In recent years, emissions trading has become an important element of programs to control air pollution. Experience indicates that an emissions trading program, if designed and implemented effectively, can achieve environmental goals faster and at lower costs than traditional command-and-control alternatives. Under such a program, emissions are capped but sources have the flexibility to find and apply the lowest-cost methods for reducing pollution. A cap-and-trade program is especially attractive for controlling global pollutants such as greenhouse gases because their warming effects are the same regardless of where they are emitted, the costs of reducing emissions vary widely by source, and the cap ensures that the environmental goal is attained.

Report authors Denny Ellerman and Paul Joskow of the Massachusetts Institute of Technology and David Harrison of National Economic Research Associates, Inc. review six diverse U.S. emissions trading programs, drawing general lessons for future applications and discussing considerations for controlling greenhouse gas emissions. The authors derive five key lessons from this experience. First, emissions trading has been successful in its major objective of lowering the cost of meeting emission reduction goals. Second, the use of emissions trading has enhanced—not compromised—the achievement of environmental goals. Third, emissions trading has worked best when the allowances or credits being traded are clearly defined and tradable without case-by-case certification. Fourth, banking has played an important role in improving the economic and environmental performance of emissions trading programs. Finally, while the initial allocation of allowances in cap-and-trade programs is important from a distributional perspective, the method of allocation generally does not impair the program’s potential cost savings or environmental performance.

With growing Congressional interest in programs to address climate change—including the recent introduction of economy-wide cap-and-trade legislation controlling greenhouse gas emissions—the application of lessons learned from previous emissions trading programs is timely. In addition to this review, the Pew Center is simultaneously releasing a complementary report, Designing a Mandatory Greenhouse Gas Reduction Program for the U.S., which examines additional options for designing a domestic climate change program.

About the book: In concise, informative chapters, Climate Economics and Policy considers the key issues involved in one of the most important policy debates of our time. Beginning with an overview and policy history, it explores the potential impact of climate change on a variety of domains, including water resources, agriculture, and forests. The contributors then provide assessments of policies that will affect greenhouse gas emissions, including electricity restructuring, carbon sequestration in forests, and early reduction programs. In considering both domestic and international policy options, the authors examine command and control strategies, energy efficiency opportunities, taxes, emissions trading, subsidy reform, and inducements for technological progress.

To improve the estimate of economic costs of future sea-level rise associated with global climate change, this report generalizes the sea-level rise cost function originally proposed by Fankhauser, and applies it to a new database on coastal vulnerability developed as part of the Dynamic Interactive Vulnerability Assessment (DIVA) tool.
      An analytic expression for the generalized sea-level rise cost function is obtained to explore the effect of various spatial distributions of capital and nonlinear sea-level rise scenarios. With its high spatial resolution, the DIVA database shows that capital is usually highly spatially concentrated along a nation's coastline, and that previous studies, which assumed linear marginal capital loss for lack of this information, probably overestimated the fraction of a nation's coastline to be protected and hence protection cost. In addition, the new function can treat a sea-level rise scenario that is nonlinear in time. As a nonlinear sea-level rise scenario causes more costs in the future than an equivalent linear sea-level rise scenario, using the new equation with a nonlinear scenario also reduces the estimated damage and protection fraction through discounting of the costs in later periods.
      Numerical calculations are performed, applying the cost function to the DIVA database and socioeconomic scenarios from the MIT Emissions Prediction and Policy Analysis (EPPA) model. The effect of capital concentration substantially decreases protection cost and capital loss compared with previous studies, but not wetland loss. The use of a nonlinear sea-level rise scenario further reduces the total cost because the cost is postponed into the future.

The experiment reported here tests the case of so-called exclusionary manipulation of emission permit markets, i.e., when a dominant firm — here a monopolist — increases its holding of permits in order to raise its rivals' costs and thereby gain more on a product market. Earlier studies have claimed that this type of market manipulation is likely to substantially reduce the social gains of permit trading and even result in negative gains. The experiment designed here parallels institutional and informational conditions likely to hold in real trade with carbon permits among electricity producers. Although the dominant firm withheld supply from the electricity market, the outcome seems to reject the theory of exclusionary manipulation. In later trading periods, closing prices on both markets, permit holdings and total electricity production are near competitive levels. Social gains of emissions trading are higher than in earlier studies.