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Abstract

This article reviews recent results on technology adoption in developing countries, primarily from field experiments. It focuses on studies that highlight three constraints to adoption: credit, insurance, and information. Interventions supplying credit are consistently effective in spurring technology adoption for a minority of farmers, while interventions supplying insurance have had more mixed results. This review suggests that one mitigating factor on demand for both of these products is incomplete information, which adds additional uninsurable risk to the technology adoption decision. A broad group of studies identify the presence of strong informational frictions. The review concludes with some potential directions for future research.

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2018-10-05
2024-04-20
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Literature Cited

  1. Aker JC, Ksoll C 2016. Can mobile phones improve agricultural outcomes? Evidence from a randomized experiment in Niger. Food Policy 60:44–51
    [Google Scholar]
  2. Ashour M, Billings L, Gilligan D, Hoel JB, Karachiwalla N 2017. Do beliefs about agricultural inputs counterfeiting correspond to actual rates of counterfeiting? Evidence from Uganda Disc. Pap. 01552 Int. Food Policy Res. Inst. Washington, DC:
  3. 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. Am. J. Agric. Econ. 91:4973–90
    [Google Scholar]
  4. Atkin D, Chaudhry A, Chaudry S, Khandelwal AK, Verhoogen E 2017. Organizational barriers to technology adoption: evidence from soccer-ball producers in Pakistan. Q. J. Econ. 132:31101–64
    [Google Scholar]
  5. Banerjee A, Breza E, Chandrasekhar AG, Mobius M 2016. Naive learning with uninformed agents Work. Pap. Stanford Univ. Stanford, CA:
  6. Banerjee A, Duflo E, Glennerster R, Kinnan C 2014. The miracle of microfinance? Evidence from a randomized evaluation. Am. Econ. J. Appl. Econ. 7:122–53
    [Google Scholar]
  7. Beaman L, BenYishay A, Magruder J, Mobarak AM 2017. Can network theory-based targeting increase technology adoption? Work. Pap. Univ. Calif. Berkeley:
  8. Beaman L, Karlan D, Thuysbaert B, Udry C 2014. Self-selection into credit markets: evidence from agriculture in Mali NBER Work. Pap. 20387
  9. BenYishay A, Jones M, Kondylis F, Mobarak AM 2016. Are gender differences in performance innate or socially mediated? Policy Res. Work. Pap. 7689 World Bank Washington, DC:
  10. BenYishay A, Mobarak AM 2017. Social learning and incentives for experimentation and communication Work. Pap. Yale Univ. New Haven, CT:
  11. Bold T, Kaizzi K, Svensson J, Yanagizawa-Drott D 2017. Lemon technologies and adoption: measurement, theory, and evidence from agricultural markets in Uganda. Q. J. Econ. 132:31055–100
    [Google Scholar]
  12. Cai H, Chen Y, Fang H, Zhou LA 2015. The effect of microinsurance on economic activities: evidence from a randomized field experiment. Rev. Econ. Stat. 97:2287–300
    [Google Scholar]
  13. Carter MR, de Janvry A, Sadoulet E, Sarris A 2017. Index insurance for developing country agriculture: a reassessment. Annu. Rev. Resour. Econ. 9:421–38
    [Google Scholar]
  14. Carter MR, 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. Am. J. Agric. Econ. 95:51345–51
    [Google Scholar]
  15. Carter MR, Laajaj R, Yang D 2014. Subsidies and the persistence of technology adoption: field experimental evidence from Mozambique NBER Work. Pap 20465
  16. Carter MR, Laajaj R, Yang D 2016. Savings, subsidies, and technology adoption: field experimental evidence from Mozambique Work. Pap. Univ. Calif. Davis:
  17. Case A, Besley T 1993. Modeling technology adoption in developing countries. Am. Econ. Rev. 83:2396–402
    [Google Scholar]
  18. Centola D, Macy M 2007. Complex contagions and the weakness of long ties. Am. J. Sociol. 113:702–34
    [Google Scholar]
  19. Cole S, Fernando AN 2012. The value of advice: evidence from mobile phone-based agricultural extension Work. Pap. 013-047 Harv. Bus. Sch. Cambridge, MA:
  20. Cole S, Giné X, Tobacman J, Topalova P, Townsend R, Vickery J 2013. Barriers to household risk management: evidence from India. Am. Econ. J. Appl. Econ. 5:1104–35
    [Google Scholar]
  21. Conley TG, Udry CR 2010. Learning about a new technology: pineapple in Ghana. Am. Econ. Rev. 100:135–69
    [Google Scholar]
  22. Crépon B, Devoto F, Duflo E, Parienté W 2015. Estimating the impact of microcredit on those who take it up: evidence from a randomized experiment in Morocco. Am. Econ. J. Appl. Econ. 7:1123–50
    [Google Scholar]
  23. DeMarzo PM, Vayanos D, Zwiebel J 2003. Persuasion bias, social influence, and unidimensional opinions. Q. J. Econ. 118:3909–68
    [Google Scholar]
  24. Duflo E, Kremer M, Robinson J 2008. How high are the returns to fertilizer? Evidence from field experiments in Kenya. Am. Econ. Rev. 98:2482–88
    [Google Scholar]
  25. Emerick K, de Janvry A, Sadoulet E, Dar MH 2016. Technological innovations, downside risk, and the modernization of agriculture. Am. Econ. Rev. 106:61537–61
    [Google Scholar]
  26. Evenson RE, Westphal LE 1995. Technological change and technology strategy. Handb. Dev. Econ. 3:Pt. A2209–99
    [Google Scholar]
  27. Feder G, Just RE, Zilberman D 1985. Adoption of agricultural innovations in developing countries: a survey. Econ. Dev. Cult. Change 33:2255–98
    [Google Scholar]
  28. Foster AD, Rosenzweig MR 1995. Learning from doing and learning from others: human capital and technical change in agriculture. J. Political Econ. 103:61176–209
    [Google Scholar]
  29. Geroski PA 2000. Models of technology diffusion. Res. Policy 29:4–5603–25
    [Google Scholar]
  30. Giné X, Yang D 2009. Insurance, credit, and technology adoption: field experimental evidence from Malawi. J. Dev. Econ. 89:11–11
    [Google Scholar]
  31. Grilliches Z 1957. Hybrid corn: an explanation in the economics of technological change. Econometrica 25:4501–22
    [Google Scholar]
  32. Hanna R, Mullainathan S, Schwartzstein J 2014. Learning through noticing: theory and evidence from a field experiment. Q. J. Econ. 129:31311–53
    [Google Scholar]
  33. Harrison G, List JA 2004. Field experiments. J. Econ. Lit. 42:41009–55
    [Google Scholar]
  34. Islam M 2014. Can a rule-of-thumb tool improve fertilizer management? Experimental evidence from Bangladesh Work. Pap. Harv. Univ. Cambridge, MA:
  35. Karlan D, Kutsoati E, McMillan M, Udry C 2011. Crop price indemnification loans for farmers: a pilot experiment in rural Ghana. J. Risk Uncertainty 78:137–55
    [Google Scholar]
  36. Karlan D, Osei R, Osei-Akato I, Udry C 2014. Agricultural decisions after relaxing credit and risk constraints. Q. J. Econ. 129:2597–652
    [Google Scholar]
  37. Kondylis F, Mueller V, Sheriff G, Zhu J 2016. Do female instructors reduce gender bias in diffusion of sustainable land management techniques? Experimental evidence from Mozambique. World Dev 78:436–49
    [Google Scholar]
  38. Kondylis F, Mueller V, Zhu J 2017. Seeing is believing? Evidence from an extension network experiment. J. Dev. Econ. 125:1–20
    [Google Scholar]
  39. Marr A, Winkel A, van Asseldonk M, Lensinck R, Bulte E 2016. Adoption and impact of index insurance and credit for smallholders in developing countries: a systematic review. Agric. Financ. Rev. 76:194–118
    [Google Scholar]
  40. Meiburg CO, Brandt K 1962. Agricultural productivity in the United States: 1870–1960. Food Res. Inst. Stud. 3:63–85
    [Google Scholar]
  41. Mobarak AM, Rosenzweig M 2012. Selling formal insurance to the informally insured Disc. Pap. 1007 Econ. Growth Cent., Yale Univ. New Haven, CT:
  42. Munshi K 2004. Social learning in a heterogeneous population: technology diffusion in the Indian green revolution. J. Dev. Econ. 73:1185–213
    [Google Scholar]
  43. Rosenzweig M, Udry C 2016. External validity in a stochastic world NBER Work. Pap 22449
  44. Schickele A 2016. Make it rain Policy Bull., Abdul Latif Jameel Poverty Action Lab, Cent. Eff. Glob. Action, Agric. Technol. Adopt. Initiat. Cambridge, MA: https://www.povertyactionlab.org/sites/default/files/publications/make-it-rain-high.pdf
  45. Schultz TW 1975. The value of the ability to deal with disequilibrium. J. Econ. Lit. 13:3827–46
    [Google Scholar]
  46. Sunding D, Zilberman D 2001. The agricultural innovation process: research and technology adoption in a changing agricultural sector. Handb. Agric. Econ. 1:Pt. A207–61
    [Google Scholar]
  47. Tarozzi A, Desai J, Johnson K 2015. The impacts of microcredit: evidence from Ethiopia. Am. Econ. J. Appl. Econ. 7:154–89
    [Google Scholar]
  48. Tjernström E 2017. Learning from others in heterogeneous environments Work. Pap. Univ. Wisc. Madison:
  49. World Bank. 2007. World development report 2008: agriculture for development Rep. World Bank Washington, DC: http://openknowledge.worldbank.org/handle/10986/5990
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