Digital technologies, labor market flows and training: Evidence from Italian employer-employee data - Valeria Cirillo; Andrea Mina; Andrea Ricci (Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM), 2024)
New technologies can shape the production process by affecting the way in which inputs are embedded in the organization, their quality, and their use. Using an original employer-employee dataset that merges firm-level data on digital technology adoption and other characteristics of production with employee-level data on worker entry and exit rates from the administrative archive of the Italian Ministry of Labor, this paper explores the effects of new digital technologies on labor flows in the Italian economy. Using a Difference-in-Difference approach, we show that digital technologies lead to an increase in the firm-level hiring rate - particularly for young workers - and reduce the firm-level separation rate. We also find that digital technologies are positively associated with workplace training, proxied by the share of trained employees and the amount of training costs per employee. Furthermore, we explore the heterogeneity of effects related to different technologies (robots, cybersecurity and IoT). Our results are confirmed through several robustness checks.
Keywords: D22; L23; J21; 330; Industry 4.0; Digital technologies; Hiring rate; Separation rate; Skills; Training; Employer-Employee data