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The Effect of Uncertainty on Pollution Control Policy

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  • Athanassoglou, Stergios

Abstract

I study a class of differential games of pollution control with profit functions that are polynomial in the global pollution stock. Given an emissions path satisfying mild regularity conditions, a simple polynomial ambient transfer scheme is exhibited that induces it in Markov-perfect equilibrium (MPE). Proposed transfers are a polynomial function of the difference between actual and desired pollution levels; moreover, they are designed so that in MPE no tax or subsidy is ever levied. Their applicability under stochastic pollution dynamics is studied for a symmetric game of polluting oligopolists with linear demand. I discuss a quadratic scheme that induces agents to adopt Markovian emissions strategies that are stationary and linear-decreasing in total pollution. Total expected ambient transfers are always non-positive and increase linearly in volatility and the absolute value of the slope of the inverse demand function. However, if the regulator is interested in inducing a constant emissions strategy then, in expectation, transfers vanish.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 16898.

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Date of creation: Jul 2009
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Handle: RePEc:pra:mprapa:16898

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Related research

Keywords: differential games; stochastic dynamics; nonpoint source pollution; policy design;

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Cited by:
  1. Tsur, Yacov & de Gorter, Harry, 2012. "Dynamic regulation of nonpoint source pollution when the number of emitters is large," Discussion Papers 122124, Hebrew University of Jerusalem, Department of Agricultural Economics and Management.
  2. Stergios Athanassoglou & Glenn Sheriff & Tobias Siegfried & Woonghee Tim Huh, 2009. "Simple Mechanisms for Managing Complex Aquifers," NCEE Working Paper Series 200905, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Oct 2009.
  3. Ewald, Christian-Oliver & Wang, Wen-Kai, 2011. "Analytic solutions for infinite horizon stochastic optimal control problems via finite horizon approximation: A practical guide," Mathematical Social Sciences, Elsevier, vol. 61(3), pages 146-151, May.

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