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Environmental Regulation With Innovation And Learning: Rules Versus Discretion

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  • Tarui, Nori
  • Polasky, Stephen

Abstract

We analyze a model of environmental regulation with learning about environmental damages and endogenous choice of emissions abatement technology by a polluting firm. We compare environmental policy under discretion, in which policy is updated upon learning new information, versus under rules, in which policy is not updated. When investment in abatement technology is made prior to the resolution of uncertainty, neither discretion nor rules with either taxes or standards achieve an efficient solution. When there is little uncertainty, rules are superior to discretion because discretionary policy gives the firm an incentive to distort investment in order to influence future regulation. However, when uncertainty is large, discretion is superior to rules because it allows regulation to incorporate new information. Under discretionary policy, taxes are superior to standards regardless of the relative slopes of marginal costs and marginal damages.

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Bibliographic Info

Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2003 Annual meeting, July 27-30, Montreal, Canada with number 21911.

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Date of creation: 2003
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Handle: RePEc:ags:aaea03:21911

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Keywords: Environmental Economics and Policy;

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  1. Hoel, Michael & Karp, Larry, 2001. "Taxes versus Quotas for a Stock Pollutant," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt5fx9p7kf, Department of Agricultural & Resource Economics, UC Berkeley.
  2. Kolstad, Charles D., 1996. "Learning and Stock Effects in Environmental Regulation: The Case of Greenhouse Gas Emissions," Journal of Environmental Economics and Management, Elsevier, vol. 31(1), pages 1-18, July.
  3. Parry, Ian & Pizer, William & Fischer, Carolyn, 1998. "Instrument Choice for Environmental Protection When Technological Innovation is Endogenous," Discussion Papers dp-99-04, Resources For the Future.
  4. Pindyck, Robert S., 1998. "Irreversibilities and the timing of environmental policy," Working papers WP 4047-98., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  5. Tracy R. Lewis, 1996. "Protecting the Environment When Costs and Benefits Are Privately Known," RAND Journal of Economics, The RAND Corporation, vol. 27(4), pages 819-847, Winter.
  6. Newell, Richard G. & Pizer, William A., 2003. "Regulating stock externalities under uncertainty," Journal of Environmental Economics and Management, Elsevier, vol. 45(2, Supple), pages 416-432, March.
  7. Benford, Frank A., 1998. "On the Dynamics of the Regulation of Pollution: Incentive Compatible Regulation of a Persistent Pollutant," Journal of Environmental Economics and Management, Elsevier, vol. 36(1), pages 1-25, July.
  8. Ulph, Alistair & Ulph, David, 1997. "Global Warming, Irreversibility and Learning," Economic Journal, Royal Economic Society, vol. 107(442), pages 636-50, May.
  9. Kelly, David L. & Kolstad, Charles D., 1999. "Bayesian learning, growth, and pollution," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 491-518, February.
  10. Milliman, Scott R. & Prince, Raymond, 1989. "Firm incentives to promote technological change in pollution control," Journal of Environmental Economics and Management, Elsevier, vol. 17(3), pages 247-265, November.
  11. Karp, Larry & Zhang, Jiangfeng, 2006. "Regulation with anticipated learning about environmental damages," Journal of Environmental Economics and Management, Elsevier, vol. 51(3), pages 259-279, May.
  12. Kydland, Finn E & Prescott, Edward C, 1977. "Rules Rather Than Discretion: The Inconsistency of Optimal Plans," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 473-91, June.
  13. Moledina, Amyaz A. & Coggins, Jay S. & Polasky, Stephen & Costello, Christopher, 2003. "Dynamic environmental policy with strategic firms: prices versus quantities," Journal of Environmental Economics and Management, Elsevier, vol. 45(2, Supple), pages 356-376, March.
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