Modelling the economic costs of climate policy

The overall objective of this report is to scrutinize previous economic models used to assess the economic costs of climate protection. We pay particular attention to the way in which different model structures and assumptions affect cost estimates, and highlight the limitations and the strengths of different types of models and approaches. The report begins by briefly discussing the concept of economic costs. We present a taxonomy of different costs, and distinguish, in particular, between direct cost, partial equilibrium costs and general equilibrium costs. Non-market costs and the impact of policy design on climate policy costs are also discussed. The different model approaches used to assess the economic impacts of climate policy put particular emphasis on some types of costs while ignoring or simplifying the representation of other costs. The conception of the cost of behavioural change in bottom-up (e.g., systems engineering models) and top-down models (e.g., general equilibrium models, neoclassical growth models etc.) differs; in the former case “a technology” represents a particular activity or process, and the costs of climate policy stems from the extra cost of a discrete shift from an activity/process to another. By contrast, in top-down models no discrete activities are represented, and instead “technology” is defined by continuous production (or cost) functions. The empirical bases for the two model approaches therefore also differ. This also means that in bottom-up models emphasis is placed on a representation of technological detail, while top-down models attempt to provide a theoretically consistent description of overall economy and the interactions be-tween different markets. This suggests that these two model approaches should be considered complements (rather than substitutes), and they have recently been combined in so-called hybrid models. The various model approaches also result in different ways of reporting cost estimates. In the report we discuss the validity of four types of measures: (a) total direct compliance costs; (b) the carbon price required to comply with a given emissions reduction; (c) the loss in gross domestic (or world) product; and (d) the equivalent variation (i.e., the change in income that would lead to the same change in a consumer’s utility as the policy considered). The latter two measures (and in particular the last one) are generally the most appealing ways of reporting costs from an economic-theoretical point of view. The estimated costs of reducing greenhouse gas emissions tend to vary a lot across different models and studies, and in the report we consult previous studies and meta-analyses to systematically review the main assumptions and methodological choices that underlie different cost estimates. We distinguish between four main types of climate policy cost drivers: (a) the baseline scenario; (b) the structural characteristics of the models; (c) the design of climate policy; and (d) the inclusion of non-market costs and benefits. The analysis shows that all these variable categories help explain model outcomes. Many of the variables discussed come out as important also when exposed to quantitative meta-analysis, although in some other cases – e.g., substitution possibilities, level of technological detail etc. – the results are in part unexpected. The importance of policy design – the degree of flexibility permitted in complying with the emission (or stabilization) target – is also well illustrated in previous studies, and poor designs may substantially raise the cost of meeting emissions reduction targets. Over the long-run the development of new technology will be essential in meeting global climate challenges. For this reason the impact of climate policy instruments on technological progress, and ultimately on compliance costs, is of great interest. Such assessments