A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates

arXiv:2205.00171v3 Announce Type: replace-cross
Abstract: This paper proposes an overidentifying restriction test for high-dimensional linear instrumental variable models. The novelty of the proposed test is that it allows the number of covariates and instruments to be larger than the sample size. The test is scale-invariant and is robust to heteroskedastic errors. To construct the final test statistic, we first introduce a test based on the maximum norm of multiple parameters that could be high-dimensional. The theoretical power based on the …

abstract arxiv econ.em errors heteroskedasticity linear math.st paper robust sample scale stat.ml stat.th test type