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Environmental Regulation With Innovation And Learning: Rules Versus Discretion

  • Tarui, Nori
  • Polasky, Stephen

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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File URL: http://purl.umn.edu/21911
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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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  1. 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.
  2. Ulph, Alistair & Ulph, David, 1997. "Global Warming, Irreversibility and Learning," Economic Journal, Royal Economic Society, vol. 107(442), pages 636-50, May.
  3. Pindyck, Robert S., 2000. "Irreversibilities and the timing of environmental policy," Resource and Energy Economics, Elsevier, vol. 22(3), pages 233-259, July.
  4. 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.
  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. 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.
  7. Hoel, Michael & Karp, Larry, 2002. "Taxes versus quotas for a stock pollutant," Resource and Energy Economics, Elsevier, vol. 24(4), pages 367-384, November.
  8. Fischer, Carolyn & Parry, Ian W. H. & Pizer, William A., 2003. "Instrument choice for environmental protection when technological innovation is endogenous," Journal of Environmental Economics and Management, Elsevier, vol. 45(3), pages 523-545, May.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. Pizer, William & Newell, Richard, 1998. "Regulating Stock Externalities Under Uncertainty," Discussion Papers dp-99-10-rev, Resources For the Future.
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