MOZAMBIQUE Agriculture Support Policy Review Realigning Agriculture Support Policies and Programs December 31, 2021 Report No: © 2021 The World Bank 1818 H Street NW, Washington, DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some Rights Reserved This work is a product of the staff of The World Bank. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the Executive Directors of the World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this work is subject to copyright. Because The World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Attribution—Please cite the work as follows: “World Bank. 2021. Mozambique Agriculture Policy Review: Realigning Agri- culture Support Policies and Programs. © World Bank.” All queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org. I Contents Figures ......................................................................................................................................................... III Tables .......................................................................................................................................................... IV List of Acronyms .......................................................................................................................................... V Acknowledgments ....................................................................................................................................... VII Execu�ve Summary ....................................................................................................................................... 1 Report Highlights .................................................................................................................................... 2 Recommenda�ons ...... ............................................................................................................................ 4 Introduc�on ................................................................................................................................................. 5 Country Context ..................................................................................................................................... 6 Sector Context ........................................................................................................................................ 8 Overview of Agricultural Support in Mozambique ................................................................................. 11 Objec�ves of Agriculture Support Policies and Programs in Mozambique ................................................. 14 Conceptual Framework for Policy Review ................................................................................................... 16 Methodology: Ra�onale and Coverage .................................................................................................. 16 OECD Methodology: Technical Concepts and Calcula�on ...................................................................... 18 Agriculture Support Es�mates: Global Snapshot and Trends ................................................................. 21 OECD and Emerging Economies: A Comparison ...................................................................................... 22 Agriculture Support Es�mates for Mozambique ......................................................................................... 26 Total Support Es�mates (TSE) ................................................................................................................. 26 Support to Agricultural Producers (PSE) ......................... ......................................................................... 27 Support to General Services for Agriculture (GSSE) ............................................................................... 32 Support to Consumers of Agricultural Products (CSE) ............................................................................ 35 Conclusions ................................................................................................................................................... 36 Main Findings .......................................................................................................................................... 36 Proposed Agriculture Policy Reform Agenda .......................................................................................... 38 Lessons from Mozambique for other Countries ..................................................................................... 41 Annex A: Supplementary Figures and Tables .............................................................................................. 42 Annex B: OECD Categories and Classifica�on Criteria ................................................................................. 48 Annex C: Conceptual Note on Price Collec�on of Agricultural Producers .................................................... 51 Annex D: Public Programs and Budgetary Expenditure ................................................................................ 55 Annex E: Strategic objec�ves and targets for the agricultural sector: PQG (2015-2019) and PNISA 1 (2013 - 2017) ................................................................................................................................................. 68 II Figures Figure 1: Share of Government Agriculture Expenditure in Total Public Expenditure (%), 2008–2018 ... 12 Figure 2: Coverage of OECD Methodology of Agriculture Support Es�mates ........................................... 17 Figure 3: OECD Methodology – Main Indicators of Transfers, by Source .................................................. 18 Figure 4: Agriculture Support Trends (54 Countries) ................................................................................ 22 Figure 5: Agriculture Support Trends –OECD Countries ................................................................................ 23 Figure 6: Agriculture Support Trends—Emerging Economies .................................................................. 23 Figure 7: Transfer to Specific Commodi�es (STC) -- OECD, 2017-2019 .................................................... 24 Figure 8: Transfer to Specific Commodi�es (SCT) – Emerging Economies, 2017-2019 ............................ 24 Figure 9: GSSE Composi�on in OECD Countries, 1986 - 2019 ................................................................... 25 Figure 10: Benchmarking TSE as share of GDP, 2018 ......... ......................................................................... 26 Figure 11: Benchmarking TSE as a share of Agriculture GDP, 2018 ........................................................... 26 Figure 12: Benchmarking Mozambique’s TSE, by Source of Transfers ...................................................... 27 Figure 13: Benchmarking %PSE, 2018 ........................................................................................................ 27 Figure 14: Level and Composi�on of Mozambique’s PSE, 2018 ................................................................. 28 Figure 15: Composi�on of Mozambique’s PSE, by Category of Support, 2018 .......................................... 29 Figure 16: Benchmarking %SCT by Commodity, 2018 .............................................................................. 30 Figure 17: Benchmarking SCT% for maize, 2018 ........................................................................................ 31 Figure 18: Benchmarking %SCT for Pork Meat, 2018 ................................................................................. 31 Figure 19: Benchmarking %SCT for Cassava, 2018 ..................................................................................... 32 Figure 20: GSSE as a share of agriculture GDP, 2018 ................................................................................. 32 Figure 21: GSSE as a share of TSE, 2018 ..................................................................................................... 33 Figure 22: Composi�on of the GSSE in Mozambique ................................................................................. 33 Figure 23: Benchmarking GSSE by Component, 2018 ................................................................................ 34 Figure 24: Benchmarking %CSE, 2018 ........................................................................................................ 35 Figure 25: Agriculture Support and Value Added per Worker, 2018 ......................................................... 37 Figure 26: Support to Maize vs Yields, 2018 .............................................................................................. 38 Figure 27: Producer Support Es�mate (PSE) and Sub-Categories .............................................................. 42 Figure 28: General Services Support Es�mate (GSSE) and Sub -Categories ................................................ 42 Figure 29: Es�mates of Support to Agriculture (54 Countries) .................................................................. 43 Figure 30: Mozambique’s TSE, 2018 .......................................................................................................... 44 Figure 31: Disaggrega�on of Mozambique’s TSE, 2018 .............................................................................. 46 Figure 32: World Trade Organiza�on Boxes .............................................................................................. 47 Figure 33: Average farm-gate price over commodity over year .................................................................. 53 Figure 34: Average consumer price over commodity over year ................................................................. 53 Figure 35: Budget PSE, by Category and Program ........................................................................................ 55 Figure 36: Budget GSSE, by Category and Project ........................................................................................ 62 Figure 37: Budget CSE .................................................................................................................................. 67 III Tables Table 1: Structure of the Economy and Sector Contribu�ons to GDP (2013 – 2017) 9 Table 2: Mozambique farm typology 10 Table 3: PEDSA II Expected Strategic Pillars 15 Table 4: Composi�on of PSE, 2018 28 Table 5: Composi�on of PSE Budgetary Payments 30 Table 6: WTO Classifica�on of Mozambique’s TSE 35 Table 7: Contribu�on in total cul�vated area, sales and produc�on 51 Table 8: WTO Classifica�on of Mozambique’s TSE 54 IV List of Acronyms AfCFTA Africa Con�nental Free Trade Area Ag GDP Agriculture Gross Domes�c Produc AgPERs Agriculture Public Expenditure Reviews CAADP Comprehensive Africa Agriculture Development Program CAP Common Agriculture Policy CFMP Medium Term Fiscal Scenario (Cenário Fiscal do Médio Prazo) CIF Cost, insurance and Freight CO2 Carbon Dioxide COVID-19 Coronavirus disease CSA Climate Smart Agriculture CSE Consumer Support Es�mate EU European Union FAO Food and Agriculture Organiza�on FDI foreign direct investment FOB Free on Board FTA Free Trade Area GDP Gross Domes�c Product GHG Greenhouse Gases GSSE General Services Support Es�mate Ha Hectare IADB Inter-American Development Bank IFC Interna�onal Finance Corpora�on IFPRI Interna�onal Food Policy and Research Ins�tute INE Na�onal Ins�tute of Sta�s�cs of Mozambique KPI Key Performance Indicator MADER Ministry of Agriculture and Rural Development MAFAP Market-oriented Smallholder Agriculture Project MEF Ministry of Economy and Finance MFN Most Favored Na�on MGS matching grant schemes MPS Market Price Support MSME Micro, small, and medium enterprise Mts Me�cal MT Metric Tons NAFTA North American Free Trade Agreement NEPAD New Partnership for Africa’s Development NSmartAg Nutri�on Smart Agriculture OECD Organisa�on for Economic coopera�on and Development PEDSA 2 Second Agrarian Sector Development Strategy PNIDSA 2 Na�onal Agriculture Investment Plan PSE Producer Support Es�mate SADC Southern Africa Development Community SCT Single Commodity Transfer V SREP Sustainable Rural Economy Program SSA Sub-Saharan Africa TSE Total Support Es�mate WB World Bank WFP World Food Programme WTO World Trade Organiza�on VI Acknowledgments The WBG team was led and coordinated by Diego Arias of the Agriculture and Food Global Prac�ce. The team members included: Aniceto Bila, Giuseppe Fantozzi, Pedro Arlindo, Hector Peña, Armando Gonzalez, Helder Zavale, Bodomalala Raba- rijohn (Agriculture and Food, WB), and Francisco Pereira Fontes (FAO). The WBG team would like to thank the Government of Mozambique for the support to undertake this review and the produc�ve discussions, in par�cular Amilcar Pereira, Duque Wilson, and Nemane Momede (Ministry of Agriculture). The WBG team would also like to thank the AgRed donor group in Mozambique for a produc�ve discussion and feedback on the report during their mee�ng of December 7 2021, as well as individual colleagues that provided valuable input and guidance, in par�cular: Shobha She�y (Prac�ce Manager, Agriculture and Food), Chris Delgado and Federica Ricaldi (Social Protec�on and Jobs), Paulo Correa (Program Leader and Country Lead Economist), Francisco Leitao Camos (Finance, Compe��veness and Innova�on), Richard Anson (Consultant), Claudia Pereira, Dario Cipolla, Rouja Johnstone, Chris�an Derlagen and Valen�na Pernechele (FAO), Paavo Eliste, Ashesh Prasann, and Madhur Gautam (Agriculture and Food). VII Execu�ve Summary This report assesses agriculture policy support es�mates how much policy/program support is invested in land in Mozambique. These es�mates represent the monetary administra�on efforts, but unable to qualify the impact value assigned to different agriculture support policies and (quality) of those policies/programs). Finally, given that programs using the OECD methodology¹ for 2018. The data for only 1 year was obtained (2018), results should be advantages of using the OECD methodology are that: (a) it seen as par�al given poten�al for year-on-year changes in provides a systema�c and integrated view of agriculture interna�onal vs. domes�c prices. At least 2 or 3 year avera- support policies and programs (not limited to the more ges are ideal for using this methodology for es�ma�ng tradi�onal public expenditure reviews or rate of protec- supports. Nevertheless, the broader structure of agricultu- �on); (b) given the large number of countries using this re support es�mates and messages remain valid. same methodology to measure support es�mates, an immediate benchmarking is possible across a large set of This assessment aims to support the Mozambique comparators² ; and (c) the methodology is simple and can Government in reviewing its agriculture policies and be integrated into the agriculture public policy analysis programs, in par�cular to: (a) provide new es�mates and a conducted by the Government and other stakeholders.³ new approach to assess sector support for policy decision- The methodology also has some disadvantages and limita- making; (b) allow for benchmarking agriculture support �ons, mainly: (a) while it quan�fies the level of support policies with a large global database of countries using the provided to producers and consumers, it does not further same es�mate methodology; and (c) help kickstart a policy disaggregate support received by type of agricultural dialogue on realigning agriculture policies and programs in producers (small-scale/large-scale; family Mozambique towards greater sector compe��veness and farm/commercial) or consumers; (b) since the es�mates fast economic recovery from the COVID-19) pandemic, are based on the monetary value of budget and price increased food security and nutri�on outcomes, and clima- support, non-monetary support, like the quality of policies, te sustainability through a build back be�er approach. is not captured (e.g., the methodology is able to iden�fy 1 See methodology manual at: http://www.oecd.org/agriculture/topics/agricultural-policy-monitoring-and-evaluation/documents/producer-support-estimates-manual.pdf 2 At present, the OECD methodology for agriculture support estimates covers 109 countries. This includes OECD countries, non-OECD EU Member States (subject to data availability), and a number of developing countries where monitoring is done by the OECD, IADB, and FAO’s MAFAP unit. The 54 countries monitored by the OECD are Argentina, Australia, Brazil, Canada, Chile, China, Colombia, Costa Rica, the European Union (Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Poland, Portugal, Spain, Slovakia, Slovenia, Sweden, the United Kingdom), India, Indonesia, Iceland, Israel, Japan, Kazakhstan, Korea, Mexico, New Zealand, Norway, the Philippines, the Russian Federation, South Africa, Switzerland, Turkey, Ukraine, the United States and Viet Nam. 3 As part of this assessment, a training of more than 15 public sector staff was undertaken to build capacity and allow for Government to update the estimates going forward. 1 Report Highlights Mozambique allocated US$509 million in annual Agriculture producer support in Mozambique is support to the agriculture sector, represen�ng 3.3 overwhelmingly funded by policies that raise domes�c percent of total GDP. agriculture prices. Ninety-five percent of the support to Total Support Es�mate (TSE) to agriculture from public agriculture producers (PSE) is through by Market Price policies and programs⁴ in Mozambique in 2018 was Support (MPS), while budgetary support only represen- es�mated to be US$509 million. This was equivalent to ted 5 percent in 2018. These transfers occur due to 12.8 percent of its agriculture gross domes�c product public policies (mainly border measures) are making the (GDP), higher than South Africa but lower than Angola domes�c prices of agriculture and food products higher (Fig. 11), the value was below OECD member countries than the interna�onal prices (compared at farm gate). In (40.2 percent on average). A neighbor and close trading other words, border measures are crea�ng an “implicit partner, South Africa, has a TSE of 9 percent of agricultu- tax” for food consumers in Mozambique and most bene- re GDP and 0.4 percent of total GDP, lower than Mozam- ficiaries of higher prices are agriculture producers that bique, while OECD countries’ support to agriculture par�cipate in market sales. MPS are thus, monetary represents 0.6 percent of total GDP. transfers from Mozambican food consumers to Mozam- bican producers. Although total agriculture support in Mozambique is high compared to other developing countries, the The structure of producer support only benefits a small por�on of support going to public goods and services is number of commercial producers and does not enhan- rela�vely low. ce sector compe��veness. MPS is based on the amount The Total Support Es�mate (TSE) is composed of support of agriculture produc�on that a farmer sells in the to producers (measured as Producer Support Es�mate, market, it is therefore poorly targeted and favors produ- PSE), Consumer Support Es�mate (CSE), and support to cers who generate larger commercial surplus rather general agriculture public goods and services (General than smallholders with smaller surpluses or who only Services Support Es�mate, GSSE)⁵. The analysis revealed produce for self-consump�on⁶. Given that small-scale that 95 percent of TSE was through producer support and subsistence-oriented family farms dominate in (largely in the form of market price support), while just 5 Mozambique and that MPS policies have been imple- percent went to GSSE. Benchmarking the TSE composi- mented mainly based on food security arguments, the �on across countries where data is available, we observe effect of MPS is the opposite, benefi�ng only a small that Mozambique’s investment in GSSE is the lowest propor�on of producers and taxing agriculture house- globally. As a share of the agriculture GDP, GSSE accoun- holds which are net food consumers. It is important to ted for just 1 percent, which was low compared to other note that these es�mates are from 2018 and aggregate developing countries average (2.7 percent) and the support across en�re commodity producers, so it is OECD’s average (5.4 percent) in 2018. possible that in recent years the situa�on may have changed for some farmers and subsectors. Neverthe- Only 7 percent of gross farm receipts were accounted less, it is well-known in the literature and evidence by Mozambique’s support to producers, more than 11 shows that MPS distorts produc�on decisions and percent points lower than the OECD average. In investments in compe��ve agriculture products as it Mozambique, 7 percent of producer’s gross farm protects producers from interna�onal market prices. receipts (%PSE) came from agriculture support policies and programs in 2018. This is 11 percent points lower Food consumers in Mozambique pay an implicit tax of than the OECD average for that same year. This shows about 5 percent. Support to food consumers (CSE) is that although total support (TSE) is rela�vely high in nega�ve in Mozambique. CSE measures the support to rela�on to total GDP, TSE as percentage of Ag GDP and (or tax on) food consumers arising from public agricultu- %PSE are average or slightly below average given the re policies. Although Mozambique does provide some- large size of the sector. %PSE in Mozambique was com- support to food consumers in the form of food aid and parable with that of countries with medium levels of school feeding programs, the overwhelming majority of support, such as Canada, Mexico and Costa Rica. 4 Agriculture support was estimated using the OECD methodology (https://www.oecd.org/agriculture/topics/agricultural-policy-monitoring-and-evaluation/documents/producer-supp ort-estimates-manual.pdf ). The total support estimate measure (TSE) is the annual monetary value of all gross transfers from taxpayers and consumers arising from public policy measres that support agriculture, net of the associated budgetary receipts, regardless of their objectives and impacts on farm production and income, or consumption of farm products. 5 GSSE’s include agriculture public goods and services such as innovation systems (agriculture R&D and education), animal and plant health services, food safety, 6 In some settings, other value chain actors (such as input suppliers) also capture part of the transfers. It’s conceivable that in those settings, they benefit more than even large-scale producers. 2 the CSE is nega�ve, due to public policies protec�ng signals the distor�ons that farmers face when making domes�c prices. CSE as a percentage of total food produc�on decisions. For example, support to sweet expenditures by food consumers was approximately 5 potatoes was US$39/ha while maize was US$60/ha and percent in 2018. This 5 percent implicit tax is a transfer cassava was US$170/ha in 2018⁷. from consumers to producers through higher domes�c food prices. It is also a regressive tax since poor consu- Mozambique is in the process of defining its 10-year mers spend a larger share of their income on food than strategy and investment plan for the agriculture sector, high-income consumers. recovering from the COVID-19 pandemic, and moving towards a more compe��ve and sustainable agricultu- Agriculture support to producers in Mozambique is re sector. In the past, support consisted largely of price basically concentrated in maize and pork meat and is support (through border measures), without addressing rela�vely high for these commodi�es compared to underlying compe��veness bo�lenecks. This approach other countries. Of the total gross revenues perceived will need to be phased out as Mozambique moves by farmers producing maize, 43 percent came from towards full par�cipa�on in regional and con�nental agriculture public support policies and programs, while free trade agreements. Programs like the Sustainable pork meat had 31 percent support, in 2018 Rural Economy Program (SREP) seek to improve the (commodity-specific support is measured by Single resilience and compe��ve posi�on of the agriculture Commodity Transfers—SCT). In comparison, the %SCT in sector. Developing agribusinesses is high in the country’s OECD countries was 3 percent for maize and 8 percent development agenda, with an important private sector for pork meat in the same year, the Mozambique levels development program and technical assistance provided were similar of the Indonesia and Colombia for maize by the World Bank (WB) and IFC. The mul�ple natural and Costa Rica or Norway for pork meat. Although the disasters of the last years and the COVID-19 pandemic actual dollar value of SCTs, and in par�cular MPS, mea- have also renewed the urgency to focus on suppor�ng sured only for a single year (2018 in this case) may not the climate resilience and nutri�on of the poorest hou- reflect exactly the support received by that commodity seholds. given temporary distor�ons caused by produc�on shocks (natural disasters) or real exchange rate misalign- This report presents some important recommenda�ons for ments, the results are s�ll valid to point out rela�ve realigning agriculture support policies and programs imbalances in support (o�en OECD support es�mates towards compe��veness, climate resilience and nutri�on are measured as a mul�-year average to avoid distor- and food security objec�ves. �ons in specific years) Therefore, the rela�ve large diffe- rences in agriculture public sector support—and there- fore profitability—across commodi�es in Mozambique Compe��veness objec�ve COVID-19 Recovery: Building back be�er Agriculture Policy Shi� (diversifica�on and trade integra�on) Nutri�on—Food Climate Resilience Security PSE to GSSE MPS to non-distor�onary PSE CSE (-) to CSE (+) SCT to non-commodity specific PSE 7 Authors calculations, based on OECD data. 3 Recommenda�ons: Shi� agriculture support from private towards public lay out such shi� and complementary agenda, learning goods and services. Agriculture support in Mozambique from the lessons of the implementa�on of PEDSA and is mainly geared towards private goods (subsidies and PNISA 1. market price support) rather than towards investments in agriculture public goods and services: almost half of Shi� from implicit taxa�on to posi�ve support to food all agriculture public expenditures (2018) went towards consumers. As the nega�ve CSE es�mates in this report investments in private goods (subsidies), such as demonstrate, Mozambican food consumers are funding payments based on agriculture inputs and services the bulk of agriculture support to the sector. A shi� away —programs that subsidize technical assistance, exten- from MPS, as suggested above, will reduce the implicit sion services, and agriculture inputs like seeds, fer�li- food tax to food consumers, consequently increasing the zers, machinery and land prepara�on. Mozambique welfare of the poorest. However, other public policies should seek to shi� its agriculture sector support and programs could be further enhanced to directly towards investments in public goods and increase GSSE’s safeguard consumers from food insecurity and nutri�on share of agriculture GDP from its current level of 0.6 challenges, by targe�ng support through social protec- percent to at least the level of South Africa, or the avera- �on programs (food aid, school feeding) and countercy- ge of developing countries (2.3 percent and 5.4 percent, clical safety nets. respec�vely), given the overwhelming and long- standing evidence that public sector investments and Shi� support to integrate environmental and nutri�on support to agriculture public goods and services deliver objec�ves within agriculture support policies and higher economic returns than public sector investments programs. Given the country’s fiscal limita�ons and the in private goods (World Bank, 2017⁸ ; Lopez and Galina- implicit tax imposed by agriculture public policies on to, 2007⁹ ; Lopez, 2005¹⁰ ; World Bank, 2001¹¹ ). This shi� Mozambican food consumers, producer support should will require a fiscal exercise to ensure that is as neutral be geared towards achieving objec�ves beyond suppor- as possible to the overall Government budget, but also �ng farmer incomes. Support can contribute towards (i) addressing some of the current structural issues with food produc�on intensifica�on (seeking to health area agriculture public expenditures (i.e. most of sector expansion as a source of agriculture growth); and (ii) expenditures go to salaries rather than investments). nutri�on objec�ves, leveling the playing field for a product like sweet potatoes vis-a-vis cassava. A cassava Shi� from distor�ve measures to compe��ve agricul- farmer receives more than double the support of what a ture policy support. Given that an overwhelmingly large tomato farmer receives in a per hectare bases and more share of Mozambique’s agriculture support is MPS (or than 4 �mes the support a sweet potato farmer recei- coupled to the produc�on of specific agriculture ves, thus making a simple plate of food—as defined by products), a transi�on plan (including a fiscal plan) for the WFP “Coun�ng the Beans” methodology—costlier agriculture to move towards a more compe��ve policy ¹³. Furthermore, Climate Smart Agriculture (CSA)¹⁴ and support environment is very much needed. In fact, Nutri�on Smart Agriculture (NSmartAg)¹⁵ technologies Mozambique will likely be engaging in MPS reduc�on and prac�ces should be integrated into farmer input and commitments in agriculture trade agreements such as technology support incen�ves, to promote produc�vity the Africa Con�nental Free Trade Area (AfCFTA), so a growth, and fulfill environmental and nutri�on objec�- complementary trade agenda is needed to support sma- ves. Moreover, decoupling producer support from speci- llholders of protected agriculture products transi�on to fic agriculture products would enable farmers to make face market prices and take advantage of trade ¹². The produc�on decisions mainly on market opportuni�es formula�on of an appropriate sector strategy (PEDSA 2) (and not on the level of public sector support). and investment plan (PNISA 2) are good opportuni�es to 8 Goyal, Aparajita; Nash, John. 2017. Achieving Better Results: Public Spending Priorities for Productivity Gains in African Agriculture. Africa Development Forum;. Washington, DC: World Bank and Agence Francaise de Développement. World Bank. https://openknowledge.worldbank.org/handle/10986/25996 License: CC BY 3.0 IGO 9 López, R., and G. I. Galinato. 2007. “Should Governments Stop Subsidies to Private Goods? Evidence from Rural Latin America.” Journal of Public Economics 91:1071-94. 10 Lopez, Ramon. Under-investing in public goods: evidence, causes, and consequences for agriculture development, equity and the environment. Journal of Agriculture Economics, Volume 32, Issue 1. January 2005: https://onlinelibrary.wiley.com/doi/full/10.1111/j.0169-5150.2004.00025.x 11 World Bank. World Development Report 2001: https://elibrary.worldbank.org/doi/pdf/10.1596/0-1952-1606-7 12 An update to the World Bank’s 2006 Diagnostic Trade Integration Study (DTIS) is under preparation and is expected to take on these questions in more detail. 13 Based on an extrapolation from the World Food Programme (WFP)’s measurement of the cost of a minimum diet globally. This methodology defines a simple plate of food to consist of pulses, a local carbohydrate—such as rice, bread, maize meal—vegetable oil, tomatoes, onions and water. https://cdn.wfp.org/2018/plate-of-food/ However, Mozambique has not yet made it into the database and this qualitative assessment assumes that maize will be considered part of Mozambique’s plate of food. 14 For a definition and approach to CSA, see: https://www.worldbank.org/en/topic/climate-smart-agriculture 15 For a definition and approach to NSmartAg see: https://www.worldbank.org/en/topic/agriculture/publication/nutrition-smart-agriculture-when-good-nutrition-is-good-business 4 Introduc�on 1. This report assesses agriculture policy support es�ma- those policies/programs). tes in Mozambique. These es�mates are the monetary value assigned to different agriculture support policies 3. Agriculture support es�mates are also expected to and programs using the OECD methodology¹⁶ for 2018. inform Mozambique’s upcoming trade nego�a�ons on The objec�ve of undertaking this assessment is to agriculture and food products in the Africa Con�nental support the Government in reviewing its agriculture Free Trade Area (AfCFTA), the Southern Africa Develop- policies and programs, and to: (a) provide new es�mates ment Community (SADC), and other interna�onal trade and a new approach to assess sector support for policy agreements. These es�mates enable Mozambique to decision-making; (b) allow for benchmarking agriculture benchmark against South Africa and Angola for the level support policies with a large global database of coun- and composi�on of agriculture support, which is key to tries using the same es�mate methodology; and (c) help successfully nego�a�ng agriculture trade agreements kickstart a policy dialogue on realigning agriculture and developing policy reforms that enhance agriculture policies and programs in Mozambique towards greater trade compe��veness. Notably, this assessment builds sector compe��veness, food security and nutri�on on the Food and Agriculture Organiza�on’s (FAO) recent outcomes, and climate sustainability. support to Mozambique, which included budgetary data collec�on as part of an analysis of agriculture price 2. Previous work in other developing countries has shown distor�ons. This report fills exis�ng coverage and price policymakers the value of using such es�mates in a data gaps, expanding the scope of assessment from a process of transforma�on of the agriculture sector. The public expenditure review to a comprehensive review of OECD methodology a complete picture of all public agricultural support¹⁹. Given the current fiscal constra- policies and programs suppor�ng agriculture and food int faced by Mozambique and the need to grow its consump�on, bringing the support from taxpayers and economy, there is a window of opportunity for the consumers alike. The advantages of using this methodo- Government of Mozambique to gradually open up the logy are that: (a) it provides a systema�c view of agricul- trade of agriculture inputs and products, while shi�ing ture support policies, programs (not limited to the more public support policies and programs towards more tradi�onal public expenditure reviews or rate of protec- targeted interven�ons that can achieve compe��veness �on), and incen�ves at different levels of the food objec�ves, as well as climate resilience and system, allowing to envision policy reforms to improve nutri�on/food security. sector compe��veness, reduce distor�ons and improve equality with trading partners; (b) given the large 4. As part of this assessment, four main ac�vi�es were number of countries using this same methodology to conducted between September 2020 and June 2021 as measure support es�mates, an immediate benchmar- the basis for the dra�ing of this report: king is possible across a large set of comparators¹⁷; and (c) it is simple and can be integrated into the agriculture Training of in-country technical experts on the public policy analysis conducted by the Government and recognized OECD agriculture support es�mate other stakeholders¹⁸. The methodology also has some methodology. In February 2021, the WB team disadvantages and limita�ons, mainly: (a) few African delivered a comprehensive training course (seven countries have carried out agriculture support es�mates modules) to build capacity on data collec�on, with it, meaning Mozambique can only benchmark processing, and analysis among public sector staff against South Africa and Angola; and (b) since the within the Ministries of Finance, Economy, and Agri- es�mates are based on the monetary value of budget culture and technical experts outside of the Govern- and price support, non-monetary support, like the quali- ment (independent consultants). The objec�ve of ty of policies, are not captured (for example, the the training was twofold: (a) to enable the na�onal methodology is able to iden�fy how much Government to update the es�mates every two policy/program support is invested in land administra- years following the OECD cycle to maintain bench- �on efforts, but not to qualify the impact (quality) of marking capacity; and (b) to help validate and 16 See methodology manual at: http://www.oecd.org/agriculture/topics/agricultural-policy-monitoring-and-evaluation/documents/producer-support-estimates-manual.pdf 17 At present, the OECD methodology for agriculture support estimates covers 109 countries. This includes OECD countries, non-OECD EU Member States (subject to data availability), and a number of developing countries where monitoring is done by the OECD, IADB, and FAO’s MAFAP unit. The 54 countries monitored by the OECD are Argentina, Australia, Brazil, Canada, Chile, China, Colombia, Costa Rica, the European Union (Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Poland, Portugal, Spain, Slovakia, Slovenia, Sweden, the United Kingdom), India, Indonesia, Iceland, Israel, Japan, Kazakhstan, Korea, Mexico, New Zealand, Norway, the Philippines, the Russian Federation, South Africa, Switzerland, Turkey, Ukraine, the United States and Viet Nam. 18 As part of this assessment, a training of more than 15 public sector staff was undertaken to build capacity and allow for Government to update the estimates going forward. 19 Under FAO (MAFAP)’s support to Mozambique, data was collected for prices and Public Expenditures since 2009. 5 discuss policy op�ons based on the 2018 es�mates. percent in 2015, albeit lower than the 60 percent rate in 2003²⁰. Most of the poor (84.9 percent) are in rural Stocktaking of agriculture public support programs areas. The country’s GDP growth had a high average of and policies impac�ng the agri-food system and 7.9 percent between 2001 and 2015 but fell to about 3.3 technical analyses to produce quan�ta�ve es�ma- percent between 2016 and 2019. Even under declining tes of agriculture support to producers (PSE), consu- poverty rates, the total number of people living in pover- mers (CSE), and to general services and support to ty has grown in the past few years, as popula�on growth agriculture (GSSEs). This ac�vity also iden�fied outpaced GDP growth, and is expected to dras�cally specific commodi�es and classified the support per increase in 2020 due to the COVID-19 pandemic. Poverty OECD categories to assess the level of distor�on, levels are also significantly higher in the northern and while enabling an automa�c benchmarking with central regions of Mozambique, which have larger popu- other countries. The WB team collaborated with the la�ons and are more distant from major urban centers trained staff to undertake a policy inventory to gain and economic hubs. experience in the produc�on of a detailed assessment on the nature and extent of public 6. The rural space is the backbone of the livelihoods for support. most of the popula�on. It also accounts for most of the country’s poor. While the share of the popula�on that Discussion of preliminary es�mates and op�ons for lives in urban centers increased from 25 to 35 percent policy and program reform with sector stakehol- between 1995 and 2017, more than half of the popula- ders: The team discussed and validated preliminary �on is projected to remain in rural areas through 2040. agriculture support es�mates with relevant policy- On the back of this trend is fast popula�on growth, par�- makers, private sector representa�ves, and other cularly among rural households in the northern and agri-food sector stakeholders in May 2021. This central regions, where on average 2.1 more children are presenta�on included benchmarked indicators of born per rural woman (6.6) than urban woman (4.5). agriculture support and dra� policy conclusions. Fast rural popula�on growth combined with a persistent dicators of agriculture support young age structure is adding an es�mated 450,000 youth to the (rural) workforce every year. Mozambique Database construc�on and ins�tu�onaliza�on of is projected to remain largely rural for this genera�on, future updates in Mozambique, to enable compara- making the focus on rural income growth impera�ve. bility with regional and global agriculture support es�mates. The database of agriculture support 7. Agriculture con�nues to represent the key economic es�mates for Mozambique is expected to feed ac�vity in Mozambique. Agriculture has a vast growth directly into the Government’s ongoing formula�on poten�al by virtue of the variety of agroecological zones of its second Agrarian Sector Development Strategy and strategic geographical posi�on that the country has (PEDSA 2) and its second Na�onal Agriculture Inves- (especially with the neighboring landlocked countries tment Plan (PNISA 2), its repor�ng for the African and the various export departure points). There are Union’s CAADP Biennial Review Scorecard, and about 4 million smallholder producers in Mozambique, other regional and global ini�a�ves targeted at and these account for approximately 98 percent of the capturing informa�on on Mozambique’s support to total workforce and produc�on in the sector, with the the sector (such as MAFAP, Agrimonitor, OECD and remaining 2 percent including micro, small, and medium others). and dra� policy conclusions. enterprises (MSMEs) and larger agribusinesses andcom- mercial farms. Even though 45 percent of the country is Country Context suitable for agriculture, less than 16 percent is currently cul�vated.²¹ 5. Mozambique is a low-income country of 29.6 million people located in Southeastern Africa. Mozambique 8. Although rural households depend mainly on agricultu- has a gross domes�c product (GDP) of approximately re income, they remain net food consumers. The rural US$12 billion and a GDP per capita of US$417, which is poor produce agriculture products largely for self- among the lowest in the world. Poverty was high at 48 consump�on, but they remain net food consumers, meaning that increases in food prices affect them nega- 20 World Bank. 2018. Poverty Assessment (Report Number 131218). 21 World Bank. 2020. Cultivating Opportunities for Faster Rural Income Growth and Poverty Reduction: Mozambique Rural Income Diagnostic. Overview Policy Report. 6 �vely. A study²² of increases in food prices in Mozambi- nearly endemic. Growth has been driven by conversion que show how this is translated in reduc�ons in food of its nonrenewable natural resources through mega- consump�on and increases in rural poverty. Therefore, project investments, with modest links to broader areas policies that seek to increase prices of food and agricul- of the economy. The country also faces challenges to the ture products do not have an overall nega�ve welfare sustainability of its renewable natural resources. Defo- impact on the poor smallholder farmer community, resta�on is high, 267,000 ha of forests have been lost while benefi�ng the rela�vely larger commercial annually for 2003–2013. This led to around 46 million farmers. tons of climate-change-causing CO₂ being emi�ed every year into the atmosphere, represen�ng 43 percent of 9. Economic expansion in agriculture yields the highest Mozambique’s overall greenhouse gas (GHG) emissions . impact on poverty reduc�on. The sector’s poten�al Deforesta�on is mostly driven by expansion of shi�ing con�nues to be challenged by low produc�vity levels, agriculture, contribu�ng to land degrada�on, water mostly due to low input intensity and technology adop- scarcity, and climate vulnerability. �on, limited provision of agricultural services, coupled with high seasonality in produc�on and increasing 11. Mozambique is ranked the third most vulnerable coun- climate vulnerability. Simula�ons show that growth in try to climate change in Africa. Large areas of the coun- agriculture would decrease poverty and inequality over try are exposed to tropical cyclones, droughts, and three �mes faster than growth in any of the other river/coastal storm surge flooding. This vulnerability is sectors²³. In addi�on, access to finance, quality assuran- heightened by the country’s 2,700 km of coastline and ce, compe��veness, and value addi�on, together with socioeconomic fragility. About 60 percent of the popula- general integra�on along value and supply chains, con�- �on lives in low-lying coastal areas, where intense nue to be persistent challenges that limit the full poten- storms from the Indian ocean and sea level rise put �al of the sector’s growth. At the same �me, agriculture infrastructure, coastal agriculture, key ecosystems, and plays a cri�cal role in ensuring food security. Rather than fisheries at risk. As the intensity of these storms increa- maximizing profit, the produc�on choices of most small- se, the impacts are star�ng to also be felt inland. Access holders is focused on food security, yet most households to markets, already a challenge for many rural produ- in the bo�om 40 percent of income produce below cers, is becoming increasingly difficult a�er disasters hit. subsistence level, being net food consumers. A structu- As 70 percent of the popula�on depends on climate- ral transi�on from agricultural employment to employ- sensi�ve agricultural produc�on for their food and liveli- ment in industry and services, which characterizes the hoods, increased frequency and intensity of storms, development process in all countries, would not be droughts, and floods are likely to put pressure on possible in the absence of rising agricultural produc�vity agricultural income and food security. Historic climate rates without endangering food security²⁴. trends show average temperatures have increased 1.5- 2°C (1961–2010), and future climate projec�ons in 10. The country is richly endowed with natural resources Mozambique show more marked temperature increases but has not been able to effec�vely translate these into in the interior, southern, and coastal areas. Associated sustained poverty reduc�on. Mozambique has ample variability in rainfall and increase in droughts are expec- arable land, water, mineral, and energy resources, inclu- ted to lead to decrease in crop yields, par�cularly for ding natural gas offshore. Its substan�al natural capital drought-sensi�ve crops. As agriculture becomes less includes 36 million ha of arable land and 32 million ha of produc�ve, and less land area is available due to increa- natural forests. Its long coastline, the 4th longest in sed flooding, more land needs to be cleared, increasing Africa, harbors some of the most spectacular coral reefs the already high rate of deforesta�on and exacerba�ng in the world and several highly produc�ve estuaries. The the problem of land degrada�on and temperature rise. country has outstanding terrestrial, freshwater, marine, With the increase in number of hot days, there is an and coastal species biodiversity, coun�ng more than upsurge of crop and livestock pests and diseases as well 10,000 species, 10 percent of which are endemic or as forest fires, leading to increased forest degrada�on. 22 World Bank (2018). Who wins and who loses from staple food price spikes? Welfare implications for Mozambique. Policy Research Working Paper 8612. https://openknowledge.world bank.org/bitstream/handle/10986/30580/WPS8612.pdf?sequence=1&isAllowed=y 23 World Bank. 2020. Cultivating Opportunities for Faster Rural Income Growth and Poverty Reduction: Mozambique Rural Income Diagnostic. Overview Policy Report. 24 World Bank. 2019. Agrarian Sector Transformation: a Strategy for Expanding the Role of the Private Sector. 25 Intended Nationally Determined Contribution (INDC) for Mozambique: https://www4.unfccc.int/sites/ndcstaging/PublishedDocuments/Mozambique%20First/MOZ_INDC_Final_Versi on.pdf 26 World Risk Index, 2016 apud IMF, 2018. Republic of Mozambique: Selected Issues. 7 Coastal resources are also affected both by natural disas- February–September 2021 FEWS NET³⁰ projec�on for ters and increasing temperatures, damaging ecosystems Mozambique is that there will be an increase of 14 that sustain ocean life and fisheries such as coral reefs, percent of the popula�on that will be living in areas mangroves, and seagrass. Warming and acidifying under crisis or worse food security condi�ons, bringing oceans cause loss of revenue from tourism and fisheries. the total number of people in this category of food inse- As ocean-atmospheric condi�ons con�nue to change, curity to 7.8 million (or 24.6 percent of the total popula- larger altera�ons in pa�erns of species richness, chan- �on of the country). The addi�onal 1.4 million poor in ges in fisheries community structure and ecosystem Mozambique is due to the growing conflict in the north func�ons, and consequen�al changes in marine goods as well as the slowdown in economy ac�vity³¹. The nega- and services are expected.²⁷ The risk of declining fish �ve impacts on income are expected to be felt rela�vely stocks posed by warming is compounded by overfishing, more in urban and peri-urban areas, where social distan- which makes fisheries more vulnerable to warming, and cing measures and business closures are having the con�nued warming will challenge efforts to rebuild greatest impact. The pandemic is also likely to exacerba- overfished popula�ons. te the fiscal situa�on and availability of public budget going to the sector as well as pre-exis�ng factors of fragi- 12. The gender gap in agriculture is extensive. Rural women lity and widen inequali�es across the country. The in Mozambique face large constraints in accessing spa�al distribu�on of poverty is skewed, it is almost essen�al produc�ve resources and services, technology, twice as high in rural as in urban areas and inequality market informa�on, and financing. They are underre- between rural and urban areas is increasing. presented in local ins�tu�ons and governance mecha- nisms and tend to have less decision-making power than Sector Context men. Prevailing gender norms and discrimina�on o�en lead to excessive work burden, and much of their labour 14. The contribu�on of agriculture to the Mozambican remains unpaid and unrecognized. Female par�cipa�on economy has been mixed. Although it was the second in the labour force is rela�vely high at around 80 percent largest sector contributor, with an average contribu�on but women are dispropor�onately concentrated in of 23 percent to GDP during the period 2013 to 2017, subsistence agriculture and the informal sector. Recent the agricultural sector’s annual growth rate has been data from two WB projects²⁸ in Mozambique implemen- low and erra�c in recent years (1.9 - 4.3% per annum), �ng matching grant schemes (MGS) in the agriculture and well below the target annual growth rate of 6 and fisheries sectors show that women benefit less from percent established under CAADP. This is because of low these schemes compared to men²⁹. Gender-specific agricultural produc�vity influenced by: (i) low use of obstacles put female farmers at a significant disadvanta- improved inputs; (ii) inadequate agricultural support ge. Improving gender equity in the agriculture and fishe- services, including extension, research and financial ries sectors would not only empower women to achieve services; (iii) high reliance on variable rainfall in predo- their highest economic poten�al but also help reduce minantly rain-fed agriculture; (iv) unsustainable land use poverty and food insecurity. prac�ces, such as widespread slash and burn agricultu- re, resul�ng in significant threats to the sustainability of 13. Due to the COVID-19 pandemic, it is expected that a natural resources, par�cularly soil and water, exacerba- sizable number of Mozambicans will fall back into �ng low produc�vity levels; (v) limited accessibility to poverty. Mozambique’s already difficult poverty situa- input and output markets, especially in the northern and �on is expected to be aggravated further. The 27 World Bank. 2019. Climate Change and Marine Fisheries in Africa: Assessing Vulnerability and Strengthening Adaptation Capacity. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/33315. License: CC BY 3.0 IGO. 28 Agriculture and Natural Resources Landscape Management (SUSTENTA, P149620) and South-west Indian Ocean Fisheries Governance and Shared Growth Project 1 (SWIOFish1, P132123). 29 Within the context of the Agriculture and Natural Resources Landscape Management (SUSTENTA) project, only 14 percent of the commercial smallholder farmers (Pequeno Agricultor Comercial Emergente, PACE) and 13 percent of smallholder farmers (PA) benefitting from the MGS are women. In the fisheries sector, only 29 percent of the beneficia ries of the Mais Peixe mechanism are women, and, on average, receiving smaller grants, totalling 22 percent of the total budget. These numbers refer to data collected from the beginning of these projects up to November 2020. 30 The Famine Early Warning Systems Network is a leading provider of early warning and analysis on food insecurity. See: http://www.fews.net/mozambique. 31 Simulations done by the World Bank’s Poverty and Equity Global Practice of the potential short-term effects of the COVID-19 shock on income and consumption provide a first order approximation of the distributional impacts on household welfare. A hypothetical reduction of 10 percent in consumption across all rural households would increase poverty from 50.7 percent (baseline rate projected for 2020) to 56.6 percent. This translates into 1.4 million more Mozambicans slipping below the poverty line. This scenario would wipe out the gains in poverty reduction achieved in the last 5–6 years, underscoring the high levels of vulnerability among rural households. Limiting the shock to urban areas and workers in sectors at high risk translates into a 2.1-percentage point increase in poverty (from 32 to 34.1 percent), or 250,000–300,000 newly urban poor. More information on the impacts of COVID-19 and the response of the Government of Mozambique (GoM) can be found in annex 5. 8 central regions; road networks provide access to only products and services. Also, limited funds were in part about 33 percent of the rural popula�on; (vi) lack of due to the withdrawal of development partners from formal land property rights; (vii) lack of other key rural the funding government ac�vi�es, and to invest in infrastructure (par�cularly storage, water storage and Mozambique, resul�ng in a decrease in foreign direct irriga�on, with only small area under irriga�on (only investment (FDI) levels from an average of 4.8 billion about 3 percent of the cul�vated area and poten�ally USD per year during the period from 2011 to 2015, to irrigable area); and (viii) fragmenta�on of ins�tu�onal 3.1 billion USD in 2016, and 2.3 billion USD in 2017. This arrangements and roles, at central and sub-na�onal slowing and erra�c macro-economic performance has levels. adversely affected Government revenues and a fiscal imbalance, and a decrease in external assistance and 15. GDP growth decelerated to 3.8% in 2016 and 3.7% in public expenditure for all sectors and func�ons of 2017. During the 2011 – 2015 period, Mozambique’s Government. growth in gross domes�c product (GDP) was amongst the highest in Sub-Saharan Africa (SSA), averaging 7 16. However, the contribu�on of agriculture to the percent per year. In subsequent years, the scenario economy did not change significantly and its contribu- changed to a downward trend, mainly due to an econo- �on to GDP remained stable at about 23% during the mic crisis provoked by unsustainable debt. Addi�onally, period 2013 - 2017 (Table 1). Apart from service sector, annual average infla�on increased from 3.6% in 2015 to which is composed of several economic ac�vi�es/sub- 18.0% in 2016, decreasing slightly to 15.5% in 2017. sectors, agriculture is the main contributor to the GDP. Moreover, small and medium-size enterprise profitabili- The rela�ve importance of the agricultural sector is even ty levels, and capacity to generate employment, have greater when its linkages to other sectors (industry, also decreased. The balance of payments for the current manufacturing and services) are taken into considera- account fluctuated from a nega�ve 2.2 billion USD in �on, and which are directly driven by the agricultural 2011, to a nega�ve 498 million USD in 2017. This change sector, as well as by the fact that approximately 80% of was mainly due to a decrease in imports, influenced by the total labor force in the country is employed in limited availability of funds for purchasing foreign agricultural or related ac�vi�es. Table 1. Structure of the Economy and Sector Contribu�ons to GDP (2013 – 2017) Sector 2013 2014 2015 2016 2017 Agriculture 24 23 23 23 21 Manufacturing 9 9 9 9 9 Industry. 8 10 11 11 16 Services 59 58 57 57 54 Source: INE (2019) 17. Agriculture is the largest economic sector in Mozambi- land is currently under cul�va�on. In the 2013/2014 que (see Table 1), and more so, when considering direct agricultural season, there were about 4 million farmers and indirect linkages with other key sectors/ac�vi�es. in Mozambique, of which 99% were smallholders (with On average, the agriculture sector has accounted for average farm size of 1.3 ha.), with only 1% medium- and 23% of direct GDP in the last five years and employs large-scale commercially oriented farmers involved in about 80% of the labor force. However, the majority of compe��ve value chains, primarily for cash crops (see the popula�on is engaged in smallholder, rain-fed, Table 1.2). These features reveal important implica�ons subsistence agriculture which frequently suffers from for the roles of the public and private sectors working climate-induced shocks, with significant nega�ve together to further develop the sector, and especially in impacts on overall economic growth and poverty reduc- the management of the state agricultural budget. �on. Only 16% of a total of 36 million hectares of arable 9 Table 2. Mozambique farm typology Farmer category Number % Number of farmers Small farmers (thousand) 3,999 98.91% Medium farmers (thousand) 44 1.08% Large farmers 436 0.01% sand) Total (thous 4,043 100.00% Cul�vated area (ha) Small farmers (thousand) 5,207 96.69% Medium farmers (thousand) 117 2.17% Large farmers (thousand) 61 1.14% Total (thousand) 5,386 100.00% Source: IAI 2014 18. The predominance of smallholder farmers relying Mozambique has a poten�al to irrigate 3 million hecta- mainly on rain-fed agriculture, using tradi�onal, low res enabling increased produc�vity and diversifica�on. produc�vity agricultural technologies, has significantly However, only about 180,000 hectares (6%) are equip- limited the performance of the agriculture sector. The ped with irriga�on infrastructure, and only about 50% of annual growth rate of the sector has been erra�c and this infrastructure is currently fully opera�onal. Thus, significantly lower than the established Malabo growth only about 3% of the country’s irriga�on poten�al is target (6% per year) and PNISA target (7% per year) currently being used. fluctua�ng from 1.9% in 2013 to 4.3% in 2017. This fluctua�on partly reflects the climate and precipita�on 20. The recent growth in commercial agriculture and out- dependency of the agricultural sector, which implies the grower schemes, from a low base, points to the need for the expansion of climate resilient agricultural country’s untapped agribusiness investment poten�al. technologies and low-cost irriga�on infra- Emerging value chains include poultry, soy, sesame and structure/schemes. cashew, and there is significant scope to intensify and expand sustainable cul�va�on of agricultural land and 19. Poten�al and Sources for Expanded and Diversified domes�c food processing. Thriving value chains in Growth. Mozambique has favorable natural condi�ons agriculture and forestry could form the backbone of the for intensifying and diversifying its agricultural produc- rural economy by crea�ng jobs, increasing rural inco- �on and value-chain development in the majority of the mes, strengthening food security, and facilita�ng be�er country through increased produc�vity and nutri�on³³. The realiza�on of this agricultural and agribusiness-driven investment. Based on the recent WB value-added poten�al will require an expanded role of study, the main sources of agricultural income include:³² an inclusive private sector, catalyzed by enhanced and produc�vity growth in exis�ng food and cash crops; appropriate agricultural policies/regula�ons, ins�tu�o- expanded area and commercializa�on levels, enabled by nal reforms and priori�zed public investment³⁴. Further- increased market integra�on; a shi� toward high value more, as per the WB’s Enabling the Business of Agricul- crops (especially co�on, sesame, tobacco and sugar ture report (2019)³⁵, Mozambique performs be�er than cane) and animal products (e.g., poultry); and expanded the Regional SSA average for a number of agribusiness rural infrastructure (especially irriga�on and sector indicators, which bodes well for a reform agenda rural/feeder roads). Irriga�on has the poten�al to signi- towards further agriculture commercializa�on. ficantly enhance smallholder agricultural produc�vity. 32 Refer to the WB report, “Mozambique Rural Income Diagnostic” study (2019). 33 There are a series of value chain studies being carried out by the WB-supported Let’s Work Program, including: Cashew Value Chain Development Strategy; Cassava Value Chain Strategy; and Plantation Forestry Value Chain Strategy. The findings of these studies illustrate the potential for expanded agricultural growth, and the main types of constraints to be addressed. 34 There is an on-going parallel study on: Private Sector Strategy for the Agricultural Sector (draft report, March, 2019). This report integrates relevant emerging findings and recommenda- tions from this parallel study. 35 See: https://eba.worldbank.org/content/dam/documents/eba/MOZ.pdf 10 21. Low agricultural produc�vity is a binding and dominant 22. Overall, the performance of the agricultural sector has constraint to Mozambique’s economic growth and been erra�c and below expecta�ons/targets in rela�on poverty reduc�on. The country’s agriculture produc�vi- to sectoral growth rates, reduc�on in rural poverty, ty levels are lower than the average for low- income increased employment, increased produc�vity, commo- countries in Southern Africa, par�cularly for maize and dity diversifica�on, and compe��ve value chain develo- rice, key food crops. Key constraints to realizing pment. Annex A highlights these indicators and targets Mozambique’s significant agricultural sector and rural and their corresponding erra�c performance. While income growth poten�al (in produc�on and value-chain establishing a�ribu�on of this erra�c performance is development) include:³⁶ always a challenge, these findings highlight structural constraints in the sector and the serious challenges Low (but growing) levels of crop produc�vity, for involved in ensuring appropriate and consistent agricul- both food and cash crops, including low input tural policies and sound agricultural public expenditure. usage/intensity (of improved seeds, chemical fer�li- zers): less than 3% of farmers use improved crop Overview of Agricultural Support in Mozambique varie�es; less than 5% of farmers use fer�lizers; less than 9.5% of farmers used animal trac�on in 2014; 23. Over the last two decades, Mozambique has witnessed low and declining public spending on agriculture. The Inadequate agricultural public goods and services, average share of agriculture in the na�onal budget was including agriculture research and extension servi- slightly above 4.0 percent from 2010 to 2014, and fell to ces; there are only 1,200 agricultural extension 4 percent in the subsequent five-year period (2015- officers employed by the public sector, resul�ng in a 2019)³⁷ ³⁸. Over the 2008–2018 period, Mozambique high farmer to extension officer ra�o; this is exacer- ranked half way among SSA countries in terms of the bated by low technology adop�on rates by most share of agriculture in total public expenditure, inves�ng farmers; less than half of the New Partnership for Africa’s Develo- pment (NEPAD) target of 10 percent (Fig. 1)³⁹. In addi- Inadequate agriculture risk management mecha- �on to the need for greater public investment, is also a nisms and strategies, including high reliance on varia- heightened need to improve the effec�veness and ble rainfall in predominantly rain-fed agriculture, efficiency of public spending in the current fiscal envi- with increasing climate change threats; Mozambique ronment. Sector spending as a share of agriculture is ranked the third most vulnerable country to clima- GDP—a rough indicator of investment effec�veness-was te change in Africa; 14.8 and 19 percent in 2017 and 2019 respec�vely, as reported by Mozambique to the CAADP Biennial Llack of formal land property rights, limited access to Reviews⁴⁰. With disaggregated informa�on on the com- finance (less than 5% of smallholders), and low levels posi�on of public spending limited to just one year and and rates of agricultural investments and economic the absence of greater data coverage, assessments of diversifica�on; and investment trends and efficiency are not possible. Nota- bly, no Agriculture Public Expenditure Reviews (AgPERs) fragmenta�on of ins�tu�onal arrangements and have been conducted in Mozambique since 2007, roles, at central and sub-na�onal levels (further leading to large evidence gaps in the understanding of detailed below). public support to the sector⁴¹. 36 Many of these constraints are identified in the recent Rural Income Diagnostic Study (WB, 2019). 37 Source: WB Africa Agriculture Policy Inventory (2021). Agriculture’s share of the national budget declined from 1.10 percent in 2013 (US$702 million) to 0.41 percent (US$544.0 million) in 2015. It is important to note that the budget allocations for the agriculture sector not only fall under the Ministry of Agriculture (MINAGRIP), but also under the Ministries of Commerce, Industry, and Transport. World Bank (2017). “Republic of Mozambique: Selected Policy Notes for Incoming Administration of Mozambique”. 38 Preliminary FAO estimates show that this share rose then to 0.5 and 0.9 percent in 2018 and 2019 respectively. MAFAP Presentation to MADER, October 2020.. 39 IFPRI, 2019. 40 Note: The authors calculated amounts for public expenditure on agriculture to be $1.47 billion and $1.66 billion in 2016 and 2018 by multiplying share of agriculture GDP (CAADP AATS Scorecards) by agriculture GDP (WDI). In absolute terms, this would indicate a large jump in resources allocated to the sector relative to 2014 and 2015. 41 At the time of the last AgPER (2007), total the investment budget was overwhelmingly directed towards irrigation projects (70%) and mechanization (21%) largely due to the priorities of external donors. The spatial concentration of these investments was also quite concentrated and did not reflect overall agricultural potential. A large portion of agricultural investment was off budget entirely, being funded from various external sources. Also, a huge amount of public expenditure, both on and off budget, is devoted to improving roads, bridges and railroads, expenditures that directly benefit both producers and consumers by bringing down the cost of transporting both inputs and outputs. https://openknowledge.worldbank.org/bitstream/handle/10986/7648/397100v20ER0P01disclosed0Feb0602008.pdf?sequence=1&isAllowed=y 11 Figure 1: Share of Government Agriculture Expenditure in Total Public Expenditure (%), 2008–2018 Annual Average Level (%) Sierra Leone Niger Nigeria Kenya Malawi Liberia Mali Senegal Madagascar Uganda Côte d'Ivoire Guinea Seychelles Egypt Ethiopia Burkina Faso Zambia Benin Rwanda Togo Cameroon Cabo Verde Morocco Zimbabwe Gambia Namibia Cent. Af. Rep. Eswa�ni Tanzania Chad Mauri�us Botswana Ghana Comoros Angola Lesotho S. Tome & Principe Mozambique Guinea-Bissau Burundi South Africa Congo, Rep. Mauritania Sudan Equatorial Guinea South Sudan Annual avg. level (2008-2014) Annual avg. level (2014-2018) CAADP 10% target Source: ReSAKSS based on IFPRI (2015), World Bank (2019), and na�onal sources. Note: Every Increment on the Y-axis represents 2 percentage points. 24. The WB conducted an Agriculture Public Expenditure GDP es�mated at 23% p.a. With respect to expendi- Review for the period 2013-2017, which has yielded the ture classifica�on, the main results are as follows: (a) following results: Recurrent and investment expenditure alloca�ons vary significantly across ministries; (b) Expenditure is Budgetary Cycle and Processes: The budgetary cycle o�en misclassified; and (c) The appropriate balance and processes in Mozambique are, in overall terms, between recurrent/investment, wage/non-wage, sound, providing the agricultural sector, and its and internal/external expenditure have to be deter- Ministries and Departments at central and provincial mined by each ministry and specific func�ons, based levels, with vital tools to ensure sound expenditure on efficiency-based benchmarks. Regarding the alloca�ons. Yet, two cross-cu�ng issues impede efficiency of agricultural expenditure, the results realizing the expected benefits of the management show that: (a) There are overall high budget execu- of the budgetary cycle and support processes, mana- �on rates (80%) in the agricultural sector (in part due ged by MEF, namely (a) capacity constraints, which to the expenditures having to do with recurrent items need to be addressed at various levels; and (b) uncer- like personnel and inputs, making them more predic- tainty regarding budgetary ceilings, which impact table that in other countries), and for internal vs. planning and priori�za�on. Furthermore, the review external funds. The �ming of disbursement is crucial found that the forward budget projec�ons were not with higher execu�on rates being “forced” to meet aligned with the planned investments under PNISA 1. end-of-year expenditure targets; (b) This pa�ern may suggest misalignment between donor and govern- Levels & Trends of Agricultural Sector Expenditures : ment procurement procedures, and higher budget Some of the key findings relevant for this policy unpredictability for external funds; (c) Provinces that review in terms of public expenditure levels and contribute a higher share to GDP are receiving rela�- trends are as follows: (a) Agricultural budgetary vely lower public expenditure in the sector; and (d) alloca�ons are erra�c and decreasing among all This misalignment suggests the need for MEF (at ministries (except MITADER); and (b) The budgetary central and provincial levels) to ensure appropriate alloca�on to the agricultural sector was well below criteria for the alloca�on of expenditure consistent the 10% expenditure target under the with the rela�ve importance of the sector in the MAPUTO/MALABO commitment, and misaligned respec�ve province. with the rela�ve importance of the sector’s share of 12 Expenditure on Selected Strategic Programs: Three and (c) internal funding sources are linked to impro- programs, namely agricultural research, extension ved revenue collec�on and are more predictable and irriga�on were analyzed in detail as they compri- than external funds. For agricultural expenditure se the engine for the transforma�on of the agrarian funded by donors, on-budget sources vary from sector. With respect to the Agricultural Research 58-68% and off-budget sources vary from 32-42%. Program, results reveal the following relevant The private sector share of agricultural finance is very aspects: (a) significant underfunding of agricultural small (varying between 5.5 – 7.5 % of total private research, about 0.43% of the agricultural GDP and sector financing). Although the agriculture sector has well below the KHARTOUM target⁴¹ of 1%; (b) a need the largest impact on poverty reduc�on, and makes a to explore appropriate public-private partnerships sizable contribu�on to GDP, the sector receives a for expanded agricultural research, especially invol- small share of the total private sector finance/credit. ving high value-chains; and (c) a low and shrinking Various constraints impede access to credit for capital investment share in agricultural research agricultural development (land security; collateral; public expenditure, coupled with limited opera�ng high interest rates). The agriculture sector ranks 4th funds, are constraining the poten�al and tangible in terms of Foreign DirectInvestment (FDI), despites benefits of highly specialized agricultural resear- its higher importance; a considerable share of FDI for chers. Regarding the Agricultural Extension Program, industry is agro-based. the results indicate the following: (a) Although - opera�ng funds are significant, there is no clear Assessment of Forward Agricultural Expenditure improvement in expected outputs and outcomes Alloca�ons: The Cenário Fiscal do Médio Prazo (e.g. adop�on rates; crop yields; $/adopter), per (CFMP) provides a good basis for budgetary planning PNISA assessment (2017); (b) There is a need, as in and is used to define the annual PES targets and the case of research, to explore appropriate public- provides an instrument to mobilize donor funding. private partnerships for expanded extension servi- ces, especially involving high value commodi�es/value-chains; and (c) There is a large dependence on external funding sources (about 70%), raising ques�ons about scalability and sustai- nability in providing improved extension services, and securing sustained increases in agricultural produc�vity. Finally, the results for the irriga�on program show : (a) that there has, and con�nues to be, significant underfunding of irriga�on, ranging from 2.5 to 25% of the original PNISA 1 budget (with a 25% share in 2017); (b) significant underfunding of agricultural irriga�on, except in 2017, primarily from external funds; and (c) a need to explore appropriate cost-recovery levels and public-private partnerships for expanded agricultural irriga�on infrastructure, especially involving high value crop produc�on and value chains. Financing of Agricultural Public Expenditures: Regar- ding the government budget, financing is mainly on-budget including for funds from other sources such as development partners. The results reveal that for On-Budget Financing, there is (a) erra�c financing levels and sources: Government (52-72% of total financing); External Loans (7-32%); and External Grants (8-20%); (b) a dominance of government reve- nues (about 70%) and increasing external borrowing; 13 Objec�ves of Agriculture Support Policies and Programs in Mozambique 25. A new Government took office in February 2020 a�er led by the WB for the Land Use Planning for Enhanced the general elec�ons. The new administra�on adopted Resilience of Landscapes in Mozambique (LAUREL, a Five-Year Government Plan 2020–-2024 (Programa P160760). It is expected that PEDSA II will include detai- Quinquenal do Governo, PQG) with a strong emphasis led investment programs (under a Na�onal Investment on promo�ng sustainable rural produc�ve development Plan, NAIP II) and that it will be aligned with the and a focus on the central and northern part of the approach of building resilience of vulnerable food- country, par�cularly in agriculture. The GoM’s strategic insecure rural households. vision is to integrate the promo�on of rural develop- ment with increased resilience and sustainability of 27. PEDSA II aspires to align government ini�a�ves from natural resources and lay the founda�on for an integra- sectors engaged in the development of the rural ted land use approach that recognizes the interdepen- economy in Mozambique, capturing synergies and dence between value chains in agriculture, forestry and harmonizing approaches. It also aspires to serve as a fisheries, and natural resources (soil, water, forests, and tool for mobilizing funding and coordina�ng interven- biodiversity). It seeks to increase rural households’ �ons from development partners, civil society, and the income while strengthening the resilience and sustaina- private sector. While it reflects priori�es from the PQG bility of these natural resources. More resilient rural 2020–2024, it iden�fies a series of complementary areas will simultaneously meet local needs (for example, interven�ons, with emphasis on cross-sectoral coordi- water availability for households and rural businesses) na�on. The PEDSA II prepara�on process has involved 11 while also contribu�ng to na�onal commitments and different government agencies across eight different interna�onal targets on climate change (NDC⁴², REDD+ ministries. The Ministry of Agriculture and Rural Develo- Strategy) and biodiversity (Na�onal Biodiversity Strategy pment (MADER) is leading the development of PEDSA II and Ac�on Plans, NBSAPs). with the Ministries of Land and Environment (MTA); Sea, Inland Waters, and Fisheries (MIMAIP); Industry and 26. With the aim of promo�ng integrated rural develop- Commerce (MIC), Minerals and Energy, Tourism and ment, the Government is developing the Agrarian Culture; Public Works, Habita�on and Water Resources Sector Strategic Plan 2021–2031 (PEDSA II, Plano Estra- (MOPHRH); and Economy and Finance (MEF)⁴³. PEDSA II tégico de Desenvolvimento do Sector Agrário II 2021- is expected to be approved by the Council of Ministers 2031). The main objec�ve of PEDSA II is to contribute to and the Agrarian Sector Coordina�on Commi�ee accelera�ng the growth and sustainable transforma�on (Comité de Coordenação do Sector Agrário, CCSA) by of the rural economy based on an improvement in the January 2022. incomes of rural families in line with the preserva�on of key ecosystem services. Ini�al key objec�ves include the 28. The full implementa�on of PEDSA II is expected to following: (a) increase the sector’s contribu�on to the deliver significant improvements in rural produc�vity, na�onal GDP; (b) substan�ally increase the produc�vity job crea�on, and sustainability, although it faces key of key agricultural crops and improve their compe��ve- challenges. Based on recent studies and analysis focu- ness; (c) increase rural household incomes; (d) create sed on the agrarian sector⁴⁴, PEDSA II iden�fies the jobs in agriculture, agro-processing, forestry, fisheries, following key issues: (a) weak produc�on sustainability aquaculture, nature-based tourism, and wildlife and resilience; (b) weak private sector par�cipa�on; (c) economy; (d) reduce chronic malnutri�on; (e) increase lack of sta�s�cal data, research and innova�on; (d) private investment into the rural economy; and (f) limited private sector investment and public financing; improve effec�veness of the management of natural (e) nega�ve food balance; (f) weak governance due to resources on which the rural economy depends. To lack of formal and structured value chains; and (g) weak achieve this objec�ve, PEDSA II is based on eight strate- intra and interins�tu�onal agrarian sector coordina�on. gic pillars (see Table 3 below). The GoM Program is adop�ng an approach supported by a mul�year effort 42 NDC = Nationally Determined Contribution; REDD+ = Reducing emissions from deforestation and forest degradation in developing countries, and the role of conservation, sustainable management of forests, and enhancement of forest carbon stocks in developing countries. 43 Government agencies involved within these line ministries include (a) National Sustainable Development Fund (Fundo Nacional de Desenvolvimento Sustentavel, FNDS); (b) National Directorate for Commercial Agriculture; (c) National Directorate for Family Agricultura; (d) National Forest Directorate (Direção Nacional de Florestas, DINAF); (e) National Administration of Conservation Areas (Administração Nacional de Áreas de Conservação, ANAC); (f) Blue Economy Development Fund (PROAZUL); (g) Institute of Cereals of Mozambique; (h) Energy Fund; (i) National Tourism Directorate; (j) National Planning and Budget Directorate; and (k) National Roads Administration (Administração Nacional de Estradas, ANE). 44 Cultivating Opportunities for Faster Rural Income Growth and Poverty Reduction (World Bank 2020); Republic of Mozambique Agrarian Sector Transformation: a Strategy for Expanding the Role of the Private Sector (World Bank 2019); Rationalization of Investments in Mozambique’s Agrarian Sector: Assessment and Emerging Strategies and Priorities (MADER 2020); Mozambique National Agricultural Investment Plan (PNISA): Assessment (MASA, 2019). 14 29. PEDSA II will be accompanied by an investment plan discussion with the Government and development part- (PNISA II). In its current form⁴⁵, PNISA II iden�fies over ners about financing PEDSA II include the WB, African US$1 billion in investments over 5 years through a series Development Bank (AfDB), UK Department for Interna- strategic pillars laid out in PEDSA II (see Table 3 below) �onal Development (FCDO), Japan Interna�onal Coope- and the financing gap (80 percent) is expected to be ra�on Agency (JICA), Interna�onal Fund for Agricultural covered by Government and donor resources in an Development (IFAD), among others. approximate ra�on of 2:1. Donors that have been in Table 3. PEDSA II Expected Strategic Pillars PEDSA II Expected Strategic Pillars Pillar 1: Agrarian Produc�vity and Compe��veness Pillar 2: Agrarian Markets Pillar 3: Agrarian Infrastructure Pillar 4: Food and Nutri�on Security Pillar 5: Natural Resources Pillar 6: Agrarian Ins�tu�ons Pillar 7: Gender Equity and Equality and Youth Engagement Pillar 8: Climate Change and Natural Disasters Source: PEDSA II (October 2021 draft version) . 30. The GoM has recognized the need to devote significant a�en�on to northern provinces. The Northern Integra- ted Development Agency (Agência de Desenvolvimento Integrado do Norte, ADIN) is a public ins�tu�on establis- hed in March 2020 with the mandate to promote inte- grated development in Mozambique’s northern provin- ces. ADIN’s tutelage was transferred in June 2020 from the Council of Ministers to MADER, highligh�ng the key role of rural development within the overall approach. ADIN will focus on boos�ng economic development in Cabo Delgado, Niassa, and Nampula, based on four main pillars: (a) humanitarian assistance, (b) economic deve- lopment, (c) community resilience, and (d) communica- �on. 45 No draft of PNISA II is under preparation along with PEDSA II. However, the Government did prepare an investment plan in 2020 (called PODERS – Sustainable Rural Economy Development Operational Program) that was never approved but which is serving as input to PNISA II. PODERS was not approved given the significant expected overlaps with PEDSA II, which the Government had decided to develop by the time PODERS draft was completedhas been shared, but only a Powerpoint dated December 2021.. 15 Conceptual Framework for Policy Review Methodology: Ra�onale and Coverage 33. There are at least three clear benefits to adop�ng this methodology for reviewing agriculture policies at a 31. Each year since 1987, the OECD has measured mone- global level: tary transfers associated with agricultural policies in a growing number of countries using a standard method. a. Monitoring and evalua�on of agricultural policies The OECD agriculture support es�mates were develo- developments: This includes policy reforms achie- ped in order to monitor and evaluate agricultural ved by countries over �me, through specific reform support policies and programs using a common and efforts (e.g., the U.S. Farm Bills and EU Common easy-to-use methodology for policy dialogue among Agriculture Policy (CAP) reforms), as well as progress countries, and to provide economic data to assess the towards achieving interna�onal commitments effec�veness and efficiency of policies. The es�mates agreed to by countries (EU, CAADP)⁴⁸. were mandated by OECD Ministers in 1987, and have since been calculated for the OECD and an increasing b. Establishment of a common base for policy dialo- number of non-OECD countries, and are widely referred gue: By using a consistent and compara�ve method to in the public domain. to evaluate the nature and incidence of agricultural policies, countries are able to engage in trade nego- 32. The objec�ves of agricultural policies in OECD countries �a�ons and common agriculture policy discussions have evolved over �me—from overcoming food shorta- (WTO, WB, IMF, and FAO). They are also useful for ges or surpluses in the post-war period to securing food farming and non-government organiza�ons, and safety, environmental quality, and preserva�on of rural research ins�tu�ons in the discussions on differen- livelihoods. Policy instruments have also changed, �ated impact of agriculture policies. Mexico, Colom- reflec�ng changes in domes�c poli�cal and economic bia, Central America and the Andean countries used se�ngs and, progressively, developments in interna�o- these es�mates to develop their transi�on into the nal economics. Given this diversity, the OECD has deve- FTAs with the U.S. and the EU. loped a methodology—referred to as PSE in the literature—to compute support indicators measuring c. Undertaking research on policy impacts: The data transfers to the agriculture sector and enabling compa- serves as an input into modeling to assess the effec- rability over �me and across countries⁴⁶ PSE indicators �veness and efficiency of policies in delivering the provide insights into the burden that agricultural outcomes for which they were designed and to support policies place on consumers (i.e., market price understand their effects on produc�on, trade, support) and taxpayers (budgetary transfers). This is the income, the environment, etc. While the indicators most widely and systema�cally used methodology to cannot by themselves quan�fy these impacts, the monitor support to the agriculture sector in the world. economic informa�on upon which they are based is The results, published annually, provide important an important building block for further analysis. The contribu�ons to the interna�onal policy dialogue on WB is undertaking an analysis with IFPRI at a global agriculture and trade⁴⁷. level, modeling the repurposing of agriculture support policies and programs towards climate change mi�ga�on/adapta�on objec�ves. 46 As it is neither affected by inflation nor the size of the sector, it allows comparisons in the level of support to be made both over time and between countries 47 OECD’s Producer Support Estimate and Related Indicators of Agricultural Support: Concepts, Calculations, Interpretation and Use (The PSE Manual). 48 This commitment stated that “agricultural trade should be more fully integrated within the open and multilateral trading system,”, and it called for OECD countries to pursue “a gradual reduction in protection and a liberalization of trade, in which a balance should be maintained as between countries and commodities.” Ministers also requested the OECD to develop a method to measure the level of protection in order to monitor and evaluate progress. 16 Figure 2: Coverage of OECD Methodology of Agriculture Support Es�mates Complete No data Par�al Source World Bank - Created with Datawrapper Note: The map represents all the countries using the OECD methodology with at least one year of es�mates for agriculture support. The OECD has tracked a subset of countries over mul�ple years. 34. There are strong advantages, but also some limita�ons, against South Africa and Angola, and (b) since the to using the OECD methodology for undertaking the es�mates are based on the monetary value of budget agriculture policy review for Mozambique. The advan- and price support, non-monetary support, like the quali- tages are that: (a) it provides a systema�c and integrated ty of policies, are not captured. As an example, the view of agriculture support policies and programs (not methodology is able to iden�fy how much limited to the more tradi�onal public expenditure policy/program support is invested in land administra- reviews or rate of protec�on); (b) given the large �on efforts, but unable to qualify the impact (quality) of number of countries using this same methodology, an those policies/programs. immediate benchmarking is possible across a large set of comparators⁴⁹ ; and (c) the methodology is simple and 35. This report produces indicators covering a range of can be integrated into the agriculture public policy agricultural support, and is expected to inform upco- analysis conducted by the Government and other ming trade nego�a�ons and policy reforms enhancing stakeholders⁵⁰. The methodology also has some disad- sector compe��veness and economic diversifica�on. vantages and limita�ons, mainly: (a) Only two African In par�cular, the indicators of support are expected to countries have carried out agriculture support es�mates be relevant to AfCTA trade nego�a�ons on agriculture with it, meaning Mozambique can only benchmark 49 At present, the OECD methodology for agriculture support estimates covers 109 countries. This includes OECD countries, non-OECD EU Member States (subject to data availability), and a number of developing countries where monitoring is done by the OECD, IADB, and FAO’s MAFAP unit. The 54 countries monitored by the OECD are Argentina, Australia, Brazil, Canada, Chile, China, Colombia, Costa Rica, the European Union (Austria, Belgium, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Poland, Portugal, Spain, Slovakia, Slovenia, Sweden, the United Kingdom), India, Indonesia, Iceland, Israel, Japan, Kazakhstan, Korea, Mexico, New Zealand, Norway, the Philippines, the Russian Federation, South Africa, Switzerland, Turkey, Ukraine, the United States and Viet Nam. 50 As part of this assessment, a training of more than 15 public sector staff was undertaken to build capacity and allow for Government to update the estimates going forward. 17 and food products. This es�ma�on will enable Mozam- consumers and taxpayers, arising from public policies bique to benchmark against trading partners and com- that support agriculture. This defini�on covers both parator countries like South Africa, in rela�on to the budgetary and non-budgetary expenditures such as level and composi�on of agriculture support. Given the credit concessions and direct subsidies (electricity, fuel, current fiscal constraint and the need to diversify its water, farm inputs). It also includes implicit support economy, there is a window of opportunity for the arising from border trade (tariffs, taxes) and domes�c Government of Mozambique to gradually open up the market measures (e.g., minimum support prices). Ove- trade of agriculture inputs and products, while shi�ing rall, the methodology enables a computa�on of total public spending towards more targeted interven�ons. transfers to producers (PSE), consumers (CSE), and gene- However, in the absence of comprehensive es�mates of ral services (GSSE) respec�vely, with a clear iden�fica- agriculture support, the evidence base for capitalizing �on of transfer sources (domes�c and interna�onal on this opportunity does not currently exist. taxpayers, consumers) (Fig. 3)⁵¹. The OECD methodology also allows the calcula�on of disaggregated PSE for each OECD Methodology: Technical Concepts and Cal- product considered. The different levels of support are cula�on reflected in the Producer Single Commodity Transfers (SCT), a measure of commodity-specific agricultural 36. According to the OECD methodology, agricultural policies indica�ng policy flexibility for producers in their support is defined as gross transfers to agriculture from choices of product mixes. Figure 3: OECD Methodology –Main Indicators of Transfers, by Source Taxpayers PSE Consumers Taxpayers TSE CSE Producers GSSE Taxpayers Source: Agricultural Policy and Monitoring OECD, 2020 37. The main indicators of support are grouped into three defined and computed. Annex B provides further details categories—producers, consumers, and general on classifica�on of support across OECD categories: support. Box 1 and 2 below show how indicators are 51 The PSE is an indicator that measures the annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, measured at the farm-gate level, arising from policy measures that support agriculture, regardless of their nature, objectives or impacts on farm production or income. The GSSE is a proxy for public support to agricultural public goods such as research and extension, agricultural education and some infrastructure investments closely linked to agriculture. It is defined as the annual monetary value of gross transfers arising from policy measures that create the public goods and the enabling conditions for the primary agricultural sector through development of private or public services, and through institutions and infrastructures regardless of their objectives and impacts on farm production and income, or consumption of farm products. 18 Box 1. OECD indicators of support to agriculture Indicators of Support for Producers Producer Support Es�mate (PSE): The absolute annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, measured at the farm gate level⁵² , arising from policy measures that support agriculture, regar- dless of their nature, objec�ves, or impacts on farm produc�on or income. The PSE includes market price support and budgetary payments. Specifically, PSE includes gross transfers from consumers and taxpayers to agricultural producers arising from policy measures based on current output, input use, area planted/animal numbers/receipts/incomes (current, non-current), and non-commodity criteria (considered one of the least distor�ve). Percentage PSE (%PSE): %PSE represents monetary gross transfers to producers as a share of gross farm receipts. As it is neither affected by infla�on nor by the size of the sector, it allows comparisons in the level of support to be made over �me, products, and between countries. %PSE is the OECD’s key indicator to measure support to agricultural producers, as it provides insights into the burden that agricultural support policies place on consumers (i.e., market price support) and taxpayers (budgetary transfers). Producer Single Commodity Transfers (producer SCT): The annual monetary value of gross transfers from consumers and taxpayers to agricultural producers, measured at the farm gate level, arising from policy measures linked to the produc- �on of a single commodity that the producer must produce to receive the transfer. Producer Percentage Single Commodity Transfers (producer %SCT): The commodity SCT as a share of gross farm receipts for the specific commodity. Indicators of Support to Consumers Consumer Support Es�mate (CSE): The annual monetary value of gross transfers from (to) consumers of agricultural commodi�es, measured at the farm-gate level, arising from policy measures that support agriculture, regardless of their nature, objec�ves or impacts on the consump�on of farm products. If nega�ve, the CSE measures the burden on consu- mers (implicit tax). Percentage CSE (%CSE): CSE as a share of consump�on expenditure (measured at farm gate) net of taxpayer transfers to consumers. It es�mates the transfers as a share of consump�on expenditure on agricultural commodi�es (at farm-gate prices), net of taxpayer transfers to consumers. The %CSE measures the implicit tax (or subsidy, if CSE is posi�ve) placed on consumers by agricultural price policies. Indicators of Support to General Services for Agriculture General Services Support Es�mate (GSSE): The annual monetary value of all transfers from taxpayers to policy measures and programs suppor�ng general agriculture public goods and services such as rural infrastructure, animal and plant health, research and development, promo�on of agriculture, agriculture schools, arising from policy measures that support agriculture, regardless of their nature, objec�ves and impacts on farm produc�on, income, or consump�on. The GSSE does not include any transfers to individual producers or ac�vi�es related to a par�cular agriculture commodity⁵³. Percentage GSSE (%GSSE): GSSE as a share of Total Support Es�mate (TSE). Indicators of Total Support to Agriculture Total Support Es�mate (TSE): The annual monetary value of all gross transfers from taxpayers and consumers arising from policy measures that support agriculture, net of the associated budgetary receipts, regardless of their objec�ves and impacts on farm produc�on and income, or the consump�on of farm products. Percentage TSE (%TSE): TSE transfers as a share of GDP. 52 The price paid to the farmer at the farm, which excludes transport costs to the market. 53 There are six main GSSE support categories and the amount of subsidies allocated under them is derived from public expenditure data. Considering the previous budget analysis made by FAO in Mozambique, we select each program according its characteristics and we classify it in the corresponding category (Agricultural research, public Infrastructure, Marketing and promotion, etc.). For example, subsidies under the program “Building and maintenance of rural roads" were considered under "Infrastructure GSSE category". Public resources of Instituto de Investigación Agronomica were considered under "Agricultural Research GSSE" category. 19 Box 2. Calcula�on of PSE for Mozambique Broadly, the PSE has two main components: market price support and budgetary alloca�ons. 1) Market Price Support (MPS) MPS is the annual monetary value of gross transfers from consumers and taxpayers to agricultural producers arising from policy measures that create a gap between the domes�c market price and the border price (without tariffs/import taxes) of a specific agricultural commodity, measured at the farm gate level. Policies crea�ng a price gap include domes�c mea- sures, such as administered pricing or market interven�ons. These policies include trade measures such as import tariffs, import quotas, tariff quotas, export subsidies, export taxes, as well as quan�ta�ve restric�ons on exports. In some cases, the gaps between domes�c and interna�onal prices are also explained by factors that are not strictly policy-related, e.g., deficiencies in physical infrastructure, inadequate informa�on, and weak market ins�tu�ons. MPS is financed by consu- mers through higher prices. In Mozambique, MPS is calculated based on the following informa�on: Period covered: 2018 Products covered: Cassava, tomato, pork meat, maize and sweet potato. These five commodi�es account for 65.7 percent of the total value of gross agricultural output (GAO) in Mozambique for 2018⁵⁴. For the purpose of the PSE es�ma�on, are treated as net imports (M)⁵⁵. Producer prices: These are average prices received by producers at the farm gate level. This informa�on has been provi- ded by a local consultant, sourced from producer surveys, farmer coopera�ves and the Na�onal Ins�tute of Sta�s�cs of Mozambique (INE) (See Annex C for technical details)⁵⁶. External reference prices: Average import/export prices were used for the products considered in this analysis⁵⁷. Prices were adjusted (added) with interna�onal transporta�on cost and other processing costs in order to make reasonable comparisons with domes�c prices⁵⁸. For all five products covered, we used average import unit prices (CIF) at the border adding transport cost to the produc- �on zone and subtrac�ng processing costs. Data for CIF prices was provided by FAOSTAT and transport and processing cost by surveys to local producers for 2018. Marke�ng margins: Marke�ng margins are es�ma�ons of processing and handling costs for a given commodity. Marke- �ng margin adjustment to the reference prices is required to compare them with domes�c prices measured at the farm gate. For products, margins data was provided by surveys to local producers. Price gap es�mates: The “zero price gap” was used when nega�ve gaps were obtained between producer prices and adjusted reference prices (farm level), as the es�mated nega�ve price gaps reflect factors other than agricultural policies. This adjustment considers transport costs from border to farm gate and the costs of processing farm products into expor- ted products. 2) Budgetary Support Budgetary support is funded by taxpayers (government revenues). Budgetary informa�on for 2018 was provided by FAO and complemented by line-item data sourced from the Ministry of Economy and Finance (MEF), the Ministry of Agricultu- re and Rural Development (MADER), and consump�on subsidies from the Na�onal Ins�tute of Social Ac�on (see Annex D for complete list)⁵⁹. 54 Source: FAOSTAT, 2020 and own estimation. 55 In the case of cassava—a thinly traded commodity—there is ambiguity on whether, on average, it is an import or export commodity for Mozambique. According to COMTRADE, for all years prior to 2018 Mozambique was a net importer (no data for 2019). According to FAOSTAT for all years Mozambique was a net exporter, but this is not official data. It is an estimate based on other sources. 56 In the case of producer prices, the arithmetic annual average (at national level) was considered. Source: Local consultant survey. 57 For a Representative Import Tariffs, the “Most Favored Nation Tariff” was considered for each product analyzed. Source: Tarifa de Pauta Aduanera. Diario de la Republica de Mozambi- que. 58 In the case of exchange rate, the arithmetic average “Sell” price was considered, as it better reflects the cost of US dollar to make local currency conversions. Source: Banco de Mozambi- que. 59 FAO AgPER data was complemented with other information directly from Ministry of Finance (that was not included in FAO exercise). 20 38. In Mozambique’s data-poor se�ng, the quality of price ble inputs—as having the strongest poten�al to distort informa�on collected is a poten�al limita�on of the agricultural produc�on and trade. During the 2017- OECD methodology. Like other measures used tocom- 2019 period, the effec�ve prices received by producers pute indicators of agriculture support⁶⁰ , the OECD were 6 percent higher than world prices, with the largest methodology has limita�ons associated with the availa- price gaps for sugar and rice. Correspondingly, Single bility, quality, and nature of market informa�on in gene- Commodity Transfers (SCT) represented above 50 ral, and prices in par�cular. Since an official source of percent of PSE and sugar and rice had the highest share producer prices and other parameters used in the analy- of SCT in commodity gross farm receipts. MPS is the sis did not exist, a survey of producers and exporters was main component of the SCT’s in most cases. On the conducted by the study team. To validate this data, the other hand, the expenditures financing general services survey results were reviewed by the Government’s tech- to the sector (GSSE) reached an annual average of nical staff and were found to have yielded credible price US$106 billion in 2017–2019, with financing of infras- levels within plausible bounds. The team’s previous tructure projects, agricultural knowledge and innova- experience in other countries has shown that the use of �on, and public stockholding accoun�ng for US$45 this methodology allows dialogue between par�es and billion, US$26 billion, and US$21 billion, respec�vely. the construc�on of be�er public policies, and there are incen�ves to systema�ze the genera�on of key informa- 41. The changes in the structure of support were rela�vely �on and develop a key public good. It is noteworthy that moderate over the last two decades, when averaged one of the results of these es�mates indicates an unde- over all countries covered by the methodology. During rinvestment in market informa�on systems in Mozambi- the 2017–2019 period, producer support represented que, despite its posi�ve externali�es for market develo- 11.7 percent of gross farm receipts (%PSE), a reduc�on pment. from 18.4 percent in 2000–-2002 (Fig. 4). Comparing the same periods, the share of the most distor�ng forms of Agriculture Support Estimates: Global Snapshot and transfers has declined slightly from 72 to 69 percent of Trends gross producer transfers in absolute terms. In terms of aggregate gross farm receipts, this share has declined 39. In the 2017–2019 period, the 54 countries monitored by from 13 percent in 2000–2002 to 8 percent in 2017- the OECD provided net total transfers of US$619 billion 2019. Notably, while distor�onary transfers based on to their agriculture sectors annually. According to the output are shrinking in rela�ve terms, those based on OECD’s Agriculture Policy Monitoring and Evalua�on unconstrained input use have increased. Among the Report (2020)⁶¹, the net transfers or total support to remaining forms of producer support, payments based agriculture (TSE) included US$708 billion of gross on areas planted, animal numbers, and historical para- support, offset by an implicit taxa�on of farmers worth meters not requiring produc�on are significant, accoun- more than US$89 billion in countries like Argen�na and �ng for 18 percent of all producer support. Notably, India, which used measures that depressed the domes- payments decoupled from current produc�on and �c prices of some commodi�es. US$425 billion of total therefore less distor�ng, have increased significantly transfers cons�tuted budgetary spending for various and represent 14 percent of all producer support support programs, and the rest was market price (Annex, Fig. 29). On average, rela�ve expenditures for support (MPS). About US$536 billion, comprising 72 GSSE (%GSSE) have declined as agricultural GDP has percent of TSE, was in the form of support to producers grown more rapidly. Conversely, the total support to (PSE). agriculture as a share of GDP (%TSE) has declined slightly over �me, mainly driven by the smaller rela�ve size of 40. Over half of producer support was provided via policy the sector within overall economies. instruments most likely to distort agricultural produc- �on and trade. The OECD methodology iden�fies support based on commodity output—MPS and subsi- dies linked to output or the unconstrained use of varia- 60 Four widely known measures are used in various studies to estimate support: the nominal rate of protection (NRP), the nominal rate of assistance (NRA), the effective rate of protection (ERP) and the effective rate of assistance (ERA). The NRP measures the increase in gross receipts from the sale of the commodity; the NRA measures the increase in gross receipts including support not linked to the sale of the commodity. The ERP measures the increase in the value added from the sale of the commodity, i.e. taking into account the price of inputs; the ERA measures the increase in value added from both the sale of the commodity and support not linked to the sale of the commodity. 61 OECD (2020), Agricultural Policy Monitoring and Evaluation 2020, OECD Publishing, Paris, https://doi.org/10.1787/928181a8-en 21 Figure 4: Agriculture Support Trends (54 Countries) 2000-02 2017-19 20% 100% 1.16 18% 1.14 1.2% 16% 80% 7% 1.12 1.0% 14% 6% 12% 60% 1.1 5% 0.8% 10% 1.08 4% 40% 0.6% 8% 1.06 3% 6% 0.4% 1.04 2% 4% 20% 0.2% 2% 1.02 1% 0% 0% 1 0% 0.0% PSE as % % poten�ally Ra� o o f prod u cer GSSE, TSE as % GDP o f rec eipts (%PSE) most distor�n g transfers* to bord er p rice (Prod u cer NPC) rela �ve to AgGV A Note: * Share of poten�ally most distor�ng transfers in cumulated gross producer transfers. Source: OECD (2020), "Producer and Consumer Support Es�mates", OECD Agriculture sta�s�cs (database), h�p://dx.doi.org/10.1787/agr-pcse-data-en. OECD and Emerging Economies: A Comparison dually (PSE) was nearly iden�cal in the OECD and in emerging economies, at 72 and 71 percent of the TSE 42. Despite a strong decline in the OECD area, producer respec�vely. However, OECD producer support accoun- support has con�nued to account for double the share ted for 17.6 percent of gross farm receipts (%PSE), twice of gross farm receipts, rela�ve to emerging economies, that of emerging economies at US$89 billion (8.5 albeit increasingly focused on achieving environmental percent), partly due to the implicit taxa�on of producers services. The numbers below show that overall there due to a large nega�ve MPS in Argen�na and India. The are substan�al varia�ons at the country and commodity %PSE indicator of producer support has trended upward levels in both groups (OECD and emerging economies). in emerging economies, growing from 4.2 percent, even During the 2017–2019 period, the total support to as it has declined from 29 percent in the OECD since agriculture (TSE) in OECD countries⁶² was US$319 billion 2000-2002 (Fig. 6, 7). The effec�ve prices received by and the corresponding figure for emerging economies⁶³ producers were 9 percent higher than the world prices, was US$295 billion. While TSE as a share of GDP had on average, but showed a declining trend over the last declined to nearly half of the 2000–2002 level in the three decades. In contrast, effec�ve prices were 5 OECD, it had only marginally declined in emerging percent higher than the world prices in emerging econo- economies. The support provided to producers indivi- mies, rising from 1 percent in 2000-2002. 62 The OECD total does not include the non-OECD EU Member States, nor Colombia which joined the OECD in April 2020. 63 The Emerging Economies total includes Argentina, Brazil, People’s Republic of China, Costa Rica, India, Indonesia, Kazakhstan, Philippines, Russian Federation, South Africa, Ukraine and Viet Nam, as well as Colombia which joined the OECD in April 2020 22 Figure 5: Agriculture Support Trends –OECD Countries 1986 -88 2000 -02 2017 - 19 40% 100% 1.5 8% 2.5% 35% 7% 80% 1.4 2.0% 30% 6% 25% 60% 5% 1.5% 1.3 20% 4% 40% 1.2 3% 1.0% 15% 10% 2% 20% 1.1 0.5% 5% 1% 0% 0% 1 0% 0.0% PSE as % % poten�ally most Ra�o of producer GSSE, TSE as % GDP of receipts (%PSE) d istor�ng transfers* to border price rela �ve to Ag GVA (Producer NPC) Notes: * Share of poten�ally most distor�ng transfers in cumulated gross producer transfers. Colombia became the 37th member of the OECD in April 2020. In the data aggregates used in this report, however, it is included as one of the 13 Emerging Economies. Source: OECD (2020), "Producer and Consumer Support Es�mates", OECD Agriculture sta�s�cs (database), h�p://dx.doi.org/10.1787/agr-pcse-data-en Figure 6: Agriculture Support Trends—Emerging Economies 1986 -88 2000 -02 9% 100% 1.06 5% 1.4% 8% 1.2% 80% 1.05 4% 7% 1.0% 6% 1.04 5% 60% 3% 0.8% 1.03 4% 0.6% 40% 2% 3% 1.02 0.4% 2% 20% 1% 1.01 0.2% 1% 0% 0% 1 0% 0.0% PSE as % % poten�ally most Ra�o of producer GSSE. TSE as % GDP of recepts (%PSE) distor�ng transfers* to border price rela�ve to AgGVA (Producer NPC) Source: OECD (2020), "Producer and Consumer Support Es�mates", OECD Agriculture sta�s�cs (database), h�p://dx.doi.org/10.1787/agr-pcse-data-en. 43. Single Commodity Transfers (SCT) accounted for more with MPS accoun�ng for the largest component in both than half of PSE in both OECD and emerging econo- groups. There was significant varia�on across commodi- mies; sugar remained among the most supported com- �es in the OECD, with domes�c prices for rice being modi�es in both groups. SCT represented about 51 more than twice the world price in 2017–2019, accoun- percent of total PSE in OECD and emerging economies, �ng for the largest share of gross farm receipts. Sugar, 23 sunflower, milk, and beef prices were 35 percent, 30 in India. Rapeseed, sugar, maize, rice and wheat had the percent, 13 percent and 13 percent above world prices. highest share of SCT in commodity gross farm receipts, In emerging economies, SCT witnessed a falling trend in while SCTs were nega�ve for barley, oilseeds, milk and recent years partly due to more nega�ve SCTs in India oats. and Argen�na and the extended direct income scheme Figure 7: Transfer to Specific Commodi�es (STC) -- OECD, 2017-2019 MPS Payments based on output Other SCT Wool Rapeseed Oats Maize Eggs Barley Wheat Sheep meat Pig meat Poultry meat Sorghum Soybeans Milk Beef and veal Sunflower Sugar Rice 0% 10% 20% 30% 40% 50% 60% % of commodity gross farm receipt for each commodity Source: OECD (2020), "Producer and Consumer Support Es�mates", OECD Agriculture. sta�s�cs (database) Figure 8: Transfer to Specific Commodi�es (SCT) – Emerging Economies, 2017-2019 MPS Payments based on output Other SCT Oats Milk Sunflower Barley Soybeans Eggs Beef and veal Sheep meat Pig meat Wheat Imported fruit and vegetables Poultry meat Rice Maize Sugar Rapeseed -20% -10% 0% 10% 20% 30% % of commodity gross farm receipt for each commodity Source: OECD (2020), "Producer and Consumer Support Es�mates", OECD Agriculture sta�s�cs (database). 24 44. The composi�on of support has shown a larger shi� nominal terms, with infrastructure financing recording a towards fewer distor�onary policies in the OECD, rela- small increase and expenditures on agriculture knowled- �ve to emerging economies. In contrast with the long- ge and innova�on growing by two thirds, and inspec�on term OECD decline in the share of transfers based on and control services also doubling (Annex, Fig. 29)⁶⁶. Fig. output and input use⁶⁴, the shares of less distor�ng 9 below illustrates the growth in the share of the agricul- forms of support such as payments decoupled from tural knowledge, inspec�on and marke�ng category commodity criteria but linked to environmental services (from 20.2 to 32.2 percent) and corresponding decline in and animal welfare objec�ves have grown⁶⁵. Over the the share public stockholding (from 22.5 to 1.6 percent) 2017–2019 period, they account for 3.5 percent of gross over the 1986–2019 period. farm receipts and a fi�h of PSE. GSSE had also grown in Figure 9: GSSE Composi�on in OECD Countries, 1986-2019 1986% 1998% 2019% 47.3 41.3 38.4 32.2 22.5 20.1 20.2 16.4 11.6 8.2 9.2 7.3 4.3 4.6 4.6 4.3 4.1 1.6 Miscellaneous Inspec�on and Cost of public Marke�ng and Agricultural Development and control stockholding promo�on knoledge and maintenance of innova�on system infrastructure in total GSSE 45. On the other hand, the share of output and input- 2019. In turn, the rela�ve importance of support for based transfers remains high at 83 percent in emerging investments, o�en related to irriga�on, has declined economies, having declined from 89 percent in 2000- over �me, now represen�ng some 9 percent of PSE. 2002. In terms of gross farm receipts, they have grown GSSE reached an annual average of US$64 billion, with from 4 to 7 percent, but remain below the OECD avera- infrastructure projects, again largely irriga�on-related, ge. Payments based on areas and animal numbers were accoun�ng 40 percent of expenditures. Public stockhol- almost non-existent in 2000–2002 but reached close to ding and agricultural knowledge and innova�on accoun- 13 percent of aggregate support to producers in 2017- ted for 31 and 13 percent respec�vely (Annex, Fig. 29). 64 MPS, payments based on output and unconstrained use of variable inputs. 65 Payments decoupled from current production, based on non-commodity criteria such as land set aside or payments for specific environmental or animal welfare outcomes. Payments based on current crop area and animal numbers have remained largely unchanged compared to 2000-02, and currently represent around 22% of total producer support. 66 The expenditures financing general services to the sector (GSSE) increased (in nominal terms) in the OECD area from US$ 36 billion per year in 2000-2002 to US$ 43 billion in 2017-2019. Most of these expenditures in 2017-2019 go to the financing of infrastructure (US$ 18.4 billion), recording a slight increase compared to 2000-2002, while the expenditures for agricultu- ral knowledge and innovation (US$ 13 billion) have increased by two thirds. Expenditures for inspection and control services doubled, while spending for marketing and promotion activities and, more substantially, public stockholding declined over the same period, but all of these represented smaller shares of the GSSE expenditure. 25 Agriculture Support Es�mates for Mozambique Total Support Es�mates (TSE) sum of PSE, GSSE, and CSE (Annex, Fig. 27, 28), Mozambique’s TSE as a share of GDP was comparable to 46. Mozambique’s total support to agriculture was 3.3 Philippines and Indonesia, and higher than Angola and percent of GDP in 2018, more than six �mes the OECD South Africa in the SSA region (Fig. 10). As a share of average. Mozambique’s total support to agriculture agriculture GDP, Mozambique’s TSE was equivalent to averaged 3.3 percent of GDP in the 2018, highest value 12.8 percent in 2018, higher than South Africa but lower of analyzed countries, in part highligh�ng the large than Angola (Fig. 11), the value was similar to Costa weight of the agriculture sector in total GDP. The level of Rica’s value. Measured in propor�on to producer total support provided to agriculture (TSE) in 2018 was income, this level of %PSE is rela�vely low (7 percent in US$509 million, equivalent to 3.3 percent of GDP, it was 2018), compared to OECD countries (18 percent) or highest value in the analyzed countries and almost seven Angola (47 percent) but higher of South Africa (5 �mes OECD average of 0.6 percent. Represen�ng the percent). Figure 10: Benchmarking TSE as share of GDP, 2018 3.3% 1.1% Argentina Viet Nam 0.6% Developing Countries Kazakhstan New Zealand Philippines Angola Mozambique Colombia Switzerland OECD South Africa Japan United States Indonesia Canada Costa Rica Turkey China Norway Chile Iceland Ukraine Australia India Mexico Korea Brazil Russia EU28 Israel Figure 11: Benchmarking TSE as a share of Agriculture GDP, 2018 41.3% Argen�na Viet Nam 12.8% 8.8%Developing Countries EU28 Norway Korea Russia Costa Rica Kazakhstan Iceland Angola OECD United States Japan Switzerland South Africa Mozambique Colombia Mexico China Indonesia Israel India New Zealand Chile Brazil Australia Canada Philippines 26 47. MPS accounted for 86 percent of Mozambique’s TSE in worth no�ng that the sources of transfers were mainly 2018, reflec�ng the rela�vely small role of budgetary consumers, who provided 86 percent of the support. transfers in rela�on to total agriculture support. Within Taxpayers contributed the remaining 14 percent⁶⁷. This budgetary transfers, GSSE and the support to farmers pa�ern is in stark contrast to OECD countries, where were nearly equal and accounted for 3 percent mainly taxpayers are the ones genera�ng the most transfers for the support based on the use of service input. It is compared to consumers. Figure 12: Benchmarking Mozambique’s TSE, by Source of Transfers 14% 47% 86% 86% 53% 53% Mozambique 2018 OECD (2011-18) Consumer Transfers Taxpayers Transfers Support to Agricultural Producers (PSE) for the support based on the use of service input. It is worth no�ng that the sources of transfers were mainly 48. MPS accounted for 86 percent of Mozambique’s TSE in consumers, who provided 86 percent of the support. 2018, reflec�ng the rela�vely small role of budgetary Taxpayers contributed the remaining 14 percent⁶⁷. This transfers in rela�on to total agriculture support. Within pa�ern is in stark contrast to OECD countries, where budgetary transfers, GSSE and the support to farmers taxpayers are the ones genera�ng the most transfers were nearly equal and accounted for 3 percent mainly compared to consumers. Figure 13: Benchmarking %PSE, 2018 18.0% Argen�na Viet Nam 7.0% 5.6% India United States OECD Paraguay Guatemala Peru Ukraine South Africa Costa Rica Mexico Israel EU28 Korea New Zealand Suriname Australia Chile Kazakhstan Developing Countries Canada Russia Turkey Japan Angola Switzerland Iceland Brazil Bolivia Mozambique China Indonesia Colombia Philippines Norway 67 This is a result of the high participation of MPS in total support. Consumers generate transfers through the payment of prices above international reference. 27 49. Market price support comprised nearly all of producer consumers⁶⁹ and distorts farmer produc�on decisions as support in Mozambique in 2018. MPS accounted for it changes domes�c rela�ve prices, reducing the exposu- 95.2 percent of Mozambique’s PSE in 2018, over budge- re of farmers to interna�onal prices. MPS tends to be tary support (Table 3)⁶⁸. In fact, Mozambique ranked top regressive, as it favors large producers who generate among the countries monitored by the OECD in terms of commercial surplus rather than smallholders, who tend MPS share of PSE in 2018 (Fig. 16). Given the dominance to have smaller commercial surpluses or only produce of direct agricultural support—i.e., coupled to commodi- for self-consump�on. It also generates a regressive tax ty output, inputs, and financed by consumers—it is likely on low-income food consumers since a rela�vely large to be highly distor�onary for domes�c food produc�on, share of their income is spent in food, compared to consump�on, and trade decisions. This type of support high-income consumers. also imposes addi�onal costs on domes�c food Table 4: Composi�on of PSE, 2018 Concept 2018 US$ Mill 2018 (%) Producer Support Es �mate (PSE) 457 100.00% (A+B+C+D+E+F+G) A.1 MPS 435 95.2% A.2 Payments based on output 2 0.3% B. Payments based on inputs⁷⁰ 20 4.5% C. Payments based on current produc�on 0 0.0% 1 D. Payments based on Non-current produc�on 0 0.0% 2 E. Payments based on Non-current produc�on 0 0.0% 3 F. Payments based on non-commodity criteria 0 0.0% G. Miscellaneous 0 0.0% Source: WB Estimates. ¹. Productioⁿ required; ². Productioⁿ required; ³. Productioⁿ ⁿot required Figure 14: Level and Composi�on of Mozambique’s PSE, 2018 35,000 7.1 7.0 MPS and Budgetary support, 30,000 6.0 Millions local currency 1,323 25,000 5.0 %PSE 20,000 4.0 15,000 3.0 26,146 10,000 2.0 5,000 1.0 Budgatery Transfer (le� scale) % Producer Support Es�mate (right scale) Support based on commodity Output (le� scale) 68 The aggregate value of MPS is the outcome of implicit taxation through negative price gaps for some commodities (a negative MPS) and price support of others (a positive MPS). Annual variations depend on movements in world prices, domestic prices and exchange rates, as well as changes in production levels. Major components of the MPS are the price differential (gap between domestic producer price and reference price) for products analyzed. 69 OECD, 2008. 70 Note that inputs include technical assistance provided along with physical inputs (i.e. extension). 28 50. Exchange rate vola�lity and other factors outside of factors that are not derived from domes�c agricultural agricultural policies, such as natural disasters impac- policies, such as market structure �ng domes�c food prices, could also par�ally explain (monopolies/monopsonies), exchange rate movements, MPS es�mates. MPS is generated by a price gap temporary disrup�ons in supply or demand due to between domes�c and external reference prices. This shocks such as natural disasters, and support policies in differen�al is commonly related to border measures⁷¹ or other countries, could also explain varia�ons in MPS direct market prices interven�ons (regulated prices) es�mates. An addi�onal, in-depth marginal analysis to that generate the gap. In Mozambique, border measures disaggregate the effects of each poten�al factor affec- in the form of import tariffs on products like maize, �ng the MPS es�mate is possible, but was determined to cassava, tomato, sweet potato and pork meat at least be beyond the original scope of this study. par�ally explain the high share of MPS⁷². However, other Figure 15: Composi�on of Mozambique’s PSE, by Category of Support, 2018 51. Budgetary support directly benefi�ng farmers avera- in the Maputo and Limpopo Corridors (PROSUL), ged just 2 percent of PSE, with input-based payments programs for intensifica�on and diversifica�on of crops, comprising the largest share. As part of this analysis, livestock development programs, rural finance support data was also collected on a diverse range of govern- program, intensifying the produc�on of food crops of ment programs financed by taxpayers and executed by cereals and legumes in provinces and extension servi- the Government of Mozambique (Ministry of Agricultu- ces, etc. were allocated to PSE categories based on their re and Rural Development, Ministry of Industry and characteris�cs. Considering only budgetary payments, it Commerce, Ministry of Land and Environment and other was observed that payments based on inputs—like land ministries, or public agencies) at the na�onal and subna- prepara�on subsidies and machinery subsidies- �onal level. Following the PSE methodology, expenditu- comprised the largest share, accoun�ng for 93.0 percent re on programs like Pro-Poor Value Chain Development of PSE budgetary payments in 2018 (Table 5). Also 71 In general, border measures include import (export) tariffs or quotas and import (export) licenses or other measures that constitute restrictions or supporting on trade. 72 The Most Favored Nation (MFN) import tariff was 10 percent during the study period (WTO). 29 output-based payments were 7 percent in 2018, reflec- sas) and Programa du Producao de Hor�culturas. �ng the effect of programs like Programa Intensificar a Mainly, public resources were directed through support Producao de Culturas Alimetares (Cereais e Legumino- to output and input based payments⁷³. Table 5: Composi�on of PSE Budgetary Payments Concept 2018 US$ Mill 2018 (%) Budgetary Payments 22 100 (A.2+B+C+D+E+F+G) A.2 Payments based on output 2 7 B. Payments based on inputs 20 93 1 0 0 C. Payments based on current produc �on 2 0 0 D. Payments based on Non-current produc �on E. Payments based on Non-current produc �on 3 0 0 F. Payments based on non-commodity criteria 0 0 G. Miscell aneous 0 0 Source: WB Es�mates. 1: Produc�on required; 2: Produc�on required; 3: Produc�on not required. 52. Producer support was highest for maize and pork meat. receipts, %SCT was also calculated all five agricultural Disaggrega�ng Mozambique’s PSE at the product-level, products. The results show that %SCT for maize was 43 this analysis examined the producer support provided to percent but the pork meat was 31 percent meanwhile major crops through commodity-specific policies. In for cassava was 7 percent, principally reflec�ng MPS 2018, the SCT was calculated to be US$179 million for through border and price measures. In contrast, the maize, US$124 million for cassava, US$2 million for pork %SCT for sweet potatoes and tomato were 0.8 percent meat, US$2 million for tomato and US$1 million for and 0.4 percent respec�vely, implying that all the sweet potato. Expressed in terms of share of gross support was budgetary. Figure 16: Benchmarking %SCT by Commodity, 2018 Corn 43.2% Pork Meat 31.0% Mandioca 6.6% Sweet Potatoe 0.8% Tomatoe 0.4% 0 10 20 30 40 50 % 73 A detailed information for each program and amounts are included in the PSE Excel calculations, which is part of this analysis. 30 53. Mozambique’s support to maize and cassava is signifi- ding support in Indonesia and Angola was 0 and 0.3 cantly higher than its OECD comparators. Of the total percent respec�vely was minimum (Fig. 19). This large revenues perceived by farmers who produce maize, 43 varia�on in public sector support among agriculture percent came from support policies and programs in commodi�es has an impact on the domes�c market by 2018, significantly higher than the OECD average of 3.2 distor�ng incen�ves and consequently, the produc�on percent (Fig. 17). Similarly, 6 percent of the revenue decisions made by farmers. To illustrate the difference, a received by cassava farmers was due to support policies maize farmer in Mozambique received the equivalent of in this year. While OECD countries do not measure speci- US$58/ha and US$170/ha for cassava⁷⁴ in 2018, while fic commodity support (SCT) for cassava, the correspon- sweet potatoes received US$39/ha Figure 17: Benchmarking SCT% for maize, 2018 Kazakhstan Argen�na Russia Viet Nam EU28 Brazil Turkey OECD -Total United States Switzerland South Africa Ukraine Mexico Developing (OECD) China Calombia Mozambique Indonesia Chile New Zealand Canada India Angola Philippines Figure 18: Benchmarking %SCT for Pork Meat, 2018 Viet Nam Norway EU(28 country) United States OECD -Total South Africa Argen�na Costa Rica Japan Korea Switzerland Australia Chile New Zealand Brazil Canada Kazakhstan Mexico Ukraine Russia Iceland Indonesia China Colombia Mozambique Philippines 74 Note that in the case of cassava, international prices are very volatility due to relatively thin markets, so MPS for cassava could not be as accurate as for other commodities. 31 Figure 19: Benchmarking %SCT for Cassava, 2018 Ind on esi a 0 An go la 0.3 Mo zamb iqu e 6.5 0 1 2 3 4 5 6 Support to General Services for Agriculture correlated with country income-level, agricultural (GSSE) growth and compe��veness⁷⁵, GSSE represented only 0.6 percent of agricultural GDP in 2018, it was lower 54. Agriculture supports funded by taxpayers (through level of the analyzed countries. On the other hand, the public expenditures) are mainly allocated to inves- corresponding averages for OECD, developing countries, tments in private goods (subsidy-PSE) rather than South Africa and Angola were 2.7 percent, 5.4 percent, public goods (GSSE). Financed by taxpayers in the form 2.3 percent and 0.8 percent, respec�vely (Fig. 20). Simi- of budgetary payments, GSSE support ac�vi�es provi- larly, GSSE accounted for 5.5 percent of TSE, less than ding general benefits or goods with public characteris- one half of the averages for OECD (13.1 percent) and �cs, i.e., agricultural innova�on (R&D and educa�on), developing countries (14.3 percent) (Fig. 21). Most animal/plant health services, marke�ng and promo�on, public expenditures went towards infrastructure develo- rural infrastructure, and public stockholding. Posi�vely pment (81 percent), Research (10 percent) and Marke- �ng and Promo�on (7%) in 2018. Figure 20: GSSE as a share of agriculture GDP, 2018 5.4% 2.7% 0.6% India Chile EU28 Brazil OECD Israel Korea China Angola Iceland Mexico Norway Canada Viet Nam Australia Colombia Argen�na Indonesia Costa Rica Kazakhstan Switzerland Philippines South Africa Mozambique New Zealand United States Developing Countries Japan 75 One interesting point is that in some countries that are currently referenced in international markets, highly market oriented and export leaders (New Zealand, Australia, Canada), the GSSE is the most important way to support their agricultural sector. 32 Figure 21: GSSE as a share of TSE, 2018 14.3% 13.1% Argen�na Viet Nam 5.5% Chile EU28 Israel Brazil OECD Korea China Japan Russia Turkey Iceland Mexico Canada Norway Ukranie Australia Colombia Indonesia Costa Rica Philippines Kazakhstan Switzerland South Africa New Zealand Mozambique United States Angola Developing Countries 55. GSSE was the lowest among the countries monitored systems⁷⁶ and 7.1 percent to marke�ng and promo�on, by the OECD. In 2018, 80.7 percent of the rela�vely with the remainder in other categories. Benchmarking small GSSE outlay (US$28 million) was allocated to against other countries, Mozambique’s GSSE was 0.6 agricultural infrastructure and maintenance, i.e., irriga- percent of agricultural GDP in 2018, similar to Angola �on equipment, hydraulic infrastructure, dam’s rehabili- (0.8) and Indonesia (0.7) but lower than South Africa ta�on and construc�on, agro-meteorology equipment, (2.3), Mozambique is the lowest value of all analyzed rural water infrastructure (PRONASAR). Ten percent was countries. allocated to agricultural knowledge and innova�on Figure 22: Composi�on of the GSSE in Mozambique J. Infrastructure development and maintenance K. Marke�ng and Promo�on 80.7% 7.1% L. Public storage 0.6% M. Micelaneous 0.0% H.Research 10.5% I. Inspec�on and control 1.1% 76 Training, R&D and resources for agricultural research institutes 33 Figure 23: Benchmarking GSSE by Component, 2018 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% India Chile Israel EU28 Korea OECD Brazil Japan China Russia Turkey Angola Iceland Mexico Canada Norway Ukranie Australia Viet Nam Colombia Indonesia Argen�na Costa Rica Kazakhstan Philippines Switzerland South Africa All Countries Total general Mozambique United States New Zealand Emergiing Economies K. Marke�ng and Promo�on I. Inspec�on and control L. Public storage J. Infrastructure development and maintenance M. Miscelaneous H. Research 56 During the study period, approximately 90 percent of mate classifica�on, the 90 percent of Mozambique’s TSE Mozambique’s total support could be classified as could be classified as belonging in the amber box (Green belonging to the WTO amber box and be subject to box is 5.5 percent) given that they include measures to countervailing measures by its trade partners. In WTO’s support prices, or subsidies directly related to produc- terminology, agricultural support is classified in three �on quan��es (Table 6). A large share of Mozambique’s boxes: green (measures with no distor�ve effect on agriculture support—because of its reliance on MPS—is produc�on and trade)⁷⁷, amber (distor�ng measures of therefore subject to reduc�on commitments and is produc�on and trade), and blue (“amber box with condi- ac�onable by impor�ng countries, i.e., they may apply �ons”) subsidies that are �ed to programs limi�ng countervailing measures. The blue box was not included produc�on. Notably, amber box support is subject to since it carried commitments to reduce support. Since reduc�on commitments and is ac�onable by impor�ng OECD and WTO methodologies do not fully correspond, countries. On the other hand, blue and green box mea- this analysis is intended to be indica�ve and instruc�ve sures are not subject to reduc�on commitments and are for policymakers. non-ac�onable (“Peace Clause”). Based on an approxi- 77 For example, research, direct payments decoupled from production, and infrastructure investment. 34 Table 6: WTO Classification of Mozambique’s TSE Total according to WTO Box As % of TSE Box 2018 (US$, Mill.) 2018 (%) Amber box 457.1 89.9 Green Box 27.8 5.5 Note 3: The shares do not sum up to 100%, because OECD es�ma�ons include other support (mainly consumer support) not considered by WTO. Support to Consumers of Agricultural Products percent in 2018, indica�ng that policies suppor�ng (CSE) agriculture (par�cularly through domes�c producer prices) acted as an implicit tax. Consequently, consu- 57. Mozambique consumers have borne the cost of MPS, mers paid higher domes�c prices than interna�onal paying an implicit food consump�on tax equivalent to prices and their consump�on expenditure rose. Compa- 5 percent of food basket value in 2018. The CSE measu- ring across countries, this aggregate tax on consumers in res the cost to consumers arising from agricultural Mozambique is higher than OECD average or Angola, policies⁷⁸. Similar to the PSE, CSE can be expressed in -7.3 and -7.5 percent, respec�vely, and lower than South rela�ve terms as a share of consump�on value (%CSE). Africa (-3.2 percent). The CSE% for Mozambique was es�mated to be 5 Figure 24: Benchmarking %CSE, 2018 Developing Countries Mozambique New Zealand South Africa Switzerland Philippines Costa Rica Indonesia Colombia Ukranie Norway Canada Mexico Iceland Angola Turkey Russia Korea Japan China OECD Israel EU28 Chile Viet Nam Kazakhstan United States Australia Brazil Argen�na India -5.0 -7.3 78 In the PSE methodology, the consumer is understood to be the first buyer of agricultural products. 35 Conclusions Main Findings Only 7 percent of gross farm receipts were accoun- ted by Mozambique’s support to producers, more 58. Based on the assessment of the agriculture support than 11 percent points lower than the OECD avera- es�mates, the main findings to be considered for ge. In Mozambique, 7 percent of producer’s gross agriculture policy decisions going forward are the farm receipts (PSE%) came from agriculture support following: policies and programs in 2018. This is 11 percent points lower than the OECD average for that same Mozambique allocated US$509 million in annual year. PSE% in Mozambique was comparable with that support to the agriculture sector, represen�ng of countries with medium levels of support, such as 1.53.3 percent of total GDP. Total Support Es�mate Canada, Mexico and Costa Rica. (TSE) to agriculture from public policies and programs⁷⁹ in Mozambique in 2018 was es�mated in Agriculture producer support in Mozambique is US$509 million. This was equivalent to 12.8 percent overwhelmingly funded by policies that raise of its agriculture GDP, higher than most developing domes�c agriculture prices. Ninety-seven percent of countries (8.8 percent on average) (Fig. 11), the value the support to agriculture producers (PSE) is funded was below OECD member countries (41.3 percent on by Market Price Support (MPS), while budgetary average). A neighbor and close trading partner, South support only represents 3 percent (in 2018). These Africa, has a TSE of 9.2 percent of agriculture GDP transfers occur due to public policies (mainly border and 0.3 percent of total GDP, while Angola has 29.5 measures) are making the domes�c prices of agricul- percent and 1.4 percent in the same items, also OECD ture and food products higher than the interna�onal countries’ support to agriculture represents 0.6 prices (compared at farm gate). In other words, percent of total GDP. border measures are crea�ng an “implicit tax” for food consumers in Mozambique and most beneficia- Although total agriculture support in Mozambique ries of higher prices are agriculture producers that is high compared to other developing countries, the par�cipate in market sales. MPS are thus, monetary por�on of support going to public goods and servi- transfers from Mozambican food consumers to ces is rela�vely low. The Total Support Es�mate (TSE) Mozambican producers. is composed of support to producers (measured as PSE), consumer support (CSE), and support to general The current structure of producer support only agriculture public goods and services (GSSE)⁸⁰. The benefits a small number of commercial producers analysis revealed that 90 percent of TSE was through and does not enhance sector compe��veness. MPS producer support (largely in the form of market price is based on the amount of agriculture produc�on support), while just 5 percent went to GSSE. Bench- that a farmer sells in the market, it is therefore poorly marking the TSE composi�on across countries where targeted and favors large producers who generate data is available, we observe that Mozambique’s commercial surplus rather than smallholders with investment in GSSE is the lowest of the analyzed smaller surpluses or who only produce for self- countries. As a share of the agriculture GDP, GSSE consump�on⁸¹. Given that small-scale and accounted for just 0.6 percent, which was low com- subsistence-oriented family farms dominate in pared to other developing countries average (2.7 Mozambique and that MPS policies have been imple- percent) and the OECD’s average (5.4 percent) in mented mainly based on food security arguments, 2018. the effect of MPS is the opposite, benefi�ng only a small propor�on of producers and taxing most poor 79 Agriculture support was estimated using the OECD methodology (https://www.oecd.org/agriculture/topics/agricultural-policy-monitoring-and-evaluation/documents/ producer-support-estimates-manual.pdf ). The total support estimate measure (TSE) is the annual monetary value of all gross transfers from taxpayers and consumers arising from public policy measures that support agriculture, net of the associated budgetary receipts, regardless of their objectives and impacts on farm production and income, or consumption of farm products. 80 GSSE’s include agriculture public goods and services such as innovation systems (agriculture R&D and education), animal and plant health services, food safety, infrastructure, agriculture promotion, land administration, and other public services.. 81 In some settings, other value chain actors (such as input suppliers) also capture part of the transfers. It’s conceivable that in those settings, they benefit more than even large-scale producers 36 agricultural households which tend to be net food Agriculture support to producers in Mozambique is consumers. Furthermore, MPS distorts produc�on deci- basically concentrated in maize and pork meat and is sions and investments in compe��ve agriculture rela�vely high for these commodi�es compared to products as it protects producers from interna�onal other countries. Of the total gross revenues perceived market prices. by farmers producing maize, 43 percent came from agriculture public support policies and programs, while Food consumers in Mozambique pay an implicit tax of pork meat had 31 percent support, in 2018 about 5 percent. Support to food consumers (CSE) is (commodity-specific support is measured by Single nega�ve in Mozambique. CSE measures the support to Commodity Transfers—SCT). In comparison, the %SCT in (or tax on) food consumers arising from public agricultu- OECD countries was 3 percent for maize and 8 percent re policies. Although Mozambique does provide some for pork meat in the same year, the Mozambique levels support to food consumers in the form of food aid and were similar of the Indonesia and Colombia for maize school feeding programs, the overwhelming majority of and Costa Rica or Norway for pork meat. This large varia- the CSE is nega�ve, due to public policies protec�ng �on in agriculture public sector support—and therefore domes�c prices. CSE as a percentage of total food profitability—across commodi�es signals the distor�ons expenditures by food consumers was approximately 5 that farmers face when making produc�on decisions. percent in 2018. This 5 percent implicit tax is a transfer For example, support to sweet potatoes was US$39/ha from consumers to producers through higher domes�c while cassava US$170/ha in 2018⁸². food prices. It is also a regressive tax since poor consu- mers spend a larger share of their income on food than high-income consumers. Figure 25: Agriculture Support and Value Added per Worker, 2018 90,000 USA 80,000 70,000 Outut per Worker, Constant US$2010 60,000 50,000 40,000 30,000 Brazil 20,000 South Africa 10,000 Mozambique Angola 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 %PSE 82 Authors calculations, based on OECD data. 37 Figure 26: Support to Maize vs Yields, 2018 12.00 USA 10.00 8.00 TM/Ha 6.00 South Africa Brazil 4.00 2.00 Mozambique Angola 0.00 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 % Proposed Agriculture Policy Reform Agenda policies and programs towards Government compe��- veness, climate resilience and nutri�on and food securi- 59. Mozambique is in the process of defining its 10-year ty objec�ves. The four main recommended policy shi�s strategy and investment plan for the agriculture sector, are summarized here below and are tagged for the recovering from the COVID-19 pandemic, and moving following expected Government objec�ves: compe��- towards a more compe��ve and sustainable agricultu- veness (COMP), climate resilience (CC) and re sector. In the past, support consisted largely of price nutri�on/food security (NFS). The recommenda�ons are support (through border measures), without addressing also iden�fied as policy reforms to be undertaken in the underlying compe��veness bo�lenecks. This approach short (ST) and long term (LT). Fiscal implica�ons need to will need to be phased out as Mozambique moves be taken into account when considering such policy towards full par�cipa�on in regional and con�nental shi�s, as well as the interna�onal experience with such free trade agreements. Programs like the Sustainable transi�ons (see Box 1 for a summary of studies of coun- Rural Economy Program (SREP) seek to improve the try experiences). resilience and compe��ve posi�on of the agriculture sector. Developing agribusinesses is high in the country’s 60. This report presents some important recommenda�ons development agenda, with an important private sector for realigning agriculture support policies and programs development program and technical assistance provided towards compe��veness, climate resilience and nutri- by the WB and IFC. The mul�ple natural disasters of the �on and food security objec�ves. last years and the COVID-19 pandemic have also renewed the urgency to focus on suppor�ng the climate resilience and nutri�on of the poorest households. It is in this context that this report presents some important recommenda�ons for realigning agriculture support 38 Compe��veness objec�ve COVID-19 Recovery: Building back be�er Agriculture Policy Shi� (diversifica�on and trade integra�on) Nutri�on—Food Climate Resilience Security PSE to GSSE MPS to non-distor�onary PSE CSE (-) to CSE (+) SCT to non-commodity specific PSE 61. Shi� agriculture support from private towards public 62. Shi� from distor�ve measures to compe��ve agricul- goods and services [COMP; LT]. Agriculture support in ture policy support [COMP; LT]. Given that an overwhel- Mozambique is mainly geared towards private goods mingly large share of Mozambique’s agriculture support (subsidies and market price support) rather than is MPS (or coupled to the produc�on of specific agricul- towards investments in agriculture public goods and ture products), a transi�on plan for agriculture to move services: almost half of all agriculture public expenditu- towards a more compe��ve policy support environment res (average for 2018 and 2019) went towards inves- is very much needed. In fact, Mozambique will likely be tments in private goods (subsidies), such as payments engaging in MPS reduc�on commitments in agriculture based on inputs—programs that subsidize agriculture trade agreements such as the Africa Con�nental Free inputs like seeds, fer�lizers, machinery and land prepa- Trade Area (AfCFTA), so a complementary trade agenda ra�on. Mozambique should seek to shi� its agriculture is needed to support smallholders of protected agricul- sector support towards investments in public goods and ture products transi�on to face market prices and take increase GSSE’s share of agriculture GDP from its current advantage of trade⁸⁵. level of 0.6 percent to at least the level of South Africa, or the average of developing countries (2.3 percent and 63. Shi� from implicit taxa�on to posi�ve support to food 5.4 percent, respec�vely), given the overwhelming and consumers [NFS; LT]. As the nega�ve CSE es�mates in long-standing evidence that public sector investments this report demonstrate, Mozambican food consumers and support to agriculture public goods and services are funding the bulk of agriculture support to the sector. deliver higher economic returns than public sector A shi� away from MPS, as suggested above, will reduce investments in private goods (World Bank, 2017⁸³ ; the implicit food tax to food consumers, consequently Lopez and Galinato, 2007⁸⁴; Lopez, 2005⁸⁵; World Bank, increasing the welfare of the poorest. However, other 2001⁸⁶). Commercial agricultural producers would bene- public policies and programs could be further enhanced fit from the opportuni�es to supply the domes�c and to directly safeguard consumers from food insecurity regional market created by the various Government and nutri�on challenges, by targe�ng support through programs for agribusiness development. social protec�on programs (food aid, school feeding) and countercyclical safety nets. 83 Goyal, Aparajita; Nash, John. 2017. Achieving Better Results: Public Spending Priorities for Productivity Gains in African Agriculture. Africa Development Forum;. Washington, DC: World Bank and Agence Francaise de Développement. © World Bank. https://openknowledge.worldbank.org/handle/10986/25996 License: CC BY 3.0 IGO 84 López, R., and G. I. Galinato. 2007. “Should Governments Stop Subsidies to Private Goods? Evidence from Rural Latin America.” Journal of Public Economics 91:1071—94 85 Lopez, Ramon. Under-investing in public goods: evidence, causes, and consequences for agriculture development, equity and the environment. Journal of Agriculture Economics, Volume 32, Issue 1. January 2005: https://onlinelibrary.wiley.com/doi/full/10.1111/j.0169-5150.2004.00025.x 86 World Bank. World Development Report 2001: https://elibrary.worldbank.org/doi/pdf/10.1596/0-1952-1606-7 87 An update to the World Bank’s 2006 Diagnostic Trade Integration Study (DTIS) is under preparation and is expected to take on these questions in more detail. 39 64. Shi� support to promote environmental and nutri�on making a simple plate of food—as defined by the WFP security objec�ves [COMP, CC. NFS; ST]. Given the “Coun�ng the Beans” methodology—costlier⁸⁸. Fur- country’s fiscal limita�ons and the implicit tax imposed thermore, Climate Smart Agriculture (CSA)⁸⁹ and Nutri- by agriculture public policies on Mozambican food �on Smart Agriculture (NSmartAg)⁹⁰ technologies and consumers, producer support should be geared towards prac�ces should be integrated into farmer input and achieving objec�ves beyond suppor�ng farmer incomes. technology support incen�ves, to promote produc�vity Support can contribute towards food and nutri�on secu- growth, and fulfill environmental and nutri�on objec�- rity objec�ves, leveling the playing field for a product ves. Moreover, decoupling producer support from speci- like sweet potatoes vis-a-vis cassava. A cassava farmer fic agriculture products would enable farmers to make receives more than double the support of what a tomato produc�on decisions mainly on market opportuni�es farmer receives in a per hectare bases and more than 4 (and not on the level of public sector support). �mes the support a sweet potato farmer receives, thus Box 3. Strategies for shi�ing from MPS to decoupled support Several studies and experiences point to poten�al pathways for Mozambique to transi�on from protec�ng a few commo- di�es and producers through market prices, to suppor�ng a more compe��ve agriculture sector and poor households through targeted and decoupled support. The implementa�on of such agriculture policy reform strategy is urgent and opportune as it can help provide a building back be�er recovery from COVID-19, but also take advantage of SADC and AfCFTA. Parikh et al. (1995) studied several agriculture sector trade liberaliza�on post GATT (Uruguay Round). The conclu- sions point out that the policy package that has shown superior growth, welfare and distribu�on effects, without raising taxes, includes: (a) switching from agriculture input subsidies to safety nets (reducing PSE and increasing CSE); and (b) increasing public investments in public goods and services (rural infrastructure)⁹¹. Various studies show how agriculture trade liberaliza�on and discon�nuity in policy reforms can lead to nega�ve impacts in the most vulnerable farming popula�on. Nyairo et al. (2010) point to the mixed experience of some African countries in agriculture trade liberaliza�on⁹² and McCorrston et al. (2013) to the mixed experience of a global set of 34 countries, finding clear drawbacks from “stop-go” policy reform programs, and results depending on the way food security and other impact variables are assessed. Uganda is one of the interes�ng cases of a mixed experience in shi�ing from MPS to direct farmer support. Reforms did not automa�cally translate into an increased value of agriculture exports, largely because world prices are beyond the control of small-country exporters. O�en, the an�cipated benefits from reducing MPS do not materialize because only limited or par�al reforms are actually implemented, i.e., there is no significant increase in incen�ves for diversifying and/or expor�ng. This is especially true of many SSA countries. Furthermore, even when significant trade reforms are implemented, important constraints remain. Several reasons explain the limited agricultural supply response towards higher compe��veness following a reduc�on in MPS. In par�cular, farmers’ ability to increase produc�on and exports to respond to increased incen�ves will be constrained by farming prac�ces, limited access to inputs, credit and new technologies (McKay et al. 1997). Poor infrastructure and natural barriers act as a tax, o�en very high, on building a compe��ve agribusiness and engaging in exports (Milner et al. 2000). Delays in implemen- �ng policy and ins�tu�onal reforms to support the compe��ve transi�on of farmers have been suggested as one factor limi�ng export supply response in Uganda. 88 Based on an extrapolation from the World Food Programme (WFP)’s measurement of the cost of a minimum diet globally. This methodology defines a simple plate of food to consist of pulses, a local carbohydrate—such as rice, bread, maize meal—vegetable oil, tomatoes, onions and water. https://cdn.wfp.org/2018/plate-of-food/ However, Mozamque has not yet made it into the database and this qualitative assessment assumes that maize will be considered part of Mozambique’s plate of food. 89 For a definition and approach to CSA, see: https://www.worldbank.org/en/topic/climate-smart-agriculture 90 For a definition and approach to NSmartAg see: https://www.worldbank.org/en/topic/agriculture/publication/nutrition-smart-agriculture-when-good-nutrition-is-good- business 91 Parikh, K., N. S. S. Narayana, Manoj Panda, & A. Ganesh Kumar. (1995). Strategies for Agricultural Liberalisation: Consequences for Growth, Welfare and Distribution. Economic and Political Weekly, 30(39), A90-A92. Retrieved May 28, 2021, from http://www.jstor.org/stable/4403270 92 Nyairo, N. M., Kola, J., & Sumelius, J. (2010). Impacts of agricultural trade and market liberalization of food security in developing countries: comparative study of Kenya and Zambia (No. 308-2016-5085). 40 Another case is Mexico, analyzed by Henriques et al. (2003)⁹³and UNCTAD (2014), poin�ng out to the sector gains and losses following the country entering the FTA with the USA and Canada (NAFTA) in 1994. Mexico nego�ated a 15-year gradual tariff reduc�on for sensi�ve crops like maize. The total value of agriculture produc�on and agriculture exports increased, including the produc�on of maize. However, some smallholder farmer support shi�ed mainly from MPS to decoupled payments (per hectare payments and social safety nets). This made them shi� out of agriculture rather than inves�ng in improving their produc�on system. Par�cular a�en�on must be paid to the food security and transi�on strategy of smallholder farmers in accessing the needed public sector support and incen�ves to embark in an agriculture transi�on path to increased compe��veness, in par�cular inves�ng in agriculture public goods and services. Finally, a successful case of policy shi�s in the context of reduc�on of MPS is Brazil, as documented by the World Bank (2014). In thirty years, it went from a food-impor�ng country (as most SSA countries), with mainly subsistence farmers, to a food expor�ng powerhouse, through a combina�on of public policy reforms including (a) direct support to vulnera- ble households through safety nets; (b) direct support to farmers through incen�ves for technology adop�on (through credit programs); and (c) large investments in agriculture public goods and services (mainly agriculture innova�on systems)⁹⁴. Lessons from Mozambique for other Countries Box 4: Lessons for Capacity Building and Database Ins�tu�onaliza�on As part of this review, the joint WB-FAO team undertook capacity building of technical counterparts in Mozambique with the objec�ve of ins�tu�onalizing the use of OECD indicators into the country’s policy analysis and policymaking process. The key lessons and experiences from this approach are summarized below. Given the low but growing coverage of this methodology in SSA, these lessons are intended to serve as a guide for other countries that are considering similar reviews of their agricultural support. i. Iden�fica�on of key responsible staff, o�en within the Ministry of Agriculture, is cri�cal for following the data collec- �on and analysis methodology correctly and ensuring ins�tu�onal memory within the Government. ii. To widen the pool of exper�se, it is also important to target not only staff from the Ministry of Agriculture and of Finance, but also from NGOs, Universi�es and private consultants that may want to use the es�mates for further policy analysis. To the extent possible, the training modules should be delivered in local languages to maximize reten- �on and learning outcomes. iii. The development of partnerships with technical organiza�ons like FAO (MAFAP) is key for building on exis�ng agricultural policy databases and ensuring the sustainability of this review. In par�cular, the integra�on of PSE updates with na�onal data sources⁹⁵ can leverage higher quality data and increase the depth and granularity of agricultural support es�mates. iv. Use a phase-in phase-out approach to the capacity building: Since this exercise is only repeated annually (or every two years), it is advisable to organize refresher courses and to ensure that na�onal counterparts are gradually able to implement the methodology independently. v. Linking the results to policies and outcomes that ma�er to Government: To ins�tu�onalize the OECD indicators in country-level policy analysis, it is key that the mid- and senior management in the Ministry of Agriculture and other ministries appreciate the full range of its applica�ons. 93 Patel, R., & Henriques, G. (2003). Agricultural trade liberalization and Mexico. Food First Policy Brief, (7). 94 Correa, P., & Schmidt, C. (2014). Public research organizations and agricultural development in Brazil: how did Embrapa get it right?. Economic Premise, 145, 1–10. 95 In the near future, household-level price data will be available in Mozambique through the data on the Relatório da campanha agrária. 41 Annex A Supplementary Figures and Tables Figure 27: Producer Support Es�mate (PSE) and Sub-Categories A. Support based on commodi�y output A.1 Market Price Support A.2 Payments Besd on output B. Payments based on input use B.1 Variable input B.2 Fixed input B.3 Services C. Payments based on current, production required C.1 based on income C.2 based on area/animal numbers PSE = A+B+C+D+E+F+G D. Paymantes based on non current, Production non required E. Paymants based on non current, Production non required C.1 Variable rates C.2 fixed rates F. Payments basedd on non commodity criteria F.1 Log term resource retirement F.2 A specific non commodity output F.3 Other non commodity criteria G. Miscellaneous Figure 28: General Services Support Es�mate (GSSE) and Sub-Categories H. Agricultural Knowledge I. Inspection and Control (safety, Inspection, Control, pest disease) J. Development of infrastructure (hydrological, storage, institutional) GSSE = H+I+J+K+L+M K. Marketing and Promotion L. Cost of Public Stockholding M. Miscellaneous 42 Figure 29: Es�mates of Support to Agriculture (54 Countries) Source: OECD (2020), “Producer and Consumer Support Es�mates”, OECD Agriculture sta�s�cs (database), h�p://dx.doi.org/10.1787/agr-pcse-data-en. Statlink 2 h�ps://doi.org/10.1787/888934143603 43 Figure 30: Mozambique’s TSE, 2018 2018 2018 MZ Mill USD Mill I. Total produc�on value (at the farm gate) 386,604.5 6,432.7 1. Of which, share of standard PSE commodi�es (%) 65.7% 0.0 II. Total consump�on value (at the farm gate) 494,729.6 8,231.8 1. Of which standard PSE commodi�es 324,986.7 5,407.4 III.1 Producer Support Es�mate (EAP) 27,469.0 457.1 A.1 Market price support 26,146.0 435.0 1. Of which standard PSE commodi�es 17,175.3 285.8 A.2 Produc�- on - based payments 92.2 1.5 B. Payments based on the use of inputs 1,230.8 20.5 1. Based on the use of variable inputs 190.9 3.2 2. Based on the use of fixed inputs 191.4 3.2 3. Based on usage of services 848.6 14.1 C. Supports based on produc�on A /An/ I. Required produc �on 0.0 0.0 1. Based on revenue 0.0 0.0 2. Based on area or number of animals 0.0 0.0 D. Supports based on A / AN / I Not Current. Produc�on required 0.0 0.0 E. Supports based on A/AN/I Not Current. Produc �on not required 0.0 0.0 1. Variable rates 0.0 0.0 2. Fixed rates 0.0 0.0 F. Support based on non-commodity criteria 0.0 0.0 1. Long term resource 0.0 0.0 2. A specific non -commodity product 0.0 0.0 3. Other non-commodity criteria 0.0 0.0 G. Miscellaneous Support 0.0 0.0 44 2018 2018 MZ Mill USD Mill III.2 Es�mated Percentage of Producer Support (EAP) 7.1 7.1 IV. General Service Support Es�mate (GSSE) 1,671.9 27.8 H. Agricultural Knowledge 175.0 2.9 I. Inspec�on and Control 18.1 0.3 J. Infrastructure Development and Maintenance 1,350.0 22.5 K. Marke�ng and promo�on 118.1 2.0 L. Cost of Public Shares 10.6 0.2 M. Miscellaneous 0.0 0.0 V.1 Consumer Support Es�mate (CSE) -24,833.5 -413.2 N. Transfers from consumers to producers (-) -26,146.0 -435.0 1. Of which standard PSE commodi�es -17,175.3 -285.8 O. Other consumer transfers (-) -115.4 -1.9 1. Of which standard PSE commodi�es -75.8 -1.3 P. Transfers from taxpayers to consumers 1,427.9 23.8 V.2 Percentage of CSE -5.0 -5.0 VI.1. Total Support Es�mate (TSE) 30,568.7 508.6 Q. Consumer transfers 26,261.4 437.0 A. Taxpayer Transfers 4,422.7 73.6 S. Budget revenue (-) -115.4 -1.9 45 Figure 31: Disaggrega�on of Mozambique’s TSE, 2018 Total Support Es�mate (509 mdd) 3.3% (GDP) 12.5 Agr GDP Producer Support Es�mate GSSE Consumer Support Es�mate (457 mdd) (25 mdd) (-413 mdd) Corn (179 mdd) Infrastructure (23 mdd) Corn (-176 mdd) Cassava (124 mdd) Knowledge (3 mdd) Cassava (-110 mdd) Pigmeat (2.4 mdd) Promo�on (2 mdd) Pigmeat (-0.2 mdd) Tomatoe (1.8 mdd) Inspec�on (0.3 mdd) Others (-126 mdd) S. Potatoe (1.2 mdd) Stockholding (0.2 mdd) Others (149 mdd) 46 Figure 32: World Trade Organiza�on Boxes Amber box Blue Box Green Box These are distor�ng This is the “amber box These are measures measures of produc- with condi�ons” - that have no distor�- �on and trade: condi�ons designed to ve effect on produc- reduce distor�on �on or trade, for These Include measu- In the current nego�a- example: research, res to support price, or �ons, some countries direct payments subsidies directly want to keep the blue related to produc�on box as it is because DECOUPLED from quan�on quan�tles they see it as a crucial produc�on, and means of moving away infrastructure inves- from distor�ng amber tment. box subsidies without causing too much hardship • Amber Box support are subject to reduc�on commitments and are ac�onable by impor�ng countries (i.e. impor�ng countries may apply countervailing measures). • Blue box and green box measures are not subject to reduc�on commitments and are non-ac�onable (“Peace Clause”). 47 Annex B From the defini�on of the PSE, a policy measure will be on-farm investment cost of farm buildings, equipment, included in the es�ma�on of agricultural support if it: (a) planta�ons, irriga�on, drainage and soil improvements. provides a transfer whose incidence is at the farm level; and (b) is directed specifically to agricultural producers B.3. On-farm services—transfers reducing the cost of or treats agricultural producers differently from other technical, accoun�ng, commercial, sanitary and phyto- economic agents in the economy. sanitary assistance, and training provided to individual farmers. Support for farm product prices, or direct payments based on agricultural produc�on or agricultural area, are C. Payments based on current produc�on, produc�on clearly agricultural and producer-specific, and are inclu- required transfers from taxpayers to agricultural produ- ded in the PSE indicator. Similarly, a payment reducing cers arising from policy measures based on current area, the price of fer�lizer or pes�cide for applica�on on farm animal numbers, receipts or income, and requiring land, or a payment compensa�ng for yield loss as a produc�on. result of prac�cing organic farming, is clearly agricultural and producer specific and are also included in the PSE. Category C is further broken into two subcategories: The impact of policy measures on variables such as produc�on, consump�on, trade, income, employment C.1. Based on current receipts/income—including and the environment depend, among other factors, on transfers through policy measures based on receipts or the way policy measures are implemented. Therefore, to income. be helpful for policy analysis, policy measures to be included in the PSE are classified according to imple- C.2. Based on current area/animal numbers—including menta�on criteria. transfers through policy measures-based area/animal numbers For a given policy measure, the implementa�on criteria are defined as the condi�ons under which the associa- D. Payments based on non-current A/An/R/I, produc- ted transfers are provided to farmers, or the condi�ons �on required of eligibility for the payment. Transfers from taxpayers to agricultural producers Here are the main criteria used to classify programs arising from policy measures based on non-current (i.e., according to OECD categories: historical) area, animal numbers, receipts or income, with current produc�on of any commodity required. I. PSE CATEGORIES E. Payments based on non-current produc�on, produc A.1. Market price support (MPS)—transfers from �on not required: transfers from taxpayers to agricultu- consumers and taxpayers (consump�on subsidies) to ral producers arising from policy measures based on agricultural producers arising from policy measures that non-current (i.e., historical or fixed) area, animal num- create a gap between domes�c market prices and bers, receipts or income, with current produc�on of any border prices of a specific agricultural commodity, mea- commodity not required but op�onal. sured at the farm gate level. Category E is further divided in two sub-categories A.2. Payments based on output—transfers from taxpa- according to the nature of payment rates used: yers to agricultural producers from policy measures based on current output of a specific agricultural com- E.1. Variable rates—transfers using payment rates modity which vary with respect to levels of current output or input prices, or produc�on/yields and/or area. B.1 Payments based on variable input use—transfers E.2. Fixed rates—transfers using payment rates which reducing the on-farm cost of a specific variable input or do not vary with respect to these parameters. a mix of variable inputs. F. Payments based on non-commodity criteria: trans- B.2. Fixed capital forma�on—transfers reducing the fers from taxpayers to agricultural producers arising 48 from policy measures based on: ving agricultural produc�on. Includes payments to ins�- tu�ons for research related to agricultural technologies F.1. Long-term resource re�rement—transfers for the and produc�on methods. In most cases, these payments long-term re�rement of factors of produc�on from com- include the financing of public research ins�tu�ons modity produc�on. The payments in this subcategory B. Agricultural schools: budgetary payments financing are dis�nguished from those requiring short-term resou- agricultural training and educa�on. Includes the public rce re�rement, which are based on commodity produc- funding of educa�on and training targeted specifically �on criteria. on the agricultural sector. F.2. A specific non-commodity output—transfers for the C. Inspec�on services: budgetary payments financing use of farm resources to produce specific noncommodi- control of quality and safety of food, agricultural inputs ty outputs of goods and services, which are not required and the environment. Includes payments to finance by regula�ons. ins�tu�ons for the control of food quality, animal health, and agricultural inputs. In most cases, these services are F.3. Other non-commodity criteria—transfers provided financed by public (governmental) organiza�ons, and equally to all farmers, such as a flat-rate or lumpsum hence the budgets of these organiza�ons are included. If payment. the unpaid services are provided on farms (e.g., animal vaccina�ons), the corresponding costs should be alloca- G. Miscellaneous payments: transfers from taxpayers to ted to the PSE. farmers for which there is insufficient informa�on to allocate them to the appropriate categories. D. Infrastructure: budgetary payments financing impro- vement of off-farm collec�ve infrastructure. Includes II. General Services Support Es�mates public expenditure financing the development of Policy measures included in the General Services produc�on-related infrastructure in rural areas. It is Support Es�mate (GSSE) are classified into one of seven important to dis�nguish support between on- and categories according to the nature of the services provi- off-farm infrastructures. ded to agriculture in general (and not to individual producers or consumers). E. Marke�ng and promo�on: budgetary payments The transfers in the GSSE are payments to eligible priva- financing assistance to marke�ng and promo�on of te or public services provided to agriculture generally. agro-food products. This category includes forms of Unlike the PSE and CSE, the GSSE transfers are not des�- government assistance to increase sales of primary ned to individual producers or consumers, and do not agricultural commodi�es, such as agricultural exhibi- directly affect farm receipts (revenue) or consump�on �ons, fairs, promo�onal campaigns, adver�sing, and expenditure, although they may affect produc�on or publica�ons consump�on of agricultural commodi�es in the longer term. F. Public stockholding: budgetary payments mee�ng the Services that benefit primary agriculture but whose costs of storage, deprecia�on and disposal of public ini�al incidence is not at the level of individual farmers: storage of agricultural products. Includes budgetary for example, agricultural educa�on, research, marke�ng expenditures that finance investments and opera�ng and promo�on of agricultural goods, general infrastruc- cost for off-farm storage and other market infrastructure tural investment rela�ng to irriga�on, and inspec�on facili�es related with handling or marke�ng agricultural services beyond the farm gate. products (silos, docks, etc.) While implementa�on criteria are used to dis�nguish whether the transfer is allocated to PSE or GSSE, the G. Miscellaneous: budgetary payments financing other defini�on of the categories in the GSSE and the alloca- general services that cannot be disaggregated and �on of policy measures to these categories is according allocated to the above categories due, for example, to a to the nature of the service, as the following: lack of informa�on A. Research and development: budgetary payments financing research and development ac�vi�es impro- 49 III. Consumer Support Es�mate type of payment classified under the CSE is budgetary transfers to consumers of agricultural commodi�es, The CSE includes price transfers from consumers, which where these are provided specifically to offset the is the inverse value of Market Price Support. A compo- higher prices resul�ng from market price support. Fina- nent of the CSE is transfers associated with market price lly, consump�on subsidies in cash or in kind (their mone- support for the produc�on of commodi�es that are tary equivalent) associated with programs of market consumed domes�cally; these are called price transfers price support for domes�c producers are also included from (to) consumers. These transfers are the same as in the CSE. This component includes, for example, those included in the PSE under category Market Price domes�c food aid programs. Support, but they are given an opposite sign in the CSE and adjusted to apply to quan��es consumed. Another 50 Annex C because they rank consistently among the top five Conceptual Note on Price Collec�on of Agricul- provinces in terms of total cul�vated area, cul�vated tural Producers area under maize, maize produc�on and maize sales; as well as in terms of chicken and pork produc�on, making I. Introduc�on these provinces rela�vely important, as illustrated in Table 1 below. Furthermore, Manica and Nampula are The objec�ve of this annex is to describe the methodo- also two main surplus markets supplying agricultural logy employed to collect data for selected agricultural commodi�es to the deficit Maputo province in Southern commodi�es to enable computa�on – using the Organi- Mozambique. Empirical evidence also shows that za�on for Economic Coopera�on and Development Manica and Nampula markets exhibit price causality in (OECD) methodology – of the main indicators of support the Granger sense with Maputo market, sugges�ng that to agriculture: (i) producer support es�mate (PSE), (ii) price changes in one market have influence on price consumer support es�mate (CSE), (iii) general service changes in another market. support es�mate (GSSE), and (iv) total support es�mate (TSE). We conducted a census of traders (including producers who sell their produc�on) of the seven commodi�es in II. Sample selec�on two open markets (Mercado Uaresta in Nampula and Mercado 38 in Manica). Some producers of agricultural Covered agricultural commodi�es include cassava, commodi�es were also distributors. Face-to-face inter- maize, sweet potato, potato, tomato, chicken, and pork views were conducted between 19 January 2021 and 23 meat. These commodi�es were selected because they January 2021 to collect recall data for the 2017/2018 accounted for more than 70.0% of the total value of and 2018/2019 agricultural seasons. The data collec�on gross agricultural output in Mozambique for 2018 and period coincided with the lean season; hence, agricultu- 2019. Farm-gate prices, transport costs and storage ral commodi�es were scarce in the markets. A total of 60 costs for these agricultural commodi�es are not availa- interviews were completed (39 in Nampula province and ble from official sta�s�cs reported by the Mozambique 21 in Manica province). This sample sizes are compara- Na�onal Ins�tute of Sta�s�cs (INE) and the Ministry of ble to that of MADER for price data collec�on through Agriculture and Rural Development (MADER). Hence, we their Agricultural Market Informa�on System (SIMA) collected required data in Manica province in Northern under which three observa�ons per day of data collec- Mozambique and Nampula province in Central Mozam- �on are collected for each tracked agricultural commo- bique. Manica and Nampula were purposively sampled dity. Table 7. Contribu�on in total cul�vated area, sales and produc�on Cul�vated area Maize Produc�on Province Maize Total sales Maize Cassava Chicken Pork Niassa 5.5% 4.6% 11.3% 8.1% 1.5% 0.6% 6.4% Cabo Delgado 6.5% 8.1% 4.9% 6.2% 8.7% 0.7% 4.8% Nampula 7.6% 16.4% 12.3% 10.2% 41.8% 12.6% 19.5% Zambezia 16.4% 20.0% 16.5% 16.3% 32.1% 0.7% 14.0% Tete 19.1% 16.2% 37.7% 28.3% 1.6% 0.8% 11.1% Manica 12.0% 8.6% 10.3% 13.5% 1.4% 6.3% 3.9% Sofala 16.1% 12.9% 5.9% 11.3% 2.4% 0.5% 13.2% Inhambane 3.0% 3.7% 0.4% 1.0% 4.2% 1.7% 13.9% Gaza 11.2% 7.2% 0.3% 4.0% 2.9% 3.3% 5.3% Maputo 2.7% 2.5% 0.4% 1.2% 3.5% 72.9% 7.8% Total 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 51 the cost of expenses related to ac�vi�es carried out III. Gathered informa�on for conserva�on and handling of commodi�es – including, but not limited to, manual or mechanical We collected the following informa�on during the cleaning, grading, slaughtering, cu�ng, and packa- face-to-face interviews: ging, but excluding shipping cost – to make them usable as food, feed or industrial raw material; • Price received by producers at farm gate • Storage costs at the market: The computa�on level: Interviewees were asked about prices during was similar to that of the transport cost. This cost the harvest and lean seasons. We considered prices includes payments for warehouse storage only; in the lean season only because we had very few All Above-men�oned informa�on, collected through observa�ons for prices in the harvest season. It is face-to-face interviews, is considered representa�ve of possible that these prices in the lean season are domes�c markets as they reflect informa�on in the main affected by the seasonality effect. Empirical evidence markets of the country where agricultural commodi�es show that retail maize prices have high seasonal price are traded. Prices received by producers at farm gate varia�on ranges with a seasonal price increase of and paid by consumers at the market are summarized in 75% in Manica and 70% in Nampula between 2000 Figures 1 and 2 below. For both prices received by and 2015. Agricultural commodi�es are generally producers and paid by consumers, as expected, livestock sold using nonstandard units such as cans of 20 liters commodi�es have higher prices compared to crop com- or sacks of 12.5 kgs among others. For this case, modi�es. For all commodi�es except tomato, both prices per ton were es�mated by dividing reported prices trended upward between the 2017/2018 and price charged for nonstandard units by the average 2018/2019 agricultural seasons. Prices were validated weight of the nonstandard unit (kgs) and then mul�- by government technical staff. plied by 1,000; • Prices paid by consumers at the market: The es�ma�on was similar to that of the farm-gate-level prices; • Transport cost from the farm gate to the market: For crop commodi�es, usually transported in packages of various sizes, transport cost per ton was computed by dividing the payment per package by the average weight (kgs) of the package and then mul�plied by 1,000. For livestock commodi�es, usua- lly transported live animals, transport cost per ton was es�mated by dividing the payment per animal by the average carcass weight (kgs) and then mul�plied by 1,000. Transport cost includes the payment for loading the commodity, truck transporta�on, and unloading. Transport market is noncompe��ve with a few transporters, making transport cost rela�vely higher especially in Northern and Central Mozambi- que. Bad road condi�ons exacerbate transport cost. Data from INE show that about 50.0% of classified roads in Mozambique are in bad condi�ons; of which 39.9% are located in Central Mozambique and 35.9% in Northern Mozambique; • Processing and handling cost: This was com- puted by dividing the processing and handling payment by the average weights (kgs) of the reported unit and then mul�plied by 1,000. This cost refers to 52 Figure 33. Average farm-gate prices over commodity over year Figure 34. Average consumer price over commodity over year 53 Transport, processing and handling and storage costs for like prices, transport, processing and handling and stora- year 2018 are summarized in Table 1 below. Similar ge costs are generally higher for crop commodi�es than figures were reported for year 2019. Table 1 shows that livestock commodi�es. Table 8 Transport, processing and handling and storage costs ('000 MZN per ton) Mean Standard devia�on Commodity Transport Processing Storage Transport Processing Storage Maize 1.36 1.57 0.24 0.80 1.16 0.05 Cassava 1.20 1.95 0.24 0.40 1.10 0.05 Sweet potato 1.10 0.35 0.22 0.34 0.07 0.04 Potato 4.00 - 0.60 1.07 - 0.35 Tomato 2.40 1.45 0.44 1.57 1.48 0.17 Chicken 4.28 - 0.12 1.95 - 0.02 Pork meat 9.20 - - 2.52 - - 54 Annex D Public Programs and Budgetary Expenditure Figure 35: Budget PSE, by Category and Program A. Apoio com base na produção de commodi�e A.2 Apoios com base na produção Origem Unidade 2018 INTENSIFICAR A PRODUCAO DE CULTURAS ALIMENTARES(CEREAIS E DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA LEGUMINOSAS ) ALIMENTAR DE CABO DELGADO MZ Mill 5.94 Apoio com base na produção de commodi�es A.2 Apoios com base na produção PRODUCAO DE HORTICULAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NAMPULA MZ Mill 1.65 PROJECTO DE DESENVOLVIMENTO DE CADEIAS DE VALOR NOS CORREDORES DELEGAÇÃO PROVINCIAL DO FUNDO DE MZ Mill 52.61 DO MAPUTO E LIMPOPO (PROSUL) DESENVOLVIMENTO AGRARIO DE GAZA Total Mz Mill 60.20 Asignacion Apoios (todos) Origem Unidade 2018 MANDIOCA Incluye varios programas MZ Mill 77.70 TOMATOE MZ Mill 3.81 MILHO MZ Mill 4.76 SWEET POTATOE MZ Mill 2.50 CERDO MZ Mill 3.37 TOTAL ASIGNADO MZ Mill 92.15 OUTRAS MZ Mill -31.95 Apoios produtos SELECCIONADOS Origem Unidade 2018 ARROZ MZ Mill CAFÉ MZ Mill PESCAS MZ Mill BATATA MZ Mill MILHO MZ Mill Total alocado para produtos selecionados MZ Mill 0.00 Total A.2 60.20 55 B. Apoios com base no uso de insumos B. 1. Com base no uso de insumos variáveis Apoios Diversos Origem Unidade 2018 PROJECTO DE DESENVOLVIMENTO DE CADEIAS DE VALOR NOS CORREDORES PROSUL MZ Mill 52.61 DO MAPUTO E LIMPOPO (PROSUL) INTENSIFICAR A PRODUCAO DE CULTURAS ALIMENTARES(CEREAIS E DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA MZ Mill 5.94 LEGUMINOSAS ) ALIMENTAR DE CABO DELGADO DIVERSOS DIVERSOS provienen del archivo MZ productos95.82 deMill no seleccionados. Ojo: Solo incluyen INTENSIFICACAO E DIVERSIFICACAO DE CULTURAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NAMPULA; DIRECCAO PROVINCIAL DA MZ Mill 17.13 AGRICULTURA E SEGURANÇA ALIMENTAR DE MAPUTO PROVINCIA PROGRAMA DE APOIO AS FINANCAS RURAISPAFR FUNDO DE APOIO A REABILITACAO DA ECONOMIA MZ Mill 0.21 Total MZ Mill 171.71 Asignacion Apoios Diversos Unidade 2018 MANDIOCA PROSUL MZ Mill 124.18 TOMATOE MZ Mill 10.88 MILHO MZ Mill 13.58 SWEET POTATOE MZ Mill 7.14 B. 1. Com base no uso de insumos variáveis B. Apoios com base no uso de insumos CERDO MZ Mill 9.63 TOTAL ASIGNADO MZ Mill 155.78 OTROS MZ Mill 15.93 Apoios SEMENTES Origem Unidade 2018 PROJECTO DE PRODUCAO LOCAL DE SEMENTE DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE INHAMBANE MZ Mill 3.97 Total MZ Mill 3.97 Asignación Apoios SEMILLAS Origem Unidade 2018 MANDIOCA MZ Mill 2.01 TOMATOE MZ Mill 0.31 MILHO MZ Mill 0.38 SWEET POTATOE incluye varios programas 0.20 MZ Mill Prorrateados con VP Agricola TOTAL ASIGNADO MZ Mill 2.90 OTROS MZ Mill 1.08 Apoios FERTILIZANTES Origem Unidade 2018 Total MZ Mill 0.00 Asignación Apoios Fer�lizantes Unidade 2018 MANDIOCA MZ Mill 0.00 TOMATOE MZ Mill 0.00 MILHO MZ Mill 0.00 SWEET POTATOE MZ Mill 0.00 TOTAL ASIGNADO MZ Mill 0.00 OTROS MZ Mill 0.00 Apoios para productos pecuarios Origem Unidade 2018 PROMOVER PROGRAMAS DE FOMENTO PECUARIO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DA ZAMBEZIA MZ Mill 6.69 INCENTIVAR A PRODUCAO PECUARIA DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE CABO DELGADO MZ Mill 22.75 PROJECTO DE PRODUCAO DE FENO PARA A SUPLEMENTACAO DO GADO NA DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA EPOCA SECA ALIMENTAR DE MANICA MZ Mill 0.56 en segundo calculo incluido Total alocado para produtos pecuarios MZ Mill 30.01 ASIGNACIÓN A PECUARIOS APOIOS Origem MZ Mill 2018 CERDO MZ Mill 22.60 con VP Pecuario Prorrateado TOTAL ASIGNADO MZ Mill 22.60 OTROS MZ Mill 7.41 TOTAL B1 Mz Mill 205.69 56 B 2. Com base no formação de capital fixo INVERSION ACTIVOS FIJOS Origem Unidade 2018 PROJECTO DE DESENVOLVIMENTO DE CADEIAS DE VALOR NOS CORREDORES DELEGAÇÃO PROVINCIAL DO FUNDO DE DO MAPUTO E LIMPOPO (PROSUL) MZ Mill 52.61 DESENVOLVIMENTO AGRARIO DE GAZA Aparentemente el presupuesto es de un solo programa ESTABELECIMENTO DE ESTUFAS PARA PRODUCAO DE HORTICOLAS DELEGAÇÃO PROVINCIAL DO FUNDO DE MZ Mill 4.15 DESENVOLVIMENTO AGRARIO DE NAMPULA PROSUL DELEGAÇÃO PROVINCIAL DO FUNDO DE MZ Mill 52.61 DESENVOLVIMENTO AGRARIO DE GAZA PROSUL ESTABECIMENTO DE ESTUFAS PARA PRODUCAO DE HORTICOLAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA MZ Mill 5.81 ALIMENTAR DE NAMPULA Fao Indica que es solo hor�cola. Deberia asignarse a todos ESTABELECIMENTO DE ESTUFAS PARA PRODUCAO DE HORTICOLAS DELEGAÇÃO PROVINCIAL DO FUNDO DE MZ Mill 4.15 DESENVOLVIMENTO AGRARIO DE NAMPULA Fao Indica que es solo hor�cola. Deberia asignarse a todos PROSUL DELEGAÇÃO PROVINCIAL DO FUNDO DE MZ Mill 52.61 DESENVOLVIMENTO AGRARIO DE GAZA PROSUL DIVERSOS Diversos provienen del archivo deMill MZ no seleccionados. Ojo: Solo incluyen productos13.38 B 2. Com base no formação de capital fixo PROGRAMA DE MACANIZACAO AGRARIA AGENCIA DE DESENVOLVIMENTO DO VALE DO ZAMBEZE MZ Mill FAO 13.11 lo contempla como comercializacion de SSGG B. Apoios com base no uso de insumos FINANCAS E MICROFINANCAS RURAIS MINISTERIO DA TERRA AMBIENTE E DESENVOLVIMENTO MZ Mill 0.16 RURAL incluido en segundo calculo FINANCAS E MICROFINANCAS RURAIS MINISTERIO DA TERRA AMBIENTE E DESENVOLVIMENTO MZ Mill 0.16 RURAL incluido en segundo calculo FINANCAS E MICROFINANCAS RURAIS MINISTERIO DA TERRA AMBIENTE E DESENVOLVIMENTO MZ Mill 0.16 RURAL incluido en segundo calculo TOTAL MZ Mill 198.90 ASIGNACION APOIOS (TODOS) Unidade 2018 MANDIOCA INCLUYE VARIOS PROGRAMAS. MZ Mill Destaca PROSUL 135.51 TOMATOE MZ Mill 12.60 MILHO MZ Mill 15.73 SWEET POTATOE MZ Mill 8.27 CERDO INCLUYE VARIOS PROGRAMAS. VER DIRECTAMENTE MZ Mill 11.81 TOTAL ASIGNADO MZ Mill 183.92 OTROS MZ Mill 14.97 APOIOS PARA PRODUCTOS SELECCIONADOS ORIGEM Unidade 2018 MZ Mill TOTAL ALOCADO PARA PRODUTOS SELECIONADOS MZ Mill 0.00 APOIOS PARA PRODUCTOS PECUARIOS ORIGEM Unidade 2018 FOMENTO PECUARIO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NIASSA MZ Mill 2.52 FOMENTO PECUARIO E REABILITACAO DE INFRAESTRUTURAS PECUARIAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NAMPULA MZ Mill 5.92 PROGRAMA INTEGRADO PARA O DESENVOLVIMENTO PECUARIO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE GAZA MZ Mill 1.45 TOTAL ALOCADO PARA PRODUTOS PECUARIOS MZ Mill 9.89 ASIGNACIÓN A PECUARIOS APOIOS ORIGEM Unidade 2018 CERDO 7.45 MZ Mill Prorrateado con VP Pecuario TOTAL ASIGNADO MZ Mill 7.45 OTROS MZ Mill 2.44 TOTAL B2 MZ Mill 208.79 57 B 3. Serviços on-farm APOIOS EXTENSION ORIGEM Unidade 2018 DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA PRODUCAO DE HORTICULAS MZ Mill 1.65 ALIMENTAR DE NAMPULA DIVERSOS DE EXTENSIONISMO DIVERSOS MZ Mill 167.81 DIVERSOS TRANSFERENCIA TECNOLOGIA DIVERSOS MZ Mill 27.96 DIVERSOS DIVERSOS MZ Mill 4.63 APOIO A PRODUCAO AGRICOLA MINISTERIO DA AGRICULTURA E SEGURANCA ALIMENTAR MZ Mill 53.23 ASSISTENCIA TECNICA E FINANCEIRA AS INICIATIVAS DE AGENCIA DE DESENVOLVIMENTO DO VALE DO ZAMBEZE MZ Mill 470.50 DESENVOLVIMENTO ECONOMICO E SOCIAL NO VALE DO ZAMBEZE DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ESTABELECER VIVEIROS DE FRUTEIRAS DIVERSAS MZ Mill 0.10 ALIMENTAR DE NIASSA DIRECCAO PROVINCIAL DA TERRA, AMBIENTE E GESTAO DE TERRAS MZ Mill 2.95 DESENVOLVIMENTO RURAL DE SOFALA DIRECCAO PROVINCIAL DA TERRA, AMBIENTE E DESENVOLVIMENTO RURAL DE MAPUTO PROVINCIA; GESTAO DE TERRAS MZ Mill 7.14 DIRECCAO PROVINCIAL DA TERRA, AMBIENTE E DESENVOLVIMENTO RURAL DE TETE DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA B. Apoios com base no uso de insumos INTENSIFICACAO E DIVERSIFICACAO DE CULTURAS MZ Mill 7.15 ALIMENTAR DE NAMPULA DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA INTENSIFICACAO E DIVERSIFICACAO DE CULTURAS MZ Mill 9.98 ALIMENTAR DE MAPUTO PROVINCIA PROGRAMA DE APOIO AS FINANCAS RURAISPAFR FUNDO DE APOIO A REABILITACAO DA ECONOMIA MZ Mill 0.21 PROJECTO DE DESENVOLVIMENTO DAS CADEIAS DE VALOR FUNDO DO DESENVOLVIMENTO AGRARIO MZ Mill 7.33 DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA PROMOVER PROGRAMAS DE FOMENTO PECUARIO MZ Mill 6.69 ALIMENTAR DA ZAMBEZIA INSTITUTO DE FOMENTO DO CAJU; FUNDO DO APOIO AO DESENVOLVIMENTO AGRARIO MZ Mill 410.15 B 3. Serviços on-farm DESENVOLVIMENTO AGRARIO incluido en segundo calculo PROMOCAO DE PRODUCAO E PRODUCTIVIDADE AGRICOLA NOS CENTROS ESTABELECIMENTO PENITENCIARIO REGIONAL NORTE MZ Mill 2.11 PENITENCIARIOS ABERTOS NAMPULA incluido en segundo calculo AGRO-PECUARIA FUNDO NACIONAL DE DESENVOLVIMENTO SUSTENTAVEL MZ Mill 60.00 incluido en segundo calculo ESTABELECIMENTO PENITENCIARIO PROVINCIAL DE PRODUCAO AGRO-PECUARIA MZ Mill 1.35 NAMPULA incluido en segundo calculo INTENFICACAO DA PRODUCAO AGRICOLA ESTABELECIMENTO PENITENCIARIO PROVINCIAL DE GAZA MZ Mill 2.70 incluido en segundo calculo APOIO AO DESENVOLVIMENTO AGRARIO FUNDO DO DESENVOLVIMENTO AGRARIO MZ Mill 30.07en segundo calculo incluido PROJECTO DE DESENVOLVIMENTO DAS CADEIAS DE VALOR FUNDO DO DESENVOLVIMENTO AGRARIO MZ Mill 7.33 en segundo calculo incluido TOTAL MZ Mill 1281.06 ASIGNACIÓN APOIOS EXTENSION ORIGEM Unidade 2018 MANDIOCA MZ Mill 533.97 Destaca PROSUL TOMATOE MZ Mill 81.15 MILHO MZ Mill 101.34 SWEET POTATOE MZ Mill Iden54.85 �ficados para mandioca CERDO MZ Mill 72.48 TOTAL ASIGNADO MZ Mill 843.80 OTROS MZ Mill 437.26 APOIOS PARA PRODUCTOS SELECCIONADOS ORIGEM Unidade 2018 TOTAL ALOCADO PARA PRODUTOS SELECIONADOS MZ Mill 0.00 APOIOS PARA PRODUCTOS PECUARIOS ORIGEM Unidade 2018 FOMENTO PECUARIO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE SOFALA MZ Mill 3.38 FOMENTO PECUARIO E REABILITACAO DE INFRAESTRUTURAS PECUARIAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NAMPULA MZ Mill 2.96 TOTAL ALOCADO PARA PRODUTOS PECUARIOS MZ Mill 6.34 ASIGNACIÓN A PECUARIOS APOIOS EXTENSION ORIGEM Unidade 2018 CERDO 4.77 MZ Mill Prorrateado con VP Pecuario TOTAL ASIGNADO MZ Mill 4.77 OTROS MZ Mill 1.56 TOTAL B3 MZ Mill 1287.39 58 C. Apoios com base na produção A /An/ I. Produccion necessária C. 1. Com base na receita C. Pagamentos com base na produção A /An/ I. Produccion necessária C. 1. Com base na receita Total C1 0.00 C. 2. Com base na área ou número de animais C. 2. Com base na área ou número EXEMPLO: APOIOS DESASTRE ORIGEM Unidade 2018 TOTAL MZ Mill 0.00 de animais ASIGNACION APOIOS (TODOS) Unidade 2018 MANDIOCA MZ Mill 0.0 TOMATOE MZ Mill 0.0 MILHO MZ Mill 0.0 SWEET POTATOE MZ Mill 0.0 CERDO MZ Mill 0.0 TOTAL ASIGNADO MZ Mill 0.00 OTROS MZ Mill 0.00 TOTAL C2 MZ Mill 0.00 59 D. Apoios com base em A / AN / I NÃO Atual. Produção necessária D. Apoios com base em A / AN / I NÃO Atual. Produção necessária ORIGEM Unidade 2018 TOTAL MZ Mill 0.00 ASIGNACION APOIOS (TODOS) Unidade 2018 MANDIOCA MZ Mill 0.0 TOMATOE MZ Mill 0.0 MILHO MZ Mill 0.0 SWEET POTATOE MZ Mill 0.0 CERDO MZ Mill 0.0 TOTAL ASIGNADO MZ Mill 0.00 OTROS MZ Mill 0.00 TOTAL D. MZ Mill 0.00 60 E. Apoios com base em A / AN / I NÃO Atual. Produção Não necessária E.1. Taxas variables E. Apoios com base em A / AN / I NÃO Atual. Produção NO necessária PROGRAMA ORIGEM Unidade 2018 E.1. Taxas variables TOTAL MZ Mill 0.00 ASIGNACION APOIOS (TODOS) Unidade 2018 MANDIOCA MZ Mill 0.00 TOMATOE MZ Mill 0.00 MILHO MZ Mill 0.00 SWEET POTATOE MZ Mill 0.00 CERDO MZ Mill 0.00 TOTAL ASIGNADO MZ Mill 0.00 OTROS MZ Mill 0.00 TOTAL E1 MZ Mill 0.00 E.2 Tasas Fixas EXEMPLO: APOIO DIRECTO RENTA Origem Unidade 2018 TOTAL MZ Mill 0.00 E.2 Tasas Fixas ASIGNACION APOIOS (TODOS) Unidade 2018 MANDIOCA MZ Mill 0.00 TOMATOE MZ Mill 0.00 MILHO MZ Mill 0.00 SWEET POTATOE MZ Mill 0.00 CERDO MZ Mill 0.00 TOTAL ASIGNADO MZ Mill 0.00 OTROS MZ Mill 0.00 TOTAL E2 Mz Mill 0.00 61 F. Apoios com base em critérios de não relacionados a commodi�es F.1. Recurso de longo prazo F.1. Recurso de longo prazo APOIOS REFORESTACION ORIGEM Unidade 2018 TOTAL MZ Mill 0.00 ASIGNACION APOIOS ENERGIA (TODOS) Unidade 2018 MANDIOCA MZ Mill 0.00 TOMATOE MZ Mill 0.00 MILHO MZ Mill 0.00 SWEET POTATOE MZ Mill 0.00 CERDO MZ Mill 0.00 TOTAL ASIGNADO MZ Mill 0.00 OTROS MZ Mill 0.00 TOTAL F1 MZ Mill 0.00 F.2. Um produto não commodity específico F.2. Um produto não commodity específico F. Apoios com base em critérios de não commodi�es APOIO PRODUCCION DE FROJOLES SIN FERTILIZANTES QUIMICOS ORIGEM Unidade 2018 TOTAL MZ Mill 0.00 ASIGNACION APOIOS ENERGIA (TODOS) Unidade 2018 MANDIOCA MZ Mill 0.00 TOMATOE MZ Mill 0.00 MILHO MZ Mill 0.00 SWEET POTATOE MZ Mill 0.00 CERDO MZ Mill 0.00 TOTAL ASIGNADO MZ Mill 0.00 OTROS MZ Mill 0.00 TOTAL F2 MZ Mill 0.00 F.3. Outros critérios não rela�vos a commodi�es F.3. Outros critérios não rela�vos a commodi�es TOTAL F3 Mz Mill 0.00 62 G. Otros G.Otros TOTAL G Mz Mill 0.00 63 Figure 36: Budget GSSE, by Category and Project H. Conhecimento Agrícola Programa Origem Unidade 2,018.00 ANALISES LABORATORIAIS DE SOLO E PLANTAS CENTRO REGIONAL DA ZONA NORDESTE DO IIAM DE NAMPULA UGB Mz Mill 0.82 DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE CONTROLO E INSEMINACAO DE GADO BOVINO Mz Mill 0.12 INHAMBANE DESENVOLVER VARIEDADES ADAPTADAS A DIVERSAS CONDICOES AGOECOLOGICAS E COM CARACTERISTICAS DESEJAVEIS PARA O CONSUMO BEM COMO AVALIAR E CENTRO REGIONAL DA ZONA NOROESTE DO IIAM DE NIASSA Mz Mill 0.40 DESENVOLVER TECNOLOGIAS DE PRODUCAO (PRATICAS AGRONOMICAS) ADAPTADAS AS MESMAS CONDICOES GERAR VARIEDADES DE CULTURAS ALIMENTARES COM ALTA PRODUTIVIDADE PARA GARANTIR A SEGURANCA ALIMENTAR CENTRO REGIONAL DA ZONA NORDESTE DO IIAM DE NAMPULA UGB Mz Mill 1.16 NA REGIAO NORDESTE INSEMINACAO ARTIFICIAL DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE GAZA Mz Mill 1.03 MAPEAMENTO DAS ZONAS ARIDAS E SEMI-ARIDAS INSTITUTO NACIONAL DE GESTAO DAS CALAMIDADES Mz Mill 3.99 MELHORAMENTO GENETICO DE RACAS LOCAIS PARA CENTRO REGIONAL DA ZONA NORDESTE DO IIAM DE NAMPULA UGB Mz Mill 1.66 PRODUCAO DE CARNE E LEITE PRODUCAO DE SEMENTE BASICA DE CULTURAS ALIMENTARES CENTRO REGIONAL DA ZONA SUL DO IIAM DE GAZA/CHOKWE Mz Mill 3.15 RAMA DE BATATA DOCE ESTACAS DE MANDIOCA E FRUTEIRAS PRODUCAO DE SEMENTES BASICA INSTITUTO DE INVESTIGACAO AGRARIA DE MOCAMBIQUE Mz Mill 8.16 PRODUZIR SEMENTE DE DIVERSAS CULTURAS PRATICADAS NA CENTRO REGIONAL DA ZONA NORDESTE DO IIAM DE NAMPULA UGB Mz Mill 1.22 REGIAO PRODUZIR SEMENTES PRE BASICA E BASICA E INSTALAR UM CENTRO REGIONAL DA ZONA NOROESTE DO IIAM DE NIASSA Mz Mill 0.77 VIVEIRO MULTIPLO PARA PRODUCAO DE MUDAS PROJECTO DE ADAPTACAO E GERACAO DE NOVAS VARIEDADES H. Conhecimento Agrícola INSTITUTO DE INVESTIGACAO AGRARIA DE MOCAMBIQUE Mz Mill 11.02 E CULTURAS ALIMENTARES E INDUSTRIAIS PROJECTO DE AQUISICAO DE TOUROS E BODES MELHORADOS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE MANICA Mz Mill 2.33 PROMOVER DISSEMINAR E PUBLICAR TECNOLOGIAS AGRARIAS CENTRO REGIONAL DA ZONA NOROESTE DO IIAM DE NIASSA Mz Mill 0.20 AOS PRODUTORES REALIZACAO DE FORMACOES E TREINAMENTOS NA CADEIA DE CENTRO REGIONAL DA ZONA NORDESTE DO IIAM DE NAMPULA UGB Mz Mill 0.55 VALOR DE FRUTAS REFORCO A COORDENACAO DO PROSAVANA MINISTERIO DA AGRICULTURA E SEGURANCA ALIMENTAR Mz Mill 1.64 REFORCO INSTITUCIONAL A INVESTIGACAO AGRARIA DE INSTITUTO DE INVESTIGACAO AGRARIA DE MOCAMBIQUE Mz Mill 15.79 MOCAMBIQUE DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE ASSISTENCIA TECNICA AOS PRODUTORES Mz Mill 2.65 MAPUTO PROVINCIA ASSISTIR PRODUTORES EM TECNOLOGIAS DE EXTENSAO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DA Mz Mill 2.65 AGRARIAS ZAMBEZIA CAPACITACAO E TRANSFERENCIA METODOLOGICA PARA O FUNDO DO DESENVOLVIMENTO AGRARIO Mz Mill 44.41 PROGRAMA MAIS ALIMENTOS AFRICA EM MOCAMBIQUE CONSTRUCAO DE AVIARIO INSTITUTO SUPERIOR POLITECNICO DE GAZA Mz Mill 1.90 CONSTRUCAO DE LABORATORIO DA ESCOLA AGRO-PECUARIA DIRECCAO PROVINCIAL DE CIENCIA E TECNOLOGIA, ENSINO SUPERIOR E TECNICO Mz Mill 1.50 DE CAIA E PROFISSIONAL DE SOFALA GESTAO DE INTERNATO ESTAGIO E PRODUCAO DE HORTICULAS INSTITUTO MEDIO DE PLANEAMENTO FISICO E AMBIENTE Mz Mill 2.58 E ANIMAIS DE PEQUENOS RUMINANTES INCUBACAO DE JOVENS NA PRODUCAO INTENSIVA DE AVES E DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE Mz Mill 1.58 AGRONEGOCIO MAPUTO CIDADE APOIO AS CALAMIDADES NATURAIS DIRECCAO PROVINCIAL DA EDUCACAO E DESENVOLVIMENTO HUMANO DE TETE Mz Mill 4.75 DIRECCAO PROVINCIAL DA EDUCACAO E DESENVOLVIMENTO HUMANO DE RECONSTRUCAO POS CALAMIDADES Mz Mill 2.80 INHAMBANE DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DA INTENSIFICAR A PRODUCAO DE CULTURAS ALIMENTARES Mz Mill 16.40 ZAMBEZIA APOIO AO DESENVOLVIMENTO AGRARIO FUNDO DO DESENVOLVIMENTO AGRARIO Mz Mill 30.07 DIRECCAO PROVINCIAL DA TERRA, AMBIENTE E DESENVOLVIMENTO RURAL DE PREVENCAO E COMBATE A EROSAO DE SOLOS Mz Mill 0.85 GAZA PROGRAMA INTEGRADO PARA O DESENVOLVIMENTO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE GAZA Mz Mill 1.45 PECUARIO PROJECTO DE DESENVOLVIMENTO DAS CADEIAS DE VALOR FUNDO DO DESENVOLVIMENTO AGRARIO Mz Mill 7.33 ESTABELECER VIVEIROS DE FRUTEIRAS DIVERSAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NIASSA Mz Mill 0.10 TOTAL Conhecimento Agrícola Mz Mill 175.05 64 I. Inspeção e Controle Program Origem Unidade 2,018.00 APOIO AO PROGRAMA DE VACINACAO E SANIDADE I. Inspeção e Controle DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE TETE Mz Mill 1.89 ANIMAL CONTROLO DE PRAGAS NAS CULTURAS ALIMENTARES NO Mz Mill DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE MANICA 1.16 SECTOR FAMILIAR PROJECTO DE PRODUCAO DE VACINAS PARA ANIMAIS INSTITUTO DE INVESTIGACAO AGRARIA DE MOCAMBIQUE Mz Mill 8.68 PROJECTO DE VACINACOES OBRIGATORIAS Mz Mill DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE MANICA 1.57 REALIZAR CAMPANHAS DE VACINACAO OBRIGATORIA Mz Mill DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DA ZAMBEZIA 1.65 VACINAR ANIMAIS CONTRA RAIVA NEW CASTLE DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NIASSAMz Mill 0.41 CARBUNCULO EMATICO E SINTOMATICO REABILITACAO DE INFRAESTRUTURAS DE ARMAZEM DE Mz Mill DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NAMPULA 2.72 SEMENTE LABORATORIO E EDIFICIO PRINCIPAL Mz Mill TOTAL Inspeção e Controle Mz Mill 18.09 65 J. Desenvolvimento e Manutenção de Infraestrutura Program Origem Unidade 2,018.00 AQUISICAO DE EQUIPAMENTO E INSTRUMENTOS DE IRRIGACAO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE TETE Mz Mill 0.02 CONSTRUCAO DA BARRAGEM MOAMBA MAJOR ADMINISTRACAO REGIONAL DAS AGUAS DO SUL Mz Mill 31.22 CONSTRUCAO DE INFRA ESTRUTURAS PECUARIAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE INHAMBANE Mz Mill 0.51 CONSTRUCAO DE INFRAESTRUTURAS HIDRAULICAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE INHAMBANE Mz Mill 1.53 CONSTRUCAO E REABILITACAO DE INFRA ESTRUTURAS DE IRRIGACAO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE TETE Mz Mill 5.94 CONSTRUCAO E REABILITACAO DE INFRAESTRUTURAS AGRARIAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE MAPUTO PROVINCIA Mz Mill 22.83 ELECTRIFICACAO DO SISTEMA DE IRRIGACAO DO DISTRITO DO DONDO DIRECCAO PROVINCIAL DOS RECURSOS MINERAIS E ENERGIA DE SOFALA Mz Mill 18.05 NA LOCALIDADE DE MANDRUZE ESTABELECIMENTO DE INFRAESTRUTURAS DE SUPORTE E FACILITACAO AGENCIA DE DESENVOLVIMENTO DO VALE DO ZAMBEZE Mz Mill 41.41 DE NEGOCIO PUBLICO E PRIVADO ESTUDOS PARA PROJECTOS DE INFRAESTRUTURAS HIDRO-AGRICOLAS INSTITUTO NACIONAL DE IRRIGACAO Mz Mill 1.78 HIDRAULICA DE CHOCKWE MINISTERIO DA AGRICULTURA E SEGURANCA ALIMENTAR Mz Mill 10.15 MELHORAMENTO DO SISTEMA DE REGA DRENAGEM E FONTES PARA DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE GAZA Mz Mill 4.40 ABEBERAMENTO DE GADO MONTAGEM DE VIVEIRO DIRECCAO PROVINCIAL DA TERRA, AMBIENTE E DESENVOLVIMENTO RURAL DE NAMPULA Mz Mill 0.47 PROJECTO DE IRRIGACAO DO VALE DO SAVE (PIVASA) FUNDO DO DESENVOLVIMENTO AGRARIO Mz Mill 27.22 REABILITACAO DA BARRAGEM DE MACARRETANE ADMINISTRACAO REGIONAL DAS AGUAS DO SUL Mz Mill 2.58 REABILITACAO DA BARRAGEM DE MASSINGIR EMPRESTIMO DE ADMINISTRACAO REGIONAL DAS AGUAS DO SUL Mz Mill 36.29 EMERGENCIA J. Desenvolvimento e Manutenção de Infraestrutura REABILITACAO DE SISTEMA DE IRRIGACAO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NIASSA Mz Mill 0.09 REABILITACAO E CONSTRUCAO DE PEQUENAS BARRAGENS ADMINISTRACAO REGIONAL DAS AGUAS DO SUL Mz Mill 129.50 REABILITACAO E MANUTENCAO DA BARRAGEM DE CORUMANA ADMINISTRACAO REGIONAL DAS AGUAS DO SUL Mz Mill 9.90 REABILITACAO/CONSTRUCAO DE REGADIOS INSTITUTO NACIONAL DE IRRIGACAO Mz Mill 1.27 52214 ASFALTAGEM DA ESTRADA NACIONAL N381/R1251: MUEDA- FUNDO DE ESTRADAS Mz Mill 2.20 NEGOMANE AQUISICAO DO SISTEMA DE REGA ESTABELECIMENTO PENITENCIARIO PROVINCIAL DE GAZA Mz Mill 1.94 AQUISICAO E INSTALACAO DE EQUIPAMENTOS METEOROLOGICOS CENTRO REGIONAL DO INSTITUTO NACIONAL DE METEOROLOGIA DE SOFALA Mz Mill 0.45 AQUISICAO E MONTAGEM DE 3 INDUSTRIAS MOAGEIRAS ESTABELECIMENTO PENITENCIARIO REGIONAL CENTRO MANICA Mz Mill 0.81 INVENTARIAR E MAPEAR A EXPLORACAO E APROVEITAMENTO DA TERRA DIRECCAO PROVINCIAL DA TERRA, AMBIENTE E DESENVOLVIMENTO RURAL DA ZAMBEZIA Mz Mill 1.70 MONITORAR A CAMPANHA AGRICOLA DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DA ZAMBEZIA Mz Mill 4.02 REABILITACAO DE ESTACOES HIDROCLIMATOLICAS ADMINISTRACAO REGIONAL DAS AGUAS DO SUL Mz Mill 0.37 REFORCO A COORDENACAO NA IMPLEMENTACAO DE POLITICAS MINISTERIO DA AGRICULTURA E SEGURANCA ALIMENTAR Mz Mill 17.48 AGRARIAS TERRA SEGURA FUNDO NACIONAL DE DESENVOLVIMENTO SUSTENTAVEL Mz Mill 17.48 TRABALHO DE INQUERITO AGRICOLA INTEGRADO DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NAMPULA Mz Mill 17.48 TRABALHO DE INQUERITO AGRICOLA TIA MINISTERIO DA AGRICULTURA E SEGURANCA ALIMENTAR Mz Mill 17.48 DIRECCAO PROVINCIAL DAS OBRAS PUBLICAS, HABITACAO E RECURSOS HÍDRICOSDE CABO AGUA RURAL Mz Mill 5.16 DELGADO 41009: CONSTRUCAO DE PONTES SOBRE OS RIOS LUCITE NHACUARARA FUNDO DE ESTRADAS Mz Mill 15.90 E MUSSAPA CONSTRUCAO DA REPRESA DE MUCANGADZI ADMINISTRACAO REGIONAL DAS AGUAS DO ZAMBEZE Mz Mill 3.61 PROGRAMA NACIONAL DE ABASTECIMENTO DE AGUA E SANEAMENTO DIRECCAO NACIONAL DE ABASTECIMENTO DE AGUA E SANEAMENTO Mz Mill 236.88 RURAL PRONASAR REABILITACAO DA REPRESA DE MORRUMBALA ADMINISTRACAO REGIONAL DAS AGUAS DO ZAMBEZE Mz Mill 1.37 REALIZAR OBRAS DE MELHORAMENTO DE ESTRADAS NAO DIRECCAO PROVINCIAL DAS OBRAS PUBLICAS, HABITACAO E RECURSOS HÍDRICOSDA Mz Mill 13.26 CLASSIFICADAS DE ACESSO AS ZONAS DE PRODUCAO ZAMBEZIA DESENVOLVIMENTO RURAL DIRECCAO PROVINCIAL DA TERRA, AMBIENTE E DESENVOLVIMENTO RURAL DE TETE Mz Mill 0.31 DIRECCAO PROVINCIAL DA TERRA, AMBIENTE E DESENVOLVIMENTO RURAL DE MAPUTO PROMOCAO DO DESENVOLVIMENTO RURAL Mz Mill 0.63 PROVINCIA 35000-MANUTENCAO DE ESTRADAS NAO PAVIMENTADAS FUNDO DE ESTRADAS Mz Mill 576.07 DIRECCAO PROVINCIAL DAS OBRAS PUBLICAS, HABITACAO E RECURSOS HÍDRICOSDE ABASTECIMENTO DE AGUA RURAL Mz Mill 7.98 INHAMBANE PROGRAMA NACIONAL DE ABASTECIMENTO DE AGUA E SANEAMENTO DIRECCAO PROVINCIAL DAS OBRAS PUBLICAS, HABITACAO E RECURSOS HÍDRICOSDE Mz Mill 0.33 RURAL PRONASAR NAMPULA PROGRAMA NACIONAL DE ABASTECIMENTO DE AGUA E SANEAMENTO DIRECCAO PROVINCIAL DAS OBRAS PUBLICAS, HABITACAO E RECURSOS HÍDRICOSDE TETE Mz Mill 0.42 RURAL PRONASAR PROGRAMA NACIONAL DE ABASTECIMENTO DE AGUA E SANEAMENTO SERVICO DISTRITAL DE PLANEAMENTO E INFRA-ESTRUTURAS DE BARUE Mz Mill 0.12 RURAL PRONASAR PROGRAMA NACIONAL DE ABASTECIMENTO DE AGUA E SANEAMENTO SERVICO DISTRITAL DE PLANEAMENTO E INFRA-ESTRUTURAS DE MABALANE Mz Mill 0.24 RURAL PRONASAR PROGRAMA NACIONAL DE ABASTECIMENTO DE AGUA E SANEAMENTO SERVICO DISTRITAL DE PLANEAMENTO E INFRA-ESTRUTURAS DE MANDLAKAZE Mz Mill 0.13 RURAL PRONASAR PROJECTO E CONSTRUCAO DA BARRAGEM DE MAPAI ADMINISTRACAO REGIONAL DAS AGUAS DO SUL Mz Mill 1.24 ABERTURA DO FURO DE AGUA DIRECCAO PROVINCIAL DA EDUCACAO E DESENVOLVIMENTO HUMANO DE MANICA Mz Mill 0.45 DIVERSOS PROGRAMAS DE ABASTECIMIEN TO DE AGUA DIVERSOS Mz Mill 59.28 TOTAL Desenvolvimento e Manutenção de Infraestrutura Mz Mill 1,349.97 66 K. Marke�ng e promoção Program Origem Unidade 2,018.00 DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE MAPUTO FEIRAS AGRARIAS Mz Mill 4.71 PROVINCIA MADE IN MOZAMBIQUE DIRECCAO PROVINCIAL DA INDUSTRIA E COMERCIO DE NAMPULA Mz Mill 2.90 K. Comercialização e promoção MONITORAR O PROCESSO DA COMERCIALIZACAO AGRICOLA DIRECCAO PROVINCIAL DA INDUSTRIA E COMERCIO DE TETE Mz Mill 0.55 PLANO INTEGRADO DE COMERCIALIZACAO AGRICOLA MINISTERIO DA INDUSTRIA E COMERCIO Mz Mill 4.68 PROJECTO DE EFECTIVACAO DE FEIRAS E INSUMOS AGRICOLAS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE MANICA Mz Mill 2.25 DIRECCAO PROVINCIAL DA INDUSTRIA E COMERCIO DE SOFALA, DIRECCAO PROMOCAO DE FEIRAS Mz Mill 1.58 PROVINCIAL DA INDUSTRIA E COMERCIO DA ZAMBEZIA REALIZACAO DE FEIRAS DE PRODUTOS AGRICOLAS A NIVEL DELEGAÇÃO PROVINCIAL DO FUNDO DE DESENVOLVIMENTOOCAO AGRARIO DA Mz Mill 0.44 DOS DISTRITOS ZAMBEZIA APOIO AO PLANO ESTRATEGICO DA BOLSA DE MERCADORIAS BOLSA DE MERCADORIAS DE MOCAMBIQUE Mz Mill 0.87 DIVULGACAO DE INFORMACAO SOBRE MERCADOS DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE TETE Mz Mill 0.70 AGROPECUARIOS DA PROVINCIA REALIZACAO DA FEIRA PROVINCIAL E PARTICIPACAO NA DIRECCAO PROVINCIAL DA INDUSTRIA E COMERCIO DE NIASSA Mz Mill 0.67 FACIM REALIZAR FEIRA PROVINCIAL E FACIM DIRECCAO PROVINCIAL DA INDUSTRIA E COMERCIO DE TETE Mz Mill 4.74 INSTALACAO DA BOLSA DE MERCADORIAS BOLSA DE MERCADORIAS DE MOCAMBIQUE Mz Mill 94.06 TOTAL Marke�ng and Promo�on Mz Mill 118.15 L. Custo de ações públicas L. Organismo público Program Origem Unidade 2,018.00 CONSTRUCAO DE SILOS ASSEMBLEIA DA REPUBLICA Mz Mill 10.61 TOTAL Organismo público Mz Mill 10.61 M. Diversos M. Diversos Program Origem Unidade 2,018.00 REALIZAR MONITORIAS DA CAMPANHA AGRICOLA 2017/2018 DIRECCAO PROVINCIAL DA AGRICULTURA E SEGURANÇA ALIMENTAR DE NIASSA Mz Mill 0.43 Total Miscelllaneous Mz Mill - Figure 37: Budget CSE APOYOS ORIGEM Unidade 2018 PROGRAMAS DIVERSOS DE SUBSIDIO SOCIAL DIRECTO DIVERSOS MZ Mill 2,092.1 PROGRAMAS DE MERENDA ESCOLAR MINISTERIO DA EDUCACAO E DESENVOLVIMENTO HUMANO MZ Mill 0.0 PROGRAMAS DIVERSOS DE ACCION SOCAL DIVERSOS MZ Mill 81.5 TOTAL MZ Mill 2,173.7 67 Agric ultural sector PQG (Strategic Ini�al strategic targets Performance strategic objec �ve s objec �ve s/re sults for the ag Indicator PQG targets Strategic indicator (c umula�ve by the end (PNISA 201 3 -201 7 ): 68 sector: 2015-2019) of period) Impact le ve l Es�mate d actual (by the end of 201 7 ) Annex E 1. Average agriculture growth rate for the Average growth rate of period from 2013 to 2016 was 3.1% per year. 7% per year for the Signi ficant and consistent shor�alls in next 10 years (PNISA). achieving the ambi �ous target. 2. Major reasons include signi ficant underfunding of PNISA (public and Growth rate of at least Households development partners) coupled with PNISA's 6% from 2015 to 2025 living in Annual agricultural (MALABO). limited scope in mobilizing funds, promo�ng absolute sector growth rate and achieving an expanded private sector poverty (%) role. Average growth rate of 7% per year for the next 10 years (PNISA). Growth rate of at least 6% from 2015 to 2025 Enhanced food security (MALABO). Improving the living and nutri �on, increased condi �ons of the income and profitability Mozambican people, Modest reduc �on in poverty (54.7% in 2009 to of agricultural Reduce poverty level increasing employment, Households 49.2% in 2015) re flects a larger reduc �on in producers, and the Reduc �on rate of by at least 50% at produc �vity and with adequate urban poverty with modest decrease in rural compe ��veness, crea �ng 75 rapid, compe ��ve and poverty headcount na �onal poverty line, consump�on sustainable increases in ra �o poverty (9% versus 3%), coupled with wealth and genera �ng a from the year 2015 to (%) market-oriented rela �vely low agricultural sector growth rate development the year 2025 agricultural produc �on trends. (2015-2019) and PNISA 1 (2013 - 2017) Households Bring down was �ng to Prevalence of with chronic 5% or less by the year Achieved: 8% in 2009 (IOF), 11.3% in 2013 16 was �ng (under five malnutri �on 2025 (MALABO and not (SETSAN) and 4.9% in 2015 (IOF) children) (%) speci fied by PNISA). Reduce from 44% in Strategic objec�ves and targets for the agricultural sector: PQG Households 2008 to 30% in 2015 Very unlikely to be met based on modest Prevalence of with adequate and 20% in 2020. increase from 45.7% in 2009 (IOF) to 47.9% in 75 stun�ng (% of under- consump�on Targets for 2013 (SETSAN) and modest decrease to 43.6% five children) (%) intermediate years in 2015 (IOF) were not de fined Incidence of chronic malnutri �on in 35 children under 5 years old (%)