Inference for Linear Conditional Moment Inequalities

Isaiah Andrews, Jonathan Roth and Ariel Pakes

No 26374, NBER Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: C12 (search for similar items in EconPapers)
Date: 2019-10
New Economics Papers: this item is included in nep-ore
Note: IO
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Citations: View citations in EconPapers (6)

Published as Isaiah Andrews & Jonathan Roth & Ariel Pakes, 2023. "Inference for Linear Conditional Moment Inequalities," Review of Economic Studies, vol 90(6), pages 2763-2791.

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Related works:
Journal Article: Inference for Linear Conditional Moment Inequalities (2023)
Working Paper: Inference for Linear Conditional Moment Inequalities (2022)
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