JAQ of all trades: Job mismatch, firm productivity and managerial quality☆

• 成果类型: Article
• 署名作者: Coraggio, Luca; Pagano, Marco; Scognamiglio, Annalisa; Tag, Joacim
• 署名单位: University of Naples Federico II; University of Naples Federico II; Hanken School of Economics; Research Institute of Industrial Economics (IFN)
• 刊物名称: JOURNAL OF FINANCIAL ECONOMICS
• ISSN/ISSBN: 0304-405X
• DOI: 10.1016/j.jfineco.2024.103992
• 发表日期: 2025
• 关键词: jobs; workers; matching; mismatch; Machine Learning; PRODUCTIVITY; management

摘要

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.