Roy Satyaki, Dutta Ronojoy, Ghosh Preetam
University of North Carolina, Chapel Hill, USA.
Deep Run High School, Glen Allen, VA, USA.
Soc Sci Humanit Open. 2021;3(1):100098. doi: 10.1016/j.ssaho.2020.100098. Epub 2020 Dec 9.
Lockdown measures to curb the spread of COVID-19 has brought the world economy on the brink of a recession. It is imperative that nations formulate administrative policies based on the changing economic landscape. In this work, we apply a statistical approach, called topic modeling, on text documents of job loss notices of 26 US states to identify the specific states and industrial sectors affected economically by this ongoing public health crisis. Our analysis reveals that there is a considerable incongruity in job loss patterns between the pre- and during-COVID timelines in several states and the recreational and philanthropic sectors register high job losses. It further shows that the interplay among several possible socioeconomic factors would lead to job losses in many sectors, while also creating new job opportunities in other sectors such as public service, pharmaceuticals and media, making the job loss trends a key indicator of the world economy. Finally, we compare the low income job loss rates against overall job losses due to COVID-19 in the US counties, and discuss the implications of press reports on reopening businesses and the unemployed workforce being absorbed by other sectors.
为遏制新冠病毒传播而采取的封锁措施已使世界经济濒临衰退边缘。各国必须根据不断变化的经济形势制定行政政策。在这项工作中,我们对美国26个州的失业通知文本文件应用了一种名为主题建模的统计方法,以确定受这场持续的公共卫生危机经济影响的具体州和工业部门。我们的分析表明,几个州在新冠疫情之前和期间的失业模式存在相当大的不一致,娱乐和慈善部门的失业人数众多。分析还进一步表明,几种可能的社会经济因素之间的相互作用将导致许多部门出现失业,同时也在公共服务、制药和媒体等其他部门创造新的就业机会,使失业趋势成为世界经济的一个关键指标。最后,我们比较了美国各县因新冠疫情导致的低收入群体失业率与总体失业率,并讨论了新闻报道对重新开业以及其他部门吸纳失业劳动力的影响。