Inference in Moment Inequality Models That Is Robust to Spurious Precision under Model Misspecification

Donald Andrews () and Soonwoo Kwon
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Soonwoo Kwon: Department of Economics, Yale University

No 2184, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: Standard tests and confidence sets in the moment inequality literature are not robust to model misspecification in the sense that they exhibit spurious precision when the identified set is empty. This paper introduces tests and confidence sets that provide correct asymptotic inference for a pseudo-true parameter in such scenarios, and hence, do not suffer from spurious precision.

Keywords: Asymptotics; confidence set; identification; inference; misspecification; moment inequalities; robust; spurious precision; test (search for similar items in EconPapers)
JEL-codes: C10 C12 (search for similar items in EconPapers)
Pages: 146 pages
Date: 2019-07
New Economics Papers: this item is included in nep-ecm and nep-ore
Note: Includes Supplimental Material
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Working Paper: Inference in Moment Inequality Models That Is Robust to Spurious Precision under Model Misspecification (2019)
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