This paper addresses the objective of including endogenous technological change in research and policy models of energy, environment, and climate change. Almost everyone, researchers and policy makers alike, agrees that the response of technology to economic incentives over the coming decades may be crucially important in the design of appropriate energy and environmental policies. Unlike policy instruments alone which affect inputs, technology has the potential to change the underlying dynamics of the climate change system. Understanding endogenous technological change is important because policies will tend to affect the evolution of technologies and therefore the costs and benefits of policies and outcomes. Current approaches to energy-environmental modeling are likely to underestimate both the impact and the lags in the effectiveness of policy options.
Thus, questions about the optimal timing and stringency of greenhouse gas abatement policies have become more concerned with assumptions about exogenous technological change in the economic models. In addressing the questions about the optimal timing of carbon abatement, Grub, Chapuis, and Duong (1995) helped focus attention on the need to fully endogenize the rate and direction of technical change. Since then, Goulder and Mathai (1996), Goulder and Schneider (1997), and Norhaus (1997) have constructed climate policy models to examine the effects of including technological change endogenously.
The purpose of this paper is not to critically evaluate particular model findings or draw policy conclusions from them. Rather, it is to examine the methodology by which induced technological change (ITC) us modeled and find both inherent modeling limitations and opportunities for improvement, drawing on insights from innovation and new growth literature. We do not attempt a comprehensive review of innovation literature – only a selective review to highlight relevant ideas and present distinctions important to ITC modeling. (A broader and more comprehensive survey of innovation literature relevant to ITC is given by Weyant , and Carraro  also reviews aspects of ITC modeling, particularly with regard to strategic gaming and geographic effects.) Since ITC modeling is at an early stage in development, this paper places emphasis in qualitative insights. A critical question concerns how much confidence we can expect to place in models of long-term technological change, and how much of the analysis should rest on the qualitative insights of policy and decision makers. The paper should be of interest both to integrated climate change and ITC modelers, as well as those drawing policy conclusions from these models.
The paper begins with a brief review of innovation literature to explore the context in which ITC models have been developed. Two elements make up the heart of models of innovation:
- private investment incentives and
- spillovers from R&D. Particular attention is devoted to reviewing the notion of spillovers from R&D and distinguishing it from private investment incentives.
Then, prominent examples of the state-of-the-art ITC models are reviewed and generalizations are made about fundamental aspects common to all of them. The final section is devoted to exploring limitations and possible extensions to ITC models such as: complementary sources of technical change; heterogeneity of innovators; uncertainty in returns from R&D; and path dependence and inertia. Besides suggesting possibilities for improvement, one of the key insights here is that induced change, as well as policy lags, may be much more significant if extensions from the conventional economic frameworks are considered. It is important to recognize, though, that the extensions are general improvements to exogenous models of technological change, and do not require a focus on ITC to be considered.