Conditional Linear Combination Tests for Weakly Identified Models

Abstract

We introduce the class of conditional linear combination tests, which reject null hypotheses concerning model parameters when a data-dependent convex combination of two identification-robust statistics is large. These tests control size under weak identification and have a number of optimality properties in a conditional problem.