Myanmar s Changing Rural Economy: Evidence from the Delta & Dry Zone Ben Belton (Michigan State University) Food Security Policy Project LIFT Donor Retreat, Yangon October 2, 2017 The brief was supported with financial assistance from the Livelihoods and Food Security Trust Fund (LIFT), and is also made possible by the generous support of the American people through the United States Agency for International Development (USAID) under the Feed the Future initiative. The views expressed herein should in no way be taken to reflect the official opinion of any of the LIFT donors or the views of USAID or the United States Government
Introduction FSP Surveys Key findings from Delta and Dry Zone 1. Infrastructure 2. Migration & wages 3. Mechanization 4. Credit 5. Rural non-farm business & off-farm employment 6. Agricultural performance 7. Climate change Implications for policy & programming
Food Security Policy Project (FSP) USAID & LIFT funded partnership implemented by MSU, CESD, and IFPRI October 2014-2019 Objectives: Generating and disseminating new knowledge to address evidence gaps and inform better agricultural policy Capacity building and strengthening for research and policy Components: Agricultural value chains and livelihoods research Policy advising Training and outreach
Surveys 2016: Myanmar Aquaculture-Agriculture Survey (MAAS) 2017: Rural Economy & Agriculture Dry Zone Survey (READZ) 3 survey components: Household; Community; Off-farm enterprise Household: Off-farm employment, migration, agricultural production, mechanization Community: Changes within last decade (infrastructure, business inventory, credit access etc.) Off-farm enterprise (machinery supply & rental, traders, processors)
MAAS locations
READZ locations Budalin (Sagaing) Myittha (Mandalay) Pwintbyu (Magway) Magway (Magway)
1. Improvements in infrastructure
Big improvements, from a low base Extent of infrastructure development regionally varied and generally quite limited Villages not accessible by car in monsoon: Delta 68%, Dry Zone 28% Villages with no electricity: Delta 88%; Dry Zone 66% But, big improvements post-2011 2/3 of all electricity connections (Dry Zone) Half of all secondary school construction (Dry Zone)
Cumulative share of primary, lower secondary and upper secondary schools established, by year (1917-2017) 100 90 80 70 60 50 40 30 20 10 0 Primary Lower secondary Upper secondary 1917 1920 1923 1926 1929 1932 1935 1938 1941 1944 1947 1950 1953 1956 1959 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017
2. Accelerating migration, rising wages
Accelerating migration in Delta 100 90 80 70 60 50 40 30 20 10 0 Urban Rural 90% rural-urban 92% domestic 16% of HH have migrants Average migrant age 21 55:45 male/female split 70% employed in manufacturing 1995 1996 1997 1998 1999 2000 2001 2004 2005 2006 2008 2009 2010 2011 2012 2013 2014 2015 Cumulative share of all migrants by year first migrated (%), 1995-2015 (MAAS)
and Dry Zone 100 90 80 70 60 50 40 30 20 10 Domestic International 86% domestic 19% of HH have long term migrants Average migrant age 24 56:44 male/female split 26% employed in manufacturing 55% low-skilled informal jobs 0 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 Cumulative share of all migrants by year first migrated (%), 1995-2016 (READZ)
Migration is driving large rural wage increases Delta Dry Zone Real daily wages (MMK) 4500 4000 3500 3000 2500 2000 1500 1000 500 0 +32% +8% 2011 2013 2016 4500 4000 3500 3000 2500 2000 1500 1000 500 0 +15% +20% 2012 2014 2016 Change in real daily wages for male casual workers (MAAS & READZ)
3. Agriculture mechanizing rapidly
Rental services enabling access to machines 60% +1839% 50% Own Rent Share of farm HHs 40% 30% 20% 10% +216% +1801% +170% 0% 10 years ago 5 years ago Today 10 years ago 5 years ago Today 10 years ago 5 years ago Today 10 years ago 5 years ago Today 2WT 4WT Combine Harvester Thresher Share of farmers using machinery, by machine type, year and ownership status (READZ)
Scale-neutral technology % of farm households using 100 90 80 70 60 50 40 30 20 10 78 83 75 <5 acres >5 & <10 acres >10 acres 60 61 50 13 8 7 0 2WT (Land Preparation) 4WT (Land Preparation) Combine (Harvesting) Share of households using agricultural machinery, by size of landholding (MAAS)
Mechanization reduces labor costs Share of production costs 100% 80% 60% 40% 20% 4% 30% 31% 32% 15% 10% 26% 25% 21% 4% 24% 30% 10% 30% 15% 42% 40% Draft animal Transportation Irrigation Seeds Machinery Inputs Casual labor 0% Monsoon paddy Dry season paddy Green gram Black gram Composition of production costs, by crop (MAAS)
4. Access to formal credit is improving
Improving access to formal financial services for machine purchases Share of sales (%) Bank 27 22 Dealer 48 2 Customer 5 17 77 68 35 Hire purchase agreements with commercial banks began in 2013 Reduced capital constraints for machine suppliers, cost of credit to buyers 2WT 4WT Combine Harvester Source of finance for machinery purchases, 2016 (MAAS)
Sources of credit diversifying 80 70 2011 2016 % of villages with access 60 50 40 30 20 10 0 Share of villages with credit access by source, 2011 & 2016 (MAAS)
Most agricultural credit from formal sources, government is biggest loan provider 60 51% TOTAL LOAN VALUE ($ '000) 50 40 30 20 10 39% 10% 0 Total value of agricultural loans taken by sample farms in 2016-17, by loan provider (READZ)
Credit becoming much cheaper as sources diversify Monthly interest rate (%) 12 2012 2017 10-3% 8-1.3% 6-1.7% -1.3% 4 2-0.1% -0.4% -5.2% 0 Monthly interest rates from informal lenders and microcredit providers, 2012 & 2017 (READZ)
5. Rural non-farm economy growing rapidly
Numbers of non-farm businesses growing quickly MEAN No. ENTERPRISES/VILLAGE 25 20 15 10 5 0 +233% Motor transport Delta 2011 2016 +50% Retail +44% Personal services +67% Food services 25 20 15 10 5 0 +200% Motor transport Dry Zone +57% Retail 2011 2017 +33% Personal services +56% Food services Mean numbers of non-farm enterprise per village by type, 2011 & 2016/17 (MAAS & READZ)
Gender wage gap smaller for non-farm work 7000 6000 0.98 Men Women 5000 4000 3000 2000 1000 0.79 0.69 0 Salaried work Non-farm casual labor Farm casual labor Average daily incomes for men and women worker, by type of work, 2017 (READZ)
Off-farm employment important for all Major role in livelihoods for most households, especially poorest, because of: High levels of landlessness (Delta = 58%, Dry Zone = 40%) Concentration of agricultural land (Bottom 1/3 of farms own 3-4% of farmland, top 1/3 own 70-80%) Household participation in farm and off-farm employment by expenditure quintile (MAAS)
BUT: Agriculture still the main source of primary employment Non-farm occupations 29% Own farm 42% Agriculture provides >70% of primary employment, plus indirect non-farm employment in value chains Agri-labor 29% Agricultural labor is 80% of off-farm employment in Dry Zone Share of individual primary employment, by type (MAAS)
6. Most agriculture performing poorly
Agricultural productivity remains low Gross margin/acre (USD) 800 600 400 200 0-200 -400 Gross Margin/acre (USD) 350 250 150 50-50 -150-250 -350 1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205 211 217 223 229 235 241 Green gram Monsoon Paddy Median = $200/acre Median = $100/acre 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 Median agricultural land = 5.5 acres; Typical annual agricultural income = $1650/HH, or $330/capita
Returns in the Dry Zone are even lower, especially for upland crops 120 115 Mean gross margin/acre (USD) 100 80 60 40 20 82 52 36 19 0 Dry season paddy Monsoon paddy Groundnut Sesame Green gram Mean gross margins (USD/acre) for selected crops (READZ)
Some adoption of improved seed, but progressing slowly 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Improved Local 10 years ago 5 years ago 2016-2017 10 years ago 5 years ago 2016-2017 10 years ago 5 years ago 2016-2017 10 years ago 5 years ago 2016-2017 Rice Groundnut Sesame Green gram Share of households using improved & local seeds, by crop, 2006-2016 (READZ)
Only rice yields are improving 55.5 58.4 62.2 10 years ago 5 years ago 2016-2017 8.7 8.2 7.7 12.2 9.6 8.4 28.9 28.0 27.3 Rice Groundnut Sesame Greengram Reported average yields for selected crops (baskets/acre) in 2016, 2011, 2007 (READZ)
7. Climate change contributing to poor agricultural performance
Increasing frequency & intensity of extreme weather 3% Communities reporting change (%) 100 90 80 70 60 50 40 30 20 10 98 94 89 81 48 37 35 Nature of change (% of communities reporting) 4% 43% 38% 52% 48% Increased a lot Increased a little More erratic Decreased a little Decreased a lot 0 13% Rainfall Temperature Perceptions of change in the intensity or frequency of climate conditions and events over the past 30 years (READZ) Community perceptions of changes in average temperature and rainfall over the past 30 years (READZ)
Yields very strongly affected by climatic conditions 2500 Average crop yield (kg/acre) 2000 1500 1000 500 262 166 45 1440 1088 538 1939 1521 998 547 371 159 432 281 112 414 261 121 Good year Average year Bad year 331 215 83 0 Average crop yields (kg/acre) in years with good, average and poor climatic conditions (READZ)
Implications for policy & programing Sustain investments in infrastructure, and complementary soft infrastructure well trained teachers, health professionals etc. Measures to support safer, less risky, higher quality migration. Overcome emerging spatial inequalities in mechanization (e.g. by improving road access, land levelling). Microcredit widely available but rarely invested in agriculture or non-farm business; Increase MADB payments for non-paddy crops RNFE complements farming but still provides relatively limited employment need options for promoting greater productivity & job growth. Land-poor HH heavily dependent on agricultural labor. Viable farm sector essential for rural incomes & employment. High value labor intensive crops (e.g. fish, melons); R&D to improve pulse, oilseed & paddy varieties and strategies to multiply and distribute. Strategies to mitigate impacts of climate extremes e.g. groundwater irrigation, water storage, stress tolerant varieties.