Inference for Linear Conditional Moment Inequalities

• 成果类型: Article
• 署名作者: Andrews, Isaiah; Roth, Jonathan; Pakes, Ariel
• 署名单位: Harvard University; Brown University
• 刊物名称: REVIEW OF ECONOMIC STUDIES
• ISSN/ISSBN: 0034-6527
• DOI: 10.1093/restud/rdad004
• 发表日期: 2023
• 页码: 2763-2791
• 关键词: parameters; models; sets

摘要

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.