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Testing utility maximization with measurement errors in the data

In: Measurement Error: Consequences, Applications and Solutions

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  • Barry E. Jones
  • David L. Edgerton

Abstract

Revealed preference axioms provide a simple way of testing data from consumers or firms for consistency with optimizing behavior. The resulting non-parametric tests are very attractive, since they do not require any ad hoc functional form assumptions. A weakness of such tests, however, is that they are non-stochastic. In this paper, we provide a detailed analysis of two non-parametric approaches that can be used to derive statistical tests for utility maximization, which account for random measurement errors in the observed data. These same approaches can also be used to derive tests for separability of the utility function.

Suggested Citation

  • Barry E. Jones & David L. Edgerton, 2009. "Testing utility maximization with measurement errors in the data," Advances in Econometrics, in: Measurement Error: Consequences, Applications and Solutions, pages 199-236, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-9053(2009)0000024012
    DOI: 10.1108/S0731-9053(2009)0000024012
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