Identification in Discrete Choice Models with Imperfect Information

Cristina Gualdani and Shruti Sinha
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Cristina Gualdani: Queen Mary University of London
Shruti Sinha: Toulouse School of Economics, University of Toulouse Capitole, Toulouse, France.

No 949, Working Papers from Queen Mary University of London, School of Economics and Finance

Abstract: 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.

Keywords: Discrete choice model; Bayesian Persuasion; Bayes Correlated Equilibrium; Incomplete Information; Partial Identification; Moment Inequalities; Spatial Model of Voting. (search for similar items in EconPapers)
JEL-codes: C01 C25 D72 D80 (search for similar items in EconPapers)
Date: 2023-06-21
New Economics Papers: this item is included in nep-dcm
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:qmw:qmwecw:949

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