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Working Paper No. 1427

JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality

Working Paper
Reference
Coraggio, Luca, Marco Pagano, Annalisa Scognamiglio and Joacim Tåg (2022). “JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality”. IFN Working Paper No. 1427. Stockholm: Research Institute of Industrial Economics (IFN).

Authors
Luca Coraggio, Marco Pagano, Annalisa Scognamiglio, Joacim Tåg

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 turns out to play a key role in job-worker matching: when existing managers are replaced by better ones, the quality of rank-and-file workers’ job matches improves. JAQ can be constructed for any employer-employee data including workers’ occupations, and used to explore research questions in corporate finance and organization economics.