Adaptation, Mitigation and “Green” R&D to Combat Global Climate Change. Insights From an Empirical Integrated Assessment Exercise

Francesco Bosello

No 59746, Sustainable Development Papers from Fondazione Eni Enrico Mattei (FEEM)

Abstract: This work develops a framework for the analysis at the macro-level of the relationship between adaptation and mitigation policies. The FEEM-RICE growth model with stock pollution, endogenous R&D investment and emission abatement is enriched with a planned-adaptation module where a defensive capital stock is built through adaptation investment. Within this framework the optimal path of planned adaptation, the optimal inter and intra temporal mix between adaptation, mitigation and investment in R&D, and the sensitivity of a strategy to each other is identified. The major conclusions of this research show that adaptation, mitigation and R&D are strategic complements as all concur together to the solution of the climate change problem; nonetheless the possibility to adapt reduces the need to mitigate and partly crowds out other forms of investment like those in R&D. The optimal intertemporal distribution of strategies is also described: it requires to anticipate mitigation effort that should start already when climate damages are low and postpone adaptation intervention until they are substantial. Thus the possibility to adapt is not a justification to delay abatement activities. A sensitivity analysis demonstrates the robustness of these results to different parameterizations, in particular to changes in expected climate-change damages and in the discount rates.

Keywords: Environmental; Economics; and; Policy (search for similar items in EconPapers)
Pages: 32
Date: 2010-03
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: Adaptation, Mitigation and “Green” R&D to Combat Global Climate Change. Insights From an Empirical Integrated Assessment Exercise (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:feemdp:59746

DOI: 10.22004/ag.econ.59746

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