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Title: Estimating utility functions using generalized maximum entropy
Authors: Pires, Cesaltina
Dionísio, Andreia
Coelho, Luís
Keywords: generalized maximum entropy
utility elicitation
Morgenstern utility
maximum entropy principle
Issue Date: 2013
Publisher: Taylor and Francic
Citation: Pires, C., A. Dionísio, L. Coelho (2013), "Estimating utility functions using GME", Journal of Applied Statistics, 40(1), 221-234.
Abstract: This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum entropy (GME), applied to data obtained by utility elicitation methods. Given the statistical advantages of this approach, we provide a comparison of the performance of the GME estimator with ordinary least square (OLS) in a real data small sample setup. The results confirm the ones obtained for small samples through Monte Carlo simulations. The difference between the two estimators is small and it decreases as the width of the parameter support vector increases. Moreover, the GME estimator is more precise than the OLS one. Overall, the results suggest that GME is an interesting alternative to OLS in the estimation of utility functions when data are generated by utility elicitation methods.
Type: article
Appears in Collections:GES - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
CEFAGE - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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