Arbeitspapier
JAQ of all trades: Job mismatch, firm productivity and managerial quality
Does the matching between workers and jobs help explain productivity differentials across firms? To address this question we develop a job-worker allocation quality measure (JAQ) by combining employer-employee administrative data with machine learning techniques. The proposed measure is positively and significantly associated with labor earnings over workers' careers. At firm level, it features a robust positive correlation with firm productivity, and with managerial turnover leading to an improvement in the quality and experience of management. JAQ can be constructed for any employer-employee data including workers' occupations, and used to explore the effect of corporate restructuring on workers' allocation and careers.
- Sprache
-
Englisch
- Erschienen in
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Series: IFN Working Paper ; No. 1427
- Klassifikation
-
Wirtschaft
Firm Behavior: Empirical Analysis
Organizational Behavior; Transaction Costs; Property Rights
Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
Mergers; Acquisitions; Restructuring; Voting; Proxy Contests; Corporate Governance
Human Capital; Skills; Occupational Choice; Labor Productivity
Wage Level and Structure; Wage Differentials
Job, Occupational, and Intergenerational Mobility; Promotion
Firm Organization and Market Structure
Organization of Production
Personnel Management; Executives; Executive Compensation
Personnel Economics: Labor Management
- Thema
-
jobs
workers
matching
mismatch
machine learning
productivity
management
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Corragio, Luca
Pagano, Marco
Scognamiglio, Annalisa
Tåg, Joacim
- Ereignis
-
Veröffentlichung
- (wer)
-
Research Institute of Industrial Economics (IFN)
- (wo)
-
Stockholm
- (wann)
-
2022
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:45 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Corragio, Luca
- Pagano, Marco
- Scognamiglio, Annalisa
- Tåg, Joacim
- Research Institute of Industrial Economics (IFN)
Entstanden
- 2022