Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approach

1 code implementation • 29 May 2019 • Falco J. Bargagli-Stoffi, Kristof De-Witte, Giorgio Gnecco

This paper introduces an innovative Bayesian machine learning algorithm to draw interpretable inference on heterogeneous causal effects in the presence of imperfect compliance (e. g., under an irregular assignment mechanism).

BIG-bench Machine Learning Causal Inference