A useful starting point for assessing the effect of a shock or intervention is a basis of comparison: those affected by a change versus those not affected. But what if everyone is potentially affected in some way? What if there is no obvious benchmark against which differences can be evaluated?
One answer is simply to create your own comparator — stitching together a credible counterfactual using attributes from real-world observations. This synthetic control method is a relatively recent innovation in empirical analysis. It offers a smart tool for identifying casual effects — under the right conditions.→