MYANMAR’S AGRIFOOD SYSTEM Historical Development, Recent Shocks, Future Opportunities E D I T E D B Y Duncan Boughton, Ben Belton, Isabel Lambrecht, Ian Masias, and Bart Minten M YA N M A R ’S A G R IFO O D SY STEM About IFPRI The International Food Policy Research Institute (IFPRI), a research center of CGIAR, provides research-based policy solutions to sustainably reduce pov- erty and end hunger and malnutrition in low- and middle-income countries. IFPRI was established in 1975 to identify and analyze national and interna- tional strategies and policies for meeting the food needs of the developing world, with particular emphasis on low-income countries and on the poorer groups in those countries. Partnerships, communications, capacity strength- ening, and data and knowledge management are essential components to translate IFPRI’s research from action to impact. 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Myanmar’s Agrifood System: Historical Development, Recent Shocks, Future Opportunities. Washington, DC: International Food Policy Research Institute. hdl.handle.net/10568/152392 This is a peer-reviewed publication. Any opinions expressed herein are those of the authors and are not necessarily representative of or endorsed by the International Food Policy Research Institute. The boundaries and names shown and the designations used on the maps do not imply official endorsement or acceptance by IFPRI. International Food Policy Research Institute, 1201 Eye Street, NW, 12th floor, Washington, DC 20005 USA, Telephone: +1-202-862-5600, www.ifpri.org ISBN: 978-0-89629-469-1 Handle: hdl.handle.net/10568/152392 A catalogue record for this book is available from the Library of Congress. https://hdl.handle.net/10568/152392 http://www.ifpri.org https://hdl.handle.net/10568/152392 CONTENTS Tables and Figures ix Abbreviations and Acronyms xxiii Foreword tk Acknowledgments tk Chapter 1 Introduction 1 Duncan Boughton, Ben Belton, Isabel Lambrecht, and Bart Minten Chapter 2 The Agrifood System: Structure and Contribution to Development Goals 19 Xinshen Diao, Ian Masias, Karl Pauw, James Thurlow, and Duncan Boughton Chapter 3 A Historical and Regional Perspective on Myanmar’s Agrifood System 43 Duncan Boughton, Steve Haggblade, and Bart Minten Chapter 4 Dietary Quality and Nutrition: Past Progress, Current and Future Challenges 79 Kristi Mahrt, Derek Headey, Olivier Ecker, Andrew Comstock, and Salauddin Tauseef Chapter 5 Vulnerability and Welfare during Multiple Crises 121 Joanna van Asselt, Isabel Lambrecht, and Zin Wai Aung Chapter 6 Agricultural Land: Inequality and Insecurity 149 Isabel Lambrecht, Ben Belton, Peixun Fang, Bart Minten, and Phyo Thandar Naing Chapter 7 Agricultural Mechanization: Drivers and Characteristics 171 Ben Belton, Myat Thida Win, Xiaobo Zhang, Mateusz Filipski, Hiroyuki Takeshima, and Ian Masias Chapter 8 Crop Production: An Engine in Need of an Upgrade 201 Nilar Aung, Cho Cho San, Duncan Boughton, Bart Minten, Phyo Thandar Naing, Ben Belton, and Isabel Lambrecht Chapter 9 Livestock, Capture Fisheries, and Aquaculture: Status and Recent Trends 221 Ben Belton and Peixun Fang Chapter 10 Farm Commercialization: A Transformation on Hold or in Reverse? 245 Bart Minten, Peixun Fang, Phyo Thandar Naing, Zin Wai Aung, and Hnin Ei Win Chapter 11 The Rice Sector 279 Paul Dorosh, Nilar Aung, and Bart Minten Chapter 12 Agricultural Value Chains: Examples of Quiet Transformation 307 Ben Belton, Ame Cho, Peixun Fang, Myat Thida Win, and David Mather Chapter 13 Food Processing: A Stalled Transformation 337 Bart Minten, Olivier Ecker, Andrew Comstock, Kristi Mahrt, Peixun Fang, Joseph Goeb, and Phoo Pye Zone Chapter 14 Agrifood Trade 369 Xinshen Diao, Ian Masias, and Wuit Yi Lwin Chapter 15 Migration Trends and Implications 405 Mateusz Filipski, Ben Belton, Joanna van Asselt, Aung Hein, A Myint Zu, Kyan Htoo, Myat Thida Win, Eaindra Theint Theint Thu, Khun Moe Htun, and Hnin Ei Chapter 16 Income Diversification and the Rural Nonfarm Economy 435 Susan Paudel, Mateusz Filipski, and Bart Minten vi CONTENTS Chapter 17 Women and Youth in Agriculture 463 Isabel Lambrecht, Kristi Mahrt, Ame Cho, and Hnin Ei Win Chapter 18 Regional Variations in Rural Livelihoods: Challenges and Opportunities 487 Ben Belton, Mateusz Filipski, Isabel Lambrecht, and Peixun Fang Chapter 19 Conclusion: From Recovery to Renewal of the Agrifood System 509 Duncan Boughton and Bart Minten Contributors 529 Appendix: Main Data Sources Used in the Analysis 537 CONTENTS vii Cover Design: Jason Chow, IFPRI Project Manager: Pamela Stedman-Edwards, IFPRI Book Layout: BookMatters Cover Photo: anantachat / Shutterstock.com ix TABLES AND FIGURES Tables 1.1 Major data sources used in this book 15 2.1 Structure of Myanmar’s agrifood system and economy, 2019 22 2.2 Value chain groups and their corresponding agricultural subsectors 26 2.3 Myanmar’s agrifood system composition by value chains trade orientation, 2019 27 2.4 Agrifood system GDP growth rates by value chain, 2011–2019 29 3.1 Average yield and trends for cereals, oilseeds, and pulses, by five-year period, 2008–2019 47 3.2 Perceptions of most important business disruption at beginning of 2021 and 2022 51 3.3 Access to agricultural extension and credit by crop farmers in 2020, 2021, and 2022 52 3.4 Input, farmgate, and retail prices, 2020, 2021, and 2022 54 3.5 Fertilizer use by macronutrient, Myanmar and neighboring countries, 2013 56 3.6 Farmers’ share in final rice prices at different market levels, Myanmar and neighboring countries 60 3.7 Global Food Security Index, Myanmar and neighboring countries, 2019 61 3.8 Expenditure shares for different food types, by quintile of total household food expenditure, 2017 63 3.9 Investments in agricultural research, Myanmar and neighboring countries, 2017 69 3.10 Ranks of ease of doing business and international trade and trade tariffs, Myanmar and neighboring countries 72 4.1 Evolution of dietary energy percentage shares by detailed food groupings, 2010 and 2015 83 4.2 Dietary energy percentage shares by detailed food groupings and consumption expenditure quintile, 2015 85 4.3 Dietary energy percentage shares by detailed food groupings and agroecological zone and Yangon, 2015 87 4.4 Bangladesh healthy diet guidelines adapted for Myanmar, daily amounts per person 89 4.5 Healthy diet deprivation index by household group 98 4.6 Income and own price elasticities of total food demand and major food groups 103 4.7 Nutrient consumption gaps (percentage) among the bottom 40 percent of the expenditure consumption distribution in Myanmar under economic shock simulation scenarios 105 4.8 Percentage share of adults with inadequate diet diversity (fewer than 5 out of 10 food groups) 109 4.9 Percentage share of children (ages 6–23 months) with inadequate diet diversity (fewer than 4 out of 7 food groups) 110 5.1 Households experiencing negative impacts from shocks, by survey year 125 5.2 Households reporting security shocks by MHWS round, 2022, percentage share 126 5.3 Income sources by share of households, 2022 129 5.4 Income-poor households by MHWS round, September 2021–August 2022 133 5.5 Comparison of household coping strategies in 2015 and 2022, nationwide, rural, and urban 135 5.6 Households that used coping strategies in month prior to interview, 2022, by MHWS round 137 5.7 Households that owed money to a lender, 2022, by MHWS round 139 x TablES aNd FigurES 5.8 Households receiving support, 2022, by MHWS round 140 5.9 Marginal effects from exploratory regression analysis of characteristics associated with income loss and income poverty 142 5.10 Estimates from logit fixed effects models of shocks on coping mechanisms 144 6.1 Population growth and evolution of average agricultural land area 151 6.2 Land ownership and cultivation, by agroecological zone and urban or rural location 157 6.3 Farm size distribution, share of agricultural households and agricultural land 158 6.4 Tenure status of agricultural parcels, by agroecological zone 160 6.5 Characteristics of smallholders and non-smallholders and parcels operated 161 6.6 Characteristics associated with having land documents for parcels with seasonal crops, probit regression results, marginal effects 164 7.1 Machines acquired per 10,000 landed households, by time period 173 7.2 Farm households using agricultural machinery in the past 12 months, by landholding size terciles and machine ownership status 175 7.3 Use by farm households of machines and draft animals, by activity and year 177 7.4 Machinery businesses by geographic zone over time, 2000–2018 181 7.5 Total annual sales of surveyed agricultural machinery supply businesses in Yangon (2012–2016) and the Dry Zone (2013–2017) 182 7.6 Share of Yangon (2016) and Dry Zone (2017) machinery supplier sales, by source of finance and machine type 189 9.1 Household average gross income from crops, livestock, and fish for producing households, by agroecological zone and consumption expenditure tercile 223 9.2 Rural households owning livestock, by agroecological zone 225 TablES aNd FigurES xi 9.3 Average gross income per rural household by type of livestock owned and agroecological zone 225 9.4 Rural households reporting purpose for owning livestock, by livestock type 226 9.5 Rural households engaging in fishing and aquaculture, by agroecological zone 227 9.6 Share of fishing households with fishing assets, by agroecological zone 228 9.7 Average gross household income from aquaculture and fishing, and marketed surplus (share of value of fish sold), by agroecological zone 228 9.8 Challenges facing livestock- and fish-producing households during the previous three months 237 10.1 Average expenditure on crop inputs per farm, by agroecological zone 247 10.2 Associates of input expenditures, by household 250 10.3 Share of crop farmers using modern inputs 253 10.4 Values of crop production and sales per farm, by agroecological zone, US$ per year 255 10.5 Commercialization rates (value of sales/value of production) for each crop (group) 256 10.6 Associates of commercialization rates, multinomial regression 258 10.7 Input and output prices in paddy rice cultivation, monsoon 2020 and monsoon 2021, kyat 267 10.8 Sales of crops and challenges, 2021, percentage of farmers reporting 269 10.9 Changes in crop sales income, early 2022 relative to year earlier, percentage of farmers reporting 271 10.10 Associates of changes in sales income during the crisis of 2021, ordered probit 271 10.11 Enabling the Business of Agriculture measures for Myanmar and neighboring countries 273 11.1 Rice area, yield, and production, 2011–2023 281 xii TablES aNd FigurES 11.2 Productivity and input use on the major rice plot of rice farmers, by season and year 283 11.3 Household rice demand, 2014/15 291 11.4 Importance of rice for calorie consumption, in food expenditures, and for markets 291 11.5 Myanmar rice model equations, variables, and parameters 295 11.6 Myanmar household rice demand parameters 296 11.7 Model simulation results, percentage change from baseline 299 12.1 Summary of surveys by commodity, geographical zone, value chain segment, number of respondents, and year 309 12.2 Maize seed sales by input suppliers and traders, 2013 and 2018 313 12.3 Selected maize farmer characteristics, by landholding tercile 313 12.4 Change in the number of enterprises in aquaculture value chain in the Ayeyarwady–Yangon aquaculture cluster, 2006 and 2016 318 12.5 Share of Dry Zone farm households producing and selling major pulse and oilseed crops, and share of production sold 321 12.6 Rates of fertilizer and improved seed use and yields for Dry Zone groundnut, sesame, and green gram producers, 2007–2017 321 13.1 Registered private industrial enterprises, 2019 339 13.2 Revenue and value added by industry, 2019 340 13.3 Rice mill operations, employment, and credit in March 2022 compared with March 2021 343 13.4 Food consumption, by processing level 352 13.5 Estimates of expenditure elasticities, QUAIDS model 355 13.6 Estimates of price elasticities, QUAIDS model 356 13.7 Price changes of major food products in 2021 compared with 2020 and 2022 compared with 2021, selected food items, rural and urban 359 14.1 Top 12 countries importing Myanmar’s agrifood exports, 1998–2022 373 14.2 Myanmar’s top 10 agrifood export commodities or commodity groups, by value, 1998–2022 374 TablES aNd FigurES xiii 14.3 Value of Myanmar’s pulse exports to selected Asian countries, 1998–2022 377 14.4 Value of rice exports between 1998 and 2022 to countries importing more than $1 million per year in 2015–2019, US$ millions 380 14.5 Top 10 countries importing Myanmar’s maize, 1998–2022 383 14.6 Top seven countries importing Myanmar’s sesame, by value, 1998–2022 386 14.7 Top seven countries importing Myanmar’s groundnut, by value, 1998–2022 386 14.8 Top 18 countries importing Myanmar’s frozen fish, by value, 1998–2022 392 15.1 Summary of household survey details, by state, region, or zone 407 15.2 Migrant characteristics, by state/region 414 15.3 Differences in migrant occupations by gender, Dry Zone and Shan State 416 15.4 Distribution of migrant occupations at destination, percentage of migrants by state/region of origin 417 15.5 Migration costs, by state/region 418 15.6 Details of migrant remittances, by state/region 420 15.7 Primary reason for returning, by state/zone 421 16.1 Importance of different activities in household income, by agroecological zone 439 16.2 Distribution of businesses, by agroecological zone, percentage of all businesses 443 16.3 Demographics of nonfarm business owners 445 16.4 Nonfarm businesses by landholding group, percentage owned by members of landholding group 447 16.5 Industry of wage work, percentage distribution by agroecological zone 449 16.6 Wage work by occupational category 449 16.7 Variables used in the regression analysis 451 16.8 Correlates of participation in nonfarm business activities 452 16.9 Associates of livelihood strategies 454 xiv TablES aNd FigurES 16.10 Difficulties encountered by nonfarm rural businesses in the triple crisis in 2022 456 16.11 Difficulties encountered by rural wage workers in the triple crisis in 2022 456 16.12 Household participation in farm and nonfarm activities, by data source 459 17.1 Rural adults (ages 15–59 years) participating in different types of employment, among all adults and among employed adults only 469 17.2 Employment in rural areas, comparing youth and non-youth 471 17.3 Characteristics associated with different types of employment 472 17.4 Average days worked in the past 12 months, daily and annual wage reported by agricultural wage workers, by youth and non-youth and by gender 474 17.5 Male and female labor contribution to household crop production in rural Myanmar 475 17.6 Land rights of rural adults and older adults, by gender 476 17.7 Land rights of rural adults, comparing youth and non-youth 477 17.8 Multivariate probit analysis of joint and sole rights to sell land and parcel management decisions, for non-youth (25–59 years) 479 17.9 Characteristics of loans received by rural adults, by gender and age group 481 18.1 Community-level access to infrastructure and public services, by zone 489 18.2 Livelihoods and income composition, by zone 493 18.3 Mean and median total crop and non-crop rural incomes in southern Shan and the Dry Zone, kyat per capita 495 A1 Myanmar Food Security Policy Project (MFSPP) Surveys 538 A2 Myanmar Agriculture Policy Support Activity (MAPSA) Surveys 539 A3 Central Statistical Organization (CSO) Surveys 543 TablES aNd FigurES xv Figures 1.1 Myanmar’s GDP, 2019, and GDP growth, 2011–2021, in a regional context 3 1.2 Myanmar kyat, official and market exchange rates to US dollar, 2021–2023 6 1.3 Shocks to Myanmar’s economy, 2020–2022 6 1.4 Retail price of rice in Yangon (Emata variety, medium), 2011–2023 9 1.5 Security and health shocks per month in Myanmar, 2014–2022 9 1.6 Conflict events reported by township, 2021–2022 11 2.1 A simple conceptual framework of the agrifood system 21 2.2 Comparing Myanmar’s agrifood system to other countries, 2019 23 2.3 Composition of Myanmar’s agrifood system GDP, household demand, and trade, 2019 24 2.4 Agriculture GDP and agrifood system GDP as share of total GDP, off-farm share of agrifood system GDP, and agricultural share of total employment, 2011 and 2019 28 2.5 Drivers of Myanmar’s agrifood system GDP growth, 2011–2019 31 2.6 Decomposition of average annual labor productivity growth rate, 2011–2019 31 2.7 Impact of value chain growth on development outcomes in Myanmar 36 2.8 Composite score of value chain growth on development outcomes in Myanmar, equal weights 39 3.1 Trends in agriculture sector GDP, 2008–2017 47 3.2 Shares of different food groups in total agricultural output (expressed in calories per capita), Myanmar and neighboring countries, 2017 57 3.3 Crop yields, Myanmar and neighboring countries, 2017 57 3.4 Share of rice, animal-source foods, processed foods, and food away from home in total value of food consumption, Myanmar and neighboring countries 59 xvi TablES aNd FigurES 3.5 Share of food purchases in value of food consumed, Myanmar and neighboring countries 59 3.6 Agricultural researchers by degree, Myanmar and neighboring countries, 2017 69 3.7 Extension agent coverage, Myanmar and neighboring countries 71 4.1 Food consumption expenditure and energy shares by food group: Actual consumption compared with the healthy diet share, by consumption expenditure quintile 90 4.2 Healthy diet costs compared with reported expenditure (August 2022 kyat), by food group and consumption expenditure quintile 91 4.3 Food group consumption shortfalls, by urban and rural areas and consumption expenditure quintile 92 4.4 Food group consumption shortfalls, by agroecological zone and Yangon 93 4.5 Nutrient intake shortfalls, by consumption expenditure quintile 95 4.6 Nutrient intake shortfalls, by agroecological zone and Yangon 96 4.7 Absolute food group contributions to the aggregate healthy diet deprivation index 99 4.8 Marginal effects of key explanatory variables with 95% confidence intervals in regression models exploring associations between the healthy diet deprivation index and household characteristics 101 4.9 Changing costs of a healthy diet, June 2020–February 2023, nominal kyat 107 4.10 Trends in inadequate dietary diversity among mothers, rural Dry Zone, 2020–2021 107 4.11 Comparisons of inadequate dietary diversity among children ages 6–16 months in the rural Dry Zone sample in 2020 and 2021, by child age 108 4.12 Linear probability model regressions of household- and community-level predictors of the proportional change in the risk of inadequate diet diversity among adults 111 TablES aNd FigurES xvii 5.1 Myanmar Household Welfare Survey of 2022, timeline of rounds compared with monsoon and maize and rice cropping calendars 123 5.2 Conflict shocks by region, September 2021–August 2022 127 5.3 Households whose income in previous three months was lower (or higher) than in same period one year earlier, by MHWS round 130 5.4 Households reporting earning less money compared with previous year, by main source of household income 130 5.5 Share of population with daily per capita income below poverty line, across three survey rounds, by states/regions, 2022 133 5.6 Households with per capita daily income below poverty line, by main income source and by rural/urban location 134 6.1 Cumulative distribution (Lorenz curve) of land area owned and operated 158 7.1 Location and number of machinery supply businesses over time, 2008–2018 180 7.2 Cumulative share of migrants from Delta and Dry Zone, by year of migration, 1990–2016 185 7.3 Average daily wage rates for casual agricultural labor in the Delta (2011–2016) and the Dry Zone (2012–2016), kyat 185 8.1 Map of Myanmar’s states, regions, and agroecological zones 203 10.1 Imports of machines and agrochemicals, 2010–2021 252 10.2 Quantity and value of fertilizer imports into Myanmar, 2011–2021 253 10.3 Area cultivated (gross area sown) of paddy and non-paddy crops 258 10.4 Cumulative distribution graph (Lorenz curve) on value of crop sales 261 10.5 Commercialization and welfare linkages 261 10.6 Remoteness of townships (travel time to a city of minimum of 50,000 people) 263 10.7 Travel time of farmers to a city of at least 50,000 people 264 10.8 Market access and prices, commercial input use, yields, and output market participation, monsoon 2021 265 xviii TablES aNd FigurES 10.9 International price evolutions: Real prices for food and fertilizer 267 11.1 Rice area, yield, and production, 1990–2023 281 11.2 Myanmar rice exports (tons), 2008/09 to 2021/22 285 11.3 Myanmar rice exports by type of rice (tons), April 2022–February 2023 285 11.4 Trade barriers to rice exports, 1996–2021 286 11.5 Myanmar and Thai rice export prices (US$/ton), 2008/09 to 2022/23 287 11.6 Rice prices in Myanmar and Thailand (kyat/kg), 2013–2023 287 11.7 Real rice prices in Myanmar and Thailand (2023 kyat/kg), 2013–2023 288 11.8 Real rice prices (2023 kyat/kg), 2019–2023 289 11.9 Seasonality in rice production and exports 292 11.10 Spatial patterns in rice markets 294 11.11 Rice and paddy prices, 2021–2023 294 11.12 Impacts of lower incomes and lower rice productivity on amounts produced, exported, and consumed 299 11.13 Impacts of lower incomes and lower productivity on rice consumption by household type, percentage change in consumption 300 11.14 Impacts of lower rice export demand on amounts produced, exported, and consumed 300 11.15 Impacts of lower household incomes, reduced rice productivity, and lower exports on rice consumption by household type 301 12.1 Cumulative number of surveyed households that adopted maize and agrochemicals, by year of adoption, 1990–2017, southern Shan State 311 12.2 Southern Shan maize traders and input suppliers selling inputs, by first year of sale, from 1988, percentage share 311 12.3 Businesses in the maize value chain in surveyed townships, 2013 and 2018 314 12.4 Density of poultry houses per village tract from integrated chicken–fish farms within a 100 km radius of central Yangon, 2014 and 2018 316 TablES aNd FigurES xix 12.5 Share of broiler and layer farms using formulated feed, by brand 316 12.6 Price index of real prices (deflated by national consumer price index) of selected animal-source foods, 2008–2018 (100 = April 2018) 319 12.7 Real monthly retail prices of groundnut and palm oil, January 2009–February 2018 326 12.8 Edible oil consumption 2015, by expenditure quintile 326 13.1 Most significant reported business disruption reported by rice millers, by mill size, March 2022 342 13.2 Purchase year of operating machines owned by modern rice mills 344 13.3 Food trade in Myanmar, by processing level, 2009–2022 346 13.4 Origins and destinations of food trade in Myanmar, by processing level, 2022 347 13.5 Import and export prices, by processing level, average for 2009–2022 349 13.6 Palm oil prices, import wholesale parity and retail, August 2021–July 2022 350 13.7 Prices per calorie for different processing categories 354 13.8 Per capita food consumption for urban and rural areas, by processing category, 2020 and 2022 359 13.9 Value of food consumption, by processing category, for urban and rural areas by poverty quintile, 2020 and 2022 361 14.1 Myanmar’s GDP and agrifood export and import levels, 2010–2022 370 14.2 Average annual growth rates for total GDP, agrifood GDP, value of total exports and imports, and value of agrifood exports and imports, 2010–2019 and 2020–2022 371 14.3 Net total exports and net agrifood exports, as a share of total GDP, 2010–2022 371 14.4 Value of exports of top agrifood commodities from Myanmar, by commodity, 2005–2022 375 14.5 Myanmar’s pulse exports, by value, total and to India, 2000–2022 376 xx TablES aNd FigurES 14.6 Rice and maize exports, by value, 2010–2022 383 14.7 Oilseed exports, by value, 2000–2022 385 14.8 Natural rubber exports to China, Malaysia, and rest of world, by value, 2010–2022 388 14.9 World natural rubber prices, annual nominal, 2010–2022 389 14.10 Unit value of natural rubber exports to China and Malaysia, annual nominal, 2010–2022 389 14.11 Exports of fishery products, by value, 2000–2022 392 14.12 Value of cattle exports, by importing market, 2010–2022 394 14.13 Fruit exports, by value, 2010–2022 395 15.1 Map of locations of household surveys 408 15.2 Year of migration for current migrants from surveyed households, by survey 409 15.3 Share of households with a migrant, by state/zone 411 15.4 Migrant destinations, by state/zone or country 411 15.5 Approximate migration flows 413 15.6 Gender of current migrants, by state/region 415 15.7 Primary activity before, during, and after migration for returned migrants from Shan State 422 15.8 Real wages over time, by state/zone 423 15.9 Use of machinery in rice production, by state/zone 425 15.10 Year of first migration for migrants surveyed in 2022 and 2023 428 15.11 Main drivers reported for whole-household internal migration, February 2021–July 2023 429 16.1 Average distribution of income sources in Myanmar’s rural sector 437 16.2 Participation by rural households in nonagricultural work, by income quintile and landholding tercile 440 16.3 Rural households engaging in various types of nonfarm businesses 441 16.4 Distribution of businesses in rural Myanmar based on years of operation 443 TablES aNd FigurES xxi 16.5 Average number of workers (hired or family) in nonfarm businesses, by type 445 16.6 Median total monthly income and income per worker in nonfarm businesses, by type 447 16.7 Sectoral division of wage occupations 448 16.8 Household participation in wage employment, by income quintile and landholding tercile 450 16.9 Correlates of the nonagricultural share of income (tobit regressions) 454 16.10 Change in income compared with the previous year (July/August 2022 vs. July/August 2021) 457 16.11 Real agricultural wages, 2020–2022, by gender of worker 458 17.1 Employment in the past 12 months, male and female rural adults, by age 470 17.2 Share of men and women participating in agricultural activities, community-level data 474 17.3 Male and female rural adults who have right to sell or are parcel decision-makers, by age 477 18.1 Cumulative share of schools, roads, and electricity connections established in surveyed communities in the Dry Zone by year, 1917–2017, conditional on community having access 491 18.2 Share of villages in southern Shan with schools, paved roads, electricity connections, rural health centers, and mobile internet access by year, 1978–2018 491 18.3 Average real daily wage rates for casual agricultural workers in the Delta (2011–2016), Dry Zone (2012–2016), and Shan (2012–2017), kyat per capita 496 19.1 Changes in urban and rural nominal income distributions and poverty lines in 2022 512 19.2 Prevalence of low household food consumption and inadequate adult dietary diversity scores, fourth quarter, 2022 514 19.3 Change in cost of common and healthy diets between March 2022 and February 2023, by area 515 xxii TablES aNd FigurES xxiii ABBREVIATIONS AND ACRONYMS ACLED Armed Conflict Location & Event Data Project AEZ(s) agroecological zone(s) AFS agrifood system(s) AMD Agricultural Mechanization Department AQSIQ General Administration of Quality Supervision, Inspection and Quarantine, People’s Republic of China ASEAN Association of Southeast Asian Nations ASFs animal-source foods BACI Base pour l’analyse du commerce international CERP COVID-19 Economic Recovery Plan CGE computable general equilibrium (model) CSO Central Statistical Organization EAO ethnic armed organization EAR estimated average requirement f.o.b. free on board (type of price for a traded commodity) FAFH food (consumed) away from home FAO Food and Agriculture Organization of the United Nations GDP gross domestic product GIS geographic information system IHLCA Integrated Household Living Conditions Assessment LIFT Livelihoods and Food Security Trust Fund MADB Myanmar Agricultural Development Bank MAF Myanmar Armed Forces MAPS Myanmar Agricultural Performance Survey MAPSA Myanmar Agriculture Policy Support Activity MFSPP Myanmar Food Security Policy Project MHWS Myanmar Household Welfare Survey MLCS Myanmar Living Conditions Survey MOALI Ministry of Agriculture, Livestock, and Irrigation MPLCS Myanmar Poverty and Living Conditions Survey NEET not in employment, education, or training QUAIDS quadratic almost ideal demand system RIAPA Rural Investment and Policy Analysis (data and modeling system) RRR relative risk ratio RUFSS Rural Urban Food Security Survey SAM social accounting matrix SD standard deviation SE standard error SLORC State Law and Order Restoration Council UNDP United Nations Development Programme USDA United States Department of Agriculture USDP Union Solidarity and Development Party xxiv abbrEviaTiONS aNd aCrONymS VFV vacant, fallow, and virgin (land) VMS vessel monitoring system WFP World Food Programme WTO World Trade Organization abbrEviaTiONS aNd aCrONymS xxv xxvii FOREWORD Following the economic and political reforms initiated in 2011, Myanmar experienced notable progress, including an increase in foreign investment and improved economic performance, marked by important advances in the agrifood sector. However, the recent crises, including political instability and the COVID-19 pandemic, have affected these gains severely. To restore and enhance the agrifood system’s potential, comprehensive efforts are needed to improve its institutions and infrastructure, boost productivity, and ensure food and nutrition security. These measures are critical to reducing poverty and fostering long-term economic development in Myanmar. This book is the culmination of a decade of rigorous empirical research on Myanmar’s agrifood system, and provides critical insights into its evolu- tion, current state, and future opportunities. The book offers a comprehensive overview of the agrifood system’s development and its economic role before and during recent crises, measures welfare outcomes in terms of poverty and nutrition, and examines the performance of various system components such as input supply, mechanization services, farm-level production, processing, retailing, and international trade. It also explores the regional dynamics of rural livelihoods through the lenses of gender and youth and identifies neces- sary investments and policies to enable the agrifood system to drive recovery and long-term economic development. The insights presented here are valuable not only for guiding immediate humanitarian assistance but also for designing future growth strategies, once a resolution to the current crisis is found that ensures lasting peace and good governance. Myanmar’s recovery from the multiple crises it has faced since 2020 will require a robust combination of effective humanitarian interventions, sustained policy reforms, and overall development support. Only through concerted efforts to address institutional, infrastructure, and productivity constraints can the agrifood system fulfill its potential as a driver of inclusive and sustainable development. The authors provide a roadmap for stakeholders at all levels—policy- makers, development practitioners, researchers, and civil society—who are committed to fostering a resilient and prosperous agrifood system in Myanmar. Their insights and recommendations should serve as a valuable resource in the collective effort to achieve food security, economic stability, and social equity in Myanmar. Broadly, this work also offers unique insights into the functioning of agrifood systems during periods of rapid growth and transformation, as well as under stress, and provides examples of pathways for recovery in fragile and conflict-affected economies, where most of the global poor and food- insecure populations reside. Johan Swinnen Director General, IFPRI Managing Director, Systems Transformation, CGIAR xxviii FOrEwOrd xxix ACKNOWLEDGMENTS This book is a collaboration between researchers from the International Food Policy Research Institute (IFPRI) and Michigan State University and has benefited from the comments and suggestions of many people. While there are too many to name, we are particularly thankful to the Myanmar researchers and support staff, whose dedication and hard work was essential to the creation of this book. These individuals include A Myint Zu, Ame Cho, Aung Hein, Aung Htun, Aung Tun Oo, Aye Mya Thinzar, Cho Cho San, Eaindra Theint Theint Thu, Hnin Ei Win, Htet Htet Khine, Khaing Wah Soe, Khin Zin Win, Khun Moe Htun, Kyan Htoo, L. Seng Kham, Lu Min Win, Moe Sabai, Myat Thida Win, Nang Lun Kham Synt, Ni Ni Myint Aung, Nilar Aung, Nweni Khin Soe, Phoo Pye Zone, Phyo Thandar Naing, Sithu Kyaw, Thu Thu San, Wuit Yi Lwin, Zaw Min Naing, and Zin Wai Aung. We extend our gratitude to the many enumerators who conducted surveys and gathered crucial data, and to the respondents who generously shared their insights, providing invaluable information for this research. Additionally, we wish to acknowledge Myanmar Survey Research (MSR), with a special thanks to Patrick Mesa and Thet Su San, and Innovations for Poverty Action (IPA) Myanmar, with a special thanks to Afke Jager and Thein Zaw Oo, for leader- ship in overseeing data collection efforts amid challenging conditions. We would like to extend our special thanks to Todd Benson for his metic- ulous reading and editing of the manuscript. His keen eye for detail and insightful feedback have significantly improved the clarity and quality of this book. We also express our sincere appreciation to Matt Curtis and Sutham Phurahong from the United States Agency for International Development (USAID) for their unwavering support and guidance to our Myanmar program. We are thankful to IFPRI’s Publications Review Committee and its chair, Gerald Shively, as well as two anonymous reviewers for their critical and valu- able comments and suggestions. We gratefully acknowledge the editing and design of this book by IFPRI’s Editorial Services, particularly Pamela Stedman-Edwards, and the Visual Design and Production team, who have been pivotal in shap- ing the book’s final presentation. We also appreciate the support of IFPRI’s Communications and Public Affairs unit, led by Charlotte Hebebrand, for their efforts in promoting and disseminating our work. This book is the culmination of a decade of investment into research on Myanmar’s agrifood system by USAID, the Livelihoods and Food Security Fund (LIFT), and the CGIAR Research Program for Policies, Institutions, and Markets (PIM). We are grateful for their commitment to the people of Myanmar. xxx aCkNOwlEdgmENTS INTRODUCTION Duncan Boughton, Ben Belton, Isabel Lambrecht, and Bart Minten A decade of rapid, albeit uneven, progress in Myanmar’s economic devel- opment was thrown into reverse by a series of shocks that began with the COVID-19 pandemic in early 2020. The pandemic was followed by the military coup of February 2021 and the global food, fuel, and fertil- izer supply crisis spurred by the armed conflict in Ukraine that began a year later. The coup led to a surge in conflict around the country, hampering and often devastating the livelihoods of the population at large while also caus- ing the internal displacement of about 2.3 million people by the end of 2023, adding to those displaced during prior conflicts (UNHCR 2024). The sharp depreciation of Myanmar’s currency since the coup multiplied the inflationary impact of international price increases for fuel, fertilizer, and imported vege- table oils, causing inflation to spiral upward even as employment opportuni- ties withered. By late 2023, over 70 percent of the population was estimated to be in poverty (MAPSA 2024), more than double the 2017 poverty rate of 25 percent (CSO, UNDP, and World Bank 2019). Though Myanmar’s agrifood system was not left unscathed by these shocks, it has proved resilient. Agriculture and the rural economy are essential to Myanmar’s development, as 70 percent of the population and 87 percent of the country’s poor live in rural areas (MOPF and World Bank 2017a). Agriculture and its associated agro-industries form a key sector of the national economy, employing half of the total labor force and contribut- ing one-third of national GDP—about 23 percent directly in farm incomes and another 11 percent in agro-processing, distribution, marketing, exports, and food retailing (Chapter 2). Ekanayake, Ambrosio, and Jaffee (2019) estimate that nearly half of Myanmar’s poverty reduction between 2005 and 2015 was attributable directly to progress in agriculture. Therefore, a well-functioning agrifood system is crucial to the welfare and food security of Myanmar’s residents. The analyses presented in this book fill an important knowledge gap for one of Southeast Asia’s major agricultural economies—one largely closed to Chapter 1 1 empirical research for several decades. Myanmar is better endowed with land and water resources than many countries in the region, with considerable ara- ble land per person, much of it irrigable, and generally reliable seasonal precipi- tation patterns that are suited for crop production. However, the performance of its agrifood system lags behind those of neighboring countries. The contrib- utors to this book combine data from standard household and enterprise sur- veys conducted during the 2015–2020 period with more recent phone surveys and a mix of analytical approaches to provide empirical insights into patterns of rural transformation over the succession of recent crises and to examine how the impacts of disease, conflict, international commodity price surges, and domestic policy changes have interacted to unravel livelihoods and dra- matically worsen welfare. This understanding is useful for guiding near-term humanitarian assistance interventions and, if there is a resolution to the cur- rent crisis that ensures lasting peace and good governance, the design of future inclusive and sustainable growth strategies. This introductory chapter places Myanmar’s development in a regional context and describes the timeline and nature of the crises that later chapters will explore in depth. We then outline the specific objectives of the book and its organization, concluding with a brief overview of the data sources used for the analyses presented in the following chapters. Myanmar’s development in regional context Independent since 1948 and known as Burma until renamed by the mili- tary junta in 1989, Myanmar has yet to evolve into a unified national state (Myint-U 2019). Its economic development has also been held back by decades of military rule, ethnic conflict, and centralized planning (Brown 2012; Fujita and Okamoto 2009). In 2019, Myanmar’s per capita GDP was just under $1,300. By comparison, Cambodia, Myanmar’s poorest neighbor, had a per capita GDP of almost $1,700, Lao People’s Democratic Republic (PDR) was almost double at $2,600, and Viet Nam at almost $3,500 and Thailand at more than $7,500 were even higher (Figure 1.1, panel A). Myanmar’s low per capita GDP reflects the delayed structural transforma- tion of its economy. At the turn of the millennium, agriculture, forestry, and fishing combined accounted for the largest share of its GDP at 57 percent. Comparable shares for Myanmar’s poorest neighbors, Cambodia and Lao PDR, were 34 percent and 33 percent, respectively. The figure for Viet Nam was just 23 percent, while in Thailand, the share of its economy made up 2 Chapter 1 by agriculture had fallen to single digits a decade before. As discussed in Chapter 3, Myanmar’s agriculture sector was underperforming due to low productivity, high inequality in land access, and underinvestment in trans- port infrastructure. FIgURe 1.1 Myanmar’s GDP, 2019, and GDP growth, 2011–2021, in a regional context 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 Cambodia Lao PDR Myanmar Thailand Viet Nam Cu rr en t U S do lla rs A: GDP per capita, 2019 –20% –15% –10% –5% 0% 5% 10% 15% B: GDP growth, 2011–2021 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Cambodia Lao PDR Myanmar Thailand Viet Nam Source: Data from World Bank (2024a). Note: Lao pDr = Lao people’s Democratic republic. IntroDuCtIon 3 Although it took catastrophic Cyclone Nargis in 2008 to trigger meaning- ful change,1 Myanmar’s development policies finally turned a corner under the quasi-civilian Union Solidarity and Development Party (USDP) govern- ment beginning in 2011. In contrast with earlier economic reforms during which market liberalization efforts were accepted as a macroeconomic neces- sity, these were now fully embraced to promote foreign direct investment and spur economic growth. From 2011 to 2019, Myanmar’s economic growth was among the highest in Southeast Asia (Figure 1.1, panel B). The opening of the country to international mobile phone service providers; relaxation of import restrictions on nearly all goods, including vehicles; reform of the bank- ing sector; loosening of restrictions on internal movement and migration; and expansion of education opportunities combined to dramatically change the economy. Major investments in road and energy infrastructure were also made—although these were geographically biased toward Bamar-majority regions of the country (Chapter 18 discusses regional development patterns). A national land use policy was also formulated with broad engagement by civil society, focusing on more equitable and secure access to land resources (Chapter 6). The transition that took place in Myanmar was not without its limitations. The USDP administration arguably laid much of the groundwork for contin- ued reform under the National League for Democracy government that took office in 2016. The poverty headcount fell dramatically from 48.2 percent in 2005 to 24.8 percent in 2017. However, there was a large gap between rural and urban poverty headcounts of 30.2 percent and 11.3 percent, respectively (MOPF and World Bank 2017b). Moreover, the rate of poverty reduction was modest relative to its economic growth and, therefore, less pro-poor and inclu- sive than it might have been (World Bank 2019). The transition also failed to establish a fully democratic system. The Myanmar Armed Forces (MAF) continued to play a large role in ruling the country; it still controlled the security forces, key cabinet positions, and 25 percent of the seats in the national and regional legislatures (Crouch 2020; Thawnghmung 2019). Further, conflict continued in many eth- nic states, and in Rakhine State it flared up significantly in 2016 and 2017 (Thawnghmung 2019). 1 See Warr and Aung (2019) for an analysis of the impact of Cyclone Nargis on poverty and inequality. 4 Chapter 1 Multiple shocks, multiple consequences Myanmar has endured three types of shocks since early 2020: the COVID- 19 pandemic, economic and social disruption following the military coup and subsequent widespread conflict, and international commodity price surges. These led to dramatic declines in economic growth, resulting in an estimated 18 percent contraction of Myanmar’s economy in 2021, as measured by GDP per capita (Figure 1.1). These shocks have overlapped in time, magnifying their economic effects. For example, the rapid depreciation of the Myanmar kyat after the military coup multiplied the impact of international commod- ity prices on domestic inflation. Figure 1.2 illustrates the fast depreciation of the Myanmar kyat against the US dollar since the beginning of 2021. While the kyat was traded at around K1,300/$1.00 at the beginning of 2021, its offi- cial value had declined by 60 percent by September 2022 to K2,100/$1.00. Informal market rates were K3,500/$1.00 at the end of 2023. The earliest reports of COVID-19 coincided with the beginning of the 2019/20 tourist season, resulting in large-scale trip cancellations. Social dis- tancing measures were introduced as awareness grew of the potential for dis- ease spread. Wet markets remained open to maintain access to food. However, the closure of international borders and uncoordinated road closures by local authorities led to the loss of perishable produce. In early April 2020, the gov- ernment ordered a three-week nationwide shutdown to coincide with the annual water festival and traditional New Year celebrations, cognizant of the country’s very constrained health system resources and the population’s reli- ance on public transport during these holidays. The pandemic response had an immediate impact on Myanmar’s economy, as well as on poverty. Closures and reduced operations in industries and small and medium nonfarm businesses led to significant reductions in household incomes (Diao and Mahrt 2020; World Bank 2024b). Further, border closures and lockdown measures reduced out-migration, while at the same time many internal and international migrants decided to return home. Remittance flows decreased significantly, reducing household income and cutting off an import- ant social safety net (ILO 2020). One way to visualize the effects of successive waves of COVID-19 is to use Google Community Mobility data, made publicly available from the incep- tion of the pandemic until October 2022. Figure 1.3 shows changes in the percentage of phone users who stayed at home from early 2020 to late 2022 relative to a five-week baseline period at the beginning of 2020 prior to the widespread emergence of COVID-19. IntroDuCtIon 5 The government moved quickly to establish a COVID-19 Economic Recovery Plan (CERP) to mitigate the economic consequences of the pan- demic (GoM 2020). CERP focused initially on COVID-19’s impact on urban sectors of the economy, such as the closure of garment factories, which employed more than half a million workers. However, with the nation’s rice supply dependent on the monsoon growing season and concerns about the potential effects of lost migrant worker remittances on farm household FIgURe 1.3 Shocks to Myanmar’s economy, 2020–2022 0 5 10 15 20 25 30 35 40 Fe b- 20 M ar -2 0 Ap r- 20 M ay -2 0 Ju n- 20 Ju l-2 0 Au g- 20 Se p- 20 Oc t- 20 No v- 20 De c- 20 Ja n- 21 Fe b- 21 M ar -2 1 Ap r- 21 M ay -2 1 Ju n- 21 Ju l-2 1 Au g- 21 Se p- 21 Oc t- 21 No v- 21 De c- 21 Ja n- 22 Fe b- 22 M ar -2 2 Ap r- 22 M ay -2 2 Ju n- 22 Ju l-2 2 Au g- 22 Se p- 22 Oc t- 22Ch an ge in p ho ne u se rs s ta yi ng a t h om e (% ) 3rd wave COVID-19 lockdowns 2nd wave COVID-19 lockdowns Impact of military takeover 1st wave COVID-19 lockdowns Source: Based on data from Google (2022). Note: Y-axis measures the percentage change relative to February 2020 in the extent to which phone users stayed at home. FIgURe 1.2 Myanmar kyat, official and market exchange rates to US dollar, 2021–2023 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500 5,000 Ja n- 21 Mar- 21 May -2 1 Ju l-2 1 Se p- 21 Nov -2 1 Fe b- 22 Ap r-2 2 Ju n- 22 Au g- 22 Oct- 22 Dec -2 2 Mar- 23 May -2 3 Ju l-2 3 Se p- 23 Nov -2 3 Ja n- 24 M ya nm ar k ya t CBM reference rate US$ market rate Source: Data from CBM (2023), private money changers. Note: CBM = Central Bank of Myanmar. 6 Chapter 1 input purchases, CERP expanded the seasonal loans provided through the Myanmar Agricultural Development Bank. As a result of such proactive measures to support the economy, combined with effective public health campaigns, the economic effects of shutdowns on the agrifood system were relatively transient during the initial COVID-19 wave and during a second wave from September to December 2020 (Boughton et al. 2021). The impacts of the military coup on February 1, 2021, had consequences of an entirely different scale and duration. Although the first few weeks saw little bloodshed, widespread protests and the emergence of a national Civil Disobedience Movement resulted in a shutdown of the health and education sectors, manufacturing, and the banking system. Given that the economy, especially the informal sector, depends heavily on cash transactions, the bank- ing shutdown quickly and widely disrupted economic activity. Large queues formed at automated teller machines, withdrawal amounts were limited, and tokens were allocated to ration access to cash. The Myanmar kyat depreciated rapidly (Figure 1.2). In mid-2021, a third wave of COVID-19—the highly contagious and lethal Delta variant—began during this political and economic chaos (Figure 1.3). Most civilian hospitals were closed or seriously understaffed, and the country also had extremely limited domestic supplies of medical oxygen. While accu- rate statistics on total infections and deaths are unavailable, reported cases and deaths soared in July and August 2021 (WHO 2023). Compared to earlier COVID-19 waves, the financial resources of affected households were heav- ily drained by medical and funeral expenses and by lost work opportunities for family members who had to care for sick relatives. Whereas previous waves had primarily affected urban centers, the breakdown of public health ser- vices and lack of adherence to disease prevention measures, combined with the much more contagious nature of the variant, meant that rural areas saw more severe impacts during this third wave. Russia’s invasion of Ukraine on February 24, 2022, just over a year after the military coup in Myanmar, resulted in a further surge in international com- modity prices. By mid-April, the US dollar price of urea fertilizer, crucial for agricultural production, was 180 percent higher than a year earlier (Baffes and Koh 2023). Price increases of imported fertilizer were further exacerbated by international freight rates, which more than doubled because of COVID-19 disruptions to shipping. Increased international fuel prices—approximately 60 percent higher in US dollars in April 2022 compared with a year earlier— added to in-country distribution costs (Trading Economics 2023). The domestic price of fertilizer was further affected by the depreciation of the kyat IntroDuCtIon 7 following the coup. In the year to August 2022, it lost more than half its value on the parallel market. Myanmar’s consumers were also negatively affected by food price infla- tion, which peaked at an annual rate close to 40 percent a year after the coup (MAPSA 2022a). The price of rice—the country’s basic staple—increased steadily from 2021 through 2023. By December 2023, its price in Yangon’s retail markets was three times higher than before the coup (Figure 1.4). International rice prices increased by 30 percent over the same period.2 Farmgate prices for rice did not change as much. However, increased trans- action costs contributed significantly to the rise in retail prices (Minten et al. 2023). Retail prices for other commodities also rose dramatically. Myanmar depends heavily on imported vegetable oil, so the combination of interna- tional price increases and disruptions to palm oil imports from Indonesia led to a quadrupling of domestic vegetable oil prices (MAPSA 2022b). Adding to the economic disruption, violent conflict widened geographi- cally as armed resistance to the coup expanded in the wake of regime crack- downs on street protests. Myanmar has long been plagued by repressive military rule and armed conflict—often, but not limited to, conflicts between the MAF and ethnic armed organizations (EAOs). In the two decades prior to the 2011 transition, MAF tried to contain EAOs through military offen- sives, ceasefires, and clientelism (Stokke et al. 2022). The strategy was largely the same after 2011 but was carried out within the new political context. The result was continued ethnic conflict across the country. Figure 1.5 gives an overview of the change in the number of fatalities because of violent events since 2014. While ceasefires slowed conflict in Kayin and Shan States, nego- tiations failed in Kachin and northern Shan States, where hostilities resumed with significant clashes in 2015 and 2019 (ACLED 2022). The August 2017 spike in fatalities in Figure 1.5 reflects violence between MAF and the Rohingya in Rakhine State. However, the course of these conflicts altered after the February 2021 mil- itary coup. The tenuous ceasefire agreements that had held conflict at bay during civilian government rule collapsed, and violence resumed or intensified between MAF and EAOs (Stokke et al. 2022). The ousted leaders of the civil- ian government, as well as activists from ethnic groups, formed the People’s Defense Force and declared war on the MAF. Figure 1.5 shows a sharp increase in fatalities in 2021 and a further spike in 2022. In this period, the 2 The Indica rice price index was 118.5 in December 2020 and 154.3 in December 2023 (FAO 2023a). 8 Chapter 1 Myanmar military bombed and burned hundreds of villages, reprising the tac- tics it had used previously in confrontations with ethnic minority groups and that had provoked a mass exodus of Rohingya in 2017. This also led to a surge in internal displacements during 2022. FIgURe 1.4 Retail price of rice in Yangon (Emata variety, medium), 2011–2023 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 Ky at /k g Ja n-1 1 Ja n-1 3 Ja n-1 4 Ja n-1 2 Ja n-1 5 Ja n-1 6 Ja n-1 7 Ja n-1 8 Ja n-1 9 Ja n- 20 Ja n- 21 Ja n- 22 Ja n- 23 Ja n- 24 Source: Data from Fao (2023b). FIgURe 1.5 Security and health shocks per month in Myanmar, 2014–2022 2,500 2,000 1,500 1,000 500 January 2014 January 2015 January 2016 January 2017 January 2018 January 2019 January 2020 January 2021 January 2022 0 3,000 2,500 2,000 1,500 1,000 500 0 Conflict-related fatalities COVID-19 deaths C o n fli ct -r el at ed fa ta lit ie s C O V ID -1 9 d ea th s Source: aCLeD (2022); Who (2023). IntroDuCtIon 9 Conflict erupted in townships that war had touched since Myanmar’s independence, as illustrated in Figure 1.6 (ACLED 2022). In March 2021, fighting broke out in Sagaing and Mandalay Regions. By May 2021, this con- flict had spread to Chin State and Magway Region. In the southeast, fight- ing broke out in Bago Region in March 2021 and Kayah and Kayin States in May 2021. Fighting commenced in Mon State, Tanintharyi Region, and southern Shan State in September 2021, though at a comparatively lesser scale. In Kachin, intense fighting began right after the coup and then picked up again in mid-2022. Additionally, tensions between MAF and the Arakan Army are growing in Rakhine State and southern Chin State. Intermittent fighting has been recorded in those areas since June 2022 (OCHA 2022). In addition to these recent shocks, Myanmar is susceptible to climate shocks, including cyclones, erratic monsoons, irregular rainfall, droughts and floods, and high winds. It is already experiencing the negative consequences of climate change. Globally, the country is ranked among the three countries most vulnerable to climate change and extreme weather events because of the large proportion of its population that lives in hazard-prone areas, its geo- graphic location, and its socioeconomic conditions (UNDRR 2015). Between 2000 and 2019, the country had 14.4 fatalities related to climate shocks per 100,000 inhabitants—10 more fatalities than the next most affected territory, Puerto Rico (Eckstein, Künzel, and Schäfer 2021). The most extreme climate event in Myanmar’s recent history was Cyclone Nargis in 2008, which killed more than 138,000 people in the Ayeyarwady Delta (Thawnghmung 2019). The country has been fortunate to avoid a major negative weather event amid the succession of recent shocks, but one (or more) could occur at any time. Given the erosion of household resilience since 2020, another cyclone like Nargis would cause devastation on a scale that neither the country nor its development partners are in any position to manage. Objectives and roadmap for the book A decade of empirical research on Myanmar’s agrifood system enables us to address the following objectives in this book: • To provide an overview of the evolution of Myanmar’s agrifood system and its role in the economy prior to and during the recent crises (Chapters 1–3). • To measure welfare outcomes in terms of poverty and nutrition for different household types and the factors associated with them (Chapters 4 and 5). 10 Chapter 1 FIgURe 1.6 Conflict events reported by township, 2021–2022 Source: aCLeD (2022). Note: number of battles, violent incidents, or explosions reported. 700–800 600–700 500–600 400–500 300–400 200–300 100–200 1–100 0 IntroDuCtIon 11 • To examine the performance of specific components of the agrifood system: farm-level production, upstream input supply and mechaniza- tion services, downstream processing, retailing, and international trade (Chapters 6–14). • To understand, through gender, youth, and ethnicity lenses, the regional dynamics of rural livelihoods and the interaction between land access, migration, and farm and nonfarm employment (Chapters 15–18). • To identify investments and policies needed for Myanmar’s agrifood sys- tem to serve as a springboard for recovery and long-term economic devel- opment (Chapter 19). Addressing the first objective, Chapter 2 measures the contribution of the agrifood system as a whole to economic growth and employment in Myanmar. The authors use economywide modeling to identify which agricultural value chains have the potential to drive inclusive economic growth and improved nutritional outcomes in the future. Chapter 3 takes a retrospective look at agricultural performance to identify structural impediments and policy and investment gaps on the supply side that have prevented the agrifood system from fulfilling its potential. Addressing the second objective, Chapter 4 examines household con- sumption and nutrition, focusing on how recent food price inflation and income losses have undermined food and nutrition security. Possible inter- ventions to mitigate the potentially serious long-term consequences are iden- tified. Chapter 5 examines the impact of different kinds of shocks—conflict, climate, health, and economic—on household income and welfare and how household coping strategies have evolved in response. These chapters reveal a high degree of fragility in livelihoods in the face of multiple shocks that affect the demand side of the agrifood system, despite a relatively resilient sup- ply side. The following four chapters characterize the farm production components of the agrifood system. Chapter 6 analyzes the distribution, tenure, and use of agricultural land across the main agroecological zones in Myanmar and eval- uates the influence of successive land policy regimes on land access. Chapter 7 documents the rapid rise of agricultural mechanization in Myanmar in the decade prior to 2020 and analyzes the factors associated with this dra- matic change and its implications for agricultural households and work- ers. The chapter also addresses changes in access to mechanization services since the onset of COVID-19. Chapter 8 examines the regional distribution, 12 Chapter 1 productivity, profitability, and extent of technology adoption in Myanmar’s major crops, including rice, pulses, and maize, highlighting reasons for under- performance and recommendations for improvement. Chapter 9 documents the characteristics of livestock and fisheries, two of Myanmar’s most dynamic high-value agrifood sectors, assessing both traditional small-scale produc- ers and more specialized production systems and their contributions to rural employment and national nutrition security. The next five chapters examine upstream and downstream linkages con- necting farm production to the rest of the agrifood system. Chapter 10 exam- ines changes in farm commercialization over time, giving close attention to fertilizer (the most important purchased input in value terms), marketed crop surpluses, and the factors associated with farmer marketing decisions. Chapter 11 focuses on the structure and performance of the rice value chain. Chapter 12 contrasts the dynamism of the maize–poultry–fish value chain nexus with challenges facing the oilseeds and pulses value chains in a con- text of market liberalization. Chapter 13 drills down into the food processing sector, which accounts for more than half of all registered industrial enter- prises in the country, analyzing the underlying drivers of domestic and inter- national demand for processed food products. Chapter 14 examines trends in international trade for Myanmar’s agricultural products broadly, noting the constraints imposed by the unpredictable trade practices of the country’s larger neighbors. An overall picture emerges of a sector struggling to real- ize its potential for adding value to farm produce due to internal and exter- nal constraints. The final chapters examine rural and urban livelihoods more broadly, applying a gender lens and considering how migration and off-farm employ- ment complement regional agrifood system constraints and opportuni- ties. Chapter 15 provides insights into the widespread phenomenon of rural out-migration using data collected in different parts of the country between 2015 and 2019 and through phone surveys during the recent crises. Migration has been and continues to be critical in sustaining or improving rural live- lihoods in Myanmar. Chapter 16 looks beyond farming as the main liveli- hood in rural areas and shows a vibrant rural nonfarm economy, though one that is inevitably affected by the ongoing crises. Chapter 17 spotlights women and youth, using nationally representative data to demonstrate their impor- tance to the country’s agricultural production. Chapter 18 provides a more detailed synthesis of the regional diversity of rural development and live- lihoods, emphasizing the uneven development paths seen both across and within regions. IntroDuCtIon 13 Chapter 19, the concluding chapter, points to implications from the analy- sis for future policy and public investment priorities to enable the agrifood sys- tem to support recovery and economic growth. Data sources The analysis in this book uses a wide range of primary sources (Table 1.1). Research between 2015 and 2019 was undertaken using household surveys in purposefully selected townships in four agroecological zones. These were combined with stacked value chain surveys for several important agricultural commodities. The data, survey instruments, and related documentation are publicly available on Harvard Dataverse under the Myanmar Food Security Policy Project (MFSPP) data series (Harvard Dataverse 2020). From the onset of COVID-19 in early 2020, non-random phone surveys of actors at all stages in the agrifood system were conducted at frequent inter- vals. In addition, a 12-round panel phone survey of 2,000 households was con- ducted over the same period. Beginning in late 2021, a multi-round nationally and regionally repre- sentative phone survey of approximately 12,000 households, the Myanmar Household Welfare Survey (MHWS), was launched under the Myanmar Agriculture Policy Support Activity (MAPSA). A multi-round survey of approximately 5,500 farm households belonging to the same sample, the Myanmar Agricultural Performance Survey (MAPS), was also launched. These data, survey instruments, and related documentation are publicly avail- able on Harvard Dataverse under the IFPRI Dataverse data series (Harvard Dataverse 2024). We also rely on secondary data, including from national household sur- veys conducted by the Central Statistical Organization (CSO) (Table 1.1). The Myanmar Living Conditions Survey (MLCS), fielded in 2017, is a com- prehensive household survey that provides information on the living condi- tions of the people of Myanmar and agricultural practices across the country (CSO 2019). It provides data representative of the country and at the level of its states and regions. In total, 13,730 households participated in the survey. We also rely on the food consumption module of the nationally representa- tive Myanmar Poverty and Living Conditions Survey (MPLCS), fielded in 2015 (MOPF and World Bank 2017a, 2017b; World Bank 2024b). MPLCS is a cross-sectional household survey that contains data from 3,658 households interviewed between January and April 2015. 14 Chapter 1 Together, these primary and secondary datasets provide a strong founda- tion for analyses to address the book’s objectives. More details on these sur- veys are provided in the Appendices. References ACLED (Armed Conflict Location & Event Data). 2022. ACLED database. Accessed December 15, 2024. http://acleddata.com Baffes, J., and W.C. Koh. 2023. “Fertilizer Prices Ease but Affordability and Availability Issues Linger.” World Bank blog, January 5. Washington, DC: World Bank. Boughton, D., J. Goeb, I. Lambrecht, et al. 2021. “Impacts of COVID-19 on Agricultural Production and Food Systems in Late Transforming Southeast Asia: The Case of Myanmar.” Agricultural Systems 188: 103026. Brown, I. 2012. Burma’s Economy in the Twentieth Century. Cambridge, UK: Cambridge University Press. CBM (Central Bank of Myanmar). 2023. “Reference Exchange Rate.” February 25. https://forex. cbm.gov.mm/index.php/fxrate Crouch, M. 2020. “Pre-emptive Constitution-Making: Authoritarian Constitutionalism and the Military in Myanmar.” Law and Society Review 54 (2): 487–515. Table 1.1 Major data sources used in this book Dataset Year Zone Myanmar Food Security Policy Project (MFSPP) aquaculture 2016 Delta pulses and oilseeds 2017 Dry Zone Maize 2018 Shan poultry and pigs 2019 Yangon Myanmar Agriculture Policy Support Activity (MAPSA) Value chain agents 2020–2022 national Social accounting Matrix (SaM) 2021 national Myanmar household Welfare Survey (MhWS) 2022 national Myanmar agricultural performance Survey (MapS) 2022 national Central Statistical Organization (CSO) Myanmar poverty and Living Conditions Survey (MpLCS) 2014–2015 national Myanmar Living Conditions Survey (MLCS) 2017 national Source: Compiled by authors. IntroDuCtIon 15 CSO (Central Statistical Organization). 2019. Myanmar Living Conditions Survey 2017: Report 02: Technical Report. Nay Pyi Taw. CSO, UNDP (United Nations Development Programme), and World Bank. 2019. Myanmar Living Conditions Survey 2017: Report 03: Poverty Report. Nay Pyi Taw. Diao, X., and K. Mahrt. 2020. “Assessing the Impacts of COVID-19 on Household Incomes and Poverty in Myanmar: A Microsimulation Approach.” Myanmar Strategy Support Program Working Paper 2. International Food Policy Research Institute (IFPRI), Washington, DC. Eckstein, D., V. Künzel, and L. Schäfer. 2021. Global Climate Risk Index 2021. Briefing Paper. Bonn, Germany: Germanwatch. Ekanayake, I.J., A.M. Ambrosio, and S.M. Jaffee. 2019. Benchmarking of Myanmar’s Food Systems: Evidence and Strategic Directions. Washington, DC: World Bank. FAO (Food and Agriculture Organization of the United Nations). 2023a. FAOSTAT database. Accessed 2023. www.fao.org/faostat FAO 2023b. “Food Price Monitoring and Analysis (FPMA) Tool.” Accessed December 2024. https://fpma.fao.org/giews/fpmat4/#/dashboard/tool/domesticFAO Fujita, K., and I. Okamoto. 2009. “Overview of Agricultural Policies and the Development in Myanmar.” In The Economic Transition in Myanmar After 1988: Market Economy Versus State Control, eds. K. Fujita, F. Mieno, and I. Okamoto, 169–215. Singapore: National University of Singapore Press. GoM (Government of the Republic of the Union of Myanmar). 2020. Overcoming as One: COVID- 19 Economic Relief Plan. Nay Pyi Taw. Google. 2022. “Google COVID-19 Community Mobility Reports.” www.google.com/covid19/ mobility/ Harvard Dataverse. 2020. “Myanmar Food Security Policy Project Dataverse.” https://dataverse. harvard.edu/dataverse/FSPP Harvard Dataverse. 2024. “IFPRI Dataverse.” https://dataverse.harvard.edu/dataverse/ IFPRI/?q=Myanmar ILO (International Labour Organization). 2020. COVID-19: Impact on Migrant Workers and Country Response in Myanmar. Geneva. MAPSA (Myanmar Agriculture Policy Support Activity). 2022a. Monitoring the Agri-food System in Myanmar: Food Vendors - March 2022. Myanmar Strategy Support Program Research Note 78. Washington, DC: MAPSA, IFPRI. MAPSA. 2022b. Monitoring the Agri-food System in Myanmar: Understanding the Rapid Price Increase of Vegetable Oils. Myanmar Strategy Support Program Research Note 77. Washington, DC: MAPSA, IFPRI. 16 Chapter 1 MAPSA. 2024. Livelihoods and Welfare: Findings from the Sixth Round of the Myanmar Household Welfare Survey. Myanmar Strategy Support Program Working Paper 53. MAPSA, IFPRI, Washington, DC. Minten, B., J. Goeb, K.Z. Win, and P.P. Zone. 2023. “Agricultural Value Chains in a Fragile State: The Case of Rice in Myanmar.” World Development 167: 106244. MOPF (Ministry of Planning and Finance) and World Bank. 2017a. An Analysis of Poverty in Myanmar: (Part 1) Trends between 2004/05 and 2015. Nay Pyi Taw: MOPF. MOPF and World Bank. 2017b. An Analysis of Poverty in Myanmar: (Part 2) Poverty Profile. Nay Pyi Taw: MOPF. Myint-U, T. 2019. The Hidden History of Burma: Race, Capitalism, and the Crisis of Democracy in the 21st Century. London: Atlantic Books. OCHA (United Nations Office for the Coordination of Humanitarian Affairs). 2022. Myanmar Humanitarian Update No. 23, 31 October 2022. Yangon, Myanmar. Stokke, K., K.K. Moo Kham, N.K.L. Nge, and S.H. Kvanvik. 2022. “Illiberal Peacebuilding in a Hybrid Regime: Authoritarian Strategies for Conflict Containment in Myanmar.” Political Geography 93: 102551. Thawnghmung, A.M. 2019. Everyday Economic Survival in Myanmar. Economic Perspectives in Southeast Asian Studies. Madison, WI: University of Wisconsin Press. Trading Economics. 2023. “Gasoline.” Accessed January 2024. https://tradingeconomics.com/ commodity/gasoline UNDRR (United Nations Office for Disaster Risk Reduction). 2015. Global Assessment Report on Disaster Risk Reduction 2015. New York. UNHCR (United Nations High Commissioner for Refugees). 2024. “Myanmar UNHCR Displacement Overview 05 Feb 2024.” https://data.unhcr.org/en/documents/details/106598 Warr, P., and L.L. Aung. 2019. “Poverty and Inequality Impact of a Natural Disaster: Myanmar’s 2008 Cyclone Nagris.” World Development 122: 446–461. WHO (World Health Organization). 2023. “COVID-19 Myanmar.” WHO Health Emergency Dashboard. https://covid19.who.int/region/searo/country/mm World Bank. 2019. Myanmar—Economic Transition amid Conflict. Washington, DC. World Bank. 2024a. “World Bank Open Data.” https://data.worldbank.org/ World Bank. 2024b. World Development Indicators database. Accessed 2023. https://databank. worldbank.org/data/source/world-development-indicators IntroDuCtIon 17 THE AGRIFOOD SYSTEM: STRUCTURE AND CONTRIBUTION TO DEVELOPMENT GOALS Xinshen Diao, Ian Masias, Karl Pauw, James Thurlow, and Duncan Boughton As countries develop, agrifood systems (AFS) are expected to evolve beyond primary agriculture (Diao, Hazell, and Thurlow 2010; Timmer 1988). The earliest stages of development are typically characterized by subsistence farming; as agricultural productivity rises, farmers begin to sup- ply surplus production to markets, which creates employment opportunities for workers in the off-farm economy (Haggblade, Hazell, and Dorosh 2007). Rising rural incomes generate demand for more diverse products; this leads to more nonfarm activities such as processing, packaging, transporting, and trad- ing. In the early stages of transformation, the agriculture sector serves as an engine of rural—and even national—economic growth. Eventually, urbaniza- tion, the nonfarm economy, and nonagricultural incomes play more dominant roles in propelling AFS development, with urban and rural nonfarm con- sumers creating most of the market demand for agricultural outputs via value chains that connect rural areas to towns and cities (Dorosh and Thurlow 2013). The exact nature of this transformation process varies across countries because of the diverse structure of their economies and the unique growth tra- jectories of their various agrifood and nonfood subsectors. A focus solely on primary agriculture without an understanding of its linkages to off-farm com- ponents of the economy masks the importance of AFS to the overall economy and its potential contribution as a driver of development going forward. In this chapter, we first measure the size, structure, and historical contribu- tion of the AFS to economic growth and transformation in Myanmar. Second, we assess the potential for AFS growth led by productivity gains in different agricultural value chains to contribute to development outcomes in Myanmar using the Rural Investment and Policy Analysis (RIAPA) model (IFPRI 2023b). We measure AFS using national accounts and employment statis- tics to either track or simulate growth and employment changes over time. We disaggregate AFS into several value chain groups, which allows the analy- sis to offer a unique and useful perspective on the drivers of AFS growth and Chapter 2 19 transformation. Finally, we discuss the implications of the recent crises for the future of the AFS and propose both short- and long-term policy recommenda- tions to help steer recovery. Myanmar’s agrifood system A simple conceptual framework A country’s AFS is a complex network of actors connected by their differing roles in supplying, using, and governing agrifood products (Fanzo et al. 2020). Figure 2.1 provides a simplified conceptual framework of AFS made up of five components, A to E (Thurlow et al. 2023). Primary agriculture (A) comprises the supply and demand of all agricultural products, including crops, livestock, fisheries, and forestry products. Agro-processing (B) is part of the manufactur- ing sector and includes those subsectors that process agriculture-related food or nonfood products. Trade and transport services (C) include those associ- ated with transporting, wholesaling, and retailing agrifood products among farms, firms, and final points of sale. Food services (D) includes services such as meals prepared at restaurants, food stalls, or hotels. Finally, input supply (E) is the portion of domestically produced intermediate inputs used directly in agricultural and agro-processing production, such as fertilizers and financial services. Using this conceptual framework, a social accounting matrix (SAM), and complementary national accounts and statistics, it is possible to measure the size and structure of an AFS from a supply-side perspective. Following the definitions of Thurlow et al. (2023), AFS gross domestic product (or AgGDP+) is the sum of the value added from the five components (A to E), while AFS employment (or AgEMP+) is the total number of jobs across those components. As the economy grows and transforms over time, changes will occur in the relative contributions of the various on-farm and off-farm com- ponents of AFS to total AgGDP+ or AgEMP+. A transforming economy, for example, will typically be characterized by more rapid growth in the off-farm components of AFS; there will thus be an increased contribution from off- farm components to AgGDP+ and AgEMP+ and a relative decline in the con- tribution of primary agriculture. By disaggregating AgGDP+ and AgEMP+ into distinct agricultural value chains, we can further assess the contribution of each of those value chains to AFS growth and transformation. 20 Chapter 2 Structure of Myanmar’s agrifood system in 2019 Table 2.1 presents the structure of the AFS in 2019. GDP figures for the total economy and aggregate economic sectors, such as primary agriculture, total manufacturing, and total services, come from the latest national accounts data for Myanmar, while employment figures were obtained from the International Labour Organization (ILO 2020). The breakdown in Table 2.1 of the non- farm components of AFS (corresponding to components B, C, and D of Figure 2.1) is based on the 2019 SAM for Myanmar (IFPRI 2023a), which includes disaggregated economic activities and the input-output relationship between economic subsectors. The SAM triangulates subsectoral employment data from the 2014 population census (MoLIP 2015), household budget and labor force surveys (MNPED 2011; ILO 2017), and additional international databases containing sectoral employment time series (de Vries et al. 2021). Table 2.1 presents the value and shares of GDP and employment (i.e., AgGDP+ and AgEMP) for the total economy, the entire AFS, and the rest of the economy outside AFS. AFS is further broken down into on-farm (pri- mary agriculture) and the four off-farm components. Furthermore, it pro- vides information on total manufacturing and services, including the trade and transport services subsector, encompassing activities in both AFS and non-AFS sectors. This offers insights into the relative size of the off-farm AFS components within the overall manufacturing and services sectors. FIGURE 2.1 A simple conceptual framework of the agrifood system Consumption of own- produced goods Purchase of primary agricultural goods Purchase of ready-made foods outside of home Purchase of processed agrifood goods Primary agriculture Agroprocessing Trade and transport Food services Trade and transport Input supply Imports Demand A C B E C D Source: thurlow et al. (2023). the agrifood SyStem: StruCture and Contribution to development goalS 21 In 2019, AFS was the primary contributor to national GDP (46.3 percent) and the economy’s largest employer (64 percent). Primary agriculture alone contributed 22 percent to GDP and represented almost half of all employ- ment. In contrast, the four off-farm components collectively represented 24.4 percent of the GDP, surpassing primary agriculture, while accounting for 14.8 percent of employment and 23 percent of AgEMP+. The comparison of on- and off-farm GDP and employment shares shows that labor productiv- ity is significantly higher in the off-farm components. Consequently, the tran- sition of farm workers into these off-farm components, a natural evolution in agricultural transformation, raises economywide labor productivity and would potentially enhance household incomes. AgGDP+ amounted to $32.2 billion, more than double the $15.2 billion generated by the primary agriculture sector. This implies that for every $1.00 of GDP generated on-farm, an additional $1.12 of GDP is generated off-farm in the AFS. Trade and transport was the largest contributor to off-farm GDP. However, labor productivity, measured as GDP per worker, was highest in agro-processing, likely because the sector is more capital intensive and uses rel- atively less labor than other components in the off-farm AFS. In general, the TABLE 2.1 Structure of Myanmar’s agrifood system and economy, 2019 Category GDP Employment Average GDP per worker ($) Value (US$ billions) Share (%) Workers (millions) Share (%) total economy 69.4 100.0 23.3 100.0 2,975 agrifood systems 32.2 46.3 14.9 64.0 2,155 primary agriculture (a) 15.2 22.0 11.5 49.2 1,328 off-farm agrifood systems 16.9 24.4 3.4 14.8 4,909 processing (b) 5.7 8.2 0.6 2.5 9,626 trade and transport (C) 7.8 11.2 2.0 8.7 3,811 food services (d) 2.3 3.3 0.7 2.9 3,392 input supply (e) 1.2 1.7 0.2 0.7 7,787 rest of economy 37.3 53.7 8.4 36.0 4,431 total manufacturing 15.2 21.9 1.5 6.6 9,903 total services 30.9 44.5 8.8 37.6 3,520 total trade and transport 23.3 33.6 6.4 27.4 3,652 Source: authors’ calculations based on 2019 myanmar Sam (ifpri 2023a). Note: gdp in the 2019 myanmar Sam is in myanmar kyat and converted to uS$ using the 2019 exchange rate of 1,518.3 kyat to 1.00 uS$ from the World development indicators database (World bank 2024). a to e correspond with the five agrifood system components from figure 2.1. 22 Chapter 2 off-farm labor productivity of $4,971 aligns with the average in the broader economy outside AFS ($4,440) and is significantly higher than on-farm labor productivity ($1,322). Comparing Myanmar’s agrifood system to other countries The structure and economic contribution of the AFS vary across different stages of a country’s development. Figure 2.2 illustrates this by comparing the AFS structures of low-income, lower-middle-income, upper-middle- income, and high-income countries with Myanmar’s AFS in 2019. Both the on- and off-farm composition of Myanmar’s AFS and its contribution to national GDP are larger than those of its peer lower-middle-income countries (panel A). However, within the four off-farm components of AFS, the trade and transport component is relatively larger in Myanmar compared to other lower-middle-income countries (panel B). This reflects the delayed trans- formation of Myanmar’s AFS as well as high transport costs due to poor infra- structure (discussed in Chapter 3). Unpacking the demand side of Myanmar’s agrifood system Panels A and B of Figure 2.3 compare the supply side of Myanmar’s AFS, as measured by AgGDP+ (panel A), with the demand side, as gauged by house- hold consumption of agrifood products (panel B). While primary agriculture contributed 47.4 percent to AgGDP+, its products make up only 26.8 percent of household demand. Conversely, processed agrifood products represent FIGURE 2.2 Comparing Myanmar’s agrifood system to other countries, 2019 33.7 37.8 38.4 46.9 26.1 33.6 31.7 42.8 38.6 21.4 35.9 45.8 23.1 13.7 11.2 18.2 27.8 13.5 11.4 5.8 11.8 13.5 10.3 7.1 B: Shares of off-farm components in total off-farm AFS GDP (%) Input supply Food services Trade and transport Processing 4.2 26.4 16.9 7.1 1.2 22.08.2 13.4 11.9 10.6 6.6 24.4 A: Shares of agricultural and off-farm AFS in total GDP (%) Primary agriculture Off-farm AFS All LIC LMIC UMIC HIC Myanmar All LIC LMIC UMIC HIC Myanmar Source: ifpri’s agrifood System database (thurlow et al. 2023) and 2019 myanmar Sam (ifpri 2023a). Note: afS = agrifood system. hiC = high-income countries. liC = low-income countries. lmiC = lower-middle-income countries. umiC = upper-middle-income countries. the agrifood SyStem: StruCture and Contribution to development goalS 23 65.9 percent of total agrifood demand despite accounting for only 17.7 percent of AgGDP+. This bias toward processed agrifood products is also reflected in the high share of agrifood imports, with 57.5 percent of exports being pro- cessed commodities (panel C), while 72.5 percent of imports are processed goods (panel D). Nevertheless, the agrifood export value is more than dou- ble the total value of agrifood imports and almost three times that of primary agricultural imports. Due to the significant surplus in its commodity trade balance, Myanmar has considerable potential for boosting agricultural exports. Moreover, the value of exports from agro-processing surpasses processing imports. However, as detailed in Chapter 13, many exported agro-processing goods involve minimal manufacturing activities. For instance, milled rice and rubber are important export commodities. Although categorized as agro-pro- cessing exports, the value addition to paddy rice and raw rubber materials is minimal. In essence, the value of agro-processing exports predominately reflects the value of primary agricultural products. FIGURE 2.3 Composition of Myanmar’s agrifood system GDP, household demand, and trade, 2019 47.4% 17.7% 35.0% A: AgGDP+ 26.8% 65.9% 7.3% B: Household agrifood demand Primary agriculture Agro-processing Other off-farm C: Agrifood exports ($5.44 bil.) $3.13 bil. 57.5% $2.31 bil. 42.5% D: Agrifood imports ($2.35 bil.) $1.70 bil. 72.5% $0.65 bil. 27.5% Source: authors’ calculations based on 2019 myanmar Sam (ifpri 2023a). Note: aggdp+ = agrifood system gdp. bil. = billion. 24 Chapter 2 Disaggregating the agrifood system across value chains Decomposing AFS across major product groups enables us to understand the structural and historical growth patterns of the AFS and track the value added by each of its five components. The 2019 Myanmar Social Accounting Matrix (SAM) includes 33 primary agricultural subsectors and 19 agro- processing sub- sectors/commodities organized into 13 groups (Table 2.2). The agro- processing subsectors are grouped based on their association with each of the 33 primary agricultural subsectors. However, two processed agricultural subsectors that manufacture highly processed food products—processed foods and bever- ages—are classified as “unattributable” and are not shown in Table 2.2, due to their complex linkages back to primary agriculture. More than 90 percent of Myanmar’s off-farm AFS can be mapped to these 13 distinct product groups, excluding the two omitted subsectors. We refer to these product groups as value chains, delineated by their primary agricultural products. On the basis of their trade orientation, we further classify the 13 value chain groups into three subgroups—exportable, importable, and less traded. Exportable and importable value chains are defined by export–output and import–consumption ratios that exceed the national average, respectively, con- sidering trade in both primary and processed agrifood products. The remaining value chains are classified as less traded. Table 2.3 shows the breakdown of these value chain groups by trade orientation and their contribution to AgGDP+, primary agricultural GDP, and GDP in the off-farm components of AFS. Consistent with Figure 2.3, Table 2.3 shows Myanmar’s comparative advantage in exports, as evidenced by the 9.7 percent export–output ratio exceeding the 4.4 percent import–consumption ratio. Together, the seven exportable value chains account for 58.1 percent of Myanmar’s AgGDP+, 51.3 percent of the off-farm share of GDP, and 65.7 percent of primary agri- cultural GDP. Milled rice, the largest exportable commodity, accounts for more off-farm GDP (32 percent) than primary agricultural GDP (22 percent), given its value addition through activities such as milling, storage, trade, and transport. Additionally, the off-farm component of the horticultural value chain is significant. Therefore, expanding the exports of rice and horticultural products and enhancing their value addition could effectively propel agricul- tural transformation and off-farm employment. It is noteworthy that many export-oriented products are widely consumed in the domestic market, while oilseeds and other cereals, which include sor- ghum, millet, wheat, and barley, hold potential for import substitution. The four less-traded value chains collectively represented 25.2 percent of AgGDP+. the agrifood SyStem: StruCture and Contribution to development goalS 25 Moreover, crops like sugarcane, tobacco, coffee, tea, cattle, and milk have sub- stantial off-farm components, contributing similar shares to both on- and off- farm GDP (25.0 and 25.4 percent, respectively).1 The information provided in this section is valuable in comprehending linkages between the AFS and the broader economy and implications for further structural changes. For instance, the off-farm AFS exhibits consid- erably lower labor intensity than farming, necessitating significant off-farm expansion to absorb workers transitioning out of agriculture as the sector transforms. However, off-farm labor productivity is higher, suggesting that transitioning workers to other sectors could enhance overall labor productiv- ity across the economy and raise incomes for rural households. Last, break- ing down AgGDP+ across value chains enables us to anticipate how different sources of agricultural growth may impact agricultural transformation differ- ently, favoring either on-farm or off-farm growth. 1 Though livestock is categorized as less tradable in Table 2.3, this classification is influenced by an export ban on livestock that was temporarily eased in October 2017 but then effectively rein- stated in 2019. TABLE 2.2 Value chain groups and their corresponding agricultural subsectors Value chain group and share of Myanmar’s AgGDP+ Individual value chains or agricultural subsectors in the group (share of group’s AgGDP+) maize (1.7%) maize (100%) rice (27.2%) rice (100%) other cereals (2.9%) Sorghum & millet (78.7%), wheat & barley (14.1%), other cereals (7.2%) oilseeds (5.8%) pulses (100%) pulses (3.7%) groundnut (46.3%), other oilseeds (53.7%) roots (2.6%) Cassava (47.4%), irish potatoes (17.8%), sweet potatoes (34.8%) horticulture (12.5%) leafy green vegetables (14%), other vegetables (24%), bananas (18.1%), other fruits (43.9%) other export crops (1.0%) nuts (73.8%), cut flowers (3.2%), rubber (23%) other crops (9.7%) Sugarcane (29%), tobacco (25.8%), cotton & fibers (0.8%), leaf tea (9.5%), coffee (19.2%), other crops (15.7%) Cattle & dairy (9.1%) Cattle meat (56.8%), raw milk (43.2%) other livestock (3.8%) poultry meat (28.9%), eggs (9.9%), small ruminants (23.6%), other livestock (37.6%) fish (9.6%) aquaculture (43.6%), capture fisheries (56.4%) forestry (2.4%) forestry (100%) Source: authors’ calculations based on 2019 myanmar Sam (ifpri 2023a). Note: aggdp+ = agrifood system gdp. 26 Chapter 2 Recent growth and transformation In this section, we assess the performance and structural transformation of Myanmar’s AFS from 2011 to 2019. AgGDP+ and AgEMP+ were derived from two SAMs—one for 2011 and another for 2019—to illustrate growth trends between the two periods. The SAMs were constructed to align with official GDP estimates at both the national and sectoral levels. Although SAMs are typically measured in current prices, the estimates were adjusted to constant prices to facilitate comparisons over time, using GDP deflators from Myanmar’s most recent GDP series. Typically, labor productivity is lowest in primary agriculture but higher in off-farm activities, such as agrifood processing, food services, or sectors out- side the AFS. Economic growth and urbanization correlate with relatively faster expansion in these nonagricultural sectors, potentially generating high- er-paying employment opportunities for both rural and urban households. TABLE 2.3 Myanmar’s agrifood system composition by value chains trade orientation, 2019 Value chain Share of GDP (%) Exports / output (%) Imports / demand (%) AFS (AgGDP+) Primary agriculture Off-farm AFS total 100.0 100.0 100.0 9.7 4.4 Exportable 58.1 65.7 51.3 16.8 1.1 maize 1.7 2.2 1.3 35.1 3.9 rice 27.2 22.0 32.0 10.6 0.3 pulses 3.7 6.8 0.9 45.4 0.0 horticulture 12.5 16.3 9.0 10.4 1.7 export crops 1.0 1.8 0.3 37.5 0.1 fish 9.6 14.7 5.1 27.1 1.2 forestry 2.4 2.0 2.8 33.7 11.2 Importable 8.7 9.3 8.1 1.6 19.4 other cereals 2.9 1.4 4.2 0.1 23.4 oilseeds 5.8 7.9 3.9 2.6 16.6 Less tradable 25.2 25.0 25.4 1.1 4.2 roots 2.6 3.9 1.4 0.0 0.0 other crops 9.7 4.5 14.3 2.6 2.0 Cattle and milk 9.1 9.8 8.6 0.1 8.3 other livestock 3.8 6.8 1.1 0.4 0.4 Source: authors’ calculations based on 2019 myanmar Sam (ifpri 2023a). Note: afS = agrifood system. aggdp+ = agrifood system gdp. the agrifood SyStem: StruCture and Contribution to development goalS 27 Consequently, even smallholder farm households with family members secur- ing off-farm employment could benefit from structural transformation. Figure 2.4 shows for 2011 and 2019 the share of national GDP made up by agricultural GDP and AgGDP+, the off-farm component’s share of AgGDP+, and agricultural employment as a percentage of total employment. During the period from 2011 to 2019, there was a notable decline in the share of agricul- tural GDP and AgGDP+ in total GDP and in the share of total employment made up by agricultural employment. In contrast, the share of AgGDP+ made up by the off-farm component experienced a rapid increase. The significant structural changes witnessed in the broader economy during this period of rapid economic growth have led to the transformation of AFS. The fact that by 2019 the share of AgGDP+ generated off-farm surpassed that of primary agriculture confirms this transformation. However, primary agriculture still maintains a substantial portion of employment despite its lower labor produc- tivity compared to the off-farm components of AFS. Table 2.4 assesses the growth performance across AFS value chains between 2011 and 2019. The value chains remain categorized based on their trade orientation. Overall, AFS grew at a 4.3 percent annual rate in total AgGDP+, with the off-farm component growing significantly faster (7.5 percent per year) than primary agriculture (1.6 percent per year). Agrifood FIGURE 2.4 Agriculture GDP and agrifood system GDP as share of total GDP, off-farm share of agrifood system GDP, and agricultural share of total employment, 2011 and 2019 29.8 50.9 41.4 54.8 22.0 46.3 52.6 49.2 Agricultural GDP share AgGDP+ share Off-farm share of AgGDP+ Agricultural employment share Sh ar e (% ) 2011 2019 Source: authors’ estimates using ifpri’s myanmar 2011 and 2019 Sams (ifpri 2023a). Note: aggdp+ = agrifood system gdp. 28 Chapter 2 processing, a subcomponent of the off-farm segment, expanded at an impres- sive rate of 10.0 percent annually. Growth varied significantly across value chains. Among the 13 value chains, six exceeded the 2011–2019 average of 4.3 percent per year. These are indicated by an asterisk in Table 2.4. Three value chains experienced negative growth rates, including pulses, Myanmar’s primary agrifood export commod- ity. Among the importable and less-traded value chains, cereals (mainly wheat) and the two livestock value chains had growth rates surpassing the AFS aver- age. Conversely, growth stagnated in oilseeds and declined in root crops. In all the rapidly growing value chains, the off-farm components of AFS experienced substantially higher growth rates than the primary agricultural component. Moreover, the processing components exhibited rapid growth in both high-growth and slower-growing value chains. This pattern in the value chains is consistent with the broader pattern of growth and structural change TABLE 2.4 Agrifood system GDP growth rates by value chain, 2011–2019 Value chain Average annual GDP growth rate (%) Total AFS Primary agriculture Off-farm AFS Agro-processing total afS 4.3 1.6 7.5 10.0 Exportable 3.3 0.9 6.8 8.6 maize 2.1 3.1 0.8 8.5 ricea 6.6 3.5 9.1 10.3 pulses −4.7 −4.5 −5.8 na horticulture 1.6 −1.1 8.1 14.2 export crops 1.9 1.7 2.7 10.4 fisha 4.3 3.6 6.6 17.5 forestry −2.4 −1.7 −2.8 −5.9 Importable 3.2 −0.2 8.2 6.9 other cerealsa 10.1 −3.1 21.0 22.3 oilseeds 0.9 0.4 1.8 3.3 Less traded 5.7 4.4 7.0 11.1 roots −3.1 −3.5 −2.0 na other cropsa 5.9 2.4 7.0 10.3 Cattle and milka 9.7 10.3 9.1 11.8 other livestocka 6.2 5.7 9.2 14.1 Source: authors’ analysis using ifpri’s 2011 and 2019 myanmar Sams (ifpri 2023a). Note: a value chains that experienced above-average aggdp+ growth over the period 2011–2019 (that is, higher than 4.3 percent). afS = agrifood system. aggdp+ = agrifo