Adaptation to climate change and economic growth in developing countries
The global climate is changing, and will continue to do so even if greenhouse gas emissions are dramatically curbed. Economies are therefore faced with the challenge of adapting to climate change. This challenge is particularly important in developing countries, which, due to a combination of unfortunate geography and high sensitivity, are most vulnerable to climate change. From a macro-economic point of view, there remains much to learn about the characteristics of optimal adaptation. In particular, it is unclear whether the best way to adapt to climate change is simply to focus on traditional growth and development goals, or to divert significant investment into ï¿½climate-proofingï¿½ productive capital. In this paper we conduct analytical and numerical modeling to gain new insights into this question. Our analytical model shows that the task of apportioning investment between productive capital and adaptation to climate change is a subtle one. While it is very unlikely that the optimal strategy involves no investment in adaptation, the scale and composition of productive and adaptive capital investments depend on empirical context. Our numerical application to Sub-Saharan Africa suggests, however, that in most contingencies it will be optimal to invest rapidly in adaptive capital over the coming decades. Our sensitivity analysis goes well beyond the existing literature in evaluating the robustness of this finding.
|Date of creation:||Sep 2011|
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- Kelly, David L. & Kolstad, Charles D., 2001.
"Malthus and Climate Change: Betting on a Stable Population,"
Journal of Environmental Economics and Management,
Elsevier, vol. 41(2), pages 135-161, March.
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- Kelly, David L. & Kolstad, Charles D. & Mitchell, Glenn T., 2005. "Adjustment costs from environmental change," Journal of Environmental Economics and Management, Elsevier, vol. 50(3), pages 468-495, November.
- Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, June.
- Kelly, David L. & Kolstad, Charles D., 1999. "Bayesian learning, growth, and pollution," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 491-518, February.
- Manoj Atolia & Edward F. Buffie, 2004. "Reverse Shooting Made Easy: Solving for the Global Nonlinear Saddle Path," Working Papers wp2009_01_01, Department of Economics, Florida State University, revised Jan 2009.
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