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Empirical Models of Consumer Behavior

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Listed author(s):
  • Aviv Nevo

Abstract

Models of consumer behavior play a key role in modern empirical Industrial Organization. In this paper, I survey some of the models used in this literature. In particular, I discuss two commonly used demand systems: multi-stage 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.

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File URL: http://www.nber.org/papers/w16511.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16511.

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Date of creation: Oct 2010
Publication status: published as Aviv Nevo, 2011. "Empirical Models of Consumer Behavior," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 51-75, 09.
Handle: RePEc:nbr:nberwo:16511
Note: IO LS PR
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Find related papers by JEL classification:
  • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
  • L0 - Industrial Organization - - General

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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. 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.
  3. Wiktor L. Adamowicz & Klaus Glenk & Jürgen Meyerhoff, 2014. "Choice modelling research in environmental and resource economics," Chapters,in: Handbook of Choice Modelling, chapter 27, pages 661-674 Edward Elgar Publishing.
  4. 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.
  5. Lázár Ede, 2014. "Quantifying the Economic Value of Warranties: A Survey," Acta Universitatis Sapientiae, Economics and Business, De Gruyter Open, vol. 2(1), pages 75-94, October.
  6. Evgeny Yakovlev, 2016. "Demand for Alcohol Consumption and Implication for Mortality: Evidence from Russia," Working Papers w0221, Center for Economic and Financial Research (CEFIR).
  7. 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, 06.
  8. 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).
  9. 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.
  10. 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: Reforming the Postal Sector in the Face of Electronic Competition, chapter 6, pages 76-88 Edward Elgar Publishing.
  11. Yukihiro Kidokoro, 2015. "Discrete choice models for multicategory goods," GRIPS Discussion Papers 15-08, National Graduate Institute for Policy Studies.
  12. 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.

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