Social vulnerability and local economic outcomes during the COVID-19 pandemic
ABSTRACTThis 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 disaste...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | Regional Studies, Regional Science |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/21681376.2023.2274097 |
| _version_ | 1797225125878169600 |
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| author | Jim Lee |
| author_facet | Jim Lee |
| author_sort | Jim Lee |
| collection | DOAJ |
| description | ABSTRACTThis 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. |
| first_indexed | 2024-03-08T21:21:01Z |
| format | Article |
| id | doaj.art-28fa97363abc44baa6eb82726547b42c |
| institution | Directory Open Access Journal |
| issn | 2168-1376 |
| language | English |
| last_indexed | 2024-04-24T14:04:03Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Regional Studies, Regional Science |
| spelling | doaj.art-28fa97363abc44baa6eb82726547b42c2024-04-03T10:52:34ZengTaylor & Francis GroupRegional Studies, Regional Science2168-13762023-12-0110184586910.1080/21681376.2023.2274097Social vulnerability and local economic outcomes during the COVID-19 pandemicJim Lee0College of Business, Texas A&M University-Corpus Christi, Corpus Christi, USAABSTRACTThis 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.https://www.tandfonline.com/doi/10.1080/21681376.2023.2274097COVID-19 pandemicsocial vulnerabilityspatial dependencespatial heterogeneitygeographically and temporally weighted autoregressive model |
| spellingShingle | Jim Lee Social vulnerability and local economic outcomes during the COVID-19 pandemic Regional Studies, Regional Science COVID-19 pandemic social vulnerability spatial dependence spatial heterogeneity geographically and temporally weighted autoregressive model |
| title | Social vulnerability and local economic outcomes during the COVID-19 pandemic |
| title_full | Social vulnerability and local economic outcomes during the COVID-19 pandemic |
| title_fullStr | Social vulnerability and local economic outcomes during the COVID-19 pandemic |
| title_full_unstemmed | Social vulnerability and local economic outcomes during the COVID-19 pandemic |
| title_short | Social vulnerability and local economic outcomes during the COVID-19 pandemic |
| title_sort | social vulnerability and local economic outcomes during the covid 19 pandemic |
| topic | COVID-19 pandemic social vulnerability spatial dependence spatial heterogeneity geographically and temporally weighted autoregressive model |
| url | https://www.tandfonline.com/doi/10.1080/21681376.2023.2274097 |
| work_keys_str_mv | AT jimlee socialvulnerabilityandlocaleconomicoutcomesduringthecovid19pandemic |