Applicability of Benford’s Law to Compliance Assessment of Self-Reported Wastewater Treatment Plant Discharge Data

Pouyan Hatami Bahman Beiglou (), Carole Gibbs (), Louie Rivers (), Umesh Adhikari () and Jade Mitchell
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Pouyan Hatami Bahman Beiglou: Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA
Carole Gibbs: #x2020;School of Criminal Justice and Department of Fisheries and Wildlife Michigan State University, East Lansing, MI 48824, USA
Louie Rivers: #x2021;Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USA
Umesh Adhikari: Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA
Jade Mitchell: Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA

Journal of Environmental Assessment Policy and Management (JEAPM), 2017, vol. 19, issue 04, 1-25

Abstract: The United States (U.S.) environmental regulatory system relies heavily on self-reports to assess compliance among regulated facilities. However, the regulatory agencies have expressed concerns regarding the potential for fraud in self-reports and suggested that the likelihood of detection in the federal and state enforcement processes is low. In this paper, we apply Benford’s Law to three years of self-reported discharge parameters from wastewater treatment plant facilities in one U.S. state. We conclude that Benford’s Law alone may not be a reliable method for detecting potential data mishandling for individual facility–parameter combinations, but may provide information about the types of parameters most likely to be fraudulently reported and types of facilities most likely to do so. From a regulatory perspective, this information may help to prioritise potential fraud risks in self reporting and better direct limited resources.

Keywords: Benford’s Law; self-report data; NPDES; wastewater; compliance assessment; environmental regulation (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1142/S146433321750017X

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