Weighing the Value of a Ton of Pollution: Introducing Trading Was a Helpful Start toward Market- Oriented Reforms, but Policymakers Need to Get the Prices of Permits Right to Get the Most out of Environmental Regulations

Article excerpt

Most efforts to control air pollution employ standards: pollution sources, no matter how different, are required to limit emissions to certain levels or employ specific pollution control technologies. Such policies are inefficient because they ignore the differences in marginal abatement costs across pollution sources--some sources may be able to reduce emissions more easily than others and so should abate more while other sources may have trouble abating and so should abate less.

In light of this inefficiency with standards, economists have long argued for market-based approaches to regulate pollution, using such policy tools as emission taxes and tradable permits. U.S. policymakers use tradable permits to control sulfur dioxide emissions from power plants and nitrogen oxide emissions from industrial point sources. These policies permit firms to trade allowances on a ton-for-ton basis. As a result, pollution sources that can reduce their emissions easily will be financially rewarded for doing so by other sources that face much higher costs.

Such policies are effective at reducing abatement costs; however, they currently overlook something that may be even more important: the damages from pollution emissions such as sulfur dioxide and nitrogen oxides depend upon where they are released. If the emissions occur near a large population center that already experiences bad air quality, the damages will often be much higher than if they occur in a sparsely populated, pristine area.

A number of policy instruments have been proposed to remedy this. Emission taxes could be calibrated to the marginal damage of emissions at each location. Trading regimes could also be adjusted to reflect spatially-variant damages. For example, markets for a cap-and-trade program could be subdivided into homogenous submarkets, allowing ton-for-ton trading within each submarket. The problem with these approaches is that they create very thin markets that may be vulnerable to manipulation. Alternatively, regulators could establish fixed exchange rates between sources that are inversely proportional to the ratio of the marginal damage of emissions. Permit trading programs that feature such fixed exchange rates effectively capture the heterogeneity in marginal damages, achieving pollution reductions at minimum social cost.

In a 2009 paper, we developed a fixed exchange rate policy design for air pollution. We summarize our findings in this article. Instead of allowing firms to exchange permits on a ton-for-ton basis, the permits in our system reflect the relative harm caused by emissions from different regulated sources. The exchange rates are equal to the inverse of the ratio of the firms' marginal damages per ton of emissions.

Of course, this efficient system requires that regulators know source-specific marginal damages in order to determine the exchange rates between sources. Regulators historically lacked these data, and so they could not implement policies featuring trading ratios. However, given recent advances in computational power and model design, the marginal damages from all of the point and aggregated nonpoint air pollution sources in the continental United States can now be calculated. We can use the Air Pollution Emission Experiments and Policy (APEEP) model to track the consequences of emissions through air quality modeling, exposure, dose-response, and valuation for many individual sources and pollutants.

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With these data, we computed the marginal damages for all 10,000 sources measured by the U.S. Environmental Protection Agency for six air pollutants: coarse particulate matter (particles up to 10 micrometers in size), fine particulate matter (particles up to 2.5 micrometers in size), nitrogen oxides, sulfur dioxide, volatile organic compounds, and ammonia. Using these marginal damages, we then calculated trading ratios between each pair of sources. …