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 Centre for Economic Policy Research

Abstract: We develop a novel measure of job-worker allocation quality (JAQ) by exploiting employer-employee data with machine learning techniques. Based on our measure, the quality of job-worker matching correlates positively with individual labor earnings and firm productivity, as well as with market competition, non-family firm status, and employees’ human capital. Management plays a key role in job-worker matching: when managerial hirings and firings persistently raise management quality, the matching of rank-and-file workers to their jobs improves. JAQ can be constructed from any employer-employee data set including workers’ occupations, and used to explore research questions in corporate finance and organization economics.

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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