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Selection and Comparative Advantage in Technology Adoption

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  • Tavneet Suri

    (Sloan School, MIT)

Abstract

This paper examines a well known empirical puzzle in the literature on technology adoption: despite the potential of technologies to increase returns dramatically, a significant fraction of households do not use these technologies. I study the use of hybrid maize and fertilizer in Kenya, where there are persistent cross-sectional differences in aggregate adoption rates with a large fraction of households switching in and out of adoption. By allowing for selection of farmers into technology use via comparative advantage differences, I examine whether the yield returns to adopting hybrid maize vary across farmers. If so, high average returns can coexist with low returns for the marginal farmer. My findings indicate the existence of two interesting subgroups in the population. A small group of farmers has potentially high returns from adopting the technologies. Yet, they do not adopt. This lack of adoption appears to stem from supply and infrastructure constraints, such as the distance to fertilizer distributors. In addition, a larger group of farmers faces very low returns to adopting hybrid maize, but chooses to adopt. This latter group might benefit substantially from the development of newer hybrid strains to increase yields. On the whole, the stagnation in hybrid adoption does not appear to be due to constraints or irrationalities.

Suggested Citation

  • Tavneet Suri, 2006. "Selection and Comparative Advantage in Technology Adoption," Working Papers 944, Economic Growth Center, Yale University.
  • Handle: RePEc:egc:wpaper:944
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    Cited by:

    1. Smale, Melinda & Olwande, John, 2011. "Is Older Better? Maize Hybrid Change on Household Farms in Kenya," Food Security International Development Working Papers 118474, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    2. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    3. Jaleta, Moti & Yirga, Chilot & Kassie, Menale & De Groote, Hugo & Shiferaw, Bekele, 2013. "Knowledge, Adoption and Use Intensity of Improved Maize Technologies in Ethiopia," 2013 Fourth International Conference, September 22-25, 2013, Hammamet, Tunisia 161483, African Association of Agricultural Economists (AAAE).
    4. Tavneet Suri, 2009. "Selection and Comparative Advantage in Technology Adoption," NBER Working Papers 15346, National Bureau of Economic Research, Inc.
    5. Elaine M. Liu, 2013. "Time to Change What to Sow: Risk Preferences and Technology Adoption Decisions of Cotton Farmers in China," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1386-1403, October.
    6. Scheiterle, L., 2018. "Soil, striga or subsidies? Determinants of maize productivity in northern Ghana," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277405, International Association of Agricultural Economists.
    7. Adejuwon, Olawale O. & Ilori, Matthew O. & Taiwo, Kehinde A., 2016. "Technology adoption and the challenges of inclusive participation in economic activities: Evidence from small scale oil palm fruit processors in southwestern Nigeria," Technology in Society, Elsevier, vol. 47(C), pages 111-120.
    8. Elaine Meichen Liu, 2008. "Time to Change What to Sow: Risk Preferences and Technology Adoption Decisions of Cotton Farmers in China," Working Papers 1064, Princeton University, Department of Economics, Industrial Relations Section..
    9. Melinda Smale & John Olwande, 2014. "Demand for maize hybrids and hybrid change on smallholder farms in Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 45(4), pages 409-420, July.

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    More about this item

    Keywords

    Technology; Heterogeneity; Comparative Advantage;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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