identification inference moment conditions robust singular variance subvector test test weak identification weak instruments C10 C12 …This paper introduces a new identification- and singularity-robust conditional quasi-likelihood ratio (SR-CQLR) test … and a new identification- and singularity-robust Anderson and Rubin (1949) (SR-AR) test for linear and nonlinear moment …

conditional likelihood ratio test confidence set identification inference moment conditions robust singular variance subvector …This paper introduces a new identification‐ and singularity‐robust conditional quasi‐likelihood ratio (SR‐CQLR) test … and a new identification‐ and singularity‐robust Anderson and Rubin (1949) (SR‐AR) test for linear and nonlinear moment …

procedures has not been determined in the literature. This paper does so. This paper shows that the LM test has correct … paper also determines a formula for the asymptotic size of the CLR test with the other weighting method. However, the … sample quantities are not necessarily asymptotically independent under some identification scenarios. Analogous results for …

criterion functions. We determine the asymptotic distributions of estimators under lack of identification and under weak, semi …-strong, and strong identification. We determine the asymptotic size (in a uniform sense) of standard t and quasi-likelihood ratio … (QLR) tests and CS's. We provide methods of constructing QLR tests and CS's that are robust to the strength of …

also establishes the correct asymptotic sizes of "robust" GMM-based Wald, t, and quasi-likelihood ratio tests and CS …'s whose critical values are designed to yield robustness to identification problems. The results of the paper are applied to a …

's robust to such identification problems. The results apply to a class of extremum estimators and corresponding tests and CS … sense) of standard and identification-robust tests and CS's are established. The results are applied to the ARMA(1, 1) time … the parameter that determines the strength of identification. This covers a class of models estimated using maximum …