Coupling climate and economic models in a cost-benefit framework: a convex optimization approach

In this paper we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99 we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model

Technological Change in Economic Models of Environmental Policy: A Survey

This paper provides an overview of the treatment of technological change in economic models of environmental policy. Numerous economic modeling studies have confirmed the sensitivity of mid- and long-run climate change mitigation cost and benefit projections to assumptions about technology costs. In general, technical progress is considered to be a noneconomic, exogenous variable in global climate change modeling. However, there is overwhelming evidence that technological change is not an exogenous variable but to an important degree endogenous, induced by needs and pressures. Hence, some environmenteconomy models treat technological change as endogenous, responding to socio-economic variables. Three main elements in models of technological innovation are: (i) corporate investment in research and development, (ii) spillovers from R&D, and (iii) technology learning, especially learning-by-doing. The incorporation of induced technological change in different types of environmental-economic models tends to reduce the costs of environmental policy, accelerates abatement and may lead to positive spillover and negative leakage

DSM in context: Understanding the value of DSM and the value of DSM program evaluation

Over the past two decades, demand-side management programs have emerged as a major element of electric utility integrated resource plans; EPRI and several PUC commissioners have concluded that DSM has saved utility and ratepayers many dollars. While DSM holds great potential as a means of abating greenhouse gas emissions and reducing acid rain, many programs have been ineffective and inefficient. If DSM is to serve the public welfare and attain its potential, extensive evaluation is required of the effectiveness of the programs and of their effects on the net energy bills of participants and non participants, as well as of the resulting short- and long-term changes in customer energy use. Since evaluation is expensive, a critical decision concerns the extensiveness of the evaluation. The authors discuss several benefits of evaluation, e.g., reducing the variance of demand forecasts and thus the need for new capacity, in order to determine the optimal level of the program. The authors model the effect of a commercial DSM program on the price of energy and use short term elasticities to estimate energy consumption for program participants and non-participants. They compare these consumption estimates to estimates of program savings to assess the magnitude of this effect and the importance of choosing the appropriate evaluation method

Model, Model on the Screen, What's the Cost of Going Green?

How much a policy is expected to cost and who bears the brunt of that cost play a significant role in the debates that shape regulations. We do not have a good track record of predicting costs and their ultimate distribution, but systematic reviews of past assessments have identified some of the factors that lead to errors. A wide range of expected costs of climate policy have been hotly debated, but all are likely to be wrong. This does not mean that we should continue a debate using ill-informed analyses. On the contrary, we need early small experiments to shed light on key unknowns. Environmental stewardship is a long-term challenge and an adaptive regulatory approach promises to inform policy targets and improve controls through sequential regulatory phases that promote: innovation, flexibility and diffusion of best technologies