Tác động của giới tính ceo đến tỷ lệ nợ xấu trong ngành ngân hàng ở Việt Nam

Nội dung text: Tác động của giới tính ceo đến tỷ lệ nợ xấu trong ngành ngân hàng ở Việt Nam

1. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 THE IMPACTS OF CEO GENDER ON NON-PERFORMING LOAN RATIO IN VIETNAM BANKING SECTOR TÁC ĐỘNG CỦA GIỚI TÍNH CEO ĐẾN TỶ LỆ NỢ XẤU TRONG NGÀNH NGÂN HÀNG Ở VIỆT NAM PhD, Nguyen Thanh Dat; MA, Vuong Bao Bao The University Of Danang - University Of Economics datnt@due.udn.vn Abstract This paper aims to analyse the relationship between CEO’s gender and the non-performing loan ratio of commercial banks in Vietnam. We employ a data set which includes 30 Vietnam commercial banks over the period 10 years from 2008 to 2018. To investigate the effect of CEO gender on credit risk, we run a fixed effect multivariate regression model in which the dependent variable is the non-performing loan measured by the sum of all debts categorized in group 3, 4 and 5. The main interested variable is CEO gender which takes the value of 1 if the CEO is a male and 0 otherwise. On average, banks with male CEO have a lower non-performing loan ratio than banks with female CEO. CEO gender coefficient is statistically significant our main regression model. The negative relationship between CEO gender and non-performing loan are consistent through another two robustness tests, namely controlling for GDP growth rate and controlling for financial crisis period. Keywords: Banking sector, CEO gender, Non-performing loan, Fixed effect model, Financial crisis Tóm tắt Nghiên cứu này nhằm phân tích mối quan hệ giữa giới tính của CEO và tỷ lệ nợ xấu của các ngân hàng thương mại tại Việt Nam. Chúng tôi sử dụng tập dữ liệu bao gồm 30 ngân hàng thương mại Việt Nam trong 10 năm từ 2008 đến 2018. Để điều tra ảnh hưởng của giới CEO đối với rủi ro tín dụng, chúng tôi sử dụng mô hình hồi quy đa biến có hiệu ứng cố định trong đó biến phụ thuộc là lệ nợ xấu được đo bằng tổng của tất cả các khoản nợ được phân loại trong nhóm 3, 4 và 5. Biến quan tâm chính là giới tính của CEO, lấy giá trị bằng 1 nếu CEO là nam và 0 nếu ngược lại. Tính trung bình, các ngân hàng có CEO là nam có tỷ lệ nợ xấu thấp hơn các ngân hàng có CEO là nữ. Hệ số của giới tính của CEO có ý nghĩa thống kê trong mô hình hồi quy chính của chúng tôi. Mối quan hệ tiêu cực giữa giới tính của CEO và khoản nợ xấu nhất quán thông qua hai bài kiểm tra bền vững, đó là kiểm soát tốc độ tăng trưởng GDP và kiểm soát cho thời kỳ khủng hoảng tài chính. Từ khóa: Ngành ngân hàng, giới tính CEO, nợ xấu, mô hình hiệu ứng cố định, khủng hoảng tài chính 1152
2. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 1. Introduction Non-performing loans (NPLs) are always long-standing problems for the banking sector because of their potential risks of losing credit. Once a loan is classified as an NPL, full debt recovery is rarely feasible and it is difficult and time-consuming to retrieve the debt. The appearance of bad debts is not only due to the customer side and the economic condition but also due to banks’ management practices. Increasing in the level of non-performing loans poses a significant risk to the banking sector in particular and the entire financial sector in general. Failure in controlling non- performing loans over a long period gradually negatively affects banks’ profitability of commercial banks (Kaaya and Pastory, 2013). Consequently, the increase of non-performing loans usually results in high loan provisioning, which leads to a drop in profits of banks (Kithinji, 2010) and gradually dimishing the capability of bank sector in contributing to the development of the economy (Abd Karim et al., 2010). Unfortunately, Vietnam’s banking sector is alarmed with the rising of non-performing loans. In 2018, NPLs account for 4.6% of outstanding loans, which is nearly doubled compared to 2017 (2.6 %). Therefore, researches that are undertaken to investigate factors that affect banks’ non-performing loan ratio are necessary. The main purpose of the research is analysing the relationship between CEO’s gender and the non-performing loan ratio of commercial banks in Vietnam. The answer to this research question is crucial to all stakeholders including administrative boards, investors and policymaker. First, understand this relationship helps boards have an appropriate risk management strategy including appointing male or female CEO. As in the literature review below, women could be more risk averse, or less risk averse. Secondly, knowing this relationship helps investors in choosing their investment portfolio. Finally, policymakers know which banks are potentially riskier than the other. In this paper, we employ a data set which includes 30 Vietnam commercial banks over the period 10 years from 2008 to 2018. To investigate the effect of CEO gender on credit risk, we run a fixed effect multivariate regression model. Our dependent variable is the non- performing loan ratio, measured by the ratio of all debts in group 3, 4 and 5 (according to the State Bank of Vietnam, 2015 and 2017) over total outstanding loans. The independent variable is CEO gender which takes the value of 1 if the CEO is a male and 0 otherwise. In order to further the analysis, we also test the impact of CEO gender on banks’ non-performing loan ratio by undertaking two robustness tests namely: (i) controlling for macroeconomic condition expressed by GDP growth rate and (ii) controlling for financial crisis. The rest of paper is organised as followed. Section 2 discusses the literature review. Section 3 describes our research data set and research methodology. Section 4 provides the main regression results and robustness tests’ results. Finally, Section 5 sets forth the conclusion remarks. 2. Literature review Related to social belief and leadership style, Vu et al. (2017) illustrate that the press 1153
3. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 demonstrates and builds up strong gender stereotyping in Vietnam society about male and female directors. Compared to male managers, female managers are thought to be better in social relationship as they are caring, friendly, flexible, and careful. These differences are likely to result in the discrepancy in making business choices. In a study about female administration in Vietnamese small companies, Vo and Harvie (2009) find that female managers had trouble when dealing with financing, being aware of the legal framework and business laws, taking advantage of technology, use of IT and seeking support from the local government. However, Pham and Talavera (2018) do not observe the same thing as been shown that if a firm is administrated by a woman, it is more likely to be granted a bank loan. Not to mention that that firm also have better link to the business community. Research on gender and risk-taking behaviour generally varies. A gender-specific difference in risk aversion has been confirmed by researches, both in psychological and economic studies. On the one hand, some researches illustrate that women are likely to be more risk averse than men (Barber and Odean, 2001). This risk aversion can be found in a variety of studies’ form, ranging from empirical evidences (Barber and Odean, 2001; Croson and Gneezy, 2009). More specifically, Barber and Odean (2001) found that by observing trading behaviour of both genders, they found that women are more risk averse. This is still true when women and men’s behaviour are analysed through a common investment game (Charness and Gneezy, 2012). Moreover, this characteristic of women is also be found in their individuals’ asset management. Finucane et al. (2000) illustrates that women usually tries to get rid of risky assets. Sunden and Surette (1998) confirms this and emphasise this is especially true when women are in their single period. Jianakoplos and Bernasek (1998) also noted that single women are in favour of avoiding risks when they conduct wealth allocation. Generally, Powell and Ansic (1997), in his study, states that among factors which can show the difference between men and women, only risk aversion stands out to be affected by the gender factor. Specifically, in banking sector, a few studies have tried to determine the effect of gender on the performance of banks. Some researches focus on the gender of loan officers and find that the default rates of loans originated by women are lower than men’s (Beck et al., 2009). This finding is consistent with the view that women take lower risk than men. In the context of bank firm relationships, Bellucci et al. (2010) also find that women are more risk averse and less self-confident. In addition, when women are members of the board of directors, research shows that they take their supervisory role very seriously. Lenard et al. (2014) studied the board of directors in all firms except in the financial sector and found that a higher proportion of women on board were associated with lower variation in market returns of stock. Robinson and Dechant (1997) note that female directors are said to work harder, with better communication skills, contributing to a better overall board problem-solving ability. Eagly and Carli (2003) suggest that women must demonstrate additional capacity to reach 1154
4. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 directorship, which implies that women are quite diligent in the role of director. On the other hand, compared to women, men could be more risk averse (Iqbal et al., 2006; Adams and Funk, 2012; Sapienza et al., 2009, Berget et al., 2014). More specifically, related to stock option awards, Iqbal et al. (2006) analysed risk attitudes of male and female executives and they found that the selling behaviour of male executives consists of more risk than what was done by the female ones. In addition, Adams and Funk (2012) provided evidence that women who are directors may not always be the same as the majority, in this case, female board members are more risk loving than their male counterparts. Using survey data, Adams and Funk (2012) demonstrate that female directors are less risk averse than their male counterparts, as opposed to overall demographic results. Sapienza et al. (2009) provide evidence of the biological basis for career options in the financial sector. They examined a sample of MBA students from the University of Chicago and found that women with higher circulating testosterone levels were associated with a reduced risk aversion. Those in the study with high testosterone and low risk aversion were more likely to pursue a financial career, even when the gender has been controlled. Berger et al. (2014) examines the effect of board member characteristics on risk taking in German banks over the period 1994-2010. They consider portfolio risk as measured by two indicators: risk-weighted asset-to-total asset ratio and Herfindahl-Hirschman index of loan portfolio concentration. By studying the composition of the executive board in the banking industry, they found that changes in board of directors resulting in a higher proportion of female members increase their portfolio risk, both in two measures. They found that higher risk taking was associated with the young age of executives, lower percentage of executives with a Ph.D. and - last but not least – female’s existence in the board. Therefore, they support the view that the presence of women in management comes with risks. However, it should be emphasised that they consider the two measures related to portfolio risk and that the proportion of women on the board of directors in their sample is very low (about 3%). Last but not least, there have been some neutral findings which tell no difference between men and women. Maxfield et al. (2010) examines risk trends and decision-making skills of female managers. Their survey found that the motivations for women to take risks are the same as the motivations identified in the study as gender blind in general. In the financial sector, Bliss and Potter (2002) found no difference in risk-taking between male and female mutual fund managers. Atkinson et al. (2003) found that male and female fixed income mutual fund managers did not differ significantly in performance or risk. Zigraiova (2015) studies how the composition of banks’ management board may influence their risk-taking behaviour for some banks in the Czech Republic in the period 2001-2012. She examines the effect of female directors in addition to the average age, the proportion of non-national directors and director education. Risk is measured by four variables: z-score, bad debt ratio, profit volatility, and ratio of liquid assets to deposits and short-term financing. She found mixed evidence on the impact of female directors on the risk-taking behaviour of banks. Different results for different types of Czech banking (building societies, commercial banking) and different risk variables. 1155
5. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 3. Researh methodology 3.1. Data The data used by the author is a secondary data source. The secondary data source used is the data collected from Finpro and the Annual Consolidated Financial Statements (including Balance Sheet, Production and Business Report, Cash Flow Report currency and financial statement) of 30 Vietnamese commercial banks over 10 years from 2008 to 2018. 1 3.2. Regression model To investigate the effect of CEO gender on credit risk, we run the following multivariate regression model: = + + (1)where NPL is non-performing loan ratio measured by the ratio of all debts in group 3, 4 and 5 (according to the State Bank of Vietnam, 2015 and 2017) over total outstanding loans. Our main interested variable is CEO which takes the value of 1 if the CEO is a male and 0 otherwise. Following the previous literature (Huang and Kisgen, 2013), our control variables include LOAN measured natural logarithm of total loans, equity on asset ratio EA, bank size measured by the natural logarithm of total assets and return to asset ratio. Model (1) is also controlled for bank fixed effects . 4. Results 4.1. D escriptive Statistics and correlations matrix Table 1 provides some descriptive statistics including the mean, maximum, minimum, standard deviation and the number of observations for each variable. Table 1: Data description Standard Variables Mean Maximum Minimum Observations Deviation NPL 0.018 0.11 0 0.016 330 CEO 0.88 1 0 0.32 311 LOAN 0.52 0. 82 0.11 0.17 330 EA 0.10 0. 46 0.03 0.06 330 SIZE 31.92 34.81 28.51 1.22 320 ROA 0.0087 0.0595 -0.0599 0.0086 330 Source: Author’s calculations. From Table 1, we can observe that the NPL ranges between 0 and 0.11 with the mean value of 0.018 and standard deviation of 0.016 indicating low variance. The average value of CEO is recorded at 0.888 which means that there are more male CEOs than female ones, standard deviation of 0.32. As for the control variables, LOAN ranges between 0.11 and 0.82 with an average of 0.52 and standard deviation of 0.17 signifies a low variance. On the other hand, the average of EA recorded at 0.10 with a range of 0.03 and 0.46, standard deviation of 0.06. The SIZE ranges between 28.51 and 34.81 with an average of 31.92 and standard 1156
6. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 deviation of 1.22 signifies a high variance. Lastly, ROA ranges between -0.0599 and 0.0595 with an average of 0.0087 and standard deviation of 0.0086 signifies a low variance. Table 2: Correlation Matrix NPL CEO LOAN EA SIZE ROA NPL 1.000 CEO -0.069 1.000 LOAN 0.068 -0.164 1.000 EA 0.011 -0.065 -0.108 1.000 SIZE 0.046 0.178 0.213 -0.711 1.000 ROA -0.102 -0.007 0.071 0.320 -0.246 1.000 Source: Author’s calculations. Table 2 reports the correlation coefficients between all variables in (1). As we can see from Table 2, no coefficient is greater than 0.7. This means our research model is free from the multicollinearity problem. 4.2. Empirical Results and Analysis Table 3: Main regression results VARIABLES NPL CEO -0.00723* (0.00368) LOAN -0.00466 (0.0105) EA 0.0682 (0.0288) SIZE 0.00355* (0.00200) ROA -0.234* (0.122) CONSTANT -0.0903 (0.0648) Observations 303 R-squared 0.046 Standard errors in parentheses. p<0.01, p<0.05, * p<0.1 Source: Author’s calculations. Our main regression results are reported in Table 3. We spot some interesting results. First, CEO have a negative impact on NPL and its coefficient is statistically significant at 10% level. The coefficient of CEO is -0.00723 which shows that on average the ratio of non- 1157
7. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 performing loan on total loans of banks with male CEOs is lower than those with female CEOs by a value off 0.00723. Among the control variables, ROA and SIZE are both statistically significant at 10% level while LOAN is statistically insignificant. In detail, EA has a positive impact on NPL. The coefficient of EA is 0.0682 which shows that when equity to total assets ratio increases by one percent the non-performing loan ratio increases by 0.0628 percent. On the other hand, bank size has the positive effect on NPL. When SIZE increases by one unit, NPL increases by 0.00355. However, ROA negatively influences NPL, with its coefficient being -0.234. 4.3. Robustness tests To make the conclusions more convincing, the authors continues to test the impact of CEO gender on banks’ non-performing loan ratio by undertaking two robustness tests namely: (i) controlling for macroeconomic condition expressed by GDP growth rate and (ii) controlling for financial crisis. 4.3.1. Controlling for GDP growth rate In the first robustness test, we regress the following model: a NPL it = a 0 + a 1CEO it + a 2LOAN it + a3EA it + a 4SIZE it + a 5ROA it + a 6GDP it + i + εit (2) where GDP is the gross domestic product growth rate. Table 4: Regression results which control GDP growth rate VARIABLES NPL CEO -0.00782 (0.00358) LOAN 0.00533 (0.0105) EA 0.0770 (0.0281) SIZE 0.00672 (0.00209) ROA -0.248 (0.118) GDP -0.573 (0.139) CONSTANT -0.163 (0.0653) Observations 303 R-squared 0.103 Standard errors in parentheses. p<0.01, p<0.05, * p<0.1 Source: Author’s calculations. 1158
8. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 The results of regression (2) are displayed in Table 4. Consistent with our main results, CEO has a negative impact on NPL. The coefficient CEO is statistically significant at 5%. Similarly, the equity to asset ratio and bank size positively associate with bank’s non- performing loan ratio, while ROA negatively affects NPL. On the other hand, GDP growth rate shows its important role in affecting banks risk performance. GDP is statistically significant at 1% level and has a negative impact on NPL. In detail, if GDP growth rate increases by one percentage point, banks’ non-performing loan ratio decreases by 0.573 percentage point on average. 4.3.2. Controlling for financial crisis The global financial crisis highlighted the importance of effective corporate governance in managing bank risk (Peni and Vahama, 2012; Pathan and Faff, 2013). Francis et al. (2015), note that the role of boards would be more important and thus more visible in terms of bank performance. In a study of banks with female CEOs, Palvia et al. (2015) provide evidence that for smaller banks, those with female CEOs and female board chairs were less likely to fail during the financial crisis. Therefore, in order to further our analysis, we also control for financial crisis periods into our main model of specification: = + + (3)where CRISIS is measured in binary data, the year with crisis takes the value of 1 and 0 otherwise. In our sample period, the year of 2008 and 2009 are recorded as financial crisis period. Table 5: Regression results which control financial crisis VARIABLES NPL CEO -0.00673* (0.00359) LOAN 0.00509 (0.0105) EA 0.0427 (0.0288) SIZE -0.00392 (0.00272) ROA -0.169 (0.120) CRISIS -0.0144 (0.00365) CONSTANT 0.147* (0.0871) Observations R-squared 303 R-squared 0.099 Standard errors in parentheses p<0.01, p<0.05, * p<0.1 Source: Author’s calculations. 1159
9. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Table 5 reports the results of regression (3). The results show that our previous analysis is hold. CEO have a negative impact on NPL and its coefficient is statistically significant at 10% confident level. Interestingly, during financial crisis the non-performing loan ratio is lower that during non-crisis period. This result may be due to the fact that banks are more cautious with their lending activity during the period of crisis. 5. Conclusion remarks This paper aims to analyse the relationship between CEO’s gender and the non- performing loan ratio of commercial banks in Vietnam. We employ a data set which includes 30 Vietnam commercial banks over the period 10 years from 2008 to 2018. To investigate the effect of CEO gender on credit risk, we run a fixed effect multivariate regression model in which the dependent variable is the non-performing loan ratio and the main interested variable is CEO gender. Our results show that male CEO, i.e. CEO takes value of 1, has a negative impact on NPL and its coefficient is statistically significant at 10% level in our main regression model. On average the ratio of non-performing loan on total loans of banks with male CEOs is lower than those with female CEOs by a value off 0.00723. The negative relationship between CEO gender and non-performing loan are consistent through another two robustness tests, namely controlling for GDP growth rate and controlling for financial crisis period. Based on the findings from the empirical analysis, boards of directors may adjust their management strategy including appointing male or female CEO. Also, investors can use these results in managing their investment portfolio, based on their risk appetite. Last but not least, policymakers, to some extent, may determine which banks are potentially riskier than the other. 1 List of 30 banks using in this study: Symbol Description ABBank An Binh Commercial Joint Stock Bank ACB Asia Commercial Bank BAB Bac A Commercial Joint Stock Bank BAOVIET Bank Bao Viet Joint Stock Commercial Bank BID Bank for Investment and Development of Viet Nam CTG Vietnam Joint Stock Commercial Bank for Industry and Trade DongA Bank Dong A Commercial Joint Stock Bank EIB Vietnam Export Import Commercial Joint Stock Bank HDB Ho Chi Minh City Development Joint Stock Commercial Bank KLB Kien Long Commercial Joint Stock Bank LPB LienViet Post Joint Stock Commercial Bank Maritime Bank Vietnam Maritime Commercial Joint Stock Bank MBB Military Commercial Joint Stock Bank 1160
10. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 NamABank Nam A Commercial Joint Stock Bank NVB National Citizen Commercial Joint Stock Bank PG Bank Petrolimex Group Commercial Joint Stock Bank PvcomBank Vietnam Public Joint Stock Commercial Bank Saigonbank Saigon Bank for Industry and Trade SCB Sai Gon Commercial Joint Stock Bank SeABank Southeast Asia Joint Stock Commercial Bank SHB Saigon – Hanoi Commercial Joint Stock Bank STB Sai Gon Thuong Tin Commercial Joint Stock Bank TCB Vietnam Technological and Commercial Joint Stock Bank TPB Tien Phong Commercial Joint Stock Bank VBB Vietnam Thuong Tin Commercial Joint Stock Bank VCB Joint Stock Commercial Bank for Foreign Trade of Vietnam VIB Vietnam International Commercial Joint Stock Bank VietABank Viet A Commercial Joint Stock Bank VietCapital Bank Viet Capital Commercial Joint Stock Bank VPB Vietnam Prosperity Joint Stock Commercial Bank REFERENCES Abd Karim, M. Z., Chan, S. G., & Hassan, S. (2010) ‘Bank efficiency and non- performing loans: Evidence from Malaysia and Singapore’, Prague Economic Papers, 2(1). Adams, R. B., & Funk, P. (2012), ‘Beyond the glass ceiling: Does gender matter?’, Management science, 58(2), 219-235. Atkinson, S. M., Baird, S. B., & Frye, M. B. (2003) ‘Do female mutual fund managers manage differently?’, Journal of Financial Research, 26(1), 1-18. Barber, B. M., & Odean, T. (2001), ‘Boys will be boys: Gender, overconfidence, and common stock investment’, The Quarterly Journal of Economics, 116(1), 261-292. Beck, T., Behr, P., & Guettler, A. (2013), ‘Gender and banking: are women better loan officers?’, Review of Finance, 17(4), 1279-1321. Bellucci, A., Borisov, A., & Zazzaro, A. (2011) ‘Do male and female loan officers differ in small business lending? A review of the literature’, In The economics of small businesses (pp. 195-219). Physica-Verlag HD. Berger, A. N., Kick, T., & Schaeck, K. (2014), ‘Executive board composition and bank risk taking’, Journal of Corporate Finance, 28, 48-65. 1161
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12. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020 ICYREB 2020 Vu, H.T., Duong, H.T., Barnett, B., & Lee, T.T. (2017), ‘A role (in)congruity study on Vietnamese journalists’ perception of female and male leadership’, Asian Journal of Communication 27(6), 648-664. Vo, A., & Harvie, C. (2009), ‘The changing face of women managers in small and medium sized enterprises in Vietnam’, In C. Rowley, & Q. Truong (Eds.), The changing face of Vietnamese management (pp. 158-182). London: Routledge Taylor & Francis Group. Zigraiova, D. (2016), ‘Management Board Composition of Banking Institutions and Bank Risk-Taking: The Case of the Czech Republic’, IES Working Paper, No. 02/2016. 1163