Occupational Mobility and the Business Cycle
Open accessAbstract
Do workers sort more randomly across different job types when jobs are harder to find?To answer this question, we study the mobility of male workers among three-digit occupations in the matched files of the monthly Current Population Survey over the 1979-2004 period.We clean individual occupational transitions using the algorithm proposed by Moscarini and Thomsson (2008).We then construct a synthetic panel comprising annual birth cohorts, and we examine the respective roles of three potential determinants of career mobility: individual ex ante worker characteristics, both observable and unobservable, labor market prospects, and ex post job matching.We provide strong evidence that high unemployment somewhat offsets the role of individual worker considerations in the choice of changing career.Occupational mobility declines with age, family commitments and education, but when unemployment is high these negative effects are weaker, and reversed for college education.The cross-sectional dispersion of the monthly series of residuals is strongly countercyclical.As predicted by Moscarini (2001)'s frictional Roy model, the sorting of workers across occupations is noisier when unemployment is high.As predicted by job-matching theory, worker mobility has significant residual persistence over time.Finally, younger cohorts, among those in the sample for most of their working lives, exhibit increasingly low unexplained career mobility.
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Incumbent workers may move to related occupations in other sectors that require similar skill levels.
“Another option for incumbent workers is to move to related occupations in other sectors that require similar skill levels (Moscarini and Vella 2008).”
From Skill-Biased Technical Change, Again? Online Gig Platforms and Local Employment (2025) · cites this paper as Moscarini and Vella 2008
The Introduction (page unavailable) discusses occupational mobility and gives an example of a worker doing the same tasks in different industries. It does not establish that workers move to related occupations in other sectors requiring similar skill levels; its cross-industry example involves the same occupation. (LLM, conf=0.83)
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Skill-Biased Technical Change, Again? Online Gig Platforms and Local Employment
Guo, X., Cheng, Z. (., & Pavlou, P. A. (2025) · Information Systems Research · doi:10.1287/isre.2022.0307 · Cited by 4 · see citing works
- Authors
- Moscarini, G., & Vella, F.
- Affiliations
- National Bureau of Economic Research (US)
- Corresponding author
- Giuseppe Moscarini
- ORCID
- Giuseppe Moscarini
- Venue
- National Bureau of Economic Research
- Publisher
- National Bureau of Economic Research
- Published
- 2008-02
- OpenAlex
- W1551108219
- Cited by
- 55
- References
- 0
- Citations by year
- 2026: 2 · 2024: 4 · 2022: 3 · 2020: 4 · 2019: 2 · 2018: 3 · 2017: 2 · 2016: 3 · 2015: 6 · 2014: 9 · 2013: 4 · 2012: 1
- Type
- report
- Language
- en
- Open access
- green
- doi.org
- Locations
- National Bureau of Economic Research (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Labor market dynamics and wage inequality
- Social Sciences › Political Science and International Relations › Education and Labor Relations
- Social Sciences › Demography › Retirement, Disability, and Employment
- Keywords
- occupational mobility, career mobility, business cycles, unemployment, job matching, worker sorting, job transitions, age, family commitment
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