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Pessimistic optimal choice for risk-averse agents

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  • Paolo Vitale Author-Name-First Paolo

    (Department of Economics, Gabriele D'Annunzio University of Chieti and Pescara)

Abstract

We propose a general framework for the analysis of dynamic optimization with risk- averse agents, extending WhittleÕs (Whittle, 1990) formulation of risk-sensitive optimal control problems to accommodate time-discounting. We show how, within a Markovian set-up, optimal risk-averse behavior is identified via a pessimistic choice mechanism and described by simple recursive formulae. We apply this methodology to two distinct problems formulated respectively in discrete- and continuous-time. In the former, we extend SvennsonÕs (Svennson, 1997) analysis of optimal monetary policy, showing that with a risk-averse central bank the inflation forecast is not longer an explicit intermediate target, the monetary authorities do not expect the inflation rate to mean revert to its target level and apply a more aggressive Taylor rule than under risk-neutrality, while the inflation rate is less volatile. In the latter, we investigate the optimal production policy of a monopolist which faces a demand schedule subject to stochastic shocks, once again showing that risk-aversion induces her to act more aggressively.

Suggested Citation

  • Paolo Vitale Author-Name-First Paolo, 2013. "Pessimistic optimal choice for risk-averse agents," Working Papers CASMEF 1306, Dipartimento di Economia e Finanza, LUISS Guido Carli.
    • Handle: RePEc:lui:casmef:1306
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    References listed on IDEAS

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    1. Vitale, Paolo, 2012. "Risk-averse insider trading in multi-asset sequential auction markets," Economics Letters, Elsevier, vol. 117(3), pages 673-675.
    2. TallariniJr., Thomas D., 2000. "Risk-sensitive real business cycles," Journal of Monetary Economics, Elsevier, vol. 45(3), pages 507-532, June.
    3. van der Ploeg, Frederick, 2009. "Prudent monetary policy and prediction of the output gap," Journal of Macroeconomics, Elsevier, vol. 31(2), pages 217-230, June.
    4. Lars Peter Hansen & Thomas J Sargent, 2014. "Robust Permanent Income and Pricing," World Scientific Book Chapters, in: UNCERTAINTY WITHIN ECONOMIC MODELS, chapter 3, pages 33-81, World Scientific Publishing Co. Pte. Ltd..
    5. Holden, Craig W. & Subrahmanyam, Avanidhar, 1994. "Risk aversion, imperfect competition, and long-lived information," Economics Letters, Elsevier, vol. 44(1-2), pages 181-190.
    6. Hong Zhang, 2004. "Dynamic Beta, Time-Varying Risk Premium, and Momentum," Yale School of Management Working Papers amz2637, Yale School of Management, revised 01 Mar 2005.
    7. Yulei Luo & Eric R. Young, 2010. "Risk-Sensitive Consumption and Savings under Rational Inattention," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(4), pages 281-325, October.
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    Cited by:

    1. Edilio Valentini & Paolo Vitale, 2019. "Optimal Climate Policy for a Pessimistic Social Planner," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(2), pages 411-443, February.

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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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