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• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
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• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础
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## 统计代写|金融统计代写Financial Statistics代考|Bank Concentration in the Euro Area

The Herfindahl-Hirschman Index (HHI) is defined as the sum of the squares of the market shares in total banking assets of all banks in a banking system. An HHI value below 1000 indicates low concentration, a value between 1000 and 1800 indicates moderate concentration, and a value above 1800 indicates high concentration. The HHI evolution for the three country groups under examination is presented in Table 2 and in Figure 3 . Country-level data from the ECB Statistical Data Warehouse (ECB 2019b) are used.

The weighted average of HHI in EA-19 peaked in 2014, when it started following a decreasing path arriving in 2017 at a value that is 56 points bigger than the HHI value for 2005 . The weighted average of HHI in EA-Co reached a peak in 2011, and started declining thereafter, in contrast to the EA-Pe countries whose weighted average of HHI followed an increasing path reaching a peak in $2017 .$ On the other hand, the row-wise and column-wise coefficients of variation in Table 2 show that there are significant disparities among the HHI values not only between countries within each year but also between different years for the same country. The biggest decline in HHI values was observed in Belgium, Estonia, and Finland, in contrast to Cyprus and Greece, which presented the biggest increase in HHI values during the period under examination.

As it is shown in Table 2 and in Figure 2, the disparities in HHI values between EA-Co countries, measured by the coefficient of variation, reached a peak of about $80 \%$ in 2010 . Afterwards they remained at high levels $(74 \%-79 \%$ until 2015 when they started decreasing, arriving at a minimum of $65 \%$ in 2017. In contrast, the disparities between EA-Pe countries, started increasing in 2011 , after having followed a decreasing path since 2005. In 2013, the disparities between EA-Pe countries reached a peak of $50 \%$, staying very close to this level thereafter. The decomposition of the HHI disparities into within-group and between-group components, using the Theil inequality index, is presented in Section 6.3.

## 统计代写|金融统计代写Financial Statistics代考|The Evolution of the CR5 Concentration Ratio

The CR5 concentration ratio is the sum of the shares of the five largest banks in a banking system. The CR5 evolution for the three country groups under examination is presented in Table 3 and in Figure 3. The weighted average of CR5 in EA-19 peaked in 2014, when it started following a decreasing path arriving in 2017 at a value that is $4.5 \%$ bigger than the CR5 value for 2005 . The weighted average of CR5 in EA-Co reached a peak in 2011, and started declining thereafter, in contrast to EA-Pe whose weighted average of CR5 followed an increasing path since $2007 .$

On the other hand, the row-wise and column-wise coefficients of variation in Table 3 show that there are significant disparities among the CR5 values not only between countries for each year but also between different years for the same country. The biggest positive evolution for CR5 was observed in Greece, Cyprus, and Spain, in contrast to Belgium and Finland, which presented the biggest decrease in the CR5 value between 2005 and $2017 .$

As it is shown in Table 3 and in Figure 2, the disparities in CR5 values between EA-Co countries, measured by the coefficient of variation, reached a peak of about $39 \%$ in 2008 , after a continuous increase from 2005. After a temporary decrease during 2010-2012, they remained at levels ranging between 36 and $38 \%$. After having followed a decreasing path since 2005 , the disparities between EA-Pe countries increased in 2013, remaining afterwards close to $27 \%$. The decomposition of the CR5 disparities into within-group and between-group components, using the Theil inequality index, is presented in Section 6.3.

## 统计代写|金融统计代写Financial Statistics代考|Credit Risk in the Euro Area

Although several years have passed since the onset of the global financial crisis of 2008 , many euro area banks still have high levels of non-performing loans (NPLs) on their balance sheets. The non-performing loans to total gross loans ratio (NPL ratio) reached $3.4 \%$ in September 2019 for the euro area as whole (ECB 2020), following a downward trend after 2012, when it reached an all-time high of around $8 \%$. However, despite this positive evolution for the euro area in total, large dispersions remain across euro area countries (ratios between $0.9 \%$ and $37.4 \%$ ). Such a large stock of NPLs puts serious constraints on many banks’ lending capacity and their ability to build further capital buffers, thus exerting a strong negative influence on economic grow through the reduction of credit supply.
Bank competition is one of the factors that have been extensively investigated in the past as one of the major determinants of credit risk, as well as of bank risk in general. In a recent study, Karadima and Louri (2019) reached the conclusion that competition exerts a statistically significant and positive impact on NPLs, supporting the “competition-stability” view in banking. This motivated us to extend the scope of the present study, by investigating the evolution and convergence of NPLs in the euro area during the period 2005-2017. The investigation is based on country-level data collected mainly from the World Bank (2019a, 2019b).

The evolution of NPL ratios for the three country groups under examination is presented in Table 4 and in Figure 4. The weighted average of the NPL ratio in EA-19 peaked in 2013, when it started following a decreasing path arriving in 2017 at a value $1.6 \%$ higher than that of 2005 . The weighted average of the NPL ratio in EA-Co reached a maximum of $3.4 \%$ in 2009 and 2013 , and started declining thereafter, reaching in 2017 a value $0.9 \%$ smaller than that of 2005 . In contrast, after a very sharp and continuous increase, which started in 2008 , the weighted average of NPL ratio in EA-Pe reached a maximum of $15.6 \%$ in 2014 , when it started decreasing arriving in 2017 at a value $8.5 \%$ higher than that of $2005 .$

## 统计代写|金融统计代写Financial Statistics代考|Bank Concentration in the Euro Area

Herfindahl-Hirschman 指数 (HHI) 被定义为银行系统中所有银行的总银行资产的市场份额的平方和。HHI 值低于 1000 表示低浓度，1000 和 1800 之间的值表示中等浓度，高于 1800 的值表示高浓度。表 2 和图 3 展示了三个受审查国家组的 HHI 演变情况。使用来自欧洲央行统计数据仓库 (ECB 2019b) 的国家级数据。

EA-19 中 HHI 的加权平均值在 2014 年达到顶峰，当时它开始沿着下降的路径到达 2017 年，该值比 2005 年的 HHI 值高 56 个点。EA-Co 的 HHI 加权平均值在 2011 年达到峰值，此后开始下降，而 EA-Pe 国家的 HHI 加权平均值在 2011 年达到峰值。2017.另一方面，表 2 中的逐行和逐列变异系数表明，HHI 值不仅在每年的国家之间存在显着差异，而且在同一国家的不同年份之间也存在显着差异。比利时、爱沙尼亚和芬兰的 HHI 值下降幅度最大，而塞浦路斯和希腊在审查期间的 HHI 值增幅最大。

## 统计代写|金融统计代写Financial Statistics代考|The Evolution of the CR5 Concentration Ratio

CR5集中度是银行系统中最大的五家银行的份额之和。表 3 和图 3 中介绍了所研究的三个国家组的 CR5 演变。EA-19 中 CR5 的加权平均值在 2014 年达到顶峰，当时它开始走下坡路，到 2017 年达到4.5%大于 2005 年的 CR5 值。EA-Co 中 CR5 的加权平均值在 2011 年达到峰值，此后开始下降，而 EA-Pe 的 CR5 加权平均值自 2011 年以来一直呈上升趋势2007.

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