JAQ of all trades: Job mismatch, firm productivity and managerial quality - Luca Corragio; Marco Pagano; Annalisa Scognamiglio; Joacim Tåg (Research Institute of Industrial Economics (IFN), 2022)
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: D22; D23; D24; G34; J24; J31; J62; L22; L23; M12; M54; 330; jobs; workers; matching; mismatch; machine learning; productivity; management