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1.
ssrn; 2021.
Preprint in English | PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.3616893

ABSTRACT

Digital technologies may make some tasks, jobs, and firms more resilient to unanticipated shocks. We extract data from over 200 million U.S. job postings to construct an index for firms’ resilience to the COVID-19 pandemic by assessing the work-from-home (WFH) feasibility of their labor demand. Using a difference-in-differences framework, we find that public firms with high pre-pandemic WFH index values had significantly higher sales, net incomes, and stock returns than their peers during the pandemic. Our results indicate that firms with higher digital resilience, as measured through our pre-pandemic WFH index, performed significantly better in general, and in non-essential industries in particular, where WFH feasibility was necessary to continue operation. The ability to use digital technologies to work remotely also mattered more in non-high-tech industries than in high-tech ones. Lastly, we find evidence that firms with lower pre-pandemic WFH feasibility attempted to catch up to their more resilient competitors via greater software investment. This is consistent with a complementarity between digital technologies and WFH practices. Our study's results are robust to a variety of empirical specifications and provide a first look at how WFH practices improved resilience to a major, unanticipated social and economic shock.


Subject(s)
COVID-19
3.
Sci Rep ; 10(1): 20021, 2020 11 18.
Article in English | MEDLINE | ID: covidwho-933724

ABSTRACT

An ongoing novel coronavirus outbreak (COVID-19) started in Wuhan, China, in December 2019. Currently, the spatiotemporal epidemic transmission, prediction, and risk are insufficient for COVID-19 but we urgently need relevant information globally. We have developed a novel two-stage simulation model to simulate the spatiotemporal changes in the number of cases and estimate the future worldwide risk. Simulation results show that if there is no specific medicine for it, it will form a global pandemic. Taiwan, South Korea, Hong Kong, Japan, Thailand, and the United States are the most vulnerable. The relationship between each country's vulnerability and days before the first imported case occurred shows an exponential decrease. We successfully predicted the outbreak of South Korea, Japan, and Italy in the early stages of the global pandemic based on the information before February 12, 2020. The development of the epidemic is now earlier than we expected. However, the trend of spread is similar to our estimation.


Subject(s)
COVID-19/epidemiology , Models, Statistical , Pandemics/statistics & numerical data , COVID-19/transmission , Humans , Spatio-Temporal Analysis
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