Lockdown effects in US states: an artificial counterfactual approach

Autor:	Carneiro, Carlos B., Ferreira, Iúri H., Medeiros, Marcelo C., Pires, Henrique F., Zilberman, Eduardo
Rok vydání:	2020
Předmět:	Statistics - Applications Economics - Econometrics Economics - General Economics Statistics - Methodology Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	We adopt an artificial counterfactual approach to assess the impact of lockdowns on the short-run evolution of the number of cases and deaths in some US states. To do so, we explore the different timing in which US states adopted lockdown policies, and divide them among treated and control groups. For each treated state, we construct an artificial counterfactual. On average, and in the very short-run, the counterfactual accumulated number of cases would be two times larger if lockdown policies were not implemented. Comment: Updated versions of this paper will be available on http://139.82.34.174/mcm/
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2009.13484 Zobrazit plný text záznamu View this record from Arxiv