The geographic distribution of environmental inspections

Models of the enforcement of environmental regulations regarding point source pollution suppose that the probability of inspection or audit is independent across facilities. However, there are a number of reasons why regulators may choose to inspect many sites in a particular geographic area at one time. If the probability a site is inspected also depends on its compliance behavior, the expected payoff from choosing to violate will depend upon the compliance decisions of neighboring sites, creating a game of strategic interdependence between firms. In this paper, we use a dataset of inspections at petroleum storage sites in Manitoba between 1981 and 1998 to consider to what extent inspections are spatially correlated and whether inspection probabilities are a function of the inspection and violation history of the site and its neighbors. Further, we examine to what extent firms take into account whether their neighbors have been previously found in violation in determining compliance.

[1]  W. Gray,et al.  Compliance and Enforcement: Air Pollution Regulation in the U.S. Steel Industry , 1996 .

[2]  Anne E. Sartori An Estimator for Some Binary-Outcome Selection Models Without Exclusion Restrictions , 2003, Political Analysis.

[3]  W. Harrington,et al.  A reconsideration of enforcement leverage when penalties are restricted , 1991 .

[4]  N. Rickman,et al.  Regulatory dealing - revisiting the Harrington paradox , 1999 .

[5]  An empirical study on effective pollution enforcement in Korea , 2004, Environment and Development Economics.

[6]  Eric A. Helland The Enforcement of Pollution Control Laws: Inspections, Violations, and Self-Reporting , 1998, Review of Economics and Statistics.

[7]  J. Harford Measurement error and state-dependent pollution control enforcement , 1991 .

[8]  L. Franckx Marginal Deterrence Through Ambient Environmental Inspections , 2004 .

[9]  John Livernois,et al.  Truth or consequences: Enforcing pollution standards with self-reporting , 1999 .

[10]  M. Raymond Enforcement leverage when penalties are restricted: a reconsideration under asymmetric information , 1999 .

[11]  Anthony Heyes,et al.  Making things stick: enforcement and compliance , 1998 .

[12]  Daniel A. Griffith,et al.  Statistical analysis for geographers , 1990 .

[13]  Winston Harrington,et al.  Enforcement leverage when penalties are restricted , 1988 .

[14]  M. Raymond Regulatory Compliance with Costly and Uncertain Litigation , 2004 .

[15]  Dietrich Earnhart,et al.  Regulatory factors shaping environmental performance at publicly-owned treatment plants , 2004 .

[16]  H. Eckert,et al.  Inspections, warnings, and compliance: the case of petroleum storage regulation , 2004 .

[17]  L. Nadeau EPA Effectiveness at Reducing the Duration of Plant-Level Noncompliance , 1997 .

[18]  Laurent Franckx,et al.  The Use of Ambient Inspections in Environmental Monitoring and Enforcement When the Inspection Agency Cannot Commit Itself to Announced Inspection Probabilities , 2002 .

[19]  B. Laplante,et al.  Environmental Inspections and Emissions of the Pulp and Paper Industry in Quebec , 1996 .

[20]  Anthony Heyes,et al.  A Theory of Filtered Enforcement , 2002 .

[21]  Robert Haining,et al.  A Comparative Evaluation of Approaches to Urban Crime Pattern Analysis , 2000 .

[22]  Anna Alberini,et al.  Environmental Regulation and Substitution Between Sources of Pollution: An Empirical Analysis of Florida’s Storage Tanks , 2001 .