The labor market channel of systemic risk

IF 1.9 3区 经济学 Q2 ECONOMICS Journal of Economic Dynamics & Control Pub Date : 2024-11-01 DOI:10.1016/j.jedc.2024.104976
Michel Alexandre , Thiago Christiano Silva , Benjamin Miranda Tabak
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Abstract

In this paper, we explore the labor market channel of systemic risk. We consider that distressed firms, besides defaulting on part of their debt commitments, also react to negative shocks by laying off part of their employees. This constitutes another source of systemic risk, as we assume that laid-off employees will default on their debt commitments. Using Brazilian data, we compute the systemic risk considering three possible strategies distressed firms can adopt: layoff of employees, default on debt commitments, or both strategies. Our findings highlight the importance of the labor market channel. It has contributed noticeably more to overall systemic risk during the study's assessment period (2015–2020). Moreover, the shock multiplier of the employees' layer is higher than that of the firms' layer. We also assess, through machine learning techniques, the determinants of firms' systemic impact under different layer configurations–that is, when the bank-firm layer is composed of the corporate loans extended to the firms, and when this is composed of the loans extended to the firms' employees. This study emphasizes the crucial role that the labor market plays in determining systemic risk dynamics and calls for improved risk management practices to address these issues effectively.
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系统性风险的劳动力市场渠道
本文探讨了系统性风险的劳动力市场渠道。我们认为,受困企业除了拖欠部分债务承诺外,还会通过解雇部分员工来应对负面冲击。这构成了系统性风险的另一个来源,因为我们假定被解雇的员工会违约。利用巴西的数据,我们计算了系统性风险,其中考虑到了受困企业可能采取的三种策略:裁员、债务承诺违约或两种策略兼而有之。我们的研究结果凸显了劳动力市场渠道的重要性。在本研究的评估期内(2015-2020 年),劳动力市场渠道对整体系统性风险的贡献明显增大。此外,雇员层的冲击乘数高于企业层。我们还通过机器学习技术,评估了不同层级配置下企业系统性影响的决定因素,即当银行-企业层级由发放给企业的公司贷款组成时,以及当银行-企业层级由发放给企业员工的贷款组成时。这项研究强调了劳动力市场在决定系统性风险动态方面所起的关键作用,并呼吁改进风险管理实践,以有效解决这些问题。
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来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
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