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Discrete choice under risk with limited consideration

Authors: Levon Barseghyan , Francesca Molinari and Matthew Thirkettle
Date: 24 June 2020
Type: cemmap Working Paper, CWP28/20
DOI: 10.1920/wp.cem.2020.2820


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.

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Levon Barseghyan, Francesca Molinari and Matthew Thirkettle February 2019, Discrete choice under risk with limited consideration, cemmap Working Paper, The IFS

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