IDEAS home Printed from
MyIDEAS: Login to save this article or follow this journal

Linking Policy to Statistical Uncertainty in Air Pollution Damages

  • Muller Nicholas Z


    (Middlebury College)

This study uses Monte Carlo analysis to characterize the uncertainty associated with per-ton damage estimates for 565 electric generating units (EGUs) in the contiguous United States (U.S.) This analysis focuses on damage estimates produced by an Integrated Assessment Model (IAM) for emissions of five local air pollutants: sulfur dioxide (SO2), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH3), and fine particulate matter (PM2.5). For each power plant and pollutant, the Monte Carlo procedure yields an empirical distribution for the damage per ton, or marginal damage. The paper links uncertainty in marginal damages to air pollution policy in two ways. First, the paper characterizes uncertainty in the magnitude of the marginal damages which is relevant to policymakers in determining the stringency of pollution controls. Second, the paper explores uncertainty in the relative damages across power plants. Relative damages are important if policymakers elect to design efficient regulations that vary in stringency according to where emissions are released. The empirical section of the paper finds that the marginal damage distributions are positively skewed and they are more variable for sources in urban areas than rural locations. The paper finds that uncertainty in three input parameters has the greatest impact on uncertainty in the magnitude of damages: the adult mortality dose-response parameter, the mortality valuation parameter, and air quality modeling. The analysis also finds that for each pollutant except for NOx only uncertainty in air quality modeling impacts efficient trading ratios calibrated to each firm's marginal damages.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by De Gruyter in its journal The B.E. Journal of Economic Analysis & Policy.

Volume (Year): 11 (2011)
Issue (Month): 1 (June)
Pages: 1-29

in new window

Handle: RePEc:bpj:bejeap:v:11:y:2011:i:1:n:32
Contact details of provider: Web page:

Order Information: Web:

No references listed on IDEAS
You can help add them by filling out this form.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:bpj:bejeap:v:11:y:2011:i:1:n:32. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Golla)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.