Spillover Effects of Mass Layoffs

政府经常补贴甚至救助濒临破产的公司。例如，在2008年和2009年，布什和奥巴马政府向通用汽车和克莱斯勒提供了总计超过500亿美元的资金，以防止工厂关闭。这些干预措施背后的主要经济原理是，通过集聚效应，工厂关闭或破产不仅会损害特定工厂的工人，还会对该地区的其他工厂和工人产生多米诺骨牌效应，从而增加失业人数。在没有这种溢出效应的情况下，很难从经济效率的角度证明使用纳税人的钱来补贴是合理的。该项目的目标是在德国劳动力市场的背景下追踪这种溢出效应。利用社会保障记录中的数据，我们使用工厂标识符来识别工厂关闭和大规模裁员。然后，我们的实证策略结合了差异中的差异方法和事件研究方法。我们将首先为每个治疗区匹配一个对照区，该对照区在大规模失业前几年与治疗区在人口结构、产业结构、工资和失业率方面相似，但没有受到冲击。为了确定大规模失业对该地区工资、就业和工人的影响，我们比较了大规模失业后几年治疗区和对照区的结果。我们的分析试图回答5个问题：1)大规模的就业破坏是否会引发当地劳动力市场的额外就业损失；如果是，在哪些领域？2)大规模失业会导致更高的失业率和更低的工资吗？3)是否降低了同一地区未受大规模裁员直接影响但在大规模裁员时已就业或正在找工作的工人的就业概率？4)在经历大规模裁员的地区，企业的生产率会发生什么变化？5)一个地区的创新能力是如何受到影响的？哪些地区最容易失去竞争优势？我们的研究结果通过研究对该地区其他工人和企业的潜在负面溢出效应，为研究流离失所效应的文献做出了贡献。如果是这样，流离失所的社会成本可能比流离失所的私人成本要大得多。我们的研究进一步为集聚效应的存在和程度提供了新的证据。因此，我们提出的研究有助于解决城市和产业集群存在的长期问题。最后，我们的研究结果具有重要的政策意义。通过对比地方劳动力市场层面和个人层面的溢出效应，我们的研究将提供新的证据，证明国家对特定企业的补贴不仅从受影响地区的角度来看是合理的，而且从整个经济的角度来看也是合理的。

Governments often subsidise or even bail out firms on the verge of bankruptcy. For example, in 2008 and 2009 both the Bush and the Obama administration provided in total over US$50 billion to General Motors and Chrysler to prevent the shut-down of plants. The main economic rationale behind these interventions is that a plant closure or bankruptcy would, through agglomeration effects, not only harm workers in the particular plant, but create a domino effect on other plants and workers in the region, thereby multiplying job losses. In the absence of such spillover effects, it is difficult to justify the use of taxpayer's money for subsidies on economic efficiency grounds. The goal of this project is to trace such spillover effects in the context of the German labour market. Using data from the social security records, we use the plant identifier to identify plant closures and mass layoffs. Our empirical strategy then combines a difference-in-difference approach with an event-study approach. We will first match for each treatment district a control district that in years prior to the mass job destruction was similar to the treatment district in terms of the demographic structure, industry structure, wages and unemployment, but that was not hit by a shock. To identify the effect of mass job destruction on wages, employment and workers in the region, we then compare outcomes in treatment and control districts in the years after the mass job destruction. Our analysis seeks to answer 5 questions: 1) Does massive job destruction trigger additional job losses in the local labour market; and if so, in which sectors? 2) Does massive job destruction lead to higher unemployment and lower wages? 3) Does it lower employment probabilities of workers in the same region who were not directly affected by the mass layoff but employed or looking for a job at the time of the mass layoff? 4) What happens to productivity in firms that are located in the region experiencing the mass layoff? And 5) how is the innovative capacity of a region affected and which regions are most vulnerable to lose their competitive edge? Our findings contribute to the literature on displacement effects by studying potential negative spillover effects on other workers and firms in the region. If so, the social costs of displacement may be substantially larger than the private costs of displacement suggest. Our research further provides novel evidence on the existence and magnitude of agglomeration effects. As such, our proposed research contributes to the long-standing question why cities and industrial clusters exist. Finally, our findings have important policy implications. By contrasting spillover effects at the local labour market level with those at the individual level, our research will provide novel evidence whether state subsidies to particular firms can be justified not only from the viewpoint of the affected region, but also from the viewpoint of the economy as a whole.