Gender Diversity Impact on Bank Performance amid COVID-19 Crisis

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Explore the significant role of women on corporate boards in enhancing bank efficiency and performance during the COVID-19 crisis. Research indicates that gender diversity leads to improved decision-making, creativity, and lower bank riskiness. Women directors have shown to positively influence bank profitability and risk management, especially during times of crisis such as the COVID-19 pandemic.

  • Gender Diversity
  • Bank Performance
  • COVID-19 Crisis
  • Women Directors
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  1. Board Gender Diversity and Bank Performance during COVID-19: Did Women Save the Day? Yuliana Loginova (ICEF HSE) Maria Semenova (LaBS HSE, msemenova@hse.ru) MENA-Asian FEBS Conference, November 21, 2024

  2. Motivation: women in bank boards The greater representation of women on corporate boards is proven to significantly enhance bank efficiency (Valls Martinez et al., 2019; Beji et al., 2021; Galletta et al., 2022) Female directors establish a comprehensive governance approach, enhancing creativity and innovation in decision-making (Huse and Solberg, 2006; Huse et al., 2009) A diverse board is also associated with superior bank performance and lower bank riskiness (Gulamhussen and Santa, 2015; Owen & Temesvary, 2018) Gulamhussen and Santa (2015) confirm the negative relation between the presence of women directors on the board and banks attitude to risk Jabari and Muhamad (2022) conclude that women directors also improve insolvency risk measures for Islamic banks. Women in senior management positions tend to have even stronger effect, which might be explained by the glass ceiling effect, as women must overcome discrimination to obtain higher positions (Adams et al., 2012) Ararat et al. (2023) find positive effects of gender diversity of the workforce on bank risk measures as well as on bank effectiveness

  3. Motivation: women in bank boards in crisis Reinert et al. (2016) show that the impact of women directors on bank performance increased during the 2007 2009 financial crisis almost doubled compared with previous and later time periods. Gender diversity as a major factor in improving bank performance during 2007-2009 crisis Italy (Del Prete and Stefani, 2021) Luxembourg, (Reinert et al., 2016) UK (Lu and Boateng (2023) ) Europe (Garc a-Meca et al., 2015) OECD (Gulamhussen and Santa, 2015) China (Ting, 2021) ASEAN: Brunei, Cambodia, Myanmar, Laos, Indonesia, Malaysia, the Philippines, Thailand, Singapore, and Vietnam (Bouteska and Mili, 2021)

  4. Motivation: COVID-19 Female national leaders did better during the first wave of the pandemic. They reacted more quickly and decisively and implemented a proactive and effective policy against COVID-19 (Garikipati and Kambhampatim, 2021) Firms with gender-diverse boards experienced higher abnormal returns as a response to the COVID-19 pandemic (Akhtar et al., 2022) Positive relationship between board gender diversity and banks responses to COVID-19: the more women on the board - the more banks support their clients and employees during the crisis + higher levels of charitable contributions and donations (Kara et al., 2022).

  5. Hypotheses Profitability Hypothesis 1: A higher share of women on boards is associated with higher bank profitability during the COVID-19 crisis Hypothesis 2: The positive impact of women on bank profitability during the COVID-19 crisis is more pronounced in the countries where the incidence of COVID-19 is higher Risks Hypothesis 3: Higher share of women on bank boards is associated with lower bank riskiness during the COVID-19 crisis Hypothesis 4: The impact of women on bank riskiness during the COVID-19 crisis is more pronounced in the countries where the incidence is higher

  6. Data 86 banks in 22 countries (Europe and the UK) 2015-2021 Board characteristics: BoardEx Bank fundamentals: Bureau van Dijk BankFocus Merging by ISIN and bank names Country-specific variables: World Bank

  7. Profitability Return on Assets (ROA) Return on Equity (ROE) Return on Average Assets (ROAA) Return on Average Equity (ROAE) 70 65.64 62.01 58.96 58.56 60 56.33 61.02 59.32 56.07 50 37.31 51.95 56.72 38.34 40 36.28 35.43 30 20 10.89 9.70 9.65 9.44 7.53 6.74 10 5.80 8.48 8.03 7.78 7.31 6.31 5.62 4.44 0 -10 2015 2016 2017 2018 2019 2020 2021 ROE ROAE ROA ROAA

  8. Risks Loan Loss Reserve Ratio (LLR) Non-performing Loans ratio (NPL) Z-score (SCORE) ) 40 33.34 35 32.62 29.75 30 27.74 25 18.82 20 15 10.03 10.11 7.86 10 7.35 6.64 6.55 4.80 4.21 3.21 5 4.01 3.98 3.62 3.88 2.35 0 2.46 1.76 -5 -10 2015 2016 2017 2018 2019 2020 2021 SCORE LLR NPL

  9. Board diversity 0.45 ? ??2 ???? = 1 ?=1 0.40 0.35 0.30 ??? ????? 0.25 ???? = 0.20 2015 2016 2017 2018 2019 2020 2021 mean_RFEM median_RFEM mean_B median_B

  10. Other variables COVID-19 DCOVID - equals 1 in 2020 and 2021 and 0 otherwise COVID - ratio of the infected to the population of a country Controls Board Controls % years years Total number of directors / total assets Average age of board members Average tenure on board of board members Bank Controls Profitability Logarithm of total assets Tier 1 capital ratio Efficiency ratio Bank Controls Risk Logarithm of total assets Capital funds / TA Gross loans / TA Country Control Logarithm of GDP per capita BoardEx BoardEx BoardEx RBOARD AGE TENURE log % % BankFocus BankFocus BankFocus LTA TIER CINC log % % BankFocus BankFocus BankFocus LTA CAPITAL LOANS log World Bank LGDP

  11. Models Hypotheses 1 and 3: 2015-2019 VS 2020-2021: ?????= ???????+ ??????????,? 1+ ??+ ??? full sample: ?????= ?????,? 1+ ? ?????? ?????? + ??????????,? 1+ +????????+ ??+ ??? Hypotheses 2 and 4: 2020-2021: ?????= ?(????? ??????) + ??????????,? 1+ ??+ ???

  12. Results: hypothesis I (FE) ROA ROAA ROE ROAE Variable 2015-2019 2020-2021 2015-2019 2020-2021 2015-2019 2020-2021 2015-2019 2020-2021 0.234** 0.817*** 0.243* 0.864* (0.331) (0.433) (0.328) (0.449) -25.777*** -26.013*** -27.006*** -25.114** (6.259) (9.808) (6.198) (10.177) -0.029 -2.968* 0.106 -3.153* (1.310) (1.729) (1.297) (1.795) 5.924*** 2.216 5.480*** 2.602 (1.724) (2.119) (1.707) (2.199) -3.768 1.461 -4.465 1.293 (3.975) (4.736) (3.937) (4.915) 4.033*** 2.147* 3.956*** 1.960 (1.100) (1.163) (1.089) (1.207) -0.859*** -0.952*** -0.893*** -1.018*** (0.188) (0.315) (0.186) (0.327) 23.111** 34.520*** 20.867* 34.122** (10.798) (12.665) (10.693) (13.142) 435 174 435 174 0.281 0.302 0.296 0.291 0.143 0.144 0.161 0.130 17.804*** 7.631*** 19.128*** 7.244*** 0.131 (0.055) 2.300** (1.034) 0.405* (0.216) 0.307 (0.285) -0.068 (0.657) 0.556*** (0.182) -0.133*** (0.031) 2.324 (1.784) 435 0.152 -0.011 8.176*** 0.167** (0.064) 1.546 (1.460) -0.244 (0.257) 0.358 (0.315) 0.564 (0.705) 0.389** (0.173) -0.157*** (0.047) 3.485* (1.886) 174 0.210 0.030 4.679*** 0.121 (0.045) 2.396*** (0.850) 0.196 (0.178) 0.359 (0.234) 0.004 (0.540) 0.430*** (0.149) -0.113*** (0.026) 2.749* (1.467) 435 0.170 0.011 9.329*** 0.153** (0.060) 0.772 (1.360) -0.338 (0.240) 0.538* (0.294) 0.269 (0.657) 0.348** (0.161) -0.106** (0.044) 2.133 (1.756) 174 0.185 0.0004 4.009*** RFEM RBOARD AGE TENURE LTA TIER CINC LGDP Observations R2 Adjusted R2 F Statistic

  13. Results: hypothesis I (system GMM) Variable RFEM ROA 7.290*** (1.25e-05) -25.22*** (0.121) 18.85*** (0.000181) + -3,130** (0.0127) 435 87 0.005 0.160 0.366 ROAA 5.476*** (0.000127) -24.17*** (0.112) 18.32*** (0.000109) + -3,210*** (0.00197) 435 87 0.000 0.191 0.300 ROE 0.130 (0.699) -1.279*** (0.659) 2.796*** (0.000308) + 194.7 (0.247) 435 87 0.001 0.022 0.420 ROAE 0.376 (0.113) -2.079*** (0.368) 2.114*** (0.000790) + -175.3 (0.207) 435 87 0.001 0.017 0.108 DCOVID RFEM*DCOVID Controls Constant Observations Number of banks AR(1) AR(2) Hansen test

  14. Results: hypothesis II (FE) Variables ROA ROAA ROE ROAE 6.737*** (2.380) 0,17 (0.480) + + 174 0,34 0,184 8.011*** 6.981*** (2.470) 0,194 (0.498) + + 174 0,33 0,172 7.646*** 1.158*** (0.351) 0,02 (0.071) + + 174 0,267 0,094 5.661*** 1.194*** (0.324) 0,038 (0.065) + + 174 0,257 0,082 5.392*** COVID*RFEM RFEM Controls Bank Fes Observations R2 Adjusted R2 F Statistic

  15. Results: hypothesis III (FE) LLR NPL SCORE 2015-2019 -0.039** (0.029) 0,39 (0.454) 0.229* (0.123) -0.725*** (0.145) -0.804*** (0.147) -0,15 (0.107) -3.263*** (0.881) yes 435 0.161 0.003 2020-2021 -0.064** (0.012) 0.523** (0.242) 0.118** (0.052) -0.262*** (0.061) -0.348*** (0.054) 0,059 (0.057) -1.759*** (0.344) yes 174 0.475 0.360 2015-2019 -0,065 (0.042) 0,259 (0.666) 0.375** (0.180) -1.218*** (0.212) -1.483*** (0.216) -0,148 (0.157) -6.835*** (1.294) yes 435 0.22 0.073 2020-2021 -0.048* (0.029) 1.078* (0.591) 0.283** (0.127) -0.394*** (0.148) -0.667*** (0.133) 0,163 (0.139) -2.925*** (0.840) yes 174 0.313 0.163 2015-2019 0.05 (0.263) -2.61 (4.142) -0.472 (1.119) 3.853*** (1.320) -1.746 (1.341) 0.526 (0.973) 9.857 (8.043) yes 435 0.03 -0.154 2020-2021 0.676 (0.636) 2.914 (12.866) -2.008 (2.774) -0,99 (3.227) -3.653 (2.891) 2.293 (3.030) 16.433 (18.272) yes 174 0.038 -0.172 Variable RFEM RBOARD AGE TENURE CAPITAL LOANS LGDP Bank FEs Observations R2 Adjusted R2 10.024*** 18.319*** 14.716*** 9.245*** 1.605*** 0.807*** F Statistic

  16. Results: hypothesis III (system GMM) Variables RFEM LLR NPL SCORE 9.470 (0.189) -0.780*** (1.04e-06) -1.335*** (1.91e-09) 33.48*** (1.05e-08) 30.21*** (0.000226) -55.2*** (0.183) DCOVID -1.240*** (6.57e-09) -0.957*** (0.00121) 19.54 (0.166) DCOVID*RFEM + + + Controls Constant 235.8*** (3.87e-06) 508.0*** (1.06e-09) 13,234** (0.0147) 435 87 0.000 0.000 0.274 435 87 0.000 0.001 0.367 435 87 0.005 0.048 0.148 Observations Number of banks AR(1) AR(2) Hansen test

  17. Results: hypothesis IV (FE) Variables COVID*RFEM LLR -0.117* (0.067) -0.028** (0.013) 0.506** (0.241) 0.121** (0.052) -0.263*** (0.060) -0.345*** (0.054) 0.053 (0.057) -1.730*** (0.342) yes 174 0.486 0.369 16.650*** NPL -0.135 (0.164) -0.035** (0.033) 1.058* (0.592) 0.285** (0.128) -0.396*** (0.148) -0.664*** (0.133) 0.156 (0.140) -2.892*** (0.842) yes 174 0.316 0.161 8.156*** SCORE 5.281 (3.551) 0.184 (0.714) -2.144* (12.822) -2.112 (2.763) -0.914 (3.214) 3.525* (2.880) 2.563 (3.023) 15.148 (18.215) yes 174 0.053 -0.162 0.988*** RFEM RBOARD AGE TENURE CAPITAL LOANS LGDP Bank FEs Observations R2 Adjusted R2 F-Statistic

  18. Profitability: Banks Separated by Board Size (FE) ROA ROAA ROE ROAE Variables LARGE SMALL LARGE SMALL LARGE SMALL LARGE SMALL DCOVID*RFEM 9.066*** 8.775*** 9.359*** 8.975*** 1.669*** 1. 063*** 1.596*** 1.208*** (3.143) (2.612) (3.167) (2.552) (0.371) (0.471) (0.349) (0.411) RFEM -0.648 0.526 0.622* 0.495** -0.064 0.048 -0.044 0.054* (0.440) (0.474) (0.443) (0.463) (0.052) (0.085) (0.049) (0.074) DCOVID -30.90*** -31.05*** -31.94*** -32.25*** -2.938** -6.334*** -3.03*** -5.120*** (10.034) (9.566) (10.113) (9.344) (1.186) (1.725) (1.114) (1.503) Controls + + + + + + + + Bank FEs + + + + + + + + Observations 305 305 305 305 305 305 305 305 R2 0.092 0.159 0.099 0.159 0.162 0.226 0.151 0.156 Adjusted R2 -0.122 -0.044 -0.114 -0.043 -0.036 0.04 -0.049 -0.047 F Statistic 2.505*** 4.615*** 2.697*** 4.641*** 4.742*** 7.159*** 4.387*** 4.529***

  19. Risks: Banks Separated by Board Size (FE) LLR NPL SCORE Variable LARGE -0.154** (0.065) -0.098* (0.052) 5.335*** (1.916) + + 305 0.062 -0.163 1.813* SMALL -0.013 (0.025) -0.020* (0.020) 1.558* (0.885) + + 305 0.204 0.016 6.996*** LARGE -0.228*** (0.080) -0.094 (0.063) 8.197*** (2.327) + + 305 0.119 -0.093 3.682*** SMALL -0.052 (0.046) -0.012* (0.037) 4.227** (1.631) + + 305 0.19 -0.001 6.411*** LARGE 2.045** (0.871) -0.543 (0.694) -50.977** (25.507) + + 305 0.047 -0.182 1.354*** SMALL 0.197 (0.476) -0.084 (0.387) -5.371 (16.890) + + 305 0.051 -0.173 1.469*** DCOVID*RFEM RFEM DCOVID Controls Bank FEs Observations R2 Adjusted R2 F Statistic

  20. Blau Index: subsample analysis Variable ROA ROAA ROE ROAE LLR NPL SCORE 2015- 2019 2015- 2019 2020- 2021 2015- 2019 2020- 2021 2015- 2019 2020- 2021 2015- 2019 2020- 2021 2015- 2019 2020- 2021 2015- 2019 2020- 2021 2020- 2021 0.491* (0.329) (0.519) (0.326) (0.538) (0.054) (0.077) (0.044) (0.072) (0.028) (0.014) (0.041) (0.035) (0.255) (0.758) + + + + + + + 0.931*** 0.497* 0.998*** 0.229** 0.162**0.188***-0.049***-0.085***-0.062**-0.092* BLAU 0,172 0,019 0,561 Controls Bank FEs Observ ations R2 Adjuste d R2 F Statistic + + + + + + + + + + + + + + + + + + + + + 435 174 435 174 435 174 435 174 435 174 435 174 435 174 0,285 0,3 0,299 0,29 0,172 0,215 0,183 0,188 0,171 0,479 0,226 0,316 0,03 0,034 0,147 0,142 0,165 0,129 0,013 0,036 0,026 0,003 0,015 0,365 0,079 0,166 -0,154 -0,177 18.104** * 7.570***19.443** 7.198***9.444***4.816***10.225** 4.070***10.791** 18.617** * 15.206** * 9.356***1.600***0.721*** * * *

  21. Blau Index: GMM VARIABLES ROA ROAA ROE ROAE LLR NPL SCORE 5.263*** 4.164*** 0.143 -0.100 -0.698*** -1.130*** 10.78 BLAU (0.000114) (0.000787) (0.611) (0.627) (1.43e-08) (0.01) (0.102) -32.48** -28.43** -1.876 -2.845 39.53*** 36.54*** -214.4 DCOVID (0.0275) (0.0494) (0.510) (0.207) (9.05e-11) (1.31e-05) (0.745) 262.6*** 264.5*** 31.01*** 27.41*** -19.4*** -16.70*** 22.2 DCOVID*BLAU (5.03e-08) + (7.58e-09) + (6.55e-11) + (5.02e-10) + (6.31e-11) + (0.000106) + (0.711) + Controls -3,588*** -3,501*** 152.7 -259.3** 251.5*** 517.6*** 10,041*** Constant (0.00161) (0.000360) (0.329) (0.0445) (1.34e-07) (0) (0.00810) 435 435 435 435 435 435 435 Observations Number of banks AR(1) AR(2) Hansen test 87 87 87 87 87 87 87 0.000 0.226 0.128 0.003 0.250 0.121 0.001 0.017 0.426 0.000 0.043 0.127 0.000 0.000 0.388 0.000 0.003 0.398 0.000 0.024 0.121

  22. Blau Index: COVID-19 exposure Variable COVID*BLAU ROA 5.240*** ROAA 5.436*** ROE 0.877*** ROAE 0.904*** LLR -0.111** NPL -0.138 SCORE 4.189 (1.861) (1.931) (0.274) (0.253) (0.053) (0.131) (2.846) 0.371 0.417 0.079 0.092 -0.038** -0.048* 0.143 BLAU (0.544) (0.565) (0.080) (0.074) (0.015) (0.037) (0.807) Controls + + + + + + + Bank FEs Observations R2 Adjusted R2 F Statistic + + + + + + + 174 0.338 0.182 7.940*** 174 0.328 0.17 7.593*** 174 0.268 0.096 5.701*** 174 0.255 0.08 5.332*** 174 0.495 0.38 17.242*** 174 0.321 0.167 8.332*** 174 0.049 -0.167 0.906***

  23. Conclusion Impact of female directors on bank profits and on bank riskiness in terms of credit risks was significant during the COVID-19 pandemic compared with the previous period The share of women on boards had a positive and significant impact on bank profitability during the COVID-19 crisis The positive impact of female board members on bank performance during the COVID-19 crisis is more pronounced in the countries where the incidence is higher Negative contribution of female directors to credit risk is also more pronounced during the pandemic compared with the previous period especially in countries with the higher incidence rates. Positive and significant contribution of women directors to the reduction of insolvency risk is proven only for banks with larger boards

  24. Thank you!

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