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The consequences of irreversibility on optimal intertemporal emission policies under uncertainty

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  • Thomas Dangl
  • Franz Wirl

Abstract

This paper investigates how irreversibility affects optimal intertemporal emission policies when negative stock externalities exist. In particular it discusses the effect of irreversible emission, i.e., it concerns the physical issue whether it is possible to recollect pollutants that have been emitted or not. We depict our analysis with the greenhouse effect as a topical example and model the uncertainty with respect to the future evolution of the world’s temperature (i.e., the uncertain factor that determines the costs) as Itô-process with the drift provided by current carbon-dioxide emissions. We show analytically that irreversibility affects the optimal emission policy only if the future impact of today’s emissions is uncertain. Under uncertainty, irreversibility leads to a conservationist policy such that emissions are reduced at any level of environmental concentration of the pollutant. The level where stopping emissions is optimal decreases in the presence of irreversibility. Furthermore, the expected duration of fossil fuel use is derived. A numerical example which is calibrated to roughly reflect the global CO 2 problem illustrates the analytical findings. Copyright Springer-Verlag 2007

Suggested Citation

  • Thomas Dangl & Franz Wirl, 2007. "The consequences of irreversibility on optimal intertemporal emission policies under uncertainty," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 15(2), pages 143-166, June.
  • Handle: RePEc:spr:cejnor:v:15:y:2007:i:2:p:143-166
    DOI: 10.1007/s10100-007-0023-1
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    Cited by:

    1. Marc Gronwald & Janina Ketterer, 2009. "Evaluating emissions trading as a policy instrument," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(11), pages 22-25, June.
    2. Chen, Hong & Long, Ruyin & Niu, Wenjing & Feng, Qun & Yang, Ranran, 2014. "How does individual low-carbon consumption behavior occur? – An analysis based on attitude process," Applied Energy, Elsevier, vol. 116(C), pages 376-386.
    3. Marc Gronwald & Janina Ketterer, 2009. "Evaluating Emission Trading as a Policy Tool - Evidence from Conditional Jump Models," CESifo Working Paper Series 2682, CESifo.

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    More about this item

    Keywords

    Optimal taxation; Optimal resource allocation; Q48; D81; C61;
    All these keywords.

    JEL classification:

    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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