COVID-19 and Economic Activity in Large U.S. Counties

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