Journal article
Measuring small business dynamics and employment with private-sector real-time data
Journal of public economics, v 250, 105477
Oct 2025
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper proposes a novel methodology to distinguish true business openings and closings from sample churn in private-sector data and to evaluate the representativeness of the resulting estimates by leveraging supplementary high-frequency information on individual business activity. The methodology produces both real-time estimates using only concurrent information and retrospective estimates that incorporate additional information as it becomes available, reflecting a fundamental trade-off between timeliness and accuracy. The methodology is applied to a real-time sample of small businesses widely used during the COVID-19 pandemic to demonstrate its usefulness under extreme circumstances. The application highlights the importance of properly accounting for business openings and closings and at the same time yields two important insights about small business dynamics during the pandemic: (i) small business employment in in-person service sectors experienced larger swings at the beginning of the pandemic than employment of larger businesses, primarily due to a spike in temporary closings; (ii) delayed access to loans from the Paycheck Protection Program significantly increased small business closings but had minimal impact on employment of continuing businesses, suggesting the program’s effectiveness operated primarily through preventing closures rather than preserving jobs at operating businesses.
•Develop a methodology for measuring business dynamics based on private-sector real-time data.•Key aspects include distinguishing true business openings and closings from sample churn and addressing selection bias.•Demonstrate the method’s value by examining small business dynamics during the COVID-19 pandemic.•Methodology extends to other economic aggregates and contexts with changing business dynamics.
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Details
- Title
- Measuring small business dynamics and employment with private-sector real-time data
- Creators
- André Kurmann (Corresponding Author) - Drexel UniversityEtienne Lalé - York UniversityLien Ta - Drexel University
- Publication Details
- Journal of public economics, v 250, 105477
- Publisher
- Elsevier
- Number of pages
- 17
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Economics (School of Economics)
- Web of Science ID
- WOS:001571261900001
- Scopus ID
- 2-s2.0-105015348471
- Other Identifier
- 991022098542004721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Economics