IDEAS home Printed from
   My bibliography  Save this paper

Production Risk and Farm Technology Adoption in Rain-Fed, Semi-Arid Lands of Kenya


  • Juma, Maurice
  • Nyangena, Wilfred
  • Yesuf, Mahmud


This study provides empirical evidence on the effects of production risk on farm technology adoption among small holder farmers using plot-level data collected from two semi-arid districts in Kenya, Machakos, and Taita Taveta. We employed a two-stage approach to estimate a production function, and computed the mean and the production risk factors (both variance and skewness) from a production function using Antle’s (1983, 1987) moment-based approach. We then used these moment estimates, together with other household and plot-level characteristics in a pseudo-fixed effect probit model to determine the effects of production risk and farm and household-level variables on households’ decisions to adopt different kinds of farm technologies. In our estimations, by means of Mundlak’s approach (1978), we controlled for unobserved heterogeneities that could potentially be correlated to some of the observed explanatory variables and otherwise bias our estimates. We also addressed the potential endogeneity issues in our estimation using a two-stage IV estimation procedure. Our results showed that, among others, yield variability and the risk of crop failures indeed affect technology adoption decisions in low-income, rain-fed agriculture. But, the direction and magnitude of effects depend on the farm technology under consideration. The results explain why poor farm households in rain-fed and risky production environments are reluctant to adopt new farm technologies with potential production gain because, at the same time, they involve enormous down-side risks. This result underscores the fact that productivity gains are necessary, but not sufficient, conditions to attract farmers to adopt new technologies and agricultural innovations. Risk implications matter. Technology- and location-specific production-risk coping strategies need to be designed to successfully upscale profitable farm technologies across poor farm households in low income countries.

Suggested Citation

  • Juma, Maurice & Nyangena, Wilfred & Yesuf, Mahmud, 2090. "Production Risk and Farm Technology Adoption in Rain-Fed, Semi-Arid Lands of Kenya," Discussion Papers dp-09-22-efd, Resources For the Future.
  • Handle: RePEc:rff:dpaper:dp-09-22-efd

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Dercon, Stefan & Christiaensen, Luc, 2011. "Consumption risk, technology adoption and poverty traps: Evidence from Ethiopia," Journal of Development Economics, Elsevier, vol. 96(2), pages 159-173, November.
    2. Dercon, Stefan, 2004. "Growth and shocks: evidence from rural Ethiopia," Journal of Development Economics, Elsevier, vol. 74(2), pages 309-329, August.
    3. Shively, Gerald E., 1997. "Consumption risk, farm characteristics, and soil conservation adoption among low-income farmers in the Philippines," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 17(2-3), December.
    4. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    5. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    6. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    7. Kassie, Menale & Yesuf, Mahmud & Köhlin, Gunnar, 2008. "The Role of Production Risk in Sustainable Land-Management Technology Adoption in the Ethiopian Highlands," Discussion Papers dp-08-15-efd, Resources For the Future.
    8. Mahmud Yesuf & Randall A. Bluffstone, 2009. "Poverty, Risk Aversion, and Path Dependence in Low-Income Countries: Experimental Evidence from Ethiopia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(4), pages 1022-1037.
    9. Ben Groom & Phoebe Koundouri & Celine Nauges & Alban Thomas, 2008. "The story of the moment: risk averse cypriot farmers respond to drought management," Applied Economics, Taylor & Francis Journals, vol. 40(3), pages 315-326.
    10. Shively, Gerald E., 2001. "Poverty, consumption risk, and soil conservation," Journal of Development Economics, Elsevier, vol. 65(2), pages 267-290, August.
    11. Kim, Kwansoo & Chavas, Jean-Paul, 2003. "Technological change and risk management: an application to the economics of corn production," Agricultural Economics, Blackwell, vol. 29(2), pages 125-142, October.
    12. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    13. Doss, Cheryl R., 2003. "Understanding Farm-Level Technology Adoption: Lessons Learned From Cimmyt'S Micro Surveys In Eastern Africa," Economics Working Papers 46552, CIMMYT: International Maize and Wheat Improvement Center.
    14. Phoebe Koundouri & Céline Nauges & Vangelis Tzouvelekas, 2006. "Technology Adoption under Production Uncertainty: Theory and Application to Irrigation Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(3), pages 657-670.
    15. Eswaran, Mukesh & Kotwal, Ashok, 1990. "Implications of Credit Constraints for Risk Behaviour in Less Developed Economies," Oxford Economic Papers, Oxford University Press, vol. 42(2), pages 473-482, April.
    16. Jackson, Matthew O. & Watts, Alison, 2002. "The Evolution of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 106(2), pages 265-295, October.
    Full references (including those not matched with items on IDEAS)

    More about this item


    farm productivity; Kenya; production risk; farm technology adoption;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rff:dpaper:dp-09-22-efd. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Webmaster). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.