The practical relevance of several concepts of exogeneity of treatments
for the estimation of causal parameters based on observational data are
discussed. We show that the traditional concepts, such as strong ignorability
and weak and super-exogeneity, are too restrictive if interest lies
in average effects (i.e. not on distributional effects of the treatment). We
suggest a new definition of exogeneity, KL−exogeneity. It does not rely
on distributional assumptions and is not based on counterfactual random
variables. As a consequence it can be empirically tested using a proposed
test that is simple to implement and is distribution-free.
2006. Vol. 132, 527-543 p.