Testing Utility Maximization with Measurement Errors in the Data

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 approaches that can be used to derive non-parametric tests for utility maximization, which can account for measurement errors in observed price or quantity data