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An Escape Time Interpretation of Robust Control




This paper studies the problem of an agent who wants to prevent the state from exceeding a critical threshold. Even though the agent is presumed to know the model, the optimal policy is computed by solving a conventional robust control problem. That is, robustness is induced here by objectives rather than uncertainty, and so is an example of the duality between risk-sensitivity and robustness. However, here the agent only incurs costs upon escape to a critical region, not during ‘normal times’. We argue this is often a more realistic model of macroeconomic policymaking.

Suggested Citation

  • In-Koo Cho & Kenneth Kasa, 2013. "An Escape Time Interpretation of Robust Control," Discussion Papers dp13-07, Department of Economics, Simon Fraser University.
  • Handle: RePEc:sfu:sfudps:dp13-07

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    References listed on IDEAS

    1. Tomasz Strzalecki, 2011. "Axiomatic Foundations of Multiplier Preferences," Econometrica, Econometric Society, vol. 79(1), pages 47-73, January.
    2. Anderson, Evan W. & Hansen, Lars Peter & Sargent, Thomas J., 2012. "Small noise methods for risk-sensitive/robust economies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 468-500.
    3. Prajit K. Dutta & Roy Radner, 1999. "Profit Maximization and the Market Selection Hypothesis," Review of Economic Studies, Oxford University Press, vol. 66(4), pages 769-798.
    4. Miao, Jianjun & Wang, Neng, 2011. "Risk, uncertainty, and option exercise," Journal of Economic Dynamics and Control, Elsevier, vol. 35(4), pages 442-461, April.
    5. Kolyuzhnov, Dmitri & Bogomolova, Anna & Slobodyan, Sergey, 2014. "Escape dynamics: A continuous-time approximation," Journal of Economic Dynamics and Control, Elsevier, vol. 38(C), pages 161-183.
    6. Pascal J. Maenhout, 2004. "Robust Portfolio Rules and Asset Pricing," Review of Financial Studies, Society for Financial Studies, vol. 17(4), pages 951-983.
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    More about this item


    robust control; large deviations;

    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

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