This paper examines the effects of stringency measures (provided by the Oxford Coronavirus Government Response Tracker) and total time spent away from home (provided by the Google COVID-19 Community Mobility Reports) on the COVID-19 outcomes (measured by total COVID-19 cases and total deaths related to the COVID-19) in the United States. The paper focuses on the daily data from March 11, 2020 to August 13, 2021. The ordinary least squares and the machine learning estimators show that stringency measures are negatively related to the COVID-19 outcomes. A higher time spent away from home is positively associated with the COVID-19 outcomes. The paper also discusses the potential economic implications for the United States.
All Keywords
【저자키워드】 COVID-19 outcomes, social mobility, stringency measures, the United States economy, ordinary least squares, machine learning estimator, 【초록키워드】 COVID-19, outcome, outcomes, response, Mobility, death, Google, Oxford, COVID-19 case, measure, Effect, The United States, implication, provided, ordinary least square, 【제목키워드】 COVID-19, Mobility, measure, Effect, the United State,
【저자키워드】 COVID-19 outcomes, social mobility, stringency measures, the United States economy, ordinary least squares, machine learning estimator, 【초록키워드】 COVID-19, outcome, outcomes, response, Mobility, death, Google, Oxford, COVID-19 case, measure, Effect, The United States, implication, provided, ordinary least square, 【제목키워드】 COVID-19, Mobility, measure, Effect, the United State,