Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection

59 Pages Posted: 15 Oct 2007 Last revised: 21 Oct 2007

See all articles by Donald W. K. Andrews

Donald W. K. Andrews

Yale University - Cowles Foundation

Gustavo Soares

Yale University - Department of Economics

Date Written: October 2007

Abstract

The topic of this paper is inference in models in which parameters are defined by moment inequalities and/or equalities. The parameters may or may not be identified. This paper introduces a new class of confidence sets and tests based on generalized moment selection (GMS). GMS procedures are shown to have correct asymptotic size in a uniform sense and are shown not to be asymptotically conservative.

The power of GMS tests is compared to that of subsampling, m out of n bootstrap, and plug-in asymptotic (PA) tests. The latter three procedures are the only general procedures in the literature that have been shown to have correct asymptotic size in a uniform sense for the moment inequality/equality model. GMS tests are shown to have asymptotic power that dominates that of subsampling, m out of n bootstrap, and PA tests. Subsampling and m out of n bootstrap tests are shown to have asymptotic power that dominates that of PA tests.

Keywords: Asymptotic size, Asymptotic power, Confidence set, Exact size, Generalized moment selection, m out of n bootstrap, Subsampling, Moment inequalities, Moment selection, Test

JEL Classification: C12, C15

Suggested Citation

Andrews, Donald W. K. and Soares, Gustavo, Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection (October 2007). Cowles Foundation Discussion Paper No. 1631, Available at SSRN: https://ssrn.com/abstract=1020920

Donald W. K. Andrews (Contact Author)

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States
203-432-3698 (Phone)
203-432-6167 (Fax)

Gustavo Soares

Yale University - Department of Economics ( email )

28 Hillhouse Ave
New Haven, CT 06520-8268
United States

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