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2004 Progress Report: Dynamic Adjustment to Incentive-Based Environmental Policy to Improve Efficiency and Performance
EPA Grant Number: R830990Title: Dynamic Adjustment to Incentive-Based Environmental Policy to Improve Efficiency and Performance
Investigators: Burtraw, Dallas , Palmer, Karen
Institution: Resources for the Future
EPA Project Officer: Wheeler, William
Project Period: June 1, 2003 through May 31, 2005
Project Period Covered by this Report: June 1, 2003 through May 31, 2004
Project Amount: $173,684
RFA: Market Mechanisms and Incentives for Environmental Management (2002)
Research Category: Economics and Decision Sciences
Description:
Objective:Policymakers advance economic efficiency when they set policy goals at levels that equate the marginal costs of additional pollution controls with the marginal benefits of improvements in environmental quality. Theory and experience indicate that economic efficiency also is advanced when policymakers employ market-based approaches such as tradable permits to achieve these goals in the least costly manner. When setting goals, policymakers face uncertainty about the costs and benefits to society of achieving a specific goal, and in particular how those costs and benefits are likely to change over time. Ideally, policymakers would like to be able to update environmental targets specified in legislation or regulation as new information about the costs or benefits of achieving a particular target becomes available.
This research project addresses incorporating new cost information into market-based environmental policy. When policymakers use market-based policies, they create an institution that provides instantaneous information about the cost of compliance, and this information might be used to update emission targets. The objective of this research project is to examine regulatory approaches that extend the use of market-based environmental policy and facilitate environmental target updates to reflect new policy cost information. We consider several mechanisms that could be used to make regulation more flexible and able to adjust to new information. We evaluate the robustness of different approaches in different situations and in response to various sources of uncertainty. A secondary focus considers the incentives for continual improvement in environmental performance that such approaches may provide. To make the research concrete and relevant to contemporary policy, we focus on emissions of NOx, SO2, and CO2 from the electricity sector, although we aim to draw lessons that have more general applicability.
Progress Summary:The research involves analytical and numerical strategies. To date, almost all of the work has involved the development of modeling capability that will serve as a laboratory for numerical simulation. The model being used and modified is Resources for the Future’s Haiku Electricity Market Model. This model is highly parameterized and has substantial detail about technology and electricity markets.
A series of issues has been tackled in the process of updating and further developing the model. One change in the model is to provide a fuller accounting of changes in economic surplus as a consequence of changes in investment and compliance behavior. Economic surplus is measured as the sum of producer and consumer surplus and government revenues stemming from the permit market. These measures are important when evaluating different flexible policy measures.
We also have completed a mapping of existing generation assets to the firm level, as firms were aggregated in January 2004. This mapping accounts for mergers and acquisitions because this feature of the model was last updated in 2002. Jointly owned generation units also are accounted for in an improved fashion. This information will be used to examine the impact on different portfolios of generation assets (organized at the firm level) of different policy instruments. This will be valuable in understanding the distribution of the burden and the cost savings imposed by each approach.
A simultaneous development in the model is the incorporation of mercury emissions abatement accounting for interaction in the investment and operation of SO2 and NOx compliance options (including fuel choice). The original proposal emphasized only SO2, NOx, and CO2. We quickly discovered, however, that an important influence on these emission markets is the regulation of mercury, and integration was important to the simulations.
The largest surprise to date in this research project was the cost and difficulty of integrating mercury controls into the model algorithm. This finally has been accomplished by leveraging the work in this research project with resources from other funded projects, as discussed below.
Preliminary analysis indicates that there are three primary sources of uncertainty that affect model results. These include technological change, electricity demand, and natural gas prices. Model development has proceeded to account for these forms of uncertainty.
Technological change has been addressed through two major updates to the model. One is a review and incorporation of information from various studies regarding the expected path in cost for integrated gasification combined cycle and the capture and storage of associated carbon emissions. Estimates also are adopted for carbon capture and storage for other technologies, including pulverized coal plants. The second major update to the model is fuller characterization of renewable technologies, including resource availability.
Uncertainty in electricity demand still is in development. Two approaches are under consideration. One approach would build a system of demand equations based on fundamental determinants of demand, including population demographics, economic activity, weather, etc. We have begun the development of an enhanced demand side to the model that would build the forecast of electricity demand according to these principles, but it is not yet finished. We will not wait for its completion, however, before preparing the first manuscript for this research project. Currently, we have available demand forecasts that are calibrated to Energy Information Administration forecasts. As a fallback strategy, therefore, we will use scenario analysis with historic variability from forecasts over the previous decade as a proxy for uncertainty in electricity demand. The fallback strategy for uncertainty in natural gas supply and price forecasts would use a similar scenario-based approach. A key aspect of modeling uncertainty is correlation among these sources of uncertainty or variability. This will be part of the numerical analysis, even though the correlations in uncertainty may be illustrative and not estimated econometrically.
The main development that is central to the research project is incorporating an intertemporal decision algorithm that allows for emission allowance banking and for the inclusion of “institutions” that we intend to model. The institutions include a safety valve, a symmetric safety valve, a declining cap, and a circuit breaker on a declining cap. These model capabilities have been developed and currently are being tested.
Finally, several approaches to emission allowance distribution have been developed for this research project and for other ongoing projects. The approaches include various forms of allocation based on historic measures of generation or emissions, allocation based on updated measures, or an auction. In each case, the model can target a subset of technologies as qualifying for allocation or as subject to compliance.
Activities to date have been oriented to developing the infrastructure that will enable us to address the research project objectives. We do not have results at this time. Substantial model development has been accomplished, and some of the development has leveraged restricted support from other public agencies, including the New York State Energy Research Development Authority and the State of Maryland Power Plant Research Program. These two grants helped leverage development of the mercury algorithm in the model and some of the technology updates. Research sponsored by EPA’s Clean Air Markets Division helped leverage the development of allocation methods for the initial distribution of emission allowances.
Future Activities:We will complete the option for characterization of uncertainty stemming from demand and natural gas supply and prices, which is expected to be a simple task, and then develop estimates of correlations among the three major sources of uncertainty. From this point, we will be able to complete the first set of model runs. The runs will provide economic measures, such as changes in consumer and producer surplus, of the cost of “surprises.” We then will use the model as a laboratory to examine the performance of alternative institutions for adjusting the environmental goal in the face of new information, and we will measure their performance according to the same economic measures.
The simulation modeling can provide convincing results, but it is especially useful for generating hypotheses. Subsequently, we will return to analytical methods to look for general propositions based on the hypotheses that are generated. We also plan to use the model to examine the various institutions that have been proposed in the economics literature and by state agencies and advocacy groups. We will examine these institutions from the viewpoint of efficiency and distributional consequences.
Journal Articles:No journal articles submitted with this report: View all 7 publications for this project
Supplemental Keywords:air, global climate, integrated assessment, particulates, public policy, cost-effectiveness, benefit-cost analysis,
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ENVIRONMENTAL PROTECTION AGENCY, Economic, Social, & Behavioral Science Research Program, Scientific Discipline, RFA, Social Science, decision-making, Economics & Decision Making, Reinvention, Ecology and Ecosystems, Economics, Market mechanisms, compliance costs, allowance allocation, decision analysis, incentives, market-based mechanisms, decision making, emissions trading, allowance market performance, cap and trade systems, market incentives, effects of policy instruments, environmental economics, compliance behavior, emission fees, incentive based environmental policy, environmental decision making
Relevant Websites:
Progress and Final Reports:
Original Abstract
2005 Progress Report
Final Report