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Nonparametric Counterfactuals in Random Utility Models

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  • Yuichi Kitamura
  • Jorg Stoye

Abstract

We bound features of counterfactual choices in the nonparametric random utility model of demand, i.e. if observable choices are repeated cross-sections and one allows for unrestricted, unobserved heterogeneity. In this setting, tight bounds are developed on counterfactual discrete choice probabilities and on the expectation and c.d.f. of (functionals of) counterfactual stochastic demand.

Suggested Citation

  • Yuichi Kitamura & Jorg Stoye, 2019. "Nonparametric Counterfactuals in Random Utility Models," Papers 1902.08350, arXiv.org, revised May 2019.
    • Handle: RePEc:arx:papers:1902.08350
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    File URL: http://arxiv.org/pdf/1902.08350
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    References listed on IDEAS

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    1. Bart Smeulders, 2018. "Column Generation Algorithms for Nonparametric Analysis of Random Utility Models," Papers 1812.01400, arXiv.org.
    2. Abi Adams, 2015. "Mutually consistent revealed preference bounds," IFS Working Papers W15/20, Institute for Fiscal Studies.
    3. Stoye, Jörg, 2019. "Revealed Stochastic Preference: A one-paragraph proof and generalization," Economics Letters, Elsevier, vol. 177(C), pages 66-68.
    4. Richard Blundell & Martin Browning & Ian Crawford, 2008. "Best Nonparametric Bounds on Demand Responses," Econometrica, Econometric Society, vol. 76(6), pages 1227-1262, November.
    5. Charles F. Manski, 2007. "Partial Identification Of Counterfactual Choice Probabilities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1393-1410, November.
    6. Jörg Stoye, 2010. "Partial identification of spread parameters," Quantitative Economics, Econometric Society, vol. 1(2), pages 323-357, November.
    7. Yuichi Kitamura & Jörg Stoye, 2013. "Nonparametric analysis of random utility models: testing," CeMMAP working papers 36/13, Institute for Fiscal Studies.
    8. Stefan Hoderlein & Jörg Stoye, 2015. "Testing stochastic rationality and predicting stochastic demand: the case of two goods," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 3(2), pages 313-328, October.
    9. Daniel McFadden, 2005. "Revealed stochastic preference: a synthesis," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 26(2), pages 245-264, August.
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    Cited by:

    1. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    2. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    3. Bart Smeulders & Laurens Cherchye & Bram De Rock, 2021. "Nonparametric Analysis of Random Utility Models: Computational Tools for Statistical Testing," Econometrica, Econometric Society, vol. 89(1), pages 437-455, January.

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