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ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Currency Equivalents Exchange Rate Effective as of June 15, 2022 Currency Unit = Br (Ethiopian birr) Br 51.45 = US$1.00 Fiscal Year = July to June Acronyms and Abbreviations ACRONYMS DEFINITION AFE Adult Female Equivalent AFS Agri-food Systems AGP Agriculture Growth Project ATI Agricultural Transformation Institute ATT Average Treatment Effect on the Treated CEM Country Economic Memorandum CHIRPS Climate Hazards Group InfraRed Precipitations with Stations COMTRADE Common Format for Transient Data Exchange CSA Central Statistics Agency CSES Cambodia Socio-economic Survey ECHO European Civil Protection and Humanitarian Aid Operations EIAR Ethiopia Institute of Agriculture Trade ESS Ethiopian Socioeconomic Survey ETB Ethiopian Birr FAO Food and Agriculture Organization of the United Nations FAOSTAT Food and Agriculture Organization Corporate Statistical Database FEWS NET Famine Early Warning Systems Network GAEZ Global Agro-Ecological Zoning GAVCs Global Agricultural Value Chains GDP Gross Domestic Product GPWv4 Gridded Population of World Version 4 GTAP Global Trade Analysis Project GVCs Global Value Chains HBS Household Budget Survey HFPS High-Frequency Phone Survey IPC Integrated Food Security Phase Classification KIHBS Kenya Integrated Household Budget Survey LFS Labor Force Survey LMMIS Large- and Medium-sized Manufacturing Industries Survey LSMS-ISA Living Standards Measurement Study - Integrated Surveys on Agriculture iv ACRONYMS AND ABBREVIATIONS MAT Multiple Agriculture Technologies MPSE Mobile Populations Survey for Ethiopia MSME Micro, Small, and Medium Enterprise NPS National Panel Survey - Tanzania OCHA Office for the Coordination of Humanitarian Affairs OECD Organization for Economic Co-operation and Development PPP Purchasing Power Parity PSI Policy Studies Institute RID Rural Income Diagnostics RuLIS Rural Livelihoods Information System SME Small and Micro Enterprise SNNP Southern Nations, Nationalities, and People's SOE State Owned Enterprise TLU Total Livestock Unit UNCTAD United Nations Conference on Trade and Development UNCTAD-TRAINS United Nations Conference on Trade and Development – Trade Analysis Information System UNICEF United Nations International Children's Emergency Fund, now officially United Nations Children's Fund UNPS Uganda National Panel Survey VHLSS Vietnam Household Living Standards Survey WDI World Development Indicators WDP WorldPop Spatial Distribution of Population WFP World Food Programme WITS World Integrated Trade Solution Regional Vice President Hafez M. H. Ghanem Country Director Ousmane Dione Senior Practice Director Carolina Sanchez-Paramo Practice Managers Benu Bidani, Holder A. Kray, Pierella Paci Task Team Leaders Obert Pimhidzai, Easther Chigumira v ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Acknowledgements This Rural Income Diagnostics (RID) study for Determinants of land use choices and their Ethiopia was prepared through collaboration impacts on household welfare; Agriculture between the Poverty and Equity Global Practice price supply response in Ethiopia; and the Agriculture and Food Global Practice. It is one of series of Rural Income Diagnostics studies • Misrak Aklilu Asfaw (Consultant, EAEPV) – Nutrition prepared with financial support from the Bill and and transition of the agri-food system; and Melinda Gates Foundation (BMGF). • Rutta Firdissa (Consultant, EAEPV) – Analysis of The report was prepared by Obert Pimhidzai (Senior coffee, sesame, wheat, beef and onion value Economist, EAEPV), Easther Chigumira (Senior chains in Ethiopia. Agriculture Specialist, SAEA3), Wondimagegn Mesfin Tesfaye, (Economist, EAEPV) and Manex The report benefited from inputs and guidance Bule Yonis (Survey Specialist), DECPM, and edited from the Government of the Federal Democratic by Peter Kjaer Milne (Consultant). The report draws Republic of Ethiopia (FDRE), led by Dr Mandefro from background papers commissioned for the (Chief Executive Officer, Agriculture Transformation study. These background papers were authored by: Institute, ATI) and participants of the roundtable discussion held on April 20, 2022, with special • Wondimagegn Mesfin Tesfaye (Economist, EAEPV) thanks to Techane Adugna (Director of Agriculture – Distributional impacts of urbanization and Commercialization Clusters, ATI) and Dr dietary transformation; Rural demand for non- Dagnachew Lule (Senior Director of Agriculture food products and agriculture servives; Commercialization Clusters, ATI) for their additional comments and inputs. The team also benefited • Gebrelibanos Gebremariam (Consultant, EAEPV) from feedback from peer reviewers: Elliot W. – Impact of multiple technology adoption on Mghenyi (Lead Agriculture Economist, SAEA3), land productivity and farm incomes; and crop Andrew L. Dabalen (Practice Manager, ESAPV), yield analysis; Tom Bundervoet (Senior Economist, EECPV), Nga Thi Viet Nguyen (Senior Economist, EECPV) and • Kaleab Kebede Haile (Consultant, EAEPV) – Impact Kenneth Simler (Formerly Senior Economist, of market participation on households’ welfare; EEAPV) and other Word Bank staff involved in team consultations – Christina Wieser; Berhe Mekonnen • Laketch Mikael (Consultant, EAEPV) – Evolution of Beyene (EAEPV); Assaye Legesse, Biruktayet Assefa policy reforms in Ethiopia’s agriculture sector; Betremariam (SAEA3); Selamawit Hailemichael Tumebo (IFC); and Marius Vismantas (Program • Manex Bule Yonis (Survey Specialist, DECPM) Leader, EAEDR). The team is grateful to Maria – Effects of migration on factor markets in Eugenia Genoni – (Senior Economist, EMNPV) and migrants’ origin communities; Alan Rennison (BMGF) for their continous feedback throughout the process of the RID preparation. • Obert Pimhidzai (Senior Economist, EAEPV) and Mike Nyawo (Economist, ETIRI) – Determinants The report was prepared with guidance from Benu non-farm participation in rural Ethiopia – a Bidani (Practice Manager, EPVGE), Pierella Paci household farm production model approach; (Practice Manager, EAEPV), Holger A. Kray (Practice Manager, SAEA3), and Elliot Mghenyi (Lead • Tawanda Chingozha (Consultant, EAEPV) – Agriculture Specialist, SAEA3). vi CONTENTS Contents Currency Equivalents ....................................................................................................................................................................................... iv Acronyms and Abbreviations ....................................................................................................................................................................... iv Acknowledgements .......................................................................................................................................................................................... vi Executive Summary .......................................................................................................................................................................................... xii INTRODUCTION ....................................................................................................................................................................................... 1 Background .......................................................................................................................................................................................... 2 Approach in the Rural Income Diagnostics ...................................................................................................................... 3 Report outline ...................................................................................................................................................................................... 6 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE ... 9 Poverty and distribution of the poor ...................................................................................................................................... 10 Household livelihoods .................................................................................................................................................................... 17 Household endowments ................................................................................................................................................................ 24 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES .... 30 The technological transformation in agriculture production ............................................................................... 33 The rise of urban consumption and the dietary transformation ........................................................................ 39 Growth in global agri-food trade ............................................................................................................................................ 47 Spatial and economic transformation .................................................................................................................................. 53 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES ..... 59 Increasing the market orientation of rural agricultural households ............................................................... 60 Livelihood diversification into off-farm activities in the agri-food system and beyond .................... 74 Enhancing opportunities through labor mobility ......................................................................................................... 86 PRIORITIES FOR INCREASING HOUSEHOLD INCOME ..................................................................................... 91 Strategic focus areas for increasing rural incomes ................................................................................................... 92 Impact of different policy interventions on different segments of the rural society ........................... 96 Evolution and feasibility of policies supporting rural incomes .......................................................................... 100 Priority policies .................................................................................................................................................................................. 105 References............................................................................................................................................................................................. 111 LIST OF MAPS Map 1: Agricultural productivity by crops and zone ................................................................................................................ 99 LIST OF FIGURES Figure 1. Poverty pathways and income growth for rural households ...................................................................... 2 Figure 2. Sectoral GDP growth rates, 2016–21 ..................................................................................................................... 11 vii ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Figure 3. Sectoral employment composition, 2005–21 .................................................................................................... 11 Figure 4. Share of rural households reporting loss in incomes (%), April–October 2020 ............................ 11 Figure 5. Inflation, year-on-year (%), 2016-22 ......................................................................................................................... 14 Figure 6. Monthly food inflation, (percent change), 2019 - 22 ........................................................................................ 14 Figure 7. Net buyer ratio (NBR) by food commodities and welfare quintiles ........................................................ 15 Figure 8. Trends in rural incomes by income source, 2012–19 (Ethiopian birr, 2019 prices) ..................... 17 Figure 9. Trends in rural incomes by income source and welfare status, 2012–19 (Ethiopian birr, 2019 prices) ............................................................................................................................................................................ 17 Figure 10. Share of total income by source, 2012–19 ............................................................................................................. 18 Figure 11. Income shares by quintiles, 2019 .............................................................................................................................. 20 Figure 12. Rural income composition by gender of household head, 2019 .............................................................. 22 Figure 13. Rural income composition by age of household head, 2019 ..................................................................... 22 Figure 14. Income composition by education status, 2019 ................................................................................................. 23 Figure 15. Population distribution by education attainment (%), 2021 ........................................................................ 24 Figure 16. Nutrition outcomes of under five years old rural children (%), 2019 .................................................... 24 Figure 17. Prevalence of undernourishment (modeled value, %) ................................................................................... 25 Figure 18. Average landholdings (ha) by quintile, 2019 ........................................................................................................ 25 Figure 19. Average landholding (ha) and caloric production potential (kcal) by welfare quintile, 2019 ..... 25 Figure 20. Livestock population distribution by regions (in TLUs), 2022 .................................................................... 26 Figure 21. Average livestock holdings by welfare quintile (TLU), 2022 ....................................................................... 26 Figure 22. Distance to the nearest financial institution by institution type and welfare quintile (km), 2019 ..... 27 Figure 23 Access to electricity, roads and urban centers (%), 2019 ........................................................................... 28 Figure 24. Distance to markets by quintile (km), 2019 ........................................................................................................... 28 Figure 25. Mobile phone ownership in rural Ethiopia, 2012–19 ...................................................................................... 29 Figure 26. Mobile phone ownership by rural quintiles, 2019 ............................................................................................ 29 Figure 27. Agriculture value added and contribution to employment and GDP, 2000–20 ............................... 31 Figure 28. Evolution of jobs in the agri-food system .............................................................................................................. 33 Figure 29. Marketed input utilization (% of farmers) over time and welfare status and land size ............. 33 Figure 30. Maize yields (kg/ha), 2000-20 ...................................................................................................................................... 34 Figure 31. Coffee yields (kg/ha), 2000-20 ..................................................................................................................................... 35 Figure 32. Multiple agriculture technology (MAT) adoption (% of plots), 2019 ....................................................... 36 Figure 33. Supply source of modern inputs in Ethiopia (% of households), 2019 ................................................. 37 Figure 34. Trends in urban population growth, 2004-21 ...................................................................................................... 39 Figure 35. Share of imports in total food supply (%), 2015-18 ......................................................................................... 43 Figure 36. Changes in jobs in the agri-food system in rural areas (‘000), 2013–21 ............................................ 45 Figure 37. Share of agri-food system in GDP, 2010-40 ......................................................................................................... 45 Figure 38. Trends in global agriculture (US$), 2010-19 ........................................................................................................ 47 viii CONTENTS Figure 39. Global food trade – key commodities (US$ million), 2010-19 ................................................................... 47 Figure 40. Ethiopia’s food trade – key commodities (US$ million), 2010-19 ............................................................ 48 Figure 41. Production index trends (base year = 2015), 2000-20 .................................................................................. 48 Figure 42. Share of net exports relative to production for selected crops, 2011-18 ........................................... 48 Figure 43. Ethiopia market share in the top 10 markets, 2011-19 (%), 2011-19 ................................................... 49 Figure 44. Arabica coffee processing method among African exporters (%), 2017 ............................................. 49 Figure 45. Revealed comparative trade in goods, 2015 ....................................................................................................... 50 Figure 46. Share of services value in exports, 2015 ............................................................................................................... 50 Figure 47. Number of non-tariff measures, 2017 .................................................................................................................... 51 Figure 48. Food and beverage tariffs (%) ...................................................................................................................................... 51 Figure 49. Number of workers and firms in the manufacturing sector in Ethiopia, 2000–17 ....................... 53 Figure 50. Comparison of Ethiopian firms’ metrics by export status, 2017............................................................... 53 Figure 51. Migration flows: the number of recent migrants, 2005–21 ........................................................................ 54 Figure 52. Education status of recent migrants, 2021 ........................................................................................................... 54 Figure 53. Reason for migration among rural-urban migrants, 2021 ........................................................................... 55 Figure 54. Trends in household land ownership (ha), 2006–20 ....................................................................................... 56 Figure 55. Food item share in household consumption (%) , 2019 .................................................................................. 61 Figure 56. Impacts of commercialization on consumption per capita, 2019 ........................................................... 62 Figure 57. Rural households market orientation ..................................................................................................................... 63 Figure 58. Share of cultivated land by crop and income group (%), 2019 .................................................................. 64 Figure 59. Share of land allocated to cash crops by ecological zones (%), 2019 ................................................... 64 Figure 60. Land allocation across crops by land ownership (% of area cultivated), 2019 ................................ 66 Figure 61. Share of land allocated to cash crops by land fertility, 2019 ..................................................................... 66 Figure 62. Rural connectivity and market participation, 2019 .......................................................................................... 67 Figure 63. Food price variation and market access, 2019 ................................................................................................... 67 Figure 64. Share of area under maize cultivation and maize price variation .......................................................... 68 Figure 65. Commercialization index (CI) and maize price variation................................................................................ 68 Figure 66. Predicted margins of commercialization index by connectivity .............................................................. 68 Figure 67. Rural households’ distribution by marketable surplus range, 2019 ..................................................... 69 Figure 68. Marketed output as share of production by land productivity, 2019 ..................................................... 69 Figure 69. Teff and maize surplus availability and commercialization index (CI) .................................................. 70 Figure 70. Maize and wheat price parity, (US$ ‘000) ............................................................................................................... 71 Figure 71. Nominal rates of protection at the farmgate, 2017 ......................................................................................... 71 Figure 72. Average household incomes (Ethiopian birr) by consumption quintile and income source, 2019 ... 74 Figure 73. Comparison of rural employment composition, 2018/19 ............................................................................ 75 Figure 74. Comparison of household participation and contribution of income sources (%), 2018/19 ... 75 Figure 75. Average wages by level of education, 2021.......................................................................................................... 76 Figure 76. Per capita non-food spending by market source, (Ethiopian Birr, 2016 prices) ............................. 77 Figure 77. Sectoral employment shares (%) and woreda population density, 2019 ............................................ 78 ix ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Figure 78. Rural off-farm job prospects and population density, 2019 ........................................................................ 78 Figure 79. Off-farm job participation by local maize prices relative to Addis Ababa, 2019 .............................. 82 Figure 80. Off-farm job participation by local teff prices relative to Addis Ababa, 2019 .................................... 82 Figure 81. Probability of non-farm employment (%) by staple food production status, 2019 ....................... 82 Figure 82. Probability of non-farm employment (%) by gender and age, 2019 ...................................................... 83 Figure 83. Probability of non-farm employment (%) by gender, age, and secondary education attainment, 2019 .................................................................................................................................................................. 83 Figure 84. Predicted probability of non-farm employment and market access index, 2019 ......................... 84 Figure 85. Non-farm employment prospects (%) and proximity to towns with populations between 20,000 and 50,000 people, 2019 ................................................................................................................................. 84 Figure 86. Probability of non-farm employment by secondary education attainment and population density, 2019 ........................................................................................................................................................................... 85 Figure 87. Comparison of migration flows by region, 2013 and 2021 .......................................................................... 86 Figure 88. The flow of migrants: 2008–21 .................................................................................................................................... 86 Figure 89. Size of remittance income relative to total consumption for the receivers (%), 2012-2016 ... 87 Figure 90. Marginal effects of determinants of migration .................................................................................................. 87 Figure 91. The change in probability of having a migrant by household members’ average years of education ... 88 Figure 92. The share of households with and without a migrant, by rural quantile pre-migration and post-migration ....................................................................................................................................................................... 88 Figure 93. Hourly wages and weekly hours worked by rural and urban residents, 2019 ................................ 89 Figure 94. Composition of agriculture and rural development expenditures, 2009–18* ................................... 100 LIST OF TABLES Table 1. Description of data sources for rural income diagnostics analysis ...................................................... 5 Table 2. Household distribution by crop market position and welfare quintile, 2019 .................................... 15 Table 3. Price elasticities of demand of major cereals, 2019 ....................................................................................... 16 Table 4. A typology of rural households by type of livelihoods, 2012-19 .............................................................. 19 Table 5. Income diversification patterns by landholding classes, 2019 ................................................................. 21 Table 6. Income diversification patterns by agro-ecological zone, 2019 ............................................................... 21 Table 7. Land ownership by gender, 2019 ............................................................................................................................... 26 Table 8. Use of improved varieties by crop (%), 2021 ....................................................................................................... 35 Table 9. Impact of MAT adoption on land productivity and net crop income, 2019 .......................................... 36 Table 10. Changes in food consumption spending patterns (food budget share), 2014–19 ......................... 39 Table 11. Forecast change in demand at the farm level (US$ ‘000) ............................................................................ 40 Table 12. Urban households income elasticity of demand .............................................................................................. 41 Table 13. Households’ participation in production and marketing of food with high urban demand, 2019 ..... 43 Table 14. Evolution of job structure in East and Southern Africa, 2010–25 ........................................................... 44 Table 15. Jobs in the agri-food system, 2021 ............................................................................................................................ 45 Table 16. Labor market outcomes of migrants, 2021 .......................................................................................................... 55 x CONTENTS Table 17. Impact of migration on factor markets in origin communities ................................................................. 56 Table 18. Relationship between crop commercialization and nutritional outcomes of households .......... 62 Table 19. Relationship between land suitability and crop ................................................................................................. 65 Table 20. Rural household annual income sources by quintile, 2019 ....................................................................... 76 Table 21. Net job creation in rural areas in Ethiopia, 2013–21 ......................................................................................... 76 Table 22. Probability of engaging in non-farm work and land ownership ................................................................. 81 Table 23. Job creation in the Ethiopia Agriculture Growth Project, 2015–2020 ..................................................... 84 Table 24. Probability of having a migrant and household access to credit and cash transfers ..................... 89 Table 25. Taxonomy of rural households in Ethiopia .............................................................................................................. 96 Table 26. Short-term priority intervention areas for increasing rural incomes ..................................................... 109 Table 27. Medium-term priority intervention areas for increasing rural incomes ............................................... 110 LIST OF BOXES Box 1. Estimation of own- and cross-price elasticities ...................................................................................................... 16 Box 2. Estimation of yield potential in Ethiopia using the stochastic frontier technique ................................ 35 Box 3. Estimation of the impact of MAT on land productivity and crop incomes in Ethiopia ........................ 37 Box 4. Estimation of income elasticities of demand ............................................................................................................. 42 Box 5. Estimation of the impacts of migration on factor markets ................................................................................. 57 Box 6. Estimation of determinants of market participation and its impacts on household welfare ....... 62 Box 7. Estimation of determinants of land use choices among rural smallholder farmers in Ethiopia ..... 65 Box 8. Agriculture Commercialization Cluster Project ........................................................................................................ 72 Box 9. Estimation of intra-household non-farm participation in rural Ethiopia ................................................... 79 xi ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Executive Summary Rural households experienced weaker growth at the recent past. Since 2020, households in Ethiopia onset of the decade and now multiple shocks at the end have had to contend with the COVID-19 pandemic, of the decade threaten to undo their marginal gains. climate change-induced droughts, pests and diseases, and conflict within the country and, Ethiopia began the decade on a great run, with more recently, the fallout from the Russia-Ukraine high economic growth and significant gains in war. The combination of these 3Cs—COVID-19, poverty reduction nationally. But the gains were climate change, and conflict—have left no part of unevenly shared. Earlier studies show that growth the country untouched. As conflict exploded in the in per capita consumption midway through the past northern parts of Ethiopia, driving 5.5 million people decade was five times faster in urban areas than into hunger as of June 2021, prolonged droughts in rural areas, where households’ consumption were wreaking havoc in lowland areas, affecting growth per capita grew by only 6 percent in total 7 million people, and a locust invasion caused during 2011–16, while the GDP per capita grew cereal losses of more than 3.5 million quintals, cumulatively by 39 percent in the same period. affecting more than 806,000 farming households. The poorest 20 percent of rural households, at Meanwhile, the effects of the COVID-19 pandemic best, did not experience any growth. Continued were felt everywhere, including rural areas where growth in the second half of the decade, averaging poverty is projected to have increased by more than 5.3 percent per year during 2016–21, should have 9 percentage points in 2020 compared with 2019. seen greater poverty reduction, but instead poverty Inflation has also been high, averaging 34 percent reduction is expected to have followed the same year-on-year between March 2021 and March uneven pattern, given that the economic growth 2022. While some net producers benefited, there model remained unchanged. are more households, especially the poor, who are net consumers with limited options for substitution Multiple shocks at the beginning of the new between food items. The increase in maize and decade threaten to discontinue progress and sorghum prices reduced welfare by as much as 10 possibly undo most of the gains made in the percent among rural households. xii EXECUTIVE SUMMARY Being primarily subsistence agriculture-based, rural by: (i) technology adoption in agriculture production; households have not been connected to the rest of and (ii) growing urban populations and incomes, and the economy the resultant dietary transformation, presents direct opportunities for expanding agricultural incomes, Being primarily subsistence-oriented, with low while at the same time creating income-generating education and disconnected from markets, rural opportunities in the non-farm segments of the food households have not been fully integrated into the system. The changing patterns in global trade, modern, faster-growing segments of the economy. specifically (iii) growth in global agri-food trade; and Despite some encouraging signs, the transition in the broader (iv) spatial and economic transformation the rural economy has been slow compared with in Ethiopia as it integrates into global value chains Ethiopia’s regional peers, Kenya, Uganda, and through expansion of urban based export-oriented Tanzania, and when compared with international industries, will create additional opportunities for comparators such as Vietnam and Cambodia, rural households, both on the farm and off the farm. whose economies were once predominantly agricultural, but have since undergone significant Technological transformation in agriculture transformation in the past two decades. The rural population in Ethiopia remains predominantly Advances have been made on the adoption of dependent on subsistence agriculture, which made advanced inputs in Ethiopia, signifying the start up three-quarters of rural incomes in 2019 and of technological transformation in agricultural employed 77.5 percent of the rural workers in 2021. production that has improved yields. The share of In contrast, agriculture contributed less than 40 households applying inorganic fertilizers increased percent of rural incomes in Cambodia in 2019 and from 49 percent in 2012 to 63 percent in 2019, for Vietnam in 2018, and around 59 percent in Uganda example, and that of households using improved in 2019. Consequently, rural households in Ethiopia seeds increased from 20 to 33 percent. However, have less diversified and more subsistence- other technologies, such as mechanization and oriented livelihoods. The low education levels irrigation, remain inaccessible and little used, with 9 among rural workers—with four out of five rural percent and less than 2 percent of rural households adults in 2021 either having never been to school irrigating and mechanizing their plots, respectively. or having dropped out of primary education at Mechanization has, however, taken off among best—has lowered both productivity in agriculture wheat farmers in the southwest regions of Ethiopia, and access to off-farm opportunities, which were with the use of combine harvesters. The adoption already limited by low market access due to poor of fertilizers and improved seeds has improved connectivity and low population density. productivity by at least 13 percentage points since 2012, placing Ethiopia’s cereals yields above its But structural transformation in the agri-food system regional peers but still lower than international and the broader economy along with changes in comparators. Gains from mechanization are evident global trade present opportunities for expanding in the wheat-producing areas. both on- and off-farm rural incomes. Despite these vulnerabilities, other economic The share of households applying inorganic developments point to greater opportunities for fertilizers increased from expanding rural incomes. The study identified four key drivers of rural income growth opportunities, 49% IN 2012 TO 63% IN 2019 rooted in the transformation path that the country is set upon and changes in global trade. The structural transformation in the agri-food system, driven xiii ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY There is considerable scope for increasing adoption, together with low access to credit, small technology adoption to further improve yields and and fragmented farm sizes, poor connectivity to create jobs in agriculture services. Despite the noted markets, and the disincentive effects that climate improvements and better performance than regional shocks have on the adoption of risky technologies. peers, yields have not reached their potential levels because the adoption of technology remains low. The rise in the urban population and dietary transitions The recent improvements in technology adoption started from such a low base that improved seeds Increased food demand and dietary transformation and inorganic fertilizers covered only 13 percent driven by urbanization and rising incomes will be of cultivated land in 2019. In addition, agriculture an important driver of rural income growth. The technologies have been adopted in isolation instead urban population grew by nearly 60 percent from of being applied together on the same plots to 2010 to nearly 23 million in 2021 and is expected maximize complementarities. On only 6 percent of to rise to 31 million by 2025. Moreover, urban the plots were improved seeds, inorganic fertilizer, households have experienced faster income growth, and soil and water conservation technologies applied resulting in high growth in food consumption. together, even though evidence suggests that their Combined with urban population growth, total joint application would double land productivity urban food consumption would have doubled in relative to the use of inorganic fertilizer alone, or those five years. These factors have contributed to increase land productivity by 45 percent more than a dietary transition as urban households in Ethiopia using improved seeds alone. Further productivity spend a higher share of their budget on teff, gains can be achieved through increasing irrigation vegetables and meat & fish, and processed foods, coverage and farm mechanization. Increased and significantly less on other cereals, especially technology adoption, including mechanization and maize. Their consumption is heavily skewed irrigation, would also create jobs in input production toward commodities with high income elasticities, and distribution, as well as agriculture services, suggesting greater potential for growth in demand such as extension services and equipment sharing, for some commodities but less so for others. The renting and repairs. Restrictions in input markets annual demand for teff, wheat, pulses and nuts, (e.g., control of the fertilizer supply chain and profit vegetables, meat and dairy products is expected to margins for improved seed varieties) have reduced increase by more than US$1.6 billion, mostly due to private sector participation, resulting in suboptimal rising teff, wheat and diary demand, while demand input supply. This has constrained technology for maize is expected to decline. xiv EXECUTIVE SUMMARY Rising urban food demand, being more reliant on wet processing, which commands a premium but markets and with higher shares of processed or only accounts for one-third of exports, unlike in packaged foods, has triggered a transition that Kenya where it accounts for 89 percent of coffee is creating jobs in the non-farm segments of exports. The second export crop, sesame oilseed, the food system. Beyond jobs created in bringing is produced by 1 million households, and has the and marketing produce to urban consumers, potential to expand if yields are improved. Ethiopia opportunities will also expand in food processing, is also catching up in high growth global agriculture packaging, marketing, and food preparation and exports commodities, such as meat and beans, retail. Initially, most of these activities will be in which are produced by smallholder farmers too, the small-scale segments of the non-food system, and have further room to expand as current exports with long and fragmented value chains that can are only a small fraction of production (e.g., only 2 present opportunities for rural Micro, Small and percent of production for meat). Maize farmers Medium Scale Enterprises (MSMEs). Recent could have benefited from growth in trade but have trends suggest the rise in urban food demand has missed out due to export controls. The shift from begun to expand job opportunities beyond primary livestock to meat exports also shows the potential agricultural production. For example, since 2013, of value addition, which could create jobs in the total employment in food manufacturing, food packaging and processing segments, provided preparation, and marketing and transport has more the right infrastructure (e.g., cold chains) and food than doubled. More of these jobs will be created safety standards are put in place. Value addition as the share of downstream segments in the food in the services segments of the agriculture value system GDP rises to close to 30 percent by 2040. chain will both create jobs and increase farmers’ Similar trends are expected regionally. However, returns too. realizing more of these gains in Ethiopia could be constrained by a challenging business environment, Spatial and economic transformation due to regulations that increase barriers to entry (especially the trading sector which can catalyze The expansion of urban based export industries value chain development but is currently closed to has generated jobs mostly filled by rural-urban foreign ownership) and the cost of doing business, migrants. Export-oriented firms, whose number inadequate infrastructure, and low access to finance. has been rising, have created more jobs per firm on average, which are mostly filled by migrants, Growth in global agri-food trade as surveys at industrial parks across the country show. About 70 percent of workers in Bole-Lemi Global agri-food trade has been on the rise Industrial Park and 52 percent of workers in and rural households in Ethiopia are primed to Hawassa Industrial Park, for example, are migrants. benefit. Global agriculture trade is estimated to With rural areas a source of labor for urban based have doubled in nominal terms between 2004 and industries, migration becomes an important 2014, which continued to expand until the COVID-19 pathway for access to employment and connecting pandemic struck. Rural households in Ethiopia rural areas to the broader economy. Close to 2 are primed to benefit, being more integrated into million people, representing one-third of all recent global agriculture value chains with high growth migrants, moved from rural to urban areas during potential or shifting into premium production. 2016–21. Rural-urban migrants tend to be younger, Coffee, the country’s top export, already supports with an average age of 27 years, and have better the livelihoods of close to 20 million people. Its education. Close to half have at least completed export revenues have stagnated, and its market primary school, with 18 percent having completed share has been declining in recent years. But secondary or post-secondary education. Most adult with the right market incentives, farmers could rural-urban migrants—about 54 percent (and two- still gain from increasing yields and switching to thirds among females)—migrated for economic xv ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY reasons, with reasonable success in finding and greater involvement in the global value jobs in their destination areas. The rural-urban chains (GVCs). First, rural households in Ethiopia migrants are as equally likely to be economically could expand agricultural incomes by becoming active, employed and in non-agricultural work more market-oriented in their production, taking as urban residents, but more likely to be in wage advantage of rising urban food demand and the employment, though a disproportionate share (17 global agri-food trade. Second, rural households percent) is engaged in domestic wage work. could diversify their livelihoods by taking advantage of opportunities created during the transition in With a rising rural population, rural-urban the food system and beyond. Third, expanding migration, and urban development, are essential incomes through increased rural-urban mobility to for facilitating rural economic transformation. The take advantage of the job opportunities as Ethiopia rural population expanded by more than 20 million integrates more into GVCs. people since 2004. It will keep expanding given the high fertility rate in rural areas, which will increase Increasing market orientation of smallholder farmers the pressure on land. The average land size per household has already declined from 1.25ha in 2006 Increasing the market orientation of smallholder to 0.89ha in 2020 for example. Migration eases the farmers improves welfare but is hampered by land pressure and catalyzes rural transformation the inherent need to attain self-sufficiency, low through two primary channels. First, it improves productivity, and high exposure to shocks. A labor productivity in origin communities and helps percentage increase in the share of output sold remaining household members feed off their land. increases rural households’ per capita consumption In Ethiopia for example, rural-urban migration by 11 percent, on average, and by more among during 2012–15 has increased the intensity of the poor. Nutrition outcomes improve with market family labor use and output per worker in migrant participation too. However, factors that incentivize origin households compared with non-migrant smallholder farmers to be food self-sufficient— households by 28.6 and 18.3 percent, respectively. market isolation and high food prices—have This implies that migration reduces disguised suppressed households’ market participation in unemployment in rural areas. Second, migration Ethiopia. Households in remote areas, facing high increased the share of land rented out by 6.6 percent transaction costs and frequent climate -related among migrant households relative to non-migrant shocks inducing higher price volatility, are more households. Thus, it increases the efficiency of the inclined to produce for own consumption instead rental markets too. In addition, migration is a coping of engaging in market-oriented production. Land mechanism for drought-related shocks and helps use choices are therefore geared toward the to improve households’ resilience. Impoverishment production of staples commonly consumed in rates—the likelihood of falling into poverty—were rural areas. Government interventions, especially 7 percentage points lower among households with agriculture extension services, have been biased a migrant during 2011–16 compared with similar toward increasing cereals production too, given the households without a migrant. country’s history of food insecurity. Most smallholder farmers also do not generate enough of a surplus Increased smallholder farmers’ market orientation, to sell due to low productivity and the impact of diversification into non-farm segments of the food climate shocks, which discourages households system and rural-urban migration, leverages these from selling their surplus and encourages them opportunities to expand rural incomes. to hold larger buffer stocks instead. Fostering market integration, improving land productivity, Three pathways are identified for expanding rural strengthening household resilience to shocks and incomes by leveraging opportunities presented risk mitigation are therefore foundational pillars for in the transformation of the agri-food system increasing market orientation of smallholder farms. xvi EXECUTIVE SUMMARY and women are similar, but primary educated men face better prospects than women with a similar background. Low market integration encourages households to focus on agricultural production. For example, net food consumers of both maize and teff tend to engage less in non-agriculture activities the higher the staple food prices in local markets relative to the price in Addis Ababa. With low density a key limiting factor, the development of the agri- food system holds potential for generating off-farm jobs in rural Ethiopia. It taps into external demand from urbanization and the global food trade, the supply chains of which are long and fragmented during the transition stage and hence dominated by MSMEs. The more than 500,000 jobs and nearly 300,000 jobs created under the marketing and agriculture support components of the AGP project, respectively, is evidence of this potential. Rural-urban migration With low economic density limiting access to local economic opportunities, rural-urban migration is an alternative pathway for improving access to better income-generating opportunities. In Ethiopia, remittances from urban migrants were equivalent to one-third of receiving households’ Promoting livelihood diversification through development consumption per capita in 2016, and more than of the agri-food system double that among the poorest quintiles. Rural urban migration is, however, constrained by non- Livelihood diversification is low in Ethiopia wage factors making integration in destination due to a combination of low rural non-farm job areas more difficult for migrants. The high cost of creation and households’ lack of education, migration is a barrier to migration. Migrants find the gender biases and the prioritization of meeting job search process more difficult, which increases subsistence needs. Rural off-farm opportunities the job search costs, and they face administrative are mostly created in the services sector, which barriers to obtain kebele IDs, inhibiting their access requires higher populations to thrive. The sparse to government services. Many typically find the population in rural areas in Ethiopia, combined with transition to urban life difficult, and females face low non-food market spending, result in limited additional challenges. Connecting migrants to local demand and constrained job creation. Job jobs and services would facilitate the labor shift prospects are found to continuously improve with into off-farm jobs in urban areas and increase increasing rural population density. Low skills and the flow of remittances to rural households. More gender biases compound the low availability of fundamentally, urban development to enhance the non-farm opportunities. The off-farm job prospects urban pull factor and adapt urban areas to rising of people with secondary education are more than populations, is essential for both the integration double the prospects of primary educated people, of migrants and relieving the impacts of urban for example. Prospects of secondary educated men population growth on infrastructure and services. xvii ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Priorities for realizing opportunities should focus on are low adoption of multiple agriculture technologies, five critical areas with the greatest impact on the exposure to climate-induced shocks and hoarding of poor and high implementation feasibility surpluses to cope with climate shocks. The critical interventions are those that promote the adoption of To expand opportunities for rural households multiple agriculture technologies, such as extension and increase their incomes, policy interventions services provision, promoting access and use of should promote a shift toward market orientation climate smart agriculture technologies, including among smallholder farmers, create opportunities expanding irrigation and conservation agriculture, for livelihood diversification and reduce barriers improving access to credit and liberalizing input for rural labor mobility. Interventions to achieve markets to increase supply. these should focus on reducing constraints in the following five key areas: iii. Overcoming the disadvantage of low economic density in remote, sparsely populated areas i. Changing incentives for households to produce for the market A major reason behind the lack of non-farm opportunities in rural areas is the lack of demand Increasing the market orientation of smallholder due to a small internal market, compounded by farmers is centered on shifting their land use choices the under development of agriculture value chains away from self-sufficiency-driven production partly due to restrictions in investment in the decisions to market demand-driven production trading sector, leading to fewer and smaller rural choices. The key factors affecting the incentives enterprises, and hence fewer jobs created. Rural faced by households that are identified in our analysis enterprises in these circumstances can only thrive by are: (i) market isolation, which requires improving serving external markets. This requires addressing rural connectivity; (ii) risks to shocks from climate the challenges of: (i) low market access, which calls change and price volatility, which can be addressed for increasing rural connectivity; (ii) low linkages with through the adoption of climate smart agriculture prospective customers, which requires investments technologies in combination with better connectivity; in improving digital connectivity, logistical services (ii) depressed returns due to state intervention in for supply and delivery to customers and suppliers, output markets, making the elimination of export and the construction of markets and other controls particularly critical; (iii) high transaction supporting infrastructure, such as warehouses and costs, which can be reduced by improving market cold storage, through private sector participation; linkages to minimize aggregation costs and improve (iii) high entry barriers in the trading sector, which information flow; and (iv) a bias in extension services calls for removal of restrictions of foreign ownership provision toward cereals production, thus calling for in the trading sector, to attract investment by firms revamping extension services provision to facilitate with knowledge and the incentive to reorganize private sector extension services provision and agriculture value chains. orient public extension services toward providing market-oriented advice. iv. Promoting rural enterprise development in the non- food segments of the food system ii. Increasing agriculture surplus generation and availability The development of rural enterprises is important Farmers, especially cereal producers, need to for off-farm rural job creation. For rural areas, have surplus output to sell if they are to participate fulfilling rising demand for food and agriculture profitability in markets. Surpluses, especially for commodities in urban areas and globally is the cereals, need to be generated by increasing land source of external demand that can drive growth. productivity and preserved by minimizing losses. The Participation in the non-farm segments of these key constraints to surplus generation and availability agriculture value chain presents opportunities for xviii EXECUTIVE SUMMARY MSMEs in rural areas. Taking advantage of these registration. More importantly urban development opportunities requires addressing challenges with through investments in urban infrastructure, the business environment, namely: (i) the lack housing, social services, and urban based industries, of access to finance, which could be addressed can spur labor mobility by improving both access to through de-risking lending to the rural economy, opportunities and social services. and the provision of startup capital through matching grants and lines of credit, coupled with Interventions to increase rural incomes should technical assistance to lenders to improve credit focus on addressing constraints to achieve these risk assessment; (ii) barriers to entry and state five outcomes. In the context of ongoing government intervention across key nodes of the value chains, reforms targeting many of the constraints to which require market deregulation in agriculture achieving these outcomes, a set of priority areas input licensing, input pricing and maize price for interventions are proposed. These have been controls, and private participation in services selected by considering the impact of the constraints provision, such as infrastructure and market on the five outcomes and gender gaps, as well as development; and (iii) limited skills, which in the feasibility of solutions in terms of how difficult they short term can be addressed through supporting are to implement, government buy-in on the reforms vocational training for the rural youth and capacity and asymmetry of benefits. The identified top priority building for cooperatives and developing an areas are: ecosystem of business development services. In the longer term, investments facilitating transition 1. Addressing infrastructure gaps focused on to secondary education are required. connectivity, irrigation, land structures and supporting infrastructure. v. Reducing costs for rural urban migration and reinforcing the urban pull factors for migration 2. Private sector participation in the delivery of supporting infrastructure. Easing the process of integration of migrants in urban areas and expanding urban development is 3. Agriculture input deregulation to shift from important for reducing the cost of migration and government direct delivery of inputs to regulation, promoting mobility. Migration has both social and stopping pricing interference for inputs supplied economic costs that can be a deterrent to prospective by the public research system and reduce migrants. These costs are driven by: (i) frictions in the preferential treatment of cooperatives for job-matching process, which can make the job search agriculture technology multiplication. costly and unaffordable for those without savings to tap into; and (ii) barriers to access to services. 4. Output market deregulation, including the The first constraint can be addressed through elimination of grain export bans. measures that reduce job search costs by improving systems that facilitate matching of jobseekers to job 5. Market making by creating market linkages, vacancies, such as setting up an employment agency such as market information and liberalizing the and strengthening public employment services; and trading sector. helping jobseekers signal their skills, for example by expanding youth apprenticeship programs. The 6. Re-orienting extension services provision second constraint can be addressed by streamlining toward the delivery of more sophisticated, administrative procedures, the most important ones market-oriented messages and permitting a being minimizing the burden of the requirement to plurality of advisory service provision. obtain kebele IDs by reducing the minimum length of stay and removing the requirement for a release 7. Financial sector reforms to reduce credit letter; and streamlining ID reforms and household controls, preferential treatment, and xix ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY overreliance on government financing for investments for agriculture commercialization and farmer inputs. food system transformation, and how new approaches like the agriculture commercialization clusters being 8. Forex reforms to align the exchange rate and piloted in the country, provide a promising model for remove foreign currency controls. addressing multiple constraints faced by small holder farmers. It also elevates some reform areas, to signal 9. Improving natural resource governance and land importance of moving fast. Such areas include (i) administration, including eliminating restrictions speeding up market deregulation of agriculture input on land transactions and the transfer of user markets to attract private investment into agriculture rights to facilitate land consolidation. technology research and improve input supply to foster productivity and job creation, and (ii) increasing private 10. Relaxing constraints on the movement of labor sector participation in delivery of infrastructure and by streamlining the administrative process post-production nodes of agriculture value chains. The required for migrants to integrate into urban diagnostics also offers empirical arguments to support areas and by improving services that connect the need for reforms in areas where either consensus people to jobs. might be lacking or there is policy hesitation, such as elimination of grain export restrictions and foreign 11. Expanding urban investments in infrastructure, exchange rate alignment to improve price incentives housing, and social services to adapt urban for agriculture producers, opening up the trading sector areas to increasing population and reinforce for foreign investment to bring in investors with the the urban pull through expanding investments knowledge and scale in the retail and wholesale sector in urban-based industries. that can catalyze agriculture value chain reorganization and development, and that encouraging rural-urban 12. Addressing gender gaps in education and training migration facilitates agriculture transformation. and access to land, as well as norms around women’s occupations and roles within households. A summary of the priority constraints and interventions, along with their prioritization On these proposed areas, the diagnostics provides ranking are presented in the following two tables. an impetus for pushing ahead with reforms and The first table shows priorities for immediate consider other actions as well. It provides evidence implementation and the second table shows reinforcing the importance of rural infrastructure medium to long term priority areas. xx EXECUTIVE SUMMARY Short-term priority intervention areas for increasing rural incomes Constraint Pathway Priority Interventions Level Investment gaps Low rural • Market-oriented production High • Rural roads investments connectivity • Increasing economic density Limited access • Agriculture surplus generation Medium • Irrigation investments to irrigation Low access to • Agriculture surplus generation High • Investment in R&D for climate-smart agriculture climate-smart technologies agriculture • Incentives for on-farm private investments technologies Lack of logistical • Rural enterprise development High • Investments in modernized physical markets, cold infrastructure • Market-oriented production chains, warehouses and storage facilities Depleting natural • Agriculture surplus generation High • Land structures for protecting or rehabilitating resources eroding landscapes Market related constraints Input shortages • Agriculture surplus generation High • Liberalization of input markets and unavailability • Rural enterprise development Weak price • Market-oriented production High • Streamlining marketing restrictions incentives due to • Rural enterprise development • Revising the incentive structure to promote market distortions premium coffee production Low market • Market-oriented production Medium • Contract farming linkages • Market information systems • Direct support to farmer groups and SMEs Risk management • Agriculture surplus generation Low • Vegetation index-based insurance financial • Livestock based insurance instruments High job search • Reducing barriers to migration Medium • Employment intermediation services costs • Market-oriented production • Youth apprenticeships • Expand investments in urban based industries Capacity constraints Limited access to • Agriculture surplus generation High • Plurality of extension services complex, • Market-orientated production • ICT based advisory service delivery mechanisms market-focused, • Rural enterprise development • Retraining of extension services providers advisory services Low education • Reducing barriers to migration High • Gender-focused vocational training and skills • Market-oriented production Gender biases in • Rural enterprise development High • Gender representation in decision making intra-household • Market orientation structure & enterprise group formation labor allocation Policies and regulations Lack of access • Agriculture surplus generation Medium • Input voucher system to credit • Rural enterprise development • Elimination of credit controls and preferential • Reducing barriers to migration treatment Land fragmentation • Agriculture surplus generation High • Cluster approach limits technological • Develop equipment rental markets suitable for adoption small farm sizes Gender bias in • Market-orientated production Medium • Enforcing land co-titling land access xxi ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Medium-term priority intervention areas for increasing rural incomes Constraint Pathway Priority Interventions Level Investment gaps Low digital • Market-oriented production High • ICT infrastructure development connectivity • Increasing economic density Limited access • Agriculture surplus generation Medium • Rationalizing institutional arrangements to irrigation • Review regulations and legal provisions for water user charges to increase Distorted incentives • Agriculture surplus generation High • Improve natural resource governance and land for natural resource management systems management Poor access to • Reducing barriers to migration High • Urban infrastructure investments urban services deterring migration Market related constraints Weak price • Market-oriented production High • Elimination of export bans incentives due to market distortions Limited knowledge • Rural enterprise development High • Open trading sector to foreign ownership and private sector investment in value chain development Capacity constraints Low education • Reducing barriers to migration High • Fostering school progression, especially among girls and skills • Market-oriented production Policies and regulations Lack of access to • Rural enterprise development High • Strengthening financial institutions capacity for credit for credit assessment rural enterprises Exchange rate • Rural enterprise development Medium • Exchange rate unification misalignment • Market oriented production • Remove foreign exchange controls Burdensome • Reducing barriers to migration Medium • Reducing minimum stay requirements for administrative obtaining Kebele IDs procedures for IDs • Removing release letter requirement • Digital IDs Limited access • Reducing barriers to migration Medium • Expand public investment in urban infrastructure, to public services housing and services and housing for migrants Land fragmentation • Agriculture surplus generation Medium • Remove restrictions on land transactions and limitations to transfer of user rights mechanization Barriers to trade • Agriculture surplus generation Medium • Free trade agreements • Rural enterprise development • Strengthening capacity and enforcement of SPS xxii INTRODUCTION 1 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Background growth in rural incomes to accelerate poverty reduction. This is in support of the ongoing Identifying opportunities and constraints to reforms in agricultural and rural development increasing rural household income through policy, along with macroeconomic and structural three complementary pathways reforms proposed under the Homegrown Economic Reform Agenda (HGERA), the overall Ethiopia has experienced rapid economic growth goal of which is promoting job creation, inclusive over the past decade, but rural households have growth, poverty reduction and creating a benefited less from this growth than their urban path to prosperity. The RID achieves this by peers. Per capita GDP cumulatively increased by 39 characterizing livelihood strategies of rural percent during 2011–16, but average consumption households, and identifying opportunities and per capita in rural areas grew by only 6 percent, or challenges to increasing their incomes through only one-fifth of per capita consumption growth in three complementary pathways, namely: (i) urban areas. The bottom 20 percent in rural areas agricultural income growth – increased profitability failed to experience any consumption growth at of smallholder farmers, greater market all (World Bank, 2020b). Consequently, poverty has participation, transition to high value production become more concentrated in rural areas, which and large-scale farming; (ii) growth in off-farm today account for 87 percent of the poor in Ethiopia. incomes – wage and self-employment in the rural non-farm economy; and (iii) migration – This Rural Income Diagnostics (RID) study both permanent and temporary migration, and therefore seeks to inform how to promote remittances (Figure 1). Figure 1. Poverty pathways and income growth for rural households • Increased profitability of smallholders in existing goods through favorable changes in relative prices, more stable prices, yield growth, reduced yield volatilty, area expansion, more cost-effective production AGRICULTURAL • Greater market participation of existing goods through commercializing a larger share of production, selling GROWTH-FARM further up the value chain, engaging in contract farming or outgrower schemes PATHWAY • Transitions of smallholders into higher value crops and non-crop agriculture including livestock • Growth in large-scale commercial farming that increases demand for agricultural wage labor LABOR INCOME • Growth in non-tradable goods and services (wage or self-employment) GROWTH NON-FARM • Growth in tradable goods through mining, tourism or rural manufacturing (wage GROWTH FOR RURAL or self-employment HOUSEHOLDS • Temporary migration of family members to urban areas or internationally MIGRATION • Permanent migration of individuals or families • Commuting Source: RID Framework. 2 INTRODUCTION The objective of the RID is to examine how STEP 2: Identifying the opportunities for income those who currently reside in rural areas can growth – What are the opportunities for agricultural have higher incomes in the future, which could growth and rural non-farm growth, and the nature entail one or more members moving to urban of migration? areas. The focus is on income growth that results in higher incomes on average, but also income STEP 3: Prioritizing constraints to achieving that is less volatile because of due consideration growth – What are the most important constraints to effective risk reduction and management, and preventing poor households from taking advantage to ensuring that growth is sustainable. While the of these opportunities? RID focuses only on income that is earned by rural households, it is much more detailed in its STEP 4: Identification of feasible policy solutions identification of the constraints because of this – What are the feasible policy actions that would narrower focus. The diagnostic provides evidence help poor households overcome these constraints to validate constraints and key areas of focus in and take advantage of the opportunities for income ongoing agriculture and rural policy reforms and growth that are present? other relevant reforms under the HGERA, elevate the importance of some reforms where immediate Complementing the wealth of existing action is required, and provide empirical arguments literature with distributional focused analysis to support important policy interventions where consensus might be lacking or there is policy This RID study builds on a wealth of existing hesitation. The RID’s quantification of impacts of evidence on the main issues of focus in Ethiopia. The identified constraints on rural incomes provides a Poverty Assessment 2020 provides a comprehensive basis for prioritizing and sequencing the reforms. description of the spatial distribution of the poor in While it identifies inadequacies in human capital Ethiopia. The evolution of rural livelihoods in Ethiopia has where relevant and presents macroeconomic been documented, showing the low non-farm income factors to provide context, the RID does not go contribution in rural incomes (Bachewe, Berhane, into detailed analysis of the constraints or identify Minten, and Taffesse, 2016), a wide gender gap in non- policy priorities to address these issues, many of farm employment (F. N. Bachewe et al., 2016), and low which are tackled in the recent Country Economic market participation in agricultural output (Minten, Memorandum (World Bank, 2022a). Dereje, Bachewe, and Tamru, 2018) and input markets (Bachewe, Berhane, Minten, and Taffesse, 2018). On Approach in the Rural agriculture, there are recent empirical studies on agricultural yields for some key crops, for example, Income Diagnostics maize (van Dijk et al., 2020) and wheat (Silva et al., 2021), farm mechanization (Daum and Birner, 2020; Diao, The diagnostic takes four steps to the identification Takeshima, and Zhang, 2020), opportunities that urban and prioritization of constraints within and across population growth offers for increasing agricultural the three types of income growth—farm incomes, incomes (Vandercasteelen, Beyene, Minten and non-farm incomes and migration: Swinnen, 2018), and agriculture production linkages and agriculture trade patterns (Eshetu and Mehare, STEP 1: Context and key dimensions of 2020; World Bank, 2016). The benefits and constraints heterogeneity – How do households currently to migration have also been analyzed in various allocate time and assets across activities to studies, including a new Rural-Urban Migration Study maximize income and reduce variability? by the World Bank (World Bank, 2022b). 3 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Despite this wealth of evidence, there are Pulling together existing evidence and the new knowledge gaps that the RID helps to fill with analysis provides an empirical basis for prioritizing new analysis. These include more detailed analysis interventions for boosting rural incomes. The to better understand patterns observed in the prioritization is at a more granular level to provide literature, such as: (i) the determinants of low market actionable policy options in Ethiopia’s context. surpluses and market participation; (ii) the influence of intra-household dynamics on gender differences in Benchmarking economic participation; (iii) how the land ownership structure influences households’ land use choices, Throughout the analysis, Ethiopia is benchmarked labor allocation between farm and non-farm activities, against country comparators. These are a and overall incomes; and (iv) how migration affects combination of regional peers (Uganda, Kenya and factor allocation in agricultural production. Tanzania) and comparator countries at the next stage of development (Cambodia and Vietnam). New analysis was also conducted to provide a Cambodia and Vietnam are selected as comparators, distribution lens and/or new perspective on topics having undergone transformation, with rapid growth where the existing literature has only paid limited in the non-agriculture sector initially driven by the attention to the distributional dimension of those garment industry, while also increasing their exports issues. The growing literature on urban growth and of key agriculture commodities such as coffee, expenditure linkages has not taken a distributional rice, and pepper. Vietnam also had similar starting angle to ask: (i) who produces the food items with high conditions as Ethiopia. It had a closed economy demand in urban areas and the elasticities of demand and limited private sector participation, which was for food products produced by the poor versus non- not allowed until 1997 and kicked off with a state- poor, or in lagging areas versus better off areas; or led development model. Benchmarking exercises (ii) to assess the agriculture supply response to price against these countries are used to explore areas changes and factors influencing/constraining this with the potential for growth or the potential for supply response to quantify the extent to which rural improvement by reducing binding constraints. households can benefit from rising urban demand. Incorporating new and innovative data sources Other areas where new analysis was conducted are those with limited evidence available in The Ethiopia Socioeconomic Survey (ESS) is used Ethiopia. These include assessing the rural demand as the main source of data for micro analysis. potential for consumer goods and services that can This survey has both a panel component, with be met locally by looking at non-food expenditure three rounds between 2011/12 and 2015/16, and patterns. As part of this, the RID digs deeper into a new round conducted in 2018/19, which is one geography and rural non-farm economic potential of the most recent surveys available in the country. to better understand the relationship between The ESS has been designed as part of the Living access to off-farm opportunities, population density, Standards Measurement Survey–Integrated connectivity, and access to markets more broadly. Survey of Agriculture (LSMS-ISA) surveys, with a rural focus and particular aim to improve the The analysis is a combination of descriptive and measurement of agriculture output and incomes. It multivariate econometric analysis depending involves more precise measurement of agriculture on the question of focus. The goal is to provide a land size, soil quality, and ownership structure sharper distributional lens on topics where this has (at plot and individual levels), labor inputs (at been lacking, conduct in-depth analysis to better plot and individual levels), and input application understand the drivers of trends/phenomena and utilization of agriculture services. Non-farm identified in the literature, and break ground on some incomes are also captured in a separate household areas that have so far received minimum attention. enterprise module and wage labor modules. The 4 INTRODUCTION survey is thus ideal for analyzing how households do, and what limits a household’s ability to earn allocate income-producing assets and labor as they higher, less volatile returns. Table 1. Description of data sources for rural income diagnostics analysis Data Source Data Type and Characteristics Ethiopia Socioeconomic • Nationally representative panel data with three waves, and a refreshed Survey (ESS) – 2011/12, 2014, sample for 2018/19 2015/16, 2018/19 • The data provides variables on: Household and individual characteristics; Land and agriculture production at plot level; Geographic characteristics such as population density, connectivity, access to services; and Prices based on an EA level market prices survey Ethiopia National Labor Force • Nationally representative, cross sectional survey data. Due to conflict the 2021 survey Survey (LFS) – 2013, 2021 excluded the Tigray region (which constitutes about 6 percent of the population) Ethiopia Transport Network • Distance matrix dataset of travel time from one woreda to another Layer 2020 • Dataset also combined with population data to generate various market indices with destination population areas weighted by travel time Gridded Population V4 • Global gridded geospatial dataset (GPWv4), LandScan Global (LSG), • GPWv4 - population counts years 2000, 2005, 2010, 2015, 2020, calibrated to WorldPop (WDP) census; Resolution about 1 km • LandScan: Resolution about 1 km These data provide Population distribution indicators - land cover, roads, slope, urban areas, and village locations The Climate Hazards Group • High frequency 30 years quasi-global rainfall at 6-hourly, daily, monthly, bi- InfraRed Precipitations with monthly, quarterly and annually Stations (CHIRPS) • Based on triangulation of Earth based rainfall gauge data and satellite imagery at 0.050 resolution FAO GAEZ Data • Geospatial data, at 9.3 x 9.3 km pixel size (resolution). The data are extracted at the EA Level Provides information on Agriculture land production potential – crop suitability, yield potential, production gaps which is combined with the ESS survey data in analysis of productivity, land use and market participation FEWSNET • Panel Data – Monthly prices from 2019 to 2021 for various crops, livestock Central Statistics Agency and non-food items (CSA) price survey WFP Food Prices data • Dataset spans the years 2000 to 2021 for maize, sorghum, teff and wheat Galor & Ozak (2016) • Geospatial data – at 9.3 x 9.3 km resolution measuring Caloric Suitability Index which measures potential variation in crop yields across space in calories per hectare per year COMTRADE • Timeseries – Trade flows data at H6 level FAOSTAT • Timeseries – Agriculture production, export, import data Source: Authors’ compilation. 5 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY The ESS data were complemented with data from and agropastoral communities that are at the other sources as necessary. Several geospatial epicenter of the current drought. datasets are used in combination with the ESS data in the analysis. High-frequency quasi-global rainfall data from the Climate Hazards Group Report outline InfraRed Precipitations with Stations (CHIRPS) are The RID comprises five chapters including this incorporated to measure the impact of climate introductory chapter. A short overview of each of shocks. Travel time and market accessibility the next four chapters is provided below. indicators are computed from the Ethiopia Transport Network Layer 2020 and global gridded population Chapter 2: A Snapshot of Rural Livelihoods – Rural datasets derived from probabilistic estimation from Incomes and Welfare. satellite imagery (Gridded Population V4, LandScan Global and WorldPop). The enumeration of area-level This chapter sets the stage for the RID by proxies for suitability and the productive potential of characterizing rural livelihoods and poverty, land are computed from the FAO GAEZ spatial data which is the first step of the diagnostic, answering and Galor and Zak (2016) caloric suitability index, questions on how households currently allocate both based on the application of machine learning time and assets across activities. The chapter then to satellite imagery. High frequency price data from discusses the evolution of rural household income FEWS NET and the World Food Programme (WFP) sources, whether there is growth in non-farm are also incorporated in the analysis. Some specific income in absolute and relative terms, and growth questions are analyzed entirely using complementary in income from market-based activities, as well as datasets, such as the Labor Force Survey (LFS) 2013 whether households have adequate human and and 2021 for labor market outcomes and COMTRADE, physical assets that they can leverage to expand FAOSTAT and GTAB datasets for agriculture trade- household incomes. These issues are presented related analysis. with a distributional lens in terms of variation across welfare quintiles, spatially and by gender. Given the multiple shocks that Ethiopia has Most of the analysis presented will be descriptive, experienced since 2020, additional evidence from relying on the most recently available data. recent but more limited surveys is brought in to capture recent developments and update trends. This chapter shows how the unfolding crises have The COVID-19 High-Frequency Phone Surveys impacted rural households and upended previous (HFPS) collected after every four weeks between trends. Ethiopia has experienced multiple, severe April 2020 and 2021 in Ethiopia by the World Bank shocks from 2020 onwards, after key data used in are used to capture changes or impacts of the the analysis were collected. This chapter reflects COVID-19 pandemic on rural outcomes. To highlight on this. It delves into how the COVID-19 pandemic, the impacts and household responses to droughts conflict and climate change-driven events, have in affected areas, the RID brings new data from impacted rural households and their responses to a Mobile Population Survey conducted between them by bringing alternative data sources to analyze December 2021 and February 2022 among pastoral these issues. By laying out how rural households currently earn their incomes, their natural and human endowments and present challenges, the Additional evidence from recent but chapter sets the stage for identifying opportunities more limited surveys has been brought in to capture recent developments and and pathways for rural households to expand their update trends incomes going forward. 6 INTRODUCTION Chapter 3: Big Picture: Key opportunities for enhancing job opportunities created during the transition rural incomes through development of the food system. of the food system. This chapter presents the key opportunities for • Rise in global agri-food trade – Trends in agriculture expanding rural incomes in Ethiopia centered trade performance at the global level and for around four trends that will drive access to Ethiopia are presented, benchmarking the opportunities in the country. The four key drivers country’s agriculture trade performance, and are: (i) the technology transformation in agriculture; identifying untapped markets. This is followed (ii) the urbanization and dietary transformation; (iii) by a discussion of how rural households might the rise in global agri-food trade; and (iv) the spatial benefit more from engaging in the global agri- and economic transformation. The chapter presents food trade, incorporating evidence from value how each one of these trends will help directly chain analysis. The analysis on this third driver increase agricultural incomes and create off-farm is mostly descriptive based on secondary data opportunities for households to diversify their sources from COMTRADE, FAOSTAT and GTAP. livelihoods. The analysis for this chapter is a mix of descriptive and sophisticated statistical analysis. • Spatial and economic transformation – The discussion of this driver starts with a descriptive • Technological transformation in agriculture – This presentation of rural-urban migration trends, job starts with a descriptive discussion of trends creation potential among urban based export- in the adoption of agriculture technologies and oriented firms, and how migrants are a major the improvement in yields in Ethiopia. Evidence source of labor for these firms. Findings from from multivariate analyses of the determinants the econometric analysis of the spillover effects of land productivity and its impact on crop of rural-urban migration on rural households incomes based on statistical models accounting and communities, such as labor productivity, for the joint determination of the two outcomes renting of land, are then presented. is presented. This is discussed together with estimates from literature and our own Chapter 4: Leveraging opportunities: Three pathways for analysis on yields and their decomposition into increasing rural incomes. various factors to assess the potential impact of technological adoption on productivity. This chapter identifies and discusses three Descriptive analyses are then presented to pathways for expanding rural incomes by show job creation potential for technological leveraging the opportunities presented in Chapter adoption in the agriculture sector. 3. The three pathways are: (i) increasing market orientation of farmers to take advantage of rising • Urbanization and dietary transformation – urban food demand and global agri-food trade; Descriptive analysis on the urban population, (ii) livelihoods diversification through off-farm job income growth and evidence of dietary creation in the agri-food system; and (iii) rural- transformation is presented first. Then the urban labor mobility. Similar to Chapter 3, a mix results from more sophisticated analysis to of results from descriptive analysis and complex identify the food items with potential for growth statistical models is presented. in demand from estimation of elasticities from a household demand system are discussed. This • Increasing market orientation of farmers – Given the is used to identify who is likely to benefit from trade-off between self-sufficiency and market the rising urban demand. Additional descriptive orientation that households must weigh in analysis of changes in jobs in the food system their production decision-making process, is presented at the end to show the off-farm this section starts by showing the impacts of 7 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY market participation on household welfare to • Rural-urban migration – This starts with a presentation make a case that market orientation enhances of evidence on the impact of migration on household smallholder farmers’ welfare. It then presents outcomes. This is followed by quantitative analysis an analysis of the constraints or factors that of the determinants of migration, combined with disincentivize households to produce for, results from qualitative studies on challenges or participate more in, the markets. These faced by rural urban migrants. factors are drawn from multivariate analysis of determinants of households’ land use choices Chapter 5: Translating pathways into action: Priorities for and determinants of market participation, which increasing rural incomes. is done jointly with the estimation of the impact of market participation on household welfare. This chapter presents priority areas for intervention for growing rural households’ • Livelihood diversification through off-farm job incomes in Ethiopia, distilling from the creation in the agri-food system – This sub- diagnostics in Chapter 3 and Chapter 4 on key section starts with a presentation of evidence opportunities and pathways for increasing rural of the contribution of livelihood diversification incomes. Emphasizing the heterogeneity among into non-farm incomes to rural households’ rural households, and the poor in particular, the incomes and poverty reduction. Descriptive chapter identifies the different groups of the poor analysis of factors affecting the presence of and discusses the most important constraints and non-farm job opportunities—low rural demand impacts of different policy interventions for these and a challenging business environment for groups. Prioritization of these interventions is then rural development—are then presented. This is placed in the context of the Government’s sectoral followed by a discussion of the main findings reforms by first presenting the key reforms from an econometric analysis of how location undertaken to address constraints identified in the factors, such as connectivity and population diagnostics and identifying areas where progress density on the one hand, and labor supply is being made and others where progress is factors such as the household farming system, stalled. A set of policy priorities are then presented, endowments and gender norms on the other considering: (i) the impacts of constraints on hand, influence the creation and access to increasing incomes across the three pathways non-farm opportunities in rural areas and identified in the study; and (ii) implementation participation in non-farm work. feasibility in the context of ongoing policy reforms. 8 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE 9 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY To inform how to promote growth in rural incomes the COVID-19 pandemic, inflation, internal conflict, and accelerate poverty, the RID starts by presenting drought, and the Russia-Ukraine crisis. The section evidence on a series of questions to provide context also highlights the welfare implications of food about rural household welfare. These includes price shocks for rural households. questions on who and where are Ethiopia’s rural poor, and how has poverty in rural areas been changing? How do rural Ethiopians earn their incomes, and what Poverty and shocks affect livelihoods? What are the main factors distribution of the poor shaping heterogeneity in rural incomes? How do key household endowments translate into rural income Strong poverty reduction but with increased gains? This section thus characterizes the current spatial disparities state of rural poverty and incomes in Ethiopia, shows trends, and identifies key dimensions of rural income There have been significant improvements in heterogeneity, for example across welfare groups, rural well-being, but the gap between rural geographical regions, and gender. The section also and urban areas has increased. In urban areas, investigates the effects of recent and contemporary poverty decreased strongly from 25.7 percent in shocks on vulnerability and welfare, and the potential 2011 to 14.8 percent in 2016, while in rural areas it implications on poverty reduction efforts in Ethiopia. It decreased from 30.4 to 25.6 percent during the same therefore provides evidence to inform the analysis and period. Consumption growth has been especially policy recommendations presented later in the report. weak among poor rural households. Growth for the bottom 15 percent was not statistically different The section starts with a quick summary of from zero, in contrast to the top of the distribution poverty trends over the period 2011–16, the most where growth rates reached a maximum of close recent period for which official poverty statistics to 6 percent per year between 2011 and 2016 are available. It then discusses the key aspects of (World Bank, 2020b). The absence of gains for poverty that likely remained the same and what the poorest segment of the population owed to could have changed using some of the descriptive generally lower growth in rural areas. The bottom analyses from the year 2021. The section also 20 percent in rural areas did not experience any marshals evidence of the recent development increase in consumption between 2011 and 2016, challenges that Ethiopia has been grappling with while annual growth rates in consumption did not and that are expected to reverse the hard-won exceed 3 percent, even for the richest percentile. In gains of the past two decades. In relation to this, contrast, mean consumption growth in urban areas the section highlights the likely welfare effects of was 5.9 percent per year and was always above 3 percent, even for the poorest. Poverty in Ethiopia is therefore disproportionately concentrated in rural areas, which accounted for 90 percent of the poor in 2016 compared with a rural population share of 80 percent, reflecting the stronger poverty reduction in urban as opposed to rural areas. The growth elasticity of poverty was low, as rural households participated less in the growth process. This is because growth in the agriculture sector, where rural labor is concentrated, has been lower than any other sector. While GDP grew by 10.6 percent on average during 2010-15, agriculture 10 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE GDP grew by 6.5 percent. The shift of labor from Households have faced multiple shocks agriculture to non-agriculture sectors has also been that increased vulnerability slow, despite the fast decline in agriculture’s share of GDP. This pattern continued during the second Multiple shocks at the beginning of the new half of the past decade. Agriculture growth was decade threaten to undo the gains made in the still lower than other sectors, though growth rates past. Since 2020, households in Ethiopia have had were converging to a lower rate (Figure 2), while to contend with the COVID-19 pandemic, climate employment data from the Labor Force Survey change-induced droughts, pests and diseases, suggest the share of rural workers employed in the conflict within the country, and now the fallout from agriculture sector declined by 6 percentage points the Russia-Ukraine war. The combination of these during 2013–21, similar to the decline observed 3Cs—COVID-19, climate change, and conflict— during 2005–13 (Figure 3). have left no single part of the country untouched. As conflict exploded in the northern parts of the Figure 2. Sectoral GDP growth rates, 2016–21 country, prolonged droughts were wreaking havoc in lowland areas, while the effects of the COVID-19 25,0% pandemic were felt everywhere, especially in 20,0% urban areas that previously were the driver of poverty reduction in the country. High-Frequency 15,0% Phone Surveys (HFPS) implemented by the World Bank after the onset of the COVID-19 10,0% pandemic showed that rural incomes declined over the course of 2020. More than half of 5,0% rural households reported that their household incomes in April 2020 were lower than the 0,0% 2017 2018 2019 2020 2021 previous month. Though declining, a high share of rural households continued to be reporting Agriculture Industry Services income losses throughout 2020 (Figure 4). Source: Authors’ estimates from WDI. Figure 3. Sectoral employment composition, 2005–21 Figure 4. Share of rural households reporting loss in incomes (%), April-October 2020 1 51,6 44,8 0,8 36,5 33,7 32,3 0,6 25,7 0,4 0,82 0,90 0,83 0,73 0,77 0,65 0,2 0 2005 2003 2021 2005 2003 2021 Apr May Jun/Jul Aug Sep Oct Ethiopia Rural Areas Agriculture Industry Services Source: Authors’ estimates from LFS 2021. Source: World Bank Staff’s estimates based on HFPS Rounds 1 - 6. Notes: For comparability, estimates from LFS 2013 were computed excluding data from Tigray, which was not covered in the LFS 2021. 11 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY The COVID-19 pandemic and Thurlow, 2020). The partial or full lockdowns across the country also limited agricultural The COVID-19 pandemic is likely to reverse the operations. Within the AFS, food services hard-won poverty reduction gains achieved in experienced the largest percentage decline in the past years. According to the World Bank’s GDP (at 83 percent), followed by agro-processing Poverty and Shared Prosperity Report 2020, the (Aragie et al., 2020). The horticulture segment pandemic could have pushed some 100 million was also highly affected by the pandemic and the people into extreme poverty in 2020 alone, leading restrictive measures taken to contain the spread to an increase in global poverty for the first time of the virus (Wieser, Ambel, Bundervoet and Haile, since 1998 (World Bank, 2020c). Ethiopia has not 2020). However, the effect of the pandemic on escaped the impacts. Besides its direct effect on the rural economy was modest, as only a small health, the most explicit impact of the COVID-19 share of farmers experienced challenges in their crisis on the welfare of households and individuals farming activities due to mobility restrictions at in Ethiopia was through the loss of income due to the onset of the pandemic in April 2020 (Wieser, disruptions of employment and transfers (Harris et Sosa, Ambel, Tsegay, and Pimhidzai, 2021). Rural al., 2021; Yimer, Alemayehu, and Taffesse, 2020). A households, however, faced challenges during World Bank study using the COVID-19 HFPS shows the planting cycle mainly through their inability to that the share of people below the 23.5th percentile purchase fertilizers and seeds. The pandemic also line (a poverty line that coincides with the recent affected the livelihood strategies of agricultural poverty headcount rate in Ethiopia) increased by households by altering them (e.g., agricultural 11.2 percent between 2019 (pre-pandemic) and intensification, livelihood diversification, and November 2020 (Wieser, Takamatsu, Yoshida, migration) and the disruption of agricultural input Zhang, and Aron, 2020). While the share of people supply chains (Asegie, Adisalem and Eshetu, in urban areas below the 23.5th percentile 2021). But the main channel through which increased by 33.2 percent, the share in rural areas rural households are negatively affected by increased by 9.4 percent. The much larger relative the pandemic and its associated restrictions of increase in poverty in urban areas reflects the movement and assembly is via reduced income. more severe impact of the COVID-19 pandemic on employment and income in urban areas. Despite The Climate Shocks the smaller poverty increase in rural areas, the sheer size of the rural population, combined with Increased occurrences of pests and diseases higher poverty rates in rural Ethiopia, means that linked to climate change have affected rural the increase in the absolute number of poor was livelihoods. Ethiopia experienced two invasions higher in rural areas. of desert locusts in 2020. The first invasion, which spread from Yemen to East Africa (including The pandemic affected the agriculture sector, Ethiopia, Kenya, Somalia, Uganda, Sudan, and mainly through indirect channels. Although no Tanzania) between January and May, is reported direct restrictions and lockdown measures were to have invaded 180–240 woredas¹ primarily in imposed on the agriculture sector (and broader eastern and southern Ethiopia. The second invasion agri-food systems, AFS), the sector faced a 4.7 and of locusts, which started in late September and 10.6 percent loss in output and value-added in the peaked in October–November, was more severe agri-food system, respectively (Aragie, Taffesse than the first invasion (Ilukor and Gourlay, 2021). A ¹ Districts of Ethiopia are also called woredas and are the third level of the administrative division of Ethiopia, after zones and the regional states. 12 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE recent study using the HFPS shows that over half of a lack of pasture and water. Households lost all rural households in their kebele² and nearly 30 income due to animal deaths or as prices went percent on their farms experienced locusts during down. The drought conditions have also led to a the first locust invasion. At the peak of the second 20 percent increase in severe acute malnutrition invasion, 37 and 20 percent of the rural households among children (UNICEF, 2022). As a result of observed locusts in their kebele and on their farms, the severe drought that led to livestock losses, respectively. The Afar, Somali, and Harar regions many families have been forced to leave home had the highest incidence of reported locusts (Ilukor without any job opportunities. Overall, the drought and Gourlay, 2021). The desert locust invasions conditions heightened the need for emergency caused an estimated cereal loss of more than food assistance in the affected regions. 3.5 million quintals, affecting more than 806,000 farming households, almost 200,000 hectares (ha) Conflict of cropland, and 1.35 million ha of pasture and browse land (about 50 percent) in the areas around The conflict in the northern part of the country Somali and Eastern Oromia that have suffered has also destroyed livelihoods. The conflict continuous attacks (Ministry of Agriculture et al., between the federal authorities and the Tigray 2020). Overall, the locust outbreak affected the food regional government has devastated Ethiopia’s security of millions of people, compounding the north. The conflict erupted in November 2020 at already bleak food security and poverty situation in the peak of the main agricultural season (meher) rural Ethiopia. While agriculture activities seemed harvest period, when many households had not to be impacted less by the COVID-19 pandemic, yet harvested their crops. It is estimated that over results from the HFPS show that one in four rural 90 percent of the crop harvest and 15 percent of households still reported a reduction in income the Tigray region’s 17 million livestock were lost. from farming activities in October 2020, much Throughout 2021, the conflict expanded beyond of which was attributable to the locust invasions Tigray into the neighboring regions of Amhara and (Wieser et al., 2021). Afar, causing high levels of food insecurity mainly through widespread crop and livelihood losses, Prolonged drought is pushing families in the and the destruction of the local economy. The lowland areas in Ethiopia to the brink. A severe resulting limitations on movement also impaired drought following three consecutive failed rain livelihood activities, market functioning, access seasons (from late 2020 into 2021) has affected to basic services, and humanitarian assistance nearly 7 million people in Oromia, the SNNP, the (WFP, 2022b). This has caused the deaths of tens South West, and the Somali regions (OCHA, 2022). of thousands, created large-scale displacements, The drought dried up water wells, killed livestock and vast humanitarian needs in northern Ethiopia and crops, and pushed hundreds of thousands (ECHO, 2022). As of June 2021, about 5.5 million of children and their families to the brink. In the people in Tigray and neighboring Afar and Amhara traditionally arid Somali region, for instance, the (nearly 93 percent of the population in northern drought has caused severe water shortage and Ethiopia) were in high acute food insecurity. The desiccated the landscape, making the grasses, most recent global food crisis report that covers shrubs, and browsing trees that camels and nearly half of the country’s 115 million population other animals typically feed on scarce. The cited Ethiopia as being among the four countries greatest impact is on livestock deaths due to with the highest number of people that faced ² A kebele is the smallest administrative unit of Ethiopia, and similar to a ward, a neighborhood or a localized and delimited group of people. 13 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Catastrophe (IPC Phase 5) in 2021, primarily due to armed confrontation since June 2021 have conflict or insecurity (WFP, 2022b). contributed to high inflation. A decline in oilseed production and a deceleration in cereal production Market Shocks had already been observed during the main harvest season of the FY2020/21 (World Bank, 2022a). Inflation has been rising in Ethiopia more recently. This supply shock was magnified in FY2021/22 After hovering at around 20 percent in 2020 and the by the subsequent conflict. According to regional first half of 2021, inflation rose to very high levels authorities in Amhara, about 41 million quintals in mid-2021, remaining above 30 percent in early of agricultural production (or about 10 percent of 2022 (World Bank, 2022c). As of February 2022, food the production of the previous year) were lost due inflation was estimated to be about 42 percent—the to the conflict in the fall of 2021 when the armed highest rate recorded during the past nine years— clashes escalated (World Bank, 2022c). The conflict while non-food inflation stood at 22.9 percent. The also affected some non-food prices. For example, primary contributors to the high inflation in the the closure of the Messobo Cement Factory (with a country since June 2021 were food prices (Figure market share of over 20 percent) due to the armed 5 and Figure 6), where bread and cereals and oils and conflict in Tigray was likely among the factors fat have contributed to about 60 percent of food contributing to an increase in the prices of building inflation. In more recent months, vegetables and materials (furnishings, household equipment, and non-alcoholic beverages, and coffee have increased routine maintenance). their contributions to food inflation. Non-food inflation was mainly driven by: (i) housing, water, The Russia-Ukraine crisis is likely to aggravate the electricity, gas, and other fuels; (ii) furnishings, already high inflation in Ethiopia and exacerbate household equipment, and routine maintenance; food insecurity through the availability and and (iii) clothing and footwear, which contributed pricing of commodities. Within just a few weeks of to about 60 percent of non-food inflation between the outbreak of the Russia-Ukraine war in February June 2021 and February 2022. The contribution of 2022, the global prices of wheat, corn, fertilizer, and alcoholic beverages and tobacco has increased in oil all soared. This will likely aggravate the already recent months. high inflation and exacerbate food insecurity in Ethiopia, through the reduced availability and Production shocks from droughts, pests and higher pricing of commodities (e.g., wheat, energy, diseases, and the escalation and spread of the oil, and fertilizer) (WFP, 2022b). Ethiopia is likely to Figure 5. Inflation rate, year-on-year (%), 2016-22 Figure 6. Monthly food inflation, (percent change), 2019-22 45 10 40 8 35 6 30 25 4 20 2 15 0 10 -2 5 0 -4 Jul-16 Oct-16 Jan-17 Apr-17 Jul-17 Oct-17 Jan-18 Apr-18 Jul-18 Oct-18 Jan-19 Apr-19 Jul-19 Oct-19 Jan-20 Apr-20 Jul-20 Oct-20 Jan-21 Apr-21 Jul-21 Oct-21 Jan-22 July August September October November December January February March April May June General Food Non-food FY19 FY20 FY21 FY22 Source: World Bank (2022c). 14 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE be more severely affected by the ongoing conflict (increases) for teff and wheat have a low impact in Ukraine, as the country imports 2.3 percent on rural households, but increases in maize and of its total imports (mainly wheat and oil) from sorghum prices have a severe impact, especially Russia and Ukraine. A shortage of fertilizers due on the rural poor as their buyer positions are to protracted fertilizer deliveries will also lead to worse (Figure 7) because net buyers of maize and rising fertilizer costs and food prices, with knock-on sorghum out number net sellers. However, the effects for agricultural production and food security poor will benefit from price increases in teff and in Ethiopia. The impact will be more severe among wheat as there are more net sellers than net buyers resource-poor and credit-constrained agricultural of these crops (Table 2). households by constraining their ability to respond to rising prices. Besides the direct effects of the Figure 7. Net buyer ratio (NBR) by food commodities and welfare quintiles conflict, the imposition of export tariffs or trade restrictions by Ukraine and Russia (e.g., export bans 0,1 on wheat to support domestic food needs should 0,08 the crisis prove to be prolonged) could slow trade 0,06 0,04 Net benefit ratio in food and fertilizers, worsening global food crises 0,02 and further fueling inflation (WFP, 2022a). 0 -0,02 Though food price increases have heterogenous -0,04 consumption effects by income groups and -0,06 market position, the impacts on rural household -0,08 welfare in Ethiopia are generally negative. High -0,1 commodity prices, particularly for food, could have Teff Barley Wheat Maize Sorghum adverse effects on consumption and poverty for Poorest Poor Middle Rich Richest net food buyers but are beneficial for net seller households. A new analysis based on the net Source: Authors’ estimates based on ESS 2018/19. buyer ratio (NBR), which expresses the household Notes: The net benefit ratio (NBR) of a food item is calculated as net production (production-consumption) divided by total household food production and consumption gap relative to a consumption. It expresses the household food production and household’s expenditure, shows that price shocks consumption gap relative to a household’s expenditure. Table 2: Household distribution by crop market position and welfare quintile, 2019 Teff Barley Wheat Maize Sorghum Self-sufficient Self-sufficient Self-sufficient Self-sufficient Self-sufficient Net seller Net seller Net seller Net seller Net seller Net buyer Net buyer Net buyer Net buyer Net buyer Poorest 17.6 11.1 71.3 8.1 9.2 82.7 8.2 6.3 85.5 9.7 44.9 45.4 11.0 17.5 71.6 Poor 13.2 19.0 67.8 9.9 11.5 78.6 11.1 14.4 74.5 7.0 37.5 55.5 5.4 21.2 73.4 Middle 14.7 22.3 63.0 5.5 9.9 84.6 9.5 20.2 70.3 5.8 35.1 59.1 3.1 19.6 77.3 Rich 11.2 19.8 69.0 5.0 8.7 86.3 6.4 14.4 79.2 3.8 44.5 51.7 2.7 18.2 79.1 Richest 9.7 24.4 65.9 4.3 2.9 92.8 6.1 14.6 79.3 2.9 28.0 69.1 1.8 15.2 83.0 Source: Authors’ estimates from ESS 2018/19. Notes: Household are classified based on their NBR as follows: Net Buyers (NBR < -0.05); Net Sellers (NBR>0.05) and Self-sufficient (-0.05 <= NBR <= 0.05) 15 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Households are fully exposed to the price increases cross-price effects appear to be rather weak for most of maize, barley and sorghum, as their consumption commodity pairs. This suggests limited possibilities in is less responsive to price changes of these crops. consumption for substitution and/or complementarity Analysis using price elasticity estimates from the Exact in Ethiopia. Diversity in the bio-physical and socio- Affine Stone Index (EASI) demand system function (Box economic landscape is likely to constrain these 1) shows that the price elasticity of demand for maize, possibilities. Rural households that produce teff and barley, and sorghum is close to zero (Table 3). In addition, wheat (commodities with high urban demand) are the poor tend to substitute teff with wheat. However, however likely to benefit from price increases. Table 3: Price elasticities of demand of major cereals, 2019 Relative income group Rural Bottom Top Teff Wheat Maize Sorghum Barley 40 percent 60 percent Teff -0.105*** -0.037** -0.079*** -0.001 -0.047*** -0.146*** -0.081* Wheat -0.199*** -0.073*** 0.074*** 0.003 -0.194*** -0.198*** Maize -0.053** 0.031*** -0.046*** 0.016 0.065*** Sorghum -0.029* -0.013 -0.01 0.008 Barley -0.003 -0.100* -0.033 Source: Authors’ estimates from ESS 2018/19. Notes: Estimates based on the Exact Affine Stone Index (EASI) demand system. * p < 0.10, ** p < 0.05, *** p < 0.01. Box 1: Estimation of own- and cross-price elasticities The Exact Affine Stone Index (EASI) demand top 60 percent, and for net seller and net system is used to estimate price elasticities of buyer households. demand for the commodities in Table 3. The EASI models, while maintaining the simplicity Market position: The definition of the net-seller/ of the AIDS model, accommodate high rank net-buyer status of households is based on three Engel curves and unobserved preference components: (i) sale of production for income heterogeneity. Observable sources of preference (income source); (ii) purchase of food on market heterogeneity are also controlled, and these are (expenditure); and (iii) own-production (stocks the gender of the head, size of household in adult for consumption, seed, or storage). A net-seller equivalence and being a PSNP beneficiary. household is a household whose combined production and stocks of the commodity is Relative income groups: To capture different more than what it consumed during the year inflationary pressures (short-term effects of the study. Similarly, a net-buyer household is of price shocks) by relative income group a household whose combined production and and net market position, we construct price stocks of the commodity is less than what it elasticities for the bottom 40 percent and consumed during the year under consideration. 16 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE Rural livelihoods – Household incomes Household livelihoods are increasing over time but stagnated for the poor The lack of consumption gains for the poor makes the progress uneven and many rural Rural incomes have significantly increased over people are still exposed to substantial risks. time although they have stagnated for the poor in Having examined rural poverty trends and the last half of the past decade. The average rural key factors influencing rural-urban disparities income grew (in nominal terms, in Ethiopian birr) in poverty reduction, this section focuses on from about Br 1,925 in 2012 to Br 6,137 in 2019. characterizing rural income patterns and Real incomes (in December 2019 prices) on average dynamics. It also identifies the main factors that grew between 2012 and 2016 and declined between shape heterogeneity in the composition of rural 2016 and 2019 (Figure 8), suggesting that there incomes, providing important evidence for setting were high inflationary pressures during this period. policy priorities. There are three factors behind The increase in total rural incomes is significant heterogeneity in rural incomes that need to be for the richest. Incomes of the richest quintile are emphasized to promote inclusive rural income more than double those of the poorest quintile, who growth. First, incomes within agriculture are have lower incomes across almost all sources. For still largely centered around crop production, instance, non-agricultural wage income is about mainly staple crop production. Second, there are six times higher for the richest quintile. Moreover, pervasive gender gaps in rural Ethiopia where income growth for the bottom 40 percent stagnated women are largely employed in agriculture and between 2014 and 2019 (Figure 9). unpaid work primarily because of low education or skills. Third, geographic location and transfers Rural livelihoods are predominantly agricultural largely determine heterogeneities in income diversification across different regions and agro- Agriculture, mainly on-farm production, remains ecological zones. the main source of livelihoods and income in rural Figure 8. Trends in rural incomes by income source, Figure 9. Trends in rural incomes by income source and 2012–19 (Ethiopian birr, 2019 prices) welfare status, 2012–19 (Ethiopian birr, 2019 prices) 8,000 1,000 345 327 800 503 622 449 6,000 580 655 275 720 600 299 1,756 2,133 4,000 444 1,896 400 495 200 1,455 2,000 3,524 3,115 2,832 0 1,633 b4O t60 b4O t60 b4O t60 b4O t60 - pct pct pct pct pct pct pct pct 2012 2014 2016 2019 2012 2014 2016 2019 Other non-agri. income Transfers Self-employment Other non-agri. income Transfers Self-employment Non-agri. wage Agri wage Livestock Crop Non-agri. wage Agri wage Livestock Crop Source: Authors' estimates based on ESS 2011/12, 2013/14, Source: Authors' estimates based on ESS 2011/12, 2013/14, 2015/16, 2018/19. 2015/16, 2018/19. 17 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Ethiopia. More than 90 percent of rural households Minten, and Taffesse, 2016). participated in agriculture (crop production, livestock raising, or agricultural wage employment) in 2019, Off-farm labor income sources—wage and self- highlighting that agriculture continues to play a employment—contribute less to rural incomes. In fundamental role in rural households’ economic the absence of a significant market for agricultural portfolios. Rural households have higher shares wage labor, the main source of alternative incomes of agricultural income or farm income (Figure 10), is non-agricultural wage employment and self- though the share of income from agriculture declined employment in a wide range of extremely varied between 2016 (81 percent) and 2019 (77 percent). activities, including agro-processing, manufacturing, Within agriculture, crop production contributes mining, commerce, transportation, utilities, tourism, a large share of agricultural and rural incomes. and other services (Haggblade et al., 2007). Reflecting Although agricultural wage employment is a common the higher level of the rural labor market supply and off-farm activity that could help the poor supplement lower-level rural non-farm enterprise development their on-farm income between cropping seasons, in Ethiopia, non-agricultural wage employment has it appears to be a much less important source of relatively higher contributions to rural income (6 income than other off-farm activities, contributing percent of income in 2019) than self-employment (3 only 2 percent of the total incomes in 2019 (Figure percent), though both sources’ contributions to rural 10). This could reflect limited opportunities for wage incomes are still low (Figure 10). employment in agriculture (FAO, 2017; Lanjouw, Quizon and Sparrow, 2001) because private and The lower share of non-agricultural wage state farmers are not common (they produce about 6 employment income is primarily because such percent of the food crops and 2 percent of the coffee) employment is a limited option in rural Ethiopia, and family labor is the most important contributor to mostly found in regions with unique endowments agricultural work with hired labor contributing about of resources, infrastructure, and services. In Sub- 7 percent of agriculture labor (Bachewe, Berhane, Saharan Africa (SSA), especially in rural areas, wage employment in productive sectors (e.g., Figure 10. Share of total income by source, 2012–19 manufacturing) is scarce, and most non-agricultural wage labor consists of jobs in the services sector. 7% 5% 5% 7% 3% 3% The most lucrative opportunities are usually available 6% 6% 7% 6% 3% to households that are already well-off, with ample 7% 5% 5% 6% human and social capital. Self-employment is believed 7% to be the most common source of off-farm income 28% 32% in developing countries and the main diversification 30% option for the poorest households. However, the 36% incidence of self-employment and its contribution to rural incomes are extremely low in rural Ethiopia. In 2019, only 15 percent of the households participated in self-employment, while participation was higher in 52% 49% 45% other countries such as Nigeria (53 percent), Malawi 36% (34 percent), and Uganda (27 percent) during the same period. The contribution of self-employment to rural income was 3 percent in Ethiopia but higher 2012 2014 2016 2019 in other SSA countries, including Malawi (8 percent), Crop Livestock Agri. wage Non agri. wage Uganda (14 percent), and Nigeria (26 percent). Self employment Transfers Other non-farm Source: Authors’ estimates based on ESS 2011/12, 2013/14, The share of non-agricultural income has 2015/16, 2018/19. increased in recent years, driven mainly by 18 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE income from transfers and other non-labor share of rural households that generates more income sources. Non-labor income from transfers than 75 percent of their income from farming alone (remittances and safety nets) and other income increased between 2012 and 2016, before it declined (such as land and property rentals, income from in 2019 (Table 4). This indicates that specialization in inheritance, or sale of assets) have contributed to on-farm activities continues to be the norm among an increase in non-agricultural income. Transfer rural households in Ethiopia, as in most African incomes are generally greater than income from countries including Kenya. Specializing in off-farm local non-farm activities (such as wage employment employment is, however, a rare phenomenon. A small or self-employment). Among the main components share of rural households specializes in off-farm of transfers are social protection programs that employment—wage employment, self-employment, seek to promote the more efficient use of resources or transfers/migration/other non-labor activities. and allow poor rural households to invest in riskier The degree of dependance on transfers is however but more remunerative livelihood activities, mainly consistent with other African countries that have by reducing liquidity constraints and supporting more than 5 percent of households specializing in labor mobility (Slater and Mccord, 2009). Other non- transfer income (Kenya, with 9 percent). The share of labor income sources, such as rents from land and households that do not derive more than 75 percent other property, contributed about 7 percent to rural from a single income source —be it farming, labor, incomes in 2019 (and increased between 2016 and transfers, or other non-agricultural sources—but 2019 by 2 percentage points). instead have a diversified income source decreased between 2012 and 2016, and then increased in 2019. Rural households are subsistence-oriented The increases in diversified income in 2019 were and less diversified driven partly by engaging more in off-farm income alternatives mainly wage employment and transfers. Most rural households specialize in farm activities, Overall, diversification was relatively low at the deriving most of their income from farming. The household level. Table 4: A typology of rural households by type of livelihoods Typology Definition 2012 2014 2016 2019 Specialized in More than 75 percent of total income from farm 61 72 75 68 farm activities production (crop/livestock) Specialized More than 75 percent of total income from agricultural/ 5 3 2 4 in wage non-agricultural wage employment employment Specialized in More than 75 percent of total income from nonfarm 4 2 3 2 self-employment self-employment Specialized in More than 75 percent of total income from transfers/ 5 3 3 6 transfers/other other nonlabor sources nonlabor Diversified Neither farming, labor, nor migration income source 25 20 17 20 contributes more than 75 percent of total income. Source: Authors’ estimates from ESS 2011/12, 2013/14, 2015/16, 2018/19. Notes: Carletto et al. (2007) and Davis et al. (2017) for the methodology. 19 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY The rural poor depend most on agriculture low returns as coping or survival strategies (Losch, Fréguin-Gresh and White, 2012).³ Agricultural income typically accounts for a larger share of income for the poorest households. The The difference in the level of engagement in off- importance of on-farm sources of income (crop farm activities between the poor and the rich could and livestock production) gradually decreases with be due to differences in resource endowments, income, as they are replaced by non-agricultural such as capital, education, and infrastructure. or off-farm income, mainly non-agricultural wage The wealthier households are the ones that often income and transfers (Figure 11). The relative seize remunerative or higher-return rural non-farm importance of off-farm (non-agricultural) income is opportunities (e.g., Barrett et al., 2001; Bezu et al., greater among wealthier households. Within non- 2012) and they are the ones that can accumulate agricultural income sources, transfer income tends to capital, increase adult labor or increase access to be relatively higher among the relatively few better- credit and savings (Bezu and Barrett, 2012). The off households (FAO, 2017). This could imply that the poor often face entry barriers that render them poorest rural households either engage in short- unable to make investments in key assets (Reardon, term migration to reduce the food security gap or Taylor, Stamoulis, Lanjouw and Balisacan, 2000). As consumption smoothing, or that household members a result, they engage in low productivity activities do not have the means to migrate. The share of such as subsistence agriculture and seasonal income from non-farm employment is similar across agricultural wage labor (Davis et al., 2017). the first four quintiles, though average non-farm incomes are higher among the better off quintiles. Land ownership dictates income diversification This might reflect a pattern of neutral diversification, in which the poorest and most marginalized households The share of non-agricultural income decreases engage in minor self-employment activities with very with the size of landholdings. Market labor income is important where population pressures on limited Figure 11. Income shares by quintiles, 2019 land resources are high or where seasonal income from farming is insufficient for survival in the 6% 6% 6% 6% 6% 4% 4% 5% 5% 5% off-season, possibly because of weather-related 5% 5% 5% 6% 6% 5% 5% 6% 7% shocks, price risks, or diseases (World Bank, 8% 2007). In Ethiopia, the share of agricultural (farm) 31% 30% 34% 31% income increases with the size of landholdings 30% driven mainly by crop production (Table 5). The rural landless tend to depend on non-agricultural income sources, including wage employment, self- 47% 49% 47% employment, and non-labor income sources. They 44% 43% are likely to depend on the non-farm income for their survival because they have limited options, Poorest 2nd 3rd 4th Richest unlike agricultural households that mostly count Quintile Quintile Quintile on non-farm earnings to diversity risk, moderate Crop Livestock Agri. wage Non agri. wage seasonal income swings, and finance agricultural Self employment Transfers Other non-farm input purchases (Haggblade, Hazell and Reardon, 2010; Kosec, Ghebru, Holtemeyer, Mueller and Source: Authors’ estimates based on ESS 2011/12, 2013/14, 2015/16, 2018/19. Schmidt, 2017; Winters et al., 2009). ³ This is in contrast to a positive diversification (generally a full-time activity), in which self-employment contributes significantly to household income. Moreover, positive diversification is accessible mostly to better-off households—those with more or better assets and the ability to make an initial investment (for example, a grinder, a sewing machine, or welding equipment). 20 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE Differences in diversification among the most important means of livelihood, contributing agro-ecological zones are primarily about half of the total household income (Table 6). Most driven by transfers regions (Amhara, Afar, Dire Dawa, Harari, Gambela, and Tigray) have agricultural income shares of between Agricultural income share is higher in high 60 and 80 percent. Livestock income is an important agriculture potential areas than in less potential source of income in drought-prone, lowland, pastoralist areas. In areas where the agro-climate is favorable, i.e., areas, and more so than elsewhere. The Somali region moisture reliable areas that include parts of Amhara, appears to be an exception, with a small share of Oromia, SNNP, and Benishangul-Gumuz regions income from agriculture (mainly livestock). In the Afar (World Bank, 2017a), households tend to earn more region as well, agriculture (livestock production) makes from farming with crop production, which tends to be the largest contribution to income. Table 5: Income diversification patterns by landholding classes, 2019 No farmland 0 - 1 ha 1 - 2 ha 2 - 4 ha > 4 Ha Rural Agricultural income 36% 80% 85% 91% 95% 77% Crop 0% 52% 53% 55% 57% 45% Livestock 34% 27% 32% 36% 37% 30% Agriculture-wage 1% 1% 0% 0% 0% 2% Non-agriculture (labor) income 29% 10% 5% 3% 2% 9% Non-agriculture. wage 20% 7% 3% 2% 1% 6% Self-employment 9% 3% 2% 1% 1% 3% Non-labor income 35% 11% 9% 6% 4% 14% Transfers 22% 5% 3% 1% 1% 7% Other non-agriculture sources 13% 6% 6% 5% 3% 7% Source: Authors’ estimates from ESS 2018/19. Table 6: Income diversification patterns by agro-ecological zone Drought- Drought-prone, Humid Moisture Moisture prone, lowland, moisture reliable, reliable, highland Pastoralist reliable, highland- highland- lowland Cereal Enset Agricultural income 75% 57% 64% 82% 80% Crop 48% 18% 33% 50% 51% Livestock 27% 39% 30% 31% 27% Agriculture-wage 0% 1% 1% 1% 1% Non-agriculture (labor) income 14% 16% 12% 8% 8% Non-agriculture. wage 12% 13% 5% 4% 5% Self-employment 2% 3% 7% 4% 3% Non-labor income 11% 27% 24% 11% 12% Transfers 7% 19% 7% 3% 6% Other non-agriculture sources 4% 8% 17% 8% 6% Source: Authors’ estimates from ESS 2018/19. 21 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Non-agricultural incomes are more important in the workforce, the share of income from agriculture lowlands due to transfers. Non-agricultural income is less among female-headed households than makes up between 18 and 20 percent of the total for male-headed households (Figure 12). This is rural household incomes in high potential agricultural primarily driven by differences in transfer incomes, areas, much of that coming from non-labor income which make up 13 percent of incomes of female- sources (Table 6). In less agriculture potential areas headed rural households compared with 5 percent that include arid regions (Tigray, Afar, and Gambela), among male-headed households. Private transfers, the non-farm sector is larger, contributing between including remittances, make up about 56 percent 25 and 43 percent of the total income. The most of the transfer income among female-headed important non-farm income sources in these areas households. The difference in the contribution of are transfers and non-agricultural wage employment, labor income (non-agricultural wage and self- contributing 19 and 13 percent of the total incomes, employment) is not as big, though female headed respectively. The contribution of wage employment household also have a higher share of income from and self-employment is also relatively higher in these these sources than male headed households. Thus, areas than those in agriculture potential areas. The differences in income composition by gender of the results hint at push factors for diversification, with household head are driven largely by transfers than households in less-favorable agroclimatic zones labor income. The higher share of income from non- (less fertile or drier regions) tending to diversify their agriculture sources for female-headed households livelihoods beyond agriculture and engage in non- could reflect that female household heads are farm activities to manage crop income risk or to cope pushed into off-farm employment because they have with the risks (Schmidt and Woldeyes, 2016; World less access to land and other factors of production Bank, 2007). than men (World Bank, 2019b). Non-agricultural incomes are more important Compared with adults, younger farmers are more for households with female heads likely to engage in non-agricultural or off-farm activities. The share of agricultural or farm income The income diversification pattern differs increases with age, accompanied by a decrease in considerably across gender. Although women the share of non-agricultural or off-farm income have traditionally been heavily engaged in farming with age (Figure 13). Households that have younger and contribute a large share of the agricultural heads (15 to 24 years of age) earn relatively a Figure 12. Rural income composition by gender of Figure 13. Rural income composition by age of household head, 2019 household head, 2019 6% 9% 9% 6% 7% 5% 6% 7% 13% 8% 7% 7% 6% 4% 8% 10% 9% 12% 31% 32% 26% 29% 22% 48% 45% 45% 35% 41% Male headed Female headed 15-24 25-34 35 or older Crop Livestock Agri. wage Non agri. wage Crop Livestock Agri. wage Non agri. wage Self employment Transfers Other non-farm Self employment Transfers Other non-farm Source: Authors’ estimates based on ESS 2018/19. Source: Authors’ estimates based on ESS 2018/19. 22 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE lower share of their income from farming (crop formal education or less education earn a larger or livestock production) compared with those with share of their income from agriculture compared older heads. The results also show that households with those households with heads that have higher that have younger heads (15 to 24 years of age) levels of formal education. Both the level and share earn a relatively higher share of income from of income from off-farm or non-agricultural sources non-agricultural wage employment and self- increase with education. The share of off-farm employment than households that have mature or income for households with a head that has no formal older heads. The findings highlight the importance education and those with post-secondary education of rural non-agricultural or off-farm jobs to rural is 24 and 69 percent, respectively. Households that youth and female-headed households. have heads with post-secondary education earn about half of their income from wage employment. Income diversification is positively correlated Self employment's contribution to total incomes is with education among households with more educated heads as well. The findings point to a high return to education Education increases prospects of non-agricultural in terms of expanding access to opportunities. employment and has high returns in rural Ethiopia. The income shares from farm sources (crop and livestock production) decrease with the level of education, while those of non-agricultural sources (mainly wage-employment) increase with education (Figure 14). Households with heads that have no Figure 14. Income composition by education status, 2019 8% 5% 8% 6% 6% 4% 5% 7% 4% 3% 6% 6% 6% 13% 32% 50% 31% 26% 7% 47% 7% 45% 42% 24% No education Primary Secondary Post-Secondary Crop Livestock Agri wage Non agri-wage Self-employment Transfers Other non-agri income Source: Authors’ estimates based on ESS 2018/19. 23 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Household the rural population remained poorly educated in 2021, although there was an improvement from endowments 2013. Women remain less educated than men. In 2021, about 71 percent of women had no formal The amount and quality of household endowments— education, compared with 60 percent of men. In human capital, land, productive resources, and addition, women are less likely to pursue higher infrastructure—affect rural households’ earning levels of education. Only 2 percent of women in capabilities and incomes. Education and land are the rural areas have completed secondary school or key household assets that have been shown to influence above, compared with 4 percent of men (Figure 15). earnings in rural areas. Also important, are productive A low level of literacy in rural Ethiopia (particularly services and infrastructure (e.g., roads, electricity, markets, among women) implies low skills and knowledge credit and insurance markets) and financial institutions, (of technologies, opportunities, etc.) that would which are crucial to both agriculture and rural non-farm constrain rural income growth. activities. Rural electrification is, for instance, a critical Figure 16. Nutrition outcomes of under five years element of rural development and diversification. Better old rural children (%), 2019 infrastructure increases investments and incomes and 41% 37% improves the supply response by providing greater access to output and input markets and allowing lower production 26% and transaction costs. This sub-section analyzes the key 23% 21% household endowments to paint a clearer picture of how people in rural Ethiopia earn their incomes. 14% 7% 8% 6% Human capital is low Education attainment is low, especially among National Urban Rural women. Education is a key asset in determining Stunted Wasted Underweight people’s capacity to earn higher incomes. However, Source: Ethiopia Mini DHS 2019. Figure 15. Population distribution by education Figure 17. Prevalence of undernourishment (modeled attainment (%), 2021 value, %) 3,3 1,7 5,5 3,4 40 26,5 31,2 35,4 35 40,1 30 25 71,3 64,5 20 52,9 60,3 15 10 Male Female Male Female 5 2013 2021 0 No education Primary Secondary Post-Secondary 2004-2006 2005-2007 2006-2008 2007-2009 2008-2010 2009-2011 2010-2012 2011-2013 2012-2014 2013-2015 2014-2016 2015-2017 2016-2018 2017-2019 2018-2020 Source: Authors’ estimates based on LFS 2013 and 2021. Notes: (a) Estimates for 2013 exclude the Tigray region which was not covered in the 2021 survey; (b) Primary – has some primary education; Secondary – has some post primary education up to complete second- ary education; Post-secondary – has some post-secondary education. Source: FAOSTAT. 24 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE Nutrition outcomes are also poor, with child The poorest own less land on average stunting very high in Ethiopia. Data from the 2019 Ethiopia Mini Demographic and Health Survey The average landholdings are small on average, (EMDHS) show that about 37, 7 and 21 percent and the poor own less land than the rich. The of children under five years of age are stunted, national average landholding is 1.02 hectares (ha) wasted, and underweight, respectively (Figure 16). per household, and about 0.90 ha among the poorest Overall, children in rural areas are more likely to quintile (Figure 18). The difference in landholdings be stunted, wasted, and underweight than those in between the rich and the poor is greater when adjusted urban areas. The prevalence of undernourishment for household size, a measure of the mouths that need decreased between 2004 and 2017, but then to be fed, and labor that needs to work on the farms slightly increased over the past five years (Figure or adjusted for the productive potential of the land. 17). A recent report shows that about 5.2 million The per capita landholding among the poor is 0.10 children under five years of age (7.2 percent) were ha, while households in the richest quintile own about wasted in 2021 (WFP, 2022b). Nutrition outcomes 0.18 ha of land per capita (Figure 19). The average per are expected to further deteriorate following the adult equivalent caloric production potential of land conflict in northern Ethiopia and the drought in owned by rural households (land suitability) is found regions in the south and southeast of Ethiopia. Low to be 885, on average, but only 708 among the poor, nutrition outcomes have negative implications for with the richest quintile owning nearly twice as much future productivity and earnings. land as the poorest quintile (Figure 19). Figure 18. Average landholdings (ha) by quintile, 2019 1,10 1,10 1,06 1,02 0,90 0,94 Poorest Q2 Q3 Q4 Richest Rural Figure 19. Average landholding (ha) and caloric production potential (kcal) by welfare quintile, 2019 1,600 0,20 Per adult caloric potential (kcal) 0,18 Per capita landholding (ha) 1,400 0,13 0,14 0,14 1,200 1,381 0,15 1,000 0,10 800 1,002 0,10 861 815 600 708 400 0,05 200 0 0,00 Poorest Q2 Q3 Q4 Richest Per adult caloric potential Per capita landholding (ha) Source: Authors’ estimates based on ESS 2018/19. Notes: The household caloric production potential is calculated as the product of the Caloric Suitability Index (CSI) and total landholding. The CSI gives the average caloric yields per hectare of land. 25 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY There are significant gender gaps in land Livestock ownership in pastoral areas is ownership, with women owning less land than also unequal men. The results indicate much larger gender gaps or inequalities in land ownership when we consider The poor in pastoral areas own less livestock landownership solely by men or women (Table 7). than the rich, on average, but ownership differs by The share of land owned only by men and women livestock species. Livestock is important in Ethiopia’s were 17 and 28 percent, respectively. Moreover, agricultural economy, as almost all farmers own the share of land with titles owned by women is some livestock. Livestock rearing is more common 20 percent, while 36 percent is owned by men. The in the pastoral and agro-pastoral areas of Ethiopia, gender differences in land ownership could explain mainly in Afar and Somali regional states, and in the existing gender gaps in productivity and constrain Southern Oromia and SNNP regions. According to a women’s opportunities to engage in the production recent survey, the total livestock population in these of high-value crops through diversification. Closing four regions is about 19.4 million total livestock units the gender gap in agricultural productivity would (TLUs). The Somali and Afar regional states make up need inclusive land-titling programs. nearly 80 percent of the total livestock population (Figure 20). In terms of the composition of the livestock Table 7: Land ownership by gender, 2019 portfolio, cattle, followed by small ruminants, are the dominant livestock species owned in the Oromiya and Share (%) the SNNP regions. The Afar and Somali regional states Total land ownership 100 have more diversified livestock portfolios composed Land owned by women 17 of cattle, small ruminants, and camels. A recent study demonstrates that the share of cattle in total livestock Land owned by men 28 output is declining, and that small ruminants are on Land jointly owned 55 the rise, especially in pastoralist areas (Bachewe, Minten, Tadesse and Taffesse, 2018). The poorest in these regions own less livestock on average than Titled land ownership 100 the rich (Figure 21). In terms of livestock species, the Land female owned by women with title 20 poorest in the SNNP region and Somali own more Land owned by men with title 36 cattle than the richest. However, it is the richest who own more cattle in Afar and Oromiya. In the Somali Land jointly owned with title 44 region, the richest own more camels on average than Source: Authors’ esitmates from ESS, 2018/19. the poor. Figure 20. Livestock population distribution by Figure 21. Average livestock holdings by welfare regions (in TLUs), 2022 quintile (TLU), 2022 7% 15% 3,6 TLU per capita 3,0 2,6 2,1 30% 1,5 49% Poorest 2nd 3rd 4th Richest Afar Somali SNNP Oromiya Quintile Quintile Quintile Source: Authors’ estimates based on Mobile Population Socio-Economic Survey (MPSE) 2022. Notes: The total estimated livestock population is 19,399,481 (in Total Livestock Units - TLUs). 26 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE Livestock output has grown in the past decade, Access to productive services and infrastructure but productivity has remained stagnant. The is also low average gross livestock revenue per capita is Br 6,505, the highest being for the SNNP region Financial institutions are few in rural Ethiopia and (Br 7,565) and the lowest for Oromiya (Br 5,150). the poor have limited access to finance. The shares Existing evidence shows that livestock output (e.g., of households that live in communities where there milk and egg production) grew at about 6 percent are Savings and Credit Cooperative Organizations per year between 2005 and 2015 (Bachewe, (SACCOs) and Microfinance Institutions (MFIs) were 35 Minten et al., 2018). Nonetheless, productivity and 24 percent, respectively. Only about 1 percent of (output per animal) stagnated during the same rural households lived in communities where there is a period, implying that rapid output growth resulted commercial bank in 2019. The share of rural households from an increase in the number of livestock. that live in communities where there are insurance Although the adoption of improved breeds and offices and cooperatives is less than 10 percent. The improved feeding practices has increased rapidly rural poor live further from financial institutions than over the past decade, linked to improved access richer households (Figure 22). The use of formal to extension and markets, this contributed little to financial services such as credit was 20 percent in growth in the livestock sector. This growth path 2019. Among the key determinants of access to credit contrasts with the crop sector, where modern among agricultural households are political and social input adoption has played an important role in networks, risks, resource endowments and wealth, and recent growth (Bachewe, Berhane, Minten and agro-ecological zone (Ali and Deininger, 2014). Overall, Taffesse, 2018). There has also been an increase Ethiopia lags behind its neighboring countries (e.g., in veterinary services provision, leading to a Kenya) and other SSA countries in financial inclusion decline in livestock death rates. However, the and access to and usage of digital financial services. number of livestock lost is still more than twice The presence of few financial institutions has a negative the number sold for meat consumption. Frequent effect on financial inclusion and the use of formal droughts in pastoral areas of the country that are financial services. As later analysis demonstrates, this associated with water and pasture shortages and limits non-farm economic development (mainly non- low livestock prices contribute to low production. agricultural business development) and investment Improving access to livestock extension, proximity in remunerative activities, including technological to markets and urban centers, and better education innovations in agriculture. Insurance markets are largely will stimulate the adoption of modern livestock underdeveloped in the country. Limited agricultural production inputs (Bachewe, Minten et al., 2018), insurance or formal insurance markets mean that which would contribute toward increased output rural households rely on their resources or adverse and productivity. risk-coping mechanisms in the face of income shocks. Figure 22. Distance to the nearest financial institution by institution type and welfare quintile (km), 2019 71 62 61 61 54 Distance (Km) 39 31 33 27 30 29 24 24 22 23 22 24 22 21 21 Distance to the nearest Distance to the nearest Distance to the nearest Distance to the nearest commercial bank microfinance institution bank agent insurance branch Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile Source: Authors’ estimates based on ESS 2018/19. 27 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY The rural poor are also poorly connected to other and increased to Br 54,043 million (11.1 percent of services. Access to electricity in rural areas is total expenditure) in 2019/20. Despite this concerted particularly limited. The share of rural households effort, rural accessibility or connectivity is still low, with access to electricity ranges from less than 5 particularly among the rural poor. The share of the percent among the poorest rural households to about rural poor population that lives within 5 km of the 17 percent among the richest households (Figure main road is about 17 percent, compared with 36 23). The Government of Ethiopia (GoE) embarked on percent for the rural rich (Figure 23). The average constructing rural roads to make public and social distance to roads, markets, population centers, or services more accessible to the rural communities. urban centers is, on average, higher among the rural Between 2010 and 2016, the government developed poor than for the rural rich (Figure 24). rural roads under the Universal Rural Road Access Program (URRAP) in about 4,000 communities, Mobile phone ownership is still low in rural Ethiopia, reaching nearly 20,000 km in total, mainly in with a gap between the poor and the rich. The use of Oromiya region. An additional 6 percent of rural mobile phones is an effective means to complement Ethiopians were connected to rural roads, the rural or replace direct and face-to-face services, and to accessibility index (RAI) increased from 46 to 52 shorten the distance between isolated smallholders percent, and the average travel time to the nearest and other actors involved in agri-value chains (Annan, town decreased by about 30 minutes (Nakamura, Conway and Dryden, 2016). As third generation (3G) Bundervoet, and Nuru, 2020). Moreover, according to broadband coverage extends to the countryside, rural data from the Ministry of Finance (MoF), the amount people are moving increasingly from basic mobile of government expenditure on roads was Br 18,549 phones, with voice and text-message capabilities, to million (19.7 percent of total expenditure) in 2010 feature phones, which support media formats such Figure 23. Access to electricity, roads and urban Figure 24. Distance to markets by quintile (km), 2019 centers (%), 2019 36% 84 32% 75 77 73 76 73 72 70 30% 72 70 68 63 62 63 Distance (Km) 26% 58 16% 17% 9% 6% 8% 4% 4% 4% 2%1%3% Share of households Lives Lives Distance to Distance to Time travel with electricity within 5km of within 5km of nearest market nearest major to nearest connection population center main road urban center urban center Poorest quintile 2nd quintile 3rd quintile Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile 4th quintile Richest quintile Source: Authors’ estimates based on ESS 2018/19. Source: Authors’ estimates based on ESS 2018/19. 28 SNAPSHOT OF RURAL LIVELIHOODS: RURAL HOUSEHOLD INCOME AND WELFARE as images and videos, and can connect to the internet contend with the COVID-19 pandemic, climate change- (FAO, 2017). There has been a dramatic improvement induced droughts, pests and diseases, and conflict in the past two decades in mobile phone coverage within the country, together with the fallout from the and adoption, although infrastructure investments Russia-Ukraine war that together threaten to undo the remain low in many developing countries. The share of gains made in the past decades by exacerbating the rural households that own a mobile phone increased already high inflation in the country that aggravates between 2012 and 2019 (Figure 25). There is a large poverty and food insecurity. gap in mobile phone ownership between the rural poor and the rural rich (Figure 26). This could contribute to Growth in rural households’ incomes has—and gaps in access to market information, technologies, continues to be—hamstrung by the same factors and business development. Improving access to the as before, exacerbated by multiple recent shocks. internet (and internet literacy) for the poor would help Livelihoods remain predominantly subsistence- leverage the potential of ICT in improving rural incomes. based agriculture, but agriculture sector growth has been lower than other sectors. This means In summary, Ethiopia has experienced high economic that boosting growth in agricultural incomes— growth and significant gains in poverty reduction through raising productivity, given small land sizes, over the past two decades, but this growth has and shifting from a subsistence to commercial been less inclusive. The pace of poverty reduction orientation—will remain the primary driver of has been slower in rural areas. Overall, poverty is rural income growth. However, the limited level of disproportionately concentrated in rural areas, as diversification suggests expanding off-farm income- labor has been slow to shift out of agriculture, which generating opportunities accessible by households has grown at a slower rate than other sectors of the with low human capital could also help rural economy. The rural population in Ethiopia remains less households raise their incomes. Transfers are also connected to the rest of the economy, has poor access to a major income source for livelihood diversification. public services, and remains predominantly dependent Meanwhile, the impact of recent shocks highlights on subsistence agriculture and has less diversified the need to strengthen households’ resilience to livelihoods. Income diversification in rural Ethiopia has future shocks. The key opportunities for increasing been driven by push factors in the form of a lack of households’ income in agriculture and through land or the receipt of social transfers in drought-prone diversification and transfer incomes are discussed areas. Since 2020, households in Ethiopia have had to in the next section. Figure 25. Mobile phone ownership in rural Figure 26. Mobile phone ownership by rural Ethiopia, 2012–19 quintiles, 2019 43% 40% 37% 48% 43% 40% % that own mobile 39% 24% 31% Poorest 2nd 3rd 4th Richest 2012 2014 2016 2019 Quintile Quintile Quintile Source: Authors’ estimates based on ESS 2011/12, 2013/14, Source: Authors’ estimates based on ESS 2011/12, 2013/14, 2015/16, 2018/19. 2015/16, 2018/19. 29 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES 30 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES opportunities for rural enterprises both upstream and downstream of agriculture value chains. This can be viewed in the context of Ethiopia making a transition from the “beginning” stage to the “agriculture surplus” stage, and then the “early integration” stage of agriculture development. Timmer (1988) outlines four phases of agriculture transformation. In the beginning stage, low agriculture labor productivity starts to rise, continuing to a point where productivity increases sufficiently to generate enough agriculture surplus to facilitate a shift of factors of production out of agriculture, which is the second phase of agriculture development. The agriculture surplus phase enables growth of non- agriculture sectors as the linkages between rural The transformation of the food system and urban areas are strengthened through more and global agri-food trade will be the main efficient markets—a process that accelerates the drivers of opportunities for rural households shift of labor and capital to more productive sectors, which is the integration phase—the third phase. Being primarily agricultural, most opportunities Agriculture will be progressively linked to the rest for expanding rural incomes will emerge from of the economy until the role of agriculture is little the transformation of the food system. This different from any other part of the economy, at which transformation is driven by technology adoption point the economy is fully industrialized—the fourth and urbanization at the domestic level, which phase. With value added per worker of US$804 and will be accompanied by increases in agricultural an agriculture output share of 33.5 percent in 2019 productivity and dietary transformation. This in turn and an employment share of 65 percent in 2021, will create opportunities for smallholder farmers Ethiopia is at the beginning phase of the agriculture to increase productivity and sell their outputs, transformation process, similar to where Vietnam while also creating non-farm income-generating and Cambodia were two decades ago (Figure 27). Figure 27. Agriculture value added and contribution to employment and GDP, 2000–20 Agriculture share in GDP (%) Value added per worker (USD) Agriculture share in employment (%) 50 2,500 90 45 80 40 2,000 70 35 60 30 1,500 50 25 40 20 1,000 30 15 500 20 10 5 10 0 0 0 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 Cambodia Ethiopia Kenya Tanzania Uganda Vietnam Source: WDI. Notes: Employment shares are based on ILO modelled estimates. 31 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY As global experience shows, both the composition incomes. The analysis presents the opportunities of agriculture output and jobs in the food system at the household level, and hence mostly focuses change during the transition process, generating on the implications for smallholder farmers, new opportunities along the way. First, the micro, small and medium rural enterprises, and composition of agriculture changes from cereals to at the individual level. Based on the identified more nutrient-dense, high value crops. In the early opportunities, the next section discusses pathways 1970s, cereals, roots and tubers made up 47 percent for expanding rural incomes leveraging on the of agriculture output in developing Asian countries identified opportunities. and this declined to 27 percent by 2010. Second, jobs in the food system shift from being primarily Figure 28. Evolution of jobs in the agri-food system farming-based toward more food manufacturing and food services-based (World Bank, 2017b; Figure 28). This suggests that growth opportunities in Ethiopia will be linked to a shift toward high value LOW INCOME crops production and off-farm jobs in the non-food eg. African countries segments of the food system. Farming: 91% MIDDLE INCOME Food manufacturing eg. Brazil At the global level, opportunities are created industry: 3% Farming: 49% Food services: 6% from the transformation in global value chains. Food manufacturing ≈ 80% OF ALL JOBS The first and most important factor for increasing industry: 25% HIGH INCOME Food services: 26% eg. US rural household incomes is that agriculture and ≈ 30% OF ALL JOBS Farming: 21% related agribusiness activities are increasingly Food manufacturing being organized into global value chains industry: 13% (GVCs), with organized supply chains displacing Food services: 66% traditional arrangements (Briones and Felipe, ≈10% OF ALL JOBS 2013). Vertically integrated plantations give way to Source: World Bank (2017b). smallholder farm systems, creating an opportunity for rural households to join these supply chains and increase their incomes. The second factor is Ethiopia’s efforts to industrialize, which have seen its increased engagement in GVCs beyond agriculture commodities, which in turn has employment and other spillovers in rural areas. On this basis, this Rural Income Diagnostics (RID) study identifies and focuses on four main drivers of opportunities for expanding rural incomes in Ethiopia. These are: (i) technological transformation in the agriculture sector; (ii) the rise of urbanization and dietary transformation; (iii) growth in global agri-food trade; and (iv) spatial and economic transformation. Each of these drivers is discussed in detail in this section, demonstrating how they directly contribute to rising agricultural incomes and non-agricultural 32 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES The technological frequently occurring weather-related shocks and sustain production (Teklewold, Gebrehiwot, & Bezabih, transformation in 2019; Tesfaye, Blalock, & Tirivayi, 2020). This helps agriculture production to reduce the impact of weather-related shocks on rural households, especially in a country like Ethiopia, where food insecurity has been a major concern. With land a limiting factor for expanding production, technological transformation in Progress is being made on the adoption of agriculture is crucial for increasing productivity improved seed varieties and fertilizers but has through sustainable intensification. Technological been limited on mechanization and irrigation transformation in agriculture production is characterized by: (i) the increased use of advanced In Ethiopia, advances have been made on the physical inputs, such as high-yielding varieties adoption of advanced inputs, signifying the start and improved combinations of fertilizers; (ii) the of technological transformation in agriculture adoption of resource-conserving practices, such as production. Households are increasingly using mixed cropping and zero tillage; (iii) the effective marketed inputs such as fertilizers and improved mobilization of water resources and more efficient seeds (Figure 29). For example, the share of irrigation to reduce rain dependance of agriculture; households applying inorganic fertilizers increased and (iv) the mechanization of the production process, from 49 percent in 2012 to 63 percent in 2019. The which enhances the productivity of labor. The latter adoption of improved seeds is also rising, with one- is essential for labor to exit from agriculture and for third of households in 2019 using improved seeds on labor reallocation to the non-farm sector. their plots, compared with 20 percent of households in 2012. The adoption of fertilizer and improved seeds Technological adoption is also crucial for is higher among farmers with larger landholdings strengthening resilience and adaptation to and generally lowest among the poorest households. climate change. The effects of climate change on Ethiopia are seen through the increased frequency Mechanization is, however, taking off in some of droughts, pests and diseases. Technologies such areas and is expected to be reinforced by the as drought-resilient crop varieties, irrigation and transformation of the rural economy. Recently, conservation agriculture, help farmers deal with imports of combine harvesters and tractors have Figure 29. Marketed input utilization (% of farmers) over time and welfare status and land size, 2019 Adoption trend, 2012-19 Adoption by welfare, 2019 Adoption by land ownership class, 2019 80% 62% 63% 63% 72% 69% 68% 66% 66% 49% 61% 61% 48% 44% 33% 37% 37% 39% 38% 32% 24% 25% 29% 29% 29% 27% 20% 22% 9% 8% 9% 8% 9% 9% 9% 11% 10% 8% 7% 5% 8% 5% 3% 3% 1% 2% 1% 2% 0% 2% 0% 1% 1% 0% 4% 2012 2014 2016 2019 Poorest Q1 Q2 Q3 Q4 Richest Poorest Q1 Q2 Q3 Q4 Richest Expenditure quintiles 2019 Land quintiles 2019 Inorganic fertilizer Improved seeds Irrigation Mechanization Source: Authors’ estimates based on ESS 2011/12, 2013/14, 2015/16, 2018/19. Notes: There is no data on agricultural mechanization for 2011/12. 33 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY increased. One-quarter of the area in Ethiopia that Access to irrigation is expected to expand with is planted with wheat is now harvested by combine increased government investments in this area. harvesters. These have been widely used in the During 2016–21, the Government financed the major wheat-growing zones in the southeast of the construction of small-scale irrigation infrastructure, country. Studies in Ethiopia show that rising rural doubling the irrigated land coverage to about 7 wages and the cost of draft animals are positively percent of total land area by 2021. In the next five correlated with mechanization (Berhane, Dereje, years, with projects such as the Food System Minten, and Tamru, 2017), and that factors such Resilience Project (FSRP), the Government will as rural-urban migration and growth of the non- finance small-scale irrigation infrastructure to farm segments of the rural economy increase rural increase the land covered by irrigation by 48,000 ha. wages, making mechanization more attractive. The planned investments in irrigation in Ethiopia are Small farm sizes and fragmented plots with therefore a major opportunity to raise agricultural their consequent limits in scale, combined with productivity and smallholder farmers’ incomes. lack of access to credit, render the use of some agriculture equipment unfeasible or unaffordable Technological adoption has reaped for smallholder farmers (FAO, 2021), while scarcity productivity gains for smallholder farmers, of foreign currency reduces their supply. The but more can be done experience from Asia, where farm sizes are even smaller and more fragmented, suggests that Technological adoption has improved agricultural mechanization can be increased with improved productivity and incomes. Empirical analysis design of farm machinery and equipment adapted shows that the adoption of input use has contributed to the specific needs of smallholder farmers (e.g., to yields and agricultural growth in Ethiopia. Some smaller farm machinery, such as hand tillers estimate that 20 percent of agricultural growth or hand tractors), coupled with well-developed between 2005 and 2014 can be attributed to rental markets for machinery or the shared use of improved seeds and chemical fertilizers (World equipment through farmer cooperatives (FAO, 2017). Bank, 2020a). A rigorous study by Muleta and Girmay (2021) finds that households utilizing irrigation from Figure 30. Maize yields (kg/ha), 2000-20 small-scale irrigation schemes in central Ethiopia doubled their gross agricultural incomes relative 60,000 to the comparable non-irrigator households. On 50,000 wheat farms in southwest Ethiopia, the adoption of combine harvesters (but not tractors) is closely 40,000 associated with higher yields, seemingly due to 30,000 lower post-harvest losses (Berhane et al., 2017). 20,000 While agricultural productivity in Ethiopia has 10,000 increased, especially for cereals, it remains 0 below potential, and has been stagnant in non- cereal crops and livestock. Maize yields in Ethiopia 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 have increased in the past decades to levels above Brazil Cambodia Ethiopia comparator countries in Eastern Africa (Figure 30). Kenya Uganda Tanzania Vietnam The average yields in cereals production overall Source: FAOSTAT. have more than doubled since 2020. However, the 34 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES yields are significantly lower than aspirational There is significant potential to increase countries such as Brazil, and countries in Asia such productivity further through the intensification as Vietnam, where input application rates have of the use of inputs, since Ethiopia is starting been higher. Analysis of the productivity potential from a low base. Stochastic frontier analysis (SFA) of crops shows that maize yields are 30 percent of shows that the yield gap is mostly explained by low their potential (van Dijk et al., 2020) and wheat is 20 technology adaptation. This is because the increase in percent of potential (Silva et al., 2021). New analysis the use of fertilizer and improved varieties is starting conducted for this report (see Box 2) shows that from such a low base. For example, only 13 percent non-cereal crops such as beans and sesame seeds of land under cereal crop cultivation is covered by are 60 and 42 percent of their potential, respectively. improved seeds as coverage of crops other than The yields for coffee, for example, have been maize is very low, ranging between 2 percent for stagnant in Ethiopia, unlike in Brazil, which had the sorghum and 18 percent for teff. For other crops same coffee yield levels as Ethiopia in 2000, but has such as coffee, uptake of improved varieties remains since managed to double them (Figure 31). very low (Table 8). Table 8: Use of improved varieties by crop (%), 2021 Figure 31. Coffee yields (kg/ha), 2000-20 30,000 Crop Share of Land covered (%) 25,000 Teff 6.74 20,000 Wheat 18.07 15,000 10,000 Maize 56.88 5,000 Barley 5.72 0 Sorghum 1.99 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 Sesame 0.3 Brazil Ethiopia Kenya Coffee 0.68 Uganda Tanzania Vietnam Source: Authors’ estimates based on AAGS 2021. Source: FAOSTAT. Box 2: Estimation of yields potential in Ethiopia using the stochastic frontier technique The Stochastic Frontier Analysis (SFA) is unit, and a component that captures deviations used to measure the plot crop production from the frontier due to inefficiency. efficiency, which is subject to different control variables such as household level, The analysis was conducted using the ESS plot characteristics, rainfall, temperature, 2018/19 data. The technical efficiency (TE) of each and crop suitability indicators. The SFA is plot was estimated and the impacts of MATs on TE used for its ability to distinguish inefficiency of plots were investigated using the Multinomial from deviations that are caused by factors Endogenous Switching Regression (MESR) model beyond the control of the plot manager and after controlling for endogeneity. The analysis was from the frontier. The model introduces also done at the individual crop level to investigate the disturbance term representing noise, the TE and yield gaps of the major crops (maize, measurement error, and exogenous shocks teff, wheat, legumes, coffee and oil seeds) among that are beyond the control of the production the smallholder farmers in Ethiopia. 35 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY The adoption of multiple agriculture technologies the impact of multiple agriculture technology (MAT) on the same plots is especially beneficial adoption on land productivity finds that the use of to farmers compared with the use of the all three technologies in combination increased land technologies in isolation, as currently practiced productivity by three times more than the impact of by most farmers in Ethiopia. While more than adopting soil and water conservation alone, two times 70 percent of plots cultivated by households more relative to the incremental impacts of fertilizer in 2018/19 were covered by at least one of the use alone, and 45 percent more relative to the use improved seed varieties, chemical fertilizers, or soil of improved seed varieties. Similar magnitudes of water conservation technologies, only 6 percent impact are observed on net crop incomes (Table of the plots used all three technologies applied in 9). These impacts were estimated controlling for combination (Figure 32). However, an analysis of the possibility of co-determination of technological adoption and land productivity, and hence provide a Figure 32. Multiple agriculture technology (MAT) rigorous quantification of the impact of MAT adoption adoption (% of plots), 2019 on land productivity (see Box 3). Studies in other All three technologies 0,06 countries also find complementarities between natural resource management technologies and Improved seed 0,10 the adoption of improved seeds and fertilizers (Wainaina, Tongruksawattana, and Qaim, 2016). Chemical fertilizer used 0,32 Soil and water conservation 0,64 Use of improved seed varieties, chemical fertilizers and soil water conservation technologies None of the three 0,30 together increases land productivity technologies by two times more than fertilizer use alone, and 45% more than using Source: Authors’ estimates based on ESS 2018/19. improved seed varieties alone Table 9: Impact of MAT adoption on land productivity and net crop income, 2019 Multiple Agriculture Technology (MAT) Adoption Average Treatment Effects (Ethiopian Birr) MATs Improved Water Chemical Land Net Regime Seed Variety Conservation Fertilizer Productivity Crop Income V1S0F0 ✅ ❎ ❎ 11,529 11,520 V0S1F0 ❎ ✅ ❎ 5,317 5,326 V0S0F1 ❎ ❎ ✅ 8,095 7,706 V1S1F0 ✅ ✅ ❎ 14,374 14,352 V0S1F1 ❎ ✅ ✅ 7,310 6,763 V1S0F1 ✅ ❎ ✅ 15,964 15,358 V1S1F1 ✅ ✅ ✅ 16,735 16,021 Source: Authors’ estimates based on ESS 2018/19. Notes: Estimates based on the multinomial endogenous switching regressions on multiple agriculture technology adoption (at the crop level) on land productivity and crop incomes. 36 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES Box 3: Estimation of the impact of MAT on land productivity and crop incomes in Ethiopia The multinomial endogenous switching regression control for farm type, using the crops growth on model (MESR model) is used to estimate the each plot. adoption and impacts of Multiple Agriculture Technologies (MATs) after controlling for observed Even without exclusion restrictions, the impacts and unobserved heterogeneities. The analysis of MATs on the outcome variables of interest focuses on the adoption and impact of three are expected to be consistent because they are combinations of MATs, namely improved seed estimated separately for the MATs adopters and varieties, soil and water conservation, and non-adopters in the MESR model. However, it is chemical fertiliser. The outcomes of interest are advised to include an exclusion restriction, as the land productivity (value-added per land) and net inverse mills ratio might not sufficiently overturn crop incomes (using an inverse hyperbolic sine endogeneity. Following the literature, the transformation to deal with negative net incomes). selection instruments used in the analysis are distance to input markets, lagged total rainfall, These are estimated using plot-level data from the lagged rainfall shock, and access to extension 2018/19 ESS data. Detailed information is used services. A simple falsification test shows that on plot characteristics, household demographics, the selection instruments indeed jointly and socio-economic status, climatic conditions and significantly affect the MATs adoption model, but crop suitability indicators to condition adoption not the land productivity outcomes, confirming and impacts of MATs. The regression models also the validity of the instruments we used. Technological adoption among rural households 2022) also show that climate shocks disincentivize is primarily influenced by access to input risk-averse households from adopting high-risk, markets, climate and knowledge. Evidence from high-return technologies. the analysis of determinants of MAT adoption shows a negative correlation between distance to market Technological adoption in agriculture and the adoption of any technological packages, generates job opportunities in input including market-based inputs (improved varieties markets and agriculture services and inorganic fertilizers). Thus, adoption rates decline the further the household is from a road or a Agriculture technological adoption generates market, implying access to input markets could be a off-farm jobs when market conditions favor constraint to adoption. The analysis also shows that private sector participation. The production and farmers with access to public extension services distribution of inputs is one source of job creation, are more likely to adopt agriculture technologies with increased demand and utilization of farm packages including fertilizer applicatoin. Those inputs. Jobs can be created in the production accessing private advisory services are more of inputs, such as improved seed varieties and likely to adopt multiple technologies instead of inorganic fertilizers, and the distribution of single agriculture technologies. This suggests that these inputs in the transportation and retail extension services have an important influence on sectors. Under the AGP II, support to farmer the adoption of agriculture technologies. Climate groups to produce and distribute improved factors have a significant influence on farmers’ seeds helped create jobs (World Bank, 2022d). adoption of technologies too, evidenced by lower Other opportunities are created in the provision adoption of agriculture technologies when annual of agriculture services linked to mechanization, temperatures are high. Other studies (Kebede, irrigation and extension services to rural farmers. 37 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Such jobs include the provision of other services, job opportunities. The reforms have generated such as renting, distribution and the repair of investor interest in fertilizer production. The recent agricultural equipment, pest control, etc. success of international investors such as Pioneer in increasing the market share of the improved The opening up of inputs markets in the Ethiopia inputs market in collaboration with cooperatives for could facilitate the realization of job creation seed multiplication shows the potential of opening potential in the production and distribution of the inputs market, not just for improving the variety agriculture inputs. Job creation in input markets and quality of inputs, but also for private sector in Ethiopia had been largely stifled by state generation of jobs. interventions. State-owned enterprises (SOEs) and unions are the main suppliers of fertilizers and The experience in Ethiopia’s primary wheat- seeds, with private sector companies supplying producing zones demonstrates that a takeoff in no more than 4 percent of farming households in mechanization creates an ecosystem of support 2019 (Figure 33). No fertilizer was being produced services that generates off-farm jobs. In major in the country and its supply chain—from wheat-growing zones in the southeast of the country, importation to the farmgate—had long been state where combine harvesters are widely used, private managed. An SOE had the sole mandate to import, mechanization service providers have rapidly and cooperatives are involved in distribution at a emerged for agricultural machinery rental services price set by the Government. This not only resulted for plowing or harvesting. Equipment service centers in limited availability and quality of fertilizers, but are also set up for the repair of tractors and combine limited job creation in the supply chain too. harvesters. Similarly, irrigation development will have substantial job-creating potential as well, Under the economic reforms, the Government through the establishment of shallow groundwater has opened the inputs sector and licensed private drilling enterprises, retailers and distributors, and firms to import fertilizers, which could expand pumps and pipes and pump repair services. Figure 33. Supply source of modern inputs in In sum, rural households in Ethiopia stand to Ethiopia (% of households), 2019 benefit from rising agriculture technological 7 7 4 adoption. These benefits extend beyond the 26 increases in agricultural productivity to off-farm 46 employment opportunities in inputs supply chains 59 and agriculture services. This potential can be 44 maximized through further input intensification, 4 given the low base of input application that Ethiopia 3 is starting from, the adoption of MATs to maximize 43 complementarities, and increased private sector 32 27 participation to realize job creation potential in inputs supply chains, the development of equipment Fertlizier Seeds Agrochemicals rental and sharing markets, and the supply of Public Private Union Other agriculture equipment tailored to the needs of Source: Authors’ estimates based on ESS 2018/19. smallholder farmers. 38 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES in Ethiopia. With an increase in income and The rise of urban urbanization, people shift their consumption from a low-quality diet (e.g., staples) to a high-quality consumption and the and nutritious diet, including fruits, vegetables, dietary transformation and animal-origin items (Bennett, 1941; Gouel and Guimbard, 2019). Consumption also shifts away from unprocessed to processed food The second key driver of opportunities for rural items, including food away from home (Berkum, income growth is increased food demand and dietary Achterbosch and Linderhof, 2017). The dietary transformation driven by urbanization and rising transformation toward high value food items is incomes. The urban population has grown by nearly 60 already evident in Ethiopia, especially in urban percent, or 5 percent annually, since 2010, rising to about areas (Table 10). During the 2014–19 period, the 25 million in 2021 (Figure 34). It is expected to rise to 31 Figure 34. Trends in urban population growth, 2004-21 million by 2025 and 52 million by 2035 (World Bank, 2020). Moreover, urban households have experienced 30,0 faster income growth, resulting in high growth in food 25,0 consumption. According to adjusted estimates from the 20,0 ESS, 2018/19, the average consumption expenditure in 15,0 urban areas grew at about 10 percent per year between 10,0 2014 and 2019. Combined with urban population 5,0 growth, total urban food consumption would have 0,0 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 doubled in those five years. Urban Population (Millions) Urbanization and rising incomes are associated Urban Population Share (%) with dietary changes that are already evident Source: National Bank of Ethiopia Annual Reports (2021). Table 10: Changes in food consumption spending patterns (food budget share), 2014–19 Rural Areas Urban Areas Food item 2014 2016 2019 2014 2016 2019 Teff 0.13 0.11 0.08 0.25 0.18 0.15 Wheat 0.03 0.08 0.06 0.06 0.04 0.03 Maize 0.01 0.09 0.11 0.04 0.03 0.05 All other cereals 0.06 0.12 0.12 0.05 0.03 0.05 Pulses & nuts 0.05 0.11 0.09 0.12 0.10 0.09 Oil seeds - 0.00 0.00 0.00 0.00 0.00 Tubers & stem 0.10 0.06 0.10 0.04 0.03 0.05 Vegetables 0.05 0.11 0.11 0.08 0.15 0.15 Fruits - 0.01 0.01 0.03 0.02 0.03 Dairy 0.06 0.04 0.03 0.04 0.03 0.02 Meat, fish, and Eggs 0.05 0.04 0.02 0.11 0.10 0.08 Fats & oils - 0.06 0.06 - 0.08 0.07 Beverages & stimulants 0.10 0.12 0.15 0.10 0.10 0.11 Condiments 0.05 0.03 0.03 0.07 0.04 0.04 Other foods - 0.01 0.02 - 0.06 0.08 Source: Authors’ estimates based on ESS 2013/14, 2015/16 and 2018/19. Notes: The consumption module was revised in the 2019, and therefore the data are not strictly comparable. 39 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY expenditure share of cereals declined from 40 current demand. These projections highlight that the to 27 percent, while the expenditure share of cereal crops segment will continue to be important, vegetables increased by 8 percentage points, fats though growth rates in non-staple crop segments and oils by 7 percentage points, and other foods are likely to be larger. Animal-origin products— by 8 percentage points. These changes have mostly meat and dairy—will also see a substantial significant implications for farm returns and on- increase in their annual consumption demand by and off-farm employment generation. about US$350 million. In total, the annual demand for food is expected to increase by about US$1.6 billion. Rising urban food demand creates direct Earlier studies (Vandercasteelen, Beyene, Minten and opportunities to increase agricultural incomes Swinnen, 2018b) show similar results. The changes in labor demand are expected to mirror the changes in Higher food consumption and changing dietary production demand. preferences in urban centers will increase urban demand for rural agricultural products. The changes Additional analysis identifies those commodities in demand will increase for some products more with higher growth potential as urban incomes than others (Table 11). In Ethiopia, maize demand is rise, by considering each commodity’s income expected to decline, while teff and wheat—which are elasticity of demand. The demand for items with a more consumed in urban areas—have the strongest positive income elasticity increases as household prospects for increased production demand (of up to a incomes increase, with an income elasticity of 1 US$500 million annually for teff) and income growth. implying a one-to-one relation between changes A larger portion of teff’s increased consumption in household incomes and consumption of the demand will benefit the smallest landholding class product. An income elasticity greater than 1 thus (< 1 ha), while increased wheat demand will benefit suggests a more-than-proportionate increase in the middle land class (2 to 5 ha) more. Respectively, the product’s consumption as household incomes annual demand for pulses and vegetables will rise. Income elasticities were estimated for various increase by nearly US$200 million and US$100 million, food products and food groups in Ethiopia using respectively, which are significant increases from a household demand system, accounting for the Table 11: Forecast change in demand at the farm level (US$ ‘000) Total Total landholding size class < 1 ha 1-2 ha 2-5 ha 5-10 ha > 10 ha Teff 565,852 195,228 164,827 179,438 21,901 4,458 Wheat 222,837 35,356 75,421 87,080 21,143 3,837 Maize -15,967 -4,925 -3,374 -7,348 -245 -75 All other cereals 95,631 23,971 35,679 28,512 7,087 382 Pulses and nuts 193,079 31,703 49,073 96,835 13,511 1,956 Tubers and stems 91,700 56,558 24,664 9,163 1,065 250 Oil seeds and spices 32,430 2,860 4,850 22,267 2,101 351 Vegetables 101,845 68,920 14,969 17,314 269 373 Fruits 30,676 25,807 1,743 2,883 241 2 Dairy 244,467 - - - - - Poultry & eggs 16,683 - - - - - Meat 94,457 - - - - - Source: Tesfaye and Dolislager (2019) in World Bank (2020) based on ESS 2016 and Authors’ estimates for Diary, poultry & eggs and meat. Notes: Projections are based on an assumption of 4.5 percent annual income growth during 2010-25. 40 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES fact that some goods are substitutes, and hence have an income elasticity of greater than 1. Their consumed in place of the other goods, while others consumption in urban areas will increase faster are complements that are consumed together, than urban income growth. such that price and demand for different foods are Table 12: Urban households income elasticity of demand interrelated. A complete demand function model for household consumption, called the Almost Food Items Expenditure Income Ideal Demand Function (AIDS), commonly used for Share Elasticity this purpose in the literature, was thus estimated Teff 0.15 1.148 using the ESS 2019 data for urban households (see Wheat 0.03 0.993 Box 4). The estimated elasticities are presented in Maize 0.05 0.02 Table 12. All other cereals 0.05 0.904 Pulses & nuts 0.09 1.203 Estimates show that consumption of urban Oil seeds 0.00 1.321 households is skewed toward those commodities Tubers & stem 0.05 0.653 with high income elasticities, suggesting greater Vegetables 0.15 0.949 potential for future urban demand growth. The Fruits 0.03 1.519 cereals most consumed in urban areas (teff and Dairy 0.02 0.877 wheat) have a unitary or greater income elasticity Poultry & eggs 0.08 1.559 of demand. In contrast, maize, which has a lower Meat & fish 0.07 1.786 budget share in urban areas than in rural areas, Fats & oils 0.11 1.152 is inelastic, and hence its consumption demand Beverages & Stimulants 0.04 1.145 in urban areas is not expected to grow. Other Condiments 0.08 0.813 nutrient-dense, high value foods constituting the Source: Authors’ estimates using ESS 2018/19. largest portion of the urban consumption basket Notes: Estimates based on Almost Ideal Demand System, im- (meat & fish, fruits, pulses & nuts, and beverages) posing the homogeneity and symmetry restrictions. 41 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Box 4: Estimation of income elasticities of demand The almost-ideal demand system (AIDS) model of Deaton & Muellbauer (1980) is utilized to estimate income elasticities of demand for main agricultural and food commodities. The model considers a consumer’s demand for a set of k food items or broad categories (e.g., teff, wheat, maize, other cereals, meat, etc.) for which the consumer has budgeted m (household income proxied by total household expenditure) units of Birr. The AIDS model gives the expenditure share equation in a k good system as: k ωi = αi + p} ∑ γ ln p + β ln { m ij j,i = 1, ..., k i i=1 where qi denotes the quantity of good i consumed by a household and define the expenditure share for good i as ωi = pi qi / m. αi is the constant coefficient in the ith share equation. The price index is denoted by p, its transcendental logarithmic function (the price deflator of the logarithm of income is) can be estimated as follows k k k ln p = α0 + ∑ αi ln pi + 1 2 ∑ ∑ γ ln p ln p ij i j i=1 i=1 j=1 Deaton & Muellbauer (1980) suggest replacing that price index with the approximation ln p ≈ ∑j ωj ln pj, resulting in a set of equations that can be fit by linear estimation techniques. The following are the resulting conditions imposed during the estimation of the constrained model (the restrictions on the demand functions are deduced from the cost function, using Shephard's duality lemma): adding up, homogeneity, and Slutsky symmetry: ∑k i=1 αi = 1, ∑k i=1 βi = 0, ∑k i=1 γ = 0, and γ = γ ij ij ji The AIDS model has the advantage that the homogeneity and symmetry restrictions are easily imposed and tested. The expenditure share equation can be interpreted as a Marshallian or uncompensated demand function in budget shares. The price elasticities of good i with respect to good j can be derived from the Marshallian price elasticities using the Slutsky equation in elasticities as follows k ( ( ∑ j=1 γ ln p )) 1 ϵij = ⎺δij + γij ⎺ βi αi + ωi ij i where δij is the Kronecker delta, defined as: δij =1 if i = j and 0 otherwise. The expenditure (income) elasticity for good i is computed as βi μij = 1 + ωi 42 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES Most of the increase in urban demand can be met Due to differences in ecologies, the expected locally. Ethiopia still imports grains and oils for its food demand surge will be different across the country, security. Its total food imports were US$1.5 billion in depending on the agro-ecology and households’ 2020. The main imported food products include grains ability to respond to urban demand. Households in (mostly wheat), vegetables oil, fruits, vegetables, meat Amhara and Oromia are the main suppliers of food and milk. However, the share of imports of the food items consumed in urban areas. While more than items with stable or increasing budget shares in 6.8 million smallholders planted teff in the 2020/21 urban areas in Ethiopia is not significant (Figure 35) cropping season, producers in Amhara and Oromia and is mostly met by local production. Compared accounted for 87 percent of the total production in with the total volume consumed in the country in 2020/21, with the East and West Gojjam of Amhara, 2018, less than 2 percent of fruits, about 1.5 percent and the East and West Shoa of Oromia being the of vegetables, and negligible amounts of meat, milk, major teff producing areas in the country. A smaller pulses, legumes and pulses, were imported. Only proportion of teff is also produced in the SNNP and for wheat, which accounted for one-quarter of food the Tigray regions. Amhara and Oromia together imports in 2018, does Ethiopia rely more on a higher also produce 81 percent of pulse crops, while the share of imports for its consumption. SNPP region accounts for 12 percent. Vegetables and fruits are however, mostly produced in the Figure 35. Share of imports in total food supply (%), SNPP region. Lastly, coffee is mostly produced in 2015-18 the Yirgachefe, Sidamo, Kaffa, Harrar, Dimmah and 12% Limu zones in Oromiya and in the SNPP region. 10% 8% Households in Somali and Afar contribute mostly 6% with livestock and animal products. 4% 2% 0% A supply response is needed for more rural Pulses, households to benefit from growing urban demand. Grains Fruits Vegetables Meat Milk legumes & nuts Only a smaller share of output of the most consumed foods in urban areas is marketed in Ethiopia, 2015 2016 2017 2018 exemplified by only 18 percent of teff production Source: FAOSTAT. being marketed (Table 13). One contributing factor Table 13: Households’ participation in production and marketing of food with high urban demand, 2019 Agriculture commodity Share Share Share of Share of Share of land in producing selling output sold land among areas crop is the producers most suitable Maize 0.547 0.02 0.237 0.434 0.471 Wheat 0.253 0.04 0.106 0.422 0.449 Teff 0.392 0.09 0.183 0.467 N/A Other cereals 0.594 0.05 0.260 0.513 0.642 Root crops 0.136 0.09 0.040 0.296 0.138 Fruits 0.114 0.32 0.026 0.233 0.082 Vegetables 0.042 0.16 0.003 0.071 0.016 Oil seeds 0.056 0.27 0.017 0.295 0.202 Coffee 0.259 0.36 0.127 0.489 0.463 Other cash crops 0.271 0.55 0.128 0.475 0.466 Livestock products (Eggs & milk) 0.733 0.12 Source: Authors’ estimates from ESS 2018/19. 43 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY is that a smaller proportion of producers market inputs and services, all the post-farm activities their produce. For example, only about 9 percent of that result in the retailing of food to consumers, teff farmers sold teff during 2018/19. Vegetables such as food storage, processing, distribution, and fruits were sold by only 32 and 11 percent of transportation, retailing, preparation, restaurants, farmers, while pulses and coffee were sold by about and many other services (World Bank, 2017b). The 8 and 9 percent of households producing these non-farm segments in the food system can make crops, respectively. Market participation is also low a significant contribution to job creation during among livestock producers, with only 4 percent of the transition of the food system that Ethiopia has them selling milk produce and about 25 percent entered. In addition to bringing and marketing reporting selling eggs. A second issue is that farmers produce to urban consumers, demand for processed, devote a small share of land to these crops, even in store-convenient foods and the consumption of areas where high value crops are among the top food away from home will also expand non-farm three most suitable crops. Vegetables account for activities, such as food processing, packaging, less than 2 percent of cultivated land in areas most marketing, and food preparation and retail. Initially, suitable for vegetable production, unlike cereals most of these activities will be in the small-scale to which farmers devote between 44 percent (for segments of the non-food system (Allen, Heinrigs, wheat) and 64 percent (sorghum and millet) in areas and Heo, 2018), with long and fragmented value most suitable for their production. chains that can present opportunities for micro, small and medium rural enterprises. Urbanization and unfolding diet transformation will create downstream job opportunities in Indeed, dietary change is expected to drive the agri-food system structural changes in labor demand and employment in the food system and beyond over the Urbanization and changing consumption patterns next decade in Africa. Tschirley, Snyder et al. (2015) will shift employment within the food system, as empirically quantify the employment implications of urban households increasingly rely on markets to diet transformation in East and Southern Africa within meet their food needs. The food system is defined the broader food system and non-food system. They as the whole set of activities required to get food find that the transformation of the food system would onto people’s plates. It extends beyond agricultural add more jobs than any other sector of the economy production and includes the supply of agricultural by 2025 (Table 14). Food services—marketing, Table 14: Evolution of job structure in East and Southern Africa, 2010–25 Jobs in 2010 Jobs in 2025 Contribution Category to total job Number (‘000) Share Number (‘000) Share growth (%) (%) (%) Agri-food systems 81,183 83 106,532 72 51.6 Farming, own wage labor 73,396 75 89,941 61 33.7 Food manufacturing 2,237 2 4,871 3 5.4 Marketing, transport, and 4,704 5 9,688 7 10.1 other services Food preparation away from home 846 1 2,032 1 2.4 Non-agri food system 17,090 17 40,879 28 48.4 Total 98,273 147,411 Source: Tschirley et al. (2015). Notes: Projections are based on an assumption of 4.5 percent annual income growth during 2010-25". 44 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES transportation and other services—will contribute 10 1.4 percent in the rural sector. As yet, there is no percent of total jobs growth between 2010 and 2025, employment related to farm inputs manufacturing assuming income growth rates of 4.5 percent per in rural areas. year, with food manufacturing contributing about 5 percent of new jobs in that time. But the rise in urban food demand has begun expanding job-opportunities beyond primary In Ethiopia a large share of the labor force is still agricultural production in Ethiopia. For example, total employed in the primary agriculture production employment in food manufacturing, food preparation, segment of the food system. Primary agriculture and marketing and transport has more than doubled made up 63 percent of employment in the country since 2013 (Figure 36). Employment in the non-food and 66 percent of employment in the food system segments of the food system will continue to increase in 2021. In rural areas, it made up 77.5 percent of as the share of downstream segments in the food total employment and 79 percent of employment system GDP rises to about 25 percent in 2025 and in the food system (Table 15). Employment in the close to 30 percent by 2040, while agriculture’s share non-farm segments of the food system in Ethiopia in GDP declines to less than 20 percent (Figure 37). is low. The agro-processing industry contributes 2.4 Thus, trends driven by urbanization will spur growth percent of the total national employment and only and employment in the non-farm economy. Table 15: Jobs in the agri-food system, 2021 National Rural Number Share Number Share Primary agriculture 22,211,655 63.3 21,249,693 77.5 Food processing 364,487 1.0 195,195 0.7 Other agro-processing 258,239 0.7 96,313 0.4 Food services 1,955,610 5.6 811,533 3.0 Farm inputs 585 0.0 0 0.0 Total Food System 24,790,576 70.6 22,352,734 81.6 Source: Authors’ estimates from LFS 2021. Notes: For comparability, estimates from LFS 2013 were computed excluding data from Tigray, which was not covered in the LFS 2021. Figure 36. Changes in jobs in the agri-food system Figure 37. Share of agri-food system in GDP, 2010-40 in rural areas (‘000), 2013–21 0 52.9 Share of national total (%) -100 528 3 -200 42.1 -300 -400 28.7 -500 20.5 23.0 -600 16.4 55 -700 -800 -762 -900 Primary Food Food Agri-industry 2010 2015 2020 2025 2030 2035 2040 agriculture processing services - processing wholesale & retail Agriculture-food system GDP share Agriculture GDP share Increase Decrease Total Downstream share of total AFS GDP Source: Authors’ estimates from LFS 2013; 2021. Source: Dorosh and Minten, ED. (2020). Notes: For comparability, estimates from LFS 2013 were computed excluding data from Tigray, which was not covered in the LFS 2021. 45 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY In short, the trends driven by urbanization will areas, but the benefits will be uneven depending not only improve the lives of millions of farmers on agro-ecological zones and households’ ability to but will also spur growth and employment in the change their land use in response to rising demand. rural non-farm economy, creating jobs for the For non-farm jobs, an emergence of small-scale rural youth. For improving farm incomes, a supply enterprises along the value chain will create more response is required to get more households to off-farm jobs, which will be crucial in the transition produce and market products in demand in urban phase of agriculture development. 46 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES Growth in global agriculture exports are concentrated in commodities with greater participation of smallholder farmers agri-food trade (Figure 40). Coffee is the country’s major export commodity, accounting for 69 percent of agriculture The evolution of global agriculture value chains has exports and nearly one-quarter of total exports in provided an initial boost in the agri-food trade, which 2019. It is cultivated by over 4 million households, Ethiopia has benefited from. An OECD 2020 study supporting the livelihoods of about 20 million people estimates that “agri-food value added used to generate in Ethiopia. The country’s second most important foreign exports increased by 123 percent in nominal export is sesame oilseed, accounting for 15 percent terms” in the 10-year period between 2004 and 2014 of agriculture exports and produced by more than 1 (OECD, 2020). Further growth since then has, however, million households. New growing areas of exports, been limited by declining commodities prices. Ethiopia’s such as meat, are primarily produced by smallholder own agri-food exports have moved in tandem with growth farmers too. Third, Ethiopia is fast catching up on some in global trade in food and agriculture commodities. Its rapidly growing agriculture exports such as meat and agriculture exports had risen to more than US$1.5 billion beans. The country’s exports of these products have by 2019 (Figure 38). This has been a boon to Ethiopia’s risen 2.5 and 3.5 times faster, respectively, than the economy, the exports of which are heavily concentrated already high global trade growth in these products. in agriculture products. Agriculture exports still made up The rise of global agri-food trade has therefore about two-thirds of the country’s exports in 2019, despite presented great opportunities for smallholder the rising contribution of garments and textile exports in farmers in Ethiopia to expand their incomes. the past decade. Smallholder farmers will benefit more from Rural smallholder farmers in Ethiopia are primed to global agri-food trade through expanding benefit from the rise of global agri-food trade. First, production, reducing trade barriers, focusing Ethiopia’s exports are concentrated in agriculture on quality and entry into new markets products that have seen high export growth globally. Animal and related products, coffee, oilseeds, and A slowdown in production of some commodities legumes have all seen global trade expansion of over has constrained export growth. While the 40 percent since 2010, while the trade in cut flowers production of many other crops has been rose by 20 percent (Figure 39). Second, Ethiopia’s increasing, both the production of sesame and Figure 38. Trends in global agriculture (US$), 2010-19 Figure 39. Global food trade – key commodities (US$ million), 2010-19 3,00 180 160 2,50 140 120 2,00 100 80 1,50 60 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 1,00 Animal (live and edible Vegetables, fruits and nuts 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 products) Foodstuff (n.e.s) Coffee, tea and spices Sugars and sugar confectionery Oil seeds, oleaginous fruits Hides and Skins World agriculture exports (trillions) Cut flowers and ornamental Cotton Ethiopia agriculture exports (billions) foliage Source: Authors' estimates from COMTRADE. Source: Authors’ estimates from COMTRADE. 47 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY beans—the second- and third-highest agriculture Export controls prevented any maize exports, even exports for Ethiopia—declined by 15 and 40 percent, though maize production has been increasing. respectively, compared with their peak production This has disadvantaged maize producers in two in 2015 (Figure 41). Their exports declined too. The respects. First, global maize exports growth value of sesame oil seed exports from Ethiopia has been very high during the past decade, and declined by more than the decline in global exports Ethiopia’s smallholder farmers completely missed of sesame oil seed. This was driven more by the 25 out on this trade boom (Figure 42). Second, the percent reduction in the quantity of sesame oil seed domestic price of maize has remained depressed, exported than the decline in prices. The decline at levels below international prices. This means in production thus constrained exports. Similarly, that maize producers faced lower prices than they the quantity of beans exports declined (by close to could have otherwise obtained, which is an implicit 27,000 tons), though the export value declined by tax on net producers and a subsidy for consumers. less, as prices remained high. Therefore, reduced Elimination of these controls will provide a boost production represented a missed opportunity for to farmers, as domestic demand for maize is smallholder farmers, as the share of production projected to decline given its low-income elasticity exported declined significantly (Figure 42). in domestic urban markets. Figure 40. Ethiopia’s food trade – key commodities (US$ million), 2010-19 2,000 1,800 1,600 1,400 1,200 800 600 400 200 - 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Live animal Meat Dairy products Fruits and vegetables Coffee Spices Oil seeds Ground nuts Beans Cereals (incl. maize and wheat) Source: Authors’ estimates from COMTRADE. Figure 41. Production index trends (base year = 2015), Figure 42. Share of net exports relative to production 2000-20 for selected crops, 2011-18 140 0,8 120 0,6 100 0,4 0,2 80 0 60 -0,2 40 -0,4 20 -0,6 0 -0,8 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 2011 2012 2013 2014 2015 2016 2017 2018 Beans, dry Coffee, green Maize Sesame seed Wheat Livestock Beans Meat Maize Wheat Source: Authors’ estimates from FAOSTAT. Source: Authors' estimates from GTAP database. 48 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES Ethiopia’s top agriculture exports have been This difference is attributed to the low quality of the losing market share in world trade, pointing to coffee supply and limited value addition, but also additional room for agriculture export growth. by traders offering lower prices to make up for the Ethiopia’s share of exports to the top 10 importers high cost of doing business to comply with stringent of coffee declined from 40 percent in 2011 to 24 marketing rules by the ECX. The reform of the pricing percent in 2019 (Figure 43). The market share for mechanism and marketing rules of the ECX, along sesame in that product’s top 10 import markets also with adoption of improved varieties, could open declined, from 17 to 12.5 percent during the same further opportunities for expanding smallholder period. These declines are a result of stagnation farmers’ incomes from coffee production. in the quantity of exports for coffee and declining production for sesame, pointing to missed market Further off-farm opportunities are created opportunities. Only for beans and meat has Ethiopia in the post-primary production phases of gained market share. agriculture export value chains Nonetheless, there is great potential to increase With linkages to a variety of sectors, agriculture both export values and farmers’ incomes in the export value chains create jobs beyond primary coffee trade by introducing market incentives and production and final product retail. Agriculture infrastructure for premium coffee production. exports generate jobs upstream (logistics and Due to the absence of quality-based payment by marketing) and downstream (e.g., use of fertilizer, the Ethiopia Commodity Exchange (ECX) and limited machinery and extension services) of the primary access to wet stations, wet processed coffee only production stages of the value chain. An analysis by accounts for about 30 percent of coffee exports, the OECD finds that agriculture only accounted for despite carrying a 20 percent price premium in 42 percent of final price paid by consumers for foods export markets. In comparison, wet processed coffee and fiber in developing countries. Services and food accounts for 89 percent of Kenya’s coffee exports processing each accounted for close to one-quarter (Figure 44). Coffee producers in Ethiopia therefore of the final price in 2014 (OECD, 2020). The study also earn a lower margin in the value chain, receiving finds that primary agriculture production made up about 60 percent of the export price compared with 73 percent of the gross value of agriculture exports, Vietnam (95 percent), for example (EIAR et al., 2018). with services making up 14 percent. Figure 43. Ethiopia market share in the top 10 markets Figure 44. Arabica coffee processing method among (%), 2011-19 African exporters (%), 2017 40,0 11 25 53 30,0 64 70 89 20,0 75 10,0 44 36 30 0,0 Coffee Sesame Cut Beans Meat Burundi Rwanda Kenya Tanzania Ethiopia Flowers 2011 2015 2019 Fully washed Semi washed Natural Source: Authors’ estimates from COMTRADE. Source: EIAR et al., 2018. 49 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Downstream processing along other value chains exported. Coffee, diary, and leather processing also helps create jobs if adequate infrastructure and have similar potential. regulatory measures are in place. Though not as pronounced as its comparators, Ethiopia has The increasing use of services along value revealed comparative advantage in the food and chains can drive domestic value-added growth beverage, and textile and apparel sectors (Figure for primary agriculture exports and create jobs. 45)—two sectors linked to agriculture. This points In general, Ethiopia has a low services content in to the potential to create jobs in the processing its exports compared with comparators (Figure segment of agriculture raw materials, from food 46), which suggests that there is an unexploited processing and other inputs such as leather for the potential to increase domestic value addition and apparel sector. However, Ethiopia currently has the the sophistication of its exports. Ethiopia’s services lowest level of backward linkages in textiles and content in exports is around 14 percent, which is on a apparel of any of the countries among the major par with the services export content in the agro-food textile and apparel exporters by a wide margin. trade. However, the domestic services content of its Some agri-food subsectors are showing promise, export is very low, at around 5 percent. Embedding though. For an example, livestock products exports more domestic services in agro-food exports, such from Ethiopia have shifted from live animals to as quality control, extension services, marketing, and meat exports, which are a packaged product. In financing, could also help increase aggregate returns 2010, US$14 million out of the US$41 million that for producers through gains from improvements Ethiopia generated from exports of live animals and in quality, even though they may capture a lower livestock products came from live animals’ exports. share of the price. That services are consumed By 2019, meat exports accounted for US$87.5 domestically suggests the potential for job creation million, while live animals’ exports dropped to in the services sector supporting primary exports. just US$780,000. Improvements in supportive infrastructure, such as cold chains and food safety Ethiopia's services content standards, will significantly boost the potential exports is around for job creation along this value chain, given that meat exports are a growth product for which only a 14% small portion of local production is currently being Figure 45. Revealed comparative trade in goods, 2015 Figure 46. Share of services value in exports, 2015 3 Ethiopia - food and beverages 2,5 Ethiopia 2 RCA score 1,5 0,98 Cambodia 0,84 0,67 0,64 0,59 1 0,6 0,6 0,49 0,5 Tanzania 0 Bangladesh Ethiopia 2000 Ethiopia 2015 Cambodia Rwanda Tanzania Uganda Vietnam Uganda Vietnam Electrical and machinery Food and beverages Metal Products Other manufacturing 0 0,1 0,2 0,3 0,4 0,5 Petroleum, chemicals, etc. Textiles and apparel Transport equipment Wood and paper Domestic services Foreign services Source: World Bank 2022a, based on WITS, UNCTAD-TRAINS data. Source: World Bank 2022a, based on WITS, UNCTAD-TRAINS data. 50 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES Addressing barriers to trade is key for Ethiopia, however, has many export controls and high integration into global agriculture value chains food and beverage tariffs, and hence stands to gain from boosting agri-food trade through further trade Improvements in food safety and traceability liberalization. Non-tariff barriers to trade in Ethiopia will be key to integration into global agriculture are raised by export controls. There are about 139 value chains. Non-tariff measures, mostly related export control measures in place, higher than Cambodia to sanitary and phytosanitary (SPS) measures and or Bangladesh, though lower than Vietnam (Figure technical measures (TBTs) such as standards, tend 47). As the case of maize shows, export controls can to be higher for agriculture and food products. have a discouraging effect on trade, preventing rural These provide assurances of quality to consumers. households from gaining from growth in global agri- Producers that can meet these requirements food trade. Furthermore, high tariffs on imports (Figure are therefore able to access high-value markets. 48) could inhibit the country’s own exports if matched Recent changes in China’s export standards and by trade partners, and also slow down the development requirements for coffee, which caught several of local industries by increasing the costs of inputs. The exporters in Ethiopia unawares, demonstrate the country and, consequently, rural households stand to importance of meeting high standards for tapping benefit from trade reforms, as simulations of alternative into export markets. An ability to demonstrate that reform scenarios suggest (World Bank, 2022a). producers can meet the standards through strong food safety measures, improved certification and In sum, the rise in global agri-food trade is creating traceability will open access to new high-value opportunities for rural households in Ethiopia to markets. For other opportunities, such as specialty increase their incomes directly in agriculture, and coffee, traceability and certification are pre- by creating non-farm jobs. Further gains will be made requisites for recognition and generating a premium through the elimination of harmful export controls, for the products. Ethiopia has more SPS and TBTs such as the maize export ban, and increasing domestic than most of its comparators other than Vietnam production of key products to recover lost market share (Figure 47). However, it is important to ensure by implementing productivity enhancing interventions, these are aligned with major export markets, to for example, those promoting the adoption of improved reduce the costs and build capacity for efficiently varieties to increase yields, to stem the stagnating enforcing them, otherwise they will merely become production of key export products. Reforming the impediments to trade. incentive structure and investing in the necessary Figure 47. Number of non-tariff measures, 2017 Figure 48. Food and beverage tariffs (%) 900 28,0 25,3 800 22,7 24,0 21,8 700 20,0 600 20,0 18,5 500 16,0 400 12,0 12,0 300 200 8,0 100 4,0 0 Bangladesh Cambodia Ethiopia Vietnam 0,0 Vietnam Cambodia Bangladesh Tanzania Uganda Ethiopia Pre-shipment inspection Price controls Other measures Quality controls Sanitary and phytosanitary Export controls Technical barriers Source: World Bank 2022a, based on WITS, UNCTAD-TRAINS data. Source: World Bank 2022a, based on WITS, UNCTAD-TRAINS data. 51 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY infrastructure to encourage quality production and food and beverage, and textile and apparel sectors, processing will both help increase farmer returns, there is an unexploited potential to increase domestic while also creating off-farm job opportunities. Though value addition and the sophistication of exports and, Ethiopia has a revealed comparative advantage in the consequently, returns to producers. 52 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES Spatial and economic Export-oriented firms create more jobs on average. In the garment sector, exporters transformation employed more than 1,000 workers per firm in 2017 compared with about 71 workers per Rural areas supplied labor to fill jobs firm among non-exporting firms (Figure 50). created during Ethiopia’s expansion of Exporting firms in the food and beverages sector urban based export industries on average employed four times more workers per firm than non-exporting firms in the sector. The Government’s thrust to boost export-oriented While fewer in number than non-exporting manufacturing through investment in urban-based firms, in some sectors exporting firms employ industrial parks has contributed to employment more workers. generation. The number of manufacturing firms Figure 49. Number of workers and firms in the quadrupled in two decades to just over 2,000 firms manufacturing sector in Ethiopia: 2000–17 in 2017, with sharp increases in the number of firms observed around 2007 and 2016. The number 200,000 10,000 180,000 9,000 Number of workers of permanent workers in the sector tripled in this 160,000 8,000 Number of firms 140,000 7,000 period (Figure 49). A cross-country analysis by Pahl, 120,000 6,000 Timmer, Gouma, & Woltjer (2019) finds evidence of 100,000 5,000 80,000 4,000 major job creation due to Ethiopia’s participation 60,000 3,000 in GVCs between 2000 and 2014. The country’s 40,000 2,000 20,000 1,000 job growth was strongest among the four African 0 0 2000 2002 2004 2007 2009 2013 2015 2017 countries in the study, and nearly as much as in Vietnam and Bangladesh. However, the backward linkages have so far been limited, and hence indirect Number of workers (left axis) Number of firms (right axis) job creation has been modest (Ndiaye et al., 2021). Source: Ndiaye et al. ( 2021). Figure 50. Comparison of Ethiopian firms’ metrics by export status, 2017 Total firms Ave. value added per firm Ave. workers per firm Foods & Not exporter 584 Foods & Not exporter 139 Foods & Not exporter 63 beverages beverages beverages Exporter 24 Exporter 1,592 Exporter 299 Textiles, Not exporter Textiles, Not exporter Textiles, Not exporter 278 126 71 apparels & apparels & apparels & leather Exporter 36 leather Exporter 446 leather Exporter 1,044 Plastic & non- Not exporter 512 Plastic & non- Not exporter 126 Plastic & non- Not exporter 70 metallic Exporter 4 metallic Exporter 367 metallic Exporter 121 Not exporter 159 Not exporter 202 Not exporter 93 Basic metals Basic metals Basic metals Exporter Exporter Exporter Other Not exporter 449 Other Not exporter 88 Other Not exporter 58 manufacturing Exporter 6 manufacturing Exporter 68 manufacturing Exporter 70 0 200 400 600 0 200 400 600 800 0 500 1,000 1,500 Firms Thousand Birr Workers Source: World Bank 2021, based on the Large and Medium Manufacturing Enterprises Survey (LMMS, 2017). 53 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Export firms established in urban areas mostly to estimates from the LFS 2021. Rural-urban employ migrants, as surveys at industrial parks migrants account for a large share of migrant across the country confirm. About 70 percent of flows in Ethiopia, even though a considerable workers in the Bole-Lemi Industrial Park were recent share of urban migrants also moved from other migrants to Addis Ababa (Abebe, Buehren, and Goldstein, urban areas (Figure 51). More than one-third of 2020) and 52 percent of workers in the Hawassa recent migrants, defined as those who migrated Industrial Park were born outside the Hawassa zone to their destination areas during the most recent (Meyer, Hardy, Witte, Kagy, and Demeke, 2021). Thus, five-year period, relocated from rural to urban rural areas are a major source of labor for urban-based areas. Thus, close to 2 million people moved from firms participating in GVCs. Evidence also suggests rural to urban areas within the five years prior to that these jobs present first time opportunities for 2021. This number has been increasing over time. people without prior formal work experience. Oya and Schaefer (2020), for example, find that 46 percent Migrants from rural areas tend to be younger and of workers in industrial parks in their study did not better educated than non-migrants, especially have any previous formal work experience and the job those migrating to urban areas. With an average was a first factory job for 58 percent of the workers. age of 27 years, the typical rural-urban migrant Increased participation in GVCs by urban-based firms is nearly 10 years younger than the typical non- generates high job demand that has so far been migrants they leave behind, most of whom are largely filled by rural migrants. illiterate. More than half of the rural non-migrant adult population has never been to school, one- Rural-urban migration is a pathway to third dropped out of primary school and just 2 employment for better educated rural youth percent have at least secondary education. In contrast, close to half of rural-urban migrants have A substantial number of people are migrating at least completed primary school, with 18 percent from rural to urban areas. More than half of having completed secondary or post-secondary the urban population in 2021 - about 10 million education (Figure 52). This suggests that rural- people - were born outside their zone, according urban migration is an outlet for the more literate Figure 51. Migration flows: the number of recent Figure 52. Education status of recent migrants, 2021 migrants, 2005–21 6,000,000 100% 5,000,000 80% 4,000,000 60% 3,000,000 40% 2,000,000 20% 1,000,000 0% Rural: Rural-rural Rural-urban Urban: - Non-migrant migrant Non-migrant 2005 2013 2021 Completed post-secondary Completed secondary Rural - rural Rural - urban Completed primary Less than primary Urban - rural Urban - Urban No education Source: Authors’ estimates from the LFS 2021. Source: Authors’ estimates from the LFS 2021. Notes: Estimates for 2021 exclude Tigray, which was not Notes: Estimates for 2021 exclude Tigray, which was not covered by the survey due to conflict. covered by the survey due to conflict. 54 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES youth in rural areas, especially women, who made Figure 53. Reason for migration among rural-urban up 60 percent of the rural-urban migrants. migrants, 2021 100% Most rural-urban migrants moved in search of better economic opportunities, especially women. Close to 80% 54 percent of all adults and 65 percent of adult women who migrated five years prior to 2021, moved for 60% economic reasons (Figure 53), either in search of a job or due to limited access to land. Rural-urban migrants are equally as likely to be economically active, employed 40% and in non-agriculture work as urban residents, but are more likely to be in wage employment (Table 16). 20% However, a disproportionate share is in engaged in domestic wage work (17 percent compared with 5 0% All adults Male Female percent among non-migrant urban residents). Thus, Economic Education Family related Shocks Others migration offers a pathway to employment for rural Source: Authors’ estimates from the LFS 2021. residents, mostly the youth with better education, Notes: Estimates for 2021 exclude Tigray, which was not covered by facing limited opportunities in rural areas. the survey due to conflict. Table 16: Labor market outcomes of migrants, 2021 Labor Market indicator Rural: Non-migrant Urban: Non-migrant Rural-urban migrant Active 74% 71% 74% Unemployed 6% 18% 20% Sector of employment Agriculture 79% 13% 13% Industry 3% 17% 20% Services 18% 70% 68% Employment type Wage employee 4% 45% 53% Self-employed 58% 42% 35% Unpaid family 37% 11% 10% Employer 0% 1% 0% Others 1% 1% 1% Source: Authors’ estimates from the LFS 2021. Notes: Estimates for 2021 exclude Tigray, which was not covered by the survey due to conflict. 55 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Rural-urban migration brings essential, Migration is linked to favorable changes to rural positive effects on rural transformation land and labor markets that facilitate rather than inhibit the transformation of the agriculture Rural-urban migration also has positive benefits sector and the rural economy. Estimates based to originating households and communities. on statistical matching techniques (see Box 5) find Migrants send remittances, which are an important a positive impact of migration on both intensity of source of livelihoods among recipient households. labor use, agriculture output per capita and land The average amount of remittances received by rental markets (Table 17). Migration increases households in 2016 was equivalent to 31 percent family labor days worked and output per capita of recipient household consumption expenditure in migrant-origin households compared with non- nationally and 70 percent among the bottom quintile migrant households by 28.6 and 18.3 percent, (World Bank, 2020b). Other research suggests that respectively. This implies that migration reduces recipient households also improve investment, disguised unemployment in rural areas. It raises both in human capital and physical capital, and the subsistence wage in the rural economy, a encourage greater risk-taking behavior. process necessary for the commercialization of a backward agriculture-based rural economy in With a rising rural population, rural-urban convergence with the modern sector, according to migration, and urban development, are essential the Lewis development model. The rising output per for facilitating rural economic transformation. The worker suggests migration enables the remaining rural population expanded by more than 20 million people since 2004, and by 11 million in the past Figure 54. Trends in household land ownership (ha), 2006–20 decade alone. With a total fertility rate of around 5.2 in 2016, the rural population will keep expanding, 1,25 1,23 increasing pressure on land. The average land size 1,18 1,17 1,14 per household has declined from 1.25 ha in 2006 1,07 to 0.89 ha in 2020 (Figure 54). The challenges of 0,92 small land sizes on agricultural productivity can 0,89 be mitigated by land consolidation interventions such as the agriculture commercialization cluster approach championed by the Government, but that has its limits. The movement of people from rural 2006 2012 2013 2014 2015 2016 2017 2020 to urban areas will be essential to relieve the land pressure and transform the agriculture sector. Source: Authors’ estimates from AAGS 2006, 2012–20. Table 17: Impact of migration on factor markets in origin communities Statistics Cultivated land Land Family labor supply Value of crop harvest (ha per capita) rented out (days per capita) (Ethiopian birr per capita) Average Treatment Effect 0.065** 0.012** 120** 938.5** on the Treated Standard Errors 0.001 0.017 21.302 369.5 97.5% Confidence Interval (0.045; 0.083) (-0.024; 0.042) (79.958; 161.455) (235.67; 1678.94) Source: Authors’ estimates based on ESS 2011/12; 2013/14; 2015/16. Notes: (a) Cultivated land per capita is the area per hectare that the household utilized for crop production. (b) Land rented out is the share of households renting/sharing out agriculture land. (c). Value crop harvest is the Ethiopia birr value of the total production. ** result statistically significant at the 5 percent level 56 THE BIG PICTURE: KEY DRIVERS OF OPPORTUNITIES FOR ENHANCING RURAL INCOMES household members in migrant-origin households GVCs. This also generates positive spillovers in to adequately feed off their land. Second, migration the rural agriculture sector, where land pressure increased the share of households that rented out has risen due to an expanding population. Rural- land by 1.2 percentage points, translating into a 6.6 urban migration helps to relieve this pressure by percent increase in the amount of land rented-out. It improving the efficiency of land markets as land has increased the rent-in rates among non-migrant rent-outs increase among migrant households, households by 1 percentage point. Thus, migration and reducing disguised unemployment, resulting improves the efficiency of the land markets too. in increased output per worker and labor productivity in rural areas. In other words, To summarize, rural-urban migration and by absorbing rural labor, the development of urban development are both a pathway to urban-based export industries has significant gainful employment for the rural youth facing development impacts for the rural economy by limited opportunities and a catalyst for rural providing opportunities for the inexperienced transformation. Opportunities for migrants are rural youth, while at the same time aiding the expanding with jobs created in urban based transformation of the agriculture sector instead export industries, as Ethiopia integrates into of holding it back. Box 5: Estimation of the impacts of migration on factor markets Analysis of impacts of migration on factor This analysis includes covariates that can affect markets uses a balanced panel dataset based the probability of migration and outcomes on the ESS for 2011/12 (wave 1), 2013/14 (wave to eliminate biases due to variable selection. 2) and 2015/16 (wave 3). The study considers The model includes household demographics, migration experience at the household level. The human and social capital, liquidity constraints, study tracked households and their member from and financial capital of the households. Drought wave 1 to wave 3 and identified members who shocks and distance to local administration moved out to other places during the household are controlled at village level. Standardized visits in wave 2 and wave 3. Households with at Precipitation Evapotranspiration Index (SPEI) least one household member aged 10 years or is applied to estimate the level of drought above who moved, are defined as a household shock at village level. The main purpose of with migrants. Using this definition of a migrant matching was to break the link between household, the impacts of migration on land migration and the premigration covariates. The and labor utilization, as well as output per original households without migrants are not capita, in migrant households is estimated comparable with households with migrants. using a propensity score matching technique The preprocessing produces statistically to correct for imbalances in baseline covariates similar propensity scores distribution for the between households with and without migrants. households with and without migrants (see This is used to construct a counterfactual chart). Households with and without migrants group statistically similar to the with migrant need to be similar in every value, except households from the pool of without-migrant having sent out a household member to other households’ data. The matching strategy involved locations. The standardized bias was computed a ‘Nearest Neighbor’ matching estimator with to test whether balance improved for each replacement among propensity scores within a covariate. The preprocessing assures that preferred caliper of 0.05 and radius of 2. balance improved for all household covariates. 57 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Propensity score distribution in the original and matched groups and overlap condition Raw Treated Matched Treated Proportion Proportion 0.15 0.15 0.00 0.00 0.0 0.2 0.4 0.6 0.8 0.0 0.2 0.4 0.6 0.8 Propensity Score Propensity Score Raw Control Matched Control Proportion Proportion 0.20 0.15 0.00 0.00 0.0 0.2 0.4 0.6 0.8 0.0 0.2 0.4 0.6 0.8 Propensity Score Propensity Score Source: Authors’ estimates based on ESS 2012. 58 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES 59 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Increasing the market as market participation consumption decisions are often jointly made within a farm household’s orientation of rural production framework. agricultural households Though it involves trade-offs, market participation enhances household welfare Linking rural households to input and output of rural agricultural households in Ethiopia. agricultural markets and their participation in markets contributes toward improving the Farmers’ market-orientation decisions can be livelihoods of rural populations. Agricultural best understood in the context of balancing commercialization is viewed as pathway toward the trade-off between food self-sufficiency economic growth and development for many and specialization for market production in agrarian economies (Timmer, 1997). It entails the face of incomplete markets. Studies have physical access to markets and actual market used the agriculture household model (AHM) participation (the sale of agricultural produce and to conceptualize rural households’ decision- the purchase of agricultural inputs). Commercial making in both perfect and incomplete markets. transformation will link rural households to input In the model, the agricultural household is both and output agricultural markets, and thus help a producer that chooses the allocation of labor contribute toward improving the livelihoods of and other inputs to farm production, and a the rural population (World Bank, 2012). Previous consumer that chooses the allocation of income research on Ethiopia suggests that there is huge from profit and labor sales to the consumption of potential to boost rural households’ incomes through goods and services (Singh, Squire, and Strauss, the diversification of production into high value 1986; Taylor and Adelman, 2003). The household crops and increased participation in agricultural maximizes utility through the consumption of all (input and output) markets (International Livestock available commodities (i.e., home-produced goods, Research Institute [ILRI], 2020; Wakeyo, Kuma, market-purchased goods, and leisure), subject to Mekonnen, and Ageba, 2017). Therefore, higher households’ budget constraints determined by net market participation is translated into higher farm revenues from agriculture and wage labor, which incomes and household welfare. are a function of agriculture production levels and input prices, including wages, farmgate prices, This section of the report showcases how and market prices for food and other commodities. increasing the market orientation of rural At the core of the AHM is whether households’ households can contribute toward improved production, consumption and labor supply livelihoods and welfare of the rural poor in decisions are simultaneously determined, or Ethiopia. Evidence based on rigorous empirical whether these decisions are taken independently models is presented to show that the participation of each other. If rural households have access of rural households in both input and output to input and output markets, then prices are markets increases real consumption per capita, exogenous, resulting in an independent decision- demonstrating that markets have the potential making process (Roe and Graham-Tomasi, 1985). to boost rural household incomes, enabling As such, production decisions (input use, the households to break out of poverty traps. The key adoption of farm technology and output choice) constraints to smallholder market participation affect consumption exclusively via income levels, are identified based on econometric analysis of and production decisions are entirely independent the determinants of households’ land use choices of consumption. But with rural households in and the determinants of market participation. Sub-Sahara Africa, Ethiopia included, confronted The latter is jointly estimated with the impact of with serious challenges related to market market participation on household consumption, access and participation due to lack of roads and 60 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES transportation infrastructure (Årethun and Bhatta, self-sufficient instead, producing food for their own 2012; Jacoby, 2000; Wudad, Naser, and Lameso, consumption irrespective of whether such food 2021) and supply chain and price information items are the most profitable for their farms. Their (Anderson, 2003; Hamill, 2017), production and choice is determined by their perceived net welfare consumption decisions tend to be made jointly. gains from the two options, given the risks, costs and expected returns from market participation. For rural farmers in Ethiopia, a joint decision on production and consumption introduces a trade- Empirical evidence suggests that the benefits of off between producing for own consumption market orientation outweigh the trade-offs for and producing for the market. Consumption self-sufficiency. For the purposes of analyzing patterns between rural areas and urban areas, whether market orientation brings net benefits which are a major target market, are different to households, an empirical investigation of the (Figure 55). Rural households primarily consume impact of market participation on household maize, and other cereals such as sorghum and consumption in Ethiopia was undertaken for this millet, tubers and stems, which urban households RID. The analysis uses statistical techniques that spend a smaller proportion of their food budgets account for the possible factors that influence the on, in addition to having a low income elasticity decision of households to participate in the market, of demand, hence limited demand potential. Thus, for example, how much surplus they produce or farmers have to weigh the trade-off between being their level of education. These factors may directly more market-oriented—maximizing income by influence households’ income-generating capacity producing the most profitable products for their and, hence, their consumption, irrespective of land, then acquiring food in the market—or being their market-participation decision (see Box 6). Figure 55. Food item share in household consumption (%), 2019 15,5% 4,9% 11,3% 9,0% 7,8% 6,6% 6,9% 5,3% 4,8% 4,6% 3,2% 3,6% 2,7% 2,3% 1,3% 0,3% Teff Wheat Maize All other cereals Pulses & nuts Oil seeds Tubers & stem Vegetables Fruits Dairy Poultry & eggs Meat & fish Fats & oils Beverage & stimulants Condiments Other foods Rural Urban Source: Authors’ estimates from ESS 2018/19. 61 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY The results show a positive benefit (close to 50 Figure 56. Impacts of commercialization on consumption percent) from market participation on 20 percent per capita, 2019 or above of rural incomes, especially for the consumption expenditure 10.4 Predicted per capita poorest households. A percentage increase in the 10.2 commercialization index (CI) of rural farmers in 10 Ethiopia increases per capita consumption by 11 9.8 percent (Figure 56), but only among crop producers. 9.6 The increase in per capita consumption is greatest 0 .2 .4 .6 .8 1 among the poor. The share of caloric intake from Commercialization Index (CI) non-staples increases with market participation. Household CI Crop CI Livestock CI More commercially-oriented rural households are Source: Authors’ estimates from ESS 2018/19. observed to have a higher protein, iron and vitamin Notes: The inverse hyperbolic sine (IHS) transformed per capita intake too (Table 18). The positive impact of market consumption is plotted against the Commercialization Index (CI) based on predicted estimates from Recursive Bivariate Regression models participation on both consumption and nutrition of market participation and household consumption per capita using outcomes shows a favorable trade-off between ESS 2018/19. A positive relationship is also found in estimates using self-sufficiency and market orientation. Endogenous Switching and Instrumental Quintile Regression Models. Table 18: Relationship between crop commercialization and nutritional outcome of households Commercialization Index N Mean Kruskal- Asymp. Sig (CI) level Rank Wallis H Energy intake from non-staples calorie/ No sale 1505 1240 8.89 0.010 day/Adult female equivalent (AFE) Below mean CI 595 1252 At least equal to mean CI 424 1358 Protein intake gm per AFE per day No sale 1505 1197 30.59 0.000 Below mean CI 595 1352 At least equal to mean CI 424 1370 VA intake per AFE per day No sale 1505 1157 104.7 0.000 Below mean CI 595 1317 At least equal to mean CI 424 1559 Source: Authors’ calculations from ESS 2018/19. Box 6: Estimation of determinants of market participation and its impacts on household welfare The empirical analysis in recent studies participation. Accordingly, this report applies the explores market access and participation ESR model to capture the presence of unobserved by using three sets of models: Endogenous variables that influence both the decision of Switching Regressions (ESR), Recursive rural households on market participation and Bivariate Regression, and Smoothed their welfare. The use of the ESR model in this Instrumental Variable Quantile Regression study is justified for two main reasons. First, models. These models look at variables related causal inference methods, such as propensity to how the road network and accessibility score matching and inverse probability weighted influence marketing and transaction costs that regression adjustment (IPWRA), which control then determine households’ market access and for only observed heterogeneities (observable 62 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES household characteristics), result in biased family size, access to credit, access to private treatment effect estimates due to unobserved and/or social transfers). Given that the ESR heterogeneity. Second, the ESR model is an model (discussed in previous slide) may suffer appropriate specification to construct accurate loss of information in the selection equation due counterfactuals for households in the two groups to aggregating a continuous commercialization to identify the causal relationship between index variable into binary, this paper also uses market participation and the outcome variables a maximum likelihood estimator of continuous of interest. Unlike the instrumental variable outcome with a continuous endogenous regressor models (such as two-stage least squares [2SLS] under the recursive bivariate regression (RBR) and control function estimations), the ESR model model, to improve causal inference on the effect is the most flexible causal estimation method of market participation of rural households on that minimizes cross-sectional modeling errors, their per adult real consumption expenditure. The which may arise due to the assumption that RBR jointly determines equations per adult real the effects of observable and unobservable consumption expenditure of rural households household characteristics are the same for all against market participation of rural households farmers, by allowing two separate specifications as measured by commercialization index. for households below and above mean commercialization index. The SIVQR estimator of Kaplan and Sun (2017) , which is similar to the two-stage least squares In this model, the determinants of market estimator in terms of specifying exclusion participation are estimated by regressing the restriction for the endogenous regressors, latent variable representing the propensity of was also used to specify a quantile level. households’ market participation above the In this model, instead of assuming that every mean commercialization index (Pi*) on a vector rural household has the same coefficients β1 of household characteristics (such as the gender as noted in the ESR model, each household was of household heads, age in years of household assumed to have its own coefficient vector b, heads, literacy status of household heads, differing by household. Despite its positive welfare impacts, the Figure 57. Rural households market orientation market participation of rural farmers is 1,0 low as land cultivation choices are inclined 0,9 0,8 toward rural staples consumption 0,7 0,48 0,6 0,5 0,27 The level of market participation among Ethiopian 0,23 0,4 0,13 farmers remains low, depending on farmers’ 0,3 0,09 0,09 0,05 0,04 0,2 0,02 production choices. The overall commercialization 0,1 index of households in rural Ethiopia is around 0,0 Maize Wheat Teff Other cereals Root crops Fruits Vegetables Oil seeds Cash Crops 17 percent, implying that rural farmers’ sales of agricultural produce equate to about 17 percent of their output value. Households that produce staples market the lowest share of their output (Figure Share of households growing the crop 57), while producers of cash crops and the foods Cultivated land share - among growers only most consumed in the urban areas generally sell Share of marketed output more of their output. The commercialization rates Source: Authors’ estimates from ESS 2018/19. 63 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY of maize are 2 percent and other cereals—millet Agriculture potential is a very important factor and sorghum—less than 5 percent, while teff’s in crop choice. The share of area cultivated by commercialization index of 9 percent is better crop and agroecological zones shows that teff is than other cereals. Cash crops—coffee and khat— commonly produced in high agriculture potential are highly commercialized, followed by oil seeds, areas in highland regions, while maize is more and then fruits and vegetables. The degree of commonly produced in high agriculture potential market participation is to some extent determined areas in lowland regions. Households in drought- by farmers’ production choices between staples prone highland areas devote more land to cultivation consumed in rural areas and crops in high demand of other cereals, such as sorghum and millet, in domestic urban markets or global markets. while those in lowland drought-prone areas and the highland enset⁴ ecological zones devote more There is a general mismatch between what land to roots and tubers (Figure 59). An empirical most rural farmers produce and the food items investigation of determinants of households’ land with a higher demand potential in urban or use choices between maize, wheat, barley, teff, fruits global markets. Households, particularly the (as a group), other cereals (sorghum and millet), poorer ones, are primarily driven to meet their cash crops, root crops and oil seeds accounting subsistence demands. The evidence from the for the interdependency of land use choices across study shows that much land use allocation is crops within households, market access, prices oriented to staple food production, maize, cereals, and farmer knowledge, among others (see Box and roots and tubers. As such, poor households 7), confirms that land suitability is an important are less likely to produce for the market, as shown determinant of how much land households devote in Figure 58. Rural households at the bottom of the to different crops. Households devote a significantly income distribution are more likely to engage in higher share of land to the most suitable crops in maize and root crop production, and less inclined their areas, by about 36.4 percentage points for to produce for the market compared with their maize, 49.6 percentage points for wheat, and 40.9 richer counterparts. percentage points for coffee. Figure 58. Share of cultivated land by crop and Figure 59. Share of land allocated to cash crops by income group (%) ecological zones (%) Moisture reliable, highland-Enset Moisture reliable, highland-Cereal Humid moisture reliable, lowland Drought prone, low- land, Pastoralist Drought prone, highland 0% 50% 100% Poorest Q2 Q3 Q4 Richest Cash crops Fruits Vegetables Oil seeds Teff Wheat Maize All other cereals Roots & tubers All other cereals Maize Pulses & nuts Roots & tubers Oil seeds Wheat Teff Vegetables Fruits Cash crops Spices Source: Authors’ estimates from ESS 2018/19. Source: Authors’ estimates from ESS 2018/19. ⁴ Enset (Ensete ventricosum), also known and the Ethiopian or “false” banana, is a member of the same botanical family as the banana, but unlike its cousin it is not grown for its fruit. 64 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES The primacy of food self-sufficiency drives rural devote less land to all other crops. However, farmers’ land use choices and government smallholder farmers do not reduce the share attention toward production of staples of land devoted to maize or teff, even when their land is more suitable for market-oriented crops The self-sufficiency motive to produce staple such as fruits and coffee, instead of another cereal crops overrides considerations for land suitability crop such as barley (Table 19). The higher land for market-oriented non-staple crop production. share devoted to the most suitable crop in these There is an asymmetric response to land use instances is achieved by reducing production of depending on the suitability of major staples such the other market-oriented crops, i.e., when coffee as maize. When the land is most suitable for the is the most suitable crop, farmers use more land production of cereals such as maize, households for its production in place of fruits and oil seeds Table 19: Relationship between crop commercialization and nutritional outcome of households Change in share of land devoted to crop (proportion) Land Suitability for Each Crop Maize Wheat Barley Teff Fruits Other Cash Root Oil Cereals Crops Crops Seeds Maize Suitability: Yes 0.364 -0.017 -0.024 -0.079 -0.015 -0.128 -0.099 -0.025 -0.020 Wheat Suitability: Yes -0.073 0.496 -0.030 -0.105 -0.009 -0.099 -0.084 -0.009 -0.019 Barley Suitability: Yes -0.093 -0.024 0.625 -0.095 -0.012 -0.084 -0.154 0.005 -0.030 Fruits Suitability: Yes -0.004 -0.038 0.012 0.009 0.096 -0.076 -0.162 -0.033 -0.025 Coffee Suitability: Yes -0.005 -0.032 0.003 -0.021 -0.085 -0.076 0.406 -0.048 -0.019 Source: Authors’ estimates from ESS 2018/19. Notes: Seemingly Unrelated Regression results. Coefficients in green font are not statistically significant. Box 7: Estimation of determinants of land use choices among rural smallholder farmers in Ethiopia The determinants of land use choices are The analysis is conducted at the landholder analyzed using a Seemingly Unrelated level using the ESS 2018/19 data. The Regression (SUR) framework. Unlike Ordinary regressors are categorized into demographic Least Squares (OLS), the SUR analytical (gender, education, household size), credit framework acknowledges the non-zero access, land sale rights and landholder age correlation between the error terms of the and market (prices of different crops, prices individual equations that define the factors relative to nearest regional capital prices, influencing each land use choice, thereby and crop-to-crop relative prices). Bio-physical reducing bias. In the SUR setup, the endogenous factors are also included, namely Galor and variable is the share of land allocated to different Ozak Caloric Suitability Index (CSI) and crop crops, in this case the shares of land under suitability dummies (that is, if crop is among wheat, teff, fruits, cash crops and oilseeds, as the three most suitable in the area) drawn the high value crops; and the shares of land from the FAO GAEZ database. Lastly, SUR under maize, barley, other cereals and root estimates also control for area-level and crops, as the low value crops. In a related layer extension factors, such as the existence of of analysis, the shares of land under the crops a woreda office, a micro finance entity, an are aggregated to the shares of land under high irrigation scheme, an extension program, and low value crops in a two-equation system. advisory services and notice boards. 65 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY production, while maintaining the land allocated only once their subsistence needs are met. The to maize, for example. Thus, smallholder farmers more fertile the land, the lower the amount of land double down on staples production when the land that households would need to produce enough is more suitable for their production but keep staples to meet their minimum subsistence needs, growing their main staple anyway even when the freeing up the remaining land for the production of land is more suitable for non-staple crops instead. other crops. This notion is supported by the observed Therefore, they devote a higher share to staples relationship between land use choices and a production than they should when marketed- geospatial index of caloric suitability, estimated from oriented crops could be more productive, implying applying machine learning to predict the maximum that other factors are at play. caloric potential of land for productive crops in each area. Estimates using this proxy of land fertility show Facing land constraints, most rural households that households with more fertile land devote a maximize the land that they own to produce significant share of their land to cash crop production their own food first. Households owning less land (Figure 61), controlling for other factors such as seem to maximize production of staple foods for prices and farmer knowledge that may influence subsistence. The production of roots and tubers land use decisions. Given the land constraints that is concentrated among the smallest farmers that poor households face, improving the yields of staple own less than 0.25 ha. The share of households crops could facilitate households’ diversification into that grow teff and wheat (cereals with urban production for the market. demand), pulses and oilseeds increase across the landholding classes, but declines among Public extension services have also been biased households that hold more than 2 ha (Figure 60). On toward the production of staples in promoting self- the other hand, households with more fertile land sufficiency. Households whose land is covered by an can devote a significant share of their land to cash extension program have a higher share of land devoted crop production (Figure 61). to teff and maize, even after accounting for other factors, such as the crop suitability of the land, market access Land use patterns suggests that smallholder and relative prices. But households receiving advisory farmers are likely to diversify into other crops services from other sources devote less land to maize Figure 60. Land allocation across crops by Figure 61. Share of land allocated to cash crops by ownership (% of area cultivated), 2019 land fertility, 2019 100% Share of land under cash crops 80% 60% 0.2 40% 20% 0.1 0% <0.25 0.25-0.5 0.50-1.0 1.0-2.0 >2 ha ha ha ha ha 0 2,000 4,000 6,000 8,000 Teff Wheat Maize All other cereals Pulses & nuts Roots & tubers Oil seeds Galor & Ozak (2016) Suitability Vegetables Fruits Cash crops Spices Source: Authors’ estimates from ESS 2018/19. Notes: The plot in Figure 61 is based on a non-parametric regression of share of land under cash crops and the crop suitability index. The estimates are backed by results from Seemingly Unrelated Regressions of land use choices. 66 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES and teff. This implies that public extension services are with large weekly markets than those in areas currently biased toward staple food production, in line without large weekly markets. with the Government’s food self-sufficiency objective, given the country’s history of food insecurity. Market isolation results in higher local prices in areas where some staples are consumed the Low market access increases costs and most. The price of maize is much higher, especially promotes self-sufficiency in remote areas (Figure 63). This encourages such households to produce for self-sufficiency. Estimates Production choices—in terms of crops and farm suggests that households produce less and less of enterprise—are influenced by rural connectivity other crops the higher the price of maize becomes and market accessibility, highlighting the relative to the nearest urban center, for example. importance of food market integration in In cases where households with poor connectivity influencing land use choices. In general, the produce a surplus, the decision to store commodities commercialization index of fruits and vegetables, oil seeds, cash crops and livestock products improve Figure 63. Food price variation and market access, 2019 with households’ access to an all-season road and 1.6 proximity to the regional capital (Figure 62). A larger Maize prices relative to proportion of households in areas with better rural 1.4 Addis Ababa connectivity and access to markets produce fruits and vegetables, oil seeds and cash crops than those 1.2 in areas with lower rural and market accessibility 1 indicators. Proximity to small and medium towns is associated with higher commercialization index 8 of spices and herbs. commercialization indices of -2 -1 0 1 2 fruits and vegetables, oil seeds, and cash crops Market access indicator (z-scores) are higher for households with the shortest Source: Authors estimates from ESS 2018/19. travel time to the regional capital. Furthermore, Notes: Based on non-parametric regressions of community commercialization indices of fruits and vegetables market survey prices for an enumeration area relative to Addis and oil seeds are higher for households in areas Ababa prices. Figure 62. Rural connectivity and market participation, 2019 A. Commercialization index of agricultural products by B. Commercialization index of agricultural products by presence of large weekly market proximity to small town 0.50 0.53 0.49 .5 0.48 .5 0.41 .4 .4 0.37 Mean of CI Mean of CI 0.29 0.25 0.21 .3 0.22 0.23 .3 0.23 0.19 0.21 0.20 .2 0.13 0.12 0.15 0.12 .2 0.17 0.13 0.14 0.12 0.11 .1 0.05 0.05 .1 0.06 0.08 0.06 0.03 0 0 Yes No 0-60 min 60-120 min 120+ min C. CI of agricutlural products by proximity to medium town D. CI of agricultural products by proximity to regional capital .6 0.58 .6 0.60 0.53 0.45 0.45 0.42 0.39 Mean of CI Mean of CI .4 0.28 .4 0.15 0.20 0.26 0.28 0.30 0.24 0.24 0.21 0.20 0.19 0.21 0.20 .2 0.13 0.13 .2 0.14 0.14 0.12 0.07 0.11 0.11 0.07 0.06 0.06 0.05 0.05 0.05 0.06 0.02 0 0 0-60 min 60-120 min 120+ min 0-60 min 60-120 min 120+ min Staples Fruits and vegetables Oil seeds Spices and herbs Cash crops Livestock products Source: Authors’ estimates based on ESS 2018/19. 67 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY for own consumption is based on high transaction between the variation in the price of wheat and the costs that make trade unattractive to households. commercialization index for teff. Estimates also show a negative relationship between the relative prices Market isolation exacerbates the price volatility of of staples to cash crops and market participation, major staples across regions and over time, which reflecting household concerns over food availability. disincentivizes market participation among risk- averse households. Analysis of monthly price data New analysis suggests that rural connectivity— from 2011 to 2017 on teff, wheat and maize, reveals the determining factor for market isolation—is the regional price disparities that affect commercialization most critical determinant of market participation. In of these crops. The share of land that households the model, which jointly estimates the determinants devote to maize production increases with its price of the degree of market participation and its impact volatility, as measured by the standard deviation of of household consumption, it is found that rural the monthly price of the crop in each region over time accessibility is significantly correlated with market (Figure 64). The commercialization index of maize participation. Estimates suggests that proximity also declines with an increase in its regional price to roads—a measure of market integration—is the volatility (Figure 65). Estimates also suggest that a 1.0 most important predictor of market participation, percent increase in the regional standard deviation with households in a community within 2 km of an of the price of teff is associated with a 9.8 percent asphalt road selling 10 percentage points or double reduction in the commercialization index. However, the output of comparable households more than 2 km no statistically significant relationship is observed from a road (Figure 66)This is consistent with the price Figure 64. Share of area under maize cultivation Figure 65. Commercialization index (CI) and maize and maize price variation price variation Share of land under maize 0.12 .25 0.11 .2 0.10 CI .15 0.09 0.08 .1 0 100 200 .8 .85 .9 .95 1 1.05 Standard deviation of maize price Standard deviation of regional monthly maize price Source: Authors’ estimates from ESS 2018/19. Notes: Estimates in Figure 64 are based on non-parametric regressions of the share of land cultivated on maize to the standard deviation (S.D) of monthly regional maize prices; Figure 65 plots predicted commercialization index (CI) from the recursive bi-variate regressions on the standard deviation (SD) of monthly regional maize prices. Figure 66. Predicted margins of commercialization index by connectivity commercialisation index .3 Linear prediction of .25 .2 .15 .1 Beyond 2km Within 2km Live within 2km of tar/asphalt road Source: Authors’ estimates based on ESS 2018/19. Notes: Predicted margins from Recursive Bivariate Regression Model of market participation and household consumption. 68 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES wedge hypothesis, arguing that remoteness increases one-quarter of rural households produce twice as transaction costs, which makes trade unattractive by much as their dietary needs for these crops (Figure increasing the cost of acquiring food from the market, 67). Estimates show that a 1 percent increase in the while depressing returns from marketing surplus output production relative to the caloric requirement production. This, together with the fact that market results in a 0.3 percent increase in the share of output isolation increases price volatility in the event of sold by rural farmers in Ethiopia. Households with low shocks, reduces smallholder market participation, first output relative to their caloric needs sell a smaller by incentivizing them to focus on producing for own share of their output on the market, if at all. Failure to consumption, and then by encouraging them to hoard generate a surplus is therefore a major constraint to the surpluses they produce. farmers’ market participation. Market participation is further limited By limiting surplus generation, low agricultural by low surplus availability due to low productivity in rural areas constrains households’ productivity and post-harvest losses market participation. As noted earlier, there are significant yield gaps for key crops such as maize, The inability to produce adequate food to meet wheat and teff, which partly explains the higher subsistence needs hinders market participation. share of households failing to generate a surplus. Most rural households neither produce sufficient food Market participation is therefore expected to to meet their subsistence needs nor have a surplus increase with rising productivity. Indeed, estimates to sell. For this analysis, an indicator for surplus based on the ESS 2018/19 show that the average availability for cereals was calculated for rural crop commercialization index increases with land households by dividing a household’s output of maize, productivity (Figure 68). Post-harvest losses further teff and wheat by the estimated required production reduce the surplus availability, contributing to the needs to meet the household’s minimum caloric low levels of commercialization. A 1 percent increase requirements per capita from these crops, given their in post-harvest losses leads to an equivalent of shares in the consumption basket. A value below 1 percent decline in the commercialization index, 1 suggests a production deficit, as the household’s suggesting that reducing post-harvest losses can production falls short of its minimum caloric intake improve market participation in Ethiopia. However, requirements, while a value of above 1 suggests a this does not appear to be a major factor, as reported surplus. Based on this indicator, about 45 percent of post-harvest losses are low, averaging less than 1 rural households do not generate a surplus and only percent of output. Figure 67. Rural households’ distribution by Figure 68. Marketed output as share of production marketable surplus range, 2019 by land productivity, 2019 0,3 Above 3.0 0,25 Share of marketed output 2.0-3.0 17% 10% 0,2 Below 0.25 1.0-2.0 33% 0,15 28% 0,1 0.25-0.50 5% 0,05 0.75-1.0 0.5-0.75 0 3% 4% 1 2 3 4 5 6 7 8 9 10 Land productivity deciles Source: Authors’ estimates from ESS 2018/19. Source: Authors’ estimates from ESS 2018/19. 69 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY High exposure to shocks discourages social assistance than non-recipient households households from market participation with similar characteristics. Similarly, households with more easily monetized assets, such as livestock, Climate-related shocks affect both land and those with greater social capital, have a higher productivity, risk tolerance, and the appetite commercialization index. As Dietrich and Schmerzeck for market engagement. Land productivity is (2019) argue, access to alternative consumption- significantly lower in areas exposed to higher smoothing measures helps households cope with impacts of weather and climate-related shocks, shocks without adopting measures that reduce their reducing surplus availability. In addition, market participation. high exposure to climate shocks discourages smallholder farmers from investing in high- Building resilience, promoting risk mitigation risk, high-return technologies, such as inorganic and post-harvest loss management are critical fertilizers, further depressing productivity (Kebede, for promoting greater market participation. 2022). In the absence of market integration, food Improvement in post-harvest handling minimizes prices increase more sharply and the purchasing losses and allows for the availability of marketable power of cash transfers or any other income source surpluses, which incentivizes market participation. In declines, especially in drought years (Dietrich addition, investments and adoption of climate smart & Schmerzeck, 2019). In response, households agriculture technologies are likely to improve land accumulate large food storage reserves before productivity and welfare, and household resilience to marketing their surplus. The analysis shows that climate and/weather-related shocks and stresses. the share of marketed output starts increasing Other strategies, such as crop diversification, are when households have surpluses that are three also found to improve market participation. times their caloric requirement (Figure 69). Market distortions depress returns and Consumption-smoothing measures facilitate discourage participation market participation, as these provide an alternative to surplus hoarding as a copying strategy for Government intervention in output markets dealing with shocks. The commercialization index constrains trade and results in a decline in trade is around 5 percent higher among recipients of balances of other crop commodities (Woldie and Siddig, 2009). The Government of Ethiopia placed Figure 69. Teff and maize surplus availability and export restrictions on cereal crops to stabilize the commercialization index (CI) domestic supply. However, export bans have not .16 been effective in stabilizing prices and supply, or in improving welfare. Bans keep domestic producer Commercialization Index .15 prices low (Figure 70), which acts as a disincentive .14 to production in terms of both planting decisions (there is an incentive to divert production to crops .13 not subjected to a ban) and productivity enhancing .12 and/or cultivated area expanding investment, in addition to market participation (AGRA, 2019). .11 Instead, bans create real costs in terms of friction 0 1 2 3 4 5 and the costs associated with the absence of Standard deviation of regional monthly maize price predictability and transparency (AGRA, 2019). Average of teff, wheat and maize Teff Maize Ethiopia is the only country in the East Africa region whose nominal protection rates for maize Source: Authors’ estimates based on ESS 2018/19. Notes: Predicted margins from Recursive Bivariate Regression protection suggest that there is a price disincentive Model of market participation and household consumption. faced by farmers (Figure 71). 70 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES Improving market integration, agricultural incentives for households to shift from autarky productivity, market incentives, resilience to market-based systems. to shocks and risk mitigation • Improving extension services to encourage The above analysis shows that the market change in crop use and increase productivity, participation of smallholder farmers has net including that of staples, through multiple positive benefits but is constrained by low agriculture technologies (MATs). market integration, low productivity, high exposure to shocks and unfavorable incentives • Investment and adoption of climate smart due to government intervention. Faced with these agriculture technologies to strengthen constraints, rural households prioritize being self- household resilience to climate/weather-related sufficient by focusing their production on the staples shocks and improve land productivity. that they consume most, instead of those consumed more in urban areas or other market-oriented non- • Market deregulation and the removal of staple foods. Consequently, households double trade controls to improve the incentives for down on staple production even when other crops increased production. would be more productive and hoard their surpluses as a coping mechanism to shocks, reducing the • Access to land, even if only through user rights availability of market surpluses. and tenure security, can help households make effective use of family labor, improve their Increasing the market orientation of smallholder nutritional status, and participate in markets. farmers thus requires improving their access to markets, the adoption of productivity enhancing Given the predominance of the food self-sufficiency interventions, and strengthening their resilience motive, improving the yields of cereals will be a to shocks. This requires the following: cornerstone for increasing market orientation of smallholder farmers. There is clear evidence • Improving connectivity to markets and food that households diversify into production of other markets to promote greater market participation, market-oriented crops without necessarily reducing as this integrates food markets and provides the staple food production. Their ability to meet Figure 70. Maize and wheat price parity, (US$ ‘000) Figure 71. Nominal rates of protection at the farmgate, 2017 2 120 100 80 1 60 40 20 0 0 -20 2011 2012 2013 2014 2015 2016 2017 -40 -60 Import price per ton_Maize Local maize unit price Ethiopia Kenya Tanzania Uganda Import price per ton_Wheat Local wheat unit price Source: FAOSTAT. Source: FAOSTAT. 71 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY those needs frees land up for other crops, facilitating through the mobilization of farmers to commit to the desired change in land use choices toward high production of the cluster commodity under their land value crops, while also providing a market surplus while retaining ownership. It encourages adoption for households to sell. Thus, increasing market of multiple technologies through fostering adoption orientation is not necessarily incompatible with food- of environmentally sustainable farm practices and self-sufficiency objectives. technologies, a comprehensive package of extension services, and access to input credit. Results reported The agriculture commercialization cluster (ACC) from the program’s second-year performance report approach piloted in Ethiopia is promising in show that farmer production clusters resulted in a addressing many of these constraints. The ACC significant increase in yields and production volumes, approach develops commodity value chains in and thus generated a higher marketable surplus. geographic clusters focused on both cereals and However, access to finance, which is still heavily horticulture crops (Box 8). The clustering increases dependent on government provision, and improved market linkages and raises prices for farmers, seed varieties for crops such as wheat, remained a as they can negotiate and supply larger groups. It challenge as agriculture technology development solves the issue associated with land fragmentation remains mostly government dependent. Box 8: Agriculture Commercialization Clusters The ACC is a geographic focused approach resource management, and facilitating land to market-driven value chain development consolidation and input/output aggregation to improve the livelihoods of smallholder through formation farmers clusters. farmers. It was launched in 2018 as a five-year program focusing on 10 commodities—maize, One of the transformative concepts under the teff, wheat, malt barley, sesame, avocado, ACC is the farmer production clusters, which banana, mango, onions and tomatoes—across are instrumental in supporting farmers to 30 clusters, in 300 woredas across four regions grow their incomes by increasing marketable (Oromia, Amhara, SNNP and Tigray). The ACC has surpluses generation and farm profitability five strategic objectives, namely: (i) increased through increased commercialization. Farmer farmer incomes; (ii) adoption of climate smart production clusters (FPCs) consolidate land agriculture practices; (iii) enhanced market and provide a commitment device for adopting mechanisms; (iv) increased commodity supply best farming practices. Farmers voluntarily to Intergrated Agro-Industrial Parks; and (v) contribute as least 0.25 ha to form at least 15 ha on-and-off farm jobs creation. It comprises of contagious land for the cluster and commit 15 projects and two systematic interventions to cultivating the same crop, following the full that promote a comprehensive package of package of farm practice recommendations. The solutions to address the multiple constraints approach is also gender sensitive in requiring faced by smallholders. These include different the cluster management team to elect four mechanisms for delivering advisory services, members, including one, but preferably two, ensuring access to inputs through ramping women representatives. The FPCs generate up seed production and access to input credit, economies of scale, helping smallholder investments in irrigation, improving market farmers solve perennial aggregation problems, linkages through investment promotion and making commercialization more profitable, market information systems, improving natural increasing farmers’ ability to supply larger 72 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES quantities with better bargaining power, and government guarantees for access to credit. and making access to otherwise expensive In its first two years, access to input credit has agriculture equipment more affordable. The depended on government financing through results so far have been encouraging, with the Regional Bureaus of Agriculture (RBA), significant increases in yields and marketable which have faced challenges in the limited surpluses, especially among FPCs. availability of government financing and high default risks. Regarding these two aspects, the Access to finance and improved seed varieties, interventions under the ACC are still heavily however, remain a key challenge under the ACC, state-dependent and, consequently, experience despite key investments in these areas. Seed the same challenges with access to inputs and production is promoted mainly through support finance in the sector. A shift toward more private for cooperative-based seed producers, relying sector delivery of solutions might be necessary on public research for technology development to speed up progress on these two areas. Comparison of crop yields (Kg/Ha) Marketable surplus by ACC crop (2018-21) 8,000 90,0% 70,0% 6,000 50,0% 4,000 30,0% 10,0% 2,000 -10,0% Teff Maize Sesame Malt Barley Wheat Tomatoes Onion Avocado Banana Mango 0 Teff Maize Wheat Sesame Malt National average ACC woredas Baseline (2018) Percentage point change Farmer production clusters 73 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Livelihood diversification than the poorest 20 percent. The difference in average non-agricultural incomes (Br 7,849 in into off-farm activities 2019) accounts for a larger share of income in the agri-food system differences between the two groups (Figure 72). More rigorous estimates in the literature and beyond suggest that non-farm participation increases the incomes of rural households by about 19 percentage points (Danso-abbeam, Dagunga, Livelihood diversification into off-farm and Ehiakpor, 2020). activities is a major driver of rural income growth and poverty reduction Figure 72. Average household incomes (Ethiopian birr) Livelihood diversification is a strong driver of by consumption quintile and income source, 2019 poverty reduction in rural areas across the world. 25,000 The transition from agriculture to non-agriculture tends to be slow. Initially, households diversify their 20,000 livelihood portfolio by adding non-agriculture income sources from household businesses, wage work 15,000 and remittances, before some begin exiting the agriculture sector altogether. This is manifested in 10,000 a decline in the share of agricultural income, even 5,000 as the share of households engaged in agriculture remains high. For example, over 80 percent of rural 0 households in Vietnam and Cambodia were still Poorest Q2 Q3 Q4 Richest engaged in agriculture in 2020, despite agriculture making up between 34 and 38 percent of rural Crop Livestock Agri wage Non-agri wage Self-employment Transfers Other non-agri income incomes there. A similar pattern is also observed in other East African countries like Uganda and Source: Authors’ estimates based on ESS 2018/19. Tanzania. International evidence suggests that this livelihood diversification into non-farm activities is a The shift from primary agriculture production key driver of poverty reduction in rural areas (Egyei, to downstream segments of the agri-food Harrison, & Adzovor, 2013; J. O. Lanjouw & Lanjouw, system and beyond—which is now starting 2001). In Vietnam for example, rising non-agricultural to occur in Ethiopia—will offer opportunities incomes were primarily responsible for the reduction for households to diversify their livelihoods. in rural poverty over the 2010–18 period (Pimhidzai Employment in primary agriculture declined, even & Niu, 2021). as the number of rural workers increased between 2013 and 2021, which is a sign of rural economic In Ethiopia, better-off rural households also structural transformation beginning to occur. More generate more income from non-agriculture than 500,000 more jobs were created in the food sources. Though the difference in agricultural services segment of the agriculture food system incomes between the bottom and the top 20 (wholesale and retail) and about 1 million more percent of households in 2019 is large (Br 5,561 people now work in jobs beyond the agri-food in 2019, or 62 percent), there is an even bigger system. Thus, opportunities are emerging in the difference in non-agricultural incomes. The food system and beyond. However, agriculture still richest 20 percent earned at least five times dominates rural employment and incomes and, as more from non-agricultural income sources a result, diversification remains limited. 74 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES in Cambodia in 2019, one-third of rural incomes in Vietnam in 2018, and 59 percent in Uganda in 2019 (Figure 74). With the COVID-19 pandemic, far fewer households in Ethiopia operated a household enterprise. According to estimates from the HFPS conducted by the World Bank, the share of rural households owning a business declined by one-third, to around 13 percent of households at the end of 2020. For most rural households, the low access to off-farm employment is compounded by the Diversification is limited by low rural low quality of opportunities accessible to them. enterprise development due to a challenging While the richest 20 percent households, and to business environment and lack of demand some extent the second-richest 20 percent, earn at the local level significantly more non-farm employment incomes, the level of participation is similar across the entire Engagement in non-farm activities in Ethiopia is socio-economic distribution. There are some notable lower than in other countries in the region. About differences in the returns and composition of non- 23 percent of rural workers in Ethiopia are employed farm incomes between the poor and non-poor. A outside primary agriculture production, compared higher share of the bottom 40 percent households with 34 percent in Kenya and more than half of earns non-farm income from wage employment the rural workers in Vietnam (Figure 73). Fewer (20 to 23 percent of households) than the richest rural households in Ethiopia generate income from households (14 percent of the 4th and 5th quintiles), household enterprises (14 percent) compared with while a higher share of the richer households its comparators in the region, such as Tanzania (41 earns incomes from non-farm enterprises than the percent) or in Asia, such as Vietnam (27 percent) bottom households. Moreover, the richer households (Figure 74). Consequently, while agriculture made up engaged in non-farm activities earn more from three-quarters of rural incomes in Ethiopia in 2019, such activities than the poor, with differences more it contributed to only 38 percent of rural incomes pronounced for non-farm business incomes. A Figure 73. Comparison of rural employment Figure 74. Comparison of household participation composition, 2018/19 and contribution of income sources (%), 2018/19 100% 100% 80% 80% 60% 60% 40% 40% 20% 20% 0% Share Income Share Income Share Income 0% with share with share with share Ethiopia Vietnam Kenya Uganda Tanzania income income income 2021 2018 2019 2020 2019 Agriculture Non-farm wage Non-farm Primary agriculture Food processing business Other agro-processing Food services Farm inputs Non-food manufacturing Ethiopia 2021 Uganda 2020 Tanzania 2019 Construction Other services Cambodia 2020 Vietnam 2018 Source: Authors’ estimates from: Left: Ethiopia – LFS 2021; Vietnam – VHLSS, 2018; Kenya – KIHBS 2019; Uganda – UNPS 2019/20; Tanzania – NPS 2019. Right: RuLIS 2021, VHLSS 2018 and CSES 2019/20. Notes: The pre-COVID-19 pandemic estimates are used for Uganda. 75 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY household business run by one of the richest 20 Meaningful value addition in rural areas has been percent rural households on average brought in limited by a challenging business environment, around Br 11,000 in 2019, compared with just Br resulting in low job creation in the food processing 321 typically brought in from a non-farm enterprise and agri-food industry. Recent estimates from the run by those among the poorest 20 percent of rural Large and Medium Scale Manufacturing (LMSM) and households (Table 20). For non-farm wages, the SME surveys suggest that fewer than 1,000 large differences in average earnings seem to be linked and medium agri-industry firms operated in Ethiopia, to low wage earning among low educated people none of which is based in rural areas or small towns, (Figure 75). The poor also tend to work more for where firms in this sector are mostly informal micro- private individuals that establishments, so they enterprises. Consequently, fewer than 200,000 out of 27 mostly take casual jobs. Estimates show that casual million rural workers in Ethiopia, excluding Tigray, are wage jobs are associated with lower household employed in either food processing or agri-industrial per capita consumption (World Bank, 2020b). Thus processing (Table 21). These segments employ fewer generating better quality non-farm employment than 1 million workers (or 0.8 percent of the workforce) opportunities, based on meaningful value addition in in the entire economy, while they employ about 2.4 the rural economy, is essential to improving access million workers in Kenya, highlighting the sectors’ to welfare enhancing diversification opportunities. relative under-development in Ethiopia. Table 20: Rural household annual income sources Figure 75: Average wages by level of education, 2021 by quintile, 2019 Non-farm wage Non-farm business Completed post-secondary 5,373 Welfare Share Average Share Average Quintile with Income with Income Completed secondary 3,500 income among income among (%) Earners (%) Earners 1st 20% 7,384 11% 321 Completed primary 2,250 2nd 23% 4,255 13% 935 Less than primary 1,600 3rd 17% 8,959 16% 4,394 4th 14% 10,183 18% 4,567 No education 1,200 5th 14% 22,279 18% 11,090 Source: Authors’ estimates from RuLIS 2021. Source: Authors’ estimates from LFS 2021. Notes: Average incomes are in Ethiopian Birr, 2019 prices; Estimates for education attainment in 2021 exclude Tigray, which was not covered by the survey due to conflict. Table 21: Net job creation in rural areas in Ethiopia, 2013–21 Contribution to 2013 2021 Rural Jobs Growth Sector Number Share (%) Number Share (%) Net Jobs Net jobs employed employed Created Share (%) Primary agriculture 22,011,925 83% 21,249,693 78% (762,232) -84% Food processing 139,738 1% 195,195 1% 55,457 6% Food services - wholesale/retail 283,999 1% 811,533 3% 527,534 58% Agro-industrial processing 93,573 0% 96,313 0% 2,740 0% Non-AFS 3,964,870 15% 5,049,413 18% 1,084,543 119% Total 26,494,105 27,402,147 908,042 Source: Authors’ estimates based on LFS 2013 and 2021. Notes: Estimates from the LFS 2013 exclude Tigray for comparability with the LFS 2021 which did not cover Tigray. 76 Rural non-farm demand is still low, which reduces influence the creation of, and access to, non-farm the viability of rural enterprises serving local opportunities in rural areas, and whether there are markets. Data from the last survey used to measure non-farm employment spillovers from proximity poverty in Ethiopia—the Household Expenditure and to urban areas. It also investigated how labor Consumption Survey 2015/16—indicate that much supply factors, such as the household farming of household non-farm consumption is on water system, endowments (such as land, education, and energy, which are primarily non-market-based. and demographics), and gender norms, influence The rest of non-food spending is largely market- participation in non-farm work. The analysis was based, but the spending levels are very low. The per undertaken using a household production model capita spending on clothing and footwear in 2016, emphasizing household joint decision-making in for example, was less than Br 500, equivalent to just the estimation of the determinants of off-farm US$20 per person at the time (Figure 76). participation (see Box 9). The ESS 2018/19 data were combined with connectivity and market-access A recent study investigating rural intra-household indicators generated from geospatial data from the labor participation in off-farm activities Ethiopia Transport Network Layer 2020 and satellite highlighted the key constraints in access to off- imagery-based population data to accurately farm jobs at the community, household, and account for the influence of woreda-level location individual levels. The study considered how location factors. The discussion that follows is based on the factors, such as connectivity and population density, key constraints identified from this analysis. Figure 76. Per capita non-food spending by market source, (Ethiopian Birr, 2016 prices) 1,264 975 457 498 480 384 135 154 60 5 57 4 31 32 85 8 68 6 38 26 Clothing and Furniture and Other Clothing and Furniture and Other footwear furnishing non-food footwear furnishing non-food 2011 2016 Market Non-Market Source: Authors’ estimates based on Household Consumption and Expenditure Survey (HCES) 2011/12 and 2015/16. 77 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Low economic density due to remoteness and above show that job prospects for both males and sparse populations in rural areas emerges as females continuously improve as population density a constraint to rural enterprise growth and job increases (Figure 78). Sensitivity analysis confirms creation. Off-farm opportunities in rural areas that higher non-farm employment prospects in high are mostly in the services sector, which requires population density areas reflect inherently more higher population densities to thrive, and hence opportunities in population density areas, rather more off-farm opportunities are available in high than being an outcome of people moving to where population density areas (Figure 77). Estimates opportunities are already high (hence increasing from the household production model described these areas’ population densities).⁵ Figure 77. Sectoral employment shares (%) and Figure 78. Rural off-farm job prospects and woreda population density, 2019 population density, 2019 1 .4 non-farm employment 0,8 Share of workers Probability of .3 0,6 0,4 .2 0,2 .1 0 0-100 per 100-500 500 - 1,000 - 5,000+ 0 1,000 2,000 3,000 4,000 km2 per km2 1,000 5,000 per km2 2018 population density per km² per km2 per km2 Agriculture Industry Services Male household head Female spouse Source: Authors’ estimates based on ESS 2018/19. Notes: Right panel – Estimates from a simultaneous probit estimation of off-farm participation for pairs of a household head and eldest member in rural areas. This shows the predicted marginal probabilities of being in non-farm work plotted against the local population density, separately for male household heads and female spouses. ⁵ There is potential reverse causality in a positive correlation between population density and off-farm employment, as people also tend to move into areas where employment prospects are greater, thereby increasing the population density of those areas. We undertook robustness checks to rule out reverse causality by using lagged population density estimates in the regressions and find a similar positive relationship between woreda-level population density and off-farm job prospects. 78 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES Box 9: Estimation of intra-household non-farm participation in rural Ethiopia The determinants of off-farm labor participation eldest working member pairs (about 80 percent in rural Ethiopia are calculated by estimating being female spouses). In the conceptual a farm household production model using a framework for the model, households allocate simultaneous probit estimation regression their labor between farm and non-farm activities, for joint non-farm participation of household subject to their individual, household, and farm heads, spouses, and adult children within the characteristics, as well as local conditions that household (Corsi and Salvioni, 2012; World include proximity indicators to capture access Bank, 2019a). This analysis is restricted to rural to markets. Rural-urban spillovers are reflected households, jointly estimating the probability by the relationship between rural off-farm of engaging in either a non-farm wage or self- employment and urban-proximity indicators in employment activity for household heads and our estimation model. Variable type Variables Data Source Individual characteristics Age, gender, education, marital status ESS, 2018/19 Household characteristics Presence of under 5 children, presence of ESS, 2018/19 elderly, land ownership Farm Characteristics Dummies for crop type (maize, teff, wheat ESS, 2018/19 and barley) and livestock, farm potential wetness index, farm slope Local Labor market Sector employment shares (agriculture, ESS, 2018/19 conditions conditions industry, services), relative prices (with Addis Ababa as benchmark) for teff, maize, wheat, and barley Geographical Population density ESS, 2018/19 conditions Travel time to nearest urban centers (any Ethiopia Transport Network type; small towns of 20,000 to 50,000 people) Layer 2020 Market access index - combines travel time Gridded Population V4 (GPWv4), Land- with destination population Scan Global (LSG), WorldPop (WDP) Access to services Presence of banks, presence of markets ESS, 2018/19 Proximity indicators are based on travel time Population Distribution (LSG) dataset; and the between origin and destination pairs (woreda to WorldPop Spatial Distribution of Population (WDP) all other woredas; woreda to all urban centers). 1 km dataset. Total reachable populations within This is calculated from GIS data extracted from 30 minutes, 60 minutes, 120 minutes, and 180 the 2020 transport network for Ethiopia by minutes are calculated from each origin woreda. determining the shortest possible path for each origin-destination pair and the speed of travel Using woreda-to-woreda origin-destination based on the type of roads connecting the pair. matrices as inputs, accessibility in terms of Similarly, accessibility in terms of population is market access was approximated for each estimated by attaching population data to the woreda as the sum of travel time weighted destination pairs (woredas, urban). Three global by population to the destination woredas population datasets are used to supplement (Donaldson and Hornbeck, 2016; World each other: Gridded Population of the World Bank, 2019a). The market-access indicator is Version 4 (GPWv4) dataset; the LandScan Global estimated by the following equation: 79 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY MA0 = ∑ o≠d τ -θ od Nd where MA0 is market access at woreda “o”, τod with λ=0.02 and timeod the optimal travel is the trade cost between two woredas “o” and time between woredas using the transport “d”, N_d is the population of woreda “d”, and Nd network of 2020. The trade elasticity, θ has a is the trade elasticity. Trade costs between two value of 8.28 (Eaton and Kortum, 2002). woredas, τod is defined by τod = exp (λtimeod) Under-development of agriculture value cheaply and develop a sizable market for medium chains due to supply-side constraints add and large processors (Reardon (2015), which to low rural demand allows processing to be located further from cities, as shown in the evolution of pig processing in By hindering value chain development, supply- China (Schneider, 2011). Both supermarket chains side constraints, such as the lack of supportive and large processors provide key markets for infrastructure, constrain rural enterprise modern wholesalers and logistics firms generating formation and growth. The spatial length of better quality jobs in the midstream segments of a rural-urban value chain is elongated with the food system. They also trigger the introduction development of logistical infrastructure, which of private standards and the shifting of financial reduces transportation costs and improves storage transactions from spot to contract transactions. A (e.g., cold chains). This not only expands the recent cost-benefit analysis of opening the trading catchment area of semi-perishable food crops, but sector to foreign investment shows that opening also facilitates production and semi-processing the retail sector brings significant net benefits to to take place further from cities. Semi-perishable both suppliers and buyers in the country (IFC, 2021). products can be produced and packaged away from the urban consumption centers, for example. Value- Limited access to finance and foreign currency chain studies conducted in Ethiopia show that the further constrains rural enterprise development. lack of supportive infrastructure is one of the major Insufficient access to finance at the production, business challenges constraining rural enterprises. collection, and processing levels affect all types Limited infrastructure, such as road connections of enterprises. At a macro level, credit provision to and storage facilities (e.g., cold storage to maximize the private sector has been crowded out by state- meat market potential), renders rural areas owned enterprises (SOEs) that receive preferential and small cities less favorable for establishing access to credit. The private sector received only processing factories. This is compounded by high 12 percent of bank credit in 2020, a share that has transaction costs that reduce profitability (e.g., for been stagnant in recent years and below the SSA coffee and sesame). average of 20 percent. As a result, only 16 percent of private sector firms in Ethiopia use credit from The limitation of foreign investment into the banks, far lower than in Kenya, where 41 percent trading sector potentially slows down value-chain of the private sector use credit from the banks development and job creation. Private investment (World Bank, 2019a). Insufficient loan amounts in the retail sector could be a catalyst for value- and an inability to meet loan requirements are chain development and alter the geography of often cited as the main reasons for firms failing agro-processing. Modern retailers with centralized to access credit, according to estimates from the procurement tend to sell processed foods more Ethiopia Large and Medium Manufacturing Industry 80 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES Survey. The survey also shows that the inability to activities, given their land resources and the market procure raw materials and inputs, due to irregular factors they face. access to foreign currency, is the most critical challenge faced by manufacturing firms across Off-farm engagement is partly driven by push all subsectors in Ethiopia. Thus, macroeconomic factors, such as a lack of agricultural land. Those distortions in the financial sector and exchange rate from households with more land are less likely to misalignment pose a major challenge for actors in engage in non-farm activities compared with similar the postproduction phases of the agri-food system. individuals in land-poor households. Both male household heads and female spouses in landless At the household level, meeting subsistence households are twice as likely to be involved in needs dominates household labor allocation non-farm work as those in households owning decisions in favor of agriculture production more than 2 ha of land, but similar in all other respects (Table 22). This suggests that households The primacy of meeting subsistence needs allocate most of their labor to agriculture and are also holds back farmers from engaging in non- less inclined to engage in non-farm work when land farm activities. Estimates from the household resources are available. production model suggest that households’ non-farm engagement is determined by factors Consumers facing higher staple food prices such as access to land, food prices, or access to compared with other regions in Ethiopia markets in a manner that encourages households devote more labor to agriculture. Our estimates to devote more labor to agriculture. This signals accounting for the effect of local economic that households prioritize meeting their own food development conditions, such as remoteness needs through their production when deciding on on non-farm employment, still find that net food the division of labor between farm and off-farm consumers tend to engage less in non-agriculture activities the higher the staple food prices in local Table 22: Probability of engaging in non-farm work markets are relative to the prices in Addis Ababa and land ownership (Figure 79 and Figure 80). Net producers react differently depending on whether the crop they Household Male Female engages in household Spouse produce is consumed more in urban areas, and nonfarm Head hence a higher price signals high external demand, No land 0.25 0.20 0.14 or whether they are consumed more in rural areas, Less than 0.2 ha 0.24 0.19 0.12 where external demand is low and prices are high, 0.20 - 0.50 ha 0.19 0.14 0.10 driven by market isolation instead. For teff, the 0.5 - 1 ha 0.16 0.12 0.09 higher income from high prices enables males in net producer households to engage in non-agriculture 1 - 2 ha 0.15 0.10 0.08 activities, though results suggest that women are More than 2 ha 0.13 0.09 0.07 left with the production responsibilities and become Source: Authors’ estimates based on ESS 2018/19. less likely to engage in non-farm work. For maize, Notes: Estimates from a simultaneous probit estimation of off- a higher price reflects market isolation rather than farm participation for pairs of a household head and the eldest member. The average of predicted marginal probabilities of strong urban demand, and hence the relationship being in nonfarm work are tabulated for male household heads between relative prices and engagement in non- and female spouses and at the household level. farm work is weaker among maize producers. 81 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Food market isolation and higher prices thus between the allocation of labor toward meeting incentivize households to be food self-sufficient subsistence needs and alternative income- and engage less in non-agriculture activities. generating sources (Figure 81). Thus, market Prices for food items that are consumed the most isolation also reduces households’ incentive to in rural areas are usually higher in less connected engage in non-farm work, since they would face woredas, incentivizing households to produce higher prices for purchasing food, leading them staples. Staple food producers engage less in to prioritize production to meet their own food non-agriculture activities, suggesting a trade-off needs instead. Figure 79. Off-farm job participation by local maize Figure 80. Off-farm job participation by local teff prices relative to Addis Ababa, 2019 prices relative to Addis Ababa, 2019 .2 .2 non-farming employment non-farm employment .15 .15 Probability of Probability of .1 .1 .05 .05 0 .5 1 1.5 2 .5 1 1.5 2 Maize relative prices (Addis Ababa prices as benchmark) Teff relative prices (Addis Ababa prices as benchmark) Maize producer - male head Maize producer - female member Teff producer - male head Teff producer - female member Maize consumer - male head Maize consumer - female member Teff consumer - male head Teff consumer - female member Source: Authors’ estimates based on ESS 2018/19. Notes: Estimates from a simultaneous probit estimation of off-farm participation for pairs of a household head and eldest member. Predicted marginal probabilities of being in non-farm work based on crop price changes for male household heads and female spouses are plotted again the crop’s local market price relative to Addis Ababa separately for producers and consumers of maize (Figure 79) and teff (Figure 80). Figure 81. Probability of non-farm employment (%) by staple food production status, 2019 0,25 0,20 0,15 0,10 0,05 0,00 Household Male Female Household Male Female Household Male Female Head Spouse Head Spouse Head Spouse Maize Teff Livestock Non-producer Producer Source: Authors’ estimates based on ESS 2018/19. Notes: Estimates from a simultaneous probit estimation of off-farm participation for pairs of a household head and eldest member. The average of predicted marginal probabilities of being in non-farm work for male household heads and female spouses are tabulated for producers and non-producers of livestock, maize and teff at the household level and for male household heads and female spouses. 82 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES At the individual level, lack of education off-farm employment is also more evident among men and gender biases limit access to off-farm and women without secondary education. opportunities, especially for women The development of a secondary economy There is a huge gender disparity in access to off-farm in the post-primary production phases of jobs disadvantaging women. There are fewer women the agri-food system is critical for creating than men engaged in off-farm work across all age groups off-farm jobs in rural areas (Figure 82). These differences in non-farm employment prospects are large among young men and women. A With low density a key limiting factor for rural off-farm rural woman aged between 20 and 25 years of age job creation, three factors point to the potential for the has a 12 percent chance of engaging in non-farm work, development of the agri-food system in generating off- while a male in that age group with a similar background farm jobs in rural Ethiopia. First, growth in low-density has close to a 20 percent chance. The gaps are smaller economies is driven by absolute advantages. For rural among older people, as the non-farm employment households in Ethiopia that absolute advantage would be prospects for both males and females are low, falling in agriculture. Second, growth in low-density economies below 10 percent among people over the age of 55 years. is dependent on external demand. Growth in urban food demand due to rising incomes and population along with Access to off-farm opportunities is primarily limited the global agri-food trade, are the external sources of by low education, with low educated women facing the demand that Ethiopia’s agro-based rural economy can lowest off-farm employment prospects. Off-farm tap into. Simulations using growth in urban populations job prospects of people with secondary education are between 2010 and 2020 show material contributions more than double the prospects of primary educated to improving employment prospects in rural areas people, even after accounting for other factors, such as by around 10 percent in low-density areas only. Third, location, farm types, and prices (Figure 83). However, growth is delivered by SMEs due to limited economies the gap is wider between women with and without of scale. International evidence suggests that, during the secondary education. Our statistical model predicts transition phases of the food chain, the value chains are that a woman in the 25–45 years age bracket has a long and fragmented, and hence dominated by MSMEs, 33 percent chance of being in non-farm employment in what Reardon (2015) calls the “quiet revolution”. The if she is secondary educated, but less than a 10 percent stylized drivers of growth in low-density areas are chance if she has no secondary education, keeping all consistent with a transition in the food system geared other factors the same. The gender disadvantage in toward serving urban and global markets. Figure 82. Probability of non-farm employment (%) Figure 83. Probability of non-farm employment (%) by by gender and age, 2019 gender, age, and secondary education attainment, 2019 .2 .4 non-farm employment non-farm employment .15 .3 Probability of Probability of .1 .2 .05 .1 0 0 10 20 30 40 50 60 10 20 30 40 50 60 Age Age Female Male Female - Secondary Edu. Female - No Secondary Edu. Male- Secondary Edu. Male - No Secondary Edu. Source: Authors’ estimates based on ESS 2018/19. Notes: Estimates from a simultaneous probit estimation of off-farm participation for pairs of a household head and eldest member. Figure 82: Predicted marginal probabilities of being in non-farm work plotted against age, undertaken separately for females and males. Figure 83: Predicted marginal probabilities of being in non-farm work plotted against age, undertaken separately for females and males with and without secondary education. 83 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY The potential for job creation in the agri-food Improving rural connectivity is critical for linking system is demonstrated in the Second Agriculture rural areas to urban and global markets, making Growth Project (AGP II). Data from a survey of up for rural areas’ low economic density. Due to the job creation under the project show that more importance of external markets as a growth driver for than 500,000 jobs were created in the marketing rural areas, connectivity and market linkages will be component of the project (Table 23), even though key for job creation in the post-production phases of the many of these jobs were only temporary. These jobs agri-food system. Estimates of non-farm employment were created through support to common interest from the household production model show that job groups, which are informal micro-enterprises. prospects only start to improve noticeably when the This demonstrates that the development of level of market access is about 0.5 standard deviations rural enterprises in the agri-food system has from the average—such as the market access levels of the potential to create job opportunities for rural Adama (Figure 84). There are significant employment households to diversify their livelihoods by adding spillovers from urban to rural areas, which rapidly income sources. That close to 300,000 jobs were decline beyond an hour’s commuting distance also created under agriculture public support between a rural woreda and the nearest urban center. services further demonstrates that jobs could be This suggests the importance of being connected to created within both the downstream and upstream secondary cities, which tend to be closer, for rural segments of the food system more broadly. non-farm employment generation (Figure 85). Table 23: Job creation in the Ethiopia Agriculture Growth Project, 2015–2020 Component Temporary Permanent Total Number Share Number Share Number Share Agricultural Public Support Services 271,289 38.4% 3,856 1.7% 275,144 29.4% Agricultural Research 46 0.0% 338 0.1% 385 0.001% Small Scale Irrigation 123,222 17.4% 4,569 2.0% 12790 13.7% Agriculture Marketing & Value Chains 312,671 44.2% 217,724 95.9% 530,395 56.8% Project Management, Capacity Building & M&E 19 0.0% 661 0.3% 680 0.1% Source: World Bank (2022d). Figure 84. Predicted probability of non-farm Figure 85. Non-farm employment prospects (%) employment and market access index, 2019 and proximity to towns with populations between 20,000 and 50,000 people, 2019 .15 17,6% non-farm employment 14,2% Probability of .1 12,4% 9,6% 8,2% .05 5,4% -2 -1 0 1 2 Market access index (z-scores) 0-100 per km² 100-500 per per km² 500-1,000 per km² Female: population density, below 100 people/km² Female: population density, 100-500 people/km² Within 60 minutes Above 60 minutes Source: Authors’ estimates based on ESS 2018/19. Notes: Estimates from a simultaneous probit estimation of off-farm participation for pairs of a household head and eldest member. Predicted marginal probabilities of being in non-farm work plotted against. Figure 84: market access for male household heads and female spouses, done separately for each local population density category. Figure 85: travel time to small towns and their local population density. 84 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES Given low education levels, skills development is food from farms to urban and global markets requires required to facilitate the growth of rural enterprises improved logistical infrastructure, from warehouses, and individual access to opportunities. Post-production cold-storage chains, and marketplaces. Second, the activities, such as marketing, business development development of rural MSMEs requires improving their services, procurement and contract management, are access to finance, as the experience of common interest more skills-oriented. Agriculture services—another key group investment shows. Third, reducing barriers to source of jobs—are also skills-oriented. At the current entry to encourage private sector investments in the stage, which is likely in the medium-term scenario agri-food system, especially in input markets, logistics given how “supermarkets” are only just beginning to and retail sectors, will be important for reorganizing emerge in Ethiopia, the value chains are fragmented production and processing further away from cities. One and long, with opportunities created in the food services such barrier is the restriction of foreign ownership in the segment that are labor-intensive and dominated by trading sector. At a later stage of the transition of the MSMEs. The skills emphasis will be on business and food system, value chains will consolidate, becoming financial management skills. Better education and skills more capital- and knowledge-intensive and changing development also help close the gender gap. Statistical institutional arrangements. Strengthening institutional predictions from the household production model arrangements to improve contract enforcement, food show that job prospects for male household heads and safety standards and traceability will become more female spouses with secondary education increase by a critical. At an economy-wide level, addressing macro- similar margin as population density increases, though level imbalances will help address some of the key non-farm job prospects increase much more for male constraints faced by agro-businesses, such as a lack household heads than female spouses among people of foreign currency. According to the World Bank without a secondary education (Figure 86). (2019) Enabling Business for Agriculture, Ethiopia has a low ranking, with a score of 46.12 out of 100, lower Improving the business-enabling environment to than its comparators Kenya (64.8), Uganda (52.1) and attract private investment in agriculture value chains Vietnam (61.41). This means that the country has the will be essential for creating a post-production least favorable regulatory environment for enabling the secondary economy. First, the process of moving business of agriculture compared with its comparators. Figure 86. Probability of non-farm employment by secondary education attainment and population density, 2019 0,5 0,4 0,3 0,2 0,1 0 No Completed Secondary No Completed Secondary Secondary Education Secondary Education Education Education Male Household Female Household 0-100 per km2 100-500 per km2 500-1,000 per km2 1,000-5,000 per km2 5,000+ per km2 Source: Authors’ estimates based on ESS 2018/19. Notes: Predicted as the marginal probability of nonfarm employment for male household heads and female spouses in rural areas from a simultaneous probit estimation of off-farm participation for pairs of a household head and eldest member are tabulated by local population density and level of education. 85 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Enhancing opportunities percent. The pattern of rural-to-urban, as well as intra- rural, migration shares to total internal migration, through labor mobility has broadly remained similar. However, there are variations at the regional level in the flow of recent Internal labor mobility is an important pathway for migrants in the five years before 2021, compared with improving access to income-generating and risk- the migrant flows before 2013. The share of migrants diversifying opportunities, both for the migrants moving from rural Afar, Benishangul, and Harari to themselves and their families back home. It also any urban center increased but declined in Somali, relaxes the inefficient allocation of resources in rural the SNNP regions, and Gambela (Figure 87). Moreover, areas and, in turn, improves rural living standards cross-regional mobility has decelerated in recent (Beegle, Weerdt, &andDercon, 2011; Gröger and years compared with the trend observed before 2013 Zylberberg, 2016). In Ethiopia, about 5 million people (Figure 88). Thus, migration largely remains an intra- moved from their place of birth to another location regional phenomenon. within the country between 2015 and 2021 according Figure 88. The flow of migrants: 2008–21 to estimates from the latest national labor force survey (LFS 2021). More than 60 percent of internal migrants Panel A: Flow of migrants: 2008–13 originated from rural areas, either to other rural areas (25 percent) or from rural-to-urban areas (34 percent). The working-age group accounts for 81 percent of those who moved from their rural origin, demonstrating that internal migration is a phenomenon of the working-age population in search of better opportunities. The migration patterns in Ethiopia suggest the rural population will continue to grow in the coming years, as rural-to-urban migration is not large enough to offset the increases in the rural population due to high fertility. The rural population increased by 24.4 percent between 2013 and 2021, notwithstanding the increase in rural-to-urban migration of 20.8 Figure 87. Moving from rural Amhara and Oromia Panel B: Flow of migrants: 2015–21 to urban areas unchanged between 2013 and 2021 100% Share of rural out migration 80% per region 60% 40% 20% 0% 2013 Afar 2021 2013 Amhara 2021 2013 Oromia 2021 2013 Somalia 2021 2013 Benishangul 2021 2013 SNNPR 2021 2013 Gambela 2021 2013 Harari 2021 2013 Dire Dawa 2021 Rural to rural Rural to urban Sources: Authors' estimates based on LFS 2013, 2021. Source: Authors’ estimates based on LFA 2013, 2021. Notes: For comparability, estimates from LFS 2013 were computed Notes: The share is to the total internal migration of the origin region. excluding data from Tigray, which was not covered in the LFS 2021. 86 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES Migration enhances welfare in migrant- the poorest quintiles (Figure 89). As a consumption- origin households in Ethiopia smoothing mechanism, remittances encourage risk-taking behavior, such as increasing market Migration increases welfare among migrant- participation among smallholder farmers. Evidence origin households in rural areas, contrary to of these positive impacts is presented in Chapter concerns that internal migration could stall 3. Tracking migrants and non-migrants after five development in migrant-origin communities. In years in 18 villages in Ethiopia, de Brauw, Mueller, Ethiopia, arguments about rural-urban migration and Woldehanna (2018) also find positive impacts stalling the development of the rural economy on real consumption levels among migrants, assume that migration among labor-constrained demonstrating the net positive benefits of migration. households would reduce agricultural output. However, with surplus labor supply in rural areas, Barriers to internal labor mobility thus slow migration has a positive effect instead by raising down the welfare improvement process of rural labor productivity and output per worker. This, households and, in turn, affect sustainable in turn, also raises household consumption. In escape from deprivation. Thus, tackling and addition, remittances that migrants send back home finding new ways of leveraging labor mobility out of contribute to households’ income and become a low economic density areas would help mitigate the source of investment and a coping mechanism disadvantages in rural areas. This section describes during shocks. This improves resilience and the mobility barriers that are rooted in households’ prevents households from falling back into poverty, shock prevalence, and their human, social and as demonstrated earlier. On average, remittances financial capital. These are analyzed based on an from urban migrants were equivalent to one-third econometric model estimating the likelihood of a of the receiving household’s consumption per household having a migrant, the main results of capita in 2016, and more than double that among which are presented in Figure 90. Figure 89. Size of remittance income relative to Figure 90. Marginal effects correlated with migration total consumption for the receivers (%), 2012-2016 Age of HH head 80 HH headed by female 70 Remittance as a % HH size: Age 0-7 60 of consumption 50 HH size: Age 7-17 40 HH size: Age 18-65 30 20 HH average years of education 10 HH access to credit 0 HH receive cash transfer All rural Poorest quintile Second quintile Third quintile Fourth quintile Richest quintile HH own livestock Drought index (SPEI) -10 0 10 20 Probability of being with migrant 2012 2014 2016 (percentage points) Source: Authors’ estimates based on ESS 2011/12, 2013/14, 2015/16. Note: Figure 90 shows marginal effects and a 95 percent confidence interval. SPEI refers Standard Precipitation-Evapotranspiration Index, calculated for a four-month accumulation period, i.e., the month of June, July, August, and September for a historical drought year. The livestock ownership variable takes a value of 1 if the household owns livestock above the national median total livestock units and 0 otherwise. The access-to-credit variable has a value of 1 if the households received a credit amount greater than the rural median and 0 otherwise. Amhara region is used as a reference region. 87 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Lack of human and social capital traps another location between 2012 and 2016. Estimates members of rural households in their rural using the average number of years of schooling to places of origin measure the education level of household members show that, even in large productive households, Social capital plays an important role in facilitating being poor in human capital blocks rural household internal migration through established networks. The members from migrating (Figure 91). Households migration decision, as well as the success of migrants, without any member who had completed secondary is closely correlated with the presence of meaningful or above education in 2011 did not have a migrant social capital, proxied by whether a household is already during the following four years. receiving remittances either from a rural, or urban area, or from abroad. This is a sign that a household is Liquidity constraint limits migration connected with the outside world other than just in the home place. Estimates comparing similar households A financial investment is needed to undertake in 2011/12 in terms of their likelihood of having a migration and this could constrain migration migrant in the second visit (2013/14) or the third visit among the poor. At the very least, migrants incur (2015/16) show that the probability of having at least transport costs to the place of destination. Once one person from a rural household migrate increases there, they incur additional costs for transportation, by 7.5 percentage points in the presence of these food, and accommodation during job searches, networks. The lack of a social network thus decreases depending on their networks and the length of their the likelihood of household members migrating. job search. Households in the bottom 40 percent in 2012 made up only one-quarter of households with Low human capital further deters migration. a migrant during 2012–16 (Figure 92), suggesting Having poorly educated members or a smaller that financially worse-off households were less number of working-age members also reduce the likely to send out members. Indeed, estimates show possibility that any of them migrates. Having one that households that initially had above-average fewer working-age household member than average livestock ownership—a proxy of wealth more easily in 2011 was associated with a 9.7-percentage-point convertible into cash—had a significantly higher lower likelihood of sending a household member to chance of having a migrant during 2012–16. Figure 91. The change in probability of having a migrant Figure 92. The share of households with and by household members’ average years of education without a migrant, by rural quantile pre-migration and post-migration 0.6 100 0.5 80 Probability of with migrant Household share 0.4 60 0.3 40 0.2 20 0.1 0 2011/12 2015/16 2011/12 2013/14 0 Household Household 2.5 5.0 7.5 10.0 12.5 without migrant with migrant Education in years Poorest Poorer Middle Rich Richest Source: Authors’ estimates based on ESS 2011/12. Note: Left: The figure shows the predicted probability of a household having a migrant during 2012–16, based on a logit regression using household characteristics in 2011/12. 88 LEVERAGING OPPORTUNITIES: THREE PATHWAYS FOR INCREASING RURAL INCOMES Liquidity constraints explain why the financially agricultural incomes (including income from crops, worse-off households are less likely to send out livestock, renting agricultural inputs, and wage migrants. Financing migration can be costly and income in agriculture). Thus, returns from rural-to- poor rural households may be unable to participate urban migration are positive in the medium term. in migration unless there is a means of relaxing Therefore, non-wage factors making integration their liquidity constraints. The bottom 40 percent into destination areas more difficult and costly of households without migrants were also without for migrants in the immediate term are a barrier access to credit or received smaller amounts than to migration for people from liquidity-constrained the rural median. Multivariate estimates show that rural households. Qualitative studies suggest households with access to larger credit amounts that migrants find that the job search process is were more than 15 percentage points more likely to more difficult than anticipated and that they face send out a migrant later. Receiving cash transfers administrative barriers in obtaining kebele IDs, increases the chance of someone migrating from a inhibiting their access to government services. household by 7.5 percentage points. This supports the Many typically find the transition to urban life notion that the lack of liquidity keeps rural households onerous, with females facing additional challenges. from participating in the migration process, as these poorer households are unable to finance the upfront Addressing the job search challenges and costs of migration. These liquidity constraints could burdensome administrative procedures would be addressed through unconditional cash transfers or reduce the financial cost and barriers to improving access to credit. migration. This can be achieved by interventions that help connect migrants to jobs, such as job Job search costs and administrative intermediation services and programs such as barriers raise the financial cost of migration youth mentorship or apprenticeship that help the youth to signal their skills, improving the job- The high costs of migration imposed by challenges matching process. It also requires streamlining in destination areas increase the barriers to administrative procedures and the burden of proof migration for liquidity-constrained households, these often place on migrants. even though the returns to migration could be high. The average monthly wage, (hours worked The bottom 40 percent of households multiplied by the hourly wage in Figure 93) in urban without migrants were also without areas is three times higher than rural agricultural access to credit or received smaller amounts than the rural median. wages, and significantly higher than average Table 24: Households’ liquidity status defines the Figure 93. Hourly wages and weekly hours worked probability of sending out a household member to by rural and urban residents, 2019 another location 43,3 36 Liquidity access Had a migrant in 2012–16 in 2011/12 27 27,0 Yes No Received cash 34.54 27.03 transfer Urban Rural Urban Rural Accessing credit 41.87 27.7 Hourly wage (birr) Weekly hours worked Source: Authors’ estimates based on ESS 2011/12, 2015/16. Source: Authors’ estimates based on ESS 2019. 89 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Adapting urban areas to rising populations is needed to reinforce the urban pull for migrants More fundamentally, the cost of migration in destination areas can be reduced by investments in urban development. Both private and public investments expanding the urban industrial base create more employment opportunities, improving the job matching prospects thus reducing job search costs for both urban residents and migrants alike. Investments in low-cost housing and expansion of public service delivery also reduce costs for migrants and make urban life more hospitable, thus reducing a big barrier to migration. Thus, adapting urban areas to expanding populations through investments in urban infrastructure, housing and social services both helps relieve pressure from rising populations while also helping migrants integrate socially and economically (World Bank, 2022b). 90 PRIORITIES FOR INCREASING HOUSEHOLD INCOME 91 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY The analysis above has identified key opportunities, Changing incentives for households to pathways and multiple constraints to raising rural produce for the market incomes. A key question for policy makers is on the relative importance of these constraints, the Increasing the market orientation of smallholder proposed interventions to address them and their farmers is centered on shifting their land use impact. To answer these questions, the discussion choices away from self-sufficiency-driven below identifies five outcomes or transmission production decisions to market demand-driven channels for increasing rural incomes across the production choices. This requires tilting the trade-off three pathways discussed in the previous section, between self-sufficiency and market orientation in then summarizes the key constraints and proposed favor of the latter. That means addressing factors that solutions for achieving these outcomes. Their incentivize or make it more optimal for households importance is then evaluated based on the sizes, to become self-sufficient due to the perceived high and position of different groups of rural households costs or reduced expected benefits from market- in the welfare distribution, and how they relate driven production. The identified factors affecting to limits and changes within the government's the incentives faced by households are: (i) market agriculture and rural development policy and isolation; (ii) risks to shocks from climate change and broader directions in economic reforms. price volatility; (iii) depressed returns due to state intervention in output markets; (iv) high transaction Strategic focus areas for costs; and (v) a bias in extension service provision toward cereals production. Interventions addressing increasing rural incomes these constraints are: To expand opportunities for rural households and • Improving rural connectivity – Improving grow their incomes, policy interventions should connectivity is critical for market integration, promote a shift toward market orientation among which helps reduce food prices and volatility in smallholder farmers, create opportunities for isolated areas, especially during droughts. livelihood diversification, and reduce barriers for rural labor mobility. Interventions to achieve these • Eliminating export controls – Surplus maize should focus on addressing constraints to achieve producers in particular face low domestic the following five outcomes: prices compared with international markets, and the prospect of local demand contractions i. Changing incentives for households to produce given maize’s very low-income elasticity of for the market; demand in urban areas. Regional markets are the only growth market for surplus maize ii. Increasing agriculture surplus generation and producers, but these are currently inaccessible availability; due to an export ban. iii. Overcoming the disadvantage of low economic • Improving market linkages – Connecting farmers density in remote, sparsely populated areas; to markets improves demand signals, while reducing transaction costs, raising expected iv. Promoting rural enterprise development in the earnings from market orientation. Potential non-farm segments of the food system; and interventions to improve market linkages include: (i) strengthening market information v. Expanding the pull factors and reducing costs systems; (ii) contract farming, which is a clear for rural urban migration. signal and assurance for demand that also 92 PRIORITIES FOR INCREASING HOUSEHOLD INCOME reduces marketing costs; and (iii) production presented above shows that key constraints to alliances to reduce aggregation costs and make surplus generation and availability are: (i) low it more profitable to produce for the market on adoption of multiple agriculture technologies; small plots. (ii) exposure to climate-induced shocks; and (iii) hoarding of surpluses to cope with climate shocks. • Revamping extension service provision – Extension Interventions to address these concerns are: service provision needs to focus on market- oriented advisory services in addition to • Extension service provision – Expansion of both technology adoption. private and public extension services provision is necessary to increase adoption of multiple • Agriculture insurance and climate information– agriculture technologies (MATs). Empirical Developing agriculture insurance products is analysis suggests that the utilization of extension an important risk mitigation measure that will services increases the adoption of MATs. protect households against production failures and excessive price volatility. This boosts the • Promoting climate smart agriculture technologies expected returns from market orientation, – Strengthening resilience to climate change with household incomes preserved in the is essential for increasing agricultural event of poor harvests or low prices. In Kenya, productivity in the face of increased rainfall and agriculture insurance has been successfully temperature variability (Tesfaye et al., 2020; combined with digital agro-weather advisories Teklewold, Gebrehiwot and Bezabih, 2019). It to ensure smallholder farmers make more also changes households’ risk calculations, informed and timely decisions in their farming. facilitating the adoption of high-risk high-return Studies conducted by the World Bank point to agriculture technologies, such as inorganic an increase in maize yields to an average of fertilizers, and reducing farmers’ incentives to 970 kg per ha compared with 210 per ha for hoard their surpluses (Dasgupta & Robinson, non-beneficiaries when farmers access agro- 2021; Kebede, 2022). The important climate weather information. Higher incomes of KSh smart agriculture interventions that can be 9,402 (Kenyan shillings) from maize sales were promoted include: (i) irrigation, which currently obtained from the beneficiaries with access to has low coverage; (ii) conservation agriculture; insurance and climate information compared and (iii) crop diversification. with KSh 3,918 for non-beneficiaries. In Ethiopia a similar trend is observed. The pattern of teff • Promoting post-harvest handling technologies yields and incomes are similar in Ethiopia, where – Post-harvest losses reduce the available beneficiaries recorded an average yield of 1,656 surpluses and negate households’ efforts to kg per ha compared with 771 kg per ha for non- maintain buffer stocks to cope with shocks. beneficiaries. The average income obtained from The adoption of metal storage (metal silos) teff for beneficiaries was Br 19,760 compared has been found to almost completely reduce with Br 17,878 for non-beneficiaries. storage loses and save farmers an average of 150–200 kg of grain (Gitonga, Groote, Kassie, Increase agriculture surplus generation & Tefera, 2013). Post-harvest management and availability training and hermetic storage bags reduced storage losses by about 77 percent (Chegere, Farmers, especially cereal producers, should Eggert and Söderbom, 2021). Improved have surplus output to sell to participate profitably harvesting techniques also reduce losses. in markets. These surpluses can be generated by increasing land productivity and preserved • Improving access to credit – This is important by minimizing post-harvest losses. The analysis both to facilitate technology adoption, which 93 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY evidence shows is partly constrained by liquidity areas, which rapidly decline beyond one constraints, especially mechanization, and as a hour’s commuting distance between a rural consumption-smoothing measure to promote woreda and the nearest urban center, implying the adoption of risky technologies in the face of significant gains from connection to secondary shocks and to manage the timing of households’ towns that are closer to most rural areas. participation in markets. • Improving market and other supporting infrastructure • Input market reforms – The availability of inputs, – Supporting infrastructure is required to the right kind at the right time, has been a better serve external markets by providing the constraint to intensification of input use. This means for preserving and getting the goods was primarily driven by state controls in input to markets, as well as the trading points. The markets such as fertilizer, the opening up of required supportive infrastructure ranges from: which should encourage investment in local (i) logistical infrastructure, such as warehouses production and increase range and availability. and cold chains; (ii) delivery services; and (iii) To encourage mechanization, the availability of physical marketplaces. agricultural equipment suited for smallholder farm structures, and the development of rental • Digital marketplace developments – It is also and sharing markets, are important. important to connect low density areas to the network economy though more direct linkages Overcoming the disadvantage of low economic to customers. This can be done by developing density in remote, sparsely populated areas digital marketplaces whose success depends on: (i) increasing digital connectivity and A major reason behind the lack of non-farm reducing costs; and (ii) expanding mobile opportunities in rural areas is low demand due to a payments to facilitate digital transactions. small internal market, leading to fewer and smaller rural enterprises and hence fewer jobs created. Facilitate rural enterprise development and Rural enterprises in these circumstances can only participation in the non-farm segments of thrive by serving external markets. This requires the food system addressing the challenges of: (i) low market access; and (ii) low linkages with prospective customers. The development of rural enterprises is important for off-farm rural job creation. For rural Overcoming the disadvantage of low economic areas, fulfilling rising demand for food in urban density in remote, sparsely populated areas areas and agriculture commodities globally is the requires interventions for promoting rural source of external demand that can drive growth. enterprise development in the non-farm segments Participation in the non-farm segments of these of the food system that include: agriculture value chains presents opportunities for MSMEs in rural areas. Taking advantage of these • Improving rural connectivity – Reducing travel opportunities requires addressing challenges with times to urban centers through improved the business environment, namely: (i) a lack of secondary road connections is needed to access to finance; (ii) barriers to entry and the high significantly increase market access and cost of doing business caused by state intervention employment generation in rural areas. The across key nodes of the value chains; and (iii) analysis presented in this report shows a limited skills. The required interventions to address dramatic increase in access to off-farm jobs as these constraints are: market access improves because of improving road infrastructure. There are significant • Developing rural finance – De-risking lending employment spillovers from urban to rural to the rural economy and improving access 94 PRIORITIES FOR INCREASING HOUSEHOLD INCOME to start-up capital to micro-enterprises are are driven by: (i) frictions in the job matching instrumental for enterprise development. process, which can make the job search costly Measures to address these issues are: (i) lines and unaffordable to those without savings to tap of credit coupled with technical assistance for into; and (ii) barriers to access to services. These rural finance, akin to the support provided for constraints can be addressed with measures on SMEs under the Ethiopia SME Finance Project; three fronts: (ii) the establishment of a credit rating system to reduce collateral requirements; and (iii) • Expansion of urban-based public and private matching grants for common interest groups, investments – There is need to reinforce the cooperatives, and MSMEs. urban pull factors for migration by expansion of investments in urban-based export industries, • Reducing state interventions – State intervention public investment in urban infrastructure and creates barriers to entry either through market services, and both public and private investment concentration or market regulations that in affordable housing. This increases the increase the cost of doing business. These can expected net benefits of rural-urban migration be reduced by adopting the following measures: by expanding access to opportunities while (i) market deregulation in input licensing, reducing costs of integrating in urban areas input pricing and maize price controls; (ii) through improving access to affordable encouraging private sector provision of services housing and services. such as logistical infrastructure, marketplace development, cold chains etc. • Connecting jobseekers to jobs – Improving systems that facilitate matching of jobseekers to job • Skills development – Developing skills will be vacancies, and programs that help jobseekers instrumental for providing the human resources signal their skills are important for reducing job required for skills-intensive activities in the search costs. Measures in this direction include: post-production economy, such as marketing (i) strengthening labor market information and business development. It is also important systems by setting up an employment agency for capacitating the management of rural and strengthening public employment services; enterprises and the development of agriculture and (ii) expanding youth apprenticeships. services. In the short term, this can be addressed by: (i) supporting vocational training • Streamlining administrative procedures – for the rural youth and capacity building for Administrative procedures should be cooperatives; and (ii) developing an ecosystem streamlined to improve access to services and of business development services. In the long ease the process of migrants to integrate and term, investments facilitating the transition to adjust to urban life. The key interventions will be: secondary education are required. (i) minimizing the burden of requirement from obtaining kebele IDs by reducing the minimum Expanding the urban pull factors and length of stay and removing the requirement reducing costs for migration for a release letter; and (ii) streamlining ID reforms and household registration. Easing the process of integration of migrants into urban areas is important for reducing the cost Developing skills will be instrumental of migration and promoting mobility. Migration providing the human resources required for skills-intensive activities has both social and economic costs that can be in the post-production economy a deterrent to prospective migrants. These costs 95 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Impact of different policy albeit to varying degrees. A cluster analysis on the ESS 2019 data identifies four groups of rural interventions on different households (Table 25). These are categorized and classified: as (i) remote, low-value cereals dependent segments of the rural society (group 1); (ii) remote, high-value cereals dependent (group 2); (iii) less remote, diversified (group 3); and The constraints to achieving each of the five (iv) connected, high-value crop dependent (group 4). outcomes or transmission channels for increasing Their characteristics and priority areas for expanding rural incomes are pertinent to all rural households, incomes are discussed below. Table 25: Taxonomy of rural households in Ethiopia Remote, Remote, high- Less remote, Connected, low-value cereals value cereals diversified high-value crops dependent (42%) dependent (32%) (31%) dependent (2%) Consumption per adult equivalent per year 12,732 12,642 15,028 19,851 Land productivity 18,176 22,589 23,612 16,170 Labor productivity 65 87 78 83 Highest number of years of education in the 5.6 5.0 7.3 6.6 household Land owned by the household (ha) 0.91 0.98 1.08 1.31 HH distance in (km) to nearest major road 19 21 16 5 Nearest population center within 5 km 0% 0% 2% 97% Large weekly market in the community 34% 90% 61% 12% Has communication assets 37% 44% 67% 52% HH owns a nonagricultural business 6% 13% 29% 3% Has diversified livelihood 7% 14% 44% 11% Household cultivates cash 53% 46% 63% 76% Household grew teff 31% 47% 39% 26% Household grew maize 63% 52% 62% 88% Household grew wheat 19% 32% 23% 0% Household grew coffee 39% 19% 46% 10% Household using irrigation 4% 11% 11% 9% Household using inorganic fertilizers 51% 73% 70% 71% Household using improved seeds 34% 38% 47% 8% Climate smart agriculture practices 1% 16% 5% 47% Households receiving a credit 10% 19% 20% 0% Moisture-reliable areas (lowland, high- 55% 76% 73% 20% land-cereal, highland-enset) Source: Authors’ estimates based on ESS 2018/19. Notes: The four groups of households are identified applying a cluster analysis to the rural sample of the ESS 2018/19 data. 96 PRIORITIES FOR INCREASING HOUSEHOLD INCOME The remote, low-value cereals dependent top priority along with improving connectivity households’ group (group 1) accounts for 42 to domestic markets. This requires increasing percent of all rural households. These are investment in agriculture technology development households with low education, predominantly for improved seed varieties for teff and wheat, located in maize-producing areas, but that have the and efficiency of their supply, by attracting lowest level of productivity and connectivity (i.e., they private investment into agriculture technology have poor access to roads and are furthest from development, multiplication, and distribution. markets), use fewer market inputs, less irrigation and Development of domestic supply chains for grains, climate smart technologies, and yet a considerable including improving market linkages, warehousing, share of households live outside moisture-reliable and attracting private investment into grain ecological areas. Increasing market orientation, processing and milling are important interventions, through both expanding surplus generation and with potential spillovers for off-farm job creation. crop diversification, is the most critical pathway for increasing incomes of this group. The top priority is The third group, made up of less remote and more improving adoption of agriculture technologies with diversified households, comprises 31 percent of improved seed varieties, fertilizers, irrigation and rural households. It has higher incomes than the climate smart agriculture technologies. Ethiopia first two groups, is dependent on maize but more is way below its comparators (Tanzania, Uganda, diversified into cash crops production (mostly coffee), Cambodia and Thailand) in terms of laws and as well as non-farm income sources. This group is also regulations on fertilizers. The second priority will be concentrated in moisture-reliable areas, with higher improving crop diversification to encourage more average education levels and living slightly closer to uptake of cash crops. Both priority areas require roads. Livelihood diversification into non-farm activities improving the policy and regulatory environment, is a primary pathway for increasing incomes of the and efficiency of agriculture input markets, combined third group, with increasing market orientation as with access to appropriate extension services. A third secondary. Development of export value chains offers priority is reducing price distortions by removing the opportunities for expanding incomes in the non-farm maize export bans (which is their primary crop) and segments of the food system, while the elimination of exchange rate alignment as they produce mostly price distortions in export output markets (incentives export-oriented crops. for premium coffee production, exchange rate alignment, and elimination of maize price controls) The remote, high-value cereals dependent will boost agricultural incomes. Improving market households’ group, the second group, accounts linkages, and access to credit and logistics are the top for 32 percent of the rural population. It comprises priorities for value-chain development and off-farm households with similar income levels and low diversification. Improving access to improved seed education as the first group, but that are more varieties is also an important priority for this group, dependent on cereals with high urban demand (i.e., given the low level of adoption, even though they are wheat and teff), have higher labor productivity, are better off than the rest of the groups. concentrated in moisture-reliable highland areas, are more likely to use inorganic fertilizers and have The fourth group of connected, high-value crop- access to weekly markets, but are slightly further dependent households is the smallest, making from roads and have low usage of improved seeds. up only 2 percent of rural households. It has the Increasing market participation, through expanding highest average incomes, comprising well-connected surplus generation, is the most important pathway households that are near roads, not far from urban for this group. It also has scope for diversification markets, and have mobile connectivity but have the into non-farm segments of the food system through lowest access to credit and use of improved seed development of domestic value chains for grains. varieties. These households own more land, have Increasing availability of improved seeds is the very diversified agriculture crop production but the 97 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY lowest diversification into off-farm activities despite also have greater potential for job creation in non- being better connected. They are dependent on farm segments of domestic value chains, which maize and concentrated in drought-prone areas, requires improving the enabling environment and more likely to use climate smart technologies. for rural enterprise development. The issues of Livelihood diversification, through promoting rural improving efficiency of input markets, adoption of enterprise development, is an important pathway for agriculture technologies and access to roads are this group given their high connectivity. Improving cross-cutting priorities across all groups, except for access to credit should be a top priority. Access to connectivity for the fourth group. improved seeds is another important priority given the group’s low land productivity. Despite the significant differences between the four groups, many of the indicators are still The top priorities are different for these groups low, except for the fourth group. Among the first depending on their dependance of high export three groups, the highest shares of households potential crops relative to domestic urban using irrigation, improved seeds and climate smart consumption crops, level of crop diversification, technologies are about 11, 47 and 16 percent, rainfall reliability, technological adoption, and respectively. This implies that the adoption of roads connectivity. These patterns differ across agriculture technologies is generally low. The and within regions (Map 1). For households outside average distance to the nearest road ranges from moisture-reliable areas, irrigation investments 16 to 19 km, access to credit is between 10 and 20 are a top priority. For those households that are percent, and the average years of education of most dependent on cereals with low urban demand but educated household members ranges between high export potential (e.g., maize) and those in 5.6 and 7.3 years. Therefore, connectivity and coffee-producing areas, price distortions, export access to finance are also a major challenge for 98 controls and the exchange rate are important percent of the population, together with low levels priorities. For households producing cereals of education. The differences in characteristics with high urban demand, the top priority is the across groups and their levels of income highlight generation of a marketable surplus through the importance of market orientation, access to improved technology adoption, better market markets, and the use of technologies to improve linkages and connectivity to domestic markets, livelihood diversification into off-farm opportunities along with supporting infrastructure. Such areas and increasing rural incomes. 98 PRIORITIES FOR INCREASING HOUSEHOLD INCOME Map 1: Agricultural productivity by crops and zone Teff Wheat Coffee Sesame Maize Barley Source: Authors’ estimates from the AGS 2021. 99 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Evolution and feasibility Figure 94. Composition of ARD expenditures, 2009–18* of policies supporting ETB millions (constant 2016) 45,000 40,000 rural incomes 35,000 30,000 25,000 20,000 For close to five decades, initially based on the 15,000 socialist ideology of the previous regime and then 10,000 5,000 continued through the “developmental state” - approach of the current government, Ethiopia has 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 followed policies that put the public sector at the center of economic growth initiatives. This has been Rural infrastructure Managing threats and Technology advancements protecting livelihoods most pronounced in agricultural and rural development Output market development Agricultural transformation Rural enterprise oversight (ARD). The Government of Ethiopia has a very hands- on policy in input distribution, particularly for fertilizer, Source: ARD PER Dataset, 2021. improved seeds and breeds, and artificial insemination (AI) services. It relies heavily on public services for Rural infrastructure development relies almost the introduction of new technologies and agriculture entirely on public resources, particularly practices, has vested ownership of land and water investments in irrigation infrastructure and resources, and leads on infrastructure development. water development for livestock, and for road The ARD policy has been effective in terms of promoting construction. These investments started from a low technology advancement in smallholder agriculture, base and, as a result, a large investment gap exists. contributing to productivity gains, mostly in cereals. But For instance, irrigation coverage, which expanded the dominant role of government in input and output under the agriculture growth project Phases 1 markets and state-led infrastructure development has and 2, only reached 7 percent of arable land by constrained private sector development and introduced 2021. Charging for the use of developed resources price distortions, adversely affecting production is uncommon in Ethiopia and, while mentioned, decisions and returns to farmers. is not well articulated in government policy and strategy documents, and therefore operation and Government-led rural infrastructure and maintenance (O&M) tends to be weak. Watershed and agriculture technology development rangeland development is undertaken by mobilizing community labor, while still under the direction of Rural infrastructure the Government, albeit within a well-developed local- level participatory approach. The ARD policy has not The Government has long recognized the need to yet developed an approach to encourage private and increase investment in rural infrastructure, focusing on-farm investment in rural infrastructure. But the primarily on natural resource development and rural Government is currently working on reforms for the connectivity. Accordingly, it has prioritized investments mobilization of multiple sources of funding for rural on rural road networks, both small-scale and large-scale infrastructure development. It is also implementing irrigation schemes, water development for livestock, and reforms to improve natural resource management, on structures to protect and rehabilitate degraded and/ while continuing with public ownership. or rapidly degrading landscapes. This is reflected in the pattern of ARD public spending (Figure 94). A recent review Support for infrastructure, such as through of government public expenditures in ARD, undertaken market centers, warehouses and wet-processing in a joint study by the World Bank and FAO/MAFAP, centers, has also been provided primarily by the shows that, since 2012, spending on rural infrastructure Government. As a result, there has been under- development is over half of total ARD spending. investment in this type of rural infrastructure. 100 PRIORITIES FOR INCREASING HOUSEHOLD INCOME The lack of access to wet-processing centers, basic technologies, toward more sophisticated for example, is one of the reasons why the main technical and economic advice, tailor-made to method for coffee processing has not been widely farmers’ circumstances and market opportunities, adopted. The lack of market centers with proper as well as expanding the menu of technologies storage facilities also contributes to high post- through further research. This could be beyond the harvest losses that depress returns, especially for capacity of the public service alone and requires: perishable products. (i) a policy shift to leverage investments that are both public and private for agricultural research; Access to extension services (ii) mobilizing different actors in extension delivery; and (iii) promoting modern delivery modalities While the ARD policy recognizes that research is (e.g., using digital technologies). Recent reforms important, the main emphasis is on agriculture have been introduced to: (i) facilitate greater extension services. Accordingly, the Government plurality in the delivery of agricultural services, expanded its extension services in the early including agricultural extension and research, to 2000s to cover most of the country, establishing allow for more nuanced approaches to technology Farmer Training Centers (FTCs) at the sub-district generation and dissemination; and (ii) a greater (kebele) level and manning each FTC with three focus within agricultural research and extension Development Agents (DAs) specializing in crop systems on technologies and agricultural practices production, livestock husbandry and natural that help farmers adapt to changing (and more resource management. Nonetheless, the functional erratic) conditions, including integrating climate status of FTCs varies, with some classified as model information into agricultural advisory services. FTCs, while others provide only basic services and The focus is therefore on reorienting the messages are barely functional. In coffee- or horticulture- and delivery modes, and not necessarily simply on producing areas, the three DAs are supported by increasing the number of government extension coffee or horticulture experts and, in a few areas service providers. with irrigation potential, irrigation agronomists are also in place. The main thrust of the policy is to reach Private sector engagement as many farmers as possible with simple, standard messages on new technologies (mostly improved Similar to the rest of the economy, private seeds and fertilizers), with a heavy emphasis on sector participation has not been a key pillar of cereals and improved agricultural practices, such agriculture and rural development in Ethiopia. as row planting, integrated pest management, The scant attention paid to rural enterprise improved animal husbandry, etc. While the development is reflected in the small budget messages are somewhat limited, the expansion share of ARD allocated to this area over the past of extension services has been significant. The decade. Under the homegrown economic reform number of DAs increased from 2,500 in 1995 to agenda, over the past two years the Government 12,500 in 2002 and then to 70,000 in 2020, and has undertaken a comprehensive review and they currently serve 80 percent of farm households revision of its policy, with an overarching thrust across the country (Bachewe et al., 2017). of revisiting the dominant role of the public sector in both service delivery and agricultural markets. To maintain healthy growth in agriculture, the The Government is opening up to greater private policy approach will need to become more sector participation and promoting market- nuanced. This includes the generation of a wider based approaches for smallholder agricultural set of new technologies and, therefore, greater development. Some of the key areas for private investment in agricultural research, and helping sector participation include agriculture services to transition from agricultural extension that provision, infrastructure development, including focuses on the dissemination of a narrow set of market development, cold chains and warehouses, 101 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY input production and distribution, and agriculture inconsistent with demand. All fertilizer is imported output marketing and processing. However, the by the Government through the Ethiopian Agricultural transition to greater private sector participation is Business Corporation (EABC) under the direction hampered by market distortions and regulations of the MoA, which is currently the sole importer of that present a challenging business environment chemical fertilizer into the country. Improved seeds for the private sector. Some of these market are developed by government research institutes distortions are highlighted below. and their multiplication is undertaken by the Ethiopia Agriculture Business Cooperation (EABC), regional Government market interventions seed companies, and a small network of private seed growers and cooperative-based seed producers Input markets (CBSP). The participation of private seed multipliers is limited. The Government also conditions access to Unlike several other African countries, Ethiopia does basic and pre-basic seeds on predetermined sales not support direct input subsidies and no funding is prices that are intended to keep prices to farmers low. allocated to such subsidies in the budget. Instead, the Thus, incentives for private actors to engage in the Government controls input distribution and influences seed supply system are weak. profit margins that cooperatives and other input distributors can charge on fertilizer and seed sales, Nonetheless, private seed companies (both local and keeps margins low at the level of multiplication/ and foreign) have started to emerge as potential imports. The Government’s hands-on policy in input actors alongside the public sector. None of them distribution is demonstrated by the predominance develops their own varieties, relying mostly on EIAR, of public agencies (government nurseries, breeding RARIs, and EABC for (pre-)basic seed of improved stations, animal feed production units, AI facilities, varieties. Consequently, there is under-investment etc.) and parastatals in the import, multiplication and in improved seed varieties, especially outside the sometimes delivery (as in the case of AI services) key cereal crops. Ethiopia scores poorly under the of key agricultural inputs and related services. The 2019 Enabling Business of Agriculture indicator biggest actors in the distribution of agricultural inputs “supplying seed,” with a score of 55 in relation to are farmers’ cooperatives and their unions, backed by its regional comparator countries Kenya (77.47), the Government. There are also Input Directorates at Tanzania (79.47) and Uganda (75.65). This indicator, the Federal Ministry of Agriculture (MoA) and Regional which assesses regulations, as well as the time and Bureaus of Agriculture (BoA) that are responsible cost of registration of a seed variety, suggests that a for overall market coordination and providing input better regulatory environment for varieties and seed demand projections to key actors in the agricultural is required. Thus, liberalization of agricultural input input supply chain. They determine the prices of inputs markets and shifting the Government’s focus toward produced or channeled through the public system building capacity for regulation as opposed to direct and assign inputs that are imported or produced by delivery is therefore necessary. public enterprises to different cooperatives/unions or woreda agricultural offices for subsequent sale to Output market price distortions farmers. Because the Government focuses on direct engagement, its capacity for oversight and regulation The prices of agricultural outputs, particularly is limited. grains, are distorted, which disincentivizes surplus production by rural farmers. The Government has The Government has a hands-on policy in input prioritized household food security and national food distribution that has kept prices low but tends sovereignty through food and cash transfers, and to crowd out the private sector, as it reduces livelihood development initiatives in rural areas. It the incentive to participate in the input supply has also subsidized imports of wheat and edible oil system. Such a policy results in supply that is and put in place grain export bans and marketing 102 PRIORITIES FOR INCREASING HOUSEHOLD INCOME restrictions with a view of controlling price escalation communal land) is often not demarcated, registered, of basic foods and ensuring supplies for urban or mapped. While rules permit for joint titling of land populations. Prices are therefore kept artificially use rights, only 44 percent of land is under joint title, low. For oilseeds and wheat, this has been further with 36 percent of titled land only male-owned and compounded by periodic imports (wheat, palm oil, 20 percent under female title. The policy allows the and food aid), subsidized distribution, and a general expropriation of land use rights for developmental lack of transparency about the quantity and timing (and other) purposes, and land holdings are often of imports, overall stocks and pricing. While the redistributed following the development of irrigation Government plans to revisit the restrictions on grain schemes and watershed/rangeland management exports and gradually eliminate subsidized imports initiatives. Rules governing the use of agricultural of wheat and edible oil, they remain a key pillar of land (land use planning) have not been developed and the Government’s food security policy, which needs this renders land administration complicated, with urgent reform. mandates overlapping various government levels. Land administration is therefore often inefficient, The establishment of the Ethiopian Commodity diverse and hinders investments aimed at improving Exchange (ECX) brought access to market data, and protecting land. Agricultural production is created orderly markets, and mitigated price risks therefore not guided by approaches that would that curb market participation by smallholder promote optimum uses of land and requirements for farmers. The ECX connects 3.5 million smallholder investments to protect land from degradation. farmers to markets. However, being the sole mode through which crops such as coffee can be exported, Financial Access the ECX marketing restrictions through approved regional centers increase the costs of doing business Rural finance remains a key challenge. Most to trade in these products, reducing the passthrough financing measures are through preferential of market prices to farmers. Its pricing mechanism access to credit, in some cases delivered by also fails to adequately incentivize the production Regional Bureaus of Agriculture in the case of and processing of high-quality coffee, resulting inputs or guarantees to favored institutions such as in low-quality coffee processing dominating the cooperatives. At the national level, there are credit market. This needs to be reviewed. controls that, for a prolonged period, provided preferential access to SOEs, resulting in stagnating Land markets credit provision to the private sector. Limited technical capacity for credit risk assessments for As per Article 40 of the 1995 Constitution, SMEs, especially rural enterprises, has further ownership of all rural and urban land and the constrained credit provision to the agriculture country’s water resources are vested in the state. sector. Furthermore, rural finance is approached However, particularly for land, rural households have from the perspective of availing resources to user rights that cannot be arbitrarily withdrawn. finance production activities, but with very few Furthermore, rural land can be leased out, as well as options developed for managing risk. Agriculture inherited. Rules governing the transfer of user rights insurance is thus underdeveloped, limiting (i.e., leasing to a third party that allows consolidation households’ options for dealing with climate- of land holdings by more progressive farmers) related shocks. This disincentivizes market are ambiguous and vary across the country. Land participation by risk-averse households that prefer certification and registration have been progressing, to hold extra buffer stocks instead. Meanwhile, but without formally enacted registration and government reforms and progress in these areas cadastral laws. Thus, some land (e.g., pastoral and have been slow. 103 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Foreign Currency Markets Government aims to build greater capacity to control the incidence of crop and livestock pest/disease The exchange rate in Ethiopia is overvalued and outbreaks and promote more sustainable agricultural accompanied by exchange rate controls on foreign practices to control environmental degradation and currency retention and withdrawals resulting their impact on livelihoods. in shortages and credit rationing. While the Government has started devaluing the currency and Restrictions on the free movement of labor has devalued by more than 40 percent in the past 18 months, the real exchange rate has continued Beyond strong government intervention in markets to appreciate due to high inflation. The parallel and economic development, there is also a tradition exchange rate premium has ranged between 25 of controlling the movement of labor. This takes the and 30 percent over this period. The exchange form of household registration requirements and rage misalignment and forex controls have two the need to obtain kebele IDs, which are required to adverse impacts on the agriculture sector. Although access government services. These requirements input imports have preferential access to foreign slow the integration of migrants and discourage currency, its scarcity results in delays in accessing migration. While the role of rural-urban migration in foreign currency, causing irregular input availability. linking rural areas to opportunities is acknowledged, Moreover, the overvalued exchange rate penalizes policy makers are more concerned about urban agriculture exporters, depressing their returns. services being overwhelmed by an expanding Various simulations provide robust evidence that urban population. Consequently, policies around agriculture exporters are net beneficiaries from an rural-urban migration are still largely focused on exchange rate alignment in Ethiopia. discouraging it. There are concerns over the outflow of labor from rural areas damaging the agriculture Resilience sector, but the analysis presented in this report suggests the opposite effect. As such, rural-urban The Government’s emphasis on household food migration is an important pathway for facilitating security and increasing the productivity of cereal both agricultural transformation and linking the production lays the foundation for improving rural rural youth to off-farm opportunities. incomes. Analysis in this report finds that farmers will only produce for the market if their basic consumption needs are met first—i.e., if their access to food is ensured—much of which is predicated on growth in cereal production. Moving forward, the challenge is to build on this foundation and shift from food security support toward building the resilience of agricultural production systems. For example, the approach to agricultural technology development and dissemination is focused on increasing agricultural yields under normal conditions, providing few solutions to help farmers withstand shocks, deal with variable weather and shifting seasons, or diversify into new production streams. Similarly, natural resource management is promoted from the perspective of rehabilitating/ protecting the physical environment, with little thought regarding linking related investments with opportunities for diversifying into more robust production systems. Under its revised ARD policy, the 104 PRIORITIES FOR INCREASING HOUSEHOLD INCOME Priority policies orientation and agriculture value-chain development to creating off-farm jobs, while investment in irrigation are important for increasing agricultural productivity for the The constraints to rural income growth identified in largest and one of the poorest groups of rural households. this RID reflect the limits that the past ARD model has The Government has devoted significant resources reached, together with the interventions required to in recent years to rural infrastructure development. take rural development to the next stage. A set of However, continued government investment is required priority areas for interventions is therefore proposed to improve rural connectivity, especially feeder roads, here, based on two broad sets of criteria. The first is the access to irrigation and supporting infrastructure. It is impact of the constraints on: (i) changing incentives for also necessary to mobilize additional funding beyond households to produce for the market; (ii) increasing the public sector. A priority area is establishing an agriculture surplus generation through productivity irrigation fund that includes both public and private gains and greater resilience to climate shocks; (iii) funding from levying water, whose current fee levels mitigating the disadvantage of low economic density and collection rates are very low and are insufficient to due to remoteness; (iv) rural enterprise development cover the O&M costs of irrigation schemes. The main along the non-farm segment of the food system; constraint on this is the absence of clear regulations and (v) reducing the cost of migration. An additional and guidelines concerning the implementation of water priority is addressing unequal access to physical use charges and irrigation service fees. The high impact and human assets for women and gendered norms of infrastructure investment on increasing market that keep women on farms. Under these criteria, orientation, agriculture surplus generation and off-farm the impact of the constraints considers whether it job creation, makes addressing infrastructure gap a high is cross-cutting across pathways, whether there is priority for immediate government action. quantitative evidence of impact on agriculture surplus generation and production orientation, or whether it Private sector participation in delivery of benefits the poor. A second broad set of criteria is the supporting infrastructure feasibility of solutions to address the constraints in terms of difficultness of implementation, government In line with the reform thrust for increased private buy-in and asymmetry of benefits across groups. sector participation, government investments in infrastructure should use, or be complemented Twelve priority areas are identified from the by, approaches that incentivize private on-farm prioritization process. These are discussed investments, and private sector participation in below, along with their priority ranking. They are infrastructure development, especially on supporting summarized in Table 26 presenting the immediate infrastructure. Such an approach is consistent with interventions and Table 27 presenting the medium- government reforms aimed at shifting from a state- to to long-term interventions. The medium- to long-term private sector-led development model. The expanded interventions are those where solutions are difficult availability of infrastructure through private sector to implement due to technical challenges or political creation has a big impact on value-chain development economy challenges, or where the interventions and elongation. It allows for production to take place require a long gestation period to bear results. from cities, creating rural jobs in the process, and hence has a cross-cutting impact on both agricultural Addressing infrastructure gaps focused on and non-agricultural incomes. It is therefore a high connectivity, irrigation, land structures for priority area for government action. protecting or rehabilitating eroding landscapes and other supporting infrastructure Agriculture input market deregulation Improving connectivity and supporting infrastructure is While restrictions on the input markets, for example, crucial for both increasing smallholder farmers’ market the importation of fertilizer, are being loosened, 105 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY there remains a strong a reliance on public Improving market linkages agencies for agriculture technology development, influence on pricing of inputs sourced from the The Government needs to shift to market facilitation public research system, preferential treatment to instead of being a market player, by focusing on cooperatives remain prevalent and a number of developing public goods such as market information public agencies that are engaged in the production systems, and by strengthening rules and regulation and distribution of agricultural inputs particularly in around contracting, and improving the environment the livestock subsector. Even under the ACC, input for enterprise growth along agriculture value chains. provision is based by promoting government backed This includes a combination of direct support to both co-operatives, which has yielded some results, but co-operatives and government under the AGP, as well still limited in terms of technological development. as MSMEs as planned under the FSPR in the short The government ought to shift focus from direct term, which the Government is making good progress delivery of agricultural inputs to oversight and on. However, opening the trading sector to foreign regulation of input supply, particularly to ensure that investment would have a strong catalyst effect on a minimum quality of inputs is maintained, which agriculture value-chain development, which could alter requires investments in building the capacity for the geography of food production and processing with regulation. This is recognized in the policy reform strong benefits to rural households’ groups producing and a new Agricultural Regulation Agency has urban consumed goods or those that have diversified been established but is yet to be fully capacitated into cash crops. The trading sector has been kept on and to lay down the systems required to effectively the negative list of sectors where foreign investment is regulate input supply. With technology application, permitted. However, the policy leaves open the option especially improved seeds low across all groups of of revisiting these restrictions, but that opening is still rural households, and strong government buy-in, being discussed suggests implementation will be slow. input market deregulation are a high priority area The interventions in this area are therefore deemed a for immediate intervention. medium- to long-term priority. Agriculture output market deregulation Re-orienting extension services provision The Government’s intervention in output markets, The Government’s public service-led approach especially the maize export bans, has artificially has promoted the adoption of basic agriculture suppressed the price of grains. This has reduced technologies that contributed to improvements incentives, as well as market opportunities, for in yields. Extension services coverage increased surplus production for cereals. There is therefore significantly. Since this is mostly biased toward a need to eliminate export restrictions. However, cereals and only delivered simple messages, the the cereal export ban remains a core part of the challenge is now to shift toward more sophisticated Government’s strategy to support urban food security. market-oriented messages, which is best achieved The policy reform has opened up the opportunity to by permitting a plurality of advisory services revisit how this is done and to loosen restrictions on provision and promoting commercial approaches exports and provide a more transparent system. In in the government research system. Re-orienting the context of rising food inflation, the loosening of extension services is a high priority intervention, export restrictions is unlikely to receive immediate given its impact on technological adaptation and traction, hence it is categorized as a top but medium- farmers production orientation. The high government to long-term priority. attention this area is receiving is warranted. 106 PRIORITIES FOR INCREASING HOUSEHOLD INCOME Financial sector reforms Improving natural resource governance and land administration Laws and regulations on the use of warehouse receipts and a functional warehousing system place Ethiopia Natural resource governance for both land and above its comparators (second only to Tanzania) on water would also need attention to complement the regulatory framework for agriculture finance. the scale-up of investments in rural infrastructure. However, credit controls at the macro level, along with Ethiopia has gone a long way in terms of preferential access, have resulted in credit rationing. establishing a system for watershed and rangeland This has affected the agriculture sector more due to management that includes investments on land typical challenges faced by SMEs that dominate the through government support and community sector, lack of capacity for risk assessment for lending mobilization and investments in irrigation to the agriculture sector, and the underdevelopment of development. However, practices on benefit financial instruments, including insurance products, sharing, distribution of rehabilitated farmlands designed for agriculture. The sector thus still relies and access to rehabilitated communal lands and to a larger degree on direct government financing for developed irrigation infrastructure are ad hoc, access to input for farmers (high default rates and discretionary, and not always equitable—distorting limited of funding have been reported as constraints to incentives for proper management and protection input credit for agriculture commercialization clusters) of resources. Furthermore, oversight on natural and cooperatives. A low take up of agriculture finance resource use including information on the resource instruments (e.g., weather-based crop insurance) base, land use planning, and oversight on water suggests high implementation challenges, making use (to avoid over exploitation of ground water this a low priority area for short-term intervention. resources and to promote equitable water sharing arrangement with downstream users) is lacking. Foreign Currency reforms While the formal land user rights have expanded, including joint land titling, the restrictions on land An overvalued exchange rate, and foreign currency transactions and the transfer of user rights under controls along with preferential access, have also the current system should be addressed to allow resulted scarcity and rationing of forex, while imposing for greater efficiency in land use and to promote an implicit tax on exporters, especially in the agriculture land consolidation. There is also a need to develop sector. The lack of foreign currency is a major constraint a land management database to improve land for the private sector economy wide. The Government’s registration and enforce joint titling and women’s homegrown economic reform agenda recognizes the land rights. This is a top but challenging priority need to address foreign exchange misalignment but area, and hence this should be considered for consensus on the impacts of this policy is lacking. The medium- to long-term implementation. distributional impacts are also asymmetric, with those currently receiving preferential treatment likely to lose Relaxing constraints on the movement of labor out. The Government has pursued with devaluation but not fast enough to depreciate the real exchange rate There is limited traction on improving in the high inflation environment and it has also rolled opportunities for rural-urban migration, but this back on previously relaxed export retention policies, remains an important pathway for expanding signaling the difficulty of implementing reforms access to off-farm opportunities to the rural in this area. The forex reforms are thus deemed a population, particularly the rural youth. This is medium-term priority area of reforms under the therefore considered a medium priority area for current environment. long-term implementation. 107 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Expanding urban investments the slightly better educated youth are likely to migrate. This is therefore considered a medium priority area for There is need to reinforce the urban pull through long-term interventions. expansion of urban-based (export) industries by attracting government and private investment into Gender equality enhancement these areas and adapting urban areas to expanding populations by expanding government investment into It is important to address gender gaps in education urban infrastructure and public service delivery. These and training, access to land, as well as norms around are critical for encouraging and managing rural-urban women’s occupations and roles within households to migration. There are significant quantified effects of equalize access to opportunities. It has both short- migration on agricultural productivity and land markets term priority interventions, such as vocational that shows attracting labor from rural to urban areas training and long-term priority areas related to has transformational benefits, but at the beginning only increasing schools’ progression, especially for girls. 108 PRIORITIES FOR INCREASING HOUSEHOLD INCOME Table 26: Short-term priority intervention areas for increasing rural incomes Constraint Pathway Priority Interventions Level Investment gaps Low rural • Market-oriented production High • Rural roads investments connectivity • Increasing economic density Limited access to • Agriculture surplus generation Medium • Irrigation investments irrigation Low access to • Agriculture surplus generation High • Investment in R&D for climate-smart agriculture climate-smart technologies agriculture • Incentives for on-farm private investments technologies Lack of logistical • Rural enterprise development High • Investments in modernized physical markets, cold infrastructure • Market-oriented production chains, warehouses and storage facilities Depleting natural • Agriculture surplus generation High • Land structures for protecting or rehabilitating resources eroding landscapes Market related constraints Input shortages • Agriculture surplus generation High • Liberalization of input markets and unavailability • Rural enterprise development Weak price • Market-oriented production High • Streamlining marketing restrictions incentives due to • Rural enterprise development • Revising the incentive structure to promote market distortions premium coffee production Low market • Market-oriented production Medium • Contract farming linkages • Market information systems • Direct support to farmer groups and SMEs Risk management • Agriculture surplus generation Low • Vegetation index-based insurance financial • Livestock based insurance instruments High job search • Reducing barriers to migration Medium • Employment intermediation services costs • Market-oriented production • Youth apprenticeships • Expand investments in urban based industries Capacity constraints Limited access to • Agriculture surplus generation High • Plurality of extension services complex, • Market-orientated production • ICT based advisory service delivery mechanisms market-focused, • Rural enterprise development • Retraining of extension services providers advisory services Low education • Reducing barriers to migration High • Gender-focused vocational training and skills • Market-oriented production Gender biases in • Rural enterprise development High • Gender representation in decision making intra-household • Market orientation structure & enterprise group formation labor allocation Policies and regulations Lack of access • Agriculture surplus generation Medium • Input voucher system to credit • Rural enterprise development • Elimination of credit controls & preferential • Reducing barriers to migration treatment Land fragmentation • Agriculture surplus generation High • Cluster approach limits technological • Develop equipment rental markets suitable for adoption small farm sizes Gender bias in • Market-orientated production Medium • Enforcing land co-titling land access 109 ETHIOPIA RURAL INCOME DIAGNOSTICS STUDY Table 27: Medium-term priority intervention areas for increasing rural incomes Constraint Pathway Priority Interventions Level Investment gaps Low digital • Market-oriented production High • ICT infrastructure development connectivity • Increasing economic density Limited access to • Agriculture surplus generation Medium • Rationalizing institutional arrangements irrigation • Review regulations and legal provisions for water user charges to increase Distorted incentives • Agriculture surplus generation High • Improve natural resource governance and land for natural resource management systems management Poor access to • Reducing barriers to migration High • Urban infrastructure investments urban services deterring migration Market related constraints Weak price • Market-oriented production High • Elimination of export bans incentives due to market distortions Limited knowledge • Rural enterprise development High • Open trading sector to foreign ownership and private sector investment in value chain development Capacity constraints Low education • Reducing barriers to migration High • Fostering school progression, especially among girls and skills • Market-oriented production Policies and regulations Lack of access to • Rural enterprise development High • Strengthening financial institutions capacity for credit for credit assessment rural enterprises Exchange rate • Rural enterprise development Medium • Exchange rate unification misalignment • Market-oriented production • Remove foreign exchange controls Burdensome • Reducing barriers to migration Medium • Reducing minimum stay requirements for administrative obtaining Kebele IDs procedures for IDs • Removing release letter requirement • Digital IDs Limited access • Reducing barriers to migration Medium • Expand public investment in urban infrastructure, to public services housing and services and housing for migrants Land fragmentation • Agriculture surplus generation Medium • Remove restrictions on land transactions and limitations to transfer of user rights mechanization Barriers to trade • Agriculture surplus generation Medium • Free trade agreements • Rural enterprise development • Strengthening capacity and enforcement of SPS 110 REFERENCES References Abebe, G., Buehren, N., & Goldstein, M. 2020. 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