Using detailed administrative microdata for two countries, we build a modeling framework that yields new explanations for the origin of firm sizes, the firm contributions to unemployment, and the job-to-job mobility of workers between firms. Firms are organized as nodes in networks where connections represent low mobility barriers for workers. These labor flow networks are determined empirically, and serve as the substrate in which workers transition between jobs. We show that highly skewed firm size distributions are predicted from the connectivity of firms. Further, our model permits the reconceptualization of unemployment as a local network phenomenon related to both a notion of firm-specific unemployment and the network vicinity of each firm. We find that firm-specific unemployment has a highly skewed distribution. In coupling the study of job mobility and firm dynamics the model provides a new analytical tool for industrial organization and makes it possible to synthesize more targeted policies managing job mobility.

我们使用两个国家的详细行政微观数据，建立了一个建模框架，为企业规模的起源，企业对失业的贡献以及企业之间工人之间的工作流动提供了新的解释。公司被组织为网络中的节点，其中连接代表了工人的低移动性障碍。这些劳动力流动网络是凭经验确定的，并且是工人在工作之间过渡的基础。我们表明，从公司的连通性可以预测高度扭曲的公司规模分布。此外，我们的模型允许将失业重新概念化为与公司特定失业概念以及每个公司的网络附近地区相关的本地网络现象。我们发现，特定于企业的失业情况的分布高度不对称。