and PLIs and real and • Revised global reference-year results should per capita real expenditures. respect, to the extent possible, regional fix- • A revision to the System of National Accounts ity—the convention whereby the price rela- (SNA) or the Classification of Individual tivities established between economies in Consumption According to Purpose (COICOP) a regional comparison are retained when may trigger a change in the ICP Classification the economies are included in the global of final expenditure on GDP. comparison. This appendix summarizes these triggers and subsequent revisions. Categories of indicators • PPPs and PLIs may be revised depending on the level of detail of the revisions of the Guidelines for revising ICP national accounts expenditure structure or indicators a change in the ICP classification of final Revisions of ICP results should be made infre- expenditure on GDP. When economies revise quently and should adhere to the following their expenditure data for major compo- guidelines. nents, categories, groups, classes, or basic headings, then PPPs (and resulting PLIs) may be revised at levels above the lowest level Historical revisions for which expenditures were revised. These • Revisions to historical input data from econo- revisions are introduced in conjunction with mies may trigger a revision to ICP results. the release of new reference-year results and These revisions will be limited to the period are limited to the PPPs and PLIs from the of revisions to the input data. For example, previous reference-year exercise only. These retrospective revisions of an economy’s GDP revisions will, in turn, trigger a revision in the from 2012 to 2019 would trigger a revision time series of PPPs and PLIs for nonreference of the real and per capita real expenditures years. Annual PPPs and PLIs for nonreference for that period only; 2011 results would not years may also be revised if CPI and national be revised. accounts deflator time series are revised. 186    Purchasing Power Parities and the Size of World Economies • Real and per capita real expenditures are revised revised to maintain consistency between the when national accounts expenditure data or published and unpublished data sets. population data are revised. These revisions are introduced on an annual basis. • Nominal and per capita nominal expenditures are Timing and communication of revised when national accounts expenditure revisions data or population data are revised. These revisions are introduced on an annual basis. • Revisions to real and per capita real expen- ditures and nominal and per capita nomi- nal expenditures, triggered by revisions of Quality review national accounts expenditure and popula- • Revised ICP data will be subject to an expert tion data, will be introduced on an annual review before they are published, to ensure basis. Revisions to PPPs and PLIs will be intro- data quality. duced in conjunction with the release of new reference-year results and be limited to the Publication of revised results PPPs and PLIs from the previous reference- year exercise and interpolated annual PPPs • Revised ICP indicators will be published once and PLIs for nonreference years. they have been compiled and undergone the quality review process. • The schedule of revisions will be announced to stakeholders and users well in advance. • Revised ICP indicators will be released at the publication level of the reference-year • When methodology is improved, the new results, as established by the ICP data access methods will be communicated to users well and archive policy. in advance. • The ICP Global Office will archive the various • Results will be made publicly available on the vintages of the data. ICP website, the World Bank’s Databank and Data Catalog, World Development Indicators, and other relevant websites. Consistency between published and unpublished data sets • The ICP Global Office can make available to Notes researchers a detailed data set, as stipulated in the ICP data access and archive policy. 1.  See icp.worldbank.org/programs/#6. This data set includes real and per capita real 2.  See icp.worldbank.org/programs/icp#5. expenditures, PPPs and PLIs, and nominal 3. See databank.worldbank.org. and per capita nominal expenditures at all 4. See datacatalog.worldbank.org. classification levels, as well as average prices. 5. See http://datatopics.worldbank.org/world When revising published ICP indicators, this -development-indicators/. unpublished detailed data set may need to be 6.  See Annex 4 of World Bank (2019a). ICP revision policy 187 APPENDIX J Classification of the world’s economies The World Bank classifies its member coun- $12,376 or more. More information is available tries and 28 other economies with populations from the World Bank’s Data Help Desk.1 of more than 30,000 by geographic region Three ICP participating economies (Anguilla, and income group. The four current income Bonaire, and Monserrat) are not classified by groups are defined using gross national income income group because their populations are (GNI) per capita, in US dollars, converted from below the 30,000 threshold. While the World local currency using the World Bank Atlas Bank does not assign them to a region for this method. For the 2020 fiscal year, low-income same reason, they are included in the Latin economies are defined as those with a GNI per America and the Caribbean region in this report. capita of $1,025 or less in 2018; lower-middle income economies are those with GNI per cap- ita between $1,026 and $3,995; upper-middle Note income economies are those with GNI per capita 1. See https://datahelpdesk.worldbank.org between $3,996 and $12,375; and high-income /knowledgebase/articles/906519-world-bank economies are those with GNI per capita of -country-and-lending-groups. 189 Table J.1  Economies in East Asia and Pacific, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group ICP 2017 World Bank fiscal year 2020 Economy administrative region income group American Samoa Nonparticipating Upper middle income Australia Eurostat-OECD High income Brunei Darussalam Asia and the Pacific High income Cambodia Asia and the Pacific Lower middle income China Asia and the Pacific Upper middle income Cook Islands Nonparticipating Not classified Fiji Asia and the Pacific Upper middle income French Polynesia Nonparticipating High income Guam Nonparticipating High income Hong Kong SAR, China Asia and the Pacific High income Indonesia Asia and the Pacific Lower middle income Japan Eurostat-OECD High income Kiribati Nonparticipating Lower middle income Korea, Rep. Eurostat-OECD High income Lao PDR Asia and the Pacific Lower middle income Macao SAR, China Nonparticipating High income Malaysia Asia and the Pacific Upper middle income Marshall Islands Nonparticipating Upper middle income Micronesia, Fed. Sts. Nonparticipating Lower middle income Mongolia Asia and the Pacific Lower middle income Myanmar Asia and the Pacific Lower middle income Nauru Nonparticipating Upper middle income New Caledonia Nonparticipating High income New Zealand Eurostat-OECD High income Niue Nonparticipating Not classified Northern Mariana Islands Nonparticipating High income Palau Nonparticipating High income Papua New Guinea Nonparticipating Lower middle income Philippines Asia and the Pacific Lower middle income Samoa Nonparticipating Upper middle income Singapore Asia and the Pacific High income Solomon Islands Nonparticipating Lower middle income Taiwan, China Asia and the Pacific High income Thailand Asia and the Pacific Upper middle income Timor-Leste Nonparticipating Lower middle income Tokelau Nonparticipating Not classified Tonga Nonparticipating Upper middle income Tuvalu Nonparticipating Upper middle income Vanuatu Nonparticipating Lower middle income Vietnam Asia and the Pacific Lower middle income Wallis and Futuna Nonparticipating Not classified Note: ICP = International Comparison Program; OECD = Organisation for Economic Co-operation and Development. 190    Purchasing Power Parities and the Size of World Economies Table J.2  Economies in Europe and Central Asia, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group ICP 2017 World Bank fiscal year 2020 Economy administrative region income group Albania Eurostat-OECD Upper middle income Armenia CIS Upper middle income Austria Eurostat-OECD High income Azerbaijan CIS Upper middle income Belarus CIS Upper middle income Belgium Eurostat-OECD High income Bosnia and Herzegovina Eurostat-OECD Upper middle income Bulgaria Eurostat-OECD Upper middle income Croatia Eurostat-OECD High income Cyprus Eurostat-OECD High income Czech Republic Eurostat-OECD High income Denmark Eurostat-OECD High income Estonia Eurostat-OECD High income Finland Eurostat-OECD High income France Eurostat-OECD High income Georgia Special participation Upper middle income Germany Eurostat-OECD High income Greece Eurostat-OECD High income Hungary Eurostat-OECD High income Iceland Eurostat-OECD High income Ireland Eurostat-OECD High income Italy Eurostat-OECD High income Kazakhstan CIS Upper middle income Kosovo Nonparticipating Upper middle income Kyrgyz Republic CIS Lower middle income Latvia Eurostat-OECD High income Lithuania Eurostat-OECD High income Luxembourg Eurostat-OECD High income Moldova CIS Lower middle income Montenegro Eurostat-OECD Upper middle income Netherlands Eurostat-OECD High income North Macedonia Eurostat-OECD Upper middle income Norway Eurostat-OECD High income Poland Eurostat-OECD High income Portugal Eurostat-OECD High income Romania Eurostat-OECD Upper middle income Russian Federationa CIS/Eurostat-OECD Upper middle income San Marino Nonparticipating High income Serbia Eurostat-OECD Upper middle income Slovak Republic Eurostat-OECD High income Slovenia Eurostat-OECD High income Spain Eurostat-OECD High income Sweden Eurostat-OECD High income Switzerland Eurostat-OECD High income Tajikistan CIS Low income Turkey Eurostat-OECD Upper middle income Turkmenistan Nonparticipating Upper middle income Ukraine Special participation Lower middle income United Kingdom Eurostat-OECD High income Uzbekistan Experimental participation Lower middle income Note: CIS = Commonwealth of Independent States; ICP = International Comparison Program; OECD = Organisation for Economic Co-operation and Development. a. Indicates a dual-participation economy in ICP 2017. Classification of the world’s economies 191 Table J.3  Economies in Latin America and the Caribbean, classified by ICP 2017 administra- tive region and World Bank fiscal year 2020 income group ICP 2017 World Bank fiscal year 2020 Economy administrative region income group Anguilla Caribbean Not classified Antigua and Barbuda Caribbean High income Argentina Latin America Upper middle income Aruba Caribbean High income Bahamas, The Caribbean High income Barbados Caribbean High income Belize Caribbean Upper middle income Bolivia Latin America Lower middle income Bonaire Caribbean Not classified Brazil Latin America Upper middle income Cayman Islands Caribbean High income Chile Eurostat-OECD High income Colombia Eurostat-OECD Upper middle income Costa Rica Eurostat-OECD Upper middle income Cuba Nonparticipating Upper middle income Curaçao Caribbean High income Dominica Caribbean Upper middle income Dominican Republic Latin America Upper middle income Ecuador Latin America Upper middle income El Salvador Latin America Lower middle income Grenada Caribbean Upper middle income Guatemala Nonparticipating Upper middle income Guyana Caribbean Upper middle income Haiti Latin America Low income Honduras Latin America Lower middle income Jamaica Caribbean Upper middle income Mexico Eurostat-OECD Upper middle income Montserrat Caribbean Not classified Nicaragua Latin America Lower middle income Panama Latin America High income Paraguay Latin America Upper middle income Peru Latin America Upper middle income Puerto Rico Nonparticipating High income Sint Maarten Caribbean High income St. Kitts and Nevis Caribbean High income St. Lucia Caribbean Upper middle income St. Vincent and the Grenadines Caribbean Upper middle income Suriname Caribbean Upper middle income Trinidad and Tobago Caribbean High income Turks and Caicos Islands Caribbean High income Uruguay Latin America High income Venezuela, RB Nonparticipating Upper middle income Virgin Islands, British Caribbean High income Note: ICP = International Comparison Program; OECD = Organisation for Economic Co-operation and Development. 192    Purchasing Power Parities and the Size of World Economies Table J.4  Economies in Middle East and North Africa, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group ICP 2017 World Bank fiscal year 2020 Economy administrative region income group Algeria Africa Upper middle income Bahrain Western Asia High income Djibouti Africa Lower middle income Egypt, Arab Rep.a Africa/Western Asia Lower middle income Iran, Islamic Rep. Special participation Upper middle income Iraq Western Asia Upper middle income Israel Eurostat-OECD High income Jordan Western Asia Upper middle income Kuwait Western Asia High income Lebanon Nonparticipating Upper middle income Libya Nonparticipating Upper middle income Malta Eurostat-OECD High income Moroccoa Africa/Western Asia Lower middle income Oman Western Asia High income Qatar Western Asia High income Saudi Arabia Western Asia High income Syrian Arab Republic Nonparticipating Low income Tunisia Africa Lower middle income United Arab Emirates Western Asia High income West Bank and Gaza Western Asia Lower middle income Yemen, Rep. Nonparticipating Low income Note: ICP = International Comparison Program; OECD = Organisation for Economic Co-operation and Development. a. Indicates a dual-participation economy in ICP 2017. Table J.5  Economies in North America, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group ICP 2017 World Bank fiscal year 2020 Economy administrative region income group Bermuda Caribbean High income Canada Eurostat-OECD High income United States Eurostat-OECD High income Note: ICP = International Comparison Program; OECD = Organisation for Economic Co-operation and Development. Table J.6  Economies in South Asia, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group ICP 2017 World Bank fiscal year 2020 Economy administrative region income group Afghanistan Nonparticipating Low income Bangladesh Asia and the Pacific Lower middle income Bhutan Asia and the Pacific Lower middle income India Asia and the Pacific Lower middle income Maldives Asia and the Pacific Upper middle income Nepal Asia and the Pacific Low income Pakistan Asia and the Pacific Lower middle income Sri Lanka Asia and the Pacific Upper middle income Note: ICP = International Comparison Program. Classification of the world’s economies 193 Table J.7  Economies in Sub-Saharan Africa, classified by ICP 2017 administrative region and World Bank fiscal year 2020 income group ICP 2017 World Bank fiscal year 2020 Economy administrative region income group Angola Africa Lower middle income Benin Africa Low income Botswana Africa Upper middle income Burkina Faso Africa Low income Burundi Africa Low income Cabo Verde Africa Lower middle income Cameroon Africa Lower middle income Central African Republic Africa Low income Chad Africa Low income Comoros Africa Lower middle income Congo, Dem. Rep. Africa Low income Congo, Rep. Africa Lower middle income Côte d’Ivoire Africa Lower middle income Equatorial Guinea Africa Upper middle income Eritrea Nonparticipating Low income Eswatini Africa Lower middle income Ethiopia Africa Low income Gabon Africa Upper middle income Gambia, The Africa Low income Ghana Africa Lower middle income Guinea Africa Low income Guinea-Bissau Africa Low income Kenya Africa Lower middle income Lesotho Africa Lower middle income Liberia Africa Low income Madagascar Africa Low income Malawi Africa Low income Mali Africa Low income Mauritania Africa Lower middle income Mauritius Africa Upper middle income Mozambique Africa Low income Namibia Africa Upper middle income Niger Africa Low income Nigeria Africa Lower middle income Rwanda Africa Low income São Tomé and Príncipe Africa Lower middle income Senegal Africa Lower middle income Seychelles Africa High income Sierra Leone Africa Low income Somalia Nonparticipating Low income South Africa Africa Upper middle income South Sudan Nonparticipating Low income Sudana Africa/Western Asia Lower middle income Tanzania Africa Low income Togo Africa Low income Uganda Africa Low income Zambia Africa Lower middle income Zimbabwe Africa Lower middle income Note: ICP = International Comparison Program. a. Indicates a dual-participation economy in ICP 2017. 194    Purchasing Power Parities and the Size of World Economies Glossary accounting period. The period to which esti- price level indexes, and volume indexes of mates of GDP refer, usually a calendar year or economies are not affected by either the a quarter. For ICP comparisons of GDP, the choice of local currency as numéraire or the accounting period is a calendar year. choice of reference economy. actual individual consumption. The total base economy. The economy, or group of value of the individual consumption expen- economies, for which the value of the PPP is ditures of households, of nonprofit institu- set at 1.00 and the value of the price level tions serving households, and of government. index and of the volume index is set at 100. It is a measure of the individual goods and services that households actually consume as basic heading. The lowest aggregation level in opposed to what they actually purchase. the ICP expenditure classification. In theory, a basic heading is defined as a group of simi- additive. A method that, for each economy lar well-defined goods or services. In practice, being compared, provides real expenditures it is defined by the lowest level of final expen- for aggregates that are equal to the sum of the real expenditures of their constituent basic diture for which explicit expenditure weights headings. An additive aggregation method can be estimated. Thus an actual basic head- provides real expenditures that satisfy the ing can cover a broader range of items than is average test for volumes but are subject to theoretically desirable and include both goods the Gerschenkron effect. and services. It is at the level of the basic aggregation. The process of weighting and heading that expenditures are defined and averaging basic-heading PPPs to obtain PPPs estimated, items are selected for pricing, for each level of aggregation up to GDP. prices are collected and validated, and PPPs are first calculated and averaged. analytical categories. GDP, main aggregates, expenditure categories, expenditure groups, basic price. The amount received by the pro- and expenditure classes for which the results ducer from the purchaser for a unit of good of a comparison are published. This categori- or service produced as output. It includes zation is not necessarily the same as those of subsidies on products and other taxes on pro- the hierarchical classification used for PPP duction. It excludes taxes on products, other calculations. subsidies on production, the supplier’s retail base country invariance. The property and wholesale margins, and separately whereby the relativities between the PPPs, invoiced transport and insurance charges. 195 Basic prices are the prices most relevant for are defined as individual, but only the final decision making by suppliers (producers). consumption expenditures by government on bilateral or binary comparison. A price or individual services are treated as individual. volume comparison between two economies collective consumption expenditure by that draws on data only for those two government. The final consumption expen- economies. diture of government on collective services. It bilateral or binary PPP. A PPP between two is a measure of the services that government economies calculated using only the prices provides to the community as a whole and and weights for those two economies. that households consume collectively. changes in inventories. The acquisition less collective services. Services provided by gov- disposals of stocks of raw materials, semifin- ernment that benefit the community as a ished goods, and finished goods that are held whole: general public services, defense, pub- by producer units prior to being processed lic order and safety, economic affairs, envi- further or sold or otherwise used. Semifinished ronmental protection, and housing and community amenities. They also include the goods cover work in progress (partially com- overall policy-making, planning, budgetary, pleted products whose production process and coordinating responsibilities of govern- will be continued by the same producer in a ment ministries overseeing individual ser- subsequent accounting period), including the vices and government research and natural growth of agricultural crops prior to development for individual services. These harvest and the natural growth in livestock activities cannot be identified with specific raised for slaughter. Inventories also cover all individual households and are considered to raw materials and goods stored by govern- benefit households collectively. ment as strategic reserves. comparability. The requirement that econo- characteristics. The technical parameters and mies price items that are identical or, if not price-determining properties of an item listed identical, equivalent. Items are said to be in an item specification. comparable if they have identical or equiva- Classification of the Functions of lent technical parameters and price-deter- Government (COFOG). Classification of mining properties. Equivalent means that transactions by government, including out- they meet the same needs with equal effi- lays on final consumption expenditure, inter- ciency so that purchasers are indifferent mediate consumption, gross fixed capital between them and are not prepared to pay formation, and capital and current transfers, more for one than for the other. The pricing by function or purpose. A major use of of comparable items ensures that the differ- COFOG is to identify which final consump- ences in prices between economies for an tion expenditures of government benefit item reflect actual price differences and are households individually and which benefit not affected by differences in quality. If differ- households collectively. ences in quality are not avoided or corrected, Classification of Individual Consumption they can be mistaken for apparent price dif- According to Purpose (COICOP). ferences, leading to an underestimation or Classification of the individual consumption overestimation of price levels and an over­ expenditures of three institutional sectors— estimation or underestimation of volume households, nonprofit institutions serving levels. households, and government—by the ends comparison-resistant. A term first used to that they wish to achieve through these describe nonmarket services that are difficult expenditures. Individual consumption expen- to compare across economies because they ditures are those that are made for the benefit have no economically significant prices with of individual households. All final consump- which to value outputs, their units of output tion expenditures by households and NPISHs cannot be otherwise defined and measured, 196    Purchasing Power Parities and the Size of World Economies the institutional arrangements for their pro- region in line with the distribution of real vision and the conditions of payment differ expenditures in the regional comparison. from economy to economy, and their quality Global PPPs for economies are calculated varies between economies but the differences indirectly with the redistributed global real cannot be identified and quantified. The term expenditure. is used, for example, to describe construction country product dummy (CPD) method. and the rental of housing, whose complexity, The multilateral method used to obtain tran- variation, and economy specificity can make sitive PPPs at the basic-heading level through it difficult to price them comparably across regression analysis. It treats the calculation of economies. PPPs as a matter of statistical inference—that compensation of employees. All payments in is, an estimation problem rather than an cash and in kind made by employers to index number problem. The underlying employees in return for work carried out dur- hypothesis is that, apart from random distur- ing the accounting period. These payments bance, the PPPs for individual items within a comprise gross wages and salaries in cash and basic heading are all constant between any in kind, employers’ actual social contribu- given pair of economies. In other words, it is tions, and imputed social contributions. assumed that the pattern of the relative prices component. A subset of goods or services or of different items within a given basic head- both that make up some defined aggregate. ing is the same in all economies. It is also assumed that each economy has its own consumption expenditure by government. overall price level for the basic heading and The actual and imputed final consumption that this overall price level fixes the levels of expenditure incurred by government on indi- absolute prices of the items in the basic head- vidual goods and services and collective ser- ing for the economy. By treating the prices vices. It is the total value of the individual observed in the economies for the basic head- consumption expenditure and collective con- ing as random samples, the PPPs between sumption expenditure by government. each pair of economies and the common pat- consumption of fixed capital. The reduction tern of relative prices can be estimated using in the value of the fixed assets used in pro- classical least square methods. The method duction during the accounting period result- allows the estimation of sampling errors for ing from physical deterioration, normal the PPPs. obsolescence, or normal accidental damage. country product dummy-weighted (CPD-W) country aggregation with redistribution method. A variant of the CPD method in (CAR) procedure. A means of obtaining which important items receive a higher aggregate global volumes and PPPs for econo- weight in the calculation than less important mies within each region that retain the rela- items. The choice of weights is arbitrary, as it tivities established between the economies in is in the Gini-Éltetö-Köves-Szulc* (GEKS*) the regional comparison. In other words, method. However, the weight of 1 for an each region’s results for the aggregate remain important item and 0 for a less important fixed when linked with the results of other item used in the GEKS* method cannot be regions. The procedure is as follows. The used in a weighted CPD because assigning a global basic-heading PPPs for all economies in weight of 0 to the prices of less important the comparison are aggregated to the level of items will remove them from the calculation. the aggregate. The global PPPs for the aggre- In ICP 2011 and ICP 2017, important items gate are used to calculate global real expendi- were given a weight of 3 and less important tures for each economy, with which the total items a weight of 1. global real expenditure on the aggregate for deflation. The division of the current value of each region can be determined. The total an aggregate by a price index—the deflator— global real expenditure of each region is in order to value its volumes at the prices of redistributed across the economies in the the price reference period. Glossary 197 economically significant price. A price that final consumption expenditure. The expen- has a significant influence on the amounts diture on goods and services consumed by that producers are willing to supply and the individual households or the community to amounts that purchasers wish to buy. This is satisfy their individual or collective needs or the basic price for producers and the pur- wants. chase price for purchasers. financial intermediation services indirectly economic territory. The geographic territory measured (FISIM). An indirect measure of of an economy plus any territorial enclaves in the value of the financial intermediation ser- the rest of the world. By convention, it vices that financial institutions provide clients includes embassies, military bases, and ships but for which they do not charge explicitly. and aircraft abroad. The economic territory Fisher-type PPP. The PPP for an aggregate does not include extraterritorial enclaves— between two economies that is defined as the that is, the parts of the economy’s own geo- geometric mean of the Laspeyres-type PPP graphic territory used by government agencies and the Paasche-type PPP for the aggregate. of other economies or by international orga- fixity. The convention whereby the relativities nizations under international treaties or between a group of economies that were agreements between states. established in a comparison covering just that editing. The first step of validation, which group of economies remain unchanged, or entails scrutinizing data for errors. It is the fixed, when the economies of the group are process of checking survey prices for nons- included in comparisons with a wider group ampling errors by identifying those prices of economies. For example, the price and that have extreme values—that is, prices volume relativities of the ICP regions and whose value is determined to be either too Eurostat–OECD remain unchanged in the high or too low vis-à-vis the average accord- global comparison. If fixity were not observed, ing to certain criteria. The price may score a there would be two sets of relativities for the value for a given test that exceeds a predeter- participating economies that would not nec- mined critical value, or its value may fall essarily be in agreement because the relativi- outside some prespecified range of acceptable ties and ranking of economies can change as values. Both are standard ways of detecting the composition of the group of economies errors in survey data, and both are employed being compared changes. Fixity ensures that by the ICP. Prices with extreme values are not participating economies have only one set of necessarily wrong. But the fact that their val- results to explain to users. ues are considered extreme suggests that they Gerschenkron effect. An effect applicable could be wrong. They are possible errors, and only to aggregation methods that use either a as such they need to be investigated to estab- reference price structure, whereby each lish whether they are actual errors. economy’s quantities are valued by a uniform employers’ actual social contributions. set of prices to obtain volumes, or a reference Payments actually made by employers to volume structure, whereby each economy’s social security funds, insurance enterprises, prices are used to value a uniform set of quantities to obtain PPPs. For methods or autonomous pension funds for the benefit employing a reference price structure, an of their employees. economy’s share of total GDP—that is, the error. The difference between the observed total for the group of economies being com- value of a PPP or volume index and its correct pared—will rise as the reference price struc- value. Errors may be random or systematic. ture becomes less characteristic of its own Random errors are generally called errors; price structure. For methods employing a systematic errors are called biases. reference volume structure, an economy’s expenditure weight. The share of nominal share of total GDP will fall as the reference expenditure of a basic heading in GDP. volume structure becomes less characteristic 198    Purchasing Power Parities and the Size of World Economies of its own volume structure. The Gerschenkron global core item. An item priced for the spe- effect arises because of the negative correla- cific purpose of providing a link or overlap tion between prices and volumes. between regional comparisons at the basic- Gini-Éltető-Köves-Szulc (GEKS) method. A heading level in order to combine them in a method used to calculate PPPs for basic head- single world comparison. For ICP 2017, lists ings or to aggregate basic-heading PPPs to of global core items were compiled for con- obtain PPPs for each level of aggregation up sumer goods and services, government ser- to GDP. There are two versions of the GEKS vices, and capital goods by the Global Office at the basic-heading level: one that takes in consultation with the regions, participating account of the importance of the items priced economies, and subject matter experts. and one that does not. The version that takes Regions selected items from the global core the importance of items into account is item lists and added them to their regional referred to as GEKS* in the literature. item lists in line with each item’s availability Strictly speaking, the GEKS is a procedure and importance in their region. The global whereby any set of intransitive binary index core items priced by the regions were included numbers are made transitive and multilateral in the regional comparisons as well as the world comparison. while respecting characteristicity (the prop- erty in which the resulting multilateral goods. Physical objects for which a demand indexes differ as little as possible from the exists, over which ownership rights can be original binary indexes). The procedure is established, and whose ownership can be independent of the method used to calculate transferred from one institutional unit to the intransitive binary indexes. But as used in another by engaging in transactions on the the current literature, GEKS covers both the market. They are in demand because they way in which the intransitive binary PPPs are may be used to satisfy the needs or wants of calculated and the procedure used to make households or the community or used to pro- them transitive and multilateral. duce other goods or services. The intransitive binary PPPs for a basic government. General government, which is heading or an aggregate are obtained by cal- the institutional sector that consists of fed- culating first a matrix of Laspeyres-type PPPs eral, central, regional, state, and local govern- and a matrix of Paasche-type PPPs and then ment units together with the social security taking the geometric mean of the two, a funds imposed and controlled by those units. matrix of Fisher-type PPPs. The Fisher-type It includes nonprofit institutions engaged in PPPs are made transitive and multilateral by nonmarket production that are controlled applying the GEKS procedure, which involves and financed mainly by government units or replacing the Fisher-type PPP between each social security funds. pair of economies by the geometric mean of gross capital formation. The total value of itself squared and all the corresponding indi- gross fixed capital formation, changes in rect Fisher-type PPPs between the pair inventories, and acquisitions less disposals of obtained using the other economies as valuables. bridges. The resulting GEKS PPPs provide real expenditures that are not subject to the gross domestic product (GDP). When esti- Gerschenkron effect and are not additive. mated from the expenditure side, the total GEKS results are considered better suited to value of the final consumption expenditures comparisons across economies of the price of households, nonprofit institutions serving and volume levels of individual basic head- households, and government plus gross capi- ings or aggregates. See Laspeyres-type PPP tal formation plus the balance of exports and and Paasche-type PPP (their formulation imports. depends on whether they are being used to gross fixed capital formation. The total value calculate basic-heading PPPs or to aggregate of acquisitions less disposals of fixed assets by basic-heading PPPs). resident institutional units during the Glossary 199 accounting period, plus the additions to the imputed social contributions. The imputa- value of nonproduced assets realized by the tions that have to be made when employers productive activity of resident institutional provide social benefits directly to their units. employees, former employees, or dependents gross operating surplus. The surplus or deficit out of their own resources without involving accruing from production before taking into an insurance enterprise or autonomous pen- account (1) consumption of fixed capital by sion fund and without creating a special fund the enterprise; (2) any interest, rent, or simi- or segregated reserve for the purpose. lar charges payable on financial or tangible indirect binary comparison. A price or vol- nonproduced assets borrowed or rented by ume comparison between two economies the enterprise; or (3) any interest, rent, or made through a third economy. For example, similar charges receivable on financial or tan- for economies A, B, and C, the PPP between gible nonproduced assets owned by the A and C is obtained by dividing the PPP enterprise. between A and B by the PPP between C and B, so that PPPA/C = PPPA/B / PPPC/B. gross wages and salaries. The wages and sala- ries in cash and in kind paid by enterprises to individual consumption expenditure by employees before the deduction of taxes and government. The actual and imputed final social contributions payable by employees. consumption expenditure incurred by gov- ernment on individual goods and services. household. A small group of persons who share the same living accommodation, who individual consumption expenditure by pool some or all of their income and wealth, households. The actual and imputed final and who consume certain types of goods and consumption expenditure incurred by resi- services collectively, mainly food and hous- dent households on individual goods and ing. A household can consist of only one services. Includes expenditures on individual person. goods and services sold at prices that are not economically significant. By definition, all importance. A concept that is defined in terms final consumption expenditures of house- of a specific economy within a basic heading. holds are for the benefit of individual house- An item is either important or less important holds and are individual. in the economy for the given basic heading. An important item is one that accounts for a individual consumption expenditure by significant share of the expenditure on the nonprofit institutions serving house- basic heading in the economy in question. holds (NPISHs). The actual and imputed Weighted PPP estimation methods use impor- final consumption expenditure incurred by tance as an indication of weight. NPISHs on individual goods and services. Because most final consumption expendi- imputed rent. The imputations that have to be tures of NPISHs are individual, all final con- made when owners occupy a dwelling to pro- sumption expenditures of NPISHs are treated duce housing services for themselves. In by convention as individual. effect, owner-occupiers are renting the dwell- ing to themselves, and the value of the rent individual good or service. A consumption has to be imputed. The imputed rent should good or service acquired by a household and be valued at the estimated rent a tenant pays used to satisfy the needs and wants of mem- for a dwelling of the same size and quality in bers of that household. a comparable location with similar neighbor- individual services. A term used to describe hood amenities. When markets for rented the services (and goods) provided to individ- accommodations are virtually nonexistent or ual households by nonprofit institutions serv- unrepresentative, the value of the imputed ing households and government. Such rent has to be derived by some other objec- services include housing, health care, recre- tive procedure, such as the user cost method. ation and culture, education, and social 200    Purchasing Power Parities and the Size of World Economies protection. They do not include the overall are employed for this purpose. Both proce- policy-making, planning, budgetary, and dures entail detecting outliers among the coordinating responsibilities of the govern- average survey prices by identifying outliers ment ministries overseeing individual ser- among the corresponding price ratios. vices. Nor do they include government Economies verify the outliers found in order research and development for individual ser- to ascertain whether they are valid observa- vices. These activities are considered to ben- tions. If they are not, the economy either cor- efit households collectively and are therefore rects or suppresses them. classified under collective services. intermediate consumption. The value of the input price approach. The approach used to goods and services, other than fixed assets, obtain PPPs for nonmarket services. Because that are used or consumed as inputs by a pro- there are no economically significant prices cess of production. with which to value the outputs of these ser- intracountry validation. The validation that vices, national accountants follow the con- precedes intercountry validation. It is under- vention of estimating the expenditures on taken by participating economies prior to nonmarket services by summing the costs of submitting their survey prices to the regional the inputs required to produce them. PPPs for coordinator. Each economy edits and verifies nonmarket services are calculated using input its own prices without reference to the price prices because these prices are consistent data of other economies. Validation is carried with the prices underlying the estimated out at the item level. The objective is to estab- expenditures. In practice, prices are only col- lish that price collectors within the economy lected for labor, which is by far the largest have priced items that match the item specifi- and most important input. cations and that the prices they have reported institutional sector. The five sectors identified are accurate. This entails an economy search- by the System of National Accounts: nonfi- ing for outliers first among the individual nancial corporations, financial corporations, prices that have been collected for each item government, households, and nonprofit insti- it has chosen to survey and then among the tutions serving households. average prices for these items. Subsequently, the economy verifies the outliers found in intercountry validation. The validation that order to ascertain whether they are valid takes place after participating economies have observations. If they are not, the economy completed their intracountry validation and either corrects or suppresses them. submitted their survey prices to the regional coordinator. It is an iterative process consist- item. A good or service that is the result of pro- ing of several rounds of questions and answers duction. Items are exchanged and used for between the regional coordinator and partici- various purposes—as inputs in the produc- pating economies. It involves editing and tion of other goods and services, for final verifying the average survey prices reported consumption, or for investment. by participating economies for a basic heading item list. The common list of well-defined and assessing the reliability of the PPPs they goods and services from which economies produce for the basic heading. The objective is participating in a comparison make a selec- to establish that the average survey prices are tion of items to price for the purpose of com- for comparable items, that the items have piling PPPs. been priced accurately, and that the allocation item specification. A list of the physical and of important indicators is correct. In other economic characteristics that can be used to words, it seeks to ascertain whether econo- identify an item selected for pricing, thereby mies have interpreted the item specifications ensuring that economies price comparable in the same way and whether their price col- items. An item specification can be either lectors have priced them without error. The brand and model specific (that is, a specifica- Quaranta and Dikhanov editing procedures tion in which a particular brand and model is Glossary 201 stipulated) or generic (that is, a specification nonmarket service. A service that is provided in which only the relevant price-determining to households free or at a price that is not and technical characteristics are given and no economically significant by nonprofit institu- brand is designated). tions serving households or by government. Jevons index. An elementary price index that nonprofit institution serving households is defined as the unweighted geometric aver- (NPISHs). A nonprofit institution that is not age of the current to base period price predominantly financed and controlled by relatives. government, that provides goods or services Laspeyres-type PPP. A PPP for an aggregate to households free or at prices that are not between two economies, economy B and economically significant, and whose main economy A, where the reference economy is resources are voluntary contributions by economy A and the weights are those of households. economy A. The PPP is defined as the numéraire currency. The currency unit weighted arithmetic average of the PPPs selected to be the common currency in which between economy B and economy A for the PPPs and real and nominal expenditures are basic headings covered by the aggregate. The expressed. expenditure shares of economy A are used as observation. An individual price, or one of a weights. number of individual prices, collected for an market price. The amount of money a willing item at an outlet. buyer pays to acquire a good or service from outlet. A shop, market, service establishment, a willing seller—that is, the actual price for a Internet site, mail order service, or other transaction agreed to by the transactors. It is place from where goods or services can be the net price inclusive of all discounts, sur- purchased and from where the purchasers’ or charges, and rebates applied to the transac- list prices of the items sold can be obtained. tion. Also called the transaction price. outlier. A term generally used to describe any multilateral comparison. A price or volume extreme value in a set of survey data. Extreme comparison of more than two economies values are not necessarily wrong, but the fact simultaneously that is made with price and that they are considered extreme suggests expenditure data from all economies covered that they could be wrong. They are possible and that produces consistent relations among errors, and as such they need to be investi- all pairs of participating economies—that is, gated to establish whether they are actual one that satisfies the transitivity requirement, errors. among other requirements. Paasche-type PPP. A PPP for an aggregate national annual average price. A price that between two economies, economy B and has been averaged both over all localities of economy A, where the reference economy is an economy in order to take into account the economy A and the weights are those of regional variations in prices and over the economy B. The PPP is defined as the weighted whole of the reference year in order to allow harmonic average of the PPPs between econ- for seasonal variations in prices as well as omy B and economy A for the basic headings general inflation and changes in price covered by the aggregate. The expenditure structures. shares of economy B are used as weights. net taxes on production. Taxes less subsidies Penn effect. The overstatement of the eco- on production. nomic size of high-income economies with nominal expenditure. An expenditure that is high price levels and the understatement of valued at national price levels. It can be the economic size of low-income economies expressed in local currencies or in a common with low price levels that result when market currency to which it has been converted with exchange rate–converted GDP is used to market exchange rates. It reflects both volume establish the relative sizes of economies. It and price differences between economies. arises because market exchange rates do not 202    Purchasing Power Parities and the Size of World Economies take into account price level differences a good or service at the time and place between economies when used to convert required by the purchaser. It excludes any their GDP to a common currency. value added tax (or similar deductible tax on price approach. The approach whereby the products) that purchasers can deduct from price comparison between two or more econ- their own VAT liability with respect to the VAT omies is made by comparing the prices for a invoiced to their customers. It includes suppli- representative sample of comparable items. ers’ retail and wholesale margins, separately PPPs are generally derived using the price invoiced transport and insurance charges, and approach. any VAT (or similar deductible tax on prod- ucts) that purchasers cannot deduct from price level index (PLI). The ratio of PPP to an their own VAT liability. For equipment goods, market exchange rate. PLIs provide a mea- it also includes the installation costs, if appli- sure of the differences in price levels between cable. The purchaser’s price is the price most economies by indicating for a given aggrega- relevant for decision making by buyers. tion level the number of units of the com- mon currency needed to buy the same purchasing power parity (PPP). Spatial price volume of the aggregation level in each deflators and currency converters that elimi- economy. At the level of GDP, they provide a nate the effects of the differences in price measure of the differences in the general levels between economies, thereby allowing price levels of economies. volume comparisons of GDP and its components. price measure. PPPs and the price level indexes to which they give rise. quantity approach. The approach whereby a volume comparison between two or more price relative. The ratio of the price of an indi- economies is made by comparing the vol- vidual item in one economy to the price of umes of a representative sample of compara- the same item in some other economy. It ble items. Volume comparisons are usually shows how many units of currency A must made not directly but indirectly, by dividing be spent in economy A to obtain the same the expenditure ratios between economies by quantity and quality—that is, the same vol- their corresponding price ratios. ume—of the item that X units of currency B purchase in economy B. real expenditure. An expenditure that has been converted to a common currency and product error. An error that occurs when price valued at a uniform price level with PPPs. It collectors price items that do not match the reflects only volume differences between item specification and neglect to report hav- economies. ing done so. They may not have been aware of the mismatch, such as when the item reference PPP. The PPP used for a basic head- specification is too loose, or they may have ing for which no prices are collected and no priced a substitute item as required by the PPP is calculated. It is based on prices col- pricing guidelines but failed to mention that lected for other basic headings and serves as a they had done so on the price reporting form. proxy for the missing PPP. reference quantity. The quantity to which the productivity adjustment. An adjustment prices collected for an item must be rebased made to the prices paid by nonmarket pro- to ensure that they refer to the same quantity ducers for labor, capital, and intermediate being compared. inputs so that they correspond to a common level of multifactor productivity. In practice, reference year. The calendar year to which the it is an adjustment made to the prices (com- results of the comparison refer. pensation of employees) paid by nonmarket resident population. The number of people producers for labor so that they represent the present in the economic territory at a given same level of labor productivity. point in time. purchaser’s price. The amount paid by the services. Outputs that are produced to order purchaser in order to take delivery of a unit of and that cannot be traded separately from Glossary 203 their production. Ownership rights cannot be (that is, taxes payable per unit of good or ser- established over services, and by the time vice produced, such as excise duties and a their production is completed, they must nondeductible value added tax) as well as have been provided to consumers. An excep- taxes that resident enterprises may pay as a tion to this rule is a group of industries, gen- consequence of engaging in production (for erally classified as service industries, some of example, payroll taxes and taxes on motor whose outputs have the characteristics of vehicles). The former are called taxes on goods. These industries are those concerned products; the latter are called other taxes on with the provision, storage, communication, production. and dissemination of information, advice, transitivity. The property whereby the direct and entertainment in the broadest sense of PPP between any two economies yields the those terms. The products of these industries, same result as an indirect comparison via any where ownership rights can be established, other economy. For example, for economies may be classified as either goods or services, A, B, and C, the ratio of the PPP between A depending on the medium by which these and B and the PPP between C and B is equal outputs are supplied. to the PPP between A and C, so that PPPA/C = social transfers in kind. Individual goods and PPPA/B / PPPC/B. services provided as transfers in kind to indi- vidual households by government units user cost method. The method of estimating (including social security funds) and non- the value of imputed rentals for owner-occu- profit institutions serving households. The piers by summing the relevant cost items: goods and services can be purchased on the intermediate consumption (current mainte- market or produced as nonmarket output by nance and repairs, insurance), consumption government units or nonprofit institutions of fixed capital, other taxes on production, serving households. and net operating surplus (nominal rate of return on the capital invested in the dwelling subsidies on production. Subsidies on goods and land). and services produced as outputs by resident enterprises that become payable as a result of value added tax (VAT). A tax on products col- the production of these goods or services lected in stages by enterprises. This wide- (that is, subsidies payable per unit of good or ranging tax is usually designed to cover most service produced) as well as subsidies that or all goods and services. Producers are resident enterprises may receive as a conse- obliged to pay the government only the dif- quence of engaging in production (for exam- ference between the VAT on their sales and ple, subsidies to reduce pollution or to the VAT on their purchases for intermediate increase employment). The former are called consumption or capital formation. The VAT is subsidies on products; the latter are called not usually levied on exports. other subsidies on production. verification. The second step of validation, System of National Accounts (SNA). The which entails investigating the possible errors internationally agreed-on standard set of rec- detected during the editing of survey prices to ommendations on how to compile measures establish whether they are actual errors and, of economic activity. The SNA describes a if they are actual errors, correcting or sup- coherent, consistent, and integrated set of pressing them. In many cases, verification macroeconomic accounts in the context of a will require revisiting the outlets where the set of internationally agreed-on concepts, defi- prices were collected to determine whether nitions, classifications, and accounting rules. what was priced matches the item description taxes on production. Taxes on the goods and and whether the correct price and quantity services produced as outputs by resident were recorded. Price observations found to be enterprises that become payable as a result of incorrect should be either eliminated or the production of these goods or services replaced by the correct observation. 204    Purchasing Power Parities and the Size of World Economies volume index. A weighted average of the rela- economic importance as measured by their tive levels in the quantities of a specified set values in one or other or both economies. of goods and services between two econo- volume measure. Volume measures are the mies. The quantities have to be homoge- real expenditures, the real expenditures per neous, and the relative levels for the different capita, and the volume indexes to which they goods and services must be weighted by their give rise. Glossary 205 References Clark, Colin. 1940. The Conditions of Economic Progress. International Comparisons of Real Gross Product. London: Macmillan. Baltimore: Johns Hopkins University Press. Clark, Colin. 1951. The Conditions of Economic Progress, 2nd Kravis, Irving B., Zoltan Kenessey, Alan Wiley Heston, edition. London: Macmillan. and Robert Summers. 1975. A System of International Clark, Colin. 1957. The Conditions of Economic Progress, 3rd Comparisons of Gross Product and Purchasing Power. edition. 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