Abstract
The principle of sustainable growth and development has influenced much of the environmental policies that have come into existence in the last three decades in the USA. Since the establishment of the U.S. Environment Protection Agency (EPA) in 1970, the regulations put in place have been increasingly stringent on the environmental standards they set over time. For instance, the Clean Air Act introduced in 1963 and the Clean Water Act founded in 1948 have been amended multiple times, each time tightening the control on the type and amount of emission allowed into the environment. This has no doubt accrued much benefit to the society within the USA in the form of reduced morbidity, increased recreational opportunity, cleaner living environment, increased ecosystem vitality, and possible increased land values (Palmer et al. 1995). Such outcomes are essential for an environmentally sustainable future and are also the cornerstone of a society that holds itself accountable to future generations. However, at the same time concerns have also been raised as to whether these benefits are worth the cost of such regulations. In addition to the direct costs of pollution abatement, proponents of this view have blamed stifled economic growth, decline of labor and capital productivity, as well as loss of jobs on such increasingly stringent environmental regulations.
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Notes
- 1.
Data Envelopment Analysis (DEA) was proposed by Farrell, M.J. 1957. “The Measurement of Productive Efficiency.” Journal of the Royal Statistical Society. Series A (General), 120(3), 253–90. and later operationalized by Charnes, A.; WW Cooper and E. Rhodes. 1978. “Measuring the Efficiency of DMU.” European Journal of Operational Research, 2(6), 429–44. Variable returns to scale to the estimation method was later added by Banker, R.D.; A. Charnes and W.W. Cooper. 1984. “Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis.” Management science, 1078–92.
- 2.
Environmental Regulations have been around since the 1940s but the bulk of regulations we see today such as The Clean Air Act and The Clean Water Act were introduced and enforced starting around 1970s when EPA was established. This brings the data used in this paper closer to the time when the costs of regulations started rising considerably making the study pertinent.
- 3.
The relationship between efficiency scores from the directional distance function approach and the Shephard’s distance function approach is \( {D}_0=\left(\frac{1}{1+{D}_0^d}\right) \) as presented in Färe, R. and S. Grosskopf. 2000. “Theory and Application of Directional Distance Functions.” Journal of Productivity Analysis, 13(2), 93–103.
- 4.
An analogous model can also be used for abated emissions but is not presented here for brevity. I leave it upon the reader to adjust the model here for such a purpose.
- 5.
To be precise, efficiency is measured as the ratio SX/MX but for ease, the distance from points θS and V to the frontier can be understood as the efficiency of these production points due to the common denominator VN and \( \theta S\overline{Z} \). Thus, the cost of regulation can be graphically interpreted as the difference between the distances of points θS and V to the frontier.
- 6.
Though θSW is larger than θSU in the construction above, this might not always be true in reality. The point here is in measuring efficiency towards a chosen direction that makes more sense rather than minimizing the efficiency loss out of regulation.
- 7.
I would like to thank John Haltiwanger for making his version of these data available to other researchers.
- 8.
While the analysis was conducted for both Paper and Oil Industries using abated PM, abated SO2, and solid waste emissions from the PACE survey, results, and summary statistics are only provided for emissions and abated PM for the pulp and paper mills. All omitted results and summary statistics are qualitatively very similar.
- 9.
For more information on SLIM-3 model, refer to Gray, W.B. and R.J. Shadbegian. 2004. “‘Optimal’pollution Abatement—Whose Benefits Matter, and How Much?” Journal of Environmental Economics and Management, 47(3), 510–34.
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Acknowledgments
I am very grateful to my advisor Wayne Gray for his continuous advice, support, and encouragement during this research. I am indebted to my committee members Junfu Zhang and Chih Ming Tan for providing valuable inputs. I also greatly benefitted from discussions with Wang Jin during the course of this research. Finally, I thank numerous conference and seminar participants for helpful comments and suggestions.
Disclaimer
Any opinions and conclusions expressed herein are those of the author and do not necessarily represent the views of the U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed.
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Sharma, S. (2016). Environmental Performance or Productivity Loss?. In: Zhang, J., Luna-Reyes, L., Pardo, T., Sayogo, D. (eds) Information, Models, and Sustainability. Public Administration and Information Technology, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-319-25439-5_3
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