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TOPIC: | FINITE SAMPLE INFERENCE IN INCOMPLETE MODELS |
ABSTRACTWe propose confidence regions for the parameters of incomplete models with exact coverage of the true parameter in finite samples. Our confidence region inverts a test, which generalizes Monte Carlo tests to incomplete models. The test statistic is a discrete analogue of a new optimal transport characterization of the sharp identified region. Both test statistic and critical values rely on simulation drawn from the distribution of latent variables and are computed using solutions to discrete optimal transport, hence linear programming problems. We also pro- pose a fast preliminary search in the parameter space with an alternative, more conservative yet consistent test, based on a parameter free critical value. Keywords: Incomplete models, set prediction, multiple equilibria, sharp identification region, simulation-based testing, finite sample inference, optimal transport. JEL Codes: C15, C57, C61. Click here to view the CV. Click here to view the paper. | |  | PRESENTERMarc Henry The Pennsylvania State University | RESEARCH FIELDEconometrics | DATE:5 March 2024 (Tuesday) | TIME:4pm - 5.30pm | VENUE:Meeting Room 5.1, Level 5
School of Economics
Singapore Management University
90 Stamford Road
Singapore 178903 |
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