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Uncertainty over uncertainty in environmental policy adoption: Bayesian learning of unpredictable socioeconomic costs

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  • Basei, Matteo
  • Ferrari, Giorgio
  • Rodosthenous, Neofytos

Abstract

The socioeconomic impact of pollution naturally comes with uncertainty due to, e.g., current new technological developments in emissions' abatement or demographic changes. On top of that, the trend of the future costs of the environmental damage is unknown: Will global warming dominate or technological advancements prevail? The truth is that we do not know which scenario will be realised and the scientific debate is still open. This paper captures those two layers of uncertainty by developing a real-options-like model in which a decision maker aims at adopting a once-and-for-all costly reduction in the current emissions rate, when the stochastic dynamics of the socioeconomic costs of pollution are subject to Brownian shocks and the drift is an unobservable random variable. By keeping track of the actual evolution of the costs, the decision maker is able to learn the unknown drift and to form a posterior dynamic belief of its true value. The resulting decision maker's timing problem boils down to a truly two-dimensional optimal stopping problem which we address via probabilistic free-boundary methods and a state-space transformation. We completely characterise the solution by showing that the optimal timing for implementing the emissions reduction policy is the first time that the learning process has become “decisive” enough; that is, when it exceeds a time-dependent percentage. This is given in terms of an endogenously determined threshold function, which solves uniquely a nonlinear integral equation. We numerically illustrate our results, discuss the implications of the optimal policy and also perform comparative statics to understand the role of the relevant model's parameters in the optimal policy.

Suggested Citation

  • Basei, Matteo & Ferrari, Giorgio & Rodosthenous, Neofytos, 2024. "Uncertainty over uncertainty in environmental policy adoption: Bayesian learning of unpredictable socioeconomic costs," Journal of Economic Dynamics and Control, Elsevier, vol. 161(C).
  • Handle: RePEc:eee:dyncon:v:161:y:2024:i:c:s0165188924000332
    DOI: 10.1016/j.jedc.2024.104841
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    References listed on IDEAS

    as
    1. Jacob LaRiviere & David Kling & James N Sanchirico & Charles Sims & Michael Springborn, 2018. "The Treatment of Uncertainty and Learning in the Economics of Natural Resource and Environmental Management," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 92-112.
    2. Federico, Salvatore & Ferrari, Giorgio & Rodosthenous, Neofytos, 2021. "Two-Sided Singular Control of an Inventory with Unknown Demand Trend," Center for Mathematical Economics Working Papers 643, Center for Mathematical Economics, Bielefeld University.
    3. Nordhaus, William D, 1991. "To Slow or Not to Slow: The Economics of the Greenhouse Effect," Economic Journal, Royal Economic Society, vol. 101(407), pages 920-937, July.
    4. Nishimura, Kiyohiko G. & Ozaki, Hiroyuki, 2007. "Irreversible investment and Knightian uncertainty," Journal of Economic Theory, Elsevier, vol. 136(1), pages 668-694, September.
    5. Paul Embrechts & Marius Hofert, 2013. "A note on generalized inverses," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 423-432, June.
    6. Boucekkine, Raouf & Fabbri, Giorgio & Federico, Salvatore & Gozzi, Fausto, 2022. "A dynamic theory of spatial externalities," Games and Economic Behavior, Elsevier, vol. 132(C), pages 133-165.
    7. Goran Peskir, 2005. "A Change-of-Variable Formula with Local Time on Curves," Journal of Theoretical Probability, Springer, vol. 18(3), pages 499-535, July.
    8. Athanassoglou, Stergios & Xepapadeas, Anastasios, 2012. "Pollution control with uncertain stock dynamics: When, and how, to be precautious," Journal of Environmental Economics and Management, Elsevier, vol. 63(3), pages 304-320.
    9. Richard S J Tol, 2018. "The Economic Impacts of Climate Change," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 4-25.
    10. Pindyck, Robert S., 2000. "Irreversibilities and the timing of environmental policy," Resource and Energy Economics, Elsevier, vol. 22(3), pages 233-259, July.
    11. Thijssen, Jacco J.J. & Bregantini, Daniele, 2017. "Costly sequential experimentation and project valuation with an application to health technology assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 202-229.
    12. Pindyck, Robert S., 2002. "Optimal timing problems in environmental economics," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1677-1697, August.
    13. Sang-Hyun Kim, 2015. "Time to Come Clean? Disclosure and Inspection Policies for Green Production," Operations Research, INFORMS, vol. 63(1), pages 1-20, February.
    14. Dalby, Peder A.O. & Gillerhaugen, Gisle R. & Hagspiel, Verena & Leth-Olsen, Tord & Thijssen, Jacco J.J., 2018. "Green investment under policy uncertainty and Bayesian learning," Energy, Elsevier, vol. 161(C), pages 1262-1281.
    15. Lappi, Pauli, 2018. "Optimal clean-up of polluted sites," Resource and Energy Economics, Elsevier, vol. 54(C), pages 53-68.
    16. Tiziano Angelis, 2020. "Optimal dividends with partial information and stopping of a degenerate reflecting diffusion," Finance and Stochastics, Springer, vol. 24(1), pages 71-123, January.
    17. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    18. Robert McDonald & Daniel Siegel, 1986. "The Value of Waiting to Invest," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 101(4), pages 707-727.
    19. Murto, Pauli, 2007. "Timing of investment under technological and revenue-related uncertainties," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1473-1497, May.
    20. Myles R. Allen & David J. Frame & Chris Huntingford & Chris D. Jones & Jason A. Lowe & Malte Meinshausen & Nicolai Meinshausen, 2009. "Warming caused by cumulative carbon emissions towards the trillionth tonne," Nature, Nature, vol. 458(7242), pages 1163-1166, April.
    21. Youngsoo Kim & H. Dharma Kwon, 2022. "Investment in the common good: free rider effect and the stability of mixed strategy equilibria," Papers 2208.11217, arXiv.org.
    22. William D. Nordhaus, 2007. "A Review of the Stern Review on the Economics of Climate Change," Journal of Economic Literature, American Economic Association, vol. 45(3), pages 686-702, September.
    23. Paolo Falbo & Giorgio Ferrari & Giorgio Rizzini & Maren Diane Schmeck, 2021. "Optimal switch from a fossil-fueled to an electric vehicle," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1147-1178, December.
    24. Jean-Paul Décamps & Thomas Mariotti & Stéphane Villeneuve, 2005. "Investment Timing Under Incomplete Information," Mathematics of Operations Research, INFORMS, vol. 30(2), pages 472-500, May.
    25. Martin L. Weitzman, 2007. "A Review of the Stern Review on the Economics of Climate Change," Journal of Economic Literature, American Economic Association, vol. 45(3), pages 703-724, September.
    26. Goran Peskir, 2005. "On The American Option Problem," Mathematical Finance, Wiley Blackwell, vol. 15(1), pages 169-181, January.
    27. Tiziano De Angelis & Fabien Gensbittel & Stephane Villeneuve, 2021. "A Dynkin Game on Assets with Incomplete Information on the Return," Mathematics of Operations Research, INFORMS, vol. 46(1), pages 28-60, February.
    28. Flora, Maria & Tankov, Peter, 2023. "Green investment and asset stranding under transition scenario uncertainty," Energy Economics, Elsevier, vol. 124(C).
    29. Richard S. J. Tol, 2006. "The Stern Review of the Economics of Climate Change: A Comment," Energy & Environment, , vol. 17(6), pages 977-981, November.
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    1. Andrea Mazzon & Peter Tankov, 2024. "Optimal stopping and divestment timing under scenario ambiguity and learning," Papers 2408.09349, arXiv.org, revised Oct 2024.

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    More about this item

    Keywords

    Environmental policy; Partial observation; Real options; Optimal stopping; Free boundaries;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

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