[Download] Tải Tác động của giới tính ceo đến tỷ lệ nợ xấu trong ngành ngân hàng ở Việt Nam – Tải về File Word, PDF

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

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

Download


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. Mời các bạn cùng tham khảo!

Bạn đang xem: [Download] Tải Tác động của giới tính ceo đến tỷ lệ nợ xấu trong ngành ngân hàng ở Việt Nam – Tải về File Word, PDF

*Ghi chú: Có 2 link để tải biểu mẫu, Nếu Link này không download được, các bạn kéo xuống dưới cùng, dùng link 2 để tải tài liệu về máy nhé!
Download tài liệu Tác động của giới tính ceo đến tỷ lệ nợ xấu trong ngành ngân hàng ở Việt Nam File Word, PDF về máy

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

Mô tả tài liệu

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. Descriptive 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

  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:
    NPLit = a0 + a1CEOit + a2LOANit + a3EAit + a4SIZEit + a5ROAit + a6GDPit + ai + 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

  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

  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

  11. INTERNATIONAL CONFERENCE FOR YOUNG RESEARCHERS IN ECONOMICS & BUSINESS 2020
    ICYREB 2020

    Bliss, R. T., & Potter, M. E. (2002), ‘Mutual fund managers: does gender matter?’, The
    Journal of Business and Economic Studies, 8(1), 1.
    Croson, R., & Gneezy, U. (2009), ‘Gender differences in preferences’, Journal of
    Economic Literature, 47(2), 448-74.
    Charness, G., & Gneezy, U. (2012), ‘Strong evidence for gender differences in risk
    taking’, Journal of Economic Behavior & Organization, 83(1), 50-58.
    Eagly, A. H., & Carli, L. L. (2003), ‘The female leadership advantage: An evaluation
    of the evidence’, The Leadership Quarterly, 14(6), 807-834.
    Finucane, M. L., Alhakami, A., Slovic, P., & Johnson, S. M. (2000). The affect heuristic
    in judgments of risks and benefits. Journal of behavioral decision making, 13(1), 1-17.
    Huang, J., & Kisgen, D. J. (2013), ‘Gender and corporate finance: Are male executives
    overconfident relative to female executives?’, Journal of Financial Economics, 108(3),
    822-839.
    Iqbal, Z., Sewon, O., & Baek, H. Y. (2006), ‘Are female executives more risk-averse
    than male executives?’, Atlantic Economic Journal, 34(1), 63-74.
    Jianakoplos, N. A., & Bernasek, A. (1998), ‘Are women more risk averse?’, Economic
    Inquiry, 36(4), 620-630.
    Kaaya, I., & Pastory, D. (2013), ‘Credit risk and commercial banks performance in
    Tanzania: A panel data analysis’.
    Kithinji, A. M. (2010), ‘Credit risk management and profitability of commercial banks
    in Kenya’.
    Lenard, M. J., Yu, B., York, E. A., & Wu, S. (2014), ‘Impact of board gender diversity
    on firm risk’, Managerial Finance, 40(8), 787-803.
    Maxfield, S., Shapiro, M., Gupta, V., & Hass, S. (2010), ‘Gender and risk: women, risk
    taking and risk aversion’, Gender in Management: An International Journal.
    Pham, T., & Talavera, O. (2018), ‘Discrimination, social capital, and financial
    constraints: The case of Viet Nam’, World Development, 102, 228-242.
    Powell, M., & Ansic, D. (1997), ‘Gender differences in risk behaviour in financial
    decision-making: An experimental analysis’, Journal of Economic Psychology, 18(6),
    605-628.
    Robinson, G., & Dechant, K. (1997), ‘Building a business case for diversity’, Academy
    of Management Perspectives, 11(3), 21-31.
    Sapienza, P., Zingales, L., & Maestripieri, D. (2009), ‘Gender differences in financial
    risk aversion and career choices are affected by testosterone’, Proceedings of the National
    Academy of Sciences, 106(36), 15268-15273.
    Sunden, A. E., & Surette, B. J. (1998), ‘Gender differences in the allocation of assets
    in retirement savings plans’, The American Economic Review, 88(2), 207-211.

    1162

  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

Download tài liệu Tác động của giới tính ceo đến tỷ lệ nợ xấu trong ngành ngân hàng ở Việt Nam File Word, PDF về máy