Testing utility maximization with measurement errors in the data

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.

Citation

Jones, B.E. and Edgerton, D.L. (2009), "Testing utility maximization with measurement errors in the data", Binner, J.M., Edgerton, D.L. and Elger, T. (Ed.) Measurement Error: Consequences, Applications and Solutions (Advances in Econometrics, Vol. 24), Emerald Group Publishing Limited, Leeds, pp. 199-236. https://doi.org/10.1108/S0731-9053(2009)0000024012