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Impact of Improved Farm Technologies on Yields: The Case of Improved Maize Varieties and Inorganic Fertilizer in Kenya

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  • Nyangena, Wilfred
  • Juma, Ogada Maurice

Abstract

This study investigates the impact of package adoption of inorganic fertilizers and improved maize seed varieties on yield among smallholder households in Kenya. We used a quasi-experimental difference-in-differences approach combined with propensity score matching to control for both time-invariant and unobservable household heterogeneity. Our findings show that inorganic fertilizers and improved maize varieties significantly increase maize yields when adopted as a package, rather than as individual elements. The impact is greater at the lower end of the yield distribution than at the upper end. A positive effect of partial adoption is experienced only in the lower quartile of yield distribution. The policy implication is that complementary agricultural technologies should be promoted as a package, and should target households and areas experiencing low yields.

Suggested Citation

  • Nyangena, Wilfred & Juma, Ogada Maurice, 2014. "Impact of Improved Farm Technologies on Yields: The Case of Improved Maize Varieties and Inorganic Fertilizer in Kenya," Discussion Papers dp-14-02-efd, Resources For the Future.
  • Handle: RePEc:rff:dpaper:dp-14-02-efd
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    File URL: http://www.rff.org/RFF/documents/EfD-DP-14-02.pdf
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    References listed on IDEAS

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    1. Esther Duflo & Michael Kremer & Jonathan Robinson, 2011. "Nudging Farmers to Use Fertilizer: Theory and Experimental Evidence from Kenya," American Economic Review, American Economic Association, vol. 101(6), pages 2350-2390, October.
    2. Jalan, Jyotsna & Ravallion, Martin, 2003. "Does piped water reduce diarrhea for children in rural India?," Journal of Econometrics, Elsevier, vol. 112(1), pages 153-173, January.
    3. Mariapia MENDOLA, 2005. "Farm households production theories: a review of institutional and behavioural responses," Departmental Working Papers 2005-01, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    4. Christopher B. Barrett & Christine M. Moser & Oloro V. McHugh & Joeli Barison, 2004. "Better Technology, Better Plots, or Better Farmers? Identifying Changes in Productivity and Risk among Malagasy Rice Farmers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 869-888.
    5. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," Review of Economic Studies, Oxford University Press, vol. 72(1), pages 1-19.
    6. Benjamin Crost & Bhavani Shankar & Richard Bennett & Stephen Morse, 2007. "Bias from Farmer Self-Selection in Genetically Modified Crop Productivity Estimates: Evidence from Indian Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 58(1), pages 24-36, February.
    7. Bellon, Mauricio R. & Hellin, Jon, 2011. "Planting Hybrids, Keeping Landraces: Agricultural Modernization and Tradition Among Small-Scale Maize Farmers in Chiapas, Mexico," World Development, Elsevier, vol. 39(8), pages 1434-1443, August.
    8. Jeffrey H. Dorfman, 1996. "Modeling Multiple Adoption Decisions in a Joint Framework," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(3), pages 547-557.
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    Cited by:

    1. Sheahan, Megan & Barrett, Christopher B., 2017. "Ten striking facts about agricultural input use in Sub-Saharan Africa," Food Policy, Elsevier, vol. 67(C), pages 12-25.

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    Keywords

    technology adoption; yield; difference-in-differences; Kenya;

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