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Financial Markets, Investment and Productivity in Agriculture

Financial Markets, Investment and Productivity in Agriculture. Christopher Udry Yale University. Root of rural poverty is low agricultural productivity. i . Yields mostly stagnant , improving recently, ag output/ag population not moving, output growth generated by extensification

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Financial Markets, Investment and Productivity in Agriculture

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  1. Financial Markets, Investment and Productivity in Agriculture Christopher Udry Yale University

  2. Root of rural poverty is low agricultural productivity i. Yields mostly stagnant, improving recently, ag output/ag population not moving, output growth generated by extensification ii. Irrigation essentially does not exist iii. Fertilizer use: north America 200 kg/ha; Africa 20 kg/ha

  3. Start with a simple question • Why is fertilizer use so low? • This is not the essential question, but perhaps can be answered • Prices are high (infrastructure, pop density) • But, even at market prices, use appears to be profitable • Looks uniform • Ask people

  4. Despite consistent responses • Barriers are dramatically different across countries • Even within communities, heterogeneity is a key feature

  5. Credit Policy Lessons Preview • Credit constraints rarely the primary barrier to improving farm profitability • Take-up of credit is often low Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  6. How might credit market constraints affect technology adoption? • Farmers don’t have cashto cover the upfront costs of adoption • Farmers don’t have collateralto back a loan • Farmers don’t have financial literacy needed to use credit • There is no credit available • Farmers struggle to save income from one harvest to the next Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  7. Does improving access to credit help? • Access to financial products can affect agricultural activity: • Switching to higher-value crops • crop-related expenditures •  fertilizer use Ashraf et al. 2009; Crepon et al. 2013; Tarozzi et al. 2013; Beaman et al. 2014; Karlan et al. 2013; Carter et al. 2013; Oseiet al. nd Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  8. Does improving access to credit help? • But in most cases, access to credit has no effecton farm profits • I will discuss 3 cases • Ashraf et al. 2009; Creponet al. 2011; Karlanet al. 2013 Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  9. 1. Capital constraints in Ghana? MiDAagriculture program in Ghana takes off from this. • 5 years (2007-12), >$60 million • 30 hours of agronomic training to almost 70,000 farmers • $230 “starter pack” of seed + fertilizer • Randomized roll-out to FBOs

  10. Osei, Osei-Akoto and Udry (2013) use the randomization in the program to show that

  11. Osei, Osei-Akoto and Udry (2013) use the randomization in the program to show that … little changed • Small increases in input use (less than the value of the ‘starter pack’) • Nothing observed on yields, output, income, welfare

  12. Credit is not the only constraint • Increasing access to credit alone rarely improves farmer income • Karlanet al 2013 Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  13. Credit is not the only constraint • Increasing access to credit alone rarely improves farmer income 2. Credit and the poor: Maize Farmers in the Northern Region (Karlan, Osei, Osei-Akoto and Udry) • Uninsured risk is often the binding constraint • Karlanet al 2013 Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  14. Credit is not the only constraint • Increasing access to credit alone rarely improves farmer income 2. Credit and the poor: Maize Farmers in the Northern Region (Karlan, Osei, Osei-Akoto and Udry) • Uninsured risk is often the binding constraint Insurance … Cash… Insurance+Cash...Control • Karlanet al 2013 Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  15. Innovations for Poverty Action Ghana Agricultural Insurance Programme

  16. Take up of credit is low ½ Only half the farmers took up vouchers for fertilizers and seeds in Mozambique 30% Only 30% of eligible households borrow from MFIs Carter et al 2013; Banerjee et al. 2013;Beamanet al. 2014 Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  17. 3. Even in one place, households face varied constraints • Mali (Beaman, Karlan, Thuysbaert, Udry 2014) The most productive farmers are more likely to borrow

  18. Summary: Policy Lessons • Credit constraints are not a primary barrier to increasing farm profitability. • Take-up of credit is often low, suggesting that other constraints play an important role • In some cases, agricultural activity and profits increase when access to capital is improved Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  19. Summary: Policy Lessons • There is evidence of positive selection into borrowing: high marginal productivity farmers who are credit constrained borrow Policy Lessons Preview  Credit Market Inefficiencies Emerging Lessons ATAI Projects Summary

  20. Resources

  21. References • Ashraf, N., Giné, X., & Karlan, D. (2009). Finding missing markets (and a disturbing epilogue): Evidence from an export crop adoption and marketing intervention in Kenya. American Journal of Agricultural Economics, 91(4), 973-990. • Ashraf, N., Karlan, D., & Yin, W. (2006). Tying Odysseus to the mast: Evidence from a commitment savings product in the Philippines. The Quarterly Journal of Economics, 121(2), 635-672. • Augsburg, Britta, Ralph de Haas, Heike Harmgart, and Costas Meghir. 2012. Microfinance at the Margin: Experimental Evidence from Bosnia and Herzegovina. Working Paper, September. • Banerjee, A., Duflo, E., Glennerster, R., & Kinnan, C. (2013). The miracle of microfinance? Evidence from a randomized evaluation. (No. w18950). National Bureau of Economic Research. • Beaman, L., Karlan, D., Thuysbaert, B., & Udry, C. (2014). Self-Selection into Credit Markets: Evidence from Agriculture in Mali. • Burke, M., & Miguel, T. (2013). Selling low and buying high: An arbitrage puzzle in Kenyan villages. • Carter, M. R., Laajaj, R., & Yang, D. (2013). The Impact of Voucher Coupons on the Uptake of Fertilizer and Improved Seeds: Evidence from a Randomized Trial in Mozambique. American Journal of Agricultural Economics, 95(5), 1345-1351. • Crépon, B., Devoto, F., Duflo, E., & Pariente, W. (2014). Estimating the impact of microcredit on those who take it up: Evidence from a randomized experiment in Morocco. Working Paper. • De Janvry, A., McIntosh, C., & Sadoulet, E. (2010). The supply-and demand-side impacts of credit market information. Journal of Development Economics,93(2), 173-188.

  22. References • Duflo, E., Kremer, M., & Robinson, J. (2009). Nudging farmers to use fertilizer: Theory and experimental evidence from Kenya (No. w15131). National Bureau of Economic Research. • Field, Erica, RohiniPande, John Papp, and Natalia Rigol. 2013. Does the Classic Microfinance Model Discourage Entrepreneurship Among the Poor? Experimental Evidence from India. American Economic Review 103 (6): 2196–2226. • Giné, X., Goldberg, J., Silverman, D., & Yang, D. (2012). Revising commitments: Field evidence on the adjustment of prior choices. (No. w18065). National Bureau of Economic Research. • Giné, X., Goldberg, J., & Yang, D. (2010). Identification strategy: A field experiment on dynamic incentives in rural credit markets. • Gine, X., Karlan, D., & Ngatia, M. (2011). Social networks, financial literacy and index insurance. Mimeo. • Karlan, D., Osei, R. D., Osei-Akoto, I., & Udry, C. (2012). Agricultural decisions after relaxing credit and risk constraints. (No. w18463). National Bureau of Economic Research. • Kaboski, Joseph P, and Robert M Townsend. (2011). A Structural Evaluation of a Large-Scale Quasi-Experimental Microfinance Initiative. Econometrica 79 (5): 1357–1406 • Kaboski, Joseph P., and Robert M. Townsend. The impact of credit on village economies. American economic journal. Applied economics 4.2 (2012): 98. • Matsumoto, T., Yamano, T., & Sserunkuuma, D. (2013). Technology adoption in agriculture: evidence from experimental intervention in maize production in Uganda. In An African Green Revolution (pp. 261-278). Springer Netherlands. • Osei, R., Osei-Akoto, I., and C. Udry (2013). The Importance of Farmer Training in changing the Subsistence Nature of Agriculture: The Case of MCA-Ghana Programme” • Tarozzi, A., Desai, J., & Johnson, K. (2013). On the impact of microcredit: Evidence from a randomized intervention in rural Ethiopia.

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