國
立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
- 30 -
ability to cope with local economic volatility, the regional risk is on a downward trend, which may be a good sign for Chinese banks to expand internationally in the future.
6 Robustness tests
6.1 Alternative measures of risk
In Table 6.1, the results of alternative risk measures demonstrate the robustness of the previous conclusion.
Table 6.1: Regression Analysis with Alternative Measures of Risk This table reports OLS regression estimates of the relation between the
internationalization of China commercial banks and their risk using International Dummy (Inter) as a measure of bank internationalization. We show models with alternative risk measures: Log of Z-score (over prior 3 years), Sharpe Ratio (over prior 3 years). Table 4.1 shows definitions for all variables. Robust t-statistics are reported in parentheses.***, **, and * indicate significance at the 1%, 5%, and 10%
levels, respectively.
‧
We first replace the original Z-score withlog value over the last three years as the dependent variable. The advantage is that we can mitigate the impact of outliners. Next, we use the Sharpe Ratio as another alternative for bank risks. In each regression, we observe that International Dummy is statistically significant at the 5%, 10% and 10%, respectively. As a result, we reaffirm that internationalization is associated with higher bank risk.
6.2 Endogeneity
We further conduct several tests for possibleendogeneity of our international dummy, which may bias our result. There may exist some variables which we didn’t include in our regressions but might influence internationalization and bank risk simultaneously. We therefore, for example, add the growth rate of bank assets (Asset Growth) and the growth rate of loans (Loan growth) in the regression since fast-growing and slow-growing banks maycause different level of returns and risks.
The following Table 6.2 is the regression result of testing endogeneity circumstances. From the Table 6.2, we can observe the same result as above, which
Z-score Log of Z-score Sharpe Ratio
Inter -9.397** -0.110* -10.907*
Dependent Variables: Alternative Measure of Risk
‧
include endogeneity variables, such as asset growth and loan growth.Table 6.2: Testing Endogeneity
This table reports OLS regression estimates of the relation between the internationalization of China commercial banks and their risk using International Dummy (Inter) as a measure of bank internationalization. We show several models with additional possible omitted variables that could influence the risk of banks:
Assets Growth and Loan Growth. Table 4.1 shows definitions for all variables.
Robust t-statistics are reported in parentheses.***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.
7 Conclusions
The impact of internationalization on bank’s risks of Chinese banks becomes significant since Chinese firms are employing the “going out “ policy to expand its overseas business. We find robust evident that the more internationalized the bank,
Main Asset Growth Loan Growth
‧
the higher the risk. Furthermore, we also conduct several different measures of risk and control for potential endogeneity. All our data suggest that internationalization of Chinese banks will lead to higher risk.
Besides, after we coming to this conclusion, we also try to figure out that whether different expanding regions may induce different level of risk that a bank need to take. We find that Asia is the riskiest region while U.S is the least risky location. Asia is the emerging market and it’s easily influenced by the macroeconomic and developed countries. Therefore, we think that the potential uncertainties are the reasons why Asia becomes the region with the highest risk.
However, no matter what region a bank chooses, all banks seem to equip with capabilities to absorb risk and mitigate it.
Chinese banks are encouraged to operate internationally by China’s central government as well as ample opportunitiesdue to the “going out” policy of Chinese firms. Our conclusions offer directions for China’s commercial banks to expand their international business. For example, we know that internationalization will lead banks into a riskier position despite their sizes and quality of management, but different location expansion may create different risk levels.
Future studies can focus on different types of expansions that Chinese commercial banks often adopt (ex. representative office, branches and subsidiaries) to study their differences and relationships between risk and internationalization.
Since Chinese commercial banks have large amount of undisclosed data, future studies should put efforts on searching proxies for targeted variables.
Reference
1. Altman, E., (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance Vol. 23, No. 4, p.589-609.
‧
2. Berger, A., Bouwman, C., Kick, T., Schaeck, K., (2012). Bank risk taking and liquidity creation following regulatory interventions and capital support.
Working paper of University of South Carolina.
3. Berger, A., (2013). Internationalization and bank risk. University of South Carolina, Columbia.
4. Boyd, J., De Nicoló G (2005). The theory of bank risk-taking and competition revisited. Journal of Finance, Vol. 60, No. 3, p. 1329-1343.
5. Beltratti, A., Stulz, R., (2012). The credit crisis around the globe: Why did some banks perform better? Journal of Financial Economics 105, p.1-17.
6. Cocheo, S., (2000). Performance picture: avoiding efficiency as a religion., ABA Banking Journal, Vol. 92 No. 2, p. 58-9.
7. Committee on the Global Financial System (2010): Long-term issues in international banking. CGFS Papers No.41.
8. Demirgüç-Kunt, A., Huizinga, H., (2010). Bank activity and funding strategies:
The impact on risk and returns. Journal of Financial Economics 98, p.626-650.
9. DeYoung, R., Roland, K., (2001). Product mix and earnings volatility at commercial banks: Evidence from a degree of total leverage model. Journal of Financial Intermediation, 10(1), p.54-84.
10. European Central Bank (2008): EU banking structures.
11. Rebecca, D., Philip, S., (1995). Diversification, size and risk at bank holding companies. Federal Reserve Bank of New York Research Paper No. 9506
12. Franco, F., David, M., Phil M., (2010). Efficiency and risk in European banking, ECB Working Paper No. 1211.
13. Gong, L., Bo, W., Yali, P., (2011). Can Chinese companies win in the global big leagues? Journal of High-Performance Business, Accenture Report No.3.
‧
14. Girardone, C., Gardener, E., Molyneux, P., (2004). Analysing the determinants of bank efficiency: the case of Italian banks. Applied Economics, 36(3), p215–27.
15. Gu-Yue, Hu (2013). Strategies research for Chinese banks “going out”
development. Graduation Thesis Paper, Anhui University.
16. Goldberg, L., Johnson, D., (1990). The determinants of US banking activity abroad, Journal of Money and Finance, 9, p123–37.
17. Geoffery, J., (1990). Banks As Multinational.Routledge.
18. Hirtle, B., (1991). Factors affecting the international competitiveness of internationally active financial institutions. Federal Reserve Bank of New York Quarterly Review 16, p38-51.
19. Houston, J., Itzkowitz, J., Naranjo, A., (2007). Borrowing beyond borders: the geography and pricing of syndicated loans. Warrington College of Business, University of Florida.
20. Hughes, J., Mester, L., (1993). A quality and risk-adjusted cost function for banks: evidence on the ‘too-big-to-fail’ doctrine. Journal of Productivity Analysis, 4, p293–315.
21. Kan, W., (2006). Comparison between the Internationalization strategies of Chinese Banks and Western Countries. Journal of China Youth College for Political Sciences (Beijing), 26(5).
22. KPMG: China Outlook 2015. KPMG Global China Practice
23. Laeven, L., Levine, R., (2007). Is there a diversification discount in financial conglomerates? Journal of Financial Economics 85, p331-367.
24. Lewis, M., Davis, T., (1987). Domestic And International Banking, p.219.
25. Laeven, L., Levine, R., (2009). Bank governance, regulation and risk taking.
Journal of Financial Economics 93, p259-275.
‧
26. Gulamhussena, M., Pinheirob, C., Pozzolo, A., (2014). International
diversification and risk of multinational banks: Evidence from the pre-crisis period, Journal of Finance, p30-43.
27. Brammer, N., (2011). Internationalization of Chinese and Indian banks: patterns and strategies”.Graduation Paper, University of Vienna.
28. Nikolaos, I., Christian, C., (2010). Leverage and risk in US commercial banking in the light of the current financial crisis.Luxembourg School of Finance
Research Working Paper No.10-12.
29. Rugman, M., (1976). Risk reduction by international diversification. Journal of International Business Studies, 7(2), p75–80.
30. Rebecca, S., Philip, E., (1995). Diversification, size and risk at bank at bank holding companies. Federal Reserve Bank of New York Research Paper No.9506.
31. Teresa, M., Dolores, M., (2005). Risk tasking behaviour and ownership in the banking industry: the Spanish evidence, Journal of Economics and Business, 60(4), p.332-354.
32. Sameh, C., (2013). Bank size and efficiency in developing countries:
intermediation approach versus value added approach and impact of non-traditional activities. Asian Economic and Financial Review, 3(5), p.593-613.
33. Yang, S., Liao, S., (2006). Trend of bank internationalization and the
international strategies for China’s banking industry. Journal of Henan Institute of Financial Management, 22(1), p.11-13.
34. Stiroh, K., Rumble, A., (2006). The dark side of diversification: The case of US financial holding companies. Journal of Banking & Finance, 30(8),
p2131-2161.
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
- 37 -
35. Stiroh, K., (2004). Diversification in banking: Is noninterest income the answer?
Journal of Money, Credit and Banking, p853-882.
36. Susan, K.,Howard, C., (2010). The Financial System in China: Risks and Opportunities Following the Global Financial Crisis.Promontory Financial Group White Paper.
37. Zhang, H., (1995). Wealth effects of U.S. bank takeovers.Applied Financial Economics (5)5, p329-336.
‧
Table 4.1: Definitions and Summary Statistics
This table presents variables definitions and reports summary statistics for the full samples of China commercial banks used in the analysis.
Variable Definition Mean Median Std
Z-score (3 years)
A bank -level measure of financial risk calculated as (Average(ROA) + Average(Capital Ratio))/Stdv. ROA. The larger the value, the lower of overall bank risk.Averages of ROA and Capital Ratio as well as the standard deviation of ROA are computed over the previous 3 year, this being our main specification.
16.57 10.12 28.04
Log of Z-score (3 years) The log of Z-score over the previous 3 years in order to mitigate the impact of outliners. 0.99 1.01 0.41
Sharpe Ratio The risk-adjusted return on equity defined as ROE/ Stdv. ROE. 14.8 8.06 24.03
International dummy A dummy variable that takes a value of 1 if the bank has overseas branches or exposures, and 0 otherwise. 0.2 0 0.41
Income Diversification A measure of testing the diversification of bank's income from different sources, which is calculated as 1-|(Net Interest
Income – Other Operating Income)/ Total Operating Income|. Source: Laeven and Levine (2007) 0.233 0.22 0.31
Size The log of total assets. 4.53 4.28 0.75
Quality of Management
It is defined as non-interest expense divided by the sum of net interest income and non-interest income.This measure is generally considered an important benchmark for examining the operating efficiency or quality of management. Source:
Cocheo (2000)
34.7 34.13 7.33
Bank Leverage Ratio It is calculated as equity divided by liabilities. It reflects the bank's usage of money and it will affect a bank's
profitability as well as the ability to survive through surpring crisis. 7.64 7.4 2.76
Bigfive It characterized China's unique banking structure. Bigfive banks in China are five state-owned banks.It's a dummy
variable that takes a value of 1 for one of a Bigfive banks, and 0 otherwise. 0.08 0 0.27
Joint Stock It characterized China's unique banking structure. Joint stock banks in China are categorized by CBRC.It's a dummy
variable that takes a value of 1 for one of a joint stock banks , and 0 otherwise. 0.08 0 0.28
City Commercial
It characterized China's unique banking structure.There are numerous city commercial banks in rural areas to serve local household and companies in China.It's a dummy variable that takes value 1 when both Bigfive and Joint Stock variables are value 0.
Asset growth The growth rate of bank asset. 27.43 23.18 18.11
Loan growth The growth rate of bank total loans. 22.93 20.72 12.49
Risk Variables
International Variables
Main Bank Characteristics
Other Variables
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
Z-SCORE Inter Size QM InDiv BLR Big5 JS
Z-SCORE 1
Inter 0.143*** 1
Size 0.28*** 0.514*** 1
QM -0.162*** 0.039 -0.053 1
InDiv 0.026 0.099 0.023 0.038 1
BLR 0.017 -0.102 -0.138*** 0.02 0.02 1
Big5 0.265*** 0.472*** 0.486*** -0.026 0.19*** -0.055 1
JS -0.047 0.309 0.337 0.101 0.125 -0.0611 -0.088 1
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
Table 5.1.2 reports differences in Z-score by bank size. We report both difference in means and medians between the characteristics of international and domestic banks. Table 4.1 shows definitions for all variables.
Table 5.2: Risk (Z-score) by Different Sizes of Bank
Variables N Mean Median N Mean Median
Z-score 66 14.5644 9.1492 261 24.5471 12.6066
Log Z 66 0.9519 0.9614 261 1.1532 1.1006
Sharpe Ratio 66 12.9205 6.8759 261 13.5192 6.9243
InDiv 66 0.2949 0.3863 261 0.2174 0.1839
Size 66 5.6419 5.7497 261 4.2550 4.1908
QM 66 34.5618 34.1002 261 35.9803 35.9600
BLR 66 0.1146 0.1188 261 0.1720 0.1450
Big5 66 0.3788 0.0000 261 0.0000 0.0000
JS 66 0.2576 0.0000 261 0.0421 0.0000
International Banks Domestic Banks
Bank Size N MEAN MEDIAN N MEAN MEDIAN
Small 9 4.09 4.1 199 4.26 4.3
Medium 15 4.75 4.77 58 5.28 5.28
Large 42 5.28 5.3 4 6.08 6.09
International Domestic