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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 …
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We propose the use of Kernel Regularized Least Squares (KRLS) for social science modeling and inference problems. KRLS borrows from machine learning methods designed to solve regression and classification problems without relying on linearity or additivity assumptions. The method constructs a...
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