Best Feasible Conditional Critical Values for a More Powerful Subvector Anderson-Rubin Test
更有检验力的子向量 Anderson–Rubin 检验:最佳可行条件临界值
For subvector inference in the linear instrumental variables model under homoskedasticity but allowing for weak instruments, Guggenberger, Kleibergen, and Mavroeidis (2019) (GKM) propose a conditional subvector Anderson and Rubin (1949) (AR) test that uses data-dependent critical values that adapt to the strength of the parameters not under test. This test has correct size and strictly higher power than the test that uses standard asymptotic chi-square critical values. The…