Coraggio, LucaPagano, MarcoScognamiglio, AnnalisaTåg, Joacim2025-02-242025-02-242025-02Coraggio , L , Pagano , M , Scognamiglio , A & Tåg , J 2025 , ' JAQ of all trades : Job mismatch, firm productivity and managerial quality ' , Journal of Financial Economics , vol. 164 , 103992 . https://doi.org/10.1016/j.jfineco.2024.10399267404406http://hdl.handle.net/10138/592941We 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.2891597engcc_by_nc_ndinfo:eu-repo/semantics/openAccess512 Business and ManagementJobsMachine learningManagementMatchingMismatchProductivityWorkersKOTA2025?1 - Publication available open access by the publisher2 - Hybrid open access publication channel1 - Self archivedhttp://hdl.handle.net/10138/5929411- Minst en av författarna har en utländsk affiliation1- Publicerad utomlands0- Ingen affiliation med ett företagArticleopenAccess85213504162c3c057ce-4e29-44a0-b8ad-de4f1571bb94