  We propose a novel approach for causal mediation analysis based on
changes-in-changes assumptions restricting unobserved heterogeneity over time.
This allows disentangling the causal effect of a binary treatment on a
continuous outcome into an indirect effect operating through a binary
intermediate variable (called mediator) and a direct effect running via other
causal mechanisms. We identify average and quantile direct and indirect effects
for various subgroups under the condition that the outcome is monotonic in the
unobserved heterogeneity and that the distribution of the latter does not
change over time conditional on the treatment and the mediator. We also provide
a simulation study and an empirical application to the Jobs II programme.
