Environmental and Resource Economics

, Volume 59, Issue 1, pp 111–135 | Cite as

Environmental Regulations, Producer Responses, and Secondary Benefits: Carbon Dioxide Reductions Under the Acid Rain Program

Article

Abstract

This paper derives a production analysis framework for modeling secondary benefits from environmental regulation, i.e. induced changes in yet unregulated pollutants. We emphasize the various ways in which the producers can respond to environmental regulations, and evaluate them in terms of their costs and their generation of secondary benefits. An application on the US electricity sector illustrates our main point: In our case, abatement technologies that reduce regulated emissions while leaving the plants’ unregulated emissions unchanged appear to be among the least costly producer responses to the existing sulfur and nitrogen regulations, but at the expense of limited secondary reductions in carbon dioxide emissions. This finding raises questions about the magnitude of the much debated secondary benefits from future regulations on carbon dioxide emissions, since similar abatement technologies are currently being developed for carbon dioxide. With new environmental issues emerging over time, our findings suggest that regulators should signal the possibilities of new regulations on connected pollutants to producers. Such information may be relevant for producers when choosing current abatement strategies—with minor cost increases to deal with today’s issues, overall compliance costs for near-future environmental problems may be lowered.

Keywords

Abatement costs Data envelopment analysis Environmental regulation Materials balance Multiple pollutants Secondary benefits 

References

  1. Aigner DJ, Lovell CAK, Schmidt P (1977) Formulation and estimation of stochastic frontier production function models. J Econom 6:21–37Google Scholar
  2. Arrow KJ, Fisher AC (1974) Environmental preservation, uncertainty, and irreversibility. Q J Econ 88:312–319Google Scholar
  3. Ayres RU, Kneese AV (1969) Production, consumption, and externalities. Am Econ Rev 59:282–297Google Scholar
  4. Ayres RU, Walter J (1991) The greenhouse effect: damages, costs and abatement. Environ Resour Econ 1:237–270Google Scholar
  5. Baumgärtner S, Arons JS (2003) Necessity and inefficiency in the generation of waste. J Ind Ecol 7:113–123Google Scholar
  6. Brännlund R, Färe R, Grosskopf S (1995) Environmental regulation and profitability: an application to Swedish pulp and paper mills. Environ Resour Econ 6:23–36Google Scholar
  7. Burtraw D, Krupnick A, Palmer K et al (2003) Ancillary benefits of reduced air pollution in the US from moderate greenhouse gas mitigation policies in the electricity sector. J Environ Econ Manage 45:650–673Google Scholar
  8. Chambers RG (1988) Applied production analysis: a dual approach. Cambridge University Press, CambridgeGoogle Scholar
  9. Cline W (1992) The economics of global warming. Institute for International Economics, Washington, DCGoogle Scholar
  10. Coelli T, Lauwers L, Van Huylenbroeck G (2007) Environmental efficiency measurement and the materials balance condition. J Prod Anal 28:3–12Google Scholar
  11. Coggins JS, Swinton JR (1996) The price of pollution: a dual approach to valuing \(\text{ SO }_{2}\) allowances. J Environ Econ Manage 30:58–72Google Scholar
  12. Conrad JM (1980) Quasi-option value and the expected value of information. Q J Econ 94:813–820Google Scholar
  13. Ebert U, Welsch H (2007) Environmental emissions and production economics: implications of the materials balance. Am J Agric Econ 89:287–293Google Scholar
  14. Ekin P (1996) The secondary benefits of \(\text{ CO }_{2}\) abatement: how much emission reduction do they justify? Ecol Econ 16:13–24Google Scholar
  15. Ellerman A D (2003) Lessons from phase 2 compliance with the U.S. Acid Rain Program. MIT _CEEPR, MIT Center for Energy and Environmental Policy ResearchGoogle Scholar
  16. EPA (2011) Clean air interstate rule, Acid Rain Program, and former \(\text{ NO }_{{\rm x}}\) budget trading program 2010 progress report. U.S. Environmental Protection AgencyGoogle Scholar
  17. Färe R, Grosskopf S, Lovell CAK et al (1989) Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. Rev Econ Stat 71:90–98Google Scholar
  18. Färe R, Grosskopf S, Lee H (1990) A nonparametric approach to expenditure-constrained profit maximization. Am J Agric Econ 72:574–581Google Scholar
  19. Färe R, Grosskopf S, Noh D-W et al (2005) Characteristics of a polluting technology: theory and practice. J Econom 126:469–492Google Scholar
  20. Färe R, Grosskopf S, Pasurka CA (2007) Pollution abatement activities and traditional productivity. Ecol Econ 62:673–682Google Scholar
  21. Färe R, Grosskopf S, Pasurka CA et al (2012) Substitutability among undesirable outputs. Appl Econ 44:39–47Google Scholar
  22. Farrell A, Carter R, Raufer R (1999) The NOx Budget: market-based control of tropospheric ozone in the northeastern United States. Resour Energy Econ 21:103–124Google Scholar
  23. Førsund FR, Strøm S (1988) Environmental economics and management: pollution and natural resources. Croom Helm, LondonGoogle Scholar
  24. Førsund FR (2009) Good modelling of bad outputs: pollution and multiple-output production. Int Rev Environ Resour Econ 3:1–38Google Scholar
  25. Frisch R (1965) Theory of production. Reidel, DordrechtGoogle Scholar
  26. Henry C (1974) Investment decisions under uncertainty: the “irreversibility effect”. Am Econ Rev 64:1006–1012Google Scholar
  27. Kohli U (1983) Non-joint technologies. Rev Econ Stud 50:209–219Google Scholar
  28. Kolstad CD (2000) Environmental economics. Oxford University Press, New YorkGoogle Scholar
  29. Kuosmanen T (2006) Stochastic nonparametric envelopment of data: combining virtues of SFA and DEA in a unified framework. MTT discussion paper, Agrifood Research FinlandGoogle Scholar
  30. Kuosmanen T (2005) Weak disposability in nonparametric production analysis with undesirable outputs. Am J Agric Econ 87:1077–1082Google Scholar
  31. Kuosmanen T (2008) Representation theorem for convex nonparametric least squares. Econom J 11:308–325Google Scholar
  32. Kuosmanen T (2009) Data envelopment analysis with missing data. J Oper Res Soc 60:1767–1774Google Scholar
  33. Kuosmanen T, Laukkanen M (2011) (In)efficient environmental policy with interacting pollutants. Environ Resour Econ 48:629–649Google Scholar
  34. Kuosmanen T, Kortelainen M (2012) Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints. J Prod Anal 38:11–28Google Scholar
  35. Kydland FE, Prescott EC (1977) Rules rather than discretion: the inconsistency of optimal plans. J Polit Econ 85:473–491Google Scholar
  36. Lauwers L (2009) Justifying the incorporation of the materials balance principle into frontier-based eco-efficiency models. Ecol Econ 68:1605–1614Google Scholar
  37. Lee H, Chambers RG (1986) Expenditure constraints and profit maximization in U.S. agriculture. Am J Agric Econ 68:857–865Google Scholar
  38. Lee M (2005) The shadow price of substitutable sulfur in the US electric power plant: a distance function approach. J Environ Manage 77:104–110Google Scholar
  39. Meeusen W, van den Broeck J (1977) Efficiency estimation from Cobb–Douglas production functions with composed error. Int Econ Rev 18:435–444Google Scholar
  40. Mekaroonreung M, Johnson AL (2012) Estimating the shadow prices of \(\text{ SO }_{2}\) and \(\text{ NO }_{{\rm x}}\) for U.S. coal power plants: a convex nonparametric least squares approach. Energy Econ 34:723–732Google Scholar
  41. Mekaroonreung M, Johnson A L (2012) Imposing conservation of mass in abatement function estimates: \(\text{ NO }_{{\rm x}}\) generation in coal-fired power plants. working paper, Texas A &M UniversityGoogle Scholar
  42. Murty S, Russell RR, Levkoff SB (2012) On modeling pollution-generating technologies. J Environ Econ Manage 64:117–135Google Scholar
  43. Nordhaus WD (1991) To slow or not to slow: the economics of the greenhouse effect. Econ J 101:920–937Google Scholar
  44. Pasurka CA (2006) Decomposing electric power plant emissions within a joint production framework. Energy Econ 28:26–43Google Scholar
  45. Pethig R (2003) The “materials balance” approach to pollution: its origin, implications and acceptance. Economics Discussion Paper, University of SiegenGoogle Scholar
  46. Pethig R (2006) Non-linear production, abatement, pollution and materials balance reconsidered. J Environ Econ Manage 51:185–204Google Scholar
  47. Riahi K, Rubin ES, Taylor MR et al (2004) Technological learning for carbon capture and sequestration technologies. Energy Econ 26:539–564Google Scholar
  48. Rødseth KL (2011) Treatment of undesirable outputs in production analysis: desirable modeling strategies and applications Dissertation, Norwegian University of Life SciencesGoogle Scholar
  49. Rødseth KL (2013) Capturing the least costly way of reducing pollution: a shadow price approach. Ecol Econ 92:16–24Google Scholar
  50. Shephard RW (1974) Indirect production functions. Anton Hain, Meisenhaven am GlanGoogle Scholar
  51. Shephard RW (1970) Theory of cost and production functions. Princeton University Press, PrincetonGoogle Scholar
  52. Shephard RW, Färe R (1974) The law of diminishing returns. Z Nationalokonomie 34:69–90Google Scholar
  53. Stern NH (2007) The economics of climate change: the Stern review. Cambridge University Press, CambridgeGoogle Scholar
  54. Swift B (2001) How environmental law works: an analysis of the utility sector’s response to regulations of nitrogen oxides and sulfur dioxide under the Clean Air Act. Tulane Environ Law J 14:309–424Google Scholar
  55. Welch E, Barnum D (2009) Joint environmental and cost efficiency analysis of electricity generation. Ecol Econ 68:2336–2343Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.School of Economics and BusinessNorwegian University of Life SciencesOsloNorway
  2. 2.School of Economics and BusinessNorwegian University of Life SciencesÅsNorway

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