Measuring Impacts and Adaptations to Climate Change: A Structural Ricardian Model of African Livestock Management
This article develops a new cross-sectional methodology that explicitly incorporates adaptation into an analysis of the impacts of climate change. The methodology examines how a farmer will change choices of species and number to adapt to climate. The approach is applied to study Africa, where the impacts of climate change are expected to be the most severe. The results indicate that in warmer places, African farmers switch from beef cattle to more heat-tolerant goats and sheep. In wetter places, farmers switch from cattle and sheep to goats and chickens. The results indicate that large commercial livestock operations specializing in beef cattle will be hard hit from climate change whereas small farmers who can easily substitute to goats and/or sheep will be more resilient.
Main Authors: | , |
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Format: | Journal Article biblioteca |
Language: | EN |
Published: |
2008
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Subjects: | Economic Development: Agriculture, Natural Resources, Energy, Environment, Other Primary Products O130, Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets Q120, Climate, Natural Disasters, Global Warming Q540, |
Online Access: | http://hdl.handle.net/10986/4933 |
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Summary: | This article develops a new cross-sectional methodology that explicitly incorporates adaptation into an analysis of the impacts of climate change. The methodology examines how a farmer will change choices of species and number to adapt to climate. The approach is applied to study Africa, where the impacts of climate change are expected to be the most severe. The results indicate that in warmer places, African farmers switch from beef cattle to more heat-tolerant goats and sheep. In wetter places, farmers switch from cattle and sheep to goats and chickens. The results indicate that large commercial livestock operations specializing in beef cattle will be hard hit from climate change whereas small farmers who can easily substitute to goats and/or sheep will be more resilient. |
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