Working Paper Series,
Research Institute of Industrial Economics

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

JEL-codes: D22; D23; D24; G34; J24; J31; J62; L22; L23; M12; M54

Language: English

45 pages, First version: April 1, 2022. Revised: October 24, 2022.

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