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新冠疫情期间领取失业救济金人群中的种族和族裔差异。

Racial and ethnic disparities in who receives unemployment benefits during COVID-19.

作者信息

Mar Don, Ong Paul, Larson Tom, Peoples James

机构信息

Economics Department, San Francisco State University, San Francisco, CA USA.

UCLA Luskin School of Public Affairs, Los Angeles, CA USA.

出版信息

SN Bus Econ. 2022;2(8):102. doi: 10.1007/s43546-022-00283-6. Epub 2022 Jul 23.

Abstract

The impact of COVID-19 on job displacement in the United States has been unevenly experienced by race, ethnicity, and the socioeconomically disadvantaged. Although unemployment benefits may mitigate the effects of job displacement, this social safety net is also unevenly distributed across workers. We examine racial/ethnic differences in receiving unemployment benefits among workers displaced by the pandemic. We use data from the US Census Household Pulse Survey (HPS), which is specifically designed to capture the real time effects of the pandemic across a wide spectrum of social issues. (US Census, 2020) Unlike the Current Population Survey (CPS) data used in the monthly unemployment rate calculations, the HPS data allow us to identify workers directly displaced from their jobs by the pandemic. We analyze over 1.3 million HPS interviews from the first stage of the pandemic when the disruptions to the labor market were the most severe, covering the period from June 11, 2020 to December 22, 2020. We contribute to the literature on the labor market effects of the pandemic in two ways. One, the HPS data allow us to identify workers who directly experienced job loss as a result of the disruptions created by COVID-19 and to determine who did not receive unemployment insurance. Two, we present both bivariate and multivariate analyses to examine racial/ethnic disparities for five groups: non-Hispanic whites, Blacks, Hispanic, Asian, and non-Hispanic Other workers. We find that Black and Hispanic workers are more likely to be unemployed without Unemployment Insurance (UI). Black workers are 12.0% of the employed but 17.5% of displaced workers without UI. Hispanic workers are even more affected. Hispanic workers are 15.6% of the employed, but are 23.4% of all displaced workers without UI. Although there are limitations to using the HPS data-the survey was administered online in only English and Spanish and occupational and industry data are not available for displaced workers, the results still provide valuable insights informing the current policy debate about the effects of expanding UI.

摘要

新冠疫情对美国就业岗位流失的影响在不同种族、族裔以及社会经济弱势群体中体现得并不均衡。尽管失业救济金可能会减轻岗位流失的影响,但这种社会安全网在不同工人之间的分配也不均衡。我们研究了因疫情而失业的工人在领取失业救济金方面的种族/族裔差异。我们使用了美国人口普查局的家庭脉搏调查(HPS)数据,该调查专门用于捕捉疫情在广泛社会问题上的实时影响。(美国人口普查局,2020年)与用于计算月度失业率的当前人口调查(CPS)数据不同,HPS数据使我们能够识别那些因疫情而直接失去工作的工人。我们分析了疫情第一阶段超过130万次HPS访谈,当时劳动力市场受到的干扰最为严重,涵盖2020年6月11日至2020年12月22日这一时期。我们从两个方面为有关疫情对劳动力市场影响的文献做出了贡献。其一,HPS数据使我们能够识别那些因新冠疫情造成的干扰而直接经历失业的工人,并确定哪些人没有领取失业保险。其二,我们进行了双变量和多变量分析,以研究五个群体的种族/族裔差异:非西班牙裔白人、黑人、西班牙裔、亚裔以及非西班牙裔其他工人。我们发现,黑人和西班牙裔工人在没有失业保险(UI)的情况下更有可能失业。黑人工人占就业人口的12.0%,但在没有UI的失业工人中占17.5%。西班牙裔工人受到的影响更大。西班牙裔工人占就业人口的15.6%,但在所有没有UI的失业工人中占23.4%。尽管使用HPS数据存在局限性——该调查仅以英语和西班牙语在线进行,且无法获取失业工人的职业和行业数据,但研究结果仍提供了有价值的见解,为当前关于扩大UI影响的政策辩论提供了参考。

相似文献

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An Intersectional Analysis of COVID-19 Unemployment.新冠疫情导致失业的交叉性分析
J Econ Race Policy. 2020;3(4):270-281. doi: 10.1007/s41996-020-00075-w. Epub 2020 Dec 15.

本文引用的文献

3
An Intersectional Analysis of COVID-19 Unemployment.新冠疫情导致失业的交叉性分析
J Econ Race Policy. 2020;3(4):270-281. doi: 10.1007/s41996-020-00075-w. Epub 2020 Dec 15.

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