This paper aims at proposing a way to get round the intrinsic deadlocks of the economic assessment of climate change impacts (absence of consistent baseline scenario and of credible description of adaptation behaviours under uncertainty). First, we use climate scenarios from two models of the PRUDENCE project (HadRM3H and ARPEGE) to search for cities whose present climates can be considered as reasonable analogues of the future climates of 17 European cities. These analogues meet rather strict criteria in terms of monthly mean temperature, total annual precipitations and monthly mean precipitations. Second, we use these analogues as a heuristic tool to understand the main features of the adaptation required by climate change. The availability of two analogues for each city provides a useful estimate of the impact of uncertainty on the required adaptation efforts. Third, we carry out a cost assessment for various adaptation strategies, taking into account the cost of possible ill-adaptations due to wrong anticipations in a context of large uncertainty (from sunk-costs to lock-in in suboptimal adaptation choices). We demonstrate the gap between an enumerative approach under perfect expectation and a calculation accounting for uncertainty and spillover effects on economic growth.

No abstract

forthcoming in Environmental Modeling and Assessment special issue on "Modeling the economic response to global climate change" Abstract: This paper examines the consequences of various attitudes towards climate damages through a family of stochastic optimal control models (RESPONSE): cost-efficiency for a given temperature ceiling; costbenefit analysis with a "pure preference for current climate regime" and full cost-benefit analysis. The choice of a given proxy of climate change risks is actually more than a technical option. It is essentially motivated by the degree of distrust regarding the legitimacy of an assessment of climate damages and the possibility of providing in due time reliable and non controversial estimates. Our results demonstrate that a) for early decades abatement, the difference between various decision-making frameworks appears to matter less than the difference between stochastic and non stochastic approach given the cascade of uncertainty from emissions to damages; b) in a stochastic approach, the possibility of non-catastrophic singularities in the damage function is sufficient to significantly increase earlier optimal abatements; c) a window of opportunity for action exists up to 2040: abatements further delayed may induce significant regret in case of bad news about climate response or singularities in damages.

We examine the Clean Development Mechanism (CDM) market as form of cooperative involvement between developing-host and developed-investor countries, likely to evolve into a form of Foreign Direct Investment (FDI) with opportunities for further collaboration. We use three variables to measure the level of cooperation, namely number of joint CDM projects, volume of CO_2 abatement realized from the CDM projects, and volume of investment in the CDM projects. We rely on international economics and international relations literature to suggest that the levels of economic development and institutional development, energy structures of the economies, country vulnerability to various climate change effects, political constraints, trade, and historic relations between the host and investor countries are good predictors of the level of cooperation in CDM projects. The main policy relevant conclusions include the importance of simplifying the CDM project regulation/clearance cycle as an essential policy option for further growth of joint CDM projects; improving governance structures in the host and investor countries that would lead to higher political stability and trust between the countries for business, including CDM; and strengthening trade or other long-term economic activities that connect the countries for fostering CDM cooperation. © 2011 by the Massachusetts Institute of Technology.

No abstract