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Discrete Choice under Risk with Limited Consideration

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  • Levon Barseghyan
  • Francesca Molinari
  • Matthew Thirkettle

Abstract

This paper is concerned with learning decision makers' preferences using data on observed choices from a finite set of risky alternatives. We propose a discrete choice model with unobserved heterogeneity in consideration sets and in standard risk aversion. We obtain sufficient conditions for the model's semi-nonparametric point identification, including in cases where consideration depends on preferences and on some of the exogenous variables. Our method yields an estimator that is easy to compute and is applicable in markets with large choice sets. We illustrate its properties using a dataset on property insurance purchases.

Suggested Citation

  • Levon Barseghyan & Francesca Molinari & Matthew Thirkettle, 2019. "Discrete Choice under Risk with Limited Consideration," Papers 1902.06629, arXiv.org, revised Jan 2021.
  • Handle: RePEc:arx:papers:1902.06629
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    Cited by:

    1. Gualdani, Cristina & Sinha, Shruti, 2019. "Identification and inference in discrete choice models with imperfect information," TSE Working Papers 19-1049, Toulouse School of Economics (TSE), revised Jun 2020.
    2. Johannes G. Jaspersen & Marc A. Ragin & Justin R. Sydnor, 2019. "Predicting Insurance Demand from Risk Attitudes," NBER Working Papers 26508, National Bureau of Economic Research, Inc.
    3. Victor H. Aguiar & Nail Kashaev, 2019. "Discrete Choice and Welfare Analysis with Unobserved Choice Sets," Papers 1907.04853, arXiv.org, revised Jul 2019.
    4. Martin, Simon, 2020. "Market transparency and consumer search - Evidence from the German retail gasoline market," DICE Discussion Papers 350, University of Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).

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