Bayesian and Frequentist Inference in Partially Identified Models

36 Pages Posted: 20 Apr 2009 Last revised: 1 Sep 2022

See all articles by Hyungsik Roger Moon

Hyungsik Roger Moon

University of Southern California - Department of Economics; USC Dornsife Institute for New Economic Thinking

Frank Schorfheide

University of Pennsylvania - Department of Economics; Centre for Economic Policy Research (CEPR); National Bureau of Economic Research (NBER); University of Pennsylvania - The Penn Institute for Economic Research (PIER)

Date Written: April 2009

Abstract

A large sample approximation of the posterior distribution of partially identified structural parameters is derived for models that can be indexed by a finite-dimensional reduced form parameter vector. It is used to analyze the differences between frequentist confidence sets and Bayesian credible sets in partially identified models. A key difference is that frequentist set estimates extend beyond the boundaries of the identified set (conditional on the estimated reduced form parameter), whereas Bayesian credible sets can asymptotically be located in the interior of the identified set. Our asymptotic approximations are illustrated in the context of simple moment inequality models and a numerical illustration for a two-player entry game is provided.

Suggested Citation

Moon, Hyungsik Roger and Schorfheide, Frank, Bayesian and Frequentist Inference in Partially Identified Models (April 2009). NBER Working Paper No. w14882, Available at SSRN: https://ssrn.com/abstract=1391829

Hyungsik Roger Moon (Contact Author)

University of Southern California - Department of Economics ( email )

KAP 300
Los Angeles, CA 90089-0253
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213-740-2108 (Phone)
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USC Dornsife Institute for New Economic Thinking ( email )

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Frank Schorfheide

University of Pennsylvania - Department of Economics ( email )

Ronald O. Perelman Center for Political Science
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Philadelphia, PA 19104-6297
United States

HOME PAGE: http://www.econ.upenn.edu/~schorf

Centre for Economic Policy Research (CEPR)

London
United Kingdom

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

University of Pennsylvania - The Penn Institute for Economic Research (PIER) ( email )

Philadelphia, PA
United States

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