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Generalized Instrumental Variable Models

Bibliographic Data

ID19040611
AuthorsAndrew Chesher (0000-0001-9646-3955, corresponding author), Adam Rosen, Adam M Rosen
Year2017
Volume85
Issue3
Pages959-989
Publication date2017-01-01
Open AccessNo
TypeARTICLE
VenueEconometrica (JOURNAL)
Journal identifiersISSN: 0012-9682 • E-ISSN: 1468-0262
PublisherWiley (PUBLISHER • GB)
DOI10.3982/ecta12223
OpenAlexW4292027072
LanguageEN
Citations received4

This paper develops characterizations of identified sets of structures and structural features for complete and incomplete models involving continuous or discrete variables.Multiple values of unobserved variables can be associated with particular combinations of observed variables.This can arise when there are multiple sources of heterogeneity, censored or discrete endogenous variables, or inequality restrictions on functions of observed and unobserved variables.The models generalize the class of incomplete instrumental variable (IV) models in which unobserved variables are singlevalued functions of observed variables.Thus the models are referred to as generalized IV (GIV) models, but there are important cases in which instrumental variable restrictions play no significant role.Building on a definition of observational equivalence for incomplete models the development uses results from random set theory that guarantee that the characterizations deliver sharp bounds, thereby dispensing with the need for case-by-case proofs of sharpness.The use of random sets defined on the space of unobserved variables allows identification analysis under mean and quantile independence restrictions on the distributions of unobserved variables conditional on exogenous variables as well as under a full independence restriction.The results are used to develop sharp bounds on the distribution of valuations in an incomplete model of English auctions, improving on the pointwise bounds available until now.Application of many of the results of the paper requires no familiarity with random set theory

Econometrics · Economics · Instrumental variable · Mathematical analysis · Statistics · Mathematics · Simulation Techniques and Applications

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Citations per year0.8
Citation span2021 - 2025 (5)
Highly citedNo
Open DOISci-Hub
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