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Optimal Acquisition of Pollution Control Equipment Under Uncertainty

Author

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  • Richard F. Hartl

    (Technische Universität Wien, Institute for Econometrics, Operations Research and Systems Theory, Argentinierstraße 8, A-1040 Wien, Austria)

Abstract

This paper considers a firm, which has to acquire a certain amount of pollution control equipment in order to comply with government pollution standards. Due to political battles and lobbying efforts, the compliance date and the date when it is announced are not known in advance. Furthermore, the target stock of pollution control equipment is also unknown. This amounts to an optimal control problem, in which the terminal time and the terminal state are random variables for which certain probability distributions can be estimated. The model explicitly considers technological progress in the production of abatement equipment, which leads to decreasing installation costs over time. Furthermore it is assumed that having a high stock of abatement equipment at early stages improves the firm's public image and thus its revenue. Tax deductions and other benefits for health conscious firms are also taken into account. Using optimal control theory the optimal investment in pollution control equipment is obtained, and the sensitivity with respect to discounting, wear out, technological progress and with respect to the parameters of the probability distributions is investigated.

Suggested Citation

  • Richard F. Hartl, 1992. "Optimal Acquisition of Pollution Control Equipment Under Uncertainty," Management Science, INFORMS, vol. 38(5), pages 609-622, May.
    • Handle: RePEc:inm:ormnsc:v:38:y:1992:i:5:p:609-622
    DOI: 10.1287/mnsc.38.5.609
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    Citations

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    Cited by:

    1. Kort, P.M., 1992. "The Effects of Marketable Pollution Permits on the Firm's Optimal Investment Policies," Papers 9242, Tilburg - Center for Economic Research.
    2. Carmen Arguedas & Francisco Cabo & Guiomar Martín-Herrán, 2017. "Optimal Pollution Standards and Non-compliance in a Dynamic Framework," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(3), pages 537-567, November.
    3. Tommy Lundgren, 2003. "A Real Options Approach to Abatement Investments and Green Goodwill," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 25(1), pages 17-31, May.
    4. Wayne Fu & Basak Kalkanci & Ravi Subramanian, 2019. "Are Hazardous Substance Rankings Effective? An Empirical Investigation of Information Dissemination About the Relative Hazards of Chemicals and Emissions Reductions," Manufacturing & Service Operations Management, INFORMS, vol. 21(3), pages 602-619, July.
    5. Peter Kort & Maria Lavrutich & Cláudia Nunes & Carlos Oliveira, 2022. "Preventing Environmental Disasters in Investment under Uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 83(1), pages 199-220, September.
    6. Suresh P. Sethi & Sushil Gupta & Vipin K. Agrawal & Vijay K. Agrawal, 2022. "Nobel laureates’ contributions to and impacts on operations management," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4283-4303, December.
    7. Di Jin & Hauke Kite-Powell & James Broadus, 1994. "Dynamic economic analysis of marine pollution prevention technologies: An application to double hulls and electronic charts," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 4(6), pages 555-580, December.
    8. Arguedas, Carmen & Cabo, Francisco & Martín-Herrán, Guiomar, 2020. "Enforcing regulatory standards in stock pollution problems," Journal of Environmental Economics and Management, Elsevier, vol. 100(C).
    9. Batabyal, Amitrajeet A., 1995. "Leading issues in domestic environmental regulation: A review essay," Ecological Economics, Elsevier, vol. 12(1), pages 23-39, January.

    More about this item

    Keywords

    optimal control; pollution control;

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