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The Effect of Incomplete Enforcement Information on Ambient Pollution Levels: Evidence from the Clean Water Act

Date and Time

Tuesday 11/19/2019 2:00PM to 3:30PM EST
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Room 1426, William Jefferson Clinton West Building
1301 Constitution Ave., NW
Washington, DC 20001


Contact: Carl Pasurka, 202-566-2275

Presenter:  Tihitina Andarge (Department of Agricultural & Resource Economics, University of Maryland)

Description:  Firms will comply with a regulation when the expected benefits of compliance exceed the expected costs. If the regulator has incomplete enforcement information and firms are aware of this, it will enter into their calculation of expected compliance benefits and costs. The literature on regulatory enforcement generally assumes that the regulator has complete information on the universe of regulated firms. This paper relaxes this assumption and develops a theoretical model of the firm’s optimal level of emissions under such conditions. The theoretical results indicate that the optimal level of emissions is decreasing in the likelihood of being known to the regulator. I analyze this effect empirically within the context of Clean Water Act (CWA) permit regulations in the Upper and Lower Mississippi River Basins. I combine several sources of data to estimate a spatial lag model of nitrogen concentration controlling for nitrogen concentration at the upstream location, point and non-point sources of pollution, catchment characteristics, population, inspections, temperature, and precipitation. Preliminary results indicate that a one percentage point increase in the share of known regulated agents is associated with a 0.33 mg/L decrease in ambient nitrogen concentration. This estimate suggests that increasing the share of firms known to the EPA by 10 percentage points would decrease nitrogen concentration by 3.28 mg/L, about 53.68% of the average nitrogen concentration in the sample. Thus, improvements in the EPA’s information on the identities of the regulated agents may greatly improve environmental quality.