| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w25418 |
| 来源ID | Working Paper 25418 |
| Learning from Coworkers | |
| Gregor Jarosch; Ezra Oberfield; Esteban Rossi-Hansberg | |
| 发表日期 | 2019-01-07 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | We investigate learning at the workplace. To do so, we use German administrative data that contain information on the entire workforce of a sample of establishments. We document that having more highly paid coworkers is strongly associated with future wage growth, particularly if those workers earn more. Motivated by this fact, we propose a dynamic theory of a competitive labor market where firms produce using teams of heterogeneous workers that learn from each other. We develop a methodology to structurally estimate knowledge flows using the full-richness of the German employer-employee matched data. The methodology builds on the observation that a competitive labor market prices coworker learning. Our quantitative approach imposes minimal restrictions on firms' production functions, can be implemented on a very short panel, and allows for potentially rich and flexible coworker learning functions. In line with our reduced form results, learning from coworkers is significant, particularly from more knowledgeable coworkers. We show that between 4 and 9% of total worker compensation is in the form of learning and that inequality in total compensation is significantly lower than inequality in wages. |
| 主题 | Macroeconomics ; Consumption and Investment ; Labor Economics ; Labor Compensation ; Development and Growth ; Innovation and R& ; D |
| URL | https://www.nber.org/papers/w25418 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/583092 |
| 推荐引用方式 GB/T 7714 | Gregor Jarosch,Ezra Oberfield,Esteban Rossi-Hansberg. Learning from Coworkers. 2019. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w25418.pdf（486KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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