Simple Adaptive Size-Exact Testing for Full-Vector and Subvector Inference in Moment Inequality Models

• Econometrics

Date and Location

Monday, December 6, 2021, 3:40 PM - 5:00 PM
Online Meeting, Zoom

Abstract

We propose a simple test for moment inequalities that has exact size in normal mod- els with known variance and has uniformly asymptotically exact size under asymptotic normality. The test compares the quasi-likelihood ratio statistic to a chi-squared criti- cal value, where the degree of freedom is the rank of the inequalities that are active in finite samples. The test requires no simulation and thus is computationally fast and especially suitable for constructing confidence sets for parameters by test inversion. It uses no tuning parameter for moment selection and yet still adapts to the slackness of the moment inequalities. Furthermore, we show how the test can be easily adapted to inference on subvectors in the common empirical setting of conditional moment inequalities with nuisance parameters entering linearly. User-friendly Matlab code to implement the test is provided.

Subscribe to Upcoming Seminars

Click here to receive weekly notice of all upcoming seminars via email.

Individual seminar and workshop announcements are circulated via separate mailing lists. To subscribe, send an email to the relevant list:

• Click here to subscribe to the Departmental Seminars.
• Click here to subscribe to the Agricultural Economics Workshop.
• Click here to subscribe to the Development Workshop.
• Click here to subscribe to the Econometrics Seminars.
• Click here to subscribe to the Environmental and Resource Economics Workshop and the Environmental and Energy Economics Workshop.