Presented By:Anushuya Dahal
Arogya Joshi
Bishal Khanal
Deepti Koirala
Dinesh Adhikari
Chairman of Finance Instruction
Committee, Tribhuvan University.
Received ‘Dirgha Sewa Padak’
2061.
Living legend of financial
management and related disciplines.
Author
Prof. Dr. Radhe S. Pradhan
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The system of rules, practices and processes by which a company is directed
and controlled .
It involves balancing the interests of the many stakeholders in a company -
these include its shareholders, management, customers, suppliers, financiers,
government and the community.
The challenge of corporate governance is to set up supervisory and incentive
alignment mechanism that alter the risk and effort orientation of agents to align
them with the interest of principals.(Tosi and Gomez-Mejia, 1989)
Introduction: Corporate Governance
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It Improves access to capital and financial markets.
Better corporate governance can also provide Shareholders with greater security
on their investment.
The adoption of corporate governance principles can play a significant role in
increasing the corporate value of a company.
Adopting good corporate governance practices leading to better internal control
systems, greater accountability, and better profit margins.
Why corporate governance
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The study examines the effect of board size, number of executive directors in board, number of independent directors in the board, number of board meetings held in the last fiscal year at the time of gathering data and leverage on bank performance.
Significance of the research
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This research study is based on the secondary data from 23 banks in
Nepal.
Main sources of data
Banking and Financial Statistics published by Nepal Rastra Bank.
NRB directives.
legal provisions incorporated in Companies Act, 2063.
Bank and Financial Institutions Act, 2063.
Study Methodology
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Bank performance = f (CG variables, control variables).
CG variables = Board size (BS), Number of executive directors
(NED), Number of independent directors (NID), and Number of
board meetings (NOM)
Control Variables = Total debt to total assets i.e. Leverage (LEV)
More specially,
Bank performance = β0 + β1 BS + β2 NED + β3 NID + β4 NOM +
β5 LEV + e
Model used
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S.No. Name of the commercial banks Study period Observations
1 Rastriya Banijya Bank 2006/07-2010/11 5
2 Nepal SBI Bank 2006/07-2010/11 5
3 Bank of Kathmandu 2006/07-2010/11 5
4 Citizens Bank International 2006/07-2010/11 5
5 Laxmi Bank 2006/07-2010/11 5
6 DCBL 2006/07-2010/11 5
7 Agricultural Development Bank 2006/07-2010/11 5
8 Bank of Asia 2006/07-2010/11 5
9 Nepal Investment Bank 2006/07-2010/11 5
10 Nepal Standard and Chartered Bank 2006/07-2010/11 5
11 Himalayan Bank 2006/07-2010/11 5
12 NMB Bank 2006/07-2010/11 5
13 Lumbini Bank 2006/07-2010/11 5
14 NABIL Bank 2006/07-2010/11 5
15 NIC Bank 2006/07-2010/11 5
16 Global Bank 2006/07-2010/11 5
17 Kumari Bank 2006/07-2010/11 5
18 Everest Bank 2006/07-2010/11 5
19 Machhapuchhre Bank 2006/07-2010/11 5
20 Prime Bank 2006/07-2010/11 5
21 Sidhartha Bank 2006/07-2010/11 5
22 Sunrise Bank 2006/07-2010/11 5
23 Nepal Bangladesh Bank 2006/07-2010/11 5
Total number of observations 115
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H1: Board size is negatively related to bank performance.
H2: Board independence is positively related to bank performance.
H3: Board dependence on executive directors is negatively related to bank performance.
H4: Number of Board meetings is positively related to bank performance.
H5: If leverage of a firm increases, it would improve the firm performance.
The model assumes the following priori hypothesis for return on assets and return on equity models:
β3, β4, β5>0 and β1, β2<0
The model assumes the following priori hypothesis for non- performing loans:
β2 and β5 >0 and β1, β3 and β4 <0
Empirical Hypothesis
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Ratio Minimum Maximum Mean Standard deviation
ROE .000 .931 .158 .198
ROA .000 .192 .0141 .021
NPL .000 .102 .0325 .156
BS 5.000 9.001 7.431 1.456
LEV .651 .924 .824 .105
NED .000 8.150 6.235 1.251
NID .000 2.000 1.00 0.001
NOM 2.000 26.00 12.975 2.356
Findings
Descriptive Statistics
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ROE ROA NPL LEV
0 0 0
0.651
0.931
0.192
0.102
0.924
0.158
0.041 0.0325
0.824
0.198
0.021
0.1560.105
DESCRIPTIVE STATISTICS FOR ROA, ROE, NPL & LEV Minimum Maximum Mean Stdd. Deviation
Graphical presentation of Dependent variable and Independent control variable
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0
5
10
15
20
25
30
BS NED NID NOM
Descriptive Statistics for BS, NED, NID & NOM
Minimum Maximum Mean Stdd. Deviation
Graphical presentation of Independent CG variable
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Correlation matrix for the dependent and
independent variables
RATIOS ROE ROA NPL BS LEV NED NID NOM
ROE 1
ROA 0.281 1
NPL -0.183 -0.325 1
BS -0.056 -0.172 -0.361 1
LEV 0.101 0.095 0.412 0.213 1
NED -0.054 -0.142 0.235 0.432 0.201 1
NID 0.029 0.116 -0.258 0.423 0.092 -0.079 1
NOM 0.134 0.145 -0.015 0.067 0.087 0.047 0.068 1
Regression of CG and control variables on ROE
MODES
LS
INTERCEPT REGRESSION COEFFICENTS OF ADJ R-
BAR2
SEE F
BS LEV NED NID NOM
1 5.13
(10.13)
-0.05
(0.89)
0.18 10.12 15.12
2 11.13
(8.12)
1.69
(2.45*)
0.23 9.89 14.32
3 13.58
(7.26)
-1.17
(2.63*)
0.15 23.57 18.25
4 8.39
(4.29)
1.12
(3.17*)
0.19 27.65 14.46
5 21.13
(3.56)
0.34
(0.89)
0.13 16.65 19.19
6 12.67
(3.35)
-0.18
(1.12)
1.52
(3.58*)
-2.14
(3.18*)
0.28 32.59 25.68
7 6.79
(5.45)
-0.15
(0.89)
0.68
(3.12*)
-1.05
(2.92*)
0.37 45.26 36.49
8 16.36
(3.68)
-0.81
(0.95)
1.24
(2.82*)
0.69
(2.25*)
0.46 56.38 43.36
9 18.93
(3.86)
-0.23
(1.23)
1.19
(2.51*)
0.21
(2.37*)
1.05
(0.93)
0.54 53.28 53.232/26/2015 14
MODESLS INTERCEPT REGRESSION COEFFICENTS OF ADJ
R-
BAR2
SEE F
BS LEV NED NID NOM
1 2.02
(5.32)
-0.25
(1.43)
0.23 4.91 35.05
2 21.05
(4.35)
2.56
(3.02*)
0.15 5.89 10.23
3 4.43
(3.27)
-4.08
(2.23*)
0.31 7.45 19.32
4 1.59
(3.53)
0.38
(2.23*)
0.28 8.32 26.54
5 18.59
(1.32)
1.27
(1.59)
0.32 6.67 21.18
6 10.26
(2.93)
-0.13
(0.35)
3.37
(4.02*)
0.34 10.34 35.61
7 14.56
(3.16)
-0.51
(0.34)
1.77
(2.58*)
-2.13
(3.12*)
0.45 28.89 38.43
8 11.36
(2.15)
-0.23
(1.12)
1.61
(3.12*)
1.15
(3.26*)
0.52 29.92 56.78
9 23.16
(2.08)
-0.31
(0.83)
1.63
(3.56*)
2.27
(2.91*)
0.78
(1.27)
0.60 34.51 86.76
Regression of CG and Control variable on ROA
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MODESLS INTERCEPT REGRESSION COEFFICENTS OF ADJ R-
BAR2
SEE F
BS LEV NED NID NOM
1 12.36
(5.68)
-1.15
(1.12)
0.20 8.86 12.14
2 9.78
(3.45)
0.25
(3.18*)
0.19 10.82 10.13
3 13.15
(6.38)
2.25
(3.15*)
0.16 9.17 21.16
4 10.15
(7.68)
-0.79
(2.57*)
0.26 15.16 27.68
5 15.35
(6.57)
-1.11
(1.02)
0.09 12.14 21.19
6 19.16
(5.25)
-2.01
(0.92)
0.26
(2.67*)
1.10
(2.13*)
0.18 21.15 32.65
7 12.37
(5.36)
-0.56
(1.16)
1.26
(2.82*)
2.12
(3.61*)
0.24 32.32 31.82
8 6.79
(4.47)
-1.61
(1.12)
1.45
(3.38*)
-1.16
(3.10*)
-0.71
(0.89)
0.37 43.15 38.38
9 12.13
(5.52)
-0.72
(0.86)
2.23
(4.12*)
-2.21
(3.12*)
0.92
(1.04)
0.43 36.12 36.56
Regression of CG and Control variables on NPL
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There is a significant impact of corporate governance on Return on assets as
well as Return on equity.
The impact of board size and total assets are positively significant with ROE
whereas the executive CEO has insignificant effect on ROE.
The study shows that average ROE is 15.8 percent while the average ROE is
14.1 percent with standard deviation of 19.8 percent and 2.1% respectively.
There is negative correlation between ROE with NPL, BS and NED.
Positive correlation of ROA with LEV, NID and NOM.
Summary and conclusion
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Data are taken only from commercial bank. Other development bank,
financial company should include.
Research is based on only secondary data.
Only quantitative techniques are not sufficient to analysis. We have to
consider qualitative techniques as well.
Limitation
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It is useful to those who want to know about corporate governance of
Nepalese banking sector.
It will also help the government in setting up various forth polices and
regulation for good corporate governance.
This research will help bankers to find out the factor which can help to
increase their ROA and ROE.
Critical appreciation
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Thank You