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Utility function estimation: The entropy approach

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  • Dionisio, Andreia
  • Reis, A. Heitor
  • Coelho, Luis

Abstract

The maximum entropy principle can be used to assign utility values when only partial information is available about the decision maker’s preferences. In order to obtain such utility values it is necessary to establish an analogy between probability and utility through the notion of a utility density function. In this paper we explore the maximum entropy principle to estimate the utility function of a risk averse decision maker.

Suggested Citation

  • Dionisio, Andreia & Reis, A. Heitor & Coelho, Luis, 2008. "Utility function estimation: The entropy approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3862-3867.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:15:p:3862-3867
    DOI: 10.1016/j.physa.2008.02.072
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    References listed on IDEAS

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    1. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
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    Cited by:

    1. A. B. Leoneti & G. A. Prataviera, 2020. "Entropy-Norm space for geometric selection of strict Nash equilibria in n-person games," Papers 2003.09225, arXiv.org.
    2. Leoneti, A.B. & Prataviera, G.A., 2020. "Entropy-norm space for geometric selection of strict Nash equilibria in n-person games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 546(C).
    3. Luca Zanin, 2021. "On the estimation of Okun’s coefficient in some countries in Latin America: a comparison between OLS and GME estimators," Empirical Economics, Springer, vol. 60(3), pages 1575-1592, March.

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