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Articles

No. 17 (2008)

Learning and Information on Preference Parameters

  • Miguel Ángel Sámano Rodríguez
  • Francisco Venegas-Martínez
DOI:
https://doi.org/10.29201/85k9bb87
Published
March 28, 2008

Abstract

This paper uses a Bayesian learning model to measure the amount of information that an individual gains on his/her utility function after consuming an initial amount of a generic good. To do so, a learning model on the parameters determining the preferences of a rational individual is developed. In this framework, Fisher´s information (1950) is used to measure the amount of information containes in the parameters of the agent's satisfaction index once consumption has startes. by using Fisher's information and Jeffreys´ rule (1961) a priori distribution on the parameters is constructed, which allows to treat information as a variable.

References

  1. Aghion, H. and J. Aghion (1991). "Optimal Learning by Experimentation", Review of Economic Studies, num. 58, pp. 621-654.

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