Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection

Donald W. K. Andrews () and Gustavo Soures
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Gustavo Soures: Dept. of Economics, Yale University, http://www.econ.yale.edu/

No 1631, Cowles Foundation Discussion Papers from Cowles Foundation, Yale University

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 (search for similar items in EconPapers)
JEL-codes: C12 C15 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2007-10
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