COVID-19 and Economic Activity in Large U.S. Counties
by Jeong, Hanbat / ICPSR Harvested Dataverse·Updated 3mo ago
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Description
This dataset underpins a dynamic spatial framework modeling the co-evolution of infectious disease transmission, economic activity, and mortality. It was applied to COVID-19 data from large U.S. counties in 2020. The author is Jeong, Hanbat.
Use Cases
Estimate the interactive fixed effects model to simulate counterfactual policy impacts on cases and economic activity.
Analyze the persistence and feedback between economic activity increases and subsequent infection rates.
Simulate optimal long-run policies, such as mask requirements and lockdowns, based on population and network centrality.
Compare suboptimal policy outcomes, like the reported 10% less economic activity and 6,000 times more cases by December 2020.
Strengths
Framework is disease-agnostic and portable to other pathogens with re-estimation.
Enables decision-relevant counterfactual simulations before widespread resistance.
Applied to a specific case (COVID-19 in large U.S. counties in 2020) with quantified policy impacts.
Limitations
Specific data volume (rows, columns) and file formats are unknown.
Application is limited to the context (large U.S. counties, 2020) until re-estimated with new parameters.
Model complexity (multivariate spatial dynamic panel with interactive fixed effects) requires advanced econometric expertise.
Provenance
Source
ICPSR Harvested Dataverse
Collection Method
Developed as part of a research framework for co-evolution modeling; specific data gathering method unknown.
Time Range
2020
Freshness
Last updated metadata indicates 2026-02-23.
Geography
Large U.S. counties
License is unknown. The framework requires re-estimation with context-specific parameters for application to other pathogens or geographies.