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Generalized Entropy and Model Uncertainty

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  • Alexander Meyer-Gohde

Abstract

I entertain a generalization of the standard Bolzmann-Gibbs-Shannon measure of entropy in multiplier preferences of model uncertainty. Using this measure, I derive a generalized exponential certainty equivalent, which nests the exponential certainty equivalent of the standard Hansen-Sargent model uncertainty formulation and the power certainty equivalent of the popular Epstein-Zin-Weil recursive preferences as special cases. Besides providing a model uncertainty rationale to these risk-sensitive preferences, the generalized exponential equivalent provides additional flexibility in modeling uncertainty through its introduction of pessimism into agents, causing them to overweight events made more likely in the worst case model when forming expectations. In a standard neoclassical growth model, I close the gap to the Hansen-Jagannathan bounds with plausible detection error probabilities using the generalized exponential equivalent and show that Hansen-Sargent and Epstein-Zin-Weil preferences yield comparable market prices of risk for given detection error probabilities.

Suggested Citation

  • Alexander Meyer-Gohde, 2017. "Generalized Entropy and Model Uncertainty," SFB 649 Discussion Papers SFB649DP2017-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2017-017
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    More about this item

    Keywords

    model uncertainty; robust control; recursive preferences; equity premium puzzle; Tsallis entropy;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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