Is Bayesian estimation useful for causal analyses?
For analyses like randomized experiments or even observational studies of natural experiments, we want unbiased estimators of the causal effect (unbiased ATE or ATT). This lends itself really well to frequentist methods where estimators are unbiased (like OLS). However, unbiasedness doesn't seem to be to goal for Bayesian analyses.
So is there a good reason to use Bayesian estimation when the treatment is randomized so causality can be identified?