Replication Data for: COVID-19 counterfactual evidence. Estimating the effects of school closures
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Scholars have started to estimate the effects of non-pharmaceutical interventions to reduce the health impact of COVID-19. However, the empirical evidence is highly contested, and since it is not known exactly what would have happened without those measures, political élites are left free to give credit to the voices that they prefer the most. We argue that any sensible assessment of the effectiveness of anti-COVID policies requires methodological reflection on what is actually comparable, and how to approximate the ideal “method of difference” theorized by John Stuart Mill. By evaluating the effectiveness of school closures as an anti-COVID policy, we provide two examples in which appropriate counterfactuals are inductively discovered rather than selected a priori. In the first one, we use Coarsened Exact Matching (CEM) in a cross-coun' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Comparative analysis","Counterfactual","Covid-19","Evaluation","School closures"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Scholars have started to estimate the effects of non-pharmaceutical interventions to reduce the health impact of COVID-19. However, the empirical evidence is highly contested, and since it is not known exactly what would have happened without those measures, political élites are left free to give credit to the voices that they prefer the most. We argue that any sensible assessment of the effectiveness of anti-COVID policies requires methodological reflection on what is actually comparable, and how to approximate the ideal “method of difference” theorized by John Stuart Mill. By evaluating the effectiveness of school closures as an anti-COVID policy, we provide two examples in which appropriate counterfactuals are inductively discovered rather than selected a priori. In the first one, we use Coarsened Exact Matching (CEM) in a cross-coun' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Scholars have started to estimate the effects of non-pharmaceutical interventions to reduce the health impact of COVID-19. However, the empirical evidence is highly contested, and since it is not known exactly what would have happened without those measures, political élites are left free to give credit to the voices that they prefer the most. We argue that any sensible assessment of the effectiveness of anti-COVID policies requires methodological reflection on what is actually comparable, and how to approximate the ideal “method of difference” theorized by John Stuart Mill. By evaluating the effectiveness of school closures as an anti-COVID policy, we provide two examples in which appropriate counterfactuals are inductively discovered rather than selected a priori. In the first one, we use Coarsened Exact Matching (CEM) in a cross-coun
Comparative analysis; Counterfactual; Covid-19; Evaluation; School closures