INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN MANAGEMENT (IJARM)

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1 INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN MANAGEMENT (IJARM) International Journal of Advanced Research in Management (IJARM), ISSN ISSN (Print) ISSN (Online) Volume 4, Issue 2, May - August 2013, pp IAEME: Journal Impact Factor (2013): (Calculated by GISI) IJARM I A E M E BOARD SIZE, COMPOSITION AND THE PERFORMANCE OF PRIVATE SECTOR BANKS Dr.S.Sudalai Muthu, Associate Professor, Department of Banking Technology, Pondicherry University, R.V.Nagar, Kalapet, Puducherry , India. R.Hariharan, Research Scholar, Department of Banking Technology, Pondicherry University, R.V.Nagar, Kalapet, Puducherry , India. ABSTRACT The Banks are a dominant component of the Indian Financial System; they are the engines of growth of Indian Economy. The size and composition of the board of directors constitute of the most essential corporate governance norms. The performance of the corporate now mostly depends on the board size and composition, it applicable to banking sector also. This paper made an attempt to assess the performance of Private sector banks and the relationship with board size and composition. To measure the performance of the banks the variables used like Return on Asset (ROA), Net Profit Margin (NPM), Interest Spread (IS), Return on Net worth (RNW) etc., and these variables are compared with board size and composition with appropriate tools. The Pooled OLS Regression Estimation Model is used to assess the relationship between board composition and performance of the banks. The result indicates that performance of the banks is depend upon on the board composition and the other performance indicator like Interest spread, Net profit Margin etc., in Private banks. The Private Banks are using the efficient management in utilization of its asset and equity base for the bank performance. Keywords: Board Size, Composition, Performance, Return of Asset (ROA) and Return on Net worth (RNW). 1. CORPORATE GOVERNANCE IN BANKS IN INDIA Banks versatile role in the economic system has caught regulatory and supervisory interest around the world in an effort to inspire high quality corporate governance standards. Board structure, in the sense of board size and composition, and its impact on corporate 1

2 performance constitutes an indispensable and, at the same time, prevalent theme of the corporate governance discussion. Banks are different from other Corporate in important respects, and that makes corporate governance of banks not only different but also more critical. Banks lubricate the wheels of the real economy, are the conduits of monetary policy transmission and constitute the economy s payment and settlement system. By the very nature of their business, banks are highly leveraged. Banks are interconnected in diverse, complex and oftentimes opaque ways underscoring their contagion potential. If a bank fails, the impact can spread rapidly through to other banks with potentially serious consequences for the entire financial system and the macro economy. A series of structural reforms raised the profile and importance of corporate governance in banks. The structural reform measures included mandating a higher proportion of independent directors on the boards; inducting board members with diverse sets of skills and expertise; and setting up of board committees for key functions like risk management, compensation, investor grievances redressal and nomination of directors. Structural reforms were furthered by the implementation of the Ganguly Committee recommendations relating to the role and responsibilities of the boards of directors, training facilities for directors, and most importantly, application of fit and proper norms for directors. 2. LITERATURE REVIEW BOARD SIZE, COMPOSITION AND PERFORMANCE The size and composition of the board of directors constitute of the most essential corporate governance themes and have caught the attention of academics and regulators alike. The board composition plays an important role in corporate performance. The composition of board consists of both inside and outside directors. Mostly insiders are members of the top management teams, and employees of the company. Outside directors have no such association (SH.D.Chatterjee, 2011). The klein (2002) and Andres and Vallelado (2008) who argue that a large board size should be preferred because of possibility of specialization for more effective monitoring and advising functions. In the view of researcher such as Fama and Jensen (1983); Lipton and Lorsch (1992); and Yermack (1996) who favor small boards. Dhawan (2006) supported this finding by pointing out that the size of the board increases with turnover, but only up to a certain level, beyond which the increasing turnover does not have any influence. Hence, knowledge and skill of the board members are of paramount importance, rather than the size of the board. Dwivedi and Jain (2005), in their study on board size and firm value, also suggested a positive relationship. On the other hand, there are studies which point to a negative relationship between board size and firm performance in the Indian context. Ghosh (2006) study on the relationship between financial performance and board parameters which include board size found that larger board size tends to have a negative influence on firm performance. The most of the literature survey talks on the board composition and its firm performance or vice versa. Board size also shows no consistent correlation with firm performance, some other studies it found on negative correlation. Some research studies reveal that large board size leads to improved firm performance, whereas there have also been evidence of larger boards being inefficient in nature. In the view of Pearce and Zahra (1992) and Dalton et al., (1999) argue that as board size increase, the strategic decision making capabilities of the board increase and but Golden and Zajac (2001) argued that smaller boards are assumed to have inadequate confidence and unclear understanding in making strategic changes. If the board size increases the cost 2

3 associated with it, like coordination cost and communication costs, also increase (Raheja, 2005). Yermack (1996) empirically demonstrated that there is a negative relationship between board size and firm performance. It result that measure of operating efficiency and profitability are negatively related to the board size. There is relationship between the inside directors with the firm performance in bank, prior research article say it does not support a clear relation between board independence and firm performance. It can said with the example of early work by Vance reports a positive correlation between the inside directors and a firm performance. Conflicting with this, the results of Adams and Mehran (2005) show a significant positive relationship between board size and bank performance, as measured by Tobin s Q. Although the structure of the bank holding company was found to be related to board size, the positive effects of a larger board were still visible after taking it into account. In addition, while they find no significant relation between the proportion of outside directors and bank performance, they show that firms with boards dominated by outsiders do perform better. Argument made by Hermalin and Weisbach (1991), that there is no relationship between board composition and firm performance. They suggested that it is good to have inside directors presence in the board of directors, it help CEOs to maximize value by providing both advice and knowledge about the day-to-day operations of the company. It also suggested that top management has as control over board selection. In the view of Bhagat and Black (1999), that there is no strong correlation between board independence and firm performance. They stated that different firms need different degrees of board independence, depending upon their growth rate. The work of Staikouras, Staikouras and Agoraki (2007) examined a sample of 58 out of the 100 largest, in terms of total assets, credit institutions operating in Europe for the period between 2002 and Their analysis inferred that bank profitability measured in terms of ROA, ROE and Tobin s Q is negatively and significantly related to the size of the Board of Directors. Finally, Pathan, Skully and Wickramanayake (2007) using a dataset of the Thai commercial banks over the period , also obtained a negative relation between board size and both ROE and ROA. 3. OBJECTIVES OF THE STUDY The study mainly focuses on the board composition and bank performance in private sector banks. To identify any relationship between board size, composition and meetings in the Private sector banks. To analyze the link between the size of the board and banks performance with respect to consistency in the Private sector banks. To achieve these above objectives the following hypothesis are included H 0 1 : There is no relationship between board size and composition in banks. H 0 2 : There is no significant relationship between board size, composition and meetings in the banks. H 0 3 : There is no significant relationship between the banks performance and board composition in the banks. 3

4 4. METHODOLOGY Sample The universe of study comprise of 87 banks in which, 26 public sector banks, 20 private sector banks and 41 foreign banks. The sample size is however, limited to eight banks of private sector banks like HDFC, ICICI, Axis, Kotak Mahindra, Indusland, Karur Vysya, City union and Lakshmi vilas bank. The convenience sampling technique is used for selection of private sector banks and the selection of the sample is based on market capitalization is divided into three levels lager, middle and lower banks, availability data corporate governance report for period ten years. Source of Data and structure The secondary data collected for eight private sector banks like Corporate Governance reports, balance sheet from the Centre for Monitoring Indian Economy (CMIE) and money control website. The Pooled data set is collected for the study consists of both time series and cross selection data set. banks. Period of the Study The study period consists of ten year from 2003 to 2012 for all eight private sector Variables and Tools for analysis The variables used for the study like board size, inside and outside directors (for board composition), number of meetings, return on asset, return on net worth, interest spread, net profit margin, business per employee, profit & loss per employee, net non performing asset and loan (for bank performance). The tools used for analysis are Summary statistics, Correlation and Pooled OLS Regression of Robust (HAC) standard errors (Fixed effect model). The pooled data model for relating a dependent variable to independent variable is compactly stated thus: Y it = α + β 1 X 1it +β 2 X 2it +β 3 X 3it +β 4 X 4it +β 5 X 5it +β 6 X 6it +β 7 X 7it +β 8 X 8it +β 9 X 9it +µ it +ε it Where i = 1,2,3,4,5,6,7,8,9,10,11,12 t=1, 2, 3, 4, 5,6,7,8,9,10 Y=Dependent variable like Return on Asset (roa) and Return on net wroth (rnw) X 1= Log inside directors (id) X 2= Log outside directors (od) X 3= Log meetings (mee) X 4= Business per employee (bpe) X 5= Log Profit & Loss per employee (lplpe) X 6= Log Interest spread (lis) X 7= Net profit margin (npm) X 8= Log Net non performing asset (lnnpa X 9= Log loan (lloa) µ= Error term Package used for Analysis Statistical package for social science (SPSS) and Gretl package (Econometric). 4

5 5. ANALYSIS AND DISCUSSION The table shows the mean, standard deviation, maximum and minimum values of the following variables: board size, outside directors, inside directors, meeting per year, return on asset, return on net worth, net profit margin, business per employee, profit & loss per employee, loan, interest spread and net non performing asset. Table 1: Private sector Banks Variable N Mean Std. Dev Max Min Board Size Inside Directors Outside Directors Meetings per year Return on Asset Return on net worth Interest spread Net profit margin Business per employee Profit & loss per employee Log Nnpa Log loan Source: Computed results based on compiled data collected from CMIE Prowess Pvt. Ltd. The Table 1, the mean size of the board are which is more similar to the average board size (12) reported for non-financial firms (Yermack, 1996, Rosenstein and Wyatt, 1997; Klein, 1998; Vafeas, 1999; Andres, Azofra, and Lopez, 2005), but close to the 17 directors obtained by Adams and Mehran (2005) in the period for banks. The maximum board size of the private bank sectors consists of 19 and to minimum of 1, inside directors mean is 3.81, outside directors mean is 7.77 it indicates that the majority of directors in the board of private sector banks are outsiders. The number of meetings per year mean is 12.5 which are more than the 8.48 meetings reported by Adams and Mehran (2005), so more number of meetings are conducted in the private sector banks in the year. The mean of return on asset is 1.33; it indicates that the private banks are generating less profit from their total assets in the banks; the maximum of return on asset is 2.49 and minimum of.08, it explicit that larger banks have efficient management utilization its asset base than the smaller banks. The return of net worth mean is 15.08, maximum and minimum -.35, it says that higher the ratio percentage the more efficient management operation its equity base in the larger banks than smaller ones. Interest spread mean is 4.78; the greater spread in the banks gives more profitable to the banks. The net profit margin 5

6 mean is 12.95, the larger profit margin is better to the banks to control on costs. Business per employee mean is and profit & loss per employee mean is.66 indicates the more the percentage the more business to the banks. Net non performing asset mean is 7.17 and loan mean is 7.30, it implies that the more the percentage stood in the number will reduce the banks profitability ratio in their business. 5.1 THE RELATIONSHIP BETWEEN THE BOARD SIZE AND BOARD COMPOSITION AND IN THE PRIVATE SECTOR BANKS H 0 1 : There is no significant relationship between board size and composition in the banks. H 0 2 : There is no significant relationship between board size, composition and meetings in the banks. The table below reveals the correlation between the board size and bank composition in the private sector banks. Table 1.2: Board size, composition and meetings in the private sector banks Pearson Correlation Coefficients (two-tailed significance levels in parentheses; sample size = 80) Correlation Board size Inside directors Outside directors Meeting per year coefficient Board size 1 between board Inside directors.002** 1 composition and meeting Outside directors.000**.001** 1 Meeting per year **. Correlation is significant at the 0.01 level (2-tailed). Source: Computed results based on compiled data collected from CMIE Prowess Pvt. Ltd. From the table, it is observed that there significant relationship between the board size, inside and outside directors (board composition) in the banks, the null hypothesis (H 0 1 ) is rejected at significant level of 0.01 percent level. Hence private sector banks composition of inside and outside directors are fit properly in the board size and there is relationship between the board size and composition in the banks. It also seen that there no significant relationship between the board composition over the board meeting conducted in the board in a year, but there is relationship between the size of the board and meeting. Hence the meeting attended by the inside and outside director in the board doesn t impact on the individually, but it affects on the board size only. 5.3 BANKS PERFORMANCE AND BOARD COMPOSITION IN THE PRIVATE SECTOR BANKS WITH POOLED OLS REGRESSION ESTIMATION H 0 3 : There is no significant relationship between the banks performance and board composition in the banks. The table depicts that Pooled OLS Regression Estimation of Robust (HAC) standard errors of model fixed effects, using 72 observations included 8 cross sectional units of the time 6

7 series length 9, dependent variable of bank performance return on asset (ROA). The model of the regression is Roa it (Performance) = α + β 1 Bpe it +β 2 logplpe it +β 3 logis it +β 4 Npm it +β 5 logid it +β 6 logod it +β 7 logmeeting it +β 8 lognnpa it + β 9 logloan it +µ it +ε it (1) Table 1.3: Pooled OLS Regression Estimation Dependent (ROA) of fixed effect model of banks performance and board composition in the private sector banks Coefficient t-ratio p-value const ( )** Bpe ( )*** logpple logis ( )*** Npm ( )*** logid logod ( )** logmeeting ( )*** lognnpa ( )** logloan P-value (F) (.0000)*** R-sq Adj R-Sq Heteroskedasticity Chi-square ( )*** Wald test P-value.0000 Auto correlation Durbin -Waston Statistically 1%(***), 5%(**) and 10%(*) level From the table, it Pooled OLS Regression of fixed effect model predict that independent variable like business per employee(bpe), Net profit margin (Npm), outside directors(logod), Non performing asset(lognnpa), Meeting (logmeeting), Interest spread (logis) are significant and another three variables like Profit & loss per employee (logplpe), inside directors(logid), loan(logloan) are not significant in the model. The overall model of pooled OLS regression fit to the equation because of the anova (F) is 1% level, it imply that OLS regression of the model have good predict over the dependent variable. The R-sq.9597 (95%) means that the independent variable have more effect on the dependent variable. The Wald test (Heteroskedasticity) is used for to test the variable are scattered and not in a group together, the P value is significant and it clearly says there is no heteroskedasticity in the model. The autocorrelation is check by the Durbin- Waston (1.7313) it shows that there is no autocorrelation between the variables and the multi collinearity diagnostics of the variances inflation factor (VIF) lies in between the variables is maximum ( 2.447) for lnnpa and minimum (1.273) for npm, its less values in the variables will predict the model more. Hence the P value (F) is significant, it reject the null hypotheses (H 0 3 ),so there is relationship between the bank performance (Roa) with board composition of outside director and meetings conducted in the year, other performance indicator effects boards performance variable like interest spread(is), business per employee(bpe), nnpa (lognnpa) and net profit margin (npm). 7

8 H 0 3 : There is no significant relationship between the banks performance and board composition in the banks. The table depicts that Pooled OLS Regression Estimation of Robust (HAC) standard errors of model fixed effects, using 72 observations included 8 cross sectional units of the time series length 9, dependent variable of bank performance return on net worth (Rnw). The model of the regression is Rnw it (Performance) = α + β 1 Bpe it +β 2 Npm it +β 3 Id 3it +β 4 Od it +β 5 lognnpa it +β 6 logloan it +β7meetingit +β 8 logis it +µ it +ε it (2) Table 1.4: Pooled OLS Regression Estimation Dependent (RNW) fixed effect model of banks performance and board composition in the private sector banks Coefficient t-ratio p-value Const Bpe ( )* Npm ( )*** Id ( )*** Od lognnpa logloan ( )*** meeting ( )** logis ( )*** P-value (F) (.0000)*** R-sq Adj R-Sq Heteroskedasticity Wald test Chi-square ( )*** P-value.0000 Auto correlation Durbin -Waston Statistically 1%(***), 5%(**) and 10%(*) level From the table, it Pooled OLS Regression of fixed effect model predict that independent variable like business per employee(bpe), Net profit margin (Npm), Inside directors(id), loan (logloan), Meeting, Interest spread (logis) are significant and another two variables like Net non performing assert (Log nnpa),outside directors(od) are not significant in the model. The overall model of pooled OLS regression fit to the equation because of the anova (F) is 1% level, it imply that OLS regression of the model have good predict over the dependent variable. The R-sq.6361 (63%) means that the independent variable have more effect on the dependent variable. The Wald test (Heteroskedasticity) is used for to test the variable are scattered and not in a group together, the P value is significant and it clearly says there is no heteroskedasticity in the model. The autocorrelation is check by the Durbin- Waston (1.6763) it shows that there is no autocorrelation between the variables and the multi collinearity diagnostics of the variances inflation factor (VIF) lies in between the variables is maximum ( 2.447) for lnnpa and minimum (1.273) for npm, its less values in the variables will predict the model more. Hence the P value (F) is significant, it reject the 8

9 null hypotheses (H 0 3 ),so there is relationship between the bank performance (Rnw) with board composition of inside director and meetings conducted in the year, other performance indicator effects boards performance variable like interest spread(lis), business per employee(bpe), loan (lloan) and net profit margin (npm). 6. CONCLUSION The analysis reveals that the board size and composition have relationship in the private sector banks, but the board meeting only related to total board size in the banks. The Pooled OLS regression model of the two equation of fit the model, it explicit that independent variable have impact on the depended variable, though the both equation of the model is significant, there is relationship between board composition and bank performance in the private sector banks. It shows that private sector banks are using the efficient management in utilization of its asset and equity base for the bank performance. REFERENCES 1. Adams, R., and Ferreira, D A theory of friendly boards. Journal of Finance, 62: Adams, R., and Mehran, H. April Is corporate governance different for bank holding companies?. Federal Reserve Bank of NY Economic Policy Review, Adams, R., and Mehran, H. August 8, Corporate performance, board structure and its determinants in the banking Industry. EFA 2005 Moscow Meetings. Available at SSRN: 4. Agoraki, Maria-Eleni, Delis, Manthos D and Staikouras,Panagiotis (2009), The effect of board size and composition on bank efficiency, Online at Paper No.18548,posted 11 November 2009/12:15 5. Anderson,C.R. and M.D.Reeb (2003) Founding-family ownership and firm performance: Evidence from the S&P500, The Journal of Finance, LVIII(3), Andres P.D. and E.Vallelado (2008). Corporate Governance in Banking: The Role of the Board of Directors, Journal of Banking & Finance 32, Dalton D R, Daily C M, Johnson J L, and Ellstrand A E (1999), Number of Directors and Financial Performance: A Meta-Analysis, Academy of Management Journal,Vol.42,No Donaldson, L. and J.H. Davis (1991). Stewardship Theory or Agency Theory: CEO Governance and Shareholder Returns, Australian Journal of Management 16, Hermalin, B.E., Weisbach, M.S. (2003): Boards of directors as an endogenously determined institution a survey of the economic literature, Economic Policy Review, 9 (1): Jackling, B. and Johl, S. (2009). Board Structure and Firm Performance: Evidence from India s Top Companies, Corporate Governance: An International Review 17(4), Pearce John A and Zahra shaker A (2000), Board composition from a strategic contingency perspective, Journal of Management Studies, vol.29,pp Raheja charu(2005), Determine of board size and composition: A theory of corporate boards, Journal of finance and quantitative analysis, Vol.40,pp Sharma J.P (2011), Corporate Governance, Business Ethics and CSR, Pg.79, New Delhi, Ane Books Pvt Ltd. 9

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