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

Luca Coraggio, Marco Pagano, Annalisa Scognamiglio (annalisa.sco@gmail.com) and Joacim Tåg
Additional contact information
Annalisa Scognamiglio: University of Naples Federico II, and, Postal: Research Institute of Industrial Economics, Stockholm, Sweden, https://www.ifn.se/en/researchers/affiliated-researchers/annalisa-scognamiglio/

No 1427, Working Paper Series from Research Institute of Industrial Economics

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 J24 J31 L22 L23 M12 M54 (search for similar items in EconPapers)
Pages: 77 pages
Date: 2022-04-01, Revised 2024-12-11
New Economics Papers: this item is included in nep-bec, nep-big, nep-eff, nep-hrm and nep-lma
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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 (2022)
Working Paper: JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality (2022)
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