{"title":"Which workers bear the burden of social distancing?","authors":"Simon Mongey, Laura Pilossoph, Alexander Weinberg","doi":"10.1007/s10888-021-09487-6","DOIUrl":null,"url":null,"abstract":"<p><p>Using data from O<sup>∗</sup>NET, we construct two measures of an occupation's potential exposure to social distancing measures: (i) the ability to conduct that job from home and (ii) the degree of physical proximity to others the job requires. After validating these measures with comparable measures from ATUS as well as realized work-from-home rates during the pandemic, we employ the measures to study the characteristics of workers in these types of jobs. Our results show that workers in low-work-from-home and high-physical-proximity jobs are more economically vulnerable across various measures constructed from the CPS and PSID: they are less educated, of lower income, have fewer liquid assets relative to income, and are more likely renters. Consistent with the idea that high physical proximity or low work-from-home occupations were more exposed to the Coronavirus shock, we show that the types of workers predicted to be employed in them experienced greater declines in employment during the pandemic. We conclude by comparing the aggregate employment losses in these occupations to their employment losses in the 2008 recession, and find evidence that these occupations were disproportionately exposed to the pandemic shock, and not just comprised of more cyclically sensitive workers.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s10888-021-09487-6.</p>","PeriodicalId":51559,"journal":{"name":"Journal of Economic Inequality","volume":"19 3","pages":"509-526"},"PeriodicalIF":3.6000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328128/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic Inequality","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s10888-021-09487-6","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/8/2 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Using data from O∗NET, we construct two measures of an occupation's potential exposure to social distancing measures: (i) the ability to conduct that job from home and (ii) the degree of physical proximity to others the job requires. After validating these measures with comparable measures from ATUS as well as realized work-from-home rates during the pandemic, we employ the measures to study the characteristics of workers in these types of jobs. Our results show that workers in low-work-from-home and high-physical-proximity jobs are more economically vulnerable across various measures constructed from the CPS and PSID: they are less educated, of lower income, have fewer liquid assets relative to income, and are more likely renters. Consistent with the idea that high physical proximity or low work-from-home occupations were more exposed to the Coronavirus shock, we show that the types of workers predicted to be employed in them experienced greater declines in employment during the pandemic. We conclude by comparing the aggregate employment losses in these occupations to their employment losses in the 2008 recession, and find evidence that these occupations were disproportionately exposed to the pandemic shock, and not just comprised of more cyclically sensitive workers.
Supplementary information: The online version contains supplementary material available at 10.1007/s10888-021-09487-6.
期刊介绍:
The Journal of Economic Inequality provides a forum for analysis of ''economic inequality'', broadly defined. Its scope includes: · Theoretical and empirical analysis· Monetary measures of ''well-being'' such as earnings, income, consumption, and wealth; non-monetary measures such as educational achievement and health and health care; multidimensional measures· Inequality and poverty within and between countries, and globally, and their trends over time· Inequalities of opportunity· Income mobility and poverty persistence· The factor distribution of income· Differences in ''well-being'' between socioeconomic groups, for example between men and women, generations, or ethnic groups· The effects of inequality on macroeconomic and other phenomena, and vice versa· Related statistical methods and data issues · Related policy analysis Papers need to prioritize the ''economic inequality'' dimension. For example, papers about trade and inequality, or inequality and growth, should not primarily be about trade or growth (in which case they should target a different journal). The same is true for papers considering the inter-relationships between the income distribution and the labour market, public policy, or demography.
Officially cited as: J Econ Inequal