SMU SOE Online Seminar (Aug 13, 2020, 10.30am-12.00pm): Simple Adaptive Size-Exact Test for Full-Vector and Subvector Inference in Moment Inequality Models

Please click here if you are unable to view this page.

ABSTRACT We propose a simple test for moment inequalities that has exact size in normal models with know variance, and has uniformly asymptotically exact size in general. The test compares the likelihood ratio statistic to a chi-squared critical value, where the degrees of freedom is the rank of inequalities active in ﬁnite samples. The test requires no simulated critical values 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 for inference on subvectors for the common empirical setting of conditional moment inequalities with nuisance parameters entering linearly. Keywords: Likelihood ratio, linear programming, moment inequalities, sub-vector inference, uniform inference. Click here to view the CV.		This seminar will be held via Zoom. A confirmation email with the Zoom meeting link will be sent the registered email by 12 August 2020.
		PRESENTER Xiaoxia Shi University of Wisconsin-Madison
		RESEARCH FIELDS Econometrics
		DATE: 13 August 2020 (Thursday)
		TIME: 10.30am - 12.00pm