Title: An application of general maximum entropy to utility
Authors: Paulo Ferreira; Andreia Dionísio
Addresses: Center for Advanced Studies in Management and Economics, University of Évora (CEFAGE-UE), Largo dos Colegiais, 2, 7000 Évora, Portugal; Agrarian Superior School of Elvas, Edifício do Trem Alto, Avenida 14 de Janeiro, 7350-903 Elvas, Portugal ' Center for Advanced Studies in Management and Economics, University of Évora (CEFAGE-UE), Largo dos Colegiais, 2, 7000 Évora, Portugal
Abstract: Methodologies related to information theory have been increasingly used in studies in economics and management. In this paper, we use generalised maximum entropy as an alternative to ordinary least squares in the estimation of utility functions. Generalised maximum entropy has some advantages: it does not need such restrictive assumptions and could be used with both well and ill-posed problems, for example, when we have small samples, which is the case when estimating utility functions. Using linear, logarithmic and power utility functions, we estimate those functions and confidence intervals and perform hypothesis tests. Results point to the greater accuracy of generalised maximum entropy, showing its efficiency in estimation.
Keywords: generalised maximum entropy; GME; linear function; utility functions; power function; logarithmic function; decision theory; utility function estimation.
International Journal of Applied Decision Sciences, 2013 Vol.6 No.3, pp.228 - 244
Received: 22 Jun 2012
Accepted: 14 Jan 2013
Published online: 28 Nov 2013 *