  The credibility revolution advances the use of research designs that permit
identification and estimation of causal effects. However, understanding which
mechanisms produce measured causal effects remains a challenge. A dominant
current approach to the quantitative evaluation of mechanisms relies on the
detection of heterogeneous treatment effects with respect to pre-treatment
covariates. This paper develops a framework to understand when the existence of
such heterogeneous treatment effects can support inferences about the
activation of a mechanism. We show first that this design cannot provide
evidence of mechanism activation without an additional, generally implicit,
assumption. Further, even when this assumption is satisfied, if a measured
outcome is produced by a non-linear transformation of a directly-affected
outcome of theoretical interest, heterogeneous treatment effects are not
informative of mechanism activation. We provide novel guidance for
interpretation and research design in light of these findings.
