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Climate Change, Crop Selection and Agricultural Revenue in Ghana: A Structural Ricardian Analysis

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  • Prince M. Etwire
  • David Fielding
  • Viktoria Kahui

Abstract

We apply a Structural Ricardian Model (SRM) to farm‐level data from Ghana for seven principal food crops in order to model the factors which influence farmers' decisions about which food crops to grow and the revenue conditional on these choices. Our application of the SRM incorporates a flexible functional form to allow for the possibility that the effects of temperature and rainfall may not be linearly separable. We use this model as a basis for simulations of the effects of climate change. These simulations suggest that extreme climate change will lead to a significant reduction in the average net revenue per hectare from maize, which accounts for over half of current food production. Across a range of climate change scenarios, there is also substantial substitution of maize for heat‐tolerant millet, and a reduction in the cultivation of other crops. Under most of the climate change scenarios that we consider, these results imply a substantial reduction in the aggregate value of agricultural production, since millet is the lowest‐value crop.

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  • Prince M. Etwire & David Fielding & Viktoria Kahui, 2019. "Climate Change, Crop Selection and Agricultural Revenue in Ghana: A Structural Ricardian Analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 70(2), pages 488-506, June.
    • Handle: RePEc:bla:jageco:v:70:y:2019:i:2:p:488-506
    DOI: 10.1111/1477-9552.12307
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    References listed on IDEAS

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    1. World Bank, 2010. "Economics of Adaptation to Climate Change: Ethiopia, Volume 2. Annexes," World Bank Publications - Reports 13214, The World Bank Group.
    2. François Bourguignon & Martin Fournier & Marc Gurgand, 2007. "Selection Bias Corrections Based On The Multinomial Logit Model: Monte Carlo Comparisons," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 174-205, February.
    3. S. Niggol Seo, 2010. "A Microeconometric Analysis of Adapting Portfolios to Climate Change: Adoption of Agricultural Systems in Latin America," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 32(3), pages 489-514.
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    1. Kan, Iddo & Reznik, Ami & Kaminski, Jonathan & Kimhi, Ayal, 2023. "The impacts of climate change on cropland allocation, crop production, output prices and social welfare in Israel: A structural econometric framework," Food Policy, Elsevier, vol. 115(C).
    2. Geoffrey Norman Tumwine & Razack B Lokina & John Mary Matovu, 2019. "The Effect of Climate Change on Agricultural Crop Returns in Uganda," Journal of Economics and Behavioral Studies, AMH International, vol. 11(4), pages 71-87.
    3. Xun Su & Minpeng Chen, 2022. "Econometric Approaches That Consider Farmers’ Adaptation in Estimating the Impacts of Climate Change on Agriculture: A Review," Sustainability, MDPI, vol. 14(21), pages 1-23, October.
    4. Bannor, Frank & Dikgang, Johane & Gelo, Dambala, 2021. "Is climate variability subversive for agricultural total factor productivity growth? Long-run evidence from sub-Saharan Africa," MPRA Paper 107590, University Library of Munich, Germany.

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