Job to Job Movements in a Simple Search Model
构建了一个包含在职搜索的均衡模型，解释工人为何从低工资企业流向高工资企业，并复现了企业规模、工资与流动性的典型事实，对理解劳动力市场动态有帮助。
On the job search is a key feature of real life labor markets. Yet, traditional equilibrium unemployment theory has not been able to account for on-thejob search in a satisfactory manner. In this paper we present an equilibrium model which includes on-thejob search as an optimal response to search frictions and differences in firm productivity. Our model is laid out in detail in ongoing research by Garibaldi and Moen (2009). In our model, on-the-job search is an optimal response to firm heterogeneity and search frictions in the labor market. The model has three key elements. First, it applies the competitive search equilibrium concept, initially proposed by Moen (1997). Thus, firms post wages and vacancies to minimize search and waiting costs, and the labor market is endogenously separated into submarkets. Second, firms have convex costs of maintaining vacancies (in our simulations, the number of vacancies per firm is fixed). Third, contracting between a firm and its employees is efficient, so that their joint income is maximized. The model tends toward an equilibrium characterization in which there is a job ladder in the labor market. Low productivity firms pay low wages, face high turnover rates, grow slowly and hire directly from the unemployment pool. More efficient firms pay higher wages, grow more quickly and hire from the employment pool. This characterization is qualitatively consistent with a variety of stylized facts about industry dynamics and worker ows: 1) workers move from low-wage to high-wage occupations, 2) more productive firms are larger and pay higher wages than less productive firms, 3) job-to-job mobility falls with average firm size and worker tenure, 4) wages increase with firm size, and 5) wages are higher in fast-growing firms. We also show that compared to traditional labor market models, our equilibrium model with on-thejob search delivers unexpected effects, even though