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Indian Journal of Finance and Banking; Vol. 4, No. 1; 2020 
                                       ISSN 2574-6081   E-ISSN 2574-609X 

Published by Centre for Research on Islamic Banking & Finance and Business, USA 

 

 
33 

                      

Corporate Governance Practices and Bank Performance: Evidence from 
Indian Banks 

 
 

Brahmaiah Bezawada PhD 
Professor of Finance and Accounting 

ICFAI Business School (IBS), IFHE, Hyderabad, India 
E-mail: brahmaiahb@ibsindia.org 

 
 
Abstract 
The study examines the corporate governance practices and analyzes the role of the board characteristics (size of the board, 
the composition of the board, and functioning of the board) on the performance and asset quality of banks. We use a 
sample of 34 commercial banks consisting of 19 public sector banks and 15 private sector banks from 2009 to 2018 
accounting for 93 percent of the total banking industry in India. The study finds that busy directors and the number of 
meetings have a positive significance on bank performance. The percentage of independent directors and the percentage of 
busy directors influence a significant negative relationship on the net non-performing assets ratio. The board size and 
number of meetings are associated negatively with Tobin's Q significantly and the percentage of busy directors is a 
significantly positive impact on Tobin's Q. The board size has a significantly negative impact on bank performance. The 
research findings provide some insights into corporate governance to the RBI for considering appropriate policy guidelines 
on corporate governance in the banking industry in India. The paper adds to the existing literature on corporate governance 
mechanisms and banking industry performance. 
 

 
 
1. Introduction 
The role and importance of the board of directors in the corporate governance of financial and banking institutions have 
become more important during the post-global financial crisis of 2008. The Basel Committee on Banking Supervision 
(BCBS, 2015) emphasizes the importance of corporate governance. The primary objective of corporate governance would 
be safeguarding stakeholders' interest in conformity with public interest on a sustained basis. Good corporate governance 
practices in banking institutions are essential conditions for achieving and maintaining public trust and confidence in the 
banking, financial and economic systems of the country. Corporate governance deals with the organizational structure 
through which the objectives of the firms are achieved. Good corporate governance will enable better financial performance 
and provide fair return and treatment to all stakeholders and incentives for management to pursue objectives that are in the 
best interests of the institution and its shareholders. 

The Indian banking sector is the largest and most complex among emerging economies of the world. The banking 
industry supported commerce, industries, trade, and personal segments of the economy by providing different types of 
banking products. The nature of the banking business enhances the information asymmetry and reduces stakeholders' ability 
to monitor bank managers' decisions. Banks do business with other people's savings and money and trust of depositors' 
forms the cornerstone of their existence. Therefore, the banking industry is subject to more intense regulation than other 
industries, as they are responsible for safeguarding and protecting the depositors' rights, guaranteeing the stability of the 
financial system, and reducing systemic risk. Regulation may be considered as an additional measure of corporate 
governance mechanism and occasionally it diminishes the effectiveness of other mechanisms in the corporate governance of 
banks. The Reserve Bank of India (RBI) widened highly and deepened banking reforms and strengthened structurally the 
banking industry. Most of the banks from the public and private sectors are listed on the stock exchanges and are actively 
trading at the stock exchanges. The Securities and Exchange Board of India (SEBI) introduced a sound corporate 
governance system to improve the functioning of the banking system. Corporate governance in banks plays an important 
role due to the complexity and uniqueness of banking institutions. Boards are expected to take proper control and fair 
decisions on various strategies and policy choices.  

Regulators may discourage competition and discipline banks by imposing restrictions on ownership structures and 
business operations. The size, composition, and functioning of boards might show directors' motivation and their ability to 
adequately supervise and advise managers' decisions. SEBI introduced a sound corporate governance system not only to 
improve the functioning of the banking system but also to ensure full and fair disclosures by the banking industry. The 
boards of directors of Indian banks are responsible and accountable for the operations and performance of the banks and to 
monitor and advise top management and operational management of banks. SEBI lays more importance on the board 
through a comprehensive and effective regulatory framework for corporate governance of banks. The RBI introduced "fit 
and proper" criteria for the constitution of the bank board and selection of the board of directors. The SEBI issued 

Keywords: Corporate Governance, Board Characteristics, Performance of Banks, Indian Banking.  



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guidelines for the board of directors under the Clause-49 listing agreements making corporate governance practices 
mandatory for all listed companies in India. 

We examine a comprehensive set of board characteristics (size, composition, and functioning of the board) that might 
affect directors' incentives and abilities to effectively advise and monitor top management. Most of the previous studies 
focus on non-bank firms and a lot of studies are on corporate governance related to the developed countries. There is little 
work carried out on the corporate governance of the banking sector of emerging economies in general and India in 
particular. The role of the board of directors in the banking sector is not well explored even in developed countries. The 
existing literature on bank corporate governance in India mainly focuses on the impact of ownership structure on bank 
performance. Only a few studies focused on corporate governance in emerging economies (Garg, 2007; Fu & Heffernan, 
2009; Liang et al., 2013).  

We study the corporate governance framework in the Indian banking industry, the role of the board of directors (size, 
composition, independence and functioning of the board) and investigate the influence of board characteristics on banks' 
performance. The paper is organized as follows. Section 2 reviews the literature on the corporate governance of banks. 
Section 3presents the research methodology and description of variables. Section 4 discusses the empirical results and the 
last section concludes the paper.  
 
2. Literature Review  
This section covers literature on board size, board independence, the proportion of executive directors, the proportion of 
busy directors and the number of meetings held on bank performance. The role of the independence of directors is the main 
focus of corporate governance in banks. The corporate governance literature on banks offers no conclusive results on the 
role of independent directors on the performance of the banks. One strand of the literature finds that the presence of 
independent directors on the board tends to lessen the conflict of interests and be more effective in reducing the agency 
problem. A lot of studies find that, while independent directors increase the quality of monitoring, while few studies find 
that they may lack sufficient knowledge of bank-specific information and lead to inferior decision making which leads to 
the poor performance of banks. 
 
2.1 Literature Review on Independence of Directors 
Rosenstein & Wyatt (1990) report that stock prices move favorably and positively to the nomination of independent 
directors on the board. Bhagat & Black (2002) conclude that corporate governance literature offers no conclusive evidence 
on the effect of appointing outside directors. Klein (2002) reports that earnings quality increases with the increasing 
proportion of independent directors. Rowe et al. (2011) use a sample of 41 banks and examine the impacts of board size, 
percentage of executive directors and independent directors, on Chinese bank performance. They find that the percentage of 
executive directors on the boards indicates a significantly negative impact on bank performance. Nguyen & Nielsen (2010) 
find that the stock price drops following the sudden death of independent directors. Francis et al. (2013) report that a 
board with strong independent directors shows a positive and significant relationship with firm performance. Liang et al. 
(2013) study a sample of 50 large Chinese banks; find that the proportion of independent directors has a significant impact 
on both bank performance and asset quality. Muniandy & Hillier (2015) examine the impact of board independence on 
firm performance using a sample of 151 South African firms and find a positive relationship between firm performance and 
independent directorship. Liu et al. (2015) conclude that independent directors have an overall positive effect on firm 
operating performance in China. Fuzi et al. (2016) study a sample from different countries, report a mixed association 
between the proportions of independent directors and firm performance. Independent directors have incentives to promote 
and protect the interests of shareholders and to be effective monitors of managers. They find that the appointment of 
outside directors is considered positively and provide excess stock returns.  
 
2.2 Literature Review on Board Size  
Jensen (1993) argues that large corporate boards are less effective due to the problems of coordination, control, and 
decision-making and give excessive control to CEOs. Yermack (1996) finds that firms with small boards had a better 
financial performance. Adams & Mehran (2005) report that board size is positively and significantly related to the 
performance of the banks. However, other researchers argue that larger boards improve firm performances by facilitating 
manager supervision and bringing more human capital to advise managers. De Andres & Vallelado (2008) find that an 
inverted U-shaped relationship between bank performance and board size, and between the proportion of non-executive 
directors and performance. Their results show that bank board composition and size are related positively significant to 
directors' ability to monitor and advise management. Fu & Heffernan (2009) study the relationship between market 
structure and performance in China’s banking and finds that the private sector banks have higher efficiency and profitability 
than the state-owned government banks. García-Herrero et al. (2009) investigate a panel data of 87 Chinese banks from 
1997 to 2004 and find that less concentrated banking ownership increases bank performance and profitability. Pathan 
(2009) examines a sample of 212 large US banks and finds that small and less restrictive boards positively affect bank risk-
taking. Adams & Mehran (2012) investigate the relationship between board governance and performance and the study 
reports that board size is positively correlated with performance. Francis et al. (2013) find that better corporate governance 
reduces the dependence of emerging market firms on internally generated cash flows, and lowers financing costs. Liang et al. 



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(2013) investigate a set of board characteristics such as size, composition, and functioning of the board, and analyze their 
impact on bank performance. They find that the board of directors plays a significant role in bank governance in China. 
Malik et al. (2014) report a significant positive relationship between board size and bank performance. However, several 
researchers (Jensen, 1993; Yermack, 1996; Liang et al., 2013) conclude a negative association between board size and firm 
performance. Hermalin & Weisbach (1991); Yermack (1996); Hermalin & Weisbach (2001); Francis et al. (2012) find no 
significant impact between independent directors of the boards and firm performance. Empirical evidence on board 
independence and firm performance is inconclusive concerning banks. (Hermalin & Weisbach, 1991; Agrawal & Knoeber, 
1996; Bhagat & Black, 2002) and some other studies find no effect (Adams & Mehran, 2012) and some other studies find a 
positive effect (Liang et al., 2013). 
 
2.3 Literature Review on Busy Directors  
We define busy directors as the director who serves on three or more boards. Fich & Shivadasani (2006) find that when a 
majority of outside directors serve on three or more boards, firms show lower market-to-book ratios and lower operating 
profitability. Fich & Shivdasan (2006) find that firms with busy boards are associated with weak corporate governance. 
These firms experience lower market-to-book ratios and weaker profitability. When directors become busy as a result of 
acquiring an additional directorship, other companies in which they hold board seats experience negative annual returns. 
Busy outside directors are more likely to depart boards following poor performance. Ahn et al. (2010) find that directors 
serving on multiple boards allow value-destroying acquisitions  
 
2.4 Literature Review of Indian Studies  
The following studies are undertaken in India by (Garg, 2007; Kumar & Singh, 2013; Gafoor et al., 2018; Sarkar & Sarkar, 
2018). Garg (2007) examines the board size and board independence on a firm's performance and finds that there is an 
inverse association between board size and firm performance of Indian firms. The study finds independent directors have 
failed to perform their monitoring role effectively and improve the performance of the firm. Kumar & Singh (2013) 
examine the relationship of board size on the firm value of listed companies in India and find a negative correlation between 
board size and performance. Gafoor et al. (2018) study a sample of 36 Indian commercial banks for the period 2001 to 
2014. They find a significant positive relationship between board size and bank performance and report a positive and 
significant relationship between board independence and bank performance. Sarkar & Sarkar (2018) examine the effect of 
board governance on the performance of Indian PSBs and PVBs for the period from 2003 to 2012. They find strong 
ownership effects with board independence and positive correlation with the performance of PVBs significantly and a 
significant but negative correlation with the performance of PSBs. They conclude that governance implications for 
strengthening the composition of the board of directors of PSBs. 
 
3. Data, Methodology, and Description of Variables 
We use a sample data of 34 scheduled commercial banks (SCBs) of India. The total sample 34 scheduled commercial banks 
consisting of 19 government-owned public sector banks (PSBs), 15 private sector banks (PVSBs) comprise 7 new 
generation technology-oriented banks (NPBS) and 8 old private sector banks (OPSBs), for a period of 10 years ranging 
from 2009 to 2018. So, the panel data are built with 340 bank-year observations. Data on board characteristics such as 
board size, number of directors, the proportion of independent directors, busy directors, executive directors and the number 
of meetings held are mainly collected from CMIE. The performance variables include return on assets (ROA), net non-
performing assets (NNPAs) ratios are taken from Statistical Tables Relating to Banks (STRB) from RBIs website, and 
shareholders’ annual market returns are calculated from yearly closings prices of respective banks’ shares, data published by 
the Bombay Stock Exchange (BSE) Ltd. The variables used for the study are three broad categories such as performance 
variables, board characteristics variables and control variables. Performance variables are used as the proxy for dependent 
variables, and board variables as the proxy for independent variables. The control variables are used to control the potential 
effects on performance.  
 
3.1 Dependent Variables: Performance Measures 
We measure bank performance by using Tobin's Q, the return on assets (ROA), the annual market return of a shareholder 
(SR), and asset quality is measured by NNPAs. We calculate Tobin's Q as the book value of total assets minus the book 
value of common equity plus the market value of common equity divided by the total book value of total assets as the usual 
proxy for Tobin's Q. We use two other bank performance ratios to examine the return on assets (ROA), and annual market 
return of a bank shareholder (SR). We measure ROA as the income before, interest, and taxes (EBIT), divided by the total 
assets. We calculate the shareholder yearly return for each year from the opening price and closing price of the year, and 
asset quality is measured by net non-performing assets (NNPAs). The NNPA ratio is measured by NNPAs and is divided 
by the net advances. SR, on the other hand, measures market performance but might be biased by market sentiment and 
market manipulations. 
 
 
 



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3.2 Independent Variables: Board Characteristics Measures  
Three board characteristics are taken for the study such as board size, board composition, and board functioning. The 
board characteristics variables include the number of directors serving on the board (bs); the percentage of independent 
directors on the board (pid) where the independent director is defined as such director that has no other position in 
commercial banks, the percentage of executive director (ped), the percentage of busy directors on the board (pbd). The busy 
director is defined as the director who serves on three or more boards and several meetings per year (nom). 
 
3.3 Control Variables 
We use total bank assets (in INR billions) to measure the size of the bank, (ta) and capital adequacy ratio (car) as a proxy 
for measuring the strength of banks' capital. CAR is measured as equity to total assets. Table 1 describes variables. 
 
Table 1.  Description of variables  
  

 Nature of variables Description of variable 

 Panel A: Dependent Variables: Bank performance variables  

1 Tobin’s Q Market Value of equity plus book value of debt divided by the book value 
of total assets 

2 Return on assets (ROA) EBIT over total assets 

3 Shareholders’ market returns
 (SR) 

Yearly stock market returns of respective banks 

4 Assets’ quality (NNPA) Net NPAs to net advances  

5 Panel B: Independent Variables: Board characteristics variables 

6 Board Size Number of directors in the board 

7 Independent Director  Percentage of directors who are independent 

8 Executive director Percentage of directors who are executives  

9 Busy Director Percentage of directors who serve on 3 or more other boards 

10 Meetings Number of board meetings  

 Panel C: Control variables  

11 Bank Size Total assets of the bank 

12 Capital Ratio   Capital adequacy ratio (CAR) (Equity/ total assets)  

 
4. Econometric Model  
The main regression equation1 

𝑷𝒆𝒓𝒇𝒐𝒓𝒎𝒂𝒏𝒄𝒆 𝑴𝒆𝒂𝒔𝒖𝒓𝒆𝒊,𝒕 = 𝜶 + ∑ 𝛽𝑗

𝑗

𝐵𝑜𝑎𝑟𝑑 𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒𝑠𝑖,𝑡
𝑗

+ ∑ 𝛾𝑘

𝑘

𝐶𝑜𝑛𝑡𝑟𝑜𝑙 𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒𝑠𝑖,𝑡
𝑘 + 𝜀𝑖,𝑡 

Where board variables are  

𝐵𝑆𝑖𝑧𝑒 = Board Size 

 𝐵𝑀𝑒𝑒𝑡𝑖𝑛𝑔 = Number of board meetings 

 𝐸𝑥𝑒 𝐷𝑖𝑟𝑒𝑐𝑡𝑜𝑟𝑖,𝑡 = Percentage of executive director 

 𝐼𝑛𝐷𝑖𝑟𝑒𝑐𝑡𝑜𝑟𝑖,𝑡 = percentage of independent directors 

𝐵𝑢𝐷𝑖𝑟𝑒𝑐𝑡𝑜𝑟𝑖,𝑡 = = percentage of directors who serve on more than or equal to 3 other boards.  

Control variables used in the above equation are: 

Bank size= Natural log of total asset of the bank 

Capital adequacy ratio (CAR) = Equity to total assets 

Performance variables are: 𝑇𝑜𝑏𝑖𝑛′𝑠 𝑄𝑖,𝑡, 𝑅𝑂𝐴𝑖,𝑡 , 𝑆𝑀𝑅𝑖,𝑡 , and 𝑁𝑁𝑃𝐴 𝑅𝑎𝑡𝑖𝑜,𝑡  

 
1𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 𝑀𝑒𝑎𝑠𝑢𝑟𝑒𝑖,𝑡 =  𝛽0 + 𝛽1𝐵𝑆𝑖𝑧𝑒𝑖,𝑡 + 𝛽2𝐵𝑀𝑒𝑒𝑡𝑖𝑛𝑔𝑖,𝑡 + 𝛽3𝐷𝑢𝑎𝑙𝑖𝑡𝑦𝑖,𝑡 + 𝛽4𝐼𝑛𝐷𝑖𝑟𝑒𝑐𝑡𝑜𝑟𝑖.𝑡 +

 𝛽5𝐵𝑢𝐷𝑖𝑟𝑒𝑐𝑡𝑜𝑟𝑖,𝑡 + 𝛽6𝐹𝑖𝑛𝐷𝑖𝑟𝑒𝑐𝑡𝑜𝑟𝑖,𝑡 + ∑ 𝛾𝑗𝑗 𝐶𝑜𝑛𝑡𝑟𝑜𝑙 𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒𝑖,𝑡 + 𝜀𝑖,𝑡 



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Variables i, t, where i denotes individual bank from 1 to bank 34 and t represents the period from 2010 to 2018. The β 
parameters capture the potential impacts of various board characteristics on bank performance. 

Table 2 presents the descriptive statistics of all the variables. Panel A, Panel B, and Panel C report bank performance 
variables, board characteristics variables and control variables respectively. The average of Tobin's Q is 1.04 times, ROA is 
0.70 percent, stock market return is 20 percent and the ratio of NNPA is 2.63 percent of our sample banks for the ten 
years 2009-2018. The average size of our sample Indian bank boards is 14, which is smaller compared to those in 
developed countries. The average number of meetings per year is 12 which is higher compared to the other developed 
countries.   

 
Table 2. Descriptive statistics 

 

 Variables N Mean  STD Min Max  

Panel A: Bank performance variables 

Tobin's Q  340 1.04 0.12 0.94 1.82 

ROA 340 0.70 0.88 -2.46 2.02 

SMR (%)  340 20.00 43.00 9.00 156.00 

NNPA  340 2.63 3.04 0.01 16.69 

Panel B: Board Characteristics variables 

Board Size 340 14.33 2.90 8.00 24.00 

No Meetings  340 12.33 4.11 4.00 28.00 

Independent Directors (%)  340 36.77 19.20 0.00 75.00 

Busy Directors (%)  340 14.00 17.00 0.00 64.00 

Exe Directors (%)  340 24.21 11.31 0.00 61.90 

Panel C: Control variables            

Bank Size (Assets in Rs. Billion) 340 2571 3619 56 34500 

CAR  340 13.32 2.32 8.67 22.04 

 
Table 3 presents the correlation matrix for all the variables. However, we do observe that there is a mild and weak 

correlation between performance measure Tobin's Q (dependent variable) and several meetings held (independent variable) 
at 0.40 and there is a positive correlation between performance measure ROA and NNPA. We find that there is a weak 
positive correlation between CAR and NNPAs. The results report there is no correlation between the variables used in the 
study. We tested for the VIF and all the models are free from the problems of multicollinearity as the Variance Inflation 
Factor (VIF) of each independent variable and the results report less than 3 VIF for all variables. Hence, we conclude that 
overall, there is no multicollinearity among the variables used for the study.  

 
Table: 3. Correlation Matrix 
 

  bs pind nom ped pbd lta car sr npa roa tq 

bs 1                     

pind -0.262 1                   

nom 0.280 -0.154 1                 

ped 0.251 -0.157 0.083 1               

pbd -0.062 0.201 -0.457 -0.013 1             

lta 0.392 -0.246 0.005 0.622 0.161 1           

car 0.001 0.177 -0.062 -0.037 -0.014 -0.123 1         

sr 0.015 0.053 -0.061 -0.078 0.103 -0.118 0.057 1       

npa -0.066 -0.230 0.043 0.209 0.012 0.219 -0.498 -0.034 1     

roa 0.073 0.160 -0.027 -0.147 -0.077 -0.183 0.664 0.049 -0.818 1   

tq -0.220 0.193 -0.397 -0.046 0.418 0.029 0.114 0.091 -0.002 0.006 1 

 
5. OLS Estimators 
Table 4 provides the OLS results of four regressions results on Tobin’s Q, ROA, SR and NNPAs on all five board 
variables. The panel data analysis is used since the sample data is a mixture of time series and cross-sectional data. This 



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allows the analysis to take into account the unobservable and constant heterogeneity, that is, the specific nature of each 
bank's business models, and strategy, management quality, and style, market perception, etc. We use OLS regressions at the 
bank level. We regress each bank performance variable on board variables, (board size, percentage of independent directors, 
percentage of executive directors, percentage of busy directors, and several meetings. The results show that board size and 
several meetings are negatively associated with Tobin's Q whereas the percentage of busy directors is positively associated 
with Tobin's Q. We find that board size and board independence are positively related to ROA whereas the percentage of 
executive directors negatively contributed to the ROA. The control variables size of the bank (total assets) and CAR are 
positively associated with ROA. We find that the percentage of executive directors is negatively significant with the bank 
performance of ROA. Board size and percentage of independent directors are negatively associated significantly with 
NNPAs (at 1% level), whereas the percentage of executive directors is positively associated with NNPA (at 1% level). Bank 
size is positively associated with NNPAs and CAR is negatively associated with NNAs. Both are at a significant 1% level. 
None of the variables is having any influence on SR including control variables.   
 
Table 4. OLS Regression results of Tobin's Q, ROA, SMR, and NNPAs 
 

Variables: Dependent  Tobin's Q ROA Stock Return NNPAs 

Intercept 1.091 
(0.000) 

-2.931 
(0.000) 

-0.199 
(0.328) 

13.836 
(0.000) 

Independent Variables  

Board Size -0.006 
(0.008) 

0.048 
(0.000) 

0.012 
(0.195) 

-0.230 
(0.000) 

Percentage of Independent Directors 0.000 
(0.518) 

0.005 
(0.034) 

0.000 
(0.854) 

-0.029 
(0.001) 

Number of Meetings -0.006 
(0.000) 

-0.010 
(0.299) 

-0.002 
(0.726) 

0.025 
(0.496) 

Percentage of Executive Directors 0.000 
(0.987) 

-0.008 
(0.012) 

-0.002 
(0.382) 

0.044 
(0.001) 

Percentage of Busy Directors 0.198 
(0.000) 

-0.312 
(0.194) 

0.293 
(0.074) 

-0.360 
(0.697) 

Control Variables 

Total Assets  0.000 
(0.386) 

0.000 
(0.019) 

0.000 
(0.125) 

0.000 
(0.000) 

Capital Adequacy Ratio 0.005 
(0.082) 

0.241 
(0.000) 

0.008 
(0.455) 

-0.652 
(0.000 

 
 

 
  

F Value  16.68 38.47 1.76 20.93 

R-Squared 0.260 0.483 0.040 0.336 

Adjusted R squared  
 

0.245 0.476 0.176 0.320 

Number of observations 340 340 340 340 

 
5. Regressions Results: Fixed Effect and Random Effect  
Table 5 presents random effect model and fixed effect model using Tobin's Q, NNPAs, ROA, and SR. Since our final 
model is fixed-effect model for Tobin's Q and NNPAs and random effect model for ROA and stock market return, we 
explain the results of fixed effect for two variables and random effect model for the other measures of performance. We use 
Hausman's test, which was rejected for ROA and SR and hence we used a random effect model for these two variables. The 
regressions results show that board size and several meetings have a significantly negative relationship with Tobin's whereas 
the percentage of busy directors is associated positively significant with Tobin's Q. The results report that board size and 
percentages of independent directors are having a negative association with NNPA significantly (at 1% level) and the 
number of meetings held is insignificant and associated positively with NNPAs.  As reported in OLS results, in this model 
also, no board variable is reported to have any association with the stock market return. However, board size and percentage 
of independent directors are positively significant with ROA and the percentage of executive directors is associated 
negatively with ROA significantly (Adams & Mehran, 2005; De Andres & Vallelado, 2008). The results support the 
hypothesis that a large board contributes to better bank performance.   



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But this has a negative association with Tobin's Q, which measures the overall performance of banks. Adams & Mehran 
(2012); Liang et al., (2013) we find that board independence is having a significantly positive impact on ROA which is 
consistent with previous studies (Baysinger & Butler, 1985; Cornett et al., 2009; De Andres & Vallelado, 2008; Garg, 2007; 
Hermalin & Weisbach, 1998; Liang et al., 2013). This finding supports the hypothesis that independent directors are better 
monitors of the managers. The results also report a significant negative relationship between the number of board meetings 
and bank accounting performance as measured in ROA. This negative relationship indicates that conducting a larger 
number of board meetings results in poor performance of the bank. Lipton & Lorsch (1992); Jensen (1993); Yermack, 
(1996); Barnhart & Rosenstein (1998) the effectiveness of the board meetings depends on the number of decisions taken in 
them in the larger interest of the bank but the implementation of these decisions is weak. This result is consistent with 
previous studies (De Andres & Vallelado, 2008; Liang et al., 2013). We also find the percentage of busy directors has a 
positive relationship with the performance measure of Tobin's Q and stock returns significantly. 
 

     Table 5. Regression results with Fixed and Random Effects 

Model Fixed Effect Model Random Effect Model 

Variables Tobin's Q NNPAs Stock Return ROA 

Intercept 1.144 
(0.000) 

15.306 
(0.000) 

-0.199 
(0.328) 

-2.931 
(0.000) 

Ind Variables 

bs -0.006 
(0.016) 

-0.218 
(0.000) 

0.012 
(0.195) 

0.048 
(0.000) 

pid 0.000 
(0.347) 

-0.039 
(0.000) 

0.000 
(0.854) 

0.005 
(0.034) 

nom -0.006 
(0.001) 

0.017 
(0.651) 

-0.002 
(0.726) 

-0.010 
(0.299) 

ped 0.000 
(0.926) 

0.049 
(0.000) 

-0.002 
(0.382) 

-0.008 
(0.012) 

pbd 0.155 
(0.000) 

-0.715 
(0.457) 

0.293 
(0.074) 

-0.312 
(0.194) 

Cont Variables 

lta 0.000 
(0.208) 

0.000 
(0.000) 

0.000 
(0.125) 

0.000 
(0.019) 

car 0.002 
(0.511) 

-0.748 
(0.000) 

0.008 
(0.455) 

0.241 
(0.000) 

R-Sq. 0.126 0.229 0.04 0.477 

F-stastics 8.22 19.62 13.81 236.48 

Noo f obs. 340 340 340 340 

Note: The table reports regression results with fixed and random effects. The values are regression 
co-efficient and P-values are in parentheses.  

 
6. Conclusions 
The objective of this paper is to examine empirically the impact of various set of board characteristics on bank performance 
and asset quality. We use OLS regressions with bank performance and asset quality. We have regressed bank performance 
variables on widely used board characteristics (board size, number of meetings, percentage of independent directors, 
percentage of executive director and percentage of busy directors). We use a panel data of 34 commercial banks from public 
and private sectors, accounting for 93 percent of total banking assets and banking business of Indian banks, for the period 
of ten years from 2010 to 2018, a recent period following the major changes in terms business environment such 
deteriorating profitability, falling credit growth rate, and eroding asset quality of Indian banks. The study finds that two 
variables:1) a percentage of busy directors, and 2) several meetings have a significant positive impact on bank performance. 
The percentage of independent directors and the percentage of busy directors has a significantly negative relationship with 
NNPAs. The board size and number meetings are associated negatively with Tobin's Q significantly and the percentage of 
busy directors is a significantly positive impact on Tobin's Q. The board size has a significantly negative impact on bank 
performance. 



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40 

             

There is strong evidence that board size and several meetings have significantly negative impacts on bank performance 
and asset quality (Tobin's Q and NNPAs). We also find evidence that the percentage of busy directors have a significantly 
positive impact on bank performance and asset quality. Our findings suggest that board independence and busy directors 
contribute to better performance and asset quality. The results report that board size and percentages of independent 
directors are having a negative association with NNPA significantly (at 1% level) and the number of meetings held is 
associated positively with NNPAs significantly (at 1% level). As reported in OLS results, in this model also, no board 
variable is reported to have any association with stock market return. Executive directors contribute negatively to the 
performance of the banks. Overall, we find that the board characteristics play a significant role in bank governance and 
certain characteristics of the bank board's impact on bank performance and asset quality. The paper adds to the existing 
literature on corporate governance mechanisms and banking industry performance 

 
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