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Do regulators overestimate the costs of regulation?

Published online by Cambridge University Press:  17 April 2015

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Abstract:

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It has occasionally been asserted that regulators typically overestimate the costs of the regulations they impose. A number of arguments have been proposed for why this might be the case. The most widely credited is that regulators fail sufficiently to appreciate the effects of innovation in reducing regulatory compliance costs. Most existing studies have found that regulators are more likely to over- than to underestimate costs. While it is difficult to develop summary statistics to aggregate the results of different studies of disparate industries, one such measure is the average of the ratio of ex ante estimates of compliance costs to ex post estimates of the same costs. This ratio is generally greater than one. In this paper I argue that neither the greater frequency of overestimates nor the fact that the average ratio of ex ante to ex post cost estimates is greater than one necessarily demonstrates that ex ante estimates are biased. There are several reasons to suppose that the distribution of compliance costs could be skewed, so that the median of the distribution would lie below the mean. It is not surprising, then, that most estimates would prove to be too high. Moreover, Jensen’s inequality implies that the expected ratio of ex ante to ex post compliance costs would be greater than one. I propose a regression-based test of the bias of ex ante compliance cost estimates, and cannot reject the hypothesis that estimates are unbiased. Failure to reject a hypothesis with limited and noisy data should not, of course, be interpreted as a strong argument to accept the hypothesis. Rather, this paper argues for the generation of more and better information. Despite the existence of a number of papers reporting ex ante and ex post compliance cost estimates, it is surprisingly difficult to get a large sample with which to make such comparisons.

Type
Research Article
Copyright
Copyright © Society for Benefit-Cost Analysis 2014

References

Anderson, J. F., & Sherwood, T. (2002). Comparison of EPA and Other Estimates of Mobile Source Rule Costs to Actual Price Changes. Paper presented at the SAE Government Industry Meeting, Washington, DC, May 14, 2002.Google Scholar
Bailey, Peter D., Haq, , Gary, , & Goudson, , Andy, . (2002). Mind the gap! Comparing ex ante and ex post assessments of the costs of complying with environmental regulation. European Environment, 12(5), 245256.Google Scholar
Dale, Larry, Antinori, , Camille, , McNeil, , Michael, , McMahon, James E., & Fujita, K. Sydny. (2009). Retrospective evaluation of appliance price trends. Energy Policy, 37(2), 597605.CrossRefGoogle Scholar
Goodstein, Eban, & Hodges, , Hart, . (1997). Polluted data: Overestimating environmental costs. American Prospect, 8(35), 6469.Google Scholar
Hahn, Robert, & Tetlock, , Paul, . (2008). Has economic analysis improved regulatory decisions? Journal of Economic Perspectives, 22(1), 6784.CrossRefGoogle Scholar
Harrington, Winston, Morgenstern, Richard D., & Nelson, , Peter, . (2000). On the accuracy of regulatory cost estimates. Journal of Policy Analysis and Management, 19(2), 297322.3.0.CO;2-X>CrossRefGoogle Scholar
Hausman, Jerry A. (2001). Mismeasured variables in econometric analysis: problems from the right and problems from the left. Journal of Economic Perspectives, 15(4), 5767.Google Scholar
Heinzerling, Lisa. (2002). Markets for arsenic. Georgetown Law Review, 90, 23112339.Google Scholar
Hodges, Hart. (1997). Falling prices: Cost of complying with environmental regulations almost always less than advertised. Economic Policy Institute Briefing Paper. Washington, DC: Economic Policy Institute.Google Scholar
Jantzen, J. (1989), Costs of Environmental Management, 1988 – 2010, 3 policy scenarios. Report for the Ministry of VROM, The Hague, 25 May 1989.Google Scholar
MacLeod, Michael, Moran, , Dominic, , Aresti, , Manuel Lago, , Harrington, , Winston, , & Morgenstern, , Richard, . (2006). Comparing the ex ante and ex post costs of complying with regulatory change. Final report to DEFRA. London: Department for Environment, Farms, and Rural Affairs.Google Scholar
National Research Council of the United States National Academies (NRC). (2011). Renewable Fuel Standards: Potential Economic and Environmental Effects of US Biofuel Policy. Washington, DC: National Academies Press.Google Scholar
Office of Management and Budget, Office of Information and Regulatory Affairs (OMB). (2005). Validating Regulatory Analysis: 2005 Report to Congress on the Costs and Benefits of Federal Regulations and Unfunded Mandates on State, Local, and Tribal Entities. Washington DC: Government Printing Office.Google Scholar
Office of Technology Assessment (OTA). (1995). Gauging Control Technology and Regulatory Impacts in Occupational Safety and Health: An Appraisal of OSHA’s Analytic Approach. OTA-ENV-635. Washington DC: Government Printing Office.Google Scholar
Oosterhuis, Frans (editor). (2006). Ex-post estimates of costs to business of EU environmental legislation. Report to European Commission DG Environment. Amsterdam: Institute for Environmental Studies, Vrije Universiteit.Google Scholar
Porter, Michael. (1991). America’s green strategy. Scientific American, 264(4), 96.Google Scholar
Putnam, Hayes, & Bartlett (PHB). (1980). “Comparisons of Estimated and Actual Pollution Control Capital Expenditures for Selected Industries,” Report Prepared for the Office of Planning and Evaluation, U.S. Environmental Protection Agency, Cambridge, Mass., (mimeo).Google Scholar
Radaelli, Claudio. (2005). What Does Regulatory Impact Assessment Mean in Europe? Washington: AEI-Brookings Joint Center for Regulatory Studies.Google Scholar
RIVM (2000), Techno 2000; Modellering van de daling van eenheidskosten van technologieën in de tijd. Rapportnummer 773008003, Bilthoven, April 2000.Google Scholar