Identification and estimation of causal effects of multiple treatments under the conditional independence assumption 论文

2001ZEW economic studies引用 713

Advanced Causal Inference TechniquesBayesian Modeling and Causal InferenceQualitative Comparative Analysis Research

Bayesian Modeling and Causal Inference Advanced Causal Inference Techniques Qualitative Comparative Analysis Research

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The assumption that the assignment to treatments is ignorable conditional on attributes plays an important role in the applied statistic and econometric evaluation literature. Another term for it is conditional independence assumption (CIA). This paper discusses identification using CIA when there are more than two types of mutually exclusive treatments. It turns out that low dimensional balancing scores, similar to the ones valid in the case of only two treatments, exist and can be used for identification of various causal effects. Therefore, a comparable reduction of the dimension of the estimation problem is achieved and the approach retains its basic simplicity. The paper also outlines a matching estimator potentially suitable in that framework.

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Michael Lechner

Identification and estimation of causal effects of multiple treatments under the conditional independence assumption 论文

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