IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2010.13937.html
   My bibliography  Save this paper

Consumer Theory with Non-Parametric Taste Uncertainty and Individual Heterogeneity

Author

Listed:
  • Christopher Dobronyi
  • Christian Gouri'eroux

Abstract

We introduce two models of non-parametric random utility for demand systems: the stochastic absolute risk aversion (SARA) model, and the stochastic safety-first (SSF) model. In each model, individual-level heterogeneity is characterized by a distribution $\pi\in\Pi$ of taste parameters, and heterogeneity across consumers is introduced using a distribution $F$ over the distributions in $\Pi$. Demand is non-separable and heterogeneity is infinite-dimensional. Both models admit corner solutions. We consider two frameworks for estimation: a Bayesian framework in which $F$ is known, and a hyperparametric (or empirical Bayesian) framework in which $F$ is a member of a known parametric family. Our methods are illustrated by an application to a large U.S. panel of scanner data on alcohol consumption.

Suggested Citation

  • Christopher Dobronyi & Christian Gouri'eroux, 2020. "Consumer Theory with Non-Parametric Taste Uncertainty and Individual Heterogeneity," Papers 2010.13937, arXiv.org, revised Jan 2021.
    • Handle: RePEc:arx:papers:2010.13937
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2010.13937
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ledoit, Olivier & Wolf, Michael, 2004. "A well-conditioned estimator for large-dimensional covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 88(2), pages 365-411, February.
    2. Moschini, Giancarlo, 1998. "The semiflexible almost ideal demand system," European Economic Review, Elsevier, vol. 42(2), pages 349-364, February.
    3. Geweke, John, 2012. "Nonparametric Bayesian modelling of monotone preferences for discrete choice experiments," Journal of Econometrics, Elsevier, vol. 171(2), pages 185-204.
    4. Dette, Holger & Hoderlein, Stefan & Neumeyer, Natalie, 2016. "Testing multivariate economic restrictions using quantiles: The example of Slutsky negative semidefiniteness," Journal of Econometrics, Elsevier, vol. 191(1), pages 129-144.
    5. Yoram Halevy & Vincent Feltkamp, 2005. "A Bayesian Approach to Uncertainty Aversion," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(2), pages 449-466.
    6. Soren Blomquist & Anil Kumar & Che-Yuan Liang & Whitney K. Newey, 2014. "Individual heterogeneity, nonlinear budget sets, and taxable income," CeMMAP working papers CWP21/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Walter Beckert & Richard Blundell, 2008. "Heterogeneity and the Non-Parametric Analysis of Consumer Choice: Conditions for Invertibility," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(4), pages 1069-1080.
    8. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    9. Burda, Martin & Harding, Matthew & Hausman, Jerry, 2008. "A Bayesian mixed logit-probit model for multinomial choice," Journal of Econometrics, Elsevier, vol. 147(2), pages 232-246, December.
    10. Alley, Andrew G & Ferguson, Donald G & Stewart, Kenneth G, 1992. "An Almost Ideal Demand System for Alcoholic Beverages in British Columbia," Empirical Economics, Springer, vol. 17(3), pages 401-418.
    11. James Banks & Richard Blundell & Arthur Lewbel, 1997. "Quadratic Engel Curves And Consumer Demand," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 527-539, November.
    12. Rishab Guha & Serena Ng, 2019. "A Machine Learning Analysis of Seasonal and Cyclical Sales in Weekly Scanner Data," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 403-436, National Bureau of Economic Research, Inc.
    13. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    14. Ian Crawford & Matthew Polisson, 2015. "Demand Analysis with Partially Observed Prices," Discussion Papers in Economics 15/12, Division of Economics, School of Business, University of Leicester, revised Dec 2016.
    15. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    16. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1975. "Transcendental Logarithmic Utility Functions," American Economic Review, American Economic Association, vol. 65(3), pages 367-383, June.
    17. BARTEN, Anton P., 1968. "Estimating demand equations," LIDAM Reprints CORE 21, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. ROLIN, Jean-Marie, 1992. "Some useful properties of the Dirichlet process," LIDAM Discussion Papers CORE 1992007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-1057, September.
    20. Yuichi Kitamura & Michael Stutzer, 1997. "An Information-Theoretic Alternative to Generalized Method of Moments Estimation," Econometrica, Econometric Society, vol. 65(4), pages 861-874, July.
    21. Karni, Edi, 1979. "On Multivariate Risk Aversion," Econometrica, Econometric Society, vol. 47(6), pages 1391-1401, November.
    22. Rolin, J.M., 1992. "Some Useful Properties on the Dirichlet Process," Papers 9202, Catholique de Louvain - Institut de statistique.
    23. 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.
    24. Rosa L. Matzkin, 2003. "Nonparametric Estimation of Nonadditive Random Functions," Econometrica, Econometric Society, vol. 71(5), pages 1339-1375, September.
    25. H. H. Thell & H. Neudecker, 1958. "Substitution, Complementarity, and the Residual Variation around Engel Curves," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 25(2), pages 114-123.
    26. Søren Asmussen & Jens Ledet Jensen & Leonardo Rojas-Nandayapa, 2016. "On the Laplace Transform of the Lognormal Distribution," Methodology and Computing in Applied Probability, Springer, vol. 18(2), pages 441-458, June.
    27. Manning, Willard G. & Blumberg, Linda & Moulton, Lawrence H., 1995. "The demand for alcohol: The differential response to price," Journal of Health Economics, Elsevier, vol. 14(2), pages 123-148, June.
    28. Serena Ng, 2017. "Opportunities and Challenges: Lessons from Analyzing Terabytes of Scanner Data," NBER Working Papers 23673, National Bureau of Economic Research, Inc.
    29. Scott F. Richard, 1975. "Multivariate Risk Aversion, Utility Independence and Separable Utility Functions," Management Science, INFORMS, vol. 22(1), pages 12-21, September.
    30. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hubner, Stefan, 2023. "Identification of unobserved distribution factors and preferences in the collective household model," Journal of Econometrics, Elsevier, vol. 234(1), pages 301-326.
    2. 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.
    3. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    4. 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.
    5. Laurens Cherchye & Bram De Rock & Frederic Vermeulen, 2023. "Nonparametric Models in Consumer Behaviour," Working Papers ECARES 2023-04, ULB -- Universite Libre de Bruxelles.
    6. davis, peter, 2006. "The Discrete Choice Analytically Flexible (DCAF) Model of Demand for Differentiated Products," CEPR Discussion Papers 5880, C.E.P.R. Discussion Papers.
    7. Paris, Quirino & Caracciolo, Francesco, 2012. "Quantity Versus Shares in Estimating Demand Systems," Working Papers 124575, University of California, Davis, Department of Agricultural and Resource Economics.
    8. William Barnett & Ousmane Seck, 2006. "Rotterdam vs Almost Ideal Models: Will the Best Demand Specification Please Stand Up?," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 200605, University of Kansas, Department of Economics.
    9. 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.
    10. Mette Lunde Christensen, 2002. "Heterogeneity in consumer demands and the income effect: evidence from panel data," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C4-1, International Conferences on Panel Data.
    11. Femenia, Fabienne, 2019. "A Meta-Analysis of the Price and Income Elasticities of Food Demand," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 68(2), June.
    12. LaFrance, Jeffrey T., 2008. "The structure of US food demand," Journal of Econometrics, Elsevier, vol. 147(2), pages 336-349, December.
    13. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    14. Neary, Peter, 2000. "True Multilateral Indexes for International Comparisons of Real Income: Theory and Empirics," CEPR Discussion Papers 2590, C.E.P.R. Discussion Papers.
    15. William A. Barnett & Ousmane Seck, 2008. "Rotterdam model versus almost ideal demand system: will the best specification please stand up?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 795-824.
    16. Paris, Quirino & Caracciolo, Francesco, 2014. "Testing the adding up condition in demand systems," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182827, European Association of Agricultural Economists.
    17. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    18. Knobel, Alexander (Кнобель, Александр) & Chentsov, Alexander (Ченцов, Александр), 2018. "The Impact of Exchange Rates and Their Volatility on Russia's Foreign Trade, Taking into Account its Membership in EAEU [Влияние Обменных Курсов И Их Волатильности На Внешнюю Торговлю России С Учет," Working Papers 061824, Russian Presidential Academy of National Economy and Public Administration.
    19. Holt, Matthew T. & Goodwin, Barry K., 2009. "The Almost Ideal and Translog Demand Systems," MPRA Paper 15092, University Library of Munich, Germany.
    20. Jeffrey LaFrance & Rulon Pope, 2008. "The Generalized Quadratic Expenditure System," Working Papers 2008-27, School of Economic Sciences, Washington State University.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2010.13937. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.