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Identifying Preferences under Risk from Discrete Choices

Author

Listed:
  • Pierre-Andre Chiappori
  • Amit Gandhi
  • Bernard Salanie
  • Francois Salanie

Abstract

When studying consumption choices, economists have often relied on the abstraction of a representative agent. Such an agent can indeed be shown to exist and to replicate the aggregate consumers' demand under standard, but not necessarily convincing assumptions (Kirman (1992)). There was also ajustifiable reluctance to introducing heterogeneous preferences, as such a step may seem ad hoc when trying to explain different consumption behaviors. The rise of empirical studies based on micro data has opened new perspectives. The micro-economic importance of uninsurable risks is now recognized, and threatens the foundations of the representative agent hypothesis often used in macroeconomics. The continuing controversies surrounding the question of individual attitudes towards risk has motivated many empirical studies and observations; most of them conclude to a bewildering diversity of individual preferences. This paper proposes to check the conditions under which heterogeneous individual attitudes toward risk can be non-parametrically identified from discrete data on choices under risk. Our main result establishes that given data that is usually available (essentially market shares of the different options, plus the realizations of the final outcomes of agents), the analyst can recover the whole distribution of individual preferences if this can be indexed by a one-dimensional parameter, provided that a fairly weak single-crossing condition holds. We then discuss several applications of our general methodology.
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Suggested Citation

  • Pierre-Andre Chiappori & Amit Gandhi & Bernard Salanie & Francois Salanie, 2009. "Identifying Preferences under Risk from Discrete Choices," LERNA Working Papers 09.11.287, LERNA, University of Toulouse.
  • Handle: RePEc:ler:wpaper:09.11.287
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    File URL: http://www2.toulouse.inra.fr/lerna/travaux/cahiers2009/09.11.287.pdf
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    Cited by:

    1. Daniel Paravisini & Veronica Rappoport & Enrichetta Ravina, 2017. "Risk Aversion and Wealth: Evidence from Person-to-Person Lending Portfolios," Management Science, INFORMS, vol. 63(2), pages 279-297, February.
    2. Henderson, Daniel J. & Li, Qi & Parmeter, Christopher F. & Yao, Shuang, 2015. "Gradient-based smoothing parameter selection for nonparametric regression estimation," Journal of Econometrics, Elsevier, vol. 184(2), pages 233-241.
    3. Keith Marzilli Ericson & Philipp Kircher & Johannes Spinnewijn & Amanda Starc, 2021. "Inferring Risk Perceptions and Preferences Using Choice from Insurance Menus: Theory and Evidence," The Economic Journal, Royal Economic Society, vol. 131(634), pages 713-744.
    4. Brian Blackburn & Aprajit Mahajan & Alessandro Tarozzi & Joanne Yoong, "undated". "Bednets, Information and Malaria in Orissa," Discussion Papers 08-025, Stanford Institute for Economic Policy Research.
    5. Ahmad Reshad Osmani & Albert Okunade, 2021. "A Double-Hurdle Model of Healthcare Expenditures across Income Quintiles and Family Size: New Insights from a Household Survey," JRFM, MDPI, vol. 14(6), pages 1-21, May.
    6. R.M.N.N. Senavirathna & R.M.N.S. Senavirathna, 2023. "Healthcare Expenditures Across Household Headship and Expenditure Quintiles: Insights From a Household Survey," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(3), pages 117-131, March.
    7. Benjamin R. Handel, 2011. "Adverse Selection and Switching Costs in Health Insurance Markets: When Nudging Hurts," NBER Working Papers 17459, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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