Question

Why does the synthetic control method work best when the treated unit is not extreme (very high or very low) in terms of observable characteristics and pretreatment trends?

Answer 1

The synthetic control method is a statistical method used to evaluate the effect of an intervention in comparative case studies. It involves the construction of a weighted combination of groups used as controls, to which the treatment group is compared.Results Advantages of the synthetic control method are that it offers an approach suitable when there is a small number of treated units and control units and it does not rely on parallel preimplementation trends like difference in difference methods.

The Synthetic Control Method as a Tool to Understand State Policy Identifying good governance depends on accurately evaluating policies for their efficiency and effectiveness, and many tools are available for that purpose. Case studies of regional economies are an often-used example in which policies are evaluated through detailed examinations of economic conditions before and after the policies are implemented. Because those analyses are qualitative rather than quantitative, rigorously identifying comparison groups whose outcomes can be contrasted with the outcome of the region undergoing the policy change is difficult. But without those control groups, separating the policy’s effect from the effects of nonpolicy variables is nearly impossible. Nearby regions are sometimes used as controls for lack of alternatives, but geographic proximity is a poor metric for similarity if regions have substantial differences in political or cultural environments. Further, policies may spill across borders, confounding any comparison. The qualitative approach also impedes the analyst’s attempt to generalize the analysis beyond the case at hand because few quantitative results can be applied to similar situations. Measures of similarity can be difficult to define, and no measures of statistical precision or accuracy exist. An increasingly popular method for policy evaluation, the synthetic control method (SCM), addresses those problems. It provides quantitative support for case studies by creating a synthetic control region that simulates what the outcome path of a region would be if it did not undergo a particular policy intervention. The SCM creates this hypothetical counterfactual region by taking the weighted average of preintervention outcomes from selected donor regions. The donor regions that combine to form the synthetic control are selected from a pool of potential candidates. Predictor variables that affect the outcome and the outcome variable itself before the policy is enacted determine the selection of donor regions and weights. The resulting synthetic closely matches the affected region’s outcome before policy enactment and is a control for the affected region following enactment. After policy enactment, the difference in outcomes between the affected region and its synthetic control counterpart reveals the policy’s effectiveness.