The economics of mass layoffs: displaced workers, displacing firms,and causes and consequences

为了准确衡量工人失业的成本，必须解决两个问题：观察到的工人特征分离的外生性，以及用于测量的样本的代表性。 该项目将在这两个方面推进知识的沿着。 孤立的外源性个人离职事件的困难，导致文献使用的分离，包括多个工人在同一时间裁员（大规模裁员）作为外源性事件的基础上，估计与雇主的非自愿变化相关的收入损失。因此，与大规模裁员相关的工作损失是一个方便的自然实验，用于研究结果，否则其测量会因分离的内隐性而产生偏差。在之前的研究中（McKinney和Vilhuber，2006; Lengermann和Vilhuber，2002; Abowd，McKinney和Vilhuber，2008; Bowlus和Vilhuber，2002），调查人员发现了一些证据，表明大规模裁员事件与公司雇用的工人的特征有关。这个项目将继续研究，调查是否可以认为大规模裁员事件的工人统计外生性，如果不是一般情况下，在什么情况下可以维持外生性假设。 其次，以前的文献使用基于调查的个人和/或家庭面板，或美国各州的行政数据来调查这些问题。调查虽然提供了详细的人口资料，但往往受到实际观察到的大规模裁员工人人数的限制，限制了对特定分组的分析，并限制了将地理或公司一级的资料纳入分析的程度。在过去，行政数据的用户一直被限制在使用一个单一的地理实体，不能跟踪工人跨越政治边界，并没有获得有关工人或公司的特点很多信息。这个项目将通过使用人口普查局纵向雇主-家庭动态计划基础设施文件系统，截至2008年1月，该数据库涵盖了46个州98%以上的私营部门就业情况（其中31个州可用于研究目的），并使用美国人口普查局提供的调查和人口普查数据，将其与有关工人的详细人口统计信息和详细的公司层面信息联系起来。该项目探索和利用详细的地理变化，调查和使用跨国界的地理流动性，并将工人和企业层面的特征纳入行政数据集的独特纵向方面和准普遍覆盖范围。该项目还提供了以前分析过的状态的更新信息。它利用数据集的规模来探索大规模裁员的替代措施，突出了结果对大规模裁员的特定措施的选择可能的敏感性。除了提供最新的结果，丰富的信息使调查人员能够确定如何衡量一个事件（或不同的事件）直接关系到裁员的外部性问题，因为大规模裁员事件本身的原因。如果能够确定一些新的衡量标准，将结果衡量标准扩大到工人原来所在地以外，并按照详细的人口统计和公司特征（包括地理位置）对分析进行分类，就有助于检查对工人收入损失所作的任何推断的可靠性。失业对工人的经济影响，特别是大规模裁员造成的影响可能很大。工人可能会经历收入比正常收入水平低10%至20%，甚至在失去工作五年或更长时间后。准确衡量失业成本与政策相关，并促使法规和法律减轻或减轻这些损失。评估这些法律的成本主要取决于每个受影响工人的估计损失和外部失业的估计发生率。

In order to accurately measure the cost of job loss for workers, two issues must be addressed: the exogeneity of the observed separation to worker characteristics, and the representativeness of the sample used for the measurement. This project would advance knowledge along both dimensions. The difficulty of isolating exogenous individual separation events has led the literature to use separations that encompass multiple worker layoffs at the same time (mass layoffs) as the exogenous event upon which to base estimates of the earnings loss associated with an involuntary change of employers. Thus, the job losses associated with mass layoffs are a convenient natural experiment for investigating outcomes whose measurement would otherwise be biased by endogeneity of the separation. In previous research (McKinney and Vilhuber, 2006; Lengermann and Vilhuber, 2002; Abowd, McKinney and Vilhuber, 2008; Bowlus and Vilhuber, 2002), the investigators have found some evidence that the mass layoff event is related to characteristics of the workers employed at the firm. This project would continue that research, investigating whether the mass layoff event can be considered statistically exogenous for the worker and, if not in general, under what circumstances the exogeneity assumption can be maintained. Second, the previous literature has used survey-based person and/or household panels, or administrative data for individual US states to investigate these issues. While providing detailed demographic information, surveys are often limited by the number of workers actually observed as part of a mass layoff, restricting the analysis of specific sub-groups and limiting the extent to which geographic or firm-level information can be incorporated into the analysis. In the past, users of administrative data have been restricted to using a single geographic entity, not being able to follow workers across political boundaries, and have not had access to much information on worker or firm characteristics.This project would address some of those shortcomings by using the Census Bureau Longitudinal Employer-Household Dynamics Program Infrastructure file system, covering more than 98% of private employment in 46 states as of January 2008 (with 31 states available for research purposes), which have been linked to select detailed demographic information on workers, and detailed firm-level information, using survey and census data available at the U.S. Census Bureau. This project explores and exploits detailed geographic variation, investigates and uses geographic mobility across state borders, and incorporates worker and firm level characteristics into the unique longitudinal aspect and quasi-universal coverage of administrative datasets. The project also provides newer and updated information on states that have been analyzed previously. It leverages the magnitude of the dataset to explore alternate measures of mass layoffs, highlighting the possible sensitivity of the results to the choice of particular measures of mass layoffs. Besides providing updated results, the wealth of information allows the investigator us to determine how one measures an event (or different events) ties directly into the question of the exogeneity of the layoff, as does the cause of the mass layoff event itself. The ability to define a number of new measures, to expand outcome measures beyond the original location of the worker, and to subset the analysis by detailed demographic and firm characteristics, including geography, helps to check the robustness of any inference made about earnings losses of workers.Broader Impacts. The economic impact of job losses on workers, in particular those resulting from large mass layoffs, can be substantial. Workers may experience earnings 10 to 20 percent below normal earnings levels even five years or longer after losing a job. Accurately measuring the cost of job loss is policy relevant and has motivated regulations and laws to mitigate or alleviate these losses. Assessing the cost of such laws depends critically on both the estimated loss by each affected worker and the estimated incidence of exogenous job loss.