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来源类型 | Discussion paper |
规范类型 | 论文 |
来源ID | DP17167 |
DP17167 JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality | |
Marco Pagano; Luca Coraggio; Annalisa Scognamiglio; Joacim Tåg | |
发表日期 | 2022-04-01 |
出版年 | 2022 |
语种 | 英语 |
摘要 | 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. |
主题 | Financial Economics ; Labour Economics |
关键词 | Jobs Workers Matching Mismatch Machine learning Productivity Management |
URL | https://cepr.org/publications/dp17167 |
来源智库 | Centre for Economic Policy Research (United Kingdom) |
资源类型 | 智库出版物 |
条目标识符 | http://119.78.100.153/handle/2XGU8XDN/546160 |
推荐引用方式 GB/T 7714 | Marco Pagano,Luca Coraggio,Annalisa Scognamiglio,et al. DP17167 JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality. 2022. |
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