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Heterogeneity and the Non-Parametric Analysis of Consumer Choice: Conditions for Invertibility

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  • Walter Beckert
  • Richard Blundell

Abstract

This paper considers structural non-parametric random utility models for continuous choice variables with unobserved heterogeneity. We provide sufficient conditions on random preferences to yield reduced-form systems of non-parametric stochastic demand functions that allow global invertibility between demands and non-separable unobserved heterogeneity. Invertibility is essential for global identification of structural consumer demand models, for the existence of well-specified probability models of choice and for the non-parametric analysis of revealed stochastic preference. We distinguish between new classes of models in which heterogeneity is separable and non-separable in the marginal rates of substitution, respectively. Copyright 2008, Wiley-Blackwell.

Suggested Citation

  • Walter Beckert & Richard Blundell, 2008. "Heterogeneity and the Non-Parametric Analysis of Consumer Choice: Conditions for Invertibility," Review of Economic Studies, Oxford University Press, vol. 75(4), pages 1069-1080.
  • Handle: RePEc:oup:restud:v:75:y:2008:i:4:p:1069-1080
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    File URL: http://hdl.handle.net/10.1111/j.1467-937X.2008.00500.x
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    References listed on IDEAS

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    1. Arthur Lewbel, 2001. "Demand Systems with and without Errors," American Economic Review, American Economic Association, vol. 91(3), pages 611-618, June.
    2. Brown, Bryan W & Walker, Mary Beth, 1989. "The Random Utility Hypothesis and Inference in Demand Systems," Econometrica, Econometric Society, vol. 57(4), pages 815-829, July.
    3. Rosa L. Matzkin, 2003. "Nonparametric Estimation of Nonadditive Random Functions," Econometrica, Econometric Society, vol. 71(5), pages 1339-1375, September.
    4. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    5. 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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    Citations

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    Cited by:

    1. Steven Berry & Amit Gandhi & Philip Haile, 2013. "Connected Substitutes and Invertibility of Demand," Econometrica, Econometric Society, vol. 81(5), pages 2087-2111, September.
    2. NAKABAYASHI Jun & HIROSE Yohsuke, 2016. "Structural Estimation of the Scoring Auction Model," Discussion papers 16008, Research Institute of Economy, Trade and Industry (RIETI).
    3. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    4. repec:ucp:jpolec:doi:10.1086/692808 is not listed on IDEAS
    5. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    6. Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014. "Bounding quantile demand functions using revealed preference inequalities," Journal of Econometrics, Elsevier, vol. 179(2), pages 112-127.
    7. Arthur Lewbel & Krishna Pendakur, 2017. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Journal of Political Economy, University of Chicago Press, vol. 125(4), pages 1100-1148.
    8. Andreas Chai & Christian Kiedaisch & Nicholas Rohde, 2017. "The saturation of spending diversity and the truth about Mr Brown and Mrs Jones," Discussion Papers in Economics economics:201701, Griffith University, Department of Accounting, Finance and Economics.
    9. Walter Beckert, 2007. "Specification and Identification of Stochastic Demand Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(6), pages 669-683.
    10. repec:spr:etbull:v:3:y:2015:i:2:d:10.1007_s40505-014-0061-5 is not listed on IDEAS
    11. Sher, Itai & Kim, Kyoo il, 2014. "Identifying combinatorial valuations from aggregate demand," Journal of Economic Theory, Elsevier, vol. 153(C), pages 428-458.
    12. Andreas Chai & Nicholas Rohde & Jacques Silber, 2015. "Measuring The Diversity Of Household Spending Patterns," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 423-440, July.
    13. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers CWP60/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Laurens Cherchye & Bram De Rock & Thomas Demuynck, 2017. "Bounding Counterfactual Demand with Unobserved Heterogeneity and Endogenous Expenditures," Working Papers ECARES ECARES 2017-41, ULB -- Universite Libre de Bruxelles.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D1 - Microeconomics - - Household Behavior

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