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


  • Bram De Rock
  • Laurens Cherchye
  • Bart Smeulders


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 note, we develop a column generation approach to operationalize the test. We show that these novel computational tools generate considerable computational gains in practice, which substantially increases the empirical usefulness of Kitamura and Stoye’s statistical test.

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  • Bram De Rock & Laurens Cherchye & Bart Smeulders, 2019. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Working Papers ECARES 2019-19, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:eca:wpaper:2013/292215

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    References listed on IDEAS

    1. Rahul Deb & Yuichi Kitamura & John K.-H. Quah & Jorg Stoye, 2017. "Revealed Price Preference: Theory and Stochastic Testing," Cowles Foundation Discussion Papers 2087, Cowles Foundation for Research in Economics, Yale University.
    2. Stefan Hoderlein & Jörg Stoye, 2014. "Revealed Preferences in a Heterogeneous Population," The Review of Economics and Statistics, MIT Press, vol. 96(2), pages 197-213, May.
    3. Yuichi Kitamura & Jörg Stoye, 2018. "Nonparametric Analysis of Random Utility Models," Econometrica, Econometric Society, vol. 86(6), pages 1883-1909, November.
    4. Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350,, revised May 2019.
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    computational tools; statistical testing;

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