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Simple Two-Stage Inference for a Class of Partially Identified Models

Shi, Xiaoxia and Shum, Matthew (2015) Simple Two-Stage Inference for a Class of Partially Identified Models. Econometric Theory, 31 (3). pp. 493-520. ISSN 0266-4666. doi:10.1017/S0266466614000425.

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This paper proposes a new two-stage estimation and inference procedure for a class of partially identified models. The procedure can be considered an extension of classical minimum distance estimation procedures to accommodate inequality constraints and partial identification. It involves no tuning parameter, is nonconservative, and is conceptually and computationally simple. The class of models includes models of interest to applied researchers, including the static entry game, a voting game with communication, and a discrete mixture model. Besides, a technical contribution is an implicit correspondence lemma which generalizes the implicit function theorem to multivalued implicit maps.

Item Type:Article
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URLURL TypeDescription DOIArticle ItemWorking Paper
Shum, Matthew0000-0002-6262-915X
Additional Information:© 2014 Cambridge University Press. We thank Yanqin Fan, Patrik Guggenberger, Bruce E. Hansen, Jack R. Porter, the editor Peter C.B. Phillips, the co-editor, and two anonymous referees for useful comments and suggestions. Xiaoxia Shi acknowledges the financial support of the Wisconsin Alumni Research Foundation via the Graduate School Fall Competition Award.
Funding AgencyGrant Number
Wisconsin Alumni Research FoundationUNSPECIFIED
Issue or Number:3
Record Number:CaltechAUTHORS:20150611-142135084
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Official Citation: Xiaoxia Shi and Matthew Shum (2015). SIMPLE TWO-STAGE INFERENCE FOR A CLASS OF PARTIALLY IDENTIFIED MODELS. Econometric Theory, 31, pp 493-520. doi:10.1017/S0266466614000425
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:58202
Deposited By: Tony Diaz
Deposited On:13 Jun 2015 01:30
Last Modified:10 Nov 2021 22:01

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