Abstract
Corporate crime scholars typically seek to identify the characteristics that distinguish between criminal (or noncompliant) and compliant corporations, usually relying on amoral calculator models to explain offending. Yet, many companies comply and even overcomply with environmental regulations by polluting significantly less than legally allowed. Broader theoretical models may be necessary to explain this phenomenon. In the current study, I explore the utility of corporate citizenship, conceptualized as the degree to which firm culture promotes or inhibits a moral commitment to society, for explaining overcompliance with the Environmental Protection Agency’s Clean Water Act regulations. Findings offer little support for the proposed relationship between corporate citizenship and environmental performance. The implications of these findings and directions for future research are discussed.
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Notes
Overall, responses to environmental violations tend to be fairly lenient. In examining more than 27,000 enforcement actions over a 13 year period, Hunter and Waterman [40] find that the most severe sanctions available (civil penalties or contempt action) were used in only 0.4 percent of cases. By far, the most common responses to violations were informal (e.g., warning letters). When penalties are issued, they tend to be low. For example, the average administrative fine imposed by the EPA in 1995 was $34,000, but the median range of fines was only $5 to $10,000 [20].
Carroll [13] uses a pyramid as a metaphor to describe four social responsibilities. He explicitly acknowledges economic responsibilities as the base of the pyramid, followed by legal, ethical, and philanthropic responsibilities. Responsible firms will develop methods to deal with these responsibilities and the tensions between them [13].
Clarkson [17] defines social performance as the level of stakeholder satisfaction—the extent to which firms respond to stakeholder issues regardless of motivation. Advocates of a stakeholder approach explicitly reject the CSP model because of its complexity [17], but stakeholder theory is compatible with other models. It can be used to define the groups to whom the firm has economic, legal, ethical, and philanthropic responsibilities [13].
Firms that take duty seriously will not ignore profits. Even the best corporate citizens (motivated by principle) are still corporations with investors and shareholders. For this reason Carroll [13] explicitly integrates economic responsibilities as one component of social responsibility (and stakeholder theorists define shareholders as one stakeholder group). Good corporate citizens merely have a broader set of consideration in addition to profits.
The authors provide a list of items used in the survey questionnaire, but it is somewhat unclear which items specify “non-financial” considerations. However, some do seem to be more social in nature. For example, Hill et al. [37] asked managers about the extent to which industry relations were used to evaluate division performance.
Pulp mills and paper industries were combined because many mills and companies engage in both industrial processes.
Major industrial facilities are distinguished from minor dischargers by the facility’s potential for discharging toxic wastes, the volume and type of wastewater, and whether the receiving water is used for drinking [79]. Although we developed an extensive procedure to match facilities to parent companies, we were unable to overcome the lack of information on minor facilities. Given that ours was a national study, contacting every state for information on minors in specific industries was beyond the resources available for the project.
Plants may be required to report the minimum, maximum or average quantity or concentration of pollutants each month. Minimums represent the lowest measurement of the month, maximums represent the highest measurement, and averages represent the mean. I focus on average values to examine the overall level of monthly compliance rather than extreme events (i.e., minimums and maximums). I also focus on monitoring locations and measurements of water the facility was directly discharging into the waterways (effluent gross value). Water samples (taken to measure pollution levels) must be taken at various locations in and around plants. I excluded measurements related to upstream and downstream monitoring.
In some cases, facilities reported discharge values that are not possible (i.e., negative values). These are likely entered in error. Consistent with Bandyopadhyay and Horowitz [7], these measurements were excluded from the sum, resulting in a small fraction of lost cases (i.e., 1.3% of all of the quantity measurements and 0.4% of the concentration measurements).
The reported discharge was extremely high in a few reports to EPA. In these cases, the compliance ratio was computed to compare the reported discharge to its associated limit. Most of the time the discharge was extremely high because the limit on pollution was very high, suggesting that it was not an error. In three reports, the reported discharge value seemed unreasonably high compared to the limit and was likely the result of a typographical error. These values were dropped, resulting in the exclusion of one report from the conventional pollutants quantity compliance ratio and two reports from the concentration compliance ratios.
Log transformation resulted in the loss of one company/year for three of the compliance ratios in which the compliance ratio equaled zero.
The EPA engaged in a heavy recruiting effort, beginning in 1991, to encourage firms to join the TRI 33/50 program. The EPA invited firms to participate in three stages with a total of approximately 8,000 invitations. Two sources were used to verify that all companies in our initial sample were invited to participate. First, firms that discharged any one of the 17 chemicals of interest were invited. Thus, TRI facility reports from 1988 and 1992 were used as verification. Second, Vidovic and Khanna [74] provided their EPA database which contained facility reports of TRI 33/50 chemicals and the parent company participation status (participated, refused, never replied, etc.).
Firms are not likely to experience reduced enforcement in exchange for participation for several reasons. First, the EPA structure keeps program offices relatively separate. Instead of integrating new legislative requirements into an agency wide strategy, the EPA creates new, separate program offices when additional regulations are passed. EPA enforcement has only recently become more centralized. In addition, much of the enforcement takes place at the state-level and the TRI 33/50 program is a federal program [4]. Finally, Arora and Cason [4] reviewed enforcement decisions and penalties under the Toxic Substances Control Act (a program separate from the TRI program) and find little evidence of enforcement reductions for participants. Thirty-five percent of the companies fined were 33/50 participants. The largest fine was also imposed on a 33/50 participant.
Although there is a growing body of literature examining the antecedents and effectiveness of the TRI 33/50 program, a similar body of literature has not developed on the Wastewise program.
In fact, the TRI reports from 1988 are used as the program baseline to avoid excluding any decreases in emissions made by firms prior to the program inception in 1991 [5].
For example, under “Community” KLD companies may be coded has having a “strength” for the following actions: generous giving, innovative giving, non-U.S. charitable giving, support for housing, support for education, and other strengths. Companies that reach the criteria for “strength” are coded as a one and those that do not are coded zero. The “Community” dimension also contains a list of concerns on which companies may be rated a zero or one, including investment controversies, negative economic impacts and other concerns.
For example, only companies that consistently give over 1.5% of trailing 3-year net earnings before taxes to charity are rated as “generous givers” under the philanthropy sub-category. On the more subjective side, KLD determines whether a company is a “prominent participant” in partnerships that support housing (rather than simply measuring participation).
The environmental ratings and product ratings are excluded because of potential endogeneity with the outcome measure. The product ratings are excluded from the global measure because almost every “concern” within the product dimension is related to crime (e.g., paying fines or penalties for regulatory actions relating to product safety). All crime related sub-categories are excluded from every dimension under study, again to reduce possible endogeneity. Criminologists would conceive of crime as an outcome of corporate citizenship rather than a measure of it. Thus, any items related to fines or civil penalties are excluded whether they refer to discrimination, pollution, antitrust or product safety issues. In addition, only one company is rated as a strength in the product dimensions at any time during the sample period. Thus, this indicator does not distinguish among the companies.
The pattern in the “missing” compliance ratio data numbers is similar in the samples lacking KLD measures. In the sample with citizenship measures, of a total possible 169 company/years, complete data is available for 89% of the conventional pollutant quantity compliance ratio; 62% of the toxic pollutant quantity compliance ratio; 81% of the conventional concentration compliance ratio; and 56% of the toxic conventional concentration compliance ratio.
The means presented and mean comparison tests are derived from the median of the log transformed monthly compliance ratio. Thus, they do not match the means presented in Table 1. Significant differences at the p = 0.05 level are included.
In the reduced sample, ROS ranges from 0.56 to 5.02 with an average of 1.09. The number of employees ranges from 5,700 to 112,900 with a mean of 28,320. Finally, 15% of the companies are steel companies and 34% are oil companies.
The reduced sample with replacement (column 2) does not different significantly from the second reduced sample (column 3) on any measure.
Several model diagnostics were examined to address other potential problems in the regression models. The tolerance/variance inflation factor for the independent variables in each of the models was examined to determine whether multicollinearity was a significant problem. The tolerance for each independent variable is never lower than 0.35. Generally the tolerance is at least 0.4 or 0.5, but usually greater. Thus, multicollinearity does not seem to be a significant problem in these models. The Ljung-Box Q Statistic was used to test for autocorrelation. It was not significant, indicating that autocorrelation is not an issue. Finally, the Cook and Weisburg test indicated that heteroskedasticity is a problem. In addition, observations of the same company over several years are not independent. Consistent with the prior literature [26, 57, 33], the STATA cluster command is used to adjust the standard errors for these two factors.
For the regression models, the number of employees is divided by 1,000 to produce more interpretable coefficients. The results do not vary substantively between the two reduced samples (KLD sample with and without replacement). Thus, the results for the sample without replacement are not presented. The substantive results also do not change when the few firm/years in violation are excluded.
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Gibbs, C. Corporate citizenship and corporate environmental performance. Crime Law Soc Change 57, 345–372 (2012). https://doi.org/10.1007/s10611-012-9365-2
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DOI: https://doi.org/10.1007/s10611-012-9365-2