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Pollution Control in a Stochastic Environment

Author

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  • Thomas Wiedmer
  • Anthony C. Fisher
  • Urvashi Nahrain

Abstract

This paper sets up a model using stochastic dynamic programming to analyze pollution control decisions. Environmental decision making is characterized by both uncertainty and irreversibility: Uncertainty might be related to future costs and benefits of adopting a particular control policy. Irreversibility may arise when investments in abatement capital are irreversible, or when environmental damage becomes irreversible at a certain point in time. Under such circumstances, the question of the optimal timing of pollution control arises. This paper shows that: (1) Increases in the uncertainty of future control benefits lead to a lower current degree of pollution control if investment in control facilities is irreversible, (2) ignoring the possibility of new information in the future leads to a higher level of control than it is optimal, and (3) the possibility of a major catastrophe may result in a lower optimal degree of pollution control.

Suggested Citation

  • Thomas Wiedmer & Anthony C. Fisher & Urvashi Nahrain, 1996. "Pollution Control in a Stochastic Environment," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 132(IV), pages 575-590, December.
  • Handle: RePEc:ses:arsjes:1996-iv-4
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