The synthetic control method (SCM) allows estimating the causal effect of an intervention in settings where panel data on a small number of treated and control units are available. We show that the existing SCM, as well as its extensions, can be easily modified to estimate how much of the ``total'' effect goes through observed causal channels. Our new mediation analysis synthetic control (MASC) method requires additional assumptions that are arguably mild in many settings. We illustrate the implementation of MASC in an empirical application estimating the direct and indirect effects of an anti-smoking intervention (California's Proposition 99).

We have benefited from comments by Simone De Angelis and participants at several seminars, workshops, and conferences. The views expressed in this paper are those of the authors and do not necessarily reflect those of the Bank of Italy. Addresses for correspondence: Giovanni Mellace (giome@sam.sdu.dk) and Alessandra Pasquini (alessandra.pasquini@bancaditalia.it)