Multiple adaptation types with mitigation: A framework for policy analysis
Effective climate policy will consist of mitigation and adaptation implemented simultaneously in a policy portfolio to reduce the risks of climate change. Previous studies of the tradeoffs between mitigation and adaptation have implicitly framed the problem deterministically, choosing the optimal paths for all time. Because climate change is a long-term problem with significant uncertainties and opportunities to learn and revise, critical tradeoffs between mitigation and adaptation in the near-term have not been considered. We propose a new framework for considering the portfolio of mitigation and adaptation that explicitly treats the problem as a multi-stage decision under uncertainty. In this context, there are additional benefits to near-term investments if they reduce uncertainty and lead to improved future decisions. Two particular features are fundamental to understanding the relevant tradeoffs between mitigation and adaptation: (1) strategy dynamics over time in reducing climate damages, and (2) strategy dynamics under uncertainty and potential for learning. Our framework strengthens the argument for disaggregating adaption as has been proposed by others. We present three stylized classes of adaptation investment types as a conceptual framework: short-lived "flow" spending, committed "stock" investment, and lower capacity "option" stock with the capability of future upgrading. In the context of sequential decision under uncertainty, these subtypes of adaptation have important tradeoffs among them and with mitigation. We argue that given the large policy uncertainty that we face currently, explicitly considering adaptation "option" investments is a valuable component of a near-term policy response that can balance between the flexible flow and committed stock approaches, as it allows for the delay of costly stock investments while at the same time allowing for lower-cost risk management of future damages. © 2013.
Felgenhauer, T; Webster, M
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