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How Predictable are Environmental Compliance Inspections?

Listed author(s):
  • Sarah L. Stafford


    (Department of Economics, College of William and Mary)

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    The goal of this paper is to examine the timing of environmental compliance inspections and determine the extent to which such inspections can be predicted. The paper focuses on modeling the inspections at hazardous waste facilities in the U.S. using detailed data on individual inspections and facilities. The paper uses a number of parametric and semi-parametric duration models to predict the timing of inspections and finds that the Exponential model provides the best balance in terms of the explanatory power and simplicity of the model. However, even with this model it is difficult to accurately predict the timing of most compliance inspections. The paper also examines the extent to which using data on individual inspections can improve empirical predictions about aggregate inspections. If the goal is to estimate the annual number of inspections at hazardous waste facilities, neither the Exponential model or a Poisson model is clearly superior. Which model is more appropriate depends on the question the researcher wants to answer. Similarly, if the focus is on whether any inspection occurred in a given time period, the benefits of using the Exponential model depend on the nature of the questions to be answered. While the Exponential model performs better than a Probit model in predicting which entities will be inspected, it also results in a higher number of "false positives," that is predicting an inspection when no inspection actually occurs.

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    Paper provided by Department of Economics, College of William and Mary in its series Working Papers with number 143.

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    Length: 39 pages
    Date of creation: 21 Aug 2013
    Handle: RePEc:cwm:wpaper:143
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