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Estimating the Distribution of Welfare Effects Using Quantiles

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  • Stefan Hoderlein

    (Boston College)

  • Anne Vanhems

    (University of Toulouse)

Abstract

This paper proposes a framework to model empirically welfare effects that are associated with a price change in a population of heterogeneous consumers which is similar to Hausman and Newey (1995), but allows for more general forms of heterogeneity. Individual demands are characterized by a general model which is nonparametric in the regressors, as well as monotonic in unobserved heterogeneity. In this setup, we first provide and discuss conditions under which the heterogeneous welfare effects are identified, and establish constructive identification. We then propose a sample counterpart estimator, and analyze its large sample properties. For both identification and estimation, we distinguish between the cases when regressors are exogenous and when they are endogenous. Finally, we apply all concepts to measuring the heterogeneous effect of a chance of gasoline price using US consumer data and find very substantial differences in individual effects across quantiles.

Suggested Citation

  • Stefan Hoderlein & Anne Vanhems, 2013. "Estimating the Distribution of Welfare Effects Using Quantiles," Boston College Working Papers in Economics 893, Boston College Department of Economics, revised 01 Feb 2016.
    • Handle: RePEc:boc:bocoec:893
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    References listed on IDEAS

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    1. Laurens Cherchye & Bram De Rock & Frederic Vermeulen, 2007. "The Collective Model of Household Consumption: A Nonparametric Characterization," Econometrica, Econometric Society, vol. 75(2), pages 553-574, March.
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    Cited by:

    1. Sebastiaan Maes & Raghav Malhotra, 2023. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," Papers 2303.01231, arXiv.org, revised Nov 2023.
    2. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric Welfare and Demand Analysis with Unobserved Individual Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 100(2), pages 349-361, May.
    3. Cherchye, Laurens & Demuynck, Thomas & Rock, Bram De, 2019. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Journal of Econometrics, Elsevier, vol. 211(2), pages 483-506.
    4. Richard Blundell & Joel Horowitz & Matthias Parey, 2022. "Estimation of a Heterogeneous Demand Function with Berkson Errors," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 877-889, December.
    5. Michael Bates & Seolah Kim, 2019. "Estimating the Price Elasticity of Gasoline Demand in Correlated Random Coefficient Models with Endogeneity," Working Papers 202021, University of California at Riverside, Department of Economics, revised Jul 2020.
    6. Escanciano, Juan Carlos, 2023. "Irregular identification of structural models with nonparametric unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 106-127.
    7. Richard Blundell & Joel L. Horowitz & Matthias Parey, 2018. "Estimation of a nonseparable heterogenous demand function with shape restrictions and Berkson errors," CeMMAP working papers CWP67/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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