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Does a cassava research-for-development program have impact at the farm level? Evidence from the Democratic Republic of Congo

Author

Listed:
  • Rusike, J.
  • Mahungu, N.M.
  • Lukombo, S.S.
  • Kendenga, T.
  • Bidiaka, S.M.
  • Alene, A.
  • Lema, A.
  • Manyong, V.M.

Abstract

This paper evaluates the impact of a cassava research-for-development program on farm level outcomes. The program was implemented in the Democratic Republic of Congo from 2001 to 2009. We apply propensity score matching, Rosenbaum bounds on treatment effects, Altonji et al. method of selection on observables and unobservables and endogenous switching regression to farm survey data collected during the 2009 cropping season. We use these methods to test whether the R4D program has a statistically significant effect on outcomes of interest and if these are not driven by selection on unobservables. Using propensity score matching, we find statistically significant positive effects on household participation in cassava markets, adoption of improved varieties and crop management practices and household food adequacy; and no statistically significant effects on yields and profits. The results show that bias due to selection on unobservables is not severe enough to invalidate the impact estimates. Bias may still be a problem that is present in the analysis. But there is evidence that it is not substantial. Although the program does not have a statistically significant positive effect on yields and profits, the significant program effects on market participation, variety adoption, and food adequacy merit further promotion of the program since these positive outcomes tend to be pre-conditions for realizing long-term yield and profit benefits.

Suggested Citation

  • Rusike, J. & Mahungu, N.M. & Lukombo, S.S. & Kendenga, T. & Bidiaka, S.M. & Alene, A. & Lema, A. & Manyong, V.M., 2014. "Does a cassava research-for-development program have impact at the farm level? Evidence from the Democratic Republic of Congo," Food Policy, Elsevier, vol. 46(C), pages 193-204.
    • Handle: RePEc:eee:jfpoli:v:46:y:2014:i:c:p:193-204
    DOI: 10.1016/j.foodpol.2014.03.012
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    1. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
    2. Alston, Julian M. & Wyatt, T. J. & Pardey, Philip G. & Marra, Michele C. & Chan-Kang, Connie, 2000. "A meta-analysis of rates of return to agricultural R & D: ex pede Herculem?," Research reports 113, International Food Policy Research Institute (IFPRI).
    3. James Heckman & Justin L. Tobias & Edward Vytlacil, 2001. "Four Parameters of Interest in the Evaluation of Social Programs," Southern Economic Journal, John Wiley & Sons, vol. 68(2), pages 210-223, October.
    4. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    5. 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, WZB Berlin Social Science Center.
    6. James Heckman & Justin L. Tobias & Edward Vytlacil, 2001. "Four Parameters of Interest in the Evaluation of Social Programs," Southern Economic Journal, John Wiley & Sons, vol. 68(2), pages 210-223, October.
    7. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    8. de Janvry, Alain, 2009. "AERC Conference on Agriculture for Development in Sub-Saharan Africa: Introduction," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt86b7b0qx, Department of Agricultural & Resource Economics, UC Berkeley.
    9. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643.
    10. Evenson, Robert E., 2001. "Economic impacts of agricultural research and extension," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 11, pages 573-628, Elsevier.
    11. Godtland, Erin M & Sadoulet, Elisabeth & De Janvry, Alain & Murgai, Rinku & Ortiz, Oscar, 2004. "The Impact of Farmer Field Schools on Knowledge and Productivity: A Study of Potato Farmers in the Peruvian Andes," Economic Development and Cultural Change, University of Chicago Press, vol. 53(1), pages 63-92, October.
    12. Bhavani Shankar & Colin Thirtle, 2005. "Pesticide Productivity and Transgenic Cotton Technology: The South African Smallholder Case," Journal of Agricultural Economics, Wiley Blackwell, vol. 56(1), pages 97-116, March.
    13. Mywish K. Maredia & David Anthony Raitzer, 2010. "Estimating overall returns to international agricultural research in Africa through benefit‐cost analysis: a “best‐evidence” approach," Agricultural Economics, International Association of Agricultural Economists, vol. 41(1), pages 81-100, January.
    14. Rejesus, Roderick M. & Palis, Florencia G. & Rodriguez, Divina Gracia P. & Lampayan, Ruben M. & Bouman, Bas A.M., 2011. "Impact of the alternate wetting and drying (AWD) water-saving irrigation technique: Evidence from rice producers in the Philippines," Food Policy, Elsevier, vol. 36(2), pages 280-288, April.
    15. Renkow, Mitch & Byerlee, Derek, 2010. "The impacts of CGIAR research: A review of recent evidence," Food Policy, Elsevier, vol. 35(5), pages 391-402, October.
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    1. Ekboir, Javier & Blundo Canto, Genowefa & Sette, Cristina, 2017. "Knowing what research organizations actually do, with whom, where, how and for what purpose: Monitoring research portfolios and collaborations," Evaluation and Program Planning, Elsevier, vol. 61(C), pages 64-75.
    2. Feleke, S. & Manyong, V. & Abdoulaye, T. & Alene, A. & Wossen, T. & Dontsop, P., 2018. "Are agricultural technologies pro-poor? The case of improved cassava varieties in sub-Saharan Africa," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277196, International Association of Agricultural Economists.

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