Inference for Linear Conditional Moment Inequalities

Isaiah Andrews, Jonathan Roth and Ariel Pakes

Papers from arXiv.org

Abstract: We show that moment inequalities in a wide variety of economic applications have a particular linear conditional structure. We use this structure to construct uniformly valid confidence sets that remain computationally tractable even in settings with nuisance parameters. We first introduce least favorable critical values which deliver non-conservative tests if all moments are binding. Next, we introduce a novel conditional inference approach which ensures a strong form of insensitivity to slack moments. Our recommended approach is a hybrid technique which combines desirable aspects of the least favorable and conditional methods. The hybrid approach performs well in simulations calibrated to Wollmann (2018), with favorable power and computational time comparisons relative to existing alternatives.

Date: 2019-09, Revised 2022-12
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Inference for Linear Conditional Moment Inequalities (2023)
Working Paper: Inference for Linear Conditional Moment Inequalities (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1909.10062

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