Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing

Bart Smeulders, Laurens Cherchye, Bram De Rock

Econometrica · 2021 · Volume 89 · Issue 1

Abstract

Kitamura and Stoye (2018) recently proposed a nonparametric statistical test for random utility models of consumer behavior. The test is formulated in terms of linear inequality constraints and a quadratic objective function. While the nonparametric test is conceptually appealing, its practical implementation is computationally challenging. In this paper, we develop a column generation approach to operationalize the test. These novel computational tools generate considerable computational gains in practice, which substantially increases the empirical usefulness of Kitamura and Stoye's statistical test.

Keywords

Random utility model, revealed preferences, column generation approach

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