We derive general, yet simple, sharp bounds on the size of the omitted variable bias for a broad class of causal … bound on the bias depends only on the additional variation that the latent variables create both in the outcome and in the … (in explaining treatment and outcome variation) are sufficient to place overall bounds on the size of the bias. Finally …

have smaller bias that is flatter as a function of first step smoothing leading to improved small sample properties. Series …

bias and so are important when the first step is machine learning. We derive LR moment conditions for dynamic discrete …

We derive general, yet simple, sharp bounds on the size of the omitted variable bias for a broad class of causal … how the bound on the bias depends only on the additional variation that the latent variables create both in the outcome … variables (in explaining treatment and outcome variation) are sufficient to place overall bounds on the size of the bias …