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Optimal Management with Potential Regime Shifts

Author

Listed:
  • Stephen Polasky

    (University of Minnesota)

  • Aart de Zeeuw

    (Tilburg University)

  • Florian Wagener

    (University of Amsterdam)

Abstract

This discussion paper led to a publication in 'Journal of Environmental Economics and Management' , 62(2), 229-40. We analyze how the threat of a potential future regime shift affects optimal management. We use a simple general growth model to analyze four cases that involve combinations of stock collapse versus changes in system dynamics, and exogenous versus endogenous probabilities of regime shift. Prior work has focused on stock collapse with endogenous probabilities and reaches ambiguous conclusions about the effect of potential regime shift on optimal management. We show that all other cases yield unambiguous results. In particular, with endogenous probability of regime shift that affects system dynamics the potential for regime shift causes optimal management to become precautionary.

Suggested Citation

  • Stephen Polasky & Aart de Zeeuw & Florian Wagener, 2010. "Optimal Management with Potential Regime Shifts," Tinbergen Institute Discussion Papers 10-111/1, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20100111
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    References listed on IDEAS

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    More about this item

    Keywords

    optimal management; growth; renewable resources; regime shift;
    All these keywords.

    JEL classification:

    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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