The Flow Approach to Labor Markets: New Data Sources and Micro–Macro Links
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New data sources and products developed by the Bureau of Labor Statistics and the Bureau of the Census highlight the fluid character of U.S. labor markets. Private sector job creation and destruction rates average nearly 8 percent of employment per quarter. Worker flows in the form of hires and separations are more than twice as large. The data also underscores the lumpy nature of micro-level employment adjustments. More than two-thirds of job destruction occurs at establishments that shrink by more than 10 percent within the quarter, and more than one-fifth occurs at those that shut down. Our study also uncovers highly nonlinear relationships of worker flows to employment growth and job flows at the micro level. These micro relations interact with movements over time in the cross-sectional density of establishment growth rates to produce recurring cyclical patterns in aggregate labor market flows. Cyclical movements in the layoffs-separations ratio, for example, and the propensity of separated workers to become unemployed reflect distinct micro relations for quits and layoffs. A dominant role for the job-finding rate in accounting for unemployment movements in mild downturns and a bigger role for the job-loss rate in severe downturns reflect distinct micro relations for hires and layoffs.
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Firms may respond to technology changes by reducing hiring before laying off existing workers.
“Firms may respond to changes in technology by reducing hiring before laying off existing workers (Davis, Faberman, and Haltiwanger 2006).”
From The Early Impacts of AI on Employment among Recent College Graduates (2026) · cites this paper as Davis, Faberman, and Haltiwanger 2006
The section “Heterogeneity and the Micro Distribution of Labor Market Flows” (page unavailable) says employers can reduce their workforce by curtailing new hires and relying on attrition. It does not tie that response to technology changes or establish that reduced hiring precedes layoffs. (LLM, conf=0.85)
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- Robert Axtell. Endogenous Firm Dynamics and Labor Flows via Heterogeneous Agents ✶ ✶Support from the John D. and Catherine T. MacArthur Foundation, the National Science Foundation (0738606), the Small Business Administration (SBAHQ-05-Q-0018), and the Mercatus Center at George Mason is gratefully acknowledged. I have no relevant or material financial interests that relate to the research described in this paper or the associated model. Earlier versions of this work were presented at research institutions (Aix-en-Provence, Arizona State, Brookings, Carnegie Mellon, Emory, Esalen, Essex, George Mason, Georgia, Georgia Tech, James Madison, Leicester, Leiden, Limerick, Nanyang Technological University, New School for Social Research, Office of Financial Research, Oxford, Queen Mary and Westfield, Sant' Anna (Pisa), Santa Fe Institute, Turino) and conferences (Eastern Economic Association, INFORMS, Society for Computational Economics, Southern Economic Association) where comments from attendees yielded significant improvements. For helpful feedback on the manuscript I am grateful to Zoltan Acs, Luis Amaral, Brian Arthur, David Audretsch, Bob Axelrod, Bob Ayres, Eric Beinhocker, Margaret Blair, Pete Boettke, David Canning, Kathleen Carley, John Chisholm, Alex Coad, Herbert Dawid, Art DeVany, Bill Dickens, Kathy Eisenhardt, Joshua Epstein, Doyne Farmer, Rich Florida, Duncan Foley, Xavier Gabaix, Chris Georges, Herb Gintis, Joe Harrington, John Holland, Stu Kauffman, Steve Kimbrough, Paul Kleindorfer, Blake LeBaron, Axel Leijonhufvud, Bob Litan, Francesco Luna, Jim March, Michael Maouboussin, Greg McRae, Benoit Morel, Scott Moss, Paul Omerod, J. Barkley Rosser Jr., Martin Shubik, Gene Stanley, Dan Teitelbaum, Leigh Tesfatsion, Sid Winter and several people who are no longer with us: Per Bak, Michael Cohen, Ben Harrison, Steve Klepper, Sam Kotz, and Benoit Mandelbrot. The late Herb Simon inspired and encouraged the work. Anna Nelson and Omar Guerrero each advanced the work through their Ph.D. dissertations. Thanks are due Miles Parker and Gabriel Balan for implementing the model in Java, first in Ascape and then in Mason. Errors are my own 157-213. [Crossref] · DOI · Paper page
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Sorted by citations
Axtell, R. (2018) · Handbook of Computational Economics · doi:10.1016/bs.hescom.2018.05.001 · Cited by 13 · see citing works
The Early Impacts of AI on Employment among Recent College Graduates
Fairlie, R., & Wu, J. (2026) · doi:10.3386/w35796
- Authors
- Davis, S. J., Faberman, R. J., & Haltiwanger, J.
- Affiliations
- American Enterprise Institute (US)
- Bureau of Labor Statistics (US)
- National Bureau of Economic Research (US)
- Venue
- Journal of Economic Perspectives
- Publisher
- American Economic Association
- Published
- 2006-05-01
- Volume
- 20
- Issue
- 3
- Pages
- 3-26
- ISSN
- 0895-3309 (ISSN-L)
- OpenAlex
- W2111910167
- Cited by
- 429
- References
- 0
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 5 · 2023: 15 · 2022: 15 · 2021: 16 · 2020: 20 · 2019: 10 · 2018: 15 · 2017: 24 · 2016: 38 · 2015: 31 · 2014: 38 · 2013: 32 · 2012: 41
- FWCI
- 48.58
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Journal of Economic Perspectives (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Unemployment and Economic Growth
- Social Sciences › Political Science and International Relations › Education and Labor Relations
- Keywords
- labor market flows, job creation and destruction, worker flows, business closures, job creation, micro-macro link, business cycles, layoffs, voluntary turnover, job finding rate, unemployment
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