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

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

Abstract

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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  • Kassie, Menale & Shiferaw, Bekele & Muricho, Geoffrey, 2010. "Adoption and Impact of Improved Groundnut Varieties on Rural Poverty: Evidence from Rural Uganda," RFF Working Paper Series dp-10-11-efd, Resources for the Future.
    • Handle: RePEc:rff:dpaper:dp-10-11-efd
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    11. Acheampong, Patricia & Owusu, Victor, 2015. "Impact of Improved cassava varieties' adoption on farmers' incomes in Rural Ghana," 2015 Conference, August 9-14, 2015, Milan, Italy 210875, International Association of Agricultural Economists.
    12. Asante, Bright Owusu & Adabah, Richard & Agyeman, Kennedy & Ayeh, Stephen John & Aidoo, Robert & Afona, Daniel, 2021. "Preference for improved varietal attributes of Bambara groundnut among smallholder farmers in Ghana," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 16(2), June.
    13. Adela, F.A. & Aurbacher, J., 2018. "Access to irrigation water-poverty nexus: Application of an Endogenous Switching Regression in Ethiopia," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277521, International Association of Agricultural Economists.
    14. Chakraborty, Sanjana & Mukherjee, Vivekananda, 2020. "Revisiting the Economic Costs of Arsenicosis: A PSM Approach," Ecology, Economy and Society - the INSEE Journal, Indian Society of Ecological Economics (INSEE), vol. 3(02), July.
    15. Bortamuly, Alin Borah & Goswami, Kishor, 2015. "Determinants of the adoption of modern technology in the handloom industry in Assam," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 400-409.
    16. Harris, David & Orr, Alastair, 2014. "Is rainfed agriculture really a pathway from poverty?," Agricultural Systems, Elsevier, vol. 123(C), pages 84-96.
    17. Dambala Gelo & Steven F. Koch, 2011. "The Welfare Effect of Common Property Forestry Rights:Evidence from Ethiopian Villages," Working Papers 201123, University of Pretoria, Department of Economics.
    18. Akua S. Akuffo & Kwamena K. Quagrainie, 2019. "Assessment of Household Food Security in Fish Farming Communities in Ghana," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
    19. Ibrahim, Mohammed & Florkowski, Wojciech J. & Kolavalli, Shashidhara, 2012. "Determinants of Farmer Adoption of Improved Peanut Varieties and their Impact on Farm Income: Evidence from Northern Ghana," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125000, Agricultural and Applied Economics Association.

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    More about this item

    Keywords

    groundnut technology adoption; crop income; poverty alleviation; propensity score matching; switching regression; stochastic dominance; Rosenbaum bounds; Uganda;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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