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Empirical Models of Consumer Behavior

Author

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  • Aviv Nevo

    () (Department of Economics, Northwestern University, Evanston, Illinois 60208)

Abstract

Models of consumer behavior play a key role in modern empirical industrial organization. In this review, I survey some of the models used in this literature. In particular, I discuss two commonly used demand systems: multistage budgeting approaches and discrete choice models. I motivate their use and highlight some key modeling assumptions. I next briefly discuss key issues of estimation and conclude by summarizing some extensions.

Suggested Citation

  • Aviv Nevo, 2011. "Empirical Models of Consumer Behavior," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 51-75, September.
    • Handle: RePEc:anr:reveco:v:3:y:2011:p:51-75
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    Cited by:

    1. Pablo Fajgelbaum & Gene M. Grossman & Elhanan Helpman, 2011. "Income Distribution, Product Quality, and International Trade," Journal of Political Economy, University of Chicago Press, vol. 119(4), pages 721-765.
    2. Evgeny Yakovlev, 2016. "Demand for Alcohol Consumption and Implication for Mortality: Evidence from Russia," Working Papers w0221, Center for Economic and Financial Research (CEFIR).
    3. Carlos Madeira, 2019. "Adverse selection, loan access and default in the Chilean consumer debt market," Working Papers Central Bank of Chile 838, Central Bank of Chile.
    4. Jorge Talero Bernal, 2016. "Una comparación del gasto por tres niveles de ingreso para Colombia bajo una estimación del sistema de ecuaciones de demanda Working y Leser y del Sistema Lineal de Gasto Extendido 2008," Revista CIFE, Universidad Santo Tomás, March.
    5. De Zhou & Xiaohua Yu & Thomas Herzfeld, 2015. "Dynamic food demand in urban China," China Agricultural Economic Review, Emerald Group Publishing, vol. 7(1), pages 27-44, February.
    6. repec:eee:ecolec:v:147:y:2018:i:c:p:48-61 is not listed on IDEAS
    7. Jose de Sousa & Eve Sihra & Thierry Mayer, 2019. "Market Integration and Convergence in Consumption Patterns," 2019 Meeting Papers 1178, Society for Economic Dynamics.
    8. Andrew Chesher & Adam M. Rosen, 2014. "An instrumental variable random‐coefficients model for binary outcomes," Econometrics Journal, Royal Economic Society, vol. 17(2), pages 1-19, June.
    9. Margaret M. Cigno & Elena S. Patel & Edward S. Pearsall, 2013. "Estimates of US postal price elasticities of demand derived from a random- coefficients discrete-choice normal model," Chapters, in: Michael A. Crew & Paul R. Kleindorfer (ed.), Reforming the Postal Sector in the Face of Electronic Competition, chapter 6, pages 76-88, Edward Elgar Publishing.
    10. repec:spr:jecstr:v:6:y:2017:i:1:d:10.1186_s40008-017-0066-y is not listed on IDEAS
    11. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2019. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," NBER Working Papers 25827, National Bureau of Economic Research, Inc.
    12. Leonardo Becchetti & Francesco Salustri & Pasquale Scaramozzino, 2018. "Nudging and Environmental Corporate Responsibility: A Natural Experiment," CEIS Research Paper 426, Tor Vergata University, CEIS, revised 03 Apr 2018.
    13. Yukihiro Kidokoro, 2015. "Discrete choice models for multicategory goods," GRIPS Discussion Papers 15-08, National Graduate Institute for Policy Studies.
    14. Mendis, Sachintha & Hovhannisyan, Vardges, 2017. "Assessing Provincial-Level Demand For Food Quantity And Quality In China: An Easi Demand System Approach," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252797, Southern Agricultural Economics Association.
    15. Federico Ciliberto & GianCarlo Moschini & Edward D. Perry, 2019. "Valuing product innovation: genetically engineered varieties in US corn and soybeans," RAND Journal of Economics, RAND Corporation, vol. 50(3), pages 615-644, September.
    16. Dardanoni, V.; & Laudicella, M.; & Li Donni, P.;, 2018. "Hospital Choice in the NHS," Health, Econometrics and Data Group (HEDG) Working Papers 18/04, HEDG, c/o Department of Economics, University of York.
    17. repec:taf:marpmg:v:43:y:2016:i:6:p:676-682 is not listed on IDEAS
    18. Wiktor L. Adamowicz & Klaus Glenk & Jürgen Meyerhoff, 2014. "Choice modelling research in environmental and resource economics," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 27, pages 661-674, Edward Elgar Publishing.
    19. ABE Naohito & INAKURA Noriko & TONOGI Akiyuki, 2016. "Estimation of Aggregate Demand and Supply Shocks Using Commodity Transaction Data," Discussion papers 16040, Research Institute of Economy, Trade and Industry (RIETI).
    20. Kidokoro, Yukihiro, 2016. "A micro foundation for discrete choice models with multiple categories of goods," Journal of choice modelling, Elsevier, vol. 19(C), pages 54-72.
    21. Lázár Ede, 2014. "Quantifying the Economic Value of Warranties: A Survey," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 2(1), pages 75-94, October.

    More about this item

    Keywords

    industrial organization; demand estimation; differentiated products; Almost Ideal Demand System; discrete choice;

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General

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