This paper is concerned with the negative collateral consequences monetary sanctions may have on companies that are prosecuted for violating federal environmental laws such as the Clean Air Act and Clean Water Act. Companies often claim fines for law violations will force them to lay off employees and possibly go bankrupt. Using the treadmill of crime theoretical lens, we employ a multivariate analysis on a unique data set of 169 companies to determine if their federal prosecutions are associated with negative collateral consequences. We find that some companies, upon being fined, are more likely to experience negative collateral consequences than others.
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See the Corporate Prosecution Registry (CPR) created by Brandon Garrett and Jon Ashley (Garrett and Ashley . It is housed with the University of Virginia Law Library, and is one of the few sources of data on corporate sentencing for public use. This data set provides only the case names and penalties—specific information regarding the crime, company information or demographic data for people living around the environmental hazard is not available.
The concern with collateral consequences extends also to the risks posed to workers, shareholders and broader communities should a successful prosecution result in a company shuttering its doors and laying off employees. This particular use of the phrase, “collateral consequences,” is associated with both the approach to prosecutorial behavior throughout the early twenty-first century (see, e.g., ) as well as critiques of the prevailing respondeat superior doctrine of corporate criminal liability in the federal criminal justice system [18,19,20].
It is important to note that the treadmill of crime theory integrates environmental sociologists’ focus on the political economy to explain continued environmental pollution in the face of financial penalties [27, 32]. The treadmill of crime theory is also consistent with the state-corporate crime perspective in criminology, which, like green criminology, originates from structural Marxist examinations of corporate crime [33,34,35].
FOIA Number 2014–03784. Completed September 23, 2014
Public Access to Court Electronic Records (www.pacer.gov)
We do not use a ‘stock price’ variable because most of the companies we analyze (81.7%) are not publicly traded.
Inspection of QIC (i.e., model fit) statistics for the models based on different specifications of the correlation structure indicate no significant disadvantage to using the autoregressive specification .
An alternative set of models using the unstandardized, logged measure of total fines revealed some differences, most notably the reversed sign of the coefficient similar to what was previously noted with the bivariate correlations in Table 2. Otherwise, the findings for the models predicting bankruptcy and number of employees are virtually identical.
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Greife, M.J., Maume, M.O. Do companies pay the price for environmental crimes? Consequences of criminal penalties on corporate offenders. Crime Law Soc Change 73, 337–356 (2020). https://doi.org/10.1007/s10611-019-09863-4