Multiply-Robust Causal Change Attribution

arXiv:2404.08839v1 Announce Type: cross
Abstract: Comparing two samples of data, we observe a change in the distribution of an outcome variable. In the presence of multiple explanatory variables, how much of the change can be explained by each possible cause? We develop a new estimation strategy that, given a causal model, combines regression and re-weighting methods to quantify the contribution of each causal mechanism. Our proposed methodology is multiply robust, meaning that it still recovers the target parameter under partial …

abstract arxiv attribution causal change cs.lg data distribution econ.em explained multiple observe regression robust samples stat.me stat.ml strategy type variables