Motoyama, Y. (2022) Is COVID-19 causing more business closures in poor and minority neighborhoods

Abstract

• The paper addresses economic damage from COVID-19 at the neighborhood level in urban areas, particularly those with high poor or minority populations.

• Uses InfoGroup Historic Business Data and Google Map API to analyze business closures in Franklin County, Ohio (Columbus Metropolitan Area).

• Key findings include high closure rates in the retail and restaurant sectors but no significant disadvantage observed for communities of color or low-income neighborhoods.

Introduction

• The COVID-19 pandemic has severely stressed the U.S. economy due to lockdowns, stay-at-home orders, and health impacts.

• Existing research provides little insight into urban crisis concentration related to business closures.

• The article aims to estimate neighborhood-level business closures, revealing varied impacts across sectors and demographics.

Methodology

• Combines InfoGroup Business Data and Google Map API to estimate business closures in Franklin County.

• The analysis excludes certain business types and accounts for geocoding discrepancies.

• Descriptive analysis shows significant variation in closure rates among sectors.

Descriptive Analysis

Business Sector Overview

• 17,944 businesses were evaluated, with 2,458 closures noted, translating to a 13.8% closure rate (double the BDS exit rate of 7%).

• Highest closure rates observed:

  • Educational services: 23.2%

  • Arts and recreation: 20.5%

  • Accommodation & food: 17.8%

• Significant sectoral differences identified, notably in the arts, educational services, and food industries.

Geographical Analysis

• Visual data shows concentrated closures in downtown Columbus and along prominent retail corridors.

• Generated detailed locality closure rates indicating neighborhoods with specific demographic trends.

Regression Analysis

Neighborhood Variables

• Logistic regression confirms that businesses in predominantly Black or high poverty neighborhoods were not significantly more likely to close than those in downtown.

• Notable exceptions include:

  • Higher closure likelihood in educational and recreation sectors.

  • Latinx populations correlated with lower closure rates.

Key Findings

• Latino business communities show resilience, possibly due to essential jobs held in contrasting sectors.

• Unexpected closures higher in areas near educational institutions, questioning previous assumptions of pressures based on demographics.

Discussion

• Contrary to popular narratives, neighborhoods with concentrations of racial or ethnic minorities did not demonstrate higher business closure rates during the pandemic.

• Closure rates among minority neighborhoods varied, with Latinx neighborhoods showing resistance to economic downturns.

• Downtown areas faced unique challenges, exacerbated by protests and civil unrest in summer 2020.

• Overall closure effects suggest sectors like retail and food services, typically vulnerable, require targeted policy interventions to recover.

Limitations

• Data dependency on InfoGroup and Google API may lead to underreporting or misclassification of closures.

• Gaps in demographic data analytics potentially impact conclusions regarding the relationship between neighborhood structure and business activity.

Conclusion

• The COVID-19 pandemic revealed significant variances in business resilience across sectors and neighborhoods in Franklin County.

• Findings emphasize the importance of localized economic strategies to support recovery from closures, particularly in affected service sectors and urban areas.

• Future research should focus on longitudinal data to understand long-term impacts of closures and recovery strategies.