The World Bank National Programme for Improving the Quality of Statistics in India (P169497) Project Information Document (PID) Appraisal Stage | Date Prepared/Updated: 21-Jan-2020 | Report No: PIDA28168 Dec 20, 2019 Page 1 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) BASIC INFORMATION OPS_TABLE_BASIC_DATA A. Basic Project Data Country Project ID Project Name Parent Project ID (if any) India P169497 National Program for Improving the Quality of Statistics in India Region Estimated Appraisal Date Estimated Board Date Practice Area (Lead) SOUTH ASIA 21-Jan-2020 19-Mar-2020 Poverty and Equity Financing Instrument Borrower(s) Implementing Agency Investment Project Financing Republic of India Ministry of Statistics and Programme Implementation Proposed Development Objective(s) To improve the quality, efficiency and user relevance of statistics produced by the India Ministry of Statistics and Programme Implementation. Components Improving Survey Data Quality Making Most of Existing Data Enhancing User Relevance of Published Statistics Project Management PROJECT FINANCING DATA (US$, Millions) SUMMARY -NewFin1 Total Project Cost 60.00 Total Financing 60.00 of which IBRD/IDA 30.00 Financing Gap 0.00 DETAILS -NewFinEnh1 World Bank Group Financing Jan 20, 2019 Page 2 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) International Bank for Reconstruction and Development (IBRD) 30.00 Non-World Bank Group Financing Counterpart Funding 30.00 Borrower/Recipient 30.00 Environmental and Social Risk Classification Low Decision The review did authorize the team to appraise and negotiate A. Country Context 1. While GDP growth has slowed in the past three years, India remains one of the fastest growing major emerging market economies. The current slowdown is primarily due to unresolved balance sheet issues in the banking and corporate sectors, compounded by stress in the non-banking segment of the financial sector. These issues have prevented a sustainable revival in private investment and private consumption growth has also slowed in FY19/20. As a result, growth is expected to reach 5% in FY19/20 — the lowest level in any year since the global financial crisis. To address the slowdown, the government has introduced various economy-wide and sectoral reforms (including a cut in corporate taxes, as well as steps to support the automobile and real estate sectors, non-banking financial companies and medium and small enterprises). As a result, growth should pick-up gradually from FY20/21 onwards and revert toward potential. On the fiscal side, the general government deficit is estimated to have widened to above 6 percent of GDP in FY18/19 and it is expected to rise further in FY19/20, owing to recently adopted tax cuts and the impact of slower economic growth on tax proceeds. The current account balance is expected to improve in FY19/20, reflecting mostly a sizeable contraction in imports. Given this and robust capital inflows, India’s foreign exchange reserves rose to USD 457.5 billion at end-December 2019 (equivalent to more than 11 months of imports). 2. Since the 2000s, India has made remarkable progress in reducing absolute poverty. Between FY11/12 and 2015, poverty declined from 21.6 percent to an estimated 13.4 percent at the international poverty line (US$ 1.90 per person per day in 2011 PPP), continuing the earlier trend of rapid poverty reduction. Thanks to robust economic growth, more than 90 million people escaped extreme poverty and improved their living standards during this period. Despite this success, poverty remains widespread. In 2015, 176 million Indians were living in extreme poverty, while 659 million - half the population- were below the higher poverty line commonly used for lower middle-income countries (US$ 3.20 per person per day in 2011 PPP). Implementation challenges of indirect tax reforms, strains on the rural economy and a high youth unemployment rate in urban areas, may have moderated the pace of poverty reduction since 2015. Jan 20, 2019 Page 3 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) 3. India is digitizing rapidly, and data is becoming ubiquitous. India’s digital push has led to 1.2 billion unique biometrics ID enrolments in the Aadhaar, more than a billion mobile connections, nearly half a billion internet users, and four-fifths of the adult population with bank accounts. India has become the world’s largest consumer of mobile data. Digital transactions are increasing at a rapid pace. The Ministry of Corporate Affairs (MCA) handles the registration of firms under the Companies Act through the MCA portal. More than 10 million businesses have been enrolled in the Good and Services Tax Network (GSTN) enabling the tracking of sales tax and trade between registered firms under one platform. Initiatives under Digital India have transformed the e-government. Several state governments have started initiatives to enhance the analysis and use of data collected through administrative processes for policy action. 4. This rich digital footprint, rapidly advancing technology, and changes to the economic landscape have had profound impacts on expectations, opportunities and risks for the statistical system. Policy makers and citizens expect more information, in real time, at a level of detail that is not always feasible through traditional surveys, in easily accessible formats, and all the while protecting privacy and confidentiality. Opportunities have grown as statistical products can potentially leverage government-wide and private sector data assets, deploy new tools to improve efficiency and quality assurance, and use advanced analytics to convert data to insights. These opportunities are not without risks – data may be nearly ubiquitous, but it is not uniformly of high quality, responsive to user needs or trustworthy. B. Sectoral and Institutional Context 5. India’s statistical system used to be among the most advanced and innovative in the world. Professor Mahalanobis (1893-1972) founded the Indian Statistical Institute (ISI) in 1931 and made myriad contributions to the field of statistics, particularly the design of large-scale sample surveys. He oversaw India’s first National Sample Survey (NSS) in 1950, establishing a practice that continues to the present – the 78th round of the NSS will start in 2020. India has an elaborate system of household and establishment surveys producing statistics that are comparable across time and space. On the World Bank’s composite Statistical Capacity Indicator which covers dimensions of methodology, source data and periodicity, India’s system scores 91.1 (out of 100), ranking it high among developing countries. India subscribes to the IMF’s Special Data Dissemination Standards, regularly updates its national accounts base year, has adopted the 2008 SNA, and has moved its system over time to meet international data standards in other areas. But the system is coming under pressure in several ways. 6. Demand for real time data to support policy decisions and track outcomes is rising. NITI Aayog, the policy thinktank of the Government of India, requires frequent and spatially disaggregated data to coordinate and monitor the government’s development agenda; the Reserve Bank of India (RBI), in their role as regulatory agency and bank supervisor, requires increasingly specialized information for financial intermediation, which is seeing rapidly growing and increasingly complex transactions. Nationwide large- sample surveys that are conducted once every five years are important, but insufficient to meet such demands. Sample sizes are not adequate for generating reliable data for administrative units below the state level; and traditional survey methodologies struggle to keep up with dynamism in the economy. Respondents – especially businesses or high-income households - are less willing to be interviewed or spend time completing survey questionnaires. Surveys will remain an important method of data collection in an Jan 20, 2019 Page 4 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) economy with a large informal sector and with large variations in state administrative capacities. However, there are opportunities to both improve survey operations to make them more efficient and of higher quality, and for statistical outputs to rely on mixed-mode statistical production combining survey and non- survey data sources including administrative databases. 7. Statistical data is required at the state, district, and local level to support effective policy and decision making. India is promoting cooperative and competitive federalism driven by a significant devolution of revenues and responsibilities to the states. The implementation capability of the public sector, particularly at the state and local level, has large and determinative effects on India’s development trajectory. There is now widespread recognition that if the public sector is to deliver better services, then citizens need agency and platforms to exert demand. For that reliable, relevant and regular information is needed. There are a variety of promising initiatives to make information available from the bottom up— such as stronger Management Information Systems (MIS) of schemes that collect transaction level data, compilation of available data on Aspirational Districts by the NITI Aayog1, and efforts by non-governmental organizations such as Pratham to make information on learning performance available in villages and districts. But systematic data collection and reporting of key outcomes at the district level has not yet been realized; insufficient data availability is only more acute at the level of rural and urban local governments. 8. There are clearly recognized needs for improving data quality and expanding the range of statistical products. More gender-disaggregated statistics and gender-relevant statistics are needed to help policy makers and stakeholders design policies to close pressing gender gaps. Gender statistics must reflect the many areas where women and men may not enjoy the same opportunities (e.g., the labor market) or where women’s and men’s lives may be affected in different ways. India still faces significant gender data gap. Data is unavailable for 13 indicators in the minimum set of gender indicators as defined by the Evidence and Data for Gender Equality (EDGE) project, a joint initiative of the United Nations Statistics Division and UN Women. Key macroeconomic indicators, such as GDP, the Index of Industrial Production, and consumer price indexes are produced with a fixed release calendar. Questions have arisen recently after a new GDP series (with the revised base year 2011-12) and associated back-series were released, as revised estimates did not seem consistent with other related macro-aggregates. The new series relies on improved data and methods but there is insufficient clarity on the respective roles of the new base, new data and improved methodology. Deciphering patterns of employment growth has proven difficult, with data from multiple (government and non-government) sources, for different time periods, coverage and sample sizes, with varying methodologies. Credible nationwide data on non-monetary indicators of well- being is not frequently available. The most recent consumption survey for which data are available was conducted in 2011-12. New consumption data for welfare monitoring and update of poverty numbers will only be available in 2021 or 2022. 9. Statistical methods and processes must adapt to a fast-changing socioeconomic landscape. It is becoming increasingly difficult to incorporate the complexities of a globalized and digitized economy in headline economic indicators. Equally, there is lack of clarity on the accuracy of measuring the sharing 1Launched in 2018, the ‘Transformation of Aspirational Districts’ programme aims to quickly and effectively transform these districts. The broad contours of the program are Convergence (of Central & State Schemes), Collaboration (of Central, State level ‘Prabhari’ Officers & District Collectors), and Competition among districts driven by a mass Movement. NITI Aayog in partnership with the Government of Andhra Pradesh has created a dashboard for monitoring the real-time progress of the districts. Jan 20, 2019 Page 5 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) economy in national accounts and employment statistics. Digitization also offers new possibilities. Information collected through administrative procedures can be used to produce statistics but requires new skills and different ways of working. Several national digital databases are hosted and overseen by the federal government (e.g. GSTN, MCA212) enabling the production of subnational statistics without relying on state contributions. To address these shortcomings and benefit from opportunities, India must adjust its production processes to maximize the gains from administrative and other data sources, change the skill mix of its data producers and adapt its institutional set-up. The statistical system must evolve from collecting data through surveys mainly for government use to integrating data holdings across government, and sometimes the private sector, and transforming that data into key indicators and analytics, and disseminating it to a broader and more diverse group of users such as news media, academic researchers, businesses, fund managers and civil society organizations, to name a few. 10. Strengthening India’s national statistical system requires stronger statistical offices at federal and state level, an increased emphasis on quality control, coordination and political commitment to the independence of the statistical authorities. A strong national statistics coordinator is of primary importance to make the decentralized system work. The national coordinator must be equipped with a mandate to set and enforce statistical standards such as definitions, classifications and data transmission protocols as well as sufficient capacity to train and advise other statistics producers and to promote compliance. The national coordinator must also build and maintain adequate ICT infrastructure to compile and process survey and non-survey data from different sources and to integrate this data to produce new statistical outputs in addition to making the statistical production process more efficient. Credible statistics also requires that the agency in charge of the production of statistics is seen as impartial, professional, and free of political interference. Achieving an effective, impartial and coherent system that serves both national and local data needs takes leadership, political will and a plurality of investments at the national and subnational level. 11. The Ministry of Statistics and Programme Implementation (MOSPI) is the main producer of official statistics in India. It has three major wings namely, the National Statistical Office (NSO), Program Implementation (PI) Wing and Finance Wing. This project is limited to the NSO as it is the nodal agency for planning and facilitating the integrated development of the national statistical system in India. All statistical operations take place under the National Statistical Office (NSO) which comprises three main verticals each headed by a Director General (DG) reporting to Secretary, MOSPI who is also the Chief Statistician of India. The three verticals are: Statistics, National Sample Survey (NSS) and Coordination, Administration and Policy (CAP). The Statistics vertical plays a crucial role in responding to the emerging and evolving data needs across a wide range of socio-economic-demographic issues and is primarily responsible for compilation of frameworks such as the India system of national accounts, monitoring and reporting on progress towards the Sustainable Development Goals (SDGs), Economic Censuses (ECs) and the indices of industrial production and consumer prices, as well as maintaining and updating national classification frameworks for industries and products. It comprises five divisions namely; National Accounts Division (NAD), Economic Statistics Division (ESD), Price Statistics Division (PSD), Social Statistics Division (SSD) and the Data Informatics and Innovation Division (DIID). DIID is responsible for the ICT related aspects of statistical 2Ministry of Corporate Affairs: the MCA21 data base comprises all information companies are obliged to report under the under the Companies Act. Jan 20, 2019 Page 6 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) production, including MOSPIs website, data archiving and dissemination, cloud, server and software management, as well as the design and roll-out of the National Integrated Information Platform (NIIP), an integrated platform for data acquisition, processing and dissemination. The second vertical, National Sample Survey (NSS), is responsible for implementing the various NSS rounds such as, consumption, employment, social expenditures, household debt and investment surveys, Annual Survey of Industries. NSS is also responsible for maintaining and updating sampling frames, questionnaire design, field work organization and survey data collection. It comprises four divisions namely, Survey Design and Research Division (SDRD), Data Quality Assurance Division (DQAD), Field Operations Division (FOD) and Survey Coordination Division (SCD). The third vertical, Coordination, Administration and Policy (CAP), is primarily responsible for all cross-cutting which require coordination among and within various internal and external stakeholders including human resource management, administration, training, management of the Statistical Service Cadre and capacity building. It is also the nodal agency for managing the capacity development scheme of the Ministry including the Support for Statistical Strengthening (SSS) scheme for States. Furthermore, while the project activities are spread across the three verticals of NSO, the Project Monitoring Unit for this project is housed under CAP. 12. MOSPI is mandated to provide leadership and coordination of the national statistical system. A National Statistical Commission (NSC) has been established as the main advisory body. In 2000, Government of India (GoI) launched a commission, chaired by Dr. C. Rangarajan, to conduct a comprehensive review of the statistical system. Following the review, GOI initiated several reforms to improve the operational efficiency of the statistical production hubs at the national and state levels, and to improve coordination between the Center and States. A National Statistical Commission (NSC) was established in 2005 with the goal of being the apex advisory body on statistical matters, and the Collection of Statistics Act was passed in 2008. MOSPI was tasked with establishing standards, norms and benchmarks for key statistical activities; and transferring technical and financial resources from the Center to States. A National Statistical Systems Training Academy (NSSTA) was set up as part of MOSPI to provide trainings to statistical personnel. The Conference of Central and State Statistical Organizations (COCSSO) was revived to strengthen institutional coordination of statistical activities between MOSPI, other central ministries and state statistical organizations. At the national level, the system benefits from a cadre of highly educated and well-trained statistical professionals collectively known as the Indian Statistical Service (ISS). C. Proposed Development Objective(s) Development Objective To improve the quality, efficiency and user relevance of statistics produced by the India Ministry of Statistics and Program Implementation. Key Results 13. Successful achievement of the Project Development Objective (PDO) above will be measured with the following PDO/outcome level indicators: • PDO indicator 1: Share of core surveys applying real-time quality control • PDO indicator 2: NSO core surveys released as per the adopted Advance Release Calendar • PDO indicator 3: National Factsheet indicators on Indian economy released quarterly Jan 20, 2019 Page 7 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) • PDO indicator 4: Legacy survey data available for use in the on-line tabulation tool D. Project Description 14. In line with the objectives defined in the PDO, the project comprises three components: (i) Improving Survey Data Quality; (ii) Making Most of Existing Data; and (iii) Enhancing User Relevance of Published Statistics. Integrated in these components are three major initiatives initiated by MOSPI which each have the potential to catalyze statistical modernization: (i) the development of a multi-modal data capture platform, which transforms survey data collection from paper-based to computer-assisted, (ii) the design of the National Integrated Information Platform, a data warehouse with data ingestion, processing, quality control and dissemination capabilities and (iii) the development of a statistical business register based on the 7th Economic Census, for which data collection is ongoing, and on administrative data systems. 15. Component (i): Improving Survey Data Quality. Improving survey data quality requires efforts in several dimensions. Non-sampling error must be reduced, and methodologies reviewed to ensure that the data collected is reliable. The delay between field data collection and the presentation of results should be shortened to ensure that statistics are timely. And, data and reports should be released in accordance with a pre-agreed timetable, to ensure that the production of statistics is predictable. The project addresses these three dimensions of survey data quality by investing in hardware (laptops and tablets) and training needed to make the transition to CAPI for real time monitoring; facilitating organizational restructuring and training needed to reduce the time between survey completion and data release; supporting the development of an Advance Release Calendar (ARC) primarily through workshops and consultations; and developing e-learning courses for investigators. After all, with the transition to tablets, investigator training can be modernized as well and on-line courses (MOOCS) and certification methods will be introduced. Furthermore, through MoUs with an established statistical office(s), the use of specialist consultants and innovation funds, this project will ensure that survey methodologies are assessed and improved. Studies funded out of the innovation funds, as well as expert advice will be critical to ensuring that survey data quality remains high and that primary data collection continues to reflect the latest developments in the field. Envisaged are analyses which inform on the consequences of the move from paper-based schedules to CAPI questionnaires on non-sampling error; effective ways to use paradata for quality control; or efficient ways to collect consumption information (role of panels; dealing with food away from home; imputation methods). 16. Component (ii): Making Most of Existing Data focuses on enhancing the efficiency and quality of statistical production by increasingly using existing data from administrative sources while introducing routine quality controls. This will be achieved through investments in specialist consultants, capacity building and training. Proceeds from the project will finance data innovation (data acquisition, specialist time, studies, software) and background studies (including data compilation for the eco-system and natural capital accounts) as well as meetings, workshops and specific hard- and software needs. The project will also help MOSPI establish arrangements (through MoUs or otherwise) with leading international statistical offices who have completed their business reengineering processes and made the transition to meta-data driven data productions systems, in the spirit of peer-to-peer learning. 17. Component (iii): Enhanced User Relevance of Published Statistics. Modern statistical offices produce core statistics relevant for monitoring key socio-economic trends, such as GDP, inflation, or employment, but also thematic material relevant to inform critical debates in society. As such one observes less reporting on e.g. results from a recently completed survey, and more reporting on thematic issues pulling together information from surveys and other data sources. To help MOSPI make this transition the project supports greater interaction with data users to identify relevant issues and promotes different ways of disseminating data: not just reports and anonymized raw data, but also tabulation Jan 20, 2019 Page 8 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) tools and interactive maps. The project will disburse against the introduction of online mapping and tabulation tools and the intensification of user-producer interactions. The project will finance data advocacy (workshops; videos; training), specialist consultants (data visualization; social media presence), hard and software (for maps and interactive tables) and software development. The Project will also support the creation of a geo-spatial unit within Data Integration and Innovation . Division (DIID) and finance the Unit’s capacity building through specialized training. . Legal Operational Policies Triggered? Projects on International Waterways OP 7.50 No Projects in Disputed Areas OP 7.60 No Summary of Assessment of Environmental and Social Risks and Impacts . 18. The scope and activities of the Project indicate a Low risk project from the environmental and social safeguards perspective. The emphasis on Technical Assistance for statistical production methods and processes, upgrading of human resource skills and expanding capacity is consistent with this assessment. The project is neither constructing nor setting up new buildings. There is no land acquisition. The disposal of new IT equipment to be acquired for data capture and processing will have environmental management implications. While environmental risks are not expected at the time of IT procurement and adoption, appropriate procedures will need to be in place for disposal of equipment as per best environmental practices. Social risks are mostly related to labor management and stakeholder engagement, including information disclosure and grievance redressal. An Environmental and Social Commitment Plan (ESCP) has been prepared to address these risks. Implementation of the material measures and actions set out in this ESCP will be monitored and reported to the Bank by MOSPI as required by the ESCP and the conditions of the legal agreement, and the Bank will monitor and assess progress and completion of the material measures and actions throughout implementation of the Project. Jan 20, 2019 Page 9 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) E. Implementation Institutional and Implementation Arrangements 19. The implementing agency is MOSPI. Project implementation resides with the statistics wing, also referred to as the National Statistical Office (NSO) led by the Secretary MOSPI who also serves as the Chief Statistician of India (CSI). Within the NSO a Project Management Unit (PMU) has been created under the Coordination, Administration and Policy (CAP) vertical which is responsible for oversight over the day-to-day implementation of the Project. The PMU for this project is supported by a Project Management Consultancy (PMC) procured following national rules. In addition to having dedicated consultants for the Project, the PMC will also support the implementation of the NIIP which is a critical component of the Project and will help ensure better integration and synergy among accompanying activities under this project such as quality control; data innovation; introduction of a multi-modal data capture platform, that are highly complementary. 20. The PMU will be headed by a Project Director and comprise MOSPI staff responsible for overseeing and facilitating project implementation. The PMC will provide support to the PMU to carry out project related tasks. The project PMC will be adequately staffed, including a deputy project manager with the following main responsibilities: project monitoring, strategic feedback on project implementation to the Project Director, administrative tasks related to implementation of the innovation funds, supporting grievance redress, preparation of progress reports and the preparation of annual implementation plans for achieving the DLIs and results identified. The PMC will also include a change management specialist and a strategy specialist who will facilitate MOSPIs business reengineering process, and associated communication, research and capacity building, as well as various consultants /junior associates to facilitate project implementation within the various divisions. Other PMC staff, including those responsible for procurement and financial management will also have joint responsibilities for NIIP and project activities. 21. Project activities will be implemented in each of the three verticals of NSO: NSS –responsible for survey implementation, Statistics responsible for national accounts, administrative statistics and provide ICT framework and Coordination, Administration and Policy, responsible for capacity building and overall management of the project. . CONTACT POINT World Bank Thomas Danielewitz Senior Economist/Statistician Borrower/Client/Recipient Republic of India Mr. Hanish Chhabra Deputy Secretary Jan 20, 2019 Page 10 of 11 The World Bank National Programme for Improving the Quality of Statistics in India (P169497) hanish.ias@ias.nic.in Implementing Agencies Ministry of Statistics and Programme Implementation Pravin Srivastava Chief Statistician of India pravin.srivastava@nic.in FOR MORE INFORMATION CONTACT The World Bank 1818 H Street, NW Washington, D.C. 20433 Telephone: (202) 473-1000 Web: http://www.worldbank.org/projects APPROVAL Task Team Leader(s): Thomas Danielewitz Approved By Environmental and Social Standards Advisor: Practice Manager/Manager: Country Director: Bhavna Bhatia 23-Jan-2020 Jan 20, 2019 Page 11 of 11