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Climate change adaptation in Africa : a microeconomic analysis of livestock choice

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  • Seo, Sungno Niggol
  • Mendelsohn, Robert

Abstract

This paper uses quantitative methods to examine the way African farmers have adapted livestock management to the range of climates found across the African continent. The authors use logit analysis to estimate whether farmers adopt livestock. They then use three econometric models to examine which species farmers choose: a primary choice multinomial logit, an optimal portfolio multinomial logit, and a demand system multivariate probit. Comparing the results of the three methods of estimating species selection reveals that the three approaches yield similar results. Using data from over 9,000 African livestock farmers in 10 countries, the analysis finds that farmers are more likely to choose to have livestock as temperatures increase and as precipitation decreases. Across all methods of estimating choice, livestock farmers in warmer locations are less likely to choose beef cattle and chickens and more likely to choose goats and sheep. As precipitation increases, cattle and sheep decrease but goats and chickens increase. The authors simulate the way farmers'choices might change with a set of uniform climate changes and a set of climate model scenarios. The uniform scenarios predict that warming and drying would increase livestock ownership but that increases in precipitation would decrease it. The climate scenarios predict a decrease in the probability of beef cattle and an increase in the probability of sheep and goats, and they predict that more heat-tolerant animals will dominate the future African landscape.

Suggested Citation

  • Seo, Sungno Niggol & Mendelsohn, Robert, 2007. "Climate change adaptation in Africa : a microeconomic analysis of livestock choice," Policy Research Working Paper Series 4277, The World Bank.
  • Handle: RePEc:wbk:wbrwps:4277
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    References listed on IDEAS

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    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    6. Neil Leary, 1999. "A Framework for Benefit-Cost Analysis of Adaptation to Climate Change and Climate Variability," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 4(3), pages 307-318, September.
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    Citations

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    Cited by:

    1. World Bank, 2007. "Environment Matters at the World Bank, 2007 Annual Review : Climate Change and Adaptation," World Bank Publications - Books, The World Bank Group, number 13096.
    2. Seo, Sungno Niggol & Mendelsohn, Robert, 2007. "The impact of climate change on livestock management in Africa : a structural Ricardian analysis," Policy Research Working Paper Series 4279, The World Bank.
    3. Kalpana Venkatasubramanian & Smita Ramnarain, 2018. "Gender and Adaptation to Climate Change: Perspectives from a Pastoral Community in Gujarat, India," Development and Change, International Institute of Social Studies, vol. 49(6), pages 1580-1604, November.
    4. Basurto-Hernandez, S. & Maddison, D. & Banerjee, A., 2018. "The effects of climate change on crop and livestock choices," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277517, International Association of Agricultural Economists.
    5. Seo, Niggol & Mendelsohn, Robert, 2007. "An analysis of livestock choice : adapting to climate change in Latin American farms," Policy Research Working Paper Series 4164, The World Bank.
    6. Ha, Thi Thuy Nong & Gan, Christopher & Hu, Baiding, 2021. "Farmers’ perception of and adaptation to climate change: An Investigation in Northeast Vietnam," Journal of Economic Development, The Economic Research Institute, Chung-Ang University, vol. 46(4), pages 65-85, December.
    7. S. Niggol Seo & Robert Mendelsohn, 2008. "Measuring impacts and adaptations to climate change: a structural Ricardian model of African livestock management-super-1," Agricultural Economics, International Association of Agricultural Economists, vol. 38(2), pages 151-165, March.

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    Keywords

    Livestock&Animal Husbandry; Wildlife Resources; Peri-Urban Communities; Rural Urban Linkages; Climate Change;
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