{"title":"Social vulnerability and local economic outcomes during the COVID-19 pandemic","authors":"Jim Lee","doi":"10.1080/21681376.2023.2274097","DOIUrl":null,"url":null,"abstract":"This paper investigates factors associated with disparities in the exposure of US counties to the initial COVID-19 economic shock in early 2020 and their disparate economic recovery paths during the pandemic. We focus on three alternative composite measures of social vulnerability to disasters: the Centers for Disease Control and Prevention’s Social Vulnerability Index, the University of South Carolina’s Social Vulnerability Index and the Census Bureau’s Community Resilience Estimate. Empirical evidence under the conventional ‘global’ regression approach supports a cross-sectional correlation between the social vulnerability indices and local economic outcomes during the recovery phase, although the results are equivocal for characterising uneven local economic downturns triggered by the pandemic. Economic outcomes were dominated by other local characteristics, including population density, the share of hospitality employment, government policy measures and unobservable factors. In addition to validating the empirical relevance of the social vulnerability indices in the context of the COVID-19 pandemic, a geographically and temporally weighted autoregressive model offers insights into both disparate and clustering patterns across broad regions in the role of inherent sociodemographic attributes for characterising local economic dynamics over time.","PeriodicalId":46370,"journal":{"name":"Regional Studies Regional Science","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Regional Studies Regional Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/21681376.2023.2274097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 0
Abstract
This paper investigates factors associated with disparities in the exposure of US counties to the initial COVID-19 economic shock in early 2020 and their disparate economic recovery paths during the pandemic. We focus on three alternative composite measures of social vulnerability to disasters: the Centers for Disease Control and Prevention’s Social Vulnerability Index, the University of South Carolina’s Social Vulnerability Index and the Census Bureau’s Community Resilience Estimate. Empirical evidence under the conventional ‘global’ regression approach supports a cross-sectional correlation between the social vulnerability indices and local economic outcomes during the recovery phase, although the results are equivocal for characterising uneven local economic downturns triggered by the pandemic. Economic outcomes were dominated by other local characteristics, including population density, the share of hospitality employment, government policy measures and unobservable factors. In addition to validating the empirical relevance of the social vulnerability indices in the context of the COVID-19 pandemic, a geographically and temporally weighted autoregressive model offers insights into both disparate and clustering patterns across broad regions in the role of inherent sociodemographic attributes for characterising local economic dynamics over time.
期刊介绍:
Regional Studies, Regional Science is an interdisciplinary open access journal from the Regional Studies Association, first published in 2014. We particularly welcome submissions from authors working on regional issues in geography, economics, planning, and political science. The journal features a streamlined peer-review process and quick turnaround times from submission to acceptance. Authors will normally receive a decision on their manuscript within 60 days of submission.