Evaluating banking crisis predictions in EU and V4 countries .

Filip Ostrihoň
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引用次数: 1

Abstract

Relying on a recently published database of financial crises, this paper assesses an early warning model for predicting banking sector distress. The exercise employs discrete choice models and a signaling approach to evaluate the performance of an existing model based on credit-to-GDP change and real house price growth in regard to predominantly post-crisis data for EU and Visegrad Group countries. As such, unbalanced panel data for 27 EU countries, spanning with annual frequency at longest the period of 2003-2017, as well as unbalanced panel data for 4 Visegrad Group countries covering at most the period 2008Q1-2017Q4 with quarterly frequency were analyzed. The results are generally in line with other empirical research featuring the same model and indicate that the model retains most of its predictive capabilities even when currently available data are used. However, the analysis identifies that the indicator of real house price growth may not be as useful of a predictor of banking crises in more recent periods for EU countries, as it might have been before the 2008 financial and economic crisis. Consequently, a simpler univariate early warning indicator approach might be sufficient for banking sector risk monitoring and management in EU and Visegrad Group countries in regard to identifying periods of distress similar to those in 2008.
评估欧盟和V4国家的银行危机预测。
基于最近发布的金融危机数据库,本文评估了一个预测银行业困境的预警模型。这项工作采用离散选择模型和信号方法来评估基于欧盟和维谢格拉德集团国家主要后危机数据的信贷与gdp变化和实际房价增长的现有模型的表现。因此,我们分析了27个欧盟国家的不平衡面板数据,最长时间跨度为2003-2017年的年度频率,以及维谢格拉德集团4个国家的不平衡面板数据,最长时间跨度为2008 - 2017q4,最长时间跨度为季度频率。结果与其他具有相同模型的实证研究基本一致,并且表明即使使用当前可用的数据,该模型也保留了其大部分预测能力。然而,分析表明,实际房价增长的指标可能不像2008年金融和经济危机之前那样,在较近的时期作为欧盟国家银行业危机的预测指标有用。因此,一种更简单的单变量预警指标方法可能足以用于欧盟和维谢格拉德集团国家的银行业风险监测和管理,以确定类似于2008年的困境时期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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