PhD Program in Economics and Business, Universidad de Málaga, Málaga, Spain.
Department of Finance and Accounting, Universidad de Málaga, Málaga, Spain.
PLoS One. 2020 Feb 12;15(2):e0228387. doi: 10.1371/journal.pone.0228387. eCollection 2020.
Capital flows is an important aspect of the international monetary system because they provide great direct and indirect benefits, and at the same time, they carry risks of vulnerability for countries with an open economy. Numerous works have studied the behavior of these flows and have developed models to predict sudden stop events. However, the existing models have limitations and the literature demands more research on the subject given that the accuracy of the models is still poor, and they have only been developed for emerging countries. This paper presents a new prediction model of sudden stop events of capital flows for both emerging countries and developed countries with the ability to estimate accurately future sudden stop scenarios globally. A sample of 103 countries was used, including 73 emerging countries and 30 developed countries, which has allowed the use of sample combinations that consider the regional heterogeneity of the warning indicators. To the sample under study, a method of decision trees has been applied, which has provided excellent prediction results given its ability to learn characteristics and create long-term dependencies from sequential data and time series. Our model has a great potential impact on the adequacy of macroeconomic policy against the risks derived from sudden stops of capital flows, providing tools that help to achieve financial stability at the global level.
资本流动是国际货币体系的一个重要方面，因为它们提供了巨大的直接和间接利益，但同时也给开放型经济国家带来了脆弱性的风险。许多研究都研究了这些流动的行为，并开发了模型来预测突然停止事件。然而，现有的模型存在局限性，文献要求对这一主题进行更多的研究，因为模型的准确性仍然很差，而且这些模型仅为新兴国家开发。本文提出了一种新的资本流动突然停止事件的预测模型，适用于新兴国家和发达国家，能够准确估计未来全球突然停止的情况。该样本包括 103 个国家，其中 73 个是新兴国家，30 个是发达国家，这使得可以使用考虑预警指标区域异质性的样本组合。对所研究的样本，应用了决策树方法，由于其能够从序列数据和时间序列中学习特征并创建长期依赖关系，因此提供了出色的预测结果。我们的模型对宏观经济政策应对资本流动突然停止风险的充分性具有重大影响，为实现全球金融稳定提供了帮助。
