Labor Market Dynamics

宏观经济分析传统上侧重于解释高度聚合的经济时间序列中的规律性。例如，在劳动力市场的背景下，寻求对总就业或失业的变动进行核算是一种常见的做法。众所周知，高度汇总的数据掩盖了大量的经济活动；即使在总体就业变化很小的时期，个别工人的就业状况和个别机构的就业分布也有很大的变化。标准的宏观经济模型是从这些变化中提炼出来的。对于某些问题，这种从潜在劳动力市场流动中抽象出来的做法可能是无害的，但在其他情况下，这肯定是一个严重的缺陷。对许多劳动力市场政策的分析显然最好是在综合模型中进行，这些模型确实考虑了劳动力市场流动。事实上，越来越多的实证和理论文献关注这些潜在的劳动力市场流动，这些模型已经被用来开始研究各种政策的影响。然而，尽管已经取得了进展，但仍有许多工作要做。这项研究的目的是加强这篇文献的理论分支和经验分支之间的联系，以便更好地理解哪些模型特征在解释数据中的关键规律方面具有数量上的重要性。这一努力还应该使经验和理论问题分别尖锐，因为将理论与数据对峙的过程将隔离那些有很大能力区分模型特征的经验关系，因此值得更仔细地审查，以及隔离那些对解释经验规则最重要的模型特征，从而指导未来的理论扩展。粗略地说，人们可能会发现导致劳动力市场流动的两个过程。一个是重新安排各机构的就业职位，另一个是重新安排现有就业职位的工人。实证研究表明，这两个过程在解释劳动力市场流动方面都很重要。虽然已经对前者进行了研究，但对于哪些模型特征在定量上与工作重新分配的周期性属性相匹配，人们仍然知之甚少。第二个过程几乎没有得到分析研究。该项目将这一功能引入了通常用于解决劳动力市场流动的匹配模型类。欧洲和美国不同的劳动力市场监管可能会扭曲第二个过程，该项目还将调查限制工人工资差异的政策对分配和福利的影响。

Macroeconomic analysis has traditionally focused on accounting for regularities in highly aggregated economic time series. In the context of the labor market, for example, it is common practice to seek to account for movements in aggregate employment or unemployment. It is well known that highly aggregated data mask a great deal of economic activity; even in periods when aggregate employment changes very little, there are very large changes in the employment status of individual workers and in the distribution of employment across individual establishments. Standard macroeconomic models abstract from these changes. For some issues, this abstraction from underlying labor market flows may be innocuous, but in other contexts it is surely a serious shortcoming. The analysis of many labor market policies are clearly best carried out in aggregate models which do account for labor market flows. Indeed, there are growing empirical and theoretical literatures that focus on these underlying labor market flows, and these models have been used to begin addressing the effects of various policies. Despite the advances that have been made, however, much remains to be done. The goal of this research is to sharpen the connection between the theoretical and empirical branches of this literature so as to better understand what model features are quantitatively important in accounting for the key regularities in the data. This effort should also sharpen both empirical and theoretical issues individually, since the process of confronting theory with data will isolate those empirical relationships which have a lot of power to discriminate between model features, and hence are worthy of closer scrutiny, as well as isolate those model features which are most significant in accounting for empirical regularities and hence guide future theoretical extensions. Loosely speaking, one may identify two processes that give rise to labor market flows. One is the rearranging of employment positions across establishments, and the other is the rearrangement of workers across existing employment positions. Empirical work has shown that both of these processes are important in accounting for labor market flows. Though the former has been studied, it remains true that not that much is known of what model features are important quantitatively to match the cyclical properties of job reallocation. The second process has been subject to little analytical study. This project brings this feature into the class of matching models commonly used to address labor market flows. Labor market regulations which differ between Europe and the US are likely to distort this second process and this project will also investigate the allocational and welfare consequences of policies which restrict wage differentials across workers.