Title: Evaluating banking crisis predictions in EU and V4 countries
Authors: Ostrihoň, Filip
Citation: Trendy v podnikání = Business trends : vědecký časopis Fakulty ekonomické ZČU v Plzni. 2020, roč. 10, č. 2, s. 64-72.
Issue Date: 2020
Publisher: Západočeská univerzita v Plzni
Document type: article
článek
URI: http://hdl.handle.net/11025/42382
ISSN: 1805-0603
Keywords: bankovní krize;modely včasného varování;modely s diskrétní volbou;signalizační přístup;kredit na HDP;index cen domů
Keywords in different language: banking crisis;early warning models;discrete choice models;signaling approach;Creditto- GDP;House Price Index
Abstract in different language: 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.
Rights: © Západočeská univerzita v Plzni
Appears in Collections:Číslo 2 (2020)
Číslo 2 (2020)

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