Agosto Arianna, Giudici Paolo, Leach Tom
Department of Economics and Management, University of Pavia, Pavia, Italy.
Front Artif Intell. 2019 May 16;2:6. doi: 10.3389/frai.2019.00006. eCollection 2019.
Calabrese et al. (2017) have shown how binary spatial regression models can be exploited to measure contagion effects in credit risk arising from bank failures. To illustrate their methodology, the authors have employed the Bank for International Settlements' data on flows between country banking systems. Here we apply a binary spatial regression model to measure contagion effects arising from corporate failures. To derive interconnectedness measures, we use the World Input-Output Trade (WIOT) statistics between economic sectors. Our application is based on a sample of 1,185 Italian companies. We provide evidence of high levels of contagion risk, which increases the individual credit risk of each company.
卡拉布雷斯等人（2017年）展示了如何利用二元空间回归模型来衡量银行倒闭引发的信用风险中的传染效应。为了说明他们的方法，作者使用了国际清算银行关于各国银行系统间资金流动的数据。在此，我们应用二元空间回归模型来衡量企业倒闭引发的传染效应。为了得出关联性度量，我们使用经济部门之间的世界投入产出贸易（WIOT）统计数据。我们的应用基于1185家意大利公司的样本。我们提供了高传染风险水平的证据，这种风险增加了每家公司的个体信用风险。
