The inclusive Synthetic Control Method

TL;DR

The paper presents the inclusive synthetic control method (iSCM), which incorporates units potentially affected by an intervention into the donor pool, effectively addressing spillover effects in causal inference.

Contribution

It introduces the iSCM, a novel modification of synthetic control methods that accounts for spillover effects and includes treated units in the donor pool.

Findings

Successfully re-estimated the impact of German reunification on GDP per capita.

Demonstrated the method's ability to handle spillover effects.

Showed that including affected units improves causal inference accuracy.

Abstract

We introduce the inclusive synthetic control method (iSCM), a modification of synthetic control methods that includes units in the donor pool potentially affected, directly or indirectly, by an intervention. This method is ideal for situations where including treated units in the donor pool is essential or where donor units may experience spillover effects. The iSCM is straightforward to implement with most synthetic control estimators. As an empirical illustration, we re-estimate the causal effect of German reunification on GDP per capita, accounting for spillover effects from West Germany to Austria.