Abstract
This paper examines the regulatory compliance of small and lightly regulated facilities using a unique dataset of hazardous waste generators in New Hampshire. In particular the paper considers the factors that encourage such facilities to adopt environmental management systems (EMS) and how that adoption affects compliance behavior. The analysis provides a relatively rare look into the behavior of small and conditionally-exempt generators (CEG) since such facilities are seldom inspected or examined. The analysis finds that CEGs are less likely to adopt an EMS relative to more strictly regulated facilities as are smaller and privately held facilities, but that local enforcement activity encourages adoption. For CEGs, EMS adoption does have a significant positive effect on overall compliance. Additionally at both small and CEG facilities, EMS adoption has a significant positive effect on one particular aspect of compliance behavior, the presence of best practices for waste storage.
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Notes
While there are other important and thoughtful studies of what makes an EMS most successful and the role of EMSs in business performance more generally, since this study does not consider those aspects of an EMS they are not included in this literature review.
A 1996 study by Henriques and Sadorsky of the 750 largest Canadian firms examined the factors that drive firms to adopt an “environmental plan,” which some may see as a precursor to a formal EMS.
Unfortunately only 8 of the surveyed facilities were inspected in 2002 or 2003 and thus had their regulatory compliance assessed. Therefore it is not possible to estimate how the compliance score relates to regulatory compliance.
Since there are only 10 counties in New Hampshire, I used zip codes for local data rather than counties.
All tests of significance are two-sided t-tests with a 95 % CI.
Because there are only 45 of the most strictly regulated facilities (LQGs) and only 21 large facilities (i.e., with more than 250 employees), the analysis does not include separate samples for these facilities.
In calculating the percentage, the facility itself is excluded from both the numerator (where relevant) and denominator.
Using facility name and location I looked each facility up in the Factiva and Hoovers databases to determine if the facility was part of a publicly-traded firm.
Some readers may be concerned that these results stem from using demographic data at the zip code level rather than some other level. Since there are only 10 counties in New Hampshire I felt that zip code data was preferable to county data. (Note in computing the Neighbor Past Inspections I had to use data at the county level given that many zipcodes have only one facility and thus I could not calculate this variable at the zip code level.) I considered using census tract data, but I could only identify latitude/longitude locations for about 90 % of the facilities. However when I run the regressions with census tract data for the more limited samples, I get the same general qualitative results for Population Density, Percent Urban, and Median Income.
Since the treatment model includes the predictor \(\rho \) from the first-stage equation which is a non-linear function of the variables in the selection equation, the second-stage model should be identified through functional form as long as the errors of the treatment equation are normally distributed (Greene 2003). However, I prefer to use an instrumental variables approach, but do note that the same results hold when I run the analysis without the exclusion restriction.
Although Population Density meets the technical requirements for an instrumental variable, i.e. it is highly significant in the EMS Adoption equation and is not significant in any of the compliance regressions, theoretically there is no clear reason why it should have an effect on EMS adoption and not compliance behavior. Thus I chose to use Neighbor Past Inspections as the instrumental variable.
Since Compliance Score is a count variable, ideally I would use a Poisson treatment model. However the full model as presented in Table 4 would not converge so I chose to present the linear treatment effects model. Given that the treatment effects model cannot reject the assumption of exogeneity, I also ran a poisson regression (without treatment effects) for the compliance regression for each sample and got qualitatively similar results which are available from the author upon request.
Recall that in the treatment effects regression, the null hypothesis that EMS Adoption is exogenous could not be rejected. Moreover, the null hypothesis is only rejected in one of the bivariate probit regressions—Best Practices for All Facilities.
Some best practices are officially required by the regulations while others are primarily a proxy for positive compliance behavior.
References
Anton, W. R., George Deltas, Q., & Khanna, M. (2004). Incentives for environmental self-regulation and implications for environmental performance. Journal of Environmental Economics and Management, 48, 632–665.
Arimura, T. H., Hibiki, A., & Katayama, H. (2008). Is a voluntary approach an effective environmental policy instrument? A case for environmental management systems. Journal of Environmental Economics and Management, 55, 281–295.
Barla, P. (2007). ISO 14001 certification and environmental performance in Quebec’s pulp and paper industry. Journal of Environmental Economics and Management, 53, 291–306.
Blackman, A. (2012). Does eco-certification boost regulatory compliance in developing countries? ISO 14001 in Mexico. Journal of Regulatory Economics, 42, 242–263.
Borck, J. C., & Coglianese, C. (2009). Voluntary environmental programs: Assessing their effectiveness. Annual Review of Environment and Resources, 34, 305–324.
Darnall, N., & Edwards, D. (2006). Predicting the cost of environmental management system adoption: The role of capabilities, resources and ownership structure. Strategic Management Journal, 27, 301–320.
Darnall, N., & Kim, Y. (2012). Which types of environmental management systems are related to greater environmental improvements? Public Administration Review, 72, 351–365.
Dasgupta, S., Hettige, H., & Wheeler, D. (2000). What improves environmental compliance? Evidence from Mexican industry. Journal of Environmental Economics and Management, 39, 39–66.
Ferron Vílchez, V., & Darnall, N. (2015). Two are better than one: The link between management systems and business performance. Business Strategy and the Environment. doi:10.1002/bse.1864
Greene, W. H. (2003). Econometric analysis (3rd ed.). New York: Prentice-Hall.
Henriques, I., & Sadorsky, P. (1996). The determinants of an environmentally responsive firm: An empirical approach. Journal of Environmental Economics and Management, 30, 381–395.
Hillary, R. (2004). Environmental management systems and the smaller enterprise. Journal of Cleaner Production, 12, 561–569.
Khanna, M., & Anton, W. R. (2002). Corporate environmental management: Regulatory and market-based incentives. Land Economics, 78, 539–558.
Low, H. H., Tan, O. K., Choi, S. L., & Rabeatul Husna, A. R. (2015). The adoption of environmental management system in Malaysia’s manufacturing organizations. Journal of Economics, Business and Management, 3, 93–97.
McKeiver, K., & Gadenne, D. (2005). Environmental management systems in small and medium businesses. International Small Business Journal, 23, 513–537.
Prakash, A., & Potoski, M. (2012). Voluntary environmental programs: A comparative perspective. Journal of Policy Analysis and Management, 31, 123–138.
Potoski, M., & Prakash, A. (2005a). Green clubs and voluntary governance: ISO 14001 and firms’ regulatory compliance. American Journal of Political Science, 49, 235–248.
Potoski, M., & Prakash, A. (2005b). Covenants with weak swords: ISO 14001 and facilities’ environmental performance. Journal of Policy Analysis and Management, 24, 745–769.
Stafford, S. L. (2007). Can consumers enforce environmental regulations? The role of the market in hazardous waste compliance. Journal of Regulatory Economics, 31, 83–107.
Stafford, S. L. (2012). Do ’Carrots’ Work? Examining the effectiveness of EPA’s compliance assistance program. Journal of Policy Analysis and Management, 31, 533–555.
Uchida, T., & Ferraro, P. J. (2007). Voluntary development of environmental management systems: motivations and regulatory implications. Journal of Regulatory Economics, 32, 37–65.
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Stafford, S.L. Environmental management systems and compliance at small and lightly regulated facilities: evidence from the New Hampshire hazardous waste program. J Regul Econ 49, 292–314 (2016). https://doi.org/10.1007/s11149-016-9296-4
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DOI: https://doi.org/10.1007/s11149-016-9296-4
Keywords
- Environmental regulation
- Voluntary environmental programs
- Environmental management systems
- Compliance
- Small business