Estimating causal effects under exogeneity hinges on two key assumptions: unconfoundedness and overlap. Researchers often argue that is more plausible when covariates are included in the analysis. Less discussed fact covariate overlap difficult to satisfy this setting. In paper, we explore implications of observational studies with high-dimensional formalize curse-of-dimensionality argument, su...
