Content uploaded by Shikha Mittal Shrivastav
Author content
All content in this area was uploaded by Shikha Mittal Shrivastav on Jan 03, 2018
Content may be subject to copyright.
Business Analyst, ISSN 0973-211X, 38(1), 173- 213, ©SRCC
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM
PERFORMANCE: EVIDENCE FROM NSE COMPANIES
Shikha Mittal Shrivastavand Anjala Kalsie
Abstract
The paper analyses the relationship between Corporate Governance Disclosure Index
(CGDI) and Firm Performance of 38 non-financial NSE listed companies in India for a
period of five years from 2008-2012. The objective of the paper is to examine the level
of disclosure and the impact of such disclosure on the firm performance of NSE Nifty
companies.The firm performance measures include Tobin’s Q, Market to Book Value
Ratio, Market Value Added, Return on Assets, Return on Capital Employed and Return
on Equity. Econometric analysis is performed using Year-wise OLS Regression, Pooled
OLS and Panel Data Models. The results of year-wise OLS regression analysis provided
a strong evidence of strengthening of the relationship between CGDI and firm
performance measures over the years. In brief, the research findings reveal that CGDI
has a positive impact on firm performance based on market based measures as well as
accounting based measures. The paper concludes firms that disclose more are likely to
result in higher performance. The results also imply that firms are more willing to
disclose more information leading to enhanced corporate governance mechanisms but
there is still scope for the improvement.
Keywords: Corporate Governance Disclosure Index, Firm Performance, Tobin’s Q,
Fixed Effect Model, Random Effect Model, Feasible Generalized Least Square.
1. Introduction
“Corporate Governance is about maintaining an appropriate balance of accountability
among three key players; the corporation’s owners, the directors whom the owners
elect, and the managers whom the directors select. Accountability requires not only
Assistant Professor, IILM Graduate School of Management, Greater Noida, Uttar Pradesh,
Email: shikhamit20@gmail.com
Assistant Professor, Faculty of Management Studies, University of Delhi, Delhi, Email:
kalsieanjala@gmail.com (Corresponding Author)
174 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
good transparency, but also an effective means to take action for poor performance or
bad decisions.” Corporate disclosure is a process through which firms communicate all
relevant information pertaining to the functioning of the company to their shareholders.
The major source of corporate disclosures is annual reports of the companies. A
transparent, informative and strong system of corporate governance is of vital
importance for firms to attract foreign funds.
Corporate governance disclosures practices adopted by a firm can influence the value of
the firm. A number of studies were based on the fact that higher disclosures by the firm
improve corporate performance. Disclosures play a significant role in ensuring integrity,
transparency and accountability. Companies’ annual report serves as the source of
information leading to disclosures. From Agency perspective increased disclosure on
corporate governance practices can enhance firm performance by aligning the interests
between the owners and the mangers. Such disclosures help management in reducing
managerial expropriation in the form of high perquisites and excessive remuneration and
make them more accountable for their actions. Higher disclosures can also enhance firm
performance by inducing investor’s confidence resulting from information symmetry.
On the other hand, greater disclosures by the firm can bring costs associated with greater
public scrutiny. But these costs are overweighed by the benefits associated with the
increased credibility among the investors.
The present paper aims at investigating the corporate governance disclosure practices
followed by the companies in India based on the clause 49 of the Listing Agreement.
The paper has two fold objectives. The primary objective is to assess the corporate
governance disclosure practices followed by the NSE Nifty companies as per the clause
49 of the listing agreement with regard to Board of directors, board meeting, annual
general meetings, board committees, mandatory and non-mandatory disclosures etc. The
secondary objective is to analyze the impact of corporate governance disclosure index
on firm’s financial performance measured by accounting and market based measures.
Keeping the objective in mind, a Corporate Governance Disclosure Index was
constructed consisting of 52 mandatory and non-mandatory parameters based on the
SEBI’s Clause 49 of the listing Agreement in order to assess the level of disclosure of
compliance of corporate governance practices by the Indian companies.
2. Review of Literature
Prior studies on corporate governance disclosure index found mixed results for the
relationship between the CGDI and firm performance. Gompers, Ishii and Metrick
(2001) constructed a Governance Index consisting of 24 distinct corporate governance
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 175 | P a g e
provisions and found that corporate governance is significantly associated with stock
returns and Tobin’s Q for 1500 firms from 1990-1999. Following the research by
Gompers et. al (2001), Bebchuk, Cohen and Ferrell (2004) investigated the relative
importance of the provisions included in the GIM governance index by further
developing an Entrenchment index (E Index) based on six provisions. The results of
OLS estimates showed a negative and significant relation between the entrenchment
index and firm value (Tobin’s Q) during the 1990-2003 periods for 8015 firm-year
observations. In a similar study based on the Gompers et al. (2003) G-Index comprising
of 24 provisions, Bhagat and Bolton (2008) created D-Index based on only four
provisions of board members. The results of Two Stage Least Square (2SLS) found a
negative relationship between D-Index and ROA for the pre-2002 time period, but a
positive relationship in the post-2002 time period. Therefore they concluded that firms
with stronger manager entrenchment actually perform better in 2003-2007 as the sign
changes from negative to positive.
Klapper and Love (2004) developed Governance Index (GOV) based on 374 firms in 14
emerging countries and found that firms with better corporate governance have higher
market valuation and operating performance as the relationship between firm
performance and governance indicators is significant and positive. These findings were
further supported by Durnev and Kim (2005) who analyzed firm-level governance data
of 859 large firms from 27 countries. They also concluded that firm’s choice of
governance and disclosure practices is positively related to investment opportunities,
external financing, and growth opportunities. For 515 Korean firms, Black, Jang and
Kim (2006) constructed a corporate governance index (KCGI) consisting of 38 usable
elements classified into four sub-indices: Shareholder Rights, Board Structure, Board
Procedure and Disclosure. The result of OLS and Instrumental Variable for the year
2000 reported strong evidence that an overall corporate governance index is an
important and likely casual factor affecting the market value irrespective of the choice
of market variable used.
In Indian Context, Gupta, Nair and Gogula (2003) examined the corporate governance
reporting practices of 30 BSE listed companies and found that the significant
determinants of corporate governance disclosures in BSE listed companies are number
of independent directors, size of the company and overseas listing status when analyzed
using OLS regression. In a similar study,Sen (2011) examined the annual reports of 50
listed companies in order to determine the extent of corporate governance disclosure by
developing an index consisting of 67 parameters in accordance with the clause 49 of
listing agreement. The paper concluded that there is significant difference between the
176 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
quantum and quality of corporate governance disclosures made by the listed companies.
The size of the company is a significant determinant of disclosures. Larger companies
showed better extent of disclosure compared to smaller ones. For BSE companies,
Raithatha and Bapat (2012) found that financial parameters like Net Profit Margin,
Market Capitalization, FII Stake and Leverage Ratio resulted in co-efficient values
which were found to be not significantly related to Corporate Governance score.
Sarkar, Sarkar and Sen (2012) constructed a Corporate Governance Index for 500 large
listed firms for the period 2003 to 2008 and found evidence of strong relationship
between Corporate Governance Index and market value of companies. Based on the
internal control mechanisms,Varshney, Kaul and Vasal (2012) constructed a corporate
governance index using a sample of 105 Indian firms for two years: 2002-03 and 2008-
09. Using Economic Value added as a measure of firm performance, they found a
positive association between corporate governance index and firm performance.
However they could not find association of positive relationship with other firm
performance measures used.Ben P. J. (2014) studied the impact of compliance with non-
mandatory disclosures in corporate governance on the performance of Indian firms in
the context of guidelines given by Securities and Exchange Board of India (SEBI) by
constructing a self-index represented by DSCORE. Firm performance is measured using
Price-to-book value and Return on Capital Employed (ROCE). The results of Ordinary
Least Square for a sample of 100 BSE listed companies found evidence of a significant
and weak relationship between the corporate governance index and firm performance,
using market based measure. However the relationship was found insignificant in the
case of ROCE.
Allegrini& Greco (2013) developed a Dscore containing 60 discretionary items based on
the Financial information, Projected information, Capital market data, Strategic
information, Risk information and Sustainability information of the companies. They
regressed the voluntary disclosure index data of 177 listed non-financial companies of
Italian Stock Exchange for the year 2007 on seven corporate governance variables viz.
Board Size, CEO duality, Board Composition, Lead independent director, Board
Committees, Board Meetings and Audit Committee Meetings. The results suggested that
there exists a complementary relationship between governance and disclosures.
Javaid&Saboor (2015) developed a Corporate Governance Composite Index based on
21 proxies to analyse the impact of Corporate governance index on firm performance
measured by ROA, ROE and Tobin’s Q of 58 Pakistani listed manufacturing firms from
year 2009-2013. The index was divided into three sub-indices namely Board Structure,
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 177 | P a g e
Ownership Structure and Disclosures. The result found that corporate governance index
(CGI) and firm performance has positive and significant association but the relationship
for each specific index is dependent upon the measure of firm performance. The sub
index 1 Board Structure is found to have positive and significant relationship with all
three performance measures. The sub index 2 is found to have significant positive
relationship with only accounting based measures of firm performance, on the other
hand, sub index 3 is only having significant relationship with ROA. The result also
found that companies having strong corporate governance mechanism has greater
chances to acquire external finance.
Cunha & Mendes (2017) analysed financial determinants of the level of corporate
governance disclosure (CGD) across a large sample of Portuguese firms, listed in the
Euronext Lisbon index, in the period between 2005 and 2011. They constructed an
index, consisting of total of 82 corporate governance attributes grouped into six
categories of information: management structure; specialized committees (remuneration
and appointment); audit and risk management; ownership structure; compliance and
corporate responsibility; and financial transparency. The results of the ordinal logistic
model showed that firm size and growth opportunities as measured by Tobin’s Q had a
significant and positive influence on Corporate Governance Disclosures. However, the
results of their study found that no relationship exists between Corporate Governance
Disclosure and financial performance measured by ROE.
3. Objectives and Methodology
3.1 Objectives
The objectives of the present paper are:
1. To study the corporate governance disclosure practices followed by the NSE
Nifty companies as per the clause 49 of the listing agreement.
2. To analyze the impact of corporate governance disclosure index on firm’s
financial performance by determining the corporate governance score of
companies with respect to SEBI guidelines of Clause 49.
Based on the extensive literature the null and alternate hypotheses are framed as
follows:
Null Hypothesis: H0: Corporate Governance Disclosure Index has no impact on
Firm Performance.
Alternative Hypothesis: H1: Corporate Governance Disclosure Index has a positive
178 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
impact on Firm Performance.
3.2 Methodology
3.2.1 Sample and Data
The Sample corresponds to the 50 companies from the NSE CNX S & P Index. After
the exclusion of banking and financial companies being governed by Banking
Regulations Act, the number of companies reduced to 40. Due to non-availability of
data with respect to corporate governance reports of the companies or the financial data,
2 companies are further excluded from the sample. Thus, the final sample consists of 38
companies from different industries. The time period of the study covered five financial
years i.e. 2007-08, 2008-09, 2009-10, 2010-11 and 2011-12.The year ending 31st March
was considered for reporting the corporate governance practices. Table-1 shows the
classification of sampled firms based on industry.
Table-1-Industry Classification of Sampled Companies
S No
Industry Group
Number of Companies
Percentage
1
AUTOMOBILE
5
13.16
2
CEMENT & CEMENT PRODUCTS
4
10.53
3
CONSTRUCTION
2
5.26
4
CONSUMER GOODS
3
7.89
5
ENERGY
7
18.42
6
INDUSTRIAL MANUFACTURING
1
2.63
7
IT
5
13.16
8
METALS
6
15.79
9
PHARMA
4
10.53
10
TELECOM
1
2.63
TOTAL
38
Source: Prowess Database
The data required to compute the corporate governance disclosure index has been
extracted from the Corporate Governance reports included in the Annual Reports of the
sampled NSE companies. The data with respect to the financial performance indicators
was collected from the Prowess Database and also from the NSE website.
3.2.2 Variables
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 179 | P a g e
Independent Variable: Corporate Governance Disclosure Index is taken as the
independent variable for the study. The Corporate Governance Disclosure Index (CGDI)
has been developed based on the mandatory and non-mandatory parameters from
SEBI’s Clause 49 of the listing agreement. The CGDI consisted of 52 parameters
categorised into eleven broad dimensions namely- Statement of Philosophy, Board of
Directors, Board Meetings, Audit committee, Shareholder’s/Investors Grievance
Committee, Remuneration Committee, Nomination Committee, General Body
Meetings, General Shareholder Information, Mandatory Disclosures and Non-
mandatory Disclosures. These 52 parameters were drawn in a framework to calculate
the corporate governance disclosure score and hence the Corporate Governance
Disclosure Index.
Computation of Corporate Governance Disclosure Index (CGDI): A dichotomous
procedure was followed in order to score each of the disclosed parameters. Disclosure of
a particular item is given a score of 1 or 0 otherwise. All the parameters were given
equal weight as they are considered equally important for the effective corporate
governance. The Overall Corporate Governance Disclosure score of each company was
calculated by summing up the individual scores of each dimension. This total indicates
the extent of information disclosed in the annual report. 52 could be the maximum
possible score that a company could score if all the items are disclosed. The Corporate
Governance Disclosure Index was then calculated as
The Value of CGDI ranged between 0 to 100 where 0 represents the worst disclosure
and 100 represent the best disclosure by a particular company. The CGDI only indicates
the presence of information in the annual or corporate governance report of a company
but not the quality and extent of disclosure of a particular parameter. The content
analysis of the annual reports of the company and the construction of the index
inevitably involves the subjective judgment of the researchers.
The CGDI of the sampled companies for 5 years is presented in Table-2:
Table 2:Corporate Governance Disclosure Index of Sampled Companies
S.
No.
Company Name
2007-08
2008-
09
2009-
10
2010-
11
2011-
12
1
A C C Ltd.
86.54
86.54
86.54
86.54
86.54
2
Ambuja Cements Ltd.
82.69
88.46
90.38
94.23
96.15
3
Asian Paints Ltd.
86.54
88.46
80.77
92.31
92.31
180 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
4
Bajaj Auto Ltd.
73.08
75.00
94.23
92.31
92.31
5
Bharat Heavy Electricals Ltd.
88.46
73.08
90.38
88.46
88.46
6
Bharat Petroleum Corpn. Ltd.
75.00
75.00
84.62
86.54
88.46
7
Bharti Airtel Ltd.
90.38
80.77
82.69
82.69
82.69
8
Cipla Ltd.
76.92
75.00
76.92
78.85
76.92
9
Coal India Ltd.
40.38
40.38
51.92
88.46
90.38
10
D L F Ltd.
88.46
90.38
90.38
90.38
90.38
11
Dr.Reddy'S Laboratories Ltd.
94.23
90.38
94.23
90.38
90.38
12
G A I L (India) Ltd.
80.77
84.62
84.62
80.77
84.62
13
Grasim Industries Ltd.
86.54
75.00
76.92
75.00
75.00
14
H C L Technologies Ltd.
86.54
98.08
98.08
98.08
98.08
15
Hero Motocorp Ltd.
82.69
86.54
86.54
84.62
84.62
16
Hindalco Industries Ltd.
61.54
78.85
78.85
82.69
82.69
17
I T C Ltd.
94.23
90.38
98.08
96.15
96.15
18
Infosys Ltd.
96.15
96.15
96.15
96.15
96.15
19
Jindal Steel & Power Ltd.
86.54
86.54
88.46
88.46
86.54
20
Larsen & Toubro Ltd.
84.62
88.46
78.85
92.31
88.46
21
Lupin Ltd.
80.77
84.62
82.69
86.54
82.69
22
Mahindra & Mahindra Ltd.
86.54
88.46
88.46
88.46
94.23
23
Maruti Suzuki India Ltd.
76.92
76.92
78.85
76.92
76.92
24
N M D C Ltd.
63.46
80.77
92.31
90.38
92.31
25
N T P C Ltd.
82.69
86.54
94.23
92.31
80.77
26
Oil & Natural Gas Corpn. Ltd.
82.69
88.46
88.46
92.31
92.31
27
Power Grid Corpn. Of India
Ltd.
82.69
94.23
84.62
86.54
94.23
28
Reliance Industries Ltd.
92.31
88.46
92.31
94.23
96.15
29
Sesa Sterlite Ltd.
86.54
84.62
86.54
88.46
88.46
30
Sun Pharmaceutical Inds. Ltd.
86.54
86.54
86.54
86.54
80.77
31
Tata Consultancy Services Ltd.
90.38
90.38
88.46
88.46
86.54
32
Tata Motors Ltd.
96.15
94.23
94.23
94.23
90.38
33
Tata Power Co. Ltd.
90.38
90.38
86.54
94.23
96.15
34
Tata Steel Ltd.
90.38
88.46
88.46
88.46
86.54
35
Tech Mahindra Ltd.
84.62
86.54
90.38
88.46
88.46
36
Ultratech Cement Ltd.
61.54
69.23
78.85
76.92
80.77
37
United Spirits Ltd.
90.38
90.38
94.23
94.23
96.15
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 181 | P a g e
38
Wipro Ltd.
96.15
98.08
96.15
96.15
98.08
Source: Authors’ compilation
Dependent Variables: The performance of the firm is considered as dependent
variable. It is measured using the Market based performance measures-Tobin’s Q,
Market to book value ratio (MBVR) and Market Value Added (MVA) as well as the
Accounting based measures-Return on Assets (ROA), Return on Capital Employed
(ROCE) and Return on Equity (ROE). The formula used for Tobin’s Q in the present
study is a modified version of Tobin’s Q. The modifications are incorporated to make it
compatible with the manner of reporting in the Indian context. Accouting based
measures are the indictor of the firm’s profitability.
Control Variables: In order to analyze the relationship between CGDI and firm
performance, the paper employed several other variables that may impact the
relationship between CGDI and firm performance. The Control Variables include Risk,
Firm Size, Firm Age, Firm Growth, Leverage, Advertising Intensity, Research Intensity,
Industry Dummies and Year Dummies. Since the sample companies belong to 10
different industries, 9 Industry Dummies were used to avoid multicollinearity trap.
Similarly, 4 year dummies were used for 5 years.
Table 3: Description of Variables
INDEPENDENT VARIABLE
Corporate
Governance
Disclosure Index
CGDI
Percentage of Total score of a particular
company to the maximum possible score
attainable by the company (i.e. 52)
DEPENDENT VARIABLES
Market Based Measures
Tobin's Q
TQ
Market value of equity(Market Capitalization) +
Book value of preference shares and borrowings
divided by total assets
Market Value
Added
MVA
Difference between Market Capitalization and
Shareholder's equity (BV per share X Number of
Shares Outstanding)
Market-to-Book
Value Ratio
MBVR
Ratio of Market value of equity to Book value of
equity
Accounting Based Measures
Return on Assets
ROA
Ratio of profit before depreciation, interest, tax
and amortization (PBDITA)to Total Assets
182 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
Return on Capital
Employed
ROCE
Ratio of profit before depreciation, interest, tax
and amortization (PBDITA) to Capital
Employed
Return on Equity
ROE
Ratio of profit before depreciation, interest, tax
and amortization (PBDITA) to Shareholders'
Equity
CONTROL VARIABLES
Firm Size
FS
Natural logarithm of total sales
Firm Age
FA
Natural Logarithm of difference between the
financial year and the incorporation year
Leverage
Lev
Ratio of total debt to shareholders funds
Firm Growth
FG
Ratio of difference between current year sales
and previous year sales to previous year sales
Research Intensity
RI
Ratio of Research and development expenditure
to total sales
Advertising
Intensity
AI
Ratio of Advertising expenditure to total sales
Risk
Risk
Value of Beta of the firm
Industry Dummies
Ind_dummies
Dummy variable carrying value 1 for a
particular industry and 0 otherwise
Year Dummies
Year_dummies
Dummy variable carrying value 1 for the
respective year and 0 otherwise
Source: Authors’ compilation
3.2.3 Econometric Analysis
The relationship between corporate governance disclosure index and firm performance
has been analyzed using various statistical and econometric tools. Descriptive statistics,
Correlation Analysis and Regression Analysis of cross-sectional, pooled and panel data
is performed. Multiple Regression Analysis using Ordinary Least Square method was
performed on the cross-sectional data and pooled data.
Cross-sectional (Year- wise) Data Analysis
In cross-sectional, data is a type data collected by observing one or more variable at the
same point of time, or without regard to differences in time.
The typical OLS multiple regression equation is as follows for cross-sectional data:
(1)
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 183 | P a g e
Where y is the dependent variable
x1, x2 ………… xk are the independent and control variables.
β0 is the constant term (intercept parameter of the regression)
β1 β2…………………..βk are the slope parameters
µ represents the unobserved factors that change over time and affect y.
Pooled Regression Analysis
In pooled data, the data has elements of both the cross-section and time-series,
The typical OLS multiple regression equation is as follows for pooled data:
(2)
Where i denote the number of firms and t denotes the time period
Panel Data Regression
The Panel data analysis uses two techniques: Fixed effect model and Random effect
model.Fixed effect model is estimated using least square dummy variable (LSDV)
regression (Ordinary least square with a set of dummies) and fixed effect within
estimates. On the other hand,Random effects assume that the entity’s error term is not
correlated with the predictors which allows for time-invariant variables to play a role as
explanatory variables. In random effects one can include time invariant variables (i.e.
gender etc.). This is the advantage of random effect over fixed effect as in the fixed
effects model these variables are absorbed by the intercept.
Feasible Generalized Least Square (FGLS)
The present paper has also employed FGLS regression to analyze the impact of board
size on the performance variables. Feasible GLS is applied when there is a certain
degree of correlation between the observations and when the variances of the
observations are unequal (heteroskedasticity). FGLS allows estimations in the presence
of heteroskedasticity across panels and first order autocorrelation within panels.
STATA Version 12 has been used for the analysis of the data
4. Results and Analysis
4.1 Descriptive Statistics
184 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
The descriptive statistics of the corporate governance disclosure index is presented in
Table-4. Year-wise descriptive statistics of the sample companies for 5 years from 2007-
08 to 2011-12 along with the descriptive statistics for 190 firm year observations is
shown. In the year 2007-08, the minimum value for CGDI is 40.38 and the maximum
value is 96.15 with the mean value of 83.24 indicating that companies in the year 2007-
2008 varied in their disclosures to a great extent. In the year 2008-09, minimum value
was same as that in the year 2007-08 but maximum value rose to a level of 98.07 which
remained the same for all subsequent years. The minimum level raised in the year 2009-
10 to a value of 51.92 and 75 in the years 2011 and 2012 respectively. The mean value
of CGDI varied from 83.24 to 88.66 in the five years period. Variation in CGDI is
highest in the year 2007-08, the variation decreased in subsequent years except for the
year 2011-12 in which the variation increased from the previous year.
The overall CGDI for 190 firm year observations for 38 sampled firms for a period of 5
years depicted a minimum value of 40.38 and a maximum value of 98.07 with the mean
value of 86.41. The standard deviation and median CGDI for all sampled firms for 5
years is 8.79 and 88.46 respectively.
Table 4: Descriptive Statistics
Variable
Obs
Mean
Median
Std. Dev.
Min
Max
CGDI 2007-08
38
83.24899
86.53846
11.22146
40.38462
96.15385
CGDI 2008-09
38
84.61538
86.53846
10.16614
40.38462
98.07692
CGDI 2009-10
38
86.89271
88.46154
8.350903
51.92308
98.07692
CGDI 2010-11
38
88.66397
88.46154
5.739519
75
98.07692
CGDI 2011-12
38
88.66397
88.46154
6.256126
75
98.07692
CGDI Total (5 years)
190
86.417
88.46154
8.797359
40.38462
98.07692
Source: Authors’ compilation
4.2 Correlation Analysis
The pair-wise correlation between the CGDI and firm performance measures is
presented in Table-5. For all the years CGDI was found to be positively correlated with
the market based performance measures (Tobin’s Q, MBVR and MVA). However, the
relationship between accounting measures ROA is negative with CGDI in the year
2007-08 and for accounting measure ROE, the relationship is negative in the year 2007-
08 and 2008-09. In the year 2009-10, the relationship between CGDI and market based
measures (Tobin’s Q, MBVR and MVA) is statistically significant at 5% level of
significance. CGDI is in positive and significant relationship with MVA for the year
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 185 | P a g e
2010-11. CGDI for 190 firm year observation for the total sample of 38 companies for a
period of 5 years is found to be positively and significantly correlated with the market
based measures at 5% level of significance but only positively correlated with the
accounting based measures (ROA, ROCE and ROE).When it comes to market based
measures the relation with CGDI is positive and significant because for listed
companies the market based measures are important since it gives the level of
transparency by the company, internal functioning of the companies and
compilation of various regulations and provisions of both SEBI guidelines and
companies act. Table-5 presents the correlation between CGDI and firm performance.
Table 5: Correlation Matrix
Tobin's Q
MVA
MBVR
ROCE
ROA
ROE
CGDI 2007-08
0.1045
0.2239
0.2011
0.0433
-0.01
-0.0116
CGDI 2008-09
0.2569
0.1344
0.1417
0.0075
0.062
-0.0292
CGDI 2009-10
0.3308*
0.3449*
0.2779*
0.0164
0.0048
0.0766
CGDI 2010-11
0.2111
0.3275*
0.2181
0.162
0.1836
0.1312
CGDI 2011-12
0.0601
0.2137
0.1034
0.1909
0.1739
0.2058
CGDI Total (5 years)
0.1709*
0.2574*
0.1806*
0.0326
0.0262
0.0077
Source: Authors’ compilation
4.3 Cross Sectional (Year Wise) OLS Regression
In order to analyze the relationship between the CGDI and firm performance, the cross
sectional OLS regression is performed with different accounting and market based
performance measures as dependent variables and CGDI as independent variable along
with the control variables such as Risk, Firm Size, Firm Age, Firm Growth, Leverage,
Advertising Intensity, Research Intensity, and Industry Dummies. The Regression
Equation for year-wise OLS Regression is as follows:
(3)
Here, Firm Performance denotes Tobin’s Q, MBVR, MVA, ROA, ROCE and ROE in
different models respectively.
The maximum value of VIF for all the five years is 1.80, 1.88, 1.66, 1.59 and 1.39
respectively. Thus the data is free from multicollinearity. To control for
heteroskedasticity robust standard errors are used.
186 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
The results of the year-wise OLS regression for the year 2007-08 are depicted in Table-
6. CGDI is found to be positively associated with the firm performance measures except
for MBVR. However the relationship is not statistically significant at 10 % level of
significance. The R-squared values ranged 0.449 to 0.683 for the models with different
performance measures.
Table 6: Regression Results- CGDI and Firm performance -2007-08
(1)
(2)
(3)
(4)
(5)
(6)
VARIABLES
Tobin’s
Q
MBVR
MVA
ROA
ROCE
ROE
CGDI
0.0134
-0.0173
15,237
0.00247
0.00256
0.00246
(0.0500)
(0.0711)
(10,315)
(0.00177)
(0.00312)
(0.00344)
Risk
-0.820
0.210
-458,062
-0.0500
-0.0501
0.0201
(1.645)
(2.342)
(339,694)
(0.0582)
(0.103)
(0.113)
FG
-1.701**
-2.304**
123,332
-0.0415
-0.0762
-0.0555
(0.774)
(1.102)
(159,810)
(0.0274)
(0.0483)
(0.0533)
FA
0.630
1.366
-199,396
-0.0963**
-0.135*
-0.234**
(1.229)
(1.750)
(253,807)
(0.0435)
(0.0766)
(0.0846)
FS
-0.166
-1.255
773,202***
0.0115
-0.0211
-0.0116
(1.170)
(1.666)
(241,547)
(0.0414)
(0.0729)
(0.0806)
Lev
-1.795*
-1.695
-484,729**
-0.141***
-0.248***
-0.0409
(1.008)
(1.435)
(208,097)
(0.0357)
(0.0628)
(0.0694)
AI
52.42
56.01
7.806e+06
-1.099
-4.624
-6.077
(68.61)
(97.69)
(1.417e+07)
(2.429)
(4.278)
(4.724)
RI
-24.74
-79.97*
-7.091e+06
-0.850
-2.045
-2.604
(29.14)
(41.49)
(6.017e+06)
(1.032)
(1.817)
(2.006)
Industry
Dummies
YES
YES
YES
YES
YES
YES
Constant
6.594
15.04
-3.547e+06**
0.204
0.585
0.698
(6.741)
(9.598)
(1.392e+06)
(0.239)
(0.420)
(0.464)
Observations
38
38
38
38
38
38
R-squared
0.449
0.573
0.642
0.683
0.655
0.569
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 187 | P a g e
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
In the OLS regression for the year 2008-09, CGDI is statistically positively significant
with the firm performance measures- Tobin’s Q and MBVR at 5 % and 10% level of
significance. With all other performance variables the relationship is positive but not
significant. The R-squared valued ranged between 0.405 to 0.682 as shown in Table-7
Table 7: Regression Results- CGDI and Firm performance -2008-09
(1)
(2)
(3)
(4)
(5)
(6)
VARIABLES
Tobin’s Q
MBVR
MVA
ROA
ROCE
ROE
CGDI
0.0494**
0.0621*
5,937
0.00246
0.00228
0.000313
(0.0199)
(0.0329)
(5,908)
(0.00191)
(0.00343)
(0.00388)
Risk
-
1.860***
-
2.880***
-375,683**
-0.0709
-0.0807
-0.0855
(0.591)
(0.976)
(175,444)
(0.0567)
(0.102)
(0.115)
FG
1.127
2.555
236,534
0.0579
0.114
0.239
(1.134)
(1.872)
(336,538)
(0.109)
(0.195)
(0.221)
FA
0.160
0.0957
-66,729
-0.0622
-0.0883
-0.159
(0.498)
(0.823)
(147,870)
(0.0478)
(0.0859)
(0.0972)
FS
0.489
0.347
351,372**
0.00235
-0.0210
-0.00979
(0.459)
(0.759)
(136,362)
(0.0441)
(0.0792)
(0.0896)
Lev
-
0.939***
-1.178**
-282,920***
-0.111***
-0.193***
-0.0229
(0.329)
(0.543)
(97,568)
(0.0315)
(0.0567)
(0.0641)
AI
22.14
20.64
576,328
-1.389
-5.038
-5.597
(32.11)
(53.03)
(9.532e+06)
(3.082)
(5.536)
(6.263)
RI
6.199
7.409
-1.444e+06
-0.836
-1.654
-2.092
(11.19)
(18.48)
(3.322e+06)
(1.074)
(1.930)
(2.183)
Industry
Dummies
YES
YES
YES
YES
YES
YES
Constant
-3.180
-1.270
-1.533e+06*
0.179
0.501
0.768
(2.797)
(4.619)
(830,254)
(0.268)
(0.482)
(0.546)
188 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
Observations
38
38
38
38
38
38
R-squared
0.575
0.631
0.682
0.630
0.581
0.405
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
The results of the OLS regression for the year 2009-10 as presented in Table-8 revealed
that CGDI is positively and significantly related with Tobin’s Q and MBVR at 5% level
of significance. The relationship is positive with all other performance measures. The
results are similar to the year 2008-09. The R-squared value is highest for the model
with dependent variable ROA i.e. 0.69 and lowest for the model with dependent variable
MBVR i.e. 0.47
Table 8: Regression Results- CGDI and Firm performance -2009-10
(1)
(2)
(3)
(4)
(5)
(6)
VARIABLES
Tobin’s
Q
MBVR
MVA
ROA
ROCE
ROE
CGDI
0.110**
0.198**
14,023
0.00195
0.00429
0.00542
(0.0435)
(0.0938)
(13,298)
(0.00186)
(0.00461)
(0.00491)
Risk
-1.409
-3.018
-78,803
-0.0966**
-0.206*
-0.242**
(1.006)
(2.169)
(307,613)
(0.0429)
(0.107)
(0.114)
FG
0.600
3.347
485,294
0.0650
0.219
0.235
(1.574)
(3.394)
(481,310)
(0.0671)
(0.167)
(0.178)
FA
0.333
0.533
-222,534
0.0168
0.0588
0.0224
(0.926)
(1.997)
(283,223)
(0.0395)
(0.0983)
(0.105)
FS
-0.357
-0.943
471,010**
0.00867
-0.000425
0.0121
(0.672)
(1.449)
(205,540)
(0.0287)
(0.0713)
(0.0759)
Lev
-0.826
-1.065
-437,866**
-
0.0706***
-0.166**
-0.0124
(0.574)
(1.238)
(175,575)
(0.0245)
(0.0609)
(0.0648)
AI
42.01
78.95
-7.589e+06
0.910
2.553
1.696
(47.81)
(103.1)
(1.462e+07)
(2.040)
(5.074)
(5.398)
RI
-4.788
-31.69
-6.581e+06
-0.636
-2.055
-2.467
(18.14)
(39.12)
(5.548e+06)
(0.774)
(1.925)
(2.048)
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 189 | P a g e
Industry
Dummies
YES
YES
YES
YES
YES
YES
Constant
-3.036
-3.806
-2.299e+06*
0.0400
0.0340
0.00322
(4.167)
(8.987)
(1.274e+06)
(0.178)
(0.442)
(0.470)
Observations
38
38
38
38
38
38
R-squared
0.567
0.470
0.632
0.697
0.631
0.556
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
For the year 2010-11, the results of the OLS regression are shown in Table-9. The
relationship between market based performance measures (Tobin’s Q, MBVR and
MVA) is positive and significant. Also CGDI is positively and significantly related with
the accounting based measure ROCE at 10% level of significance. With ROA and ROE,
the relationship is found positive. The R-squared value reached to a level of 0.74 for the
model with Tobin’s Q as dependent variable.
Table 9: Regression Results- CGDI and Firm performance -2010-11
(1)
(2)
(3)
(4)
(5)
(6)
VARIABLES
Tobin’s
Q
MBVR
MVA
ROA
ROCE
ROE
CGDI
0.0810*
0.167*
42,810**
0.00403
0.00921*
0.00954
(0.0518)
(0.0915)
(19,176)
(0.00238)
(0.00515)
(0.00626)
Risk
-0.480
0.382
-319,638
-
0.0840***
-0.150**
0.0235
(0.625)
(1.104)
(231,351)
(0.0288)
(0.0622)
(0.0756)
FG
-0.772
-1.055
475,669*
-0.0288
-0.0398
-0.0168
(0.634)
(1.120)
(234,647)
(0.0292)
(0.0631)
(0.0766)
FA
-0.232
-0.307
482,278
-0.0102
0.0178
0.00628
(1.186)
(2.095)
(439,064)
(0.0546)
(0.118)
(0.143)
FS
-
4.255***
-
7.154***
-886,474**
-0.136**
-0.237**
-0.294**
(1.089)
(1.925)
(403,291)
(0.0501)
(0.108)
(0.132)
Lev
-1.079
-1.452
-133,069
-0.144***
-0.218**
-0.226**
(0.850)
(1.502)
(314,789)
(0.0391)
(0.0846)
(0.103)
190 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
AI
-50.10
-76.02
6.093e+06
-6.021***
-10.03**
-9.837**
(36.36)
(64.26)
(1.347e+07)
(1.674)
(3.620)
(4.398)
RI
-24.40
-50.79*
-8.921e+06
-1.845**
-3.530**
-3.917*
(16.15)
(28.54)
(5.981e+06)
(0.743)
(1.608)
(1.953)
Industry
Dummies
YES
YES
YES
YES
YES
YES
Constant
6.389
6.015
-
4.348e+06**
0.403
0.367
0.314
(5.485)
(9.693)
(2.031e+06)
(0.252)
(0.546)
(0.663)
Observations
38
38
38
38
38
38
R-squared
0.740
0.669
0.593
0.730
0.663
0.532
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
Finally for the year 2011-2012, the results of the OLS, showed that CGDI is positively
and significantly associated with only two performance measures i.e. MVA and ROCE
at 10% level of significance as shown in Table-10. For rest of the performance
measures, the relationship is positive but not significant. The R-squared value for the
models ranged between a maximum value of 0.786 to a minimum value of 0.490.
Table 10: Regression Results- CGDI and Firm performance -2011-12
(1)
(2)
(3)
(4)
(5)
(6)
VARIABLES
Tobin’s Q
MBVR
MVA
ROA
ROCE
ROE
CGDI
0.0505
0.0977
25,462*
0.00393
0.00802
*
0.00779
(0.0396)
(0.0705)
(14,052)
(0.00252)
(0.00452
)
(0.00537
)
Risk
-
3.823***
-
6.237***
-
1.179e+06***
-
0.146***
-0.221**
-0.270**
(0.753)
(1.339)
(266,983)
(0.0479)
(0.0860)
(0.102)
FG
0.444
3.244
342,159
0.123
0.417
0.474
(2.703)
(4.804)
(958,154)
(0.172)
(0.308)
(0.366)
FA
-0.728
-0.804
-258,741
-0.0927*
-0.147
-0.131
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 191 | P a g e
(0.766)
(1.362)
(271,526)
(0.0487)
(0.0874)
(0.104)
FS
-0.594
-0.510
245,080
0.0213
0.0544
0.0911
(0.589)
(1.048)
(208,906)
(0.0374)
(0.0673)
(0.0798)
Lev
-0.269
-0.114
-110,602
-
0.0764**
-0.159**
-0.0132
(0.525)
(0.933)
(186,101)
(0.0334)
(0.0599)
(0.0711)
AI
-80.05
-95.43
-3.260e+07
-3.450
-6.064
-3.343
(53.80)
(95.64)
(1.907e+07)
(3.419)
(6.141)
(7.284)
RI
-21.94
-43.60
-1.473e+07**
-1.759*
-3.588**
-3.673*
(14.69)
(26.11)
(5.206e+06)
(0.933)
(1.676)
(1.988)
Industry
Dummies
YES
YES
YES
YES
YES
YES
Constant
7.138
6.588
-1.008e+06
0.0715
-0.176
-0.323
(4.655)
(8.276)
(1.650e+06)
(0.296)
(0.531)
(0.630)
Observations
38
38
38
38
38
38
R-squared
0.786
0.735
0.627
0.656
0.644
0.490
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
Thus, the results of the year-wise OLS regression analyzing the relationship between
CGDI and firm performance indicates that corporate governance disclosure index
positively impacts the performance of the firm when measured using various
performance measures. However, the relationship is not statistically significant for all
the years and for different performance measures used.
4.4 Pooled OLS Regression
To further analyse the relationship between CGDI and firm performance measures,
Pooled OLS regression technique was employed. The data for the five years is pooled
and regressed with firm performance measures as dependent variables and CGDI as
explanatory variable along with the control variables. In addition to the Industry
dummies, 4 year dummies were also added in the regression equation representing four
years from 2009 to 2012.
Regression Equation for Pooled Data is as follows:
192 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
(4)
Here, Firm Performance denotes Tobin’s Q, MBVR, MVA, ROA, ROCE and ROE in
different models respectively.
The maximum VIF is 1.33 implying that the data is free from the problem of
multicollinearity. For heteroskedasticity, robust standard errors are used. The Durbin
Watson value revolved around 2 which mean that there is no first order autocorrelation
in the data.
The results of the Pooled OLS regression are depicted in Table-11. The coefficients of
the CGDI are found to be significantly and positively associated with all the
performance measures used. However, the level of significance varied. CGDI is
significantly associated at 1% level of significance with market based performance
measures (Tobin’s Q, MBVR and MVA), at 5% level of significance with ROA and
ROCE and with 10% level of significance with ROE. The R-squared value for the
Pooled OLS regression dropped as compared to the year-wise OLS regression
Table 11: Pooled OLS Regression estimates: CGDI and Firm
Performances-2008-12
(1)
(2)
(3)
(4)
(5)
(6)
VARIABLES
Tobin’s Q
MBVR
MVA
ROA
ROCE
ROE
CGDI
0.0464**
*
0.0850**
*
16,379***
0.00185**
0.00291*
*
0.00289*
(0.0156)
(0.0267)
(4,310)
(0.000749
)
(0.00140)
(0.00158
)
Risk
-1.493***
-2.421***
-445,877***
-
0.0457***
-0.0689**
-
0.0938**
(0.366)
(0.625)
(100,863)
(0.0175)
(0.0329)
(0.0370)
FG
-0.0400
0.101
-103,727
-
0.0768***
-0.111***
-
0.154***
(0.371)
(0.634)
(102,294)
(0.0178)
(0.0333)
(0.0375)
FA
-0.418
-0.576
156,590*
-0.0132
-0.0135
-0.0137
(0.343)
(0.586)
(94,628)
(0.0164)
(0.0308)
(0.0347)
FS
-0.111
-0.336
439,221***
0.00508
-0.00213
0.0263
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 193 | P a g e
(0.300)
(0.512)
(82,677)
(0.0144)
(0.0269)
(0.0303)
Lev
-0.893***
-0.875**
-340,783***
-
0.0949***
-0.181***
-0.0137
(0.259)
(0.443)
(71,463)
(0.0124)
(0.0233)
(0.0262)
AI
22.55
38.51
5.873e+06
-1.826**
-3.726**
-3.334*
(18.22)
(31.13)
(5.026e+06)
(0.873)
(1.638)
(1.845)
RI
0.347
-12.46
-5.228e+06**
-0.714**
-1.593**
-1.692**
(7.385)
(12.62)
(2.037e+06)
(0.354)
(0.664)
(0.748)
Industry
Dummies
YES
YES
YES
YES
YES
YES
Year Dummies
YES
YES
YES
YES
YES
YES
Constant
1.672
2.903
-
2.368e+06**
*
0.237***
0.406**
0.400**
(1.858)
(3.174)
(512,388)
(0.0890)
(0.167)
(0.188)
Observations
190
190
190
190
190
190
R-squared
0.437
0.413
0.476
0.513
0.493
0.351
Durbin Watson
Stats
2.06
2.16
1.92
1.81
1.75
1.86
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
4.5 Panel Data Regression
4.5.1 Specification Tests
4.5.1.1 Hausman Test
In order to choose between the Fixed Effect and Random Effect Model, the study
employed Hausman Test. Hausman Test rejects the null hypothesis for models with
performance variables Tobin’s Q, MBVR, MVA and ROA, implying that Fixed Effect
Model is favoured over Random Effect Model. However, for ROCE and ROE, Random
Effect Model is favoured as Hausman Test accepts the null hypothesis. Thus, the study
used Fixed Effect Model for Dependent Variables-Tobin’s Q, MBVR, MVA and ROA
and Random Effect Model for ROCE and ROE. Table- 12 shows the results pertaining
to Hausman Test.
194 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
Table 12: Hausman Test
Specification Tests
Hausman Test
VARIABLES
Chi square
p-value
Tobin’s Q
31.7
0.0015***
MBVR
55.05
0.0000***
MVA
21.7
0.041***
ROA
20.88
0.0347***
ROCE
16.58
0.1211
ROE
7.95
0.7179
Source: Authors’ Analysis
Note: *** Statistically Significant at 1% Level
4.5.1.2 Multicollinearity Test
The correlation value less than 0.8 signifies that there is no multicollinearity among the
variables. The results of Correlation Analysis as shown in Table-13 confirm that there is
no issue of multicollinearity in the data.
Table 13: Pairwise Correlation between CGDI and Control Variables
CGDI
Risk
FG
FS
Lev
FA
AI
RI
CGDI
1
Risk
0.1833*
1
FG
-0.2317*
-0.0883
1
FS
0.2764*
0.2879*
-0.1289
1
Lev
0.0442
0.1749*
0.0039
0.1376
1
FA
0.0865
0.3266*
-0.0437
0.1058
-0.0085
1
AI
0.0721
-0.1819*
-0.007
-0.1638*
-0.0694
-0.1552*
1
RI
0.014
-0.2597*
0.0169
-0.2990*
-0.1767*
-0.0852
-0.1833*
1
Table-14 presented the VIF statistics as a check for multicollinearity. VIF values are
found very less with the mean VIF of 1.21 for all CGDI (independent variable) and
control variable. This also signifies that there is no multicollinearity among the
variables.
Table 14: Collinearity Statistics
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 195 | P a g e
Variabl
e
CGDI
Risk
FA
FG
FS
Lev
AI
RI
Mean
VIF
VIF
1.2
1.33
1.14
1.06
1.32
1.07
1.2
1.3
1.21
Source: Authors’ Analysis
4.5.1.3 Heteroskedasticity Tests
The results of Likelihood ratio test for testing the panel level heteroskedasticity are
depicted in Table-15. Test results showed that there is heteroskedasticity in the case of
all dependent variables.
Table 15: Heteroskedasticity Tests
Specification Tests
Likelihood Ratio (LR) Test for Panel Level Heteroskedasticity
VARIABLES
Chi square
p-value
Tobin’s Q
250.55
0.0000***
MBVR
238.51
0.0000***
MVA
316.28
0.0000***
ROA
139.65
0.0000***
ROCE
172.88
0.0000***
ROE
166.76
0.0000***
Source: Authors’ Analysis
Note: *** Statistically Significant at 1% Level
4.5.1.4 Autocorrelation Test
The results of Wooldridge test for serial correlation as show in Table-16 concluded the
presence of first order autocorrelation in all the panel models with different dependent
variables.
Table16: Autocorrelation Test
Specification Tests
Wooldridge Test for Autocorrelation in Panel Data
VARIABLES
F Stats
p-value
Tobin’s Q
38.183
0.0000***
MBVR
32.071
0.0000***
MVA
17.391
0.0002***
ROA
12.546
0.0011***
196 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
ROCE
11.203
0.0019***
ROE
12.418
0.0012***
Source: Authors’ Analysis
Note: *** Statistically Significant at 1% Level
Following the results of the heteroskedasticity and autocorrelation, the panel data regression
models use cluster robust Standard Errors to control for heteroskedasticity and
autocorrelation Table-17 below shows the summary of the regression used in the study.
Table17: Regression Summary
REGRESSION SUMMARY
Tobin's Q, MBVR,
MVA and ROA
Fixed effect Model (With-in) adjusted for “cluster robust” standard
error.
LSDV adjusted for “cluster robust” standard error.
FGLS model adjusted for heteroskedasticity and first order
autocorrelation.
ROCE and ROE
Random effect Model adjusted for “cluster robust” standard error.
FGLS model adjusted for heteroskedasticity and first order
autocorrelation.
Source: Authors’ Compilation
4.5.2 Regression with Tobin’s Q as a measure of firm performance
In order to analyze the relationship between CGDI and firm performance, CGDI is
regressed with Tobin’s Q as dependent variable based on the regression summary as
described in Table-17. Below are the regression equations. In Model 1, only CGDI
(independent variable) is regressed as explanatory variables with Tobin’s Q as
dependent variable. On the other hand in Model 2 regression of CGDI along with the
various control variables is performed using Tobin’s Q as firm performance measure.
FIXED EFFECT WITH-IN ESTIMATES EQUATION
MODEL 1:
(5)
MODEL 2:
(6)
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 197 | P a g e
LEAST SQUARE DUMMY VARIABLE (LSDV) EQUATION
MODEL 1:
(7)
MODEL 2:
(8)
The results of the regression analysis (Table-18) showed that CGDI has a positive
impact on Tobin’s Q irrespective of the regression technique employed. In both the
models (without and with control variables) CGDI showed a positive relationship with
Tobin’s Q. However, the impact of CGDI is found significant only in the case of FGLS
at 1% level of significance. Risk is found to be negatively and significantly associated
with Tobin’s Q. On the other hand, Ai and RI are positively and significantly associated
with Tobin’s Q. The relationship of Tobin’s Q with other control variables is found
insignificant.
Table 18: Regression Results Using Tobin’s Q as firm performance
measure
(1)
(2)
(1)
(2)
(1)
(2)
VARIABLES
Fixed Effect with
Cluster Robust
Standard errors
LSDV with Cluster
Robust Standard
Errors
FGLS with Panels
Heteroskedastic and
First order Auto-
Correlation
CGDI
0.0493
0.00846
0.0493
0.00846
0.0165***
0.0234***
(0.0625)
(0.0597)
(0.0697)
(0.0671)
(0.00503)
(0.00873)
Risk
-1.423***
-1.423***
-0.802***
(0.430)
(0.483)
(0.255)
FG
-0.400*
-0.400
-0.239
(0.213)
(0.239)
(0.202)
FA
9.154**
9.154**
-0.0530
198 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
(3.403)
(3.827)
(0.334)
FS
-2.052
-2.052
-0.256
(1.538)
(1.729)
(0.221)
Lev
-0.574
-0.574
-0.571***
(0.391)
(0.440)
(0.173)
AI
108.7**
108.7**
53.24***
(40.98)
(46.08)
(14.00)
RI
34.53***
34.53***
8.874*
(9.039)
(10.16)
(4.793)
Industry Dummies
NO
YES
YES
Year Dummies
YES
YES
YES
Constant
-1.747
-0.869
-1.747
-0.869
1.002**
2.986**
(5.397)
(6.987)
(6.022)
(7.856)
(0.441)
(1.449)
Observations
190
190
190
190
190
190
R-squared
0.055
0.408
0.596
0.747
Number of Firms
38
38
38
38
38
38
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
4.5.3 Regression with MBVR as a measure of firm performance
Regression equations are as follows:
FIXED EFFECT WITH-IN ESTIMATES EQUATION
MODEL 1:
(9)
MODEL 2:
(10)
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 199 | P a g e
LEAST SQUARE DUMMY VARIABLE (LSDV) EQUATION
MODEL 1:
(11)
MODEL 2:
(12)
As shown in Table-19 CGDI is significantly positively associated with MBVR for
FGLS methodology at 1 % level of significance. With Fixed effect and LSDV
regression the relationship between CGDI and MBVR is positive but not
significant.Like Tobin’s Q Risk is negatively and significantly associated with MBVR.
Except FG other control variables also depicted the same relationship with MBVR as
with Tobin’s Q
Table 19: Regression Results MBVR as firm performance measure
(1)
(2)
(1)
(2)
(1)
(2)
VARIABLES
Fixed Effect with
Cluster Robust
Standard errors
LSDV with Cluster
Robust Standard
Errors
FGLS with Panels
Heteroskedastic and
First order Auto-
Correlation
CGDI
0.0894
0.0327
0.0894
0.0327
0.0382***
0.0420***
(0.0898)
(0.0803)
(0.100)
(0.0903)
(0.00796)
(0.0154)
Risk
-2.877***
-2.877***
-1.547***
(0.656)
(0.738)
(0.366)
FG
-0.615*
-0.615*
-0.262
(0.321)
(0.361)
(0.341)
FA
19.40***
19.40***
0.0294
(5.053)
(5.682)
(0.506)
FS
-3.282
-3.282
-0.162
(2.697)
(3.032)
(0.282)
Lev
0.657
0.657
-0.430**
200 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
(1.045)
(1.175)
(0.188)
AI
168.9***
168.9**
82.36***
(55.63)
(62.56)
(26.62)
RI
54.04**
54.04*
3.860
(24.73)
(27.81)
(7.899)
Industry Dummies
NO
YES
YES
Year Dummies
YES
YES
YES
Constant
-3.391
-9.699
-3.391
-9.699
0.924
4.438**
(7.756)
(12.98)
(8.655)
(14.59)
(0.701)
(2.072)
Observations
190
190
190
190
190
190
R-squared
0.065
0.458
0.600
0.768
Number of Firms
38
38
38
38
38
38
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
4.5.4 Results with MVA as a measure of firm performance
Like Tobin’s Q and MBVR, Regression is performed using FE, LSDV and FGLS
models adjusted for heteroskedasticity and autocorrelation. The Regression equations
are as follows:
FIXED EFFECT WITH-IN ESTIMATES EQUATION
MODEL 1:
(13)
MODEL 2:
(14)
LEAST SQUARE DUMMY VARIABLE (LSDV) EQUATION
MODEL 1:
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 201 | P a g e
(15)
MODEL 2:
(16)
Table-20 reveals the impact of CGDI on MVA as firm performance measure. CGDI is
found to be significantly positively associated with MVA under different estimation
models. But the level of significance varied. With Fixed effect and LSDV model the
level of significance is 10% whereas with FGLS the level of significance is 1%. Risk is
found to be negatively significantly associated with MVA. FG, FS and Leverage are
negatively associated on the other hand; AI and RI are positively associated with MVA.
FA depicted a positive relationship under Fixed Effect and LSDV model and negative
relationship under FGLS model.
Table 20: Regression Results Using MVA as firm performance
measure
(1)
(2)
(1)
(2)
(1)
(2)
VARIABLES
Fixed Effect with
Cluster Robust
Standard errors
LSDV with Cluster
Robust Standard Errors
FGLS with Panels
Heteroskedastic and
First order Auto-
Correlation
CGDI
19,097*
10,478*
19,097*
10,478*
9,522***
6,303***
(11,079)
(10,633)
(12,362)
(11,956)
(2,107)
(1,856)
Risk
-225,192**
-225,192**
-94,106*
(83,292)
(93,654)
(59,729)
FG
-40,605
-40,605
-72,282
(53,550)
(60,212)
(48,060)
FA
770,078
770,078
-99,718
(533,852)
(600,266)
(63,478)
FS
-55,522
-55,522
-
452,455***
(340,693)
(383,077)
(68,991)
202 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
Lev
-22,742
-22,742
-
184,840***
(80,393)
(90,395)
(47,364)
AI
1.951e+07
***
1.951e+07
***
8.105e+06*
*
(5.974e+06
)
(6.717e+06
)
(3.424e+06)
RI
4.328e+06
4.328e+06
1.780e+06
(4.487e+06
)
(5.045e+06
)
(1.131e+06)
Industry
Dummies
NO
YES
YES
Year Dummies
YES
YES
YES
Constant
-
1.212e+
06
-1.301e+06
-
1.212e+0
6
-1.301e+06
-
464,838*
**
-
2.041e+06*
**
(957,430
)
(1.561e+06
)
(1.068e+
06)
(1.755e+06
)
(178,558)
(375,881)
Observations
190
190
190
190
190
190
R-squared
0.148
0.348
0.751
0.809
Number of
Firms
38
38
38
38
38
38
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
4.5.5 Regression with ROA as a measure of firm performance
Regression equations for the two models (without and with control variables) with ROA
as dependent variable are as follows:
FIXED EFFECT WITH-IN ESTIMATES EQUATION
MODEL 1:
(17)
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 203 | P a g e
MODEL 2:
(18)
LEAST SQUARE DUMMY VARIABLE (LSDV) EQUATION
MODEL 1:
(19)
MODEL 2:
(20)
CGDI has positive but insignificant impact on firm performance measure ROA under
various regression techniques used as presented in the Table-21. The relationship
between control variables and ROA is different as against market based performance
measures (Tobin’s Q, MBVR and MVA). Risk demonstrated a positive relationship with
ROA under Fixed effect and LSDV model and negative under FGLS techniques. FS is
found to be significantly positively associated with ROA. FG is negatively associated
with ROA whereas AI and RI are negatively associated with ROA. As far as leverage is
concerned, it is negatively and significantly associated with ROA.
Table 21: Regression Results Using ROA as firm performance
measure
(1)
(2)
(1)
(2)
(1)
(2)
VARIABLES
Fixed Effect with
Cluster Robust
Standard errors
LSDV with Cluster
Robust Standard
Errors
FGLS with Panels
Heteroskedastic and
First order Auto-
Correlation
CGDI
0.000200
6.54e-05
0.000200
6.54e-05
6.79e-05
0.000217
(0.00123)
(0.00139)
(0.00137)
(0.00156
)
(0.000214
)
(0.000451)
Risk
0.0226
0.0226
-0.00744
204 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
(0.0165)
(0.0186)
(0.00928)
FG
-0.0131*
-0.0131
-0.00848
(0.00773)
(0.00869
)
(0.00737)
FA
0.0882
0.0882
-
0.0994***
(0.0933)
(0.105)
(0.0165)
FS
0.115**
0.115*
0.0249*
(0.0532)
(0.0598)
(0.0144)
Lev
-
0.109***
-0.109**
-0.123***
(0.0388)
(0.0437)
(0.0130)
AI
-0.0268
-0.0268
-0.708
(0.847)
(0.953)
(0.479)
RI
-0.630
-0.630
-0.104
(0.615)
(0.692)
(0.348)
Industry Dummies
NO
YES
YES
Year Dummies
YES
YES
YES
Constant
0.224**
-0.447
0.224*
-0.447
0.199***
0.264***
(0.106)
(0.284)
(0.119)
(0.319)
(0.0191)
(0.0862)
Observations
190
190
190
190
190
190
R-squared
0.001
0.263
0.747
0.813
Number of Firms
38
38
38
38
38
38
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
4.5.6 Results with ROCE as a measure of firm performance
As Hausman test accepted the null hypothesis for ROCE of significant Random effects,
Regression is performed using Random Effect Model. Also FGLS model adjusted for
heteroskedasticity and autocorrelation is used.
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 205 | P a g e
RANDOM EFFECT EQUATION
MODEL 1:
(21)
MODEL 2:
(22)
Like ROA, CGDI is positively associated with ROCE across all models as shown in
Table-22. Control variable Leverage, AI and RI are negatively and significantly
impacting firm performance measure ROCE. FG also showed a negative but
insignificant relationship with ROCE. FS has a positive and insignificant impact on
ROCE. Risk showed a negative relationship with ROCE under Random effect
regression and positive relationship under FGLS estimation.
Table 22: Regression Results Using ROCE as firm performance
measure
(1)
(2)
(1)
(2)
VARIABLES
Random Effect with
Cluster Robust Standard
errors
FGLS with Panels
Heteroskedastic and First
order Auto-Correlation
CGDI
0.000365
0.00134
0.000531
0.000789
(0.00169)
(0.00173)
(0.000372)
(0.000740)
Risk
0.0163
-0.00837
(0.0319)
(0.0180)
FG
-0.0101
-0.00376
(0.0139)
(0.0117)
FA
-0.0529
-0.165***
(0.0557)
(0.0298)
FS
0.0301
0.0646**
(0.0431)
(0.0256)
Lev
-0.206***
-0.193***
206 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
(0.0606)
(0.0274)
AI
-0.0783*
-1.554*
(1.470)
(0.906)
RI
-1.041**
-1.157**
(0.521)
(0.468)
Industry Dummies
YES
YES
Year Dummies
YES
YES
Constant
0.285*
0.214
0.270***
0.295**
(0.146)
(0.205)
(0.0319)
(0.134)
Observations
190
190
190
190
Number of Firms
38
38
38
38
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
4.5.7 Regression with ROE as a measure of firm performance
For ROE also Hausman Test accepted the null hypothesis, thus the regression is
performed using Random effect along with FGLS.
RANDOM EFFECT EQUATION
MODEL 1:
(23)
MODEL 2:
(24)
The regression estimates are shown in Table-23. Like accounting measures ROA and
ROCE, The relationship between CGDI and ROE is found to be positive irrespective of
the regression technique employed. Control variable Risk, FA and RI are negatively
significantly associated with ROE, but the relationship with FG and AI is only negative.
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 207 | P a g e
FS has a positive and significant impact on ROE. Leverage also has a positive impact on
ROE; however the impact is found significant only under FGLS estimation.FA is
negatively and significantly associated with ROE because of company and
products life cycle growth stage, as it calculated taken into account the date of
incorporation. RI research is negative and significantly associated with ROE as
the firms and product becomes older there is a need to spend lot on R&D
expenditure which is adversely impacting the ROE. Firm growth isnegatively
associated with ROE, as this measure is calculated with the help of sales
numbers, when sales dip ROE will falls, but this fall is not statistically significant
as it is clear from the model (name the model), AI isnegatively associated with
ROE, spending on advertising to a large extent is a controllable cost and its
impact is not significant on the ROE. FS is positive and significantly associated
with ROE, large and big firms because of their conglomerate/ diversified
character, huge asset base in their balance sheet has a significant impact on ROE
Table 23: Regression Results Using ROE as firm performance
measure
(1)
(2)
(1)
(2)
VARIABLES
Random Effect with
Cluster Robust Standard
errors
FGLS with Panels
Heteroskedastic and First
order Auto-Correlation
CGDI
0.000803
0.00127
0.000575
0.000627
(0.00195)
(0.00185)
(0.000635)
(0.000774)
Risk
-0.0259*
-0.0305*
(0.0343)
(0.0184)
FG
-0.00992
-0.00366
(0.0170)
(0.0127)
FA
-0.120*
-0.177***
(0.0699)
(0.0255)
FS
0.0624*
0.0793***
(0.0444)
(0.0240)
Lev
0.0212
0.0329*
(0.0637)
(0.0188)
AI
-0.0612
-1.143
208 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
(1.389)
(1.001)
RI
-1.218*
-1.050**
(0.651)
(0.512)
Industry Dummies
YES
YES
Year Dummies
YES
YES
Constant
0.466***
0.231
0.451***
0.286**
(0.173)
(0.243)
(0.0571)
(0.137)
Observations
190
190
190
190
Number of Firms
38
38
38
38
Robust Standard Errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Source: Authors’ Analysis
5. Conclusion
In the present paper we have outlined the construction of corporate governance
disclosure Index for NSE listed firms in India. The index is based on eleven broad
dimensions namely- Statement of Philosophy, Board of directors, Board meetings, Audit
committee, Shareholder’s/Investors Grievance Committee, Remuneration Committee,
Nomination Committee, General Body Meetings, General Shareholder Information,
Mandatory Disclosures and Non-mandatory Disclosures. 52 parameters form these
eleven dimensions were used to develop the overall CGDI. The CGDI for the 5 years
form 2008-12 for 38 non-financial NSE nifty 50 companies showed an upward trend in
the governance practices. Companies are moving close to each other in terms of their
CGDI. However, the results revealed that there is significant scope for improvement in
the corporate governance disclosure practices followed by the companies as not even a
single company in the period of 5 years attained a maximum value of CGDI i.e. 100.
The results of Cross Sectional OLS regression, Pooled OLS regression and Panel Data
regression concluded that CGDI has a positive impact on firm performance measured
either with market based measures or accounting based measures. The Cross-Sectional
OLS regression analysis results provided a sound proof of strengthening of the
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 209 | P a g e
relationship between CGDI and firm performance measures over the years. This
strengthening of relationship is attributable to the growing corporate governance
reforms as enacted in Indian corporate sector over these years. The results of pooled
OLS regression found a positive and significant relationship between the CGDI and
Firm performance measures. Panel Data regression results reported a significant and
positive relationship between CGDI and market based performance measures but only
positive relationship with accouting measures. The results are consistent with agency
theory of Corporate Governance which focuses on monitoring the performance
managers so that they align their interests with the interests of the shareholders of the
company. The findings are in line with the previous studies in both developed and
developing market (Klapper and Love, 2004; Durnev and Kim, 2005; Sarkar et. al,
2012; Black et. al, 2006; Varshney et. al, 2012). The study implies that firms that
disclose more are likely to result in higher performance.
The research paper is subject to certain limitations. The study is restricted to a limited
number of companies for a period of 5 years. The findings may be different if a larger
sample was included for a longer time period. Also the parameters included in the study
were recorded based on the information disclosed in the annual reports and it is thus
assumed that the information is fair and accurate. A worthwhile avenue for future
research could be to use same hypothesis to analyse the corporate governance disclosure
practices followed by other developing countries and more developed countries for a
large number of companies and in light of other control variables.
Despite the limitations, the results provided strong evidence in favour of the theoretical
arguments that corporate disclosures reduces agency costs arising due to separation of
ownership and control and information asymmetry.
References
Allegrini, M., & Greco, G. (2013). “Corporate Boards, Audit Committees and Voluntary
Disclosure: Evidence from Italian Listed Companies,” Journal of Management &
Governance, 17(1), 187-216.
Bebchuk, L., Cohen, A., & Ferrell, A. (2009). “What Matters in Corporate Governance?” Review
of Financial studies, 22(2), 783-827.
Bhagat, S., & Bolton, B. (2008). “Corporate Governance and Firm Performance” Journal of
Corporate Finance, 14(3), 257-273.
Bhuiyan, M., Ullah, H., & Biswas, P. K. (2007). “Corporate Governance and Reporting: an
Empirical Study of the Listed Companies in Bangladesh” Dhaka University Journal of Business
Studies, 28(1).
210 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
Black, B. S., Jang, H., & Kim, W. (2006). “Does Corporate Governance Predict Firms' Market
Values? Evidence from Korea.” Journal of Law, Economics, and Organization, 22(2), 366-413.
Brown, L. D., & Caylor, M. L. (2006). “Corporate Governance and Firm Valuation.” Journal of
accounting and public policy, 25(4), 409-434.
Cunha, V. L. M., & Mendes, S. M. D. (2017). “Financial Determinants of Corporate Governance
Disclosure: Portuguese Evidence.” Athens Journal of Business and Economics, 3(1), 21-35.
Drukker, D. M. (2003). “Testing for Serial Correlation in Linear Panel-Data Models.” Stata
Journal, 3(2), 168-177.
Durnev, A., & Kim, E. (2005). “To Steal or not to Steal: Firm Attributes, Legal Environment,
and Valuation.” The Journal of Finance, 60(3), 1461-1493.
Gompers, P. A., Ishii, J. L., & Metrick, A. (2001). “Corporate Governance and Equity
Prices.” Working Paper No. w 8449, National Bureau of Economic Research.
Gupta, A., & Parua, A. (2006, December). An Enquiry into Compliance of Corporate
Governance Codes by the Private Sector Indian Companies. In 10th Indian Institute of Capital
Markets Conference Paper.
Gupta, A., Nair, A. P., & Gogula, R. (2003). “Corporate Governance Reporting by Indian
Companies: A Content Analysis Study.” The ICFAI Journal of Corporate Governance, 2(4), 7-
18.
Javaid, F., & Saboor, A. (2015). “Impact of Corporate Governance Index on Firm Performance:
Evidence from Pakistani Manufacturing Sector.” Journal of Public Administration and
Governance, 5(2), 1-21.
Kamal Hassan, M. (2012). “A Disclosure Index to Measure the Extent of Corporate Governance
Reporting by UAE Listed Corporations.” Journal of Financial Reporting and Accounting, 10(1),
4-33.
Klapper, L. F., & Love, I. (2004). “Corporate Governance, Investor Protection, and Performance
in Emerging Markets.” Journal of corporate Finance, 10(5), 703-728.
Lehn, K. M., Patro, S., & Zhao, M. (2009). “Determinants of the Size And Composition Of Us
Corporate Boards: 19352000.” Financial Management, 38(4), 747-780.
Prince, J. B. (2014). “Corporate Governance Index and firm performance.” Journal of
Contemporary Research in Management, 9(3).
Raithatha, M., & Bapat, V. (2012). “Corporate Governance Compliance Practices Of Indian
Companies.” Research Journal of Finance and Accounting, 3(8), 19-26.
Sarkar, J., Sarkar, S., & Sen, K. (2012). “A Corporate Governance Index for Large Listed
Companies in India.” Available at SSRN 2055091.
Sen, A. (2011). “Corporate Governance in India: Clause 49 of the Listing Agreement.” JM
International Journal of Management Research, 1, 162-172.
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 211 | P a g e
Varshney, P., Kaul, V. K., & Vasal, V. K. (2012). “Corporate Governance Index and Firm
Performance: Empirical Evidence from India.” Available at SSRN 2103462.
ANNEXURE
Corporate Governance Disclosure Index
S.NO
MAIN
DIMENSION
SUB DIMENSION
Points
Assigne
d
Scor
e
1
Statement
of
Philosophy
Statement of Company's Philosophy on Code of
governance
1
1
2
Board of
Directors
Details of Board of Directors
1
6
3
Percentage of non-executive directors as
stipulated
1
4
Percentage of Independent directors as
stipulated
1
5
Details of membership in other companies
1
6
Details of membership/Chairmanship in other
committees
1
7
Disclosure of tenure & age limit of directors
1
8
Board
Meetings
Number of board meetings in a year
1
4
9
Dates of Board meetings
1
10
Attendance of each director at the Board
Meeting
1
11
Attendance of each director at the last AGM
1
15
Audit
Committee
Description of Audit Committee terms of
Reference
1
7
16
Members of Audit Committee
1
17
Audit Committee chaired by Independent
Director
1
18
Presence of member with expertise in
accountancy
1
19
Number of audit committee meetings
1
20
Dates of audit committee meetings
1
21
Attendance of each director in the committee
meeting
1
22
Shareholde
rs' /
Investors
Members of Shareholders' / Investors
Grievance Committee
1
6
23
Independence of Shareholders' / Investors
1
212 | P a g e B u s i n e s s A n a l y s t A p r i l 2 0 1 7 - S e p t e m b e r 2 0 1 7
Grievance
Committee
Grievance Committee
24
Number of Shareholders' / Investors Grievance
committee meetings
1
25
Dates of Shareholders' / Investors Grievance
committee meetings
1
26
Attendance of each director in the committee
meeting
1
27
Information on the number of Grievance
received and addressed
1
28
Remunerati
on
Committee
Brief description of terms of reference
1
5
29
Composition, name of members and
Chairperson of Remuneration Committee
1
30
Dates of Remuneration Committee Meetings
1
31
Attendance of each director in the committee
meeting
1
32
Details of remuneration to all the directors, as
per format in main report.
1
33
Nomination
Committee
Presence of Nomination Committee
1
1
12
General
Body
Meetings
Dates, Time and Location of last three AGMs
1
3
13
Details of Special Resolution passed in the last
three AGMs
1
14
Details of Resolution passed through postal
ballot in the last financial year
1
34
General
Shareholde
r
Information
Listing on Stock Exchange
1
7
35
Stock Code
1
36
Registrar and Transfer Agents
1
37
Share transfer System
1
38
Distribution of Shareholding
1
39
Plant Locations
1
40
Address for Correspondence
1
41
Mandatory
Disclosures
Information and Compliance of Code of
Conduct
1
8
42
Significant Related Party transactions
1
43
Non-compliance by the company, penalties &
strictures imposed
1
44
Management Discussion & Analysis Report
1
45
Remuneration to Directors
1
46
Means of Communication Information
1
CORPORATE GOVERNANCE DISCLOSURE INDEX AND FIRM PERFORMANCE 213 | P a g e
47
CEO/CFO Certification
1
48
Compliance Report on Corporate Governance
1
49
Non
Mandatory
Disclosures
Whistle Blower Policy
1
4
50
Training of the Board Members
1
51
Audit Qualification
1
52
Shareholder Rights
1
Total
52
52
