Luca Coraggio (), Marco Pagano (), Annalisa Scognamiglio () and Joacim Tåg ()
Luca Coraggio: University of Naples Federico II
Marco Pagano: University of Naples Federico II, and, Postal: Research Institute of Industrial Economics, Stockholm, Sweden
Annalisa Scognamiglio: University of Naples Federico II, and, Postal: Research Institute of Industrial Economics, Stockholm, Sweden
Joacim Tåg: Research Institute of Industrial Economics (IFN), Postal: Research Institute of Industrial Economics, Box 55665, SE-102 15 Stockholm, Sweden
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.
45 pages, First version: April 1, 2022. Revised: October 24, 2022.
Full text files
wp1427.pdf Full text
Questions (including download problems) about the papers in this series should be directed to Elisabeth Gustafsson ()
Report other problems with accessing this service to Sune Karlsson ().
This page generated on 2022-10-27 09:45:11.