COVID-19 counterfactual evidence. Estimating the effects of school closures

Scholars have started to estimate the effects of non-pharmaceutical interventions reduce health impact COVID-19. However, empirical evidence is highly contested, and since it not known exactly what would happened without those measures, political élites are left free give credit voices that they prefer most. We argue any sensible assessment effectiveness anti-COVID policies requires methodological reflection on actually comparable, how approximate ideal “method difference” theorized by John Stuart Mill. By evaluating school closures as an policy, we provide two examples in which appropriate counterfactuals inductively discovered rather than selected a priori. In first one, use Coarsened Exact Matching (CEM) cross-country setting, while second implement Synthetic Control Method within-country analysis. The article highlights advantages including these techniques toolbox policy scholars, both confirm closures.