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.

This study investigates the determinants of human capital stocks, measured by the Penn World Table data, in the panel dataset of 122 countries from 1996 to 2019. The special role is given to the World Pandemics Uncertainty index to measure pandemics uncertainty across countries. The paper finds that per capita gross domestic product and population increase human capital stocks. The decline in fertility rates leads to a higher level of human capital. The interesting evidence is that pandemics' uncertainty decreases human capital. These findings are valid when we focus on both the high-income and the middle/low-income economies. These results are against the Becker-Lewis theory's validity since sources of uncertainty are negatively related to human capital.