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We handle a Main problem in causal inference: estimating heterogeneous therapy consequences employing panel details with normal treatment designs.
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With this perform, we suggest and Appraise a completely new approach that 1st partitions observations into disjoint clusters with comparable cure effects employing a regression tree, and then leverages the (assumed) low-rank structure with the panel facts to estimate the normal procedure influence for every cluster.
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