The assessment of climate change mitigation policies mainly depends on three not mutually exclusive modeling decisions: First, the chosen discount rate, since costs are incurred today and long-term benefits occur in the future. A low (high) discount rate favors immediate (delayed) action. Second, the uncertainties related to the problem of climate change. This debate was revived by the literature dealing with Martin Weitzman's "dismal theorem", stating that the unknown unknowns could be too large for cost-benefit analysis of long-term climate policy measures. Third, the treatment of technological change in economic modeling of climate policy.

Climate change, climate policy measures and technological change are highly intertwined matters. In general, the close relationship lies in negative and positive economic externalities. On the level of an individual firm as well as on a more global scale, pollution and climate change are negative externalities. On the other hand, the generation of knowledge represents a positive externality. The appropriate modeling of both is a crucial decision each modeler has to make. Many empirical studies have demonstrated the sensitivity of long-term analysis to assumptions about technological change. Most economic modeling was done under the assumption of exogenous technological change. These models are unable to capture and examine important links between policy and technical change. The wider literature acknowledged that technical change is not autonomous and that it is possible to identify processes which are responses to market conditions, expectations and governmental regulatory standards. To capture these developments, models incorporating endogenous technological change were developed, but the empirical base for the linkage between environmental policy and technical change was weak. In the past few years, significant improvements in the description of technological progress in climate policy assessment models have been achieved.

The purpose of this paper is threefold: First, we want to sketch the different options for modeling technological change on both a microeconomic and macroeconomic level, where our main focus will lie on large-scale macroeconomic models. Second, we want to give an overview of the different models surrounding climate change and energy economics. How is technological change implemented in the models? How does this affect the results? Which efforts have been made to endogenize the technological progress previously treated as exogenous? And finally we want to give a brief discussion of open research issues.

Although many problems associated with modeling technological change as exogenous have been resolved, numerous questions still remain unanswered. As technological change is an uncertain phenomenon, these uncertainties have to be incorporated in large-scale models more carefully. This holds particularly true for major innovations. Another important dimension of technical change that has to be taken into account is the potential for path-dependency, inertias and lock-in situations. Environment-energy-economy models can account for such effects by a careful inclusion of learning-by-doing, time lags, assumptions about the diffusion rates of innovations and directed (or biased) technological change. A further important aspect of the innovation process not appropriately accounted for is the heterogeneity of firms, as different firms respond differently to environmental policies.