Author
Listed:
- Qiannan Shen
(Graduate School of Arts and Science, Boston University, Boston, MA 02115, USA
These authors contributed equally to this work.)
- Dingyuan Liu
(Kenan-Flagler Business School, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
These authors contributed equally to this work.)
- Yue Zou
(Fu Foundation School of Engineering and Applied Science, Columbia University, New York, NY 10027, USA)
- Zhiying Xiao
(Department of Civil, Environmental, and Architectural Engineering, Worcester Polytechnic Institute, Worcester, MA 01609, USA)
- Tongchen Zhang
(Independent Researcher, Chicago, IL 60605, USA)
Abstract
This paper develops a Business Resilience Index (BRI) that measures county-level resilience to natural disasters at a county-quarter frequency for the United States over 2014–2024. The index integrates high-frequency labor market outcomes from the Quarterly Census of Employment and Wages with flood insurance policy information from FEMA, disaster damages from the NOAA Storm Events Database, and social and health determinants from County Health Rankings. Starting from a broad candidate set, we apply an interpretable feature-screening pipeline to retain 79 variables and then use principal component analysis to extract four orthogonal structural dimensions of resilience: market scale, socioeconomic resilience, urban density risk, and industrial economy profile. We construct a domain-weighted strategic index and benchmark it against data-driven and equal-weight alternatives, showing that county rankings are highly stable across weighting schemes. To evaluate whether the BRI aligns with recovery behavior under acute shocks, we implement a matched difference-in-differences event study around two major flood episodes—Texas in 2015Q2 and North Carolina in 2018Q3. Conditional on exposure intensity and matched comparability, higher pre-event BRI counties exhibit earlier stabilization and a stronger post-event employment path relative to lower BRI counties, with differences in magnitude and timing across cases. Overall, the BRI provides an interpretable, high-frequency baseline for identifying capacity constraints that may slow recovery and for supporting preparedness targeting and post-disaster monitoring.
Suggested Citation
Qiannan Shen & Dingyuan Liu & Yue Zou & Zhiying Xiao & Tongchen Zhang, 2026.
"Business Resilience Index (BRI): Evaluating Economic Recovery Through Event-Study Heterogeneity,"
Sustainability, MDPI, vol. 18(8), pages 1-27, April.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:8:p:3980-:d:1921878
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