Labor Market Dynamics

劳动力市场动态

• 批准号: 9811391
• 负责人: Richard Rogerson
• 金额: --
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Continuing grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-08-01 至 2002-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9811391&HistoricalAwards=false
• 关键词: Labor; Market; Dynamics

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.

宏观经济分析传统上侧重于对高度综合的经济时间序列中的通货膨胀进行核算。例如，在劳动力市场的背景下，通常的做法是设法说明总就业或失业的变动。众所周知，高度综合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企业的就业分布也会发生很大的变化。标准的宏观经济模型从这些变化中抽象出来。对某些问题而言，这种对潜在劳动力市场流动的抽象可能是无害的，但在其他情况下，它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考虑劳动力市场流动的总体模型中进行。 事实上，关注这些劳动力市场流动的实证和理论文献越来越多，这些模型已经开始用于研究各种政策的影响。然而，尽管取得了进展，仍有许多工作要做。本研究的目标是加强本文献的理论和实证分支之间的联系，以便更好地了解什么样的模型特征在定量上对数据中的关键变量具有重要意义。这一努力还应该使经验问题和理论问题分别尖锐化，因为理论与数据相对抗的过程将隔离那些具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，以及隔离那些在解释经验错误方面最重要的模型特征，从而指导未来的理论扩展。 不严格地说，人们可以确定两个过程，导致劳动力市场流动。一种是在各机构之间重新安排就业岗位，另一种是在现有就业岗位之间重新安排工人。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。虽然前者已经被研究过，但对于什么样的模型特征在数量上对匹配工作重新分配的周期性属性是重要的，仍然知之甚少。对第二个过程的分析研究很少。该项目将这一功能引入到通常用于解决劳动力市场流动的匹配模型中。欧洲和美国之间不同的劳动力市场法规可能会扭曲这第二个过程，本项目还将调查限制工人工资差异的政策的分配和福利后果。