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Identification in discrete choice models with imperfect information

Cristina Gualdani, Shruti Sinha

arXiv 11 Nov 2019 · Econometrics · publishedJournal of Econometrics (2024) · 8 citations (OpenAlex)

arXiv:1911.04529 · PDF · DOI · OpenAlex · Extracted main text

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 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.

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Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Identification and Estimation of Dynamic Games with Unknown Information Structure1.00073
2Testing Information Ordering for Strategic Agents0.40511
3Revealed Information0.40511