Cristina Gualdani , Queen Mary University of London Shruti Sinha , Toulouse School of Economics, University of Toulouse Capitole, Toulouse, France.
June 21, 2023
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We study identification of preferences in static single-agent discrete choice models where decision makers may be imperfectly informed about the state of the world. We leverage the notion of one-player Bayes Correlated Equilibrium by Bergemann and Morris (2016) to provide a tractable characterization of the sharp identified set. We develop a procedure to practically construct the sharp identified set when the state of the world is continuous following a sieve approach, and provide sharp bounds on counterfactual outcomes of interest. We use our methodology and data on the 2017 UK general election to estimate a spatial voting model under weak assumptions on agents’ information about the returns to voting. Counterfactual exercises quantify the consequences of imperfect information on the well-being of voters and parties.
J.E.L classification codes: C01, C25, D72, D80
Keywords:Discrete choice model, Bayesian Persuasion, Bayes Correlated Equilibrium, Incomplete Information, Partial Identification, Moment Inequalities, Spatial Model of Voting.