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Adoption and Impact of Improved Groundnut Varieties on Rural Poverty: Evidence from Rural Uganda

  • Kassie, Menale
  • Shiferaw, Bekele
  • Muricho, Geoffrey

This paper evaluates the ex-post impact of adopting improved groundnut varieties on crop income and rural poverty in rural Uganda. The study utilizes cross-sectional farm household data collected in 2006 in seven districts of Uganda. We estimated the average adoption premium using propensity score matching (PSM), poverty dominance analysis tests, and a linear regression model to check robustness of results. Poverty dominance analysis tests and linear regression estimates are based on matched observations of adopters and non-adopters obtained from the PSM. This helped us estimate the true welfare effect of technology adoption by controlling for the role of selection problem on production and adoption decisions. Furthermore, we checked covariate balancing with a standardized bias measure and sensitivity of the estimated adoption effect to unobserved selection bias, using the Rosenbaum bounds procedure. The paper computes income-based poverty measures and investigates their sensitivity to the use of different poverty lines. We found that adoption of improved groundnut technologies has a significant positive impact on crop income and poverty reduction. These results are not sensitive to unobserved selection bias; therefore, we can be confident that the estimated adoption effect indicates a pure effect of improved groundnut technology adoption.

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Paper provided by Resources For the Future in its series Discussion Papers with number dp-10-11-efd.

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Date of creation: 25 May 2010
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Handle: RePEc:rff:dpaper:dp-10-11-efd
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  1. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, Social Science Research Center Berlin (WZB).
  2. Alex Bryson & Richard Dorsett & Susan Purdon, 2002. "The use of propensity score matching in the evaluation of active labour market policies," LSE Research Online Documents on Economics 4993, London School of Economics and Political Science, LSE Library.
  3. Sascha O. Becker & Marco Caliendo, 2007. "mhbounds - Sensitivity Analysis for Average Treatment Effects," Discussion Papers of DIW Berlin 659, DIW Berlin, German Institute for Economic Research.
  4. Heckman, James J & Ichimura, Hidehiko & Todd, Petra E, 1997. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 605-54, October.
  5. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," NBER Working Papers 6699, National Bureau of Economic Research, Inc.
  6. Shaohua Chen & Datt, Gaurav & Ravallion, Martin, 1993. "Is poverty increasing in the developing world?," Policy Research Working Paper Series 1146, The World Bank.
  7. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
  8. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-66, May.
  9. Pinstrup-Andersen, Per & Pandya-Lorch, Rajul, 1995. "Agricultural growth is the key to poverty alleviation in low-income developing countries," 2020 vision briefs 15, International Food Policy Research Institute (IFPRI).
  10. Ingrid Rhinehart & C. Michael Deom, 2007. "Peanut Research and Poverty Reduction: Impacts of Variety Improvement to Control Peanut Viruses in Uganda," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(2), pages 448-460.
  11. Coelli, Tim & Fleming, Euan, 2004. "Diversification economies and specialisation efficiencies in a mixed food and coffee smallholder farming system in Papua New Guinea," Agricultural Economics, Blackwell, vol. 31(2-3), pages 229-239, December.
  12. Kasenge, Valentine & Taylor, Daniel B. & Bonabana-Wabbi, Jackline, 2006. "A Limited Dependent Variable Analysis of Integrated Pest Management Adoption in Uganda," 2006 Annual meeting, July 23-26, Long Beach, CA 21040, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  13. Paul Mosley & Sanzidur Rahman, 1999. "Impact of technological change on income distribution and poverty in Bangladesh agriculture: an empirical analysis," Journal of International Development, John Wiley & Sons, Ltd., vol. 11(7), pages 935-955.
  14. Andreas Drichoutis & Panagiotis Lazaridis & Rodolfo Nayga, 2009. "Can Mediterranean diet really influence obesity? Evidence from propensity score matching," The European Journal of Health Economics, Springer, vol. 10(4), pages 371-388, October.
  15. Mendola, Mariapia, 2007. "Agricultural technology adoption and poverty reduction: A propensity-score matching analysis for rural Bangladesh," Food Policy, Elsevier, vol. 32(3), pages 372-393, June.
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