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Agricultural Technology Adoption and Rural Poverty: Application of an Endogenous Switching Regression for Selected East African Countries

  • Asfaw, Solomon
  • Shiferaw, Bekele A.
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    Achieving agricultural growth and development and thereby improving rural household welfare will require increased efforts to provide yield enhancing and natural resources conserving technologies. Agricultural research and technological improvements are therefore crucial to increase agricultural productivity and thereby reduce poverty. However evaluation of the impact of these technologies on rural household welfare have been very limited by lack of appropriate methods and most of previous research has therefore failed to move beyond estimating economic surplus and return to research investment. This paper evaluates the potential impact of adoption of modern agricultural technologies on rural household welfare measured by crop income and consumption expenditure in rural Ethiopia and Tanzania. The study utilizes cross-sectional farm household level data collected in 2007 from a randomly selected sample of 1313 households (700 in Ethiopia and 613 in Tanzania). We estimate the casual impact of technology adoption by utilizing endogenous switching regression and propensity score matching methods to assess results robustness. This helps us estimate the true welfare effect of technology adoption by controlling for the role of selection problem on production and adoption decisions. Our analysis reveals that adoption of improved agricultural technologies has a significant positive impact on crop income although the impact on consumption expenditure is mixed. This confirms the potential direct role of technology adoption on improving rural household welfare, as higher incomes from improved technology translate into lower income poverty.

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    File URL: http://purl.umn.edu/97049
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    Paper provided by African Association of Agricultural Economists (AAAE) & Agricultural Economics Association of South Africa (AEASA) in its series 2010 AAAE Third Conference/AEASA 48th Conference, September 19-23, 2010, Cape Town, South Africa with number 97049.

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    Date of creation: Sep 2010
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    Handle: RePEc:ags:aaae10:97049
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    1. Hausman, Jerry A, 1978. "Specification Tests in Econometrics," Econometrica, Econometric Society, vol. 46(6), pages 1251-71, November.
    2. Byerlee, Derek, 2000. "Targeting poverty alleviation in priority setting for agricultural research," Food Policy, Elsevier, vol. 25(4), pages 429-445, August.
    3. Michael Lokshin & Zurab Sajaia, 2004. "Maximum likelihood estimation of endogenous switching regression models," Stata Journal, StataCorp LP, vol. 4(3), pages 282-289, September.
    4. Lee, Lung-Fei & Trost, Robert P., 1978. "Estimation of some limited dependent variable models with application to housing demand," Journal of Econometrics, Elsevier, vol. 8(3), pages 357-382, December.
    5. Rajeev H. Dehejia & Sadek Wahba, 1998. "Propensity Score Matching Methods for Non-experimental Causal Studies," NBER Working Papers 6829, National Bureau of Economic Research, Inc.
    6. David W. Carter & J. Walter Milon, 2005. "Price Knowledge in Household Demand for Utility Services," Land Economics, University of Wisconsin Press, vol. 81(2).
    7. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
    8. Heckman, J J & Tobias, Justin & Vytlacil, Ed, 2001. "Four Parameters of Interest in the Evaluation of Social Programs," Staff General Research Papers 12022, Iowa State University, Department of Economics.
    9. Jeffrey Smith & Petra Todd, 2003. "Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators?," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20035, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
    10. Arega Alene & V. Manyong, 2007. "The effects of education on agricultural productivity under traditional and improved technology in northern Nigeria: an endogenous switching regression analysis," Empirical Economics, Springer, vol. 32(1), pages 141-159, April.
    11. Nelson, Forrest D., 1984. "Efficiency of the two-step estimator for models with endogenous sample selection," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 181-196.
    12. Bekele A. Shiferaw & Tewodros A. Kebede & Liang You, 2008. "Technology adoption under seed access constraints and the economic impacts of improved pigeonpea varieties in Tanzania," Agricultural Economics, International Association of Agricultural Economists, vol. 39(3), pages 309-323, November.
    13. Hartman, Raymond S, 1991. "A Monte Carlo Analysis of Alternative Estimators in Models Involving Selectivity," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 41-49, January.
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