April 4, 2024, 4:44 a.m. | Susan Athey, Raj Chetty, Guido Imbens, Hyunseung Kang

stat.ML updates on arXiv.org arxiv.org

arXiv:1603.09326v4 Announce Type: replace-cross
Abstract: Estimating the long-term effects of treatments is of interest in many fields. A common challenge in estimating such treatment effects is that long-term outcomes are unobserved in the time frame needed to make policy decisions. One approach to overcome this missing data problem is to analyze treatments effects on an intermediate outcome, often called a statistical surrogate, if it satisfies the condition that treatment and outcome are independent conditional on the statistical surrogate. The validity …

abstract arxiv challenge decisions econ.em effects fields index long-term multiple policy role stat.me stat.ml treatment type

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