ENHANCING BAHIA’S AGRICULTURE SUPPORT: POLICIES FOR A COMPETITIVE, GREEN, AND INCLUSIVE AGRIFOOD SECTOR Marie Paviot, Hector Peña, Mauro del Grossi, Elena Mora López, María Florencia Tejeda, Victoria Traverso, Beatriz Garcia, Luisa Leite 2025 © 2025 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 with external contributions. 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. Although the World Bank makes reasonable efforts to ensure all the information presented in this document is correct, its accuracy and integrity cannot be guaranteed. 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Paviot, M., Peña, H., del Grossi, M., Mora López, E., Tejeda, M. F., Traverso, V., Garcia Ferreira, B. M., Leite, L. World Bank: Washington, DC. Any 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. ENHANCING BAHIA’S AGRICULTURE SUPPORT: POLICIES FOR A COMPETITIVE, GREEN, AND INCLUSIVE AGRIFOOD SECTOR Marie Paviot, Hector Peña, Mauro del Grossi, Elena Mora López, María Florencia Tejeda, Victoria Traverso, Beatriz Garcia, Luisa Leite 2025 CONTENTS ACKNOWLEDGEMENTS 11 ACRONYMS 12 1. INTRODUCTION 14 2. ECONOMIC PERFORMANCE OF THE AGRICULTURAL SECTOR (BRAZIL AND BAHIA) 16 2.1 Gross Domestic Product Brazil 16 2.2 Value Added and Contribution to GDP by Economic Sector 17 2.3 Contribution to GDP by State 19 2.4 External trade 19 2.5 National Consumer Price Index 26 2.6 Bahia 26 2.6.1 State Gross Domestic Product 26 2.6.2 Value Added and Contribution to GDP by Economic Sector 27 3. EVALUATION OF SUPPORT FOR AGRICULTURE IN BAHIA (2017-2021) 30 3.1 Methodology 30 3.2 Producer Support Estimates (PSE) 35 3.2.1 Level of Support 35 3.2.2 Composition and Structure of the Producer Support Estimate (PSE) by Support Category 37 3.2.3 Analysis of Producer Support by Product 40 3.3 Consumer Support Estimates (CSE) 41 3.3.1 Structure of the Consumer Support Estimate (CSE) 42 3.3.2 Estimated Consumer Support by Product 42 3.4 General Service Support Estimates (GSSE) 43 3.5 Total Agricultural Support Estimates (TSE) 46 3.6 Sources of Funding for Support in Bahia 49 3.7 Environmental Impact of Support to the Agricultural Sector in Bahia 50 4. SUMMARY AND RECOMMENDATIONS 52 REFERENCES 58 ANNEX 1. SUMMARY OF THE ESTIMATE OF SUPPORT FOR THE AGRICULTURAL SECTOR IN BAHIA 2017-2021 59 ANNEX 2. BUDGET EXERCISED BY THE STATE OF BAHIA PROGRAM (GENERAL SERVICES) 61 ANNEX 3. BUDGET EXERCISED BY BAHIA STATE PROGRAM (OTHER DIRECT SUPPORT) 63 6 FIGURES FIGURE 1 17 ANNUAL CHANGE IN GROSS DOMESTIC PRODUCT (GDP) FIGURE 2 18 ANNUAL VARIATION IN VALUE ADDED BY ECONOMIC SECTOR (2011-2020) FIGURE 3 18 COMPOSITION OF BRAZIL’S GROSS DOMESTIC PRODUCT: 2011 VS 2021 FIGURE 4 19 STATE SHARE OF TOTAL GDP: 2011 VS 2020 FIGURE 5 20 BRAZIL’S FOREIGN TRADE (MILLION USD) FIGURE 6 21 BRAZIL EXPORTS BY ECONOMIC ACTIVITY (MUSD) FIGURE 7 22 EXPORTS OF MAIN PRODUCTS (SHARE OF VALUE OF TOTAL EXPORTS) FIGURE 8 23 AGRICULTURAL SECTOR EXPORTS, 2022 - 100%= $74.787 MILLION FIGURE 9 24 TOTAL EXPORTS BY COUNTRY OF DESTINATION - (100% = $334.136 MILLION) FIGURE 10S 26 ANNUAL VARIATION OF THE NATIONAL CONSUMER PRICE INDEX (INPC) - 2017 TO MAY 2023 FIGURE 11 27 ANNUAL VARIATION OF GDP FIGURE 12 28 ANNUAL VARIATION IN VALUE ADDED BY ECONOMIC SECTOR IN BAHIA: 2011 – 2020 Figures 7 FIGURE 13 28 COMPOSITION OF THE GROSS DOMESTIC PRODUCT OF BAHIA: 2011 VS 2021 FIGURE 14 29 BAHIA: SECTORAL BREAKDOWN OF GHG EMISSIONS FIGURE 15 32 SCHEME OF TRANSFERS ASSOCIATED WITH THE IMPLEMENTATION OF AGRICULTURAL POLICIES FIGURE 16 36 BAHIA PRODUCER SUPPORT ESTIMATE AS A PROPORTION OF TOTAL INCOME (%PSE) FIGURE 17 36 BENCHMARKING %PSE - 2017-2021 FIGURE 18 40 %PSE BY PRODUCT BAHIA (AVERAGE 2017-2021) FIGURE 19 45 BENCHMARKING GSSE AS PROPORTION OF AGRICULTURAL GDP – AVERAGE 2017-2021 FIGURE 20 46 BENCHMARKING THE COMPOSITION OF THE GSSE FIGURE 21 47 BAHIA, COMPOSITION OF TSE FIGURE 22 48 TSE ABSOLUTE AND AS A % OF STATE AGRI GDP FIGURE 23 48 BENCHMARKING TSE AS SHARE OF AG GDP FIGURE 24 49 BENCHMARKING TSE BY SOURCES OF TRANSFERS 8 LIST OF TABLES TABLE 1. 25 EXPORTS BY STATE - (100% = $334.136 MILLION) TABLE 2 38 STRUCTURE AND COMPOSITION OF PSE. BAHIA - (AVERAGE 2017-2021) TABLE 3 39 STRUCTURE AND COMPOSITION OF PSE. BAHIA, SANTA CATARINA, SÃO PAULO AND OECD - (AVERAGE 2017-2021) TABLE 4 41 %PSE PER PRODUCT PER YEAR TABLE 5 43 %CSE BY PRODUCT IN BAHIA (2017-2021) TABLE 6 44 GENERAL SERVICES SUPPORT ESTIMATE IN BAHIA TABLE 7 57 AREAS OF REFORMS FOR A COMPETITIVE, GREEN, RESILIENT AND INCLUSIVE AGRICULTURE SECTOR IN BAHIA 9 LIST OF BOXES BOX 1 31 OECD INDICATORS OF SUPPORT FOR AGRICULTURE BOX 2 33 APPROACH TO TSE CALCULATION FOR BAHIA 10 ACKNOWLEDGEMENTS 11 ACKNOWLEDGEMENTS This report was prepared by a World Bank team led by Marie Paviot (Senior Agriculture Economist, World Bank), and including Elena Mora López (Agriculture Economist, World Bank), María Florencia Tejeda (Agriculture Economist, World Bank), Victoria Traverso (Agriculture Analyst, World Bank), Beatriz Garcia (Intern, World Bank), Hector Peña (Consultant), Mauro del Grossi (Consultant), Luisa Leite (Intern, World Bank). The team is grateful for the guidance and support received from Diego Arias (Practice Manager, World Bank), Eli Weiss (Program Leader, World Bank), Edward Bresnyan (Lead Agriculture Economist, World Bank), Sergiy Zorya (Lead Agriculture Economist, World Bank), Svetlana Edmeades (Lead Agriculture Economist, World Bank), Vanina Daphne Forget (Senior Agriculture Economist, World Bank) and Paolo de Salvo (Senior Sector Specialist for Rural Development, Inter-American Development Bank), Barbara Farinelli (Senior Agriculture Economist, World Bank), Eirivelthon Santos Lima (Senior Agriculture Economist, World Bank), Leonardo Bichara (Senior Agriculture Economist, World Bank). The team expresses its gratitude for logistical and administrative support from Kayo Barbosa (Team Assistant, World Bank). 12 ACRONYMS AAGR GHG Average Annual Growth Rate Greenhouse Gas ABC GRID Low Carbon Agriculture – Agricultura Green, Resilient and Inclusive Development de Baixo Carbono GSSE AgGDP General Services Support Estimate Agricultural Gross Domestic Product IBGE APP Brazilian Institute of Geography and Statistics Area of Permanent Preservation - Area - Instituto Brasileiro de Geografia e Estatística de Preservação Permanente LAC BNDES Latin America and Caribbean Brazilian National Development Bank – Banco LCA Nacional de Desenvolvimento Economico e Social Agricultural Credit Notes – Letras CAR de Crédito do Agronegocio Rural Environmental Cadaster – LPI Cadastro Ambiental Rural Logistics Performance Index CNPA MAPA National Agricultural Policy Council – Ministry of Agriculture and Livestock – Conselho Nacional de Política Agrícola Ministerio de Agricultura e Pecuaria CSE MPS Consumer Support Estimate Market Price Support EMBRAPA NDC Brazilian Agricultural Research Corporation - Nationally Determined Contribution Empresa Brasileira de Pesquisa Agropecuaria NPC GDP Nominal Protection Coefficient Gross Domestic Product 13 OECD PSE Organization for Economic Producer Support Estimate Cooperation and Development PSR PGPM Premium Subsidy Program Minimum Price Guarantee Policy R&D PNCPD Research and Development National Program for Conversion of Degraded RL Pastures to Sustainable Agrifood Productive Legal Reserve - Reserva Legal Systems - Programa Nacional de Conversão de Pastagens Degradadas em Sistemas de Produção SCT Agropecuários e Florestais Sustentáveis Single Commodity Transfer PPCDAm SICAR Plan for the Prevention and Control of National Electronic System for Rural Deforestation in the Legal Amazon Environmental Cadaster – Sistema Nacional de Cadastro Ambiental Rural PPP Purchasing Power Parity SNCR National Rural Credit System – Sistema PROAGRO Nacional de Crédito Rural Agricultural Activity Guarantee Program TFP PRONAF Total Factor Productivity National Program to Strengthen Family Farming – Programa Nacional de TSE Fortalecimento da Agricultura Familiar Total Support Estimate 14 1. INTRODUCTION 1. There are various efforts to conduct comprehensive assessments of agricultural policies in countries around the world. With the use of various methodologies, the work of international bodies such as the Food and Agriculture Organization of the United Nations (FAO), the World Trade Organization (WTO), the International Food and Policy Research Institute (IFPRI), and the Organization for Economic Cooperation and Development (OECD) have carried out several efforts towards this goal. 2. In the case of the OECD, its methodology (designed in the 1970s and first applied in the 1980s) has been adapted and consolidated as an effective tool for policy monitoring and evaluation. In practical terms, it has frequently been used as a reference for establishing a dialogue at the national and international levels. Its standard character allows comparisons between countries, economies or over time; highlighting the impact of policies on the gross income of both consumers and producers. 3. Importantly, the OECD methodology estimates the value of monetary transfers made by taxpayers and consumers to agricultural producers. In its definition, the transfers generated as a result of the implementation of agricultural policies are considered. Based on this, it is possible to observe, as part of its indicators, the importance of these transfers in the total gross income of producers. 4. The methodology considers four basic indicators to determine the amount of transfers to the agricultural sector and to the consumer of agricultural products: Introduction 15  Total Support Estimates (TSE). Quantifies, in monetary terms, the impact of all policies and the sector as a whole.  Producer Support Estimates (PSE): Quantifies the total transfers to the producer resulting from the implementation of agricultural policies aimed at a specific product or group of products.  Producer Support Estimates as a percentage of gross income (PSE%): Estimates the impact of estimated transfers as a proportion of the gross income of the producer under analysis.  Consumer Support Estimates (CSE): Quantifies the impact of agricultural policies on domestic consumers or on a particular product. 5. One of the objectives of this analysis is to quantify the impact of the agricultural policies of the state government of Bahia on producers, consumers, and the sector as a whole based on the transfers that these policies generate, thus, in this analysis the result obtained will only reflect the transfers derived from the implementation of agricultural policies of the government of the state of Bahia. In this sense, the transfers derived from the implementation of national policies are not considered in this exercise and in any case both could be considered as complementary and measure their total impact on the income of the State producer. During the analysis, the amount of these transfers is estimated, as well as their importance within the producer’s gross 1 income, which facilitates comparisons over time and with other economies. 6. This exercise shows results obtained from the estimation of the transfers generated to the agricultural sector and its consumers, as a result of the implementation of agricultural policies of the government of the state of Bahia. The analysis considers the period 2017-2021, which is relevant considering the various events that affected the sector during that period, such as the presence of the global pandemic and a food price crisis. Based on the results obtained, recommendations for repurposing public policies and programs to foster a competitive, green and resilient growth of the sector have been formulated in the final section. 1 The OECD annually estimates the transfers derived from the implementation of national government policies, considering Brazil as a non-member country. Its results are published on the Organization’s website. 16 2. ECONOMIC PERFORMANCE OF THE AGRICULTURAL SECTOR (BRAZIL AND BAHIA) 2.1 Gross Domestic Product Brazil 7. The pace of growth of the country’s economy has slowed over the past ten years. According to data from the Brazilian Institute of Geography and Statistics (IBGE), in 2020 the Gross Domestic Product (GDP) was recorded at 7.6 trillion reais, which represented an annual growth of 3.0 percent over the previous year which meant a decrease of 9.6 p.p. compared to the annual growth of 12.6 percent recorded in 2011 when GDP stood at 3,885,847.00 million reais. For that period, the Average Annual Growth Rate (AAGR) of GDP stood at 5.7 percent. 8. It is important to note that, during 2020, the pandemic and the confinement and social distancing measures to contain the spread of the virus significantly affected the economic activity, resulting in challenges for which the country implemented a series of measures such as direct cash transfers, support for small and medium-sized enterprises, postponement of the payment of certain taxes, among others. Economic Performance of the Agricultural Sector (Brazil and Bahia) 17 FIGURE 1. Annual change in Gross Domestic Product (GDP) (Source: Author based on IBGE) 12.6% 10.7% 10.0% 8.4% 6.4% AAGR 4.6% 5.0% 5.5% 5.7% 3.8% 3.0% 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2.2 Value Added and Contribution to GDP by Economic Sector 9. Despite the decrease in GDP growth in recent years, the value added of Brazil agricultural production has had the greatest dynamism among sectors. In 2020, the annual variation in Agricultural Value Added was recorded at 39.9 percent, which implied an increase of 21.1 p.p. compared to 2011. For the 2011-2020 period, the agricultural sector had an average annual growth rate of 8.6 percent. 10. During 2020, a year in which there was low growth of the economy in general due to the effects of COVID-19, the agricultural sector showed resilience being an important engine for development, providing food security with record productions in crops such as corn and soybeans and recorded solid exports. According to data from the Ministry of Trade (Brazil), agricultural exports grew by 4.9 percent in 2020 compared to those observed in 2019, while exports corresponding to the processing and extractive industries decreased by 9.7 percent and 3.0 percent, respectively. 18 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector FIGURE 2. Annual Variation in Value Added by Economic Sector (2011-2020) (Source IBGE) 45.0% 39.9% 40.0% 35.0% 30.0% 25.0% 18.8% 20.0% 15.0% 10.0% 5.0% 0.0% -5.0% 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Agricultural Industry Services Administration Taxes 11. In addition, the agricultural sector has increased its participation in the total economy. In 2020, the agricultural sector contributed 5.7 percent of the Total GDP, which implied an increase in the sector’s share of 1.6 p.p. after ten years, only behind the contribution of the service sector, which increased by 2.6 p.p. for the same period. Economic Performance of the Agricultural Sector (Brazil and Bahia) 19 FIGURE 3. Composition of Brazil’s Gross Domestic Product: 2011 vs 2021 (Source IBGE) Composition of Brazil’s GDP: 2011 Composition of Brazil’s GDP: 2020 Agricultural 4.1% Administration 13.8% Agricultural 5.7% Administration 15.1% Industry 23.3% Taxes 15.0% Industry 19.5% Taxes 13.3% Services 43.8% Services 46.4% 2.3 Contribution to GDP by State FIGURE 4. State Share of Total GDP: 2011 vs 2020 (Source IBGE) Share of the State of Bahia Share of the State of Bahia in the National GDP: 2011 in the National GDP: 2020 Bahia 3.8% Bahia 4.0% Others 96.3% Others 96.0% 20 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector 12. During 2020, the State of Bahia contributed 4.0 percent of the country’s GDP, 0.2, p.p. more than 2011, being the seventh state with the highest contribution to the economy. 2.4 External trade 13. Brazil’s trade balance is historically in surplus, however, in recent years imports have recorded a higher rate of growth than exports. Between 2017 and 2022, exports registered a AAGR of 9.2 percent, while the average growth of imports was 11.4 percent. In 2022, the trade balance stood at 61.525 million dollars, the result of a total amount of 334.136 million dollars of exports and 272.611 million dollars of imports. FIGURE 5. Brazil’s foreign trade (Million USD) (Source: Ministry of Development, Industry, Trade and Services / Ministry of Trade (Brazil). https://www.gov.br/produtividade-e-commerce-exterior/pt-br/assuntos/commerce-exterior/estatisticas) 400,000 300,000 200,000 100,000 0 2017 2018 2019 2020 2021 2022 Exports Imports 14. By the end of 2022, the main export economic activity was the transformation industry, with a participation of 54.3 percent over the total exports, followed by the extractive industry with a participation of 22.8 percent and the agricultural activity with 22.4 percent. It should be noted that the processing Economic Performance of the Agricultural Sector (Brazil and Bahia) 21 industry, as the main export activity, is strongly driven by the export of agri-food, which accounts for almost a third of this sector. FIGURE 6 Brazil exports by economic activity (MUSD) (Source: Ministry of Development, Industry, Trade and Services / Ministry of Trade (Brazil). https://www.gov.br/produtividade-e-commerce-exterior/pt-br/assuntos/commerce-exterior/estatisticas) Agriculture 22.4% Extractive Industry 22.8% Agrifood 31% Processing Industry 54.3% Others 69% Others 0.5% 15. The main export products, according to 2022 figures, were soybeans, crude oil, and iron ore, with shares of total exports of 13.9 percent, 12.7 percent, and 8.7 percent, respectively. Between 2017 and 2022, these products recorded high average annual growth rates of 12.6 percent, 20.7 percent, and 8.5 percent, respectively. In addition, 10 of the 22 main products exported come from the processing industry, 7 of which are agri-food. 22 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector FIGURE 7. Exports of main products (Share of value of total exports) (Source: Ministry of Development, Industry, Trade and Services / Ministry of Trade (Brazil). https://www.gov.br/produtividade-e-commerce-exterior/pt-br/assuntos/commerce-exterior/estatisticas) 2017 Soy 12% Cellulose 3% Iron ores 9% Coffee 2% Crude petroleum oils 8% Fuel oils 1% Sugar 5% Bird meat 3% Passenger motor vehicles 3% Unground corn 2% Soy flour 3% Semi-products Beef 2% 2022 Soy 13.9% Sugars 3.3% Crude petroleum oils 12.7% Cellulose 2.5% Iron ore 8.7% Beef 3.5% Fuel oils 3.9% Coffee 2.5% Unground corn 3.6% Semi-products: Soya flour 3.3% Bird meat 2.7% 16. In 2022, exports from the agricultural sector grew by 35.6 percent compared to the previous year and at an average annual rate of 14.2 percent over the last five years. In addition to soy, other products such as corn (16.3 percent), coffee (11.4 percent), and cotton (4.9 percent) stand out. Economic Performance of the Agricultural Sector (Brazil and Bahia) 23 FIGURE 8. Agricultural sector exports, 2022 - 100%= $74.787 million (Source: Ministry of Development, Industry, Trade and Services / Ministry of Trade (Brazil). https://www.gov.br/produtividade-e-commerce-exterior/pt-br/assuntos/commerce-exterior/estatisticas) Soy 46.559 | 3% Wheat 12.184 | 1% Coffee 8.514 | 1% Cotton 3.676 | 0% Fruits and Non-oilseed nuts 946 | 62% Rice 312 | 20% Wood 194 | 13% Others 2.401 | 0% 17. The main destinations of Brazil’s exports are China with 26.8 percent of the total; United States with 11.2 percent, and Argentina with 4.6 percent. Despite China concentrating about a quarter of exports, Brazil has a good diversification of trading partners, according to the Herfindahl and Hirschman Index (IHH) of 947. 24 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector FIGURE 9. Total exports by country of destination - (100% = $334.136 million) (Source: Ministry of Development, Industry, Trade and Services / Ministry of Trade (Brazil). https://www.gov.br/produtividade-e-commerce-exterior/pt-br/assuntos/commerce-exterior/estatisticas) China 26.8% Singapure 2.5% United States 11.2% Mexico 2.1% Argentina 4.6% Japan 2.0% Netherlands 3.6% India 1.9% Spain 2.9% Others 39.7% Chile 2.7% 18. The five main exporting states accounted for 56.6 percent of the total export value in 2022. São Paulo generated the highest value for this item with 20.8 percent, followed by Rio de Janeiro with 13.6 percent. The latter state also showed considerable growth in its total share of exports with an average annual rate of 18.3 percent. 25 TABLE 1. Exports by State - (100% = $334.136 million) # State 2022 % in 2022 AAGR 2022/m 1 SAO PAULO 69,631 20.80% 6.60% 2 RIO DE JANEIRO 45,514 13.60% 18.30% 3 MINAS GERAIS 40,194 12.00% 9.70% 4 MATO GROSSO 32,508 9.70% 17.20% 5 RIO GRANDE DO SUL 22,565 6.80% 4.90% 6 PARANA 22,133 6.60% 4.30% 7 PARA 21,515 6.40% 8.20% 8 GOIAS 14,148 4.20% 15.40% 9 BAHIA 13,923 4.20% 11.60% 10 SANTA CATARINA 11,966 3.60% 7.10% OTHERS 40,040 12.0% 5.2% Total 334.136 100.00% 9.20% (Source: Ministry of Development, Industry, Trade and Services / Ministry of Foreign Trade (Brazil). https://www.gov.br/produtividade-e-commerce-exterior/pt-br/assuntos/commerce-exterior/estatisticas) 26 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector 2.5 National Consumer Price Index 19. The pace of price growth has slowed for most of 2022 and so far in 2023. In May 2023, the National Consumer Price Index (INPC) was recorded at 6,893.3 points, for that date, the annual variation of the index was 3.7 percent, which represents a slower growth rate compared to the 11.9 percent annual variation of the same month of 2022. FIGURE 10. Annual variation of the National Consumer Price Index (INPC) - 2017 to May 2023 (Source: IBGE) 14.00 2017 2018 2019 2020 2021 2022 2023 12.00 10.00 8.00 6.00 4.00 2.00 0.00 Jan Mar May Jul Sep Jan Mar May Jul Sep Jan Mar May Jul Sep Jan Mar May Jul Sep Jan Mar May Jul Sep Jan Mar May Jul Sep Jan Mar May Nov Nov Nov Nov Nov Nov 2.6 Bahia 2.6.1 State Gross Domestic Product 20. The growth rate of the State’s economy showed a decrease during the period of analysis. The annual variation of Bahia’s GDP went from 7.9 percent in 2011 to 4.1 percent in 2020, meaning 3.8 p.p. less. The Average Annual Growth Rate (AAGR) of GDP stood at 6.2 percent for the period under analysis. Economic Performance of the Agricultural Sector (Brazil and Bahia) 27 FIGURE 11. Annual variation of GDP (Source IBGE) 7.9% 12.2% 9.6% 9.3% 9.4% AAGR 6.5% 5.6% 6.2% 3.9% 4.1% 2.4% 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2.6.2 Value Added and Contribution to GDP by Economic Sector 21. The annual growth of the Value Added of the agricultural sector in Bahia has had the greatest dynamism among the sectors. From 2011 to 2020, the annual variation in Agricultural Value Added went from 11.0 percent to 60.1 percent, that is, an increase of 49.1 p.p. The CAGR recorded in this period for the sector was 8.9 percent. 22. This remarkable growth in the agricultural sector in 2020, a year highlighted by the presence of COVID-19 in Brazil and the rest of the world, was influenced by local, national, and international factors. According to data from the Brazilian Ministry of Trade, grew in Bahia by 10.1 percent between 2019 and 2020, while the processing industry, which is largely explained by agri-foods, grew by 11.0 percent. This highlights the importance of the sector in the State as an economic engine in the face of various macroeconomic phenomena. 28 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector FIGURE 12. Annual Variation in Value Added by Economic Sector in Bahia: 2011 – 2020 (Source: IBGE) 70.0% 60.1% 60.0% 50.0% 40.0% 30.0% 20.0% 11.0% 10.0% 0.0% -10.0% -7.4% -20.0% 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Agricultural Industry Services Administration Taxes 23. The agricultural sector has increased its participation in the economy of Bahia, going from 6.9 percent in 2011 to 9.2 percent in 2020, while the services sector had a decrease in its economic contribution from 40.3 percent to 40.2 percent in those years. FIGURE 13. Composition of the Gross Domestic Product of Bahia: 2011 vs 2021 (Source IBGE) Composition of Bahia’s GDP: Composition of Bahia’s GDP: 2011 2020 Agricultural 6.9% Agricultural 9.2% Industry 23.8% Industry 19.5% Services 40.3% Services 40.2% Administration 16.7% Administration 19.0% Taxes 12.3% Taxes 12.1% Economic Performance of the Agricultural Sector (Brazil and Bahia) 29 24. The State of Bahia is the 10th State when it comes to GHG emissions within the country. The Agriculture sector and Land Use Change represent the bulk of the State’s GHG emissions with 46 and 12 percent respectively. Within agriculture, it is worth noting that 70 percent of GHG emissions come from enteric fermentation, 26 percent from soils. Emissions coming from the agriculture sector increased by 19 percent between 2002 and 2022, while emissions from Land Use Change reduces by 78 percent during the same period. FIGURE 14. Bahia: Sectoral breakdown of GHG emissions (Source: SEEG) Agriculture 46% Land Use Change 12% Energy 32% Waste 8% Industry 2% 30 3. EVALUATION OF SUPPORT FOR AGRICULTURE IN BAHIA (2017-2021) 3.1 Methodology 25. This section provides a quantitative assessment of monetary transfers to agriculture in Santa Catarina, derived from the implementation of agricultural policies, during the period 2017-2021. For the estimation of these transfers, the OECD methodology for estimating agricultural support has been taken as a base reference, including the Producer Support Estimate (PSE), the Consumer Support Estimate (CSE), the Total Support Estimate (TSE), and the General Service Support Estimate (GSSE), see Box 1. It is important to note that for the estimates, the transfers derived solely from the implementation of state government policies have been considered, which allows quantifying them and estimating their impact on the producer/ consumer or on the state sector. In this sense, national policies are not considered since this would correspond to an analysis of transfers associated with national policies, which is not part of the objectives of this analysis. 31 BOX 1 OECD INDICATORS OF SUPPORT FOR AGRICULTURE • Indicators of support for producers the farm level, arising from the implementation of policy measures by the state that support agriculture, Throughout this document, it will be emphasized that regardless of their nature, objectives, or impacts on the estimation of the various supports will consider the consumption of agricultural products. only the implementation of policy measures by the State and their impact on the state sector or state CSE in percentage (CSE%): CSE as a percentage of producer/consumer. consumption expenditure (measured on an operating basis) net of transfers from taxpayers to consumers. Producer Support Estimate (PSE): The annual monetary value of gross consumer and taxpayer • Indicators of support to general services for transfers to agricultural producers, measured at agriculture the farm level and derived from the implementation of state government agricultural policy measures General Service Support Estimate (GSSE): The that support agriculture, regardless of their nature, annual monetary value of gross transfers to general objectives, or impacts on agricultural production services provided to agricultural producers collectively or incomes. (such as research, development, training, inspection, marketing, and promotion), derived from measures Percentage of PSE (%PSE): PSE as a percentage of of the implementation of policies that support gross agricultural income (including transfers). agriculture by the state, regardless of their nature, objectives, and impacts on agricultural production, Single Commodity Transfers (SCT) represent the income, or consumption. The GSSE does not include total annual monetary value of transfers from any transfers to individual producers. consumers and taxpayers to agricultural producers. These transfers are measured at the farm gate Percentage GSSE (% GSSE): GSSE as a percentage level and are a result of policies specifically tied to of the Total Support Estimate (TSE). the production of a single commodity — conditional transfers. In order to receive the payment, producers • Indicators of Total support to the sector are required to produce the designated commodity. This category also encompasses broader policies Total Support Estimate (TSE): The annual where transfers are specified on a per-commodity monetary value of all gross transfers from taxpayers basis. It can also be expressed as a percentage of and consumers resulting from the implementation Gross Agricultural Income for the specific product. of agricultural support policy measures by the state, net of associated budget revenues, regardless of their • Indicators of support to consumers objectives and impacts on agricultural production and incomes, or consumption of agricultural products. Consumer Support Estimate (CSE): The annual monetary value of gross transfers from (to) Percentage TSE (TSE%): TSE as a consumers of agricultural products, measured at percentage of GDP. 32 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector 26. The OECD methodology makes it possible to identify the beneficiaries of transfers and also identifies (and quantifies) the sources of financing for such transfers. The following figure outlines the relationship between beneficiaries and sources of financing for the transfers generated. In relation to recipients, there are fundamentally three types of transfers: to individual producers, to the sector, and to consumers. First, and to the extent that a state policy measure benefits a product or group of products, these measures are classified within the PSE and their source of financing can be consumers (through higher prices) or taxpayers (through tax payments with which the support programs are financed). Secondly, when a measure is carried out and benefits the sector as a whole, it is classified as GSSE. Virtually all of these measures are funded by taxpayers. Finally, policy measures that promote or hinder the consumption of agricultural products are classified within the CSE. The sources of financing for these measures are through taxpayers (public programs that subsidize the consumption of products) or through consumers themselves (through intervention measures that affect the market price). FIGURE 15. Scheme of Transfers Associated with the Implementation of Agricultural Policies Tot l Support Estim te Producer Support Support for Consumer Support Estim te Gener l Services Estim te M rket M rket Bud et r Bud et r Price Price Tr nsfers Tr nsfers Support Support Consumers T xp er Sources 27. The methodology applied in this study is consistent with that used in OECD reports that monitor and evaluate agricultural policies in the OECD and other countries. Box 2 provides basic information on how this methodology has been applied to the case of Bahia, Brazil. 33 BOX 2 APPROACH TO TSE CALCULATION FOR BAHIA The approach to estimating support for the sector generate an increase (or decrease) in the domestic in the state of Santa Catarina faithfully applies the price in relation to an international reference. principles of the OECD methodology. In this sense, the Additionally, other types of policies can be included estimate is limited to estimating the support derived within these measures, including the imposition from the implementation of State government of managed prices (maximum and minimum), policies in the agricultural sector. Likewise, the government purchases, etc., which generate a gap indicators will indicate the impact that, in the margin, between prices. the State support represents on the producer’s gross income, on GDP, etc. This allows a reasonable In some cases, differences between domestic and comparison with other economies. international prices are also explained by factors that are not strictly policy-related, for instance, It is worth mentioning that during the analysis, some deficiencies in physical infrastructure, inadequate support programs have been found that have a pari information, and weak market institutions or passum financing scheme, with a national and a exchange rate variations (considering that the state contribution. In those cases, only the State comparison is commonly made in a local single contribution has been considered, as for the case of currency). The OECD methodology indicates that, the school feeding program. if the gap detected is due to the presence of any of these factors, it is not considered for its calculations). Under this principle, it is clear that the support that a producer can receive in the State is complemented It is important to mention that the implementation by the support they receive from national policy of policies related to border measures (restriction/ measures (although the latter are not estimated in promotion of imports/exports) based on the this exercise). imposition of tariffs/quotas/subsidies is an exclusive 2 power of the national government. However, other • PSE calculation for Bahia measures that can generate a domestic price gap in relation to international references can be Broadly speaking, the PSE has two main components: implemented by the state government, including, for support via market prices and budget support. example: administered prices, and public purchases or production quotas. • Market price support (MPS) In the case of Bahia, and with the support of the local Market price support is based on measuring the consultant, there was no evidence that, during the difference between a country’s (or state’s) domestic period analyzed (2017-2021), the state government prices and international (property-level) reference implemented any policy that intervened in the prices. This price gap is the result of a variety of prices of the products analyzed and generated a policy measures that prevent domestic prices from gap in relation to the international reference price. aligning with international levels. These policies Accordingly, the MPS is calculated based on the include trade measures such as import tariffs, tariff following information: quotas, export subsidies, export taxes, quantitative restrictions on exports and other measures that 34 Analyzed products and representativeness: The local consultant provided data on FOB prices The products analyzed were cocoa, cotton and and transportation and processing costs from soybeans. These three products together represent information generated by Brazil’s National Land 47 percent of the total value of gross agricultural Transportation Agency (ANTT), adjusted for inflation 3 production in Bahia by 2021. The OECD methodology between 2018 and 2021. suggests analyzing a sample of products that together represent about 70 percent of the value of Price gap estimates: The “zero price gap” was used agricultural production (in this case state agricultural when negative gaps were obtained, as the estimated production), so a complementary analysis is negative price gaps reflect factors other than suggested to add new products to the “basket” of agricultural policies. products analyzed. • Budget Support Prices to the domestic producer: Corresponds to the average annual prices received by producers Budgetary support comes from information on public at the farm level in Bahia. This information has spending at the sectoral level executed by the State been provided by the local Consultant, based Government through any of its agencies or entities on information from the Superintendência de that executed programs to support the sector in Estudos Sociais e Econômicos da Bahia (SEI) and the period. The budget information was provided by the Secretaria de Agricultura, Pecuária, Irrigação, the Local Consultant, using Sefaz/Seagri/Casa Civil Abastecimento e Pesca do Estado da Bahia (SEAGRI); (Núcleo de Monitoramento e Avaliação das Políticas Públicas). External reference prices: Average annual export prices (FOB) were used for the products under analysis. These prices were adjusted at the farm level with the cost of transport to port and other processing costs, in order to make reasonable comparisons with domestic prices. The adjustment followed the comparability criterion (like to like) suggested by the OECD. Evaluation of support for Agriculture in Bahia (2017-2021) 35 3.2 Producer Support Estimates (PSE) 3.2.1 Level of Support 28. The Producer Support Percentage Estimate (%PSE) is one of the most important indicators used by the OECD to measure the impact on the farmer of transfers associated with the implementation of (state) policies, expressing this amount as a proportion of the gross agricultural income 2 of the state producer. Under this criterion, this indicator reasonably allows comparisons of the impact between products, countries or over time and the OECD considers it as the “most appropriate indicator to compare changes in the level of support to the farmer”. 29. The %PSE expresses the monetary value of state aid transfers to agricultural producers in the state as a percentage of that producer’s gross income. As it is unaffected by inflation, it allows for comparisons in the level of support both over time and across countries. This indicator provides information on consumer and taxpayer transfers (budget transfers) to farmers. 30. Figure 15 shows the estimate of %PSE of Bahia for the period 2017-2021. For the first year, the %PSE shows that 0.29 percent of the gross income of agricultural producers was generated by state support policies. By 2021, this level stands at 0.20 percent. The average %PSE for the period was 0.2 percent. All these levels denote a low (almost zero) average impact of state direct support policies on producers’ income. This situation also reflects that the products used for this analysis are mainly export products, and therefore exposed to international prices. Finally, and as will be shown below, there were no policies by the government of the state of Bahia that implied an interventionist measure in prices, since these are fundamentally governed by market conditions. 2 Calculated as the value of production plus transfers received. 36 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector FIGURE 16. Bahia Producer Support Estimate as a proportion of Total Income (%PSE) 0,29% 0,25% 0,20% 0,16% 0,16% 0,14% 2017 2018 2019 2020 2021 2017-2021 Average 31. The %PSE indicator allows for reasonable comparisons, in this case with other countries, including the OECD countries, and other states in Brazil. The average level of support to the producer in Bahia as a proportion of income in the analyzed period (0.2 percent) is comparatively lower than that observed in other economies such as Chile, Mexico, etc., although slightly higher than that of São Paulo and Santa Catarina. FIGURE 17. Benchmarking %PSE - 2017-2021 17,4% 9,8% 9,8% 4,8% 2,4% 2,8% 0,1% 0,1% 0,2% -25,5% Argentina Sta. Sao Paulo* Bahia* Brazil Chile LATAM Mexico USA OECD Catarina* Evaluation of support for Agriculture in Bahia (2017-2021) 37 3.2.2 Composition and Structure of the Producer Support Estimate (PSE) by Support Category 32. A fundamental part of the research on support to the sector should include not only the analysis of the level and impact, but also the composition of the sector. The relative importance of each of the categories of support considered by the OECD methodology reveals the way in which the supports are granted and from there, conclusions can be reached on the degree of efficiency (inefficiency) and progressiveness (regression) of the supports. In practical terms, this can help identify that not necessarily a high (or low) level of support implies that it is being done efficiently or equitably. 33. For example, aid can be granted through support via prices or subsidies to inputs. It can take the form of a payment per hectare or per animal, or compensation to the producer’s income; but its impact (measured from various angles) can differ. Also, by identifying the various categories of support, it is possible to determine in the first instance, the impact that the form of support can have on production, trade or income or other variables of great relevance such as the environment. 34. Support through market prices (MPS) is considered a highly distorting measure with a high social cost, since its implementation is necessarily linked to the production of the products to which it is directed, which implies a market distortion. On the other hand, the MPS imposes additional costs on domestic consumers, as it promotes an additional increase in the price for consumers, which represents an “implicit tax” on them and particularly on lower-income net consumers, who must allocate a greater part of their income to food spending, also making it highly regressive. It is worth noting that during the analyzed period, Bahia did not implement any price support measures. 35. Table 2 shows that, during the period of analysis, direct support to producers in Bahia was for more than 60 percent provided through payments based on inputs. The State Government carried out programs such as “Distribution of Inputs for family agriculture”, “Distribution of support equipment for productive 38 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector 3 inclusion” and “Support Programs for technical assistance and extension”. A smaller part of the total support (14 percent of the total) consisted of production-based support, which included resources managed through the PRODEAGRO fund and PROALBA (cotton) implemented by the State Government. The supports of these programs/funds are linked to production. 36. Finally, it is observed that an important portion (21.7 percent) of the direct support that the government of Bahia executed was implemented through programs that were placed in the category of “Support based on non-production criteria”, which have a positive impact on the environment and natural resources, such as the “Environmental Regularization of Rural Properties” program. Based on its characteristics, this program can be considered a “green” program. TABLE 2 Structure and Composition of PSE. Bahia - (average 2017-2021) Bahia Item Rs Mill % III.1 Producer Support Estimates (PSE) 59.7 100,0% Market Price Support 0.0 0.0% Production-based payments 8.6 14.3% Payments based on the use of inputs 38.2. 63.9% Supports based on non-current production A/ 0.0 0.0% AN/I. REQUIRED PRODUCTION : Supports based on non-current production A/ 0.0 0.0% AN/I. No production is required. Support based on non-production criteria 13.0 21.7% Others 0.0 0.0% 3 See the annex for details of the programmes Evaluation of support for Agriculture in Bahia (2017-2021) 39 37. In a comparative analysis of the structure with other states in Brazil and OECD countries (Table 3), two aspects are highlighted: the first is that unlike in the OECD, market price support is not used as a policy instrument to transfer resources to the sector. The second is that, in the OECD, most of the policy instruments that transfer resources to the sector (40.1 percent), are carried out through programs that are not conditional on production (decoupled) and thus, are less distorting, considered less harmful to the environment and result in support that is not subject to sanctions or trade compensation within the WTO’s foreign trade rules (green box). In general, the OECD observes the use of a more diverse range of categories and is mostly oriented towards decoupled support categories. Compared to other Sates in Brazil the share of support to producers that goes through decoupled payments in Bahia is quite high, though remains below OECD level. TABLE 3 Structure and Composition of PSE. Bahia, Santa Catarina, São Paulo and OECD - (average 2017-2021) São Paulo Santa Catarina Bahia OCDE Category % % % % III. Producer Support 100% 100% 100% 100% Estimate (PSE) Market Price Support 0.0% 0.0% 0.0% 17.1% Production-based payments 0.0% 0.0% 14.3% 0.3% Payments based on 96.6% 98.7% 63.9% 14.1% the use of inputs Supports based on non- current production A/AN/I. 0.0% 0.0% 0.0% 27.0% REQUIRED PRODUCTION Supports based on non- current production A/AN/I. 0.0% 0.0% 0.0% 40.1% No production in required Support based on non- 3.4% 1.3% 21.7% 1.1% production criteria Others 0.0% 0.0% 0.0% 0.3% 40 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector 3.2.3 Analysis of Producer Support by Product 38. The OECD methodology allows obtaining a disaggregated level for each product selected as the basis for the analysis. By definition, the methodology allows identifying the supports that are transferred to a type of product or group of products (PSE) and this estimate is presented in this section. Formally, the analysis of support by product is called “Individual commodity transfers”. For these purposes, we will call it “Product Producer Support Estimate (product name)”. The PSE per product can also be expressed both in absolute terms and as a percentage of the gross revenue of the product under analysis. For the latter case, a figure of 33 percent, for example, indicates that the value of the transfers derived from the implementation of state agricultural policies, which are specific to that commodity, is equivalent, on average, to one third of the gross agricultural income of the producers of that product in the particular state and for the year or period analyzed. 39. Figure 17 shows the PSE of Bahia in percentage (%PSE) for the three products included in the support estimation analysis, considering the average of the analyzed period. Throughout that period, soybeans presented the highest level of %PSE. FIGURE 18. %PSE by Product Bahia (average 2017-2021) Soy 0.35% Cocoa 0.34% Cotton 0.30% 0.27% 0.28% 0.29% 0.30% 0.31% 0.32% 0.33% 0.34% 0.35% 0.36% Evaluation of support for Agriculture in Bahia (2017-2021) 41 TABLE 4 %PSE per product per year Bahia 2017 2018 2019 2020 2021 Cotton 0.6% 0.4% 0.2% 0.2% 0.2% Cocoa 0.6% 0.4% 0.3% 0.2% 0.3% Soya 0.6% 0.4% 0.3% 0.2% 0.3% 40. Table 4 includes the monitoring of this indicator for each year and a secular reduction is observed from 2017 to 2021 for the three products. This indicates that the level of support towards 2021 was reduced when measured as a proportion of the producer’s gross income. The reason for this is that, towards 2021, production increased significantly and created at a higher rate than the level of support. 3.3 Consumer Support Estimates (CSE) 41. The Consumer Support Estimate (CSE) measures the cost (or benefit) to state consumers of implementing state sector support policies. A negative CSE indicates a negative cost to the consumer, which is equivalent to an implicit tax on the consumption of agricultural products. To the extent that a state agricultural policy raises the domestic price above the international reference prices (for example, the imposition of administered prices), the consumer is the one who must bear that cost and transfers them as a benefit to the producer. Conversely, an agricultural policy that generates a domestic price below the international reference price (for example, a maximum price) generates an “implicit subsidy” to the consumer financed by the producer. 42 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector 42. The OECD methodology considers, in addition to these supports, those that may result from consumption subsidy programs, and which are financed by taxpayers. In any case, both sources of financing are considered in the calculations to determine the net support to the consumer. 3.3.1 Structure of the Consumer Support Estimate (CSE) 43. Like the PSE, the CSE can be expressed in relative terms as a percentage of consumption expenditures (%CSE). The average percentage of CSE for Bahia was zero for the entire period. Since the state government did not observe measures to support the sector that would result in higher prices received by the producer (including measures such as price administration, production quotas, public purchases), the consumer was not affected. On the other hand, no information was obtained from state government programs for the consumption subsidy. Under these circumstances, the existence of programs of these characteristics would have made this indicator positive. 3.3.2 Estimated Consumer Support by Product 44. In the following table, the %CSE is observed at the level of each product and during the analyzed period. The %CSE for all analyzed products was null. It is important to note that this result shows that the State of Bahia (i) did not implement measures that intervenes in the level of market prices. Thus, the consumer has not transferred resources to the sector through the payment of a price higher than that prevailing in the reference markets; nor (ii) did implement program to support the consumption of the analyzed products. Evaluation of support for Agriculture in Bahia (2017-2021) 43 TABLE 5 %CSE by product in Bahia (2017-2021) (average Status Product 2017 2018 2019 2020 2021 2017-2021) Bahia Cocoa 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Bahia Cotton 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% Bahia Soya 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 3.4 General Service Support Estimates (GSSE) 45. In addition to transfers received by individual producers, government policies assist the agricultural sector by financing activities that provide general benefits to the sector as a whole (public goods), such as agricultural research and development, training and extension, inspection, information, sector promotion, etc. The generation of this type of public services creates positive externalities to the sector as a whole. The OECD methodology estimates this type of transfer to the sector through the General Services Support Estimate (GSSE), which considers the amount of public investment (from the state government) towards these activities. The GSSE is financed by taxpayers and its financing by the state government is key insofar as, due to its characteristics as a public good, the level provided by the market is lower than the socially optimal level. 46. During the period of 2017-2021 (Table 6), the GSSE for Bahia totaled an annual average of 132.6 RS Millions. More than half of these transfers (52 percent) were allocated to infrastructure and maintenance financing and almost 40 percent to Research and Development. The remaining was allocated to actions related to the promotion and marketing of the sector. 44 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector TABLE 6 General Services Support Estimate in Bahia (average Investment in 2017 2018 2019 2020 2021 2017-2021) General Services Rs Mill % Bahia 104.28 134.10 124.82 110.76 189.24 132.64 100% Agricultural 59.2 62.8 46.9 52.7 41.8. 52.7 40% knowledge Inspection and 0.0 0.0 0.0 0.0 0.0 0.0 0% monitoring Infrastructure development and 29.3 57.1 69.0 52,0 135.5 68.6 52% maintenance Marketing and 15.7 14.2 9.0 6.1 11.9 11.4 9% Promotion Cost of public 0.0 0.0 0.0 0.0 0.0 0.0 0% actions Miscellaneous 0.0 0.0 0.0 0.0 0.0 0.0 0% 47. It is worth mentioning that although the GSSE has represented a very important part of the total support (about 69 percent on average between 2017-2021), when the level of GSSE is analyzed as a proportion of the state’s agricultural GDP (0.6 percent), it is relatively lower than that presented in other States such as São Paulo (1.2 percent),and much lower than those observed in OECD countries (5.3 percent). Evaluation of support for Agriculture in Bahia (2017-2021) 45 FIGURE 19. Benchmarking GSSE as proportion of agricultural GDP – Average 2017-2021 5,3% 1,21% 0,57% 0,70% 0,51% Brazil Bahia Santa São OECD Catarina Paulo 48. Evidence shows that the level of GSSE is positively correlated with the degree of development of countries. In addition, this type of support is in the green box in the WTO, which means that it is not subject to any compensatory measures by trade counterparts. Investment in EASG is often associated with long-term agricultural growth and competitiveness. 49. Supporting innovation plays a vital role in helping to mitigate agricultural emissions. There is ample evidence that public investments in agricultural research and development also generate high rates of return (Alston, Pardey, & Rao, 2021). Agricultural research and development are a key driver of productivity growth, which can help reduce emissions by allowing more food to be produced with the same amount or fewer emissions-intensive inputs (e.g., land, fertilizers). Innovations such as improvements in agricultural management practices, new crop varieties and livestock breeds, and new digital technologies (e.g., precision agriculture) can reduce the intensity of production emissions while mitigating emissions from land-use change. 50. Figure 20 shows the distribution of public investment in general services for Bahia and other states, as well as the OECD. São Paulo and Bahia concentrate this investment in important areas such as Research, Inspection and Infrastructure. In the case of Santa Catarina, it shows a more diverse distribution of its investment in other categories, a case similar to the OECD. 46 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector FIGURE 20. Benchmarking the composition of the GSSE 6.3% 2.28% 3.7% 6% 8.6% 1.02% 3.52% 0.16% 1.4% 3% 12.8% 22.0% 12.5% 2% 8.8% 29% 18.5% 51.7% 30.4% 42.5% 93.02% 24% 12.5% 13.5% 59.5% 39.7% 36% 31.1% 24.5% BAHIA SANTA SÃO PAULO BRAZIL OECD LATAM CATARINA Agriculture innovation Infrastructure Development and Maintenance Inspection and control Marketing and promotion Cost of public actions Others 3.5 Total Agricultural Support Estimates (TSE) 51. The Total Support Estimates for Agriculture (TSE) estimate is the indicator that includes the sum of transfers to agricultural producers directed both individually (PSE) and collectively (GSSE), in addition to direct budget transfers to consumers arising from state agricultural policies. This indicator can be expressed in absolute terms or as a percentage of agricultural GDP. In the latter case, %TSE provides an indication of the cost that support to 4 the agricultural sector entails for the state economy and is mostly used to make comparisons between economies or in the most reasonable time. 4 Sometimes it is also represented as a proportion of the State’s Gross Domestic Product. In any case, the use of one or another variable corresponds to a criterion and depends on the objectives of the researcher. Evaluation of support for Agriculture in Bahia (2017-2021) 47 52. Figure 21 shows the composition of the TSE in Bahia for the period 2017- 2021. It is shown that of the total estimated average annual amount for that period (192.4 Rs Mill), the GSSE constituted 69 percent, followed by the PSE (31 percent). There was no budget support for consumers. FIGURE 21. Bahia, Composition of TSE Total Support Estimate R$ 192.4 million USD 38.3 million Bahia General Services Producer Support Support Estimate, Estimate 68.9% 31.0% 53. When this level of total support (TSE) is measured as a percentage of state agricultural GDP, it is observed that the average TSE for the period was 0.9 percent. The evolution of this indicator in the period under analysis 5 shows a maximum in 2017 and a recovery trend towards 2021. 5 The recovery towards 2021 is mainly explained by the increase in the budget of support to General Services and particularly the program “Implantação de Projeto de Desenvolvimento Rural Sustentavel - Bahia Produtiva”, which finances productive infrastructure 48 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector FIGURE 22. TSE absolute and as a % of State Agri GDP Bahia 1.1% 1.0% 1.0% 0.91% 0.6% 266.2 166.4 200.1 167.1 162.0 173.9 2017 2018 2019 2020 2021 2017-2021 Average Total Support Estimate (TSE) RS Millions and TSE/Ag GDP EAT/PIB AGRO 54. These results are relatively low compared to those observed in São Paulo and Santa Catarina. FIGURE 23. Benchmarking TSE as share of Ag GDP 54.7% 46.4% 42.0% 13.9% 14.5% 11.1% 6.8% 6.7% 0.91% 0.95% 2.9% Colombia UE OECD Mexico EEUU Costa Brazil Chile Bahia* Santa São Rica Catarina* Paulo* Evaluation of support for Agriculture in Bahia (2017-2021) 49 3.6 Sources of Funding for Support in Bahia 55. The OECD methodology allows estimating the level of support considering the source of financing of transfers to the sector. This analysis is widely useful as it helps determine the associated cost for the two groups identified as main sources (Consumers and Taxpayers) and, from there, evaluate their efficiency from an economic and distributive point of view. 56. Figure 23 shows the sources of transfers (consumers and taxpayers) to the sector during the period 2017-2021. From the total generated in Bahia, its taxpayers generated all the transfers to the sector during the period of analysis. It was mentioned above that, to the extent that no policy instruments were observed that intervened in market prices, consumers did not generate any transfer to the sector. The methodology considers other possible consumer transfers made from the payment of taxes and tariffs for foreign trade, where the “beneficiary” is not the agricultural sector but the government, which represents a public income. For this analysis, and since these tariffs are not derived from a state government policy, these transfers have not been taken into account. FIGURE 24. Benchmarking TSE by sources of Transfers 22.3% 85.2% 100% 100% 100% 77.7% 14.8% Bahía Santa Catarina São Paulo Brazil OECD Consumers' transfers Taxpayers' transfers 50 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector 3.7 Environmental Impact of Support to the Agricultural Sector in Bahia 57. Agriculture is an important source of greenhouse gas emissions, particularly in Brazil, and is at the same time highly vulnerable to it. It is estimated that on average the Brazilian agriculture sector loses 1 percent of agricultural GDP every 6 year due to climate events. The sector however has ample opportunities to reduce its emissions, enhance carbon storage and increase its climate resilience. 58. Recent research shows that reducing the impact of agriculture on GHG emissions can come directly from increases in productivity and activity- associated factors, including restoration of degraded land, increased soil carbon sequestration in croplands, and rangelands and afforestation, etc. In recent years, the importance of various tools that can help this purpose or that could negatively affect it, has been emphasized. These tools include the various policies to support the sector, which directly or indirectly have an impact on the contribution of the sector in focusing on the environment. 59. In recent years, the OECD has considered the categories of support for agriculture and has labeled those that have a negative impact and those whose impact is minor or zero (potentially positive). For OECD, market price support (MPS) provides incentives for additional production, the intensification of the use of inputs, the allocation of land to supported crops, and the entry of land into the agricultural sector and, thus, is considered harmful to the environment. Similarly, input supports (particularly if based on production, current cropping area, or number of animals), typically encourage farmers to increase their output, either through intensification, land expansion, or retention of farms that would be financially unviable without support. 60. On the other hand, the development of new types of support that has been observed in OECD countries have included a “decoupled” ingredient, that is, they are not conditional on the production of any particular product or products and in that sense, their impact is less or minimal. 6 World Bank. 2015. Rapid and Integrated Agriculture Risk Management Review for Brazil Evaluation of support for Agriculture in Bahia (2017-2021) 51 Finally, other supports that incorporate incentives for the non-use of certain natural resources or stimulate the growth of environmental activities are considered. This type of support generates positive or pro- environmental impacts, such as payments for environmental services. 61. In Bahia, a majority of direct support to producers (PSE) was granted through payments based on inputs or production (see Table 2) which, according to the OECD criteria, have a negative effect on the environment and GHG emissions. Unlike what was observed in São Paulo and Santa Catarina, where most of the direct support is also through inputs-based payments, in the case of Bahia, no information could be obtained to establish that such support was conditional on the implementation of environmentally sustainable practices. It is worth noting though that 21 percent of the PSE in Bahia was implemented through decoupled payments that are considered to have a positive impact on the environment, like the “Environmental Regularization of Rural Properties”. 62. Decoupled payments are considered to generate positive environmental results, encouraging farmers to provide environmental goods and services such as carbon sequestration, preservation of rural landscapes, resilience to natural disasters, pollination, provision of habitat, etc. These types of measures are potentially among the most beneficial types of support measures for the environment (DeBoe, 2020). 52 4. SUMMARY AND RECOMMENDATIONS 63. Total support to agriculture (TSE) in Bahia averaged RS Millions 192.4 per year in the period 2017-2021, which is equivalent to 0.87 percent of the state agricultural GDP. These levels are lower than the levels observed in Santa Catarina (0.95 percent) and in São Paulo (2.89 percent). This total support corresponds to transfers derived from the implementation of agricultural policies of the state government. 64. Most of this support was transferred through state investment in public goods and services to the sector in general (69 percent of the total), and a smaller part (31 percent of the total) through direct support from the state government. There was no budget transfer to consumers implemented by the government of Bahia during the analyzed period. 65. The support that is granted directly to producers (and that derives from the implementation of state policies) measured by the PSE was, on average, equivalent to 0.2 percent of the total gross income of producers during the period under analysis. This level of support was lower than the support observed in OECD countries (17.4 percent) and in Brazil (2.2 percent). The low level of direct support to producers Summary and recommendations 53 reflects the sector’s competitiveness and alignment with international markets. No MPS was observed during the analyzed period. For promoting competitiveness, equity, and considering the sector as an income- generating engine, non-intervention in pricing is desirable to continue. 66. The majority of direct support to producers happened through payment based on inputs or linked to production, though it is important to note than 1/5 of PSE was made through decoupled payments. Six out of ten reais transferred directly by the state government to producers were through payments based on inputs. This type of support is sometimes considered inefficient in transferring income to the producer. It is also questioned within international trade processes and may be subject to compensation by importing countries. In addition, the payment based on inputs are considered to have a high negative impact on the environment. A portion of these supports are through extension services, which could add environmental practices to their content to be considered a more efficient type of support and reducing the potentially negative impact on the environment. 67. On the other hand, Bahia carried out sectoral programs with support for the environment, through decoupled payments. These measures allow farmers to follow market signals in their production decisions as production is not a condition to receive payments. It will be important to strengthen them financially, disseminate and promote their use, particularly among small and medium producers. 68. In relation to support for the sector as a whole and that is generated from spending on public goods and services (GSSE), there is a relatively low proportion of investment in public goods in the sector, when measured as a proportion of the state’s agricultural GDP. In the period under analysis, it was equivalent to 0.57 percent of the Agricultural GDP, a level that is below the OECD average (more than 5 percent). It is also below São Paulo (1.2 percent) and Santa Catarina (0.7 percent). This level should increase in the coming years, to promote competitiveness and challenges related to productivity, resilience, and the sector as an income generator in the medium and long term. 54 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector 69. When analyzing the composition of investment in general services and comparing it with other states and the OECD countries, it was observed that OECD countries maintain a very diversified investment among the categories that make up general services. In Bahia inspection services represent 50 percent of GSSE, with support to agricultural innovation (R&D) another important investment. It is important to note that investment in public goods is the most important factor that will promote the most efficient use of factors and, therefore, sustained long-term productivity. In that sense, it directly contributes to food security and stimulates the potential of sector to reduce GHG emissions through carbon sequestration. Using public spending on agricultural support to invest in the development and adoption of green innovations (i.e., new technologies that reduce emissions and increase productivity, such as climate-smart agriculture) can reduce emissions from agriculture and land use, and from productivity and lower use of inputs that are emission-intensive. 70. As of estimated consumer support, and because the implementation of MPS was not observed, consumers were not negatively affected. Implementation of state consumer subsidy programs was not observed as well. Implemented through well targeted programs, this type of support can be an efficient support with real impact amongst the most vulnerable population. 71. The recommendations for realigning agriculture support policies and programs towards greater competitiveness while increasing climate mitigation and resilience of the sector can be summarized around the following three key areas. There was no market price support observed during the analyzed period and in view of promoting competitiveness it is desirable that the State keeps without any price interventions.  Increase support to agricultural public goods and services. In Bahia, GSSE represented an important share of TSE (68.9 percent), showcasing a strong orientation of the State’s public support to the agricultural sector towards public goods. However, when brought as a share of the agricultural GDP, GSSE (0.57 percent of AgGDP) is well below the average observed in OECD countries (5.3 percent). It has been demonstrated that support to agriculture public goods and services yield higher economic return than Summary and recommendations 55 7 public investments in private goods. In the context of climate change that already has an important impact on the sector, it is even more crucial to ensure further innovations are brought to the farmers to adapt to climate change and mitigate the sector’s impacts on the environment, that stronger Sanitary and Phytosanitary systems are in place to face increased occurrence of pest and diseases and that infrastructure is developed to support the changes the sector is facing. For these reasons it is important to seek, whenever the fiscal space allows it, to increase support to public goods and services. It will also be important to foster the synergies and complementarities between the public goods and services supported at State and federal levels, to increase the diffusion of innovations to all farmers, in particular medium and family farmers, and improve rural infrastructure across the various regions of the countries.  Repurpose direct support to producers to foster adaptation and mitigation of the sector to climate change. Producer support (PSE) could be revised to not only support farmers’ incomes, but also to support 8 the adoption of climate-smart and low-carbon agriculture and seek to stop agricultural area expansion. The State of Bahia should link its direct support to producers to environmental conditions, including the support that is provided through extension services for dedicated crops should foster the use of sustainable practices and prevent excessive use of inputs with a potentially negative impact on the environment. Furthermore, the State of Bahia already dedicates more than 20 percent of its direct support through decoupled payments and should seek to increase that share, to strengthen them financially, and to disseminate and promote their use, particularly among small and medium- sized producers. This would enable the State to continue promoting transfers that generate income for the farmers in an efficient way, while allowing farmers to make production decisions based on market opportunity rather than the level of public support needed. Decoupled payments also are considered to be less harmful on the environment. 7 World Bank. 2001. World Development Report 2002. https://doi.org/10.1596/0-1952-1606-7, And DeBoe, G. et al. 2020. Reforming Agricultural Policies Will Help to Improve Environmental Performance, EuroChoices, Vol. 19/1, pp. 30-35, https://doi.org/10.1111/1746-692X.12247. 8 See https://www.worldbank.org/en/topic/climate-smart-agriculture 56 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector  Expand risk management instruments. Agricultural production in Bahia is facing increasing risks as a result of climate change, with extreme events becoming more frequent, causing significant crop failures and an increase in the volume of rural insurance claims. Strengthening the State’s agricultural policy through measures that protect rural producers and reduce the negative the negative impacts of climatic and socio-environmental events on the sector is more and more crucial. It is desirable to promote support for risk management by including risk mitigation instruments, which in the case of Bahia were not observed. This support is particularly important for small and medium-sized producers who are paradoxically highly vulnerable to the presence of these risks. 9 Given that uninsured risk hampers farmers’ investment , shifting part of agricultural public subsidies towards instruments that promote risk management could help improve the management of environmental and social risks in the agricultural sector. To do so in an inclusive manner, it would be important to design such a shift in a progressive way and to ensure it respond to the specific needs of small and medium farmers, who have the most difficulties in accessing those instruments through the market. In this way, the resilience of the sector can be effectively strengthened and the impact of risks on income can be mitigated.  Explore the possibility to develop well targeted consumer support programs. During the analyzed period it was not observed the implementation of programs subsidizing consumers. The State of Bahia could explore the possibility of developing such programs to safeguards the most vulnerable consumers from food insecurity and nutrition challenges, by targeting support through social protection programs (food aid, school feeding) and countercyclical safety nets. If implemented under an appropriate design and well targeted they could represent an efficient support with a real impact on the most vulnerable population. 9 SOUZA, Priscila; ASSUNÇÃO, Juliano. 2020. Risk Management in Brazilian Agriculture: Instruments, Public Policy, and Perspectives. Climate Policy Initiative. 57 Table 7 Areas of reforms for a competitive, green, resilient and inclusive agriculture sector in Bahia Competitiveness Climate mitigation Inclusiveness Agriculture Policy Shift objective and resilience objective Shift from providing private goods (PSE) X X X to public goods and services (GSSE) Shift direct support to producers X to climate-smart subsidies Expand risks management instruments X Develop well targeted consumer X support programs 58 REFERENCES Alston, J., P. Pardey and DeBoe, G. et al. (2020), Heisey, P. and K. Fuglie OECD. Agricultural Policy X. Rao (2021), “Payoffs to “Reforming Agricultural (2018), “Public agricultural Monitoring and Evaluation a half century of CGIAR Policies Will Help to R&D in high-income OECD iLibrary | Agricultural research,” American Journal Improve Environmental countries: Old and new Policy Monitoring and of Agricultural Economics, Performance”, EuroChoices, roles in a new funding Evaluation 2020-2022 Vol. 104/2, pp. 502-529, Vol. 19/1, pp. 30-35, https:// environment”, Global Food (oecd-ilibrary.org) https://doi.org/10.1111/ doi.org/10.1111/1746- Security, Vol. 17, pp. 92-102, ajae.12255. 692X.12247. https://doi.org/10.1016/j. OECD data monitoring gfs.2018.03.008. and evaluation: Reference Anderson, K. and E. FAO (2021), The share Tables : Total Support Valenzuela (2021), “What of agri-food systems in Henderson, B. and J. Estimate (TSE) (oecd.org) impact are subsidies and total greenhouse gas Lankoski (2020), “Assessing trade barriers abroad emissions: Global, regional the Environmental having on Australasian and country trends Impacts of Agricultural and Brazilian agriculture?”, 1990–2019, Food and Policies”, Applied Economic Australian Journal Agriculture Organization Perspectives and Policy, of Agricultural and of the United Nations, pp. 1-16, https://doi. Resource Economics, Rome, Italy, https:// org/10.1002/aepp.13081. Vol. 65/2, https:// fenixservices.fao.org/ doi.org/10.1111/1467- faostat/static/documents/ Forest Service. How 8489.12413. EM/cb7514en.pdf Transportation Costs Affect Fresh Fruit and Blandford, D. and K. Guerrero, S. et al. (2022), Vegetable Prices. Richard Hassapoyannes (2018), “The Impacts of Agricultural Volpe, Edward Roeger, and “The role of agriculture in Trade and Support Ephraim Leibtag (2013). global GHG mitigation”, Policy Reform on Climate OECD Food, Agriculture Change Adaptation OECD (2019), Enhancing and Fisheries Papers, No. and Environmental Climate Change Mitigation 112, OECD Publishing, Paris, Performance: A Model- through Agriculture, https://doi.org/10.1787/ Based Analysis”, OECD OECD Publishing, Paris, da017ae2-en. Food, Agriculture and https://doi.org/10.1787/ Fisheries Papers, No. 180, e9a79226-en OECD Publishing, Paris, https://www.oecd-ilibrary. OECD. Agricultural Market org/agriculture-and-food/ Information System: Home oecd-food-agriculture- (amis-outlook.org) and-fisheriesworking- papers_18156797. Annex 1. Summary of the Estimate of Support for the agricultural sector in Bahia 2017-2021 59 ANNEX 1. SUMMARY OF THE ESTIMATE OF SUPPORT FOR THE AGRICULTURAL SECTOR IN BAHIA 2017-2021 2019- Concept/Cateogry Unit 2017 2018 2019 2020 2021 2021 Average I. Total Production Value (at farm gate) Rs Mill 21.603,0 26.415,0 27.106,0 37.238,0 49.428,0 32.358,0 1. Of which the share of PSE products (%) % 37,0% 44,2% 40,0% 43,0% 47,3% 0,4 II. Total Consumption Rs Mill 17.691,2 26.230,8 29.004,0 37.283,4 43.839,2 30.809,7 value (at farm gate) 1. Of which the share of PSE products (%) Rs Mill 6.553,0 11.584,7 11.611,9 16.019,5 20.747,1 13.303,2 III.1 Producer Support Estimate (PSE) Rs Mill 62,1 66,0 42,3 51,3 77,0 59,7 A.1 Market Price Support Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 1. Of which the share of PSE products (%) Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 A.2 Payments based on production Rs Mill 4,8 7,8 7,6 8,0 14,7 8,6 B. Supports based on the use of inputs Rs Mill 43,3 44,4 24,2 34,1 44,9 38,2 1. Variable inputs Rs Mill 14,3 19,1 15,5 17,2 19,2 17,1 2. Fixed inputs Rs Mill 15,8 13,8 0,0 12,0 14,6 11,2 3. Services Rs Mill 13,2 11,6 8,7 4,9 11,0 9,9 C. Supports based on production Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 A /An/ I. Production required 1. Based on income Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 2. Based on surface the Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 number of animals D. Supports based on A / AN / I Not Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 current. necessary production E. Supports based on A / AN / I Not Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 current. production not necessary 1. Variable Rates Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 2. Fixed Rates Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 F. Support granted in criteria not related to the production Rs Mill 14,1 13,8 10,5 9,1 17,4 13,0 of agricultural products 60 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector 2019- Concept/Cateogry Unit 2017 2018 2019 2020 2021 2021 Average 1. Long term resources Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 2. A specific product Rs Mill 10,1 13,8 10,5 9,1 17,4 12,2 3. Other criteria not related to products Rs Mill 4,0 0,0 0,0 0,0 0,0 0,8 G. Miscellaneous supports Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 III.2 Producer Support Estimate % 0,0 0,0 0,0 0,0 0,0 0,0 in Percentage (PSE%) IV. Estimate of Support to Rs Mill 104,3 134,1 124,8 110,8 189,2 132,6 General Services (GSSE) H. Agricultural Knowledge Rs Mill 59,2 62,8 46,9 52,7 41,8 52,7 I. Inspection and Control Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 J. Infrastructure development Rs Mill 29,3 57,1 69,0 52,0 135,5 68,6 and maintenance K. Marketing and promotion Rs Mill 15,7 14,2 9,0 6,1 11,9 11,4 L. Public storage Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 M. Various Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 V.1 Consumer Support Estimate (CSE) Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 N. Transfers from consumers Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 to producers (-) 1. Of which the share of PSE products Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 O. Other consumer transfers (-) Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 1. Of which the share of PSE products Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 P. Transfers from taxpayers Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 to consumers V.2 Percentage of CSE % 0,00 0,00 0,00 0,00 0,00 0,0 VI.1. Total Support Estimate (TSE) Rs Mill 166,4 200,1 167,1 162,0 266,2 192,4 Q. Consumer Transfers Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 R. Taxpayers Transfers Rs Mill 166,4 200,1 167,1 162,0 266,2 192,4 S. Budget revenue (-) Rs Mill 0,0 0,0 0,0 0,0 0,0 0,0 Annex 2. Budget exercised by the State of Bahia Program (General Services) 61 ANNEX 2. BUDGET EXERCISED BY THE STATE OF BAHIA PROGRAM (GENERAL SERVICES) Agricultural Knowledge Program Description Origin Unit 2017 2018 2019 2020 2021 Technical Assistance to Rural Producers of the Semi-Arid Region Technical of Bahia - Pró-Semiárido: Provide https:// Assistance to Technical Assistance and Rural www. Produtor Rural Extension services - ATER for bahia. Rs Mill 19 22 24 30 31 do Semiárido family agriculture, traditional ba.gov. Baiano - towns and communities, settlers br/ Prosemiárido of the agrarian reform, young people, blacks and women. Technical Assistance to Rural Producers of the Semi-Arid Region of Bahia - Pró-Semiárido: Provision https:// Technical of Technical Assistance and www. Assistance to Rural Extension - ATER services bahia. Rs Mill 23 24 12 17 3 Family Farmers for family agriculture, traditional ba.gov. towns and communities, settlers br/ of the agrarian reform, young people, blacks and women. Technical Assistance to Rural Producers of the Semi-Arid Region of Bahia - Pró-Semiárido: Provide https:// Assistência Technical Assistance and Rural www. Técnica de Extension services - ATER for bahia. Rs Mill 3 6 6 4 6 Associações family agriculture, traditional ba.gov. Comunitárias towns and communities, settlers br/ of the agrarian reform, young people, blacks and women. Social and https:// Environmental Socio-environmental technical www. Technical Advice assistance to families in bahia. Rs Mill 11 6 3 1 1 to the Areas agrarian reform areas. ba.gov. of Agrarian br/ Reform - ATES Land regularization for family https:// Regularização farmers: Promote land regularization www. Fundiária para in occupied areas, prioritizing bahia. Rs Mill 4 6 2 0 1 Agricultor peasant families, villages and ba.gov. Familiar traditional communities. br/ Agricultural Knowledge Rs Mill 59 63 47 53 42 62 ENHANCING BRAZIL’S AGRICULTURE SUPPORT: Policies for a Competitive, Green, and Inclusive Agrifood Sector Infrastructure Development and Maintenance Program Description Origin Unit 2017 2018 2019 2020 2021 Implementation of the Sustainable Rural Development Project - Bahía Productiva: Fomentar la agroindustrialização, comercialização, Implantação gestão, organização, de Projeto de empreendimento, https:// Desenvolvimento cooperativism of family www.bahia. Rs Mill 29 57 69 52 136 Rural Sustentavel agriculture and Solidarity ba.gov.br/ - Bahia Produtiva Economy, of traditional peoples and communities, settlers of the agrarian reform, young people and women, considering the particularities and territorial potentialities. Infrastructure Development and Maintenance   Rs Mill 29 57 69 52 136 Marketing and Promotion               Program Description Origin Unit 2017 2018 2019 2020 2021 Implementation of a Marketing and Production Support Project: Promote agro-industrialization, marketing, management, organization, Implantação de entrepreneurship, family https:// Projetos de Apoio farming cooperativism www.bahia. Rs Mill 16 14 9 6 12 à Comercialização and solidarity economy, ba.gov.br/ e Produção traditional peoples and communities, inhabitants of agrarian reform, young people and women, considering the particularities and territorial potentialities Marketing and     Rs Mill 16 14 9 6 12 Promotion Annex 3. Budget Exercised by Bahia State Program (Other Direct Support) 63 ANNEX 3. BUDGET EXERCISED BY BAHIA STATE PROGRAM (OTHER DIRECT SUPPORT) Program Description Origin Unit 2017 2018 2019 2020 2021 Fund phytosanitary PRODEAGRO control projects for http://www.seagri. PRODEAGRO Rs Mill 12.89 17.59 18.97 18.72 30.96 crops, research and ba.gov.br/content/ paving of road corridors prodeagro Promote sustainable production systems of family farming, traditional towns and Distribution SDR communities, agrarian of Inputs for https://www. Rs Mill 4.71 5.30 4.22 5.49 5,79 reform settlers, young Family Farming bahia.ba.gov.br/ people and women, considering the particularities and territorial potentialities Participação Guarantee minimum SDR Estadual income of farmers https://www. Rs Mill 33.99 37.86 34.48 34.48 34.86 no Fundo in case of loss of bahia.ba.gov.br/ Garantia Safra agricultural harvest Expand rural Distribution infrastructure and of Apoio services for family SDR 42– Equipment farming, traditional https://www. Rs Mill 31.22 0.00 28.02 30.90 56. to Inlcusão villages and bahia.ba.gov.br/ Produtiva communities, and land reform settlers Provide Technical Apoio à Assistance and execução de Rural Extension Projeto de (ATER) services SDR Assistência for family farming, https://www. Rs Mill 35.55 26.22 21.69 11.37 23.32 Técnica e traditional villages bahia.ba.gov.br/ Extensão and communities, land Rural Pública reform settlers, youth, e Não Estatal blacks, and women Recover and develop cotton cultivation PROALBA http://www. in the territory of (Algodão:10% seagri.ba.gov.br/ Rs Mill 10.06 13.76 10.48 9.14 17.43 Bahia, especially in of 50%) content/proalba terms of technological modernization Environmental http://www. Improve quality and Regularization meioambiente. Rs Mill 3,15 0.00 0.00 0.00 0.00 environmental control of Imóvel Rural ba.gov.br/