Good Governance Problems and Recent Financial Crises in Some EU Countriestitle of article [Dataset]

The starting point for the research has been the list of 147 banking crises within the period 1976-2011 prepared by the International Monetary Fund. The countries with crises have been analysed with respect to publicly available World Bank indicators in the periods of three years before the crises. The machine learning methodology for subgroup discovery has been used for the analysis. It enabled identification of five subsets of crises. Two of them have been identified as especially useful for the characterization of EU countries with banking crises in the year 2008. Fast growing credit activity is characteristic for the first subgroup while socioeconomic problems recognized by non-increasing quality of public health are decisive for the second subgroup. Comparative analysis of EU countries included into these subgroups demonstrated statistically significant differences with respect to World Bank good governance indicator values for the period before the crisis. Control of corruption, rule of law, and government effectiveness are the indicators which are statistically different for these sets of countries. The significance of the result is in the segmentation of the corpus of countries with banking crises and the recognition of connections between banking crises, socioeconomic problems, and governance effectiveness in some EU countries

本研究的初始数据集为国际货币基金组织（International Monetary Fund）整理的1976至2011年间的147起银行业危机清单。研究针对发生银行业危机的国家，以危机爆发前三年的可公开获取的世界银行（World Bank）指标为分析维度展开研究。本次分析采用子群发现（subgroup discovery）机器学习方法，最终识别出五类危机子集。其中两类子集可有效刻画2008年发生银行业危机的欧盟（European Union）国家特征：第一类子集的典型特征为信贷活动高速扩张，第二类子集则以公共卫生质量停滞所体现的社会经济问题为决定性区分特征。对纳入这两类子集的欧盟国家开展对比分析后发现，危机前的世界银行良好治理指标存在统计学意义上的显著差异，其中腐败管控、法治水平与政府效能为该两组国家中呈现统计学差异的三项指标。本研究的核心贡献在于完成了银行业危机国家样本集的细分，并揭示了部分欧盟国家的银行业危机与社会经济问题、治理效能之间的内在关联。