How do the costs of adaptation affect optimal mitigation when there is uncertainty, irreversibility and learning?

TitleHow do the costs of adaptation affect optimal mitigation when there is uncertainty, irreversibility and learning?
Publication TypeTyndall Working Paper
SeriesTyndall Centre Working Papers
Tyndall Consortium Institution

Southampton

Secondary TitleTyndall Centre Working Paper 74
Keywordscosts of adaptation, irreversibility, learning, optimal mitigation, uncertainty
AuthorsIngham, A., J. Ma, and A. Ulph
Year of Publication2005
Abstract

In this paper we survey the literature on the economic analysis of mitigation and adaptation in the context of climate change. We present an overview of the main elements of what formal economic analysis there has been of adaptation and mitigation. This uses the familiar economic framework of expected utility maximization to capture behaviour. Mitigation and adaptation are two different ways which societies can reduce the damages that might be caused by climate change relationship which shows how mitigation and adaptation reduce the damage costs caused by climate change, and known costs of adaptation and of mitigation. A single social planner can choose the optimal mix of adaptation and mitigation to minimize total social costs in general the optimal combination of mitigation and adaptation will require the use of both strategies. This just reflects the rather mild assumption that the first bit of mitigation or adaptation is cheap relative to the marginal reduction in damage costs they bring about. This confirms the view of Kane and Yohe (2000) and Parry et al. (2000) that we need to have an integrated approach to adaptation and mitigation, and we cannot rely on either mitigation alone or adaptation alone to deal with climate change. It is sometime claimed that this joint determination of mitigation and adaptation means that adaptation and mitigation are complementary Thus, an increase in damage costs would be expected to lead to an increase in both adaptation and mitigation [1]. But in the context we have sketched so far, in technical economic terms, adaptation and mitigation are substitutes (Kane and Yohe (2000)), in the sense that if, say, the cost of adaptation fell, the optimal response would be to do more adaptation but less mitigation [2]. This just reflects the fact that these are two different ways of reducing damage costs, so if one becomes more expensive we should make more use of the other. This has obviously important policy implications. A central focus is the extent to which adaptation and mitigation are substitutes, in the sense that if, say, the cost of adaptation fell, the optimal response would be to do more adaptation but less mitigation. We introduce uncertainty and learning, and argue that a crucial determinant of the costs of adaptation is the rate at which those who respond to climate change, such as individual households, farmers, firms and so on, can learn about a changing environment. Now the above argument is based on a simple partial economic analysis, and it is conceivable in principle that with general equilibrium effects adaptation and mitigation might become complements. For example, if increased mitigation caused energy prices to fall this could make it more attractive to use some forms of adaptation. Nevertheless it is sometimes believed that there may again be a kind of complementarity between mitigation and adaptation in that mitigation `buys time' for adaptation. It is not clear what underlies this belief. In part it might reflect issues to do with the ability to learn IPCC (2001) notes there are still significant uncertainties attached to climate change. This raises the important question of how such uncertainty, and the prospect of getting better information in the future, affecting optimal policy towards mitigation and adaptation. Introducing uncertainty would lead to an increase in current mitigation relative to a model in which all parameters took their certainty equivalent values, and empirical models showed this effect to be significant. However introducing the possibility of learning, together with the irreversibility of emissions, has ambiguous effects on the optimal current policy towards mitigation, although in empirical applications this effect is small. In this section we begin by asking how these results are affected when we allow for both mitigation and adaptation. It is straightforward to show that if one introduces an exogenous risk of climate change damages into the simple models of the previous sections, then the main results go through in a straightforward way: an increase in the risk of climate change will cause the optimal levels of mitigation and adaptation to rise, but adaptation and mitigation remain substitutes. Kane and Shogren (2000) obtain slightly different results by using a static model in which adaptation and mitigation play asymmetric roles: the level of damage costs can be reduced by adaptation, but mitigation reduces the risk of climate change, so risk is now endogenous. They show that an exogenous increase in risk has an ambiguous effect - it always leads to an increase in adaptation but the effect on mitigation depends on whether an exogenous increase in risk causes an increase or decrease in the marginal effectiveness of mitigation in reducing risk, and they give examples of how this effect could go either way. However, we show in IMU that it remains the case that adaptation and mitigation are substitutes, in the formal economic sense in which we have been using this term. This is confirmed by some empirical examples. The above analysis is static and so does not allow for important dynamic aspects of the problem: the possibility that over time one can acquire better scientific information which may reduce current uncertainties and the fact that the atmospheric concentration of greenhouse gases is effectively irreversible. This raises an important timing question: should we moderate the current level of action to deal with climate change while we wait to get better scientific information, or should we increase the level of current action in case we learn that climate change is a much more serious problem that we currently expect but then find that because of irreversibility the costs of taking effective action are prohibitive. When include both adaptation and mitigation, although only for the simple case of quadratic cost functions. [3]. We show that the same ambiguity that arose when we only have mitigation applies also when we have adaptation as well: current actions (mitigation and adaptation) with learning may be higher or lower than current actions with no learning depending on the precise parameters of the model. A contribution of the paper is to provide a single coherent analytical framework in which to demonstrate the formal economic analysis of adaptation and mitigation, in which the information available, preferences and objectives, and economic constraints are explicitly set out so that optimizing behaviour can be modelled. We also extend the existing literature in the context of climate change, which has focussed just on issues of mitigation, to include both mitigation and adaptation.

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