JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality

Luca Coraggio, Marco Pagano, Annalisa Scognamiglio and TÃ¥g, Joacim
Authors registered in the RePEc Author Service: Joacim Tåg

No 17167, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: 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.

Keywords: Jobs; Workers; Matching; Mismatch; Machine learning; Productivity; Management (search for similar items in EconPapers)
JEL-codes: D22 D23 D24 G34 J24 J31 J62 L22 L23 M12 M54 (search for similar items in EconPapers)
Date: 2022-04
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Related works:
Journal Article: JAQ of all trades: Job mismatch, firm productivity and managerial quality (2025)
Working Paper: JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality (2024)
Working Paper: JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality (2022)
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