Abstract Understanding causal relationships is one of the most important goals modern science. So far, inference literature has focused almost exclusively on outcomes coming from Euclidean space Rp. However, it increasingly common that complex datasets are best summarized as data points in nonlinear spaces. In this paper, we present a novel framework effects for Wasserstein cumulative distribut...