臺灣博碩士論文加值系統

本研究使用14家中國大陸銀行資料，期限從2006年至2010年，探討在不同的資本適足率下，中國大陸銀行財務指標與績效間之非線性關係。實證研究發現 當資本適足率在轉換值10.2172%及10.3383%時，銀行財務指標對ROE與ROA之影響存在結構性改變。流動性比率、效率比率、與總資產分別對 ROE與ROA有顯著的正向關係，且不受限於資本適足率之高低；而不良貸款率與凈利息收益率對ROE與ROA的影響會因銀行資本適足率的高低而有所不同。本研究可作為管理當局在規定銀行資本適足率規範之參考，尤其是中國大陸銀行。

Using a sample set of fourteen listed commercial banks in China from 2006 to 2010, this study investigates the non-linear relationship between bank performance and financial indicators in different levels of capital adequacy ratio. Results showed that there is a structural change on the effect of financial indicators on return on assets and return on equity when capital adequacy is equal to the transition value 10.2172% and 10.3383%, respectively. The empirical results also indicate that the impact of liquidity ratios, efficiency ratios and total assets on return on equity and return on assets are positively correlated regardless of the capital adequacy ratio level; while the impact of non-performing loans and net interest margins on return on assets and return on equity depends on the level of the bank’s capital adequacy ratio. The research can be considered as a reference point for regulators seeking to identify the optimal level of capital adequacy ratio for banks, especially for the Chinese banking sector.

Table of Contents

TABLE OF CONTENTS II
LIST OF FIGURES IV
LIST OF TABLES V
CHAPTER 1: INTRODUCTION 1
1.1. Research motivations 1
1.2. Research Objectives 4
1.3. Flow Chart 6
CHAPTER 2: CAPITAL ADEQUACY RATIO AND BANKING BACKGROUND IN CHINA 7
2.1. The Basel Capital Accords 7
2.2. Overview of Chinese Banking background 10
2.3. Review of capital adequacy ratio in China 14
CHAPTER 3: LITERATURES REVIEW 17
3.1. Literature review of bank performance and capital adequacy ratio 17
3.2. Literature review of control variables 22
CHAPTER 4: METHODOLOGIES 26
4.1. Panel Unit Root Test 26
4.1.1. LLC Test 27
4.1.2. IPS Test 27
4.1.3. ADF-Fisher Test 28
4.2. Panel Smooth Transition Regression 28
4.3. Building Panel Smooth Transition Regression Models 35
4.3.1. Homogeneity test 35
4.3.2. Estimation of transition model 37
4.3.3. Estimation of the number of regimes 38
4.4. Data description 40
4.4.1. Sample selection 40
4.4.2. Variable description 42
CHAPTER 5: EMPIRICAL RESULTS 45
5.1. Descriptive statistics 45
5.2. Panel unit roots test 46
5.3. Empirical results of Panel Smooth Transition model 48
5.3.1. Panel smooth transition effect between capital adequacy ratio and return on assets 48
5.3.2. Panel smooth transition effect between capital adequacy ratio and return on equity 54
CHAPTER 6: CONCLUSIONS 63
REFERENCES IN ENGLISH 66
REFERENCES IN CHINESE 71


List of Figures

Figure 1.3.1 Flow Chart 6
Figure 2.2.1 Market share (by assets) of China banking institution as of end 2010 12
Figure 2.2.2: Breakdown of After-tax profits of China banking institution as of end 2010 13
Figure 2.3.1: number of commercial banks complied with the regulatory of 8% capital adequacy 16
Figure 4.2.1: Transition Functions when m=1 33
Figure 4.2.2: Transition Functions when m=2 34
Figure 5.3.1: Estimated Transition Function for ROA 54
Figure 5.3.2: Estimated Transition Function for ROE 60


List of Tables

Table 2.1.1: Basel III Implemetation Timeline………………………………………10
Table 5.1.1: Variable Desciptive Statitics…………………………………………….46
Table 5.2.2: Unit Roots Tests………………………………………………………...48
Table 5.3.1: Linearity Test between CAR and ROA…………………………………49
Table 5.3.2: Number of regimes for the PSTR model of CAR and ROA…………...50
Table 5.3.3: Parameter Estimation of PSTR Model for ROA with r=1 and m=1…...52
Table 5.3.4: Estimation of Coefficients of Control Variables in PSTR Models of ROA………………………………………………………………………………….53
Table 5.3.5: Linearity Test between CAR and ROE…………………………………55
Table 5.3.6: Number of regimes for the PSTR model of CAR and ROE……….......56
Table 5.3.7: Parameter Estimation of PSTR Model for ROE with r=1 and m=1..….58
Table 5.3.8: Estimation of Coefficients of Control Variables in PSTR Models of ROE……………………………………………………………………………….….59
Table 5.3.9: Estimation of Coefficients of Control Variables in PSTR Models both ROE and ROA………………………………………………………………………..61

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