IDEAS home Printed from https://ideas.repec.org/a/eee/wdevel/v108y2018icp28-46.html
   My bibliography  Save this article

Who benefits from which agricultural research-for-development technologies? Evidence from farm household poverty analysis in Central Africa

Author

Listed:
  • Ainembabazi, John Herbert
  • Abdoulaye, Tahirou
  • Feleke, Shiferaw
  • Alene, Arega
  • Dontsop-Nguezet, Paul M.
  • Ndayisaba, Pierre Celestin
  • Hicintuka, Cyrille
  • Mapatano, Sylvain
  • Manyong, Victor

Abstract

It remains a challenge for agricultural research-for-development (AR4D) institutions to demonstrate to donors which technologies contribute significantly to poverty reduction due to a multitude of impact pathways. We attempt to overcome this challenge by utilizing the potential outcomes framework and quantile treatment effects analytical approaches applied on panel household data collected from Central Africa. Our findings show that adoption of AR4D technologies reduced the probability of being poor by 13 percentage points. A large share of this poverty reduction is causally attributable to adoption of improved crop varieties (32%) followed by adoption of post-harvest technologies (28%) and crop and natural resource management (26%), with the rest 14% attributable to unidentified and/or unmeasured intermediate outcomes or factors. The findings further indicate that relatively poor farm households benefit from adopting improved crop varieties more than the relatively better-off households. Correspondingly, the relatively better off households benefit from adopting post-harvest technologies enhancing crop commercialization much more than the relatively poor households. The findings reveal interesting policy implications for successful targeting of agricultural interventions aimed at reducing rural poverty.

Suggested Citation

  • Ainembabazi, John Herbert & Abdoulaye, Tahirou & Feleke, Shiferaw & Alene, Arega & Dontsop-Nguezet, Paul M. & Ndayisaba, Pierre Celestin & Hicintuka, Cyrille & Mapatano, Sylvain & Manyong, Victor, 2018. "Who benefits from which agricultural research-for-development technologies? Evidence from farm household poverty analysis in Central Africa," World Development, Elsevier, vol. 108(C), pages 28-46.
  • Handle: RePEc:eee:wdevel:v:108:y:2018:i:c:p:28-46
    DOI: 10.1016/j.worlddev.2018.03.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305750X18300950
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Christiaensen, Luc & Demery, Lionel & Kuhl, Jesper, 2011. "The (evolving) role of agriculture in poverty reduction--An empirical perspective," Journal of Development Economics, Elsevier, vol. 96(2), pages 239-254, November.
    2. 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.
    3. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    4. Fan, Shenggen & Zhang, Linxiu & Zhang, Xiaobo, 2004. "Reforms, Investment, and Poverty in Rural China," Economic Development and Cultural Change, University of Chicago Press, vol. 52(2), pages 395-421, January.
    5. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
    6. Shenggen Fan & Peter Hazell & Sukhadeo Thorat, 2000. "Government Spending, Growth and Poverty in Rural India," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(4), pages 1038-1051.
    7. Feleke, Shiferaw & Manyong, Victor & Abdoulaye, Tahirou & Alene, Arega D., 2016. "Assessing the impacts of cassava technology on poverty reduction in Africa," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 118(2), pages 1-11, August.
    8. Shenggen Fan & Xiaobo Zhang, 2008. "Public Expenditure, Growth and Poverty Reduction in Rural Uganda," African Development Review, African Development Bank, vol. 20(3), pages 466-496.
    9. Imai, Kosuke & Keele, Luke & Tingley, Dustin & Yamamoto, Teppei, 2011. "Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies," American Political Science Review, Cambridge University Press, vol. 105(4), pages 765-789, November.
    10. Cattaneo, Matias D., 2010. "Efficient semiparametric estimation of multi-valued treatment effects under ignorability," Journal of Econometrics, Elsevier, vol. 155(2), pages 138-154, April.
    11. Flores, Carlos A. & Flores-Lagunes, Alfonso, 2009. "Identification and Estimation of Causal Mechanisms and Net Effects of a Treatment under Unconfoundedness," IZA Discussion Papers 4237, Institute of Labor Economics (IZA).
    12. Markus Frölich & Blaise Melly, 2013. "Unconditional Quantile Treatment Effects Under Endogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 346-357, July.
    13. Papke, Leslie E. & Wooldridge, Jeffrey M., 2008. "Panel data methods for fractional response variables with an application to test pass rates," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 121-133, July.
    14. Becker, Sascha O. & Caliendo, Marco, 2007. "mhbounds – Sensitivity Analysis for Average Treatment Effects," IZA Discussion Papers 2542, Institute of Labor Economics (IZA).
    15. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588.
    16. Awudu Abdulai & Wallace Huffman, 2014. "The Adoption and Impact of Soil and Water Conservation Technology: An Endogenous Switching Regression Application," Land Economics, University of Wisconsin Press, vol. 90(1), pages 26-43.
    17. Nicole M. Mason & Melinda Smale, 2013. "Impacts of subsidized hybrid seed on indicators of economic well-being among smallholder maize growers in Zambia," Agricultural Economics, International Association of Agricultural Economists, vol. 44(6), pages 659-670, November.
    18. Arslan, Aslihan & Belotti, Federico & Lipper, Leslie, 2017. "Smallholder productivity and weather shocks: Adoption and impact of widely promoted agricultural practices in Tanzania," Food Policy, Elsevier, vol. 69(C), pages 68-81.
    19. Shadish, William R. & Clark, M. H. & Steiner, Peter M., 2008. "Can Nonrandomized Experiments Yield Accurate Answers? A Randomized Experiment Comparing Random and Nonrandom Assignments," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1334-1344.
    20. Gaurav Datt & Martin Ravallion, 1998. "Farm productivity and rural poverty in India," Journal of Development Studies, Taylor & Francis Journals, vol. 34(4), pages 62-85.
    21. 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.
    22. Alston, Julian M. & Marra, Michele C. & Pardey, Philip G. & Wyatt, T.J., 2000. "Research returns redux: a meta-analysis of the returns to agricultural R&D," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 44(2), pages 1-31.
    23. Di Zeng & Jeffrey Alwang & George W. Norton & Bekele Shiferaw & Moti Jaleta & Chilot Yirga, 2017. "Agricultural technology adoption and child nutrition enhancement: improved maize varieties in rural Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 48(5), pages 573-586, September.
    24. 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.
    25. Bezu, Sosina & Kassie, Girma T. & Shiferaw, Bekele & Ricker-Gilbert, Jacob, 2014. "Impact of Improved Maize Adoption on Welfare of Farm Households in Malawi: A Panel Data Analysis," World Development, Elsevier, vol. 59(C), pages 120-131.
    26. Coromaldi, Manuela & Pallante, Giacomo & Savastano, Sara, 2015. "Adoption of modern varieties, farmers' welfare and crop biodiversity: Evidence from Uganda," Ecological Economics, Elsevier, vol. 119(C), pages 346-358.
    27. Shiferaw, Bekele & Kassie, Menale & Jaleta, Moti & Yirga, Chilot, 2014. "Adoption of improved wheat varieties and impacts on household food security in Ethiopia," Food Policy, Elsevier, vol. 44(C), pages 272-284.
    28. Di Zeng & Jeffrey Alwang & George W. Norton & Bekele Shiferaw & Moti Jaleta & Chilot Yirga, 2015. "Ex post impacts of improved maize varieties on poverty in rural Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 46(4), pages 515-526, July.
    29. Abdulai, Abdul-Nafeo & Abdulai, Awudu, 2017. "Examining the impact of conservation agriculture on environmental efficiency among maize farmers in Zambia," Environment and Development Economics, Cambridge University Press, vol. 22(2), pages 177-201, April.
    30. Moti Jaleta & Menale Kassie & Paswel Marenya & Chilot Yirga & Olaf Erenstein, 2018. "Impact of improved maize adoption on household food security of maize producing smallholder farmers in Ethiopia," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(1), pages 81-93, February.
    31. 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.
    32. Kassie, Menale & Shiferaw, Bekele & Muricho, Geoffrey, 2011. "Agricultural Technology, Crop Income, and Poverty Alleviation in Uganda," World Development, Elsevier, vol. 39(10), pages 1784-1795.
    33. Robin Burgess & Rohini Pande, 2005. "Do Rural Banks Matter? Evidence from the Indian Social Banking Experiment," American Economic Review, American Economic Association, vol. 95(3), pages 780-795, June.
    34. Khonje, Makaiko & Manda, Julius & Alene, Arega D. & Kassie, Menale, 2015. "Analysis of Adoption and Impacts of Improved Maize Varieties in Eastern Zambia," World Development, Elsevier, vol. 66(C), pages 695-706.
    35. Wasantha Athukorala & Clevo Wilson, 2017. "Distributional impacts of irrigation-induced agricultural development in a semi-subsistence economy: new evidence," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(1), pages 59-75, January.
    36. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    37. Teklewold, Hailemariam & Kassie, Menale & Shiferaw, Bekele & Köhlin, Gunnar, 2013. "Cropping system diversification, conservation tillage and modern seed adoption in Ethiopia: Impacts on household income, agrochemical use and demand for labor," Ecological Economics, Elsevier, vol. 93(C), pages 85-93.
    38. Julius Manda & Arega D. Alene & Cornelis Gardebroek & Menale Kassie & Gelson Tembo, 2016. "Adoption and Impacts of Sustainable Agricultural Practices on Maize Yields and Incomes: Evidence from Rural Zambia," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(1), pages 130-153, February.
    39. Markus Frolich & Blaise Melly, 2010. "Estimation of quantile treatment effects with Stata," Stata Journal, StataCorp LP, vol. 10(3), pages 423-457, September.
    40. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    41. David A Raitzer & Timothy G Kelley, 2008. "Assessing the contribution of impact assessment to donor decisions for international agricultural research," Research Evaluation, Oxford University Press, vol. 17(3), pages 187-199, September.
    42. De los Santos-Montero, Luis A. & Bravo-Ureta, Boris E., 2017. "Natural Resource Management and Household Well-being: The Case of POSAF-II in Nicaragua," World Development, Elsevier, vol. 99(C), pages 42-59.
    43. Becerril, Javier & Abdulai, Awudu, 2010. "The Impact of Improved Maize Varieties on Poverty in Mexico: A Propensity Score-Matching Approach," World Development, Elsevier, vol. 38(7), pages 1024-1035, July.
    44. Solomon Asfaw & Menale Kassie & Franklin Simtowe & Leslie Lipper, 2012. "Poverty Reduction Effects of Agricultural Technology Adoption: A Micro-evidence from Rural Tanzania," Journal of Development Studies, Taylor & Francis Journals, vol. 48(9), pages 1288-1305, September.
    45. Becker, Sascha O. & Caliendo, Marco, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 1-13.
    46. Bokusheva, Raushan & Finger, Robert & Fischler, Martin & Berlin, Robert & Marin, Yuri & Perez, Francisco Jose & Paiz, Francisco, 2012. "Factors Determining the Adoption and Impact of a Postharvest Storage Technology," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 125138, International Association of Agricultural Economists.
    47. Knowler, Duncan & Bradshaw, Ben, 2007. "Farmers' adoption of conservation agriculture: A review and synthesis of recent research," Food Policy, Elsevier, vol. 32(1), pages 25-48, February.
    48. Arega D. Alene & Abebe Menkir & S. O. Ajala & B. Badu‐Apraku & A. S. Olanrewaju & V. M. Manyong & Abdou Ndiaye, 2009. "The economic and poverty impacts of maize research in West and Central Africa," Agricultural Economics, International Association of Agricultural Economists, vol. 40(5), pages 535-550, September.
    49. Verkaart, Simone & Munyua, Bernard G. & Mausch, Kai & Michler, Jeffrey D., 2017. "Welfare impacts of improved chickpea adoption: A pathway for rural development in Ethiopia?," Food Policy, Elsevier, vol. 66(C), pages 50-61.
    50. 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.
    51. Freebairn, Donald K., 1995. "Did the Green Revolution Concentrate Incomes? A Quantitative Study of Research Reports," World Development, Elsevier, vol. 23(2), pages 265-279, February.
    52. 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.
    53. Abdul Nafeo Abdulai, 2016. "Impact of conservation agriculture technology on household welfare in Zambia," Agricultural Economics, International Association of Agricultural Economists, vol. 47(6), pages 729-741, November.
    54. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
    55. Frank Mmbando & Edilegnaw Wale & Lloyd Baiyegunhi, 2015. "Welfare impacts of smallholder farmers’ participation in maize and pigeonpea markets in Tanzania," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 7(6), pages 1211-1224, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Junying Lin & Zhonggen Zhang & Lingli Lv, 2019. "The Impact of Program Participation on Rural Household Income: Evidence from China’s Whole Village Poverty Alleviation Program," Sustainability, MDPI, Open Access Journal, vol. 11(6), pages 1-15, March.

    More about this item

    Keywords

    AR4D; Poverty; Impact evaluation; Central Africa;

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    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:eee:wdevel:v:108:y:2018:i:c:p:28-46. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/worlddev .

    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.