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Revealed price preference: theory and empirical analysis

Author

Listed:
  • Rahul Deb

    (Institute for Fiscal Studies)

  • Yuichi Kitamura

    (Institute for Fiscal Studies and Yale University)

  • John Quah

    (Institute for Fiscal Studies)

  • Jorg Stoye

    (Institute for Fiscal Studies and Cornell University)

Abstract

With the aim of determining the welfare implications of price change in consumption data, we introduce a revealed preference relation over prices. We show that an absence of cycles in this preference relation characterizes a model of demand where consumers trade-off the utility of consumption against the disutility of expenditure. This model is appropriate whenever a consumer’s demand over a strict subset of all available goods is being analyzed. For the random utility extension of the model, we devise nonparametric statistical procedures for testing and welfare comparisons. The latter requires the development of novel tests of linear hypotheses for partially identified parameters. In doing so, we provide new algorithms for the calculation and statistical inference in nonparametric counterfactual analysis for a general partially identified model. Our applications on national household expenditure data provide support for the model and yield informative bounds concerning welfare rankings across different prices.

Suggested Citation

  • Rahul Deb & Yuichi Kitamura & John Quah & Jorg Stoye, 2018. "Revealed price preference: theory and empirical analysis," CeMMAP working papers CWP57/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:57/18
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    References listed on IDEAS

    as
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    Cited by:

    1. Roy Allen & Paweł Dziewulski & John Rehbeck, 2024. "Revealed statistical consumer theory," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 77(3), pages 823-847, May.
    2. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2023. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," Econometrica, Econometric Society, vol. 91(1), pages 107-146, January.
    3. Khushboo Surana, 2022. "How different are we? Identifying the degree of revealed preference heterogeneity," Discussion Papers 22/09, Department of Economics, University of York.
    4. Han, Sukjin & Yang, Shenshen, 2024. "A computational approach to identification of treatment effects for policy evaluation," Journal of Econometrics, Elsevier, vol. 240(1).
    5. Changkuk Im & John Rehbeck, 2021. "Non-rationalizable Individuals, Stochastic Rationalizability, and Sampling," Papers 2102.03436, arXiv.org, revised Oct 2021.
    6. Yuichi Kitamura & Jörg Stoye, 2018. "Nonparametric Analysis of Random Utility Models," Econometrica, Econometric Society, vol. 86(6), pages 1883-1909, November.
    7. John K. -H. Quah & Gerelt Tserenjigmid, 2022. "Price Heterogeneity as a source of Heterogenous Demand," Papers 2201.03784, arXiv.org, revised Jan 2022.
    8. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    9. Stoye, Jörg, 2019. "Revealed Stochastic Preference: A one-paragraph proof and generalization," Economics Letters, Elsevier, vol. 177(C), pages 66-68.
    10. Wilfried Youmbi, 2024. "Nonparametric Analysis of Random Utility Models Robust to Nontransitive Preferences," Papers 2406.13969, arXiv.org.
    11. Natalia Lazzati & John K.-H. Quah & Koji Shirai, 2018. "Nonparametric analysis of monotone choice," Discussion Paper Series 184, School of Economics, Kwansei Gakuin University.
    12. Daniele Caliari & Henrik Petri, 2024. "Irrational Random Utility Models," Papers 2403.10208, arXiv.org.

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