corporate disclosure practices in indian software industry

7/30/2019 Corporate Disclosure Practices in Indian Software Industry

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AN EMPIRICAL INVESTIGATION OF THECORPORATE DISCLOSURE PRACTICES IN

INDIAN SOFTWARE INDUSTRY

Poonam Mahajan

Junior Research Fellow

Department of Commerce & Business Management

Guru Nanak Dev University, [email protected]

+91-98159-66291

Dr. Subhash Chander

Professor

Department of Commerce & Business Management

Guru Nanak Dev University, [email protected]

+91-98140-01493
mailto:[email protected]:[email protected]:[email protected]:[email protected]


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AN EMPIRICAL INVESTIGATION OF THE CORPORATE

DISCLOSURE PRACTICES IN INDIAN SOFTWARE INDUSTRY

ABSTRACT

This study empirically examines the quantum of corporate disclosure and itsassociation with corporate attributes, such as, age, size, profitability, leverage, listing status,

shareholding pattern, audit firm, and residential status of a company. It is based on a sample

of 50 companies from the software industry drawn from PROWESS database of the Centerfor Monitoring Indian Economy (CMIE) for the year 2004-05 on the basis of market

capitalization as on march, 31, 2005. An unweighted disclosure index consisting of 90 items

of information was constructed, which was used to compute the disclosure score of eachselected company. Pearson correlation product moment matrix was used to check the

multicolleanarity between independent variables. Multiple regression analysis revealed that

significant association exists between size, profitability, and audit firm and disclosure level.However, no significant association was found between disclosure score and age, listing

status, leverage, shareholding pattern, and residential status of a company.

INTRODUCTION

Corporate disclosure and its determinant analysis has become a thrust area of research for

various researchers and academicians. Many researchers have contributed towards exploration

of this area of research. Still, many questions arise in the mind of an analyst or researcher as

to why do different firms in the same industry has varying disclosure practices? The need is to

explore the area why extent of information is differing among industries or in same industry?

Day by day the concept of disclosure is also changing. Now, it does not mean disclosing

immaterial, irrelevant, vague information. Now emphasis is given to the qualitative aspect of

information which is relevant to informed investors for making economic decisions. The main

reason for this emphasis is that full and complete disclosure is the cornerstone to protect the

shareholders rights. Shareholders are the owners of a company and they should be informed

about the working prospects of a company. Only through full and complete disclosure canshareholders feel confident that the firm to which they have given their hard earned money is

being operated with their best interests in mind.

Forward-thinking companies report both financial and regulatory (operational) data to key

external and internal constituents. They monitor market and stakeholder reactions to the

reported information and then adapt their disclosure in response to such feedback as well as

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other market, regulatory, and social developments. In return for such transparent, proactive

reporting, the companies enjoy benefits such as stronger stakeholder relationships, greater

support throughout all operations for reporting initiatives, larger following of investment

analysts, easier access to capital, and lower reputation risk. (Price Waterhouse Coopers, 2005,

p. 3).

With globalization of Indian economy and subsequent entry of foreign institutional investors,

there has been demand for more disciplined financial reporting (Mathew, 1999, p.373).

Globalization of capital markets has been accompanied by calls for globalization of financial

reporting (Healy and Palepu, 2000, p. 42). The challenges faced in the corporate disclosure

are now greater than ever (Hutton, 2004, p 8). It has become a precondition for the proper

working of the capital markets. It may be viewed as a special protection instrument that

investors and creditors (banks in particular) have at their disposal to protect their interest

(Farina, 2005, p.6). Better disclosure has a positive impact on the efficient functioning of the

capital markets (Patel, Dallas, 2002, p. 5). It is vital for the optimum decision of investors and

for a stable capital market (Datt, 1999, p. 660). Greater transparency and better disclosure

keep corporate stakeholders better informed about the way company is being managed.

The developing nations in need of external finance both from domestic as well as foreign

sources are under a great pressure to improve the quality of reporting practices for their

economic growth and well being. Todays complex business environment has increased the

pressure on companies to be more transparent in their financial reporting.

CONCEPT OF DISCLOSURE

The subject of corporate disclosure which is also known as Financial Reporting,

Corporate Reporting and Disclosure has increasingly gained significance during the recent

years. A lot of changes have taken place in economic environment of the country and the

corporate sector in particular, due to market oriented policies introduced by the Government

since 1991 and emergence of new multilateral trading system under the aegis of World Trade

Organization (Committee report on companies bill (1997), 2002, p. 4).

The term disclosure can be defined in different ways. Kohlers Dictionary for Accountants

defines it as an explanation, or exhibits, attached to a financial statement, or embodied in a

report (e.g. auditor report) containing a fact, opinion or detail required or helpful in the

interpretation of the statement or report (cooper and Ijiri, 1984, p.176). It means the

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communication of material and relevant facts concerning financial position and the results of

the reporting concerns to various users (Meigs, Johnson and Meigs, 1977, p. 493). The term

Disclosure refers to the fact of disclosing any information concerning a company, whether

on voluntary or on statutory basis (Farina, 2005, p. 15).

Disclosure is a process of providing certain financial information to a wide variety of users,

relevant to their data needs, concerning the performance of an entity (Datt, 1999, p. 660). The

extent of information disclosure, its adequacy, relevance and reliability are important

characteristics of financial reporting practices prevalent in a country. So, in nutshell,

disclosure means to convey financial and non-financial information to various users that assist

them in taking economic and financial decision of better quality.

SIGNIFICANCE OF DISCLOSURE

The need for full disclosure is irrefutable in a free enterprise economy (Chander, 1992, p.4).

Investors have a very real interest in what companies disclose, in the trustworthiness of the

disclosure, and in how and when they disclose (Litan, 2003, p. 8). Better disclosure enhances

the quality and level of monitoring of firm by shareholders and strengthens corporate

governance. Over the years, the information provided by business organizations has increased

in quantity, quality, variety and timeliness (Narayanswamy, 2005, p.55). The working groups

on Indian Companies Act stated that other things being equal, greater the quality of

disclosure, the more loyal are a companys shareholders (CII report, 1998, p. 7).

Besides investors, financial disclosure is significant from the point of view of large number of

other potential users, these include in addition to present and future investors, employees,

suppliers, creditors, management, customers, financial analysts, advisors, brokers,

underwriters, stock exchange authorities, legislators, financial press, reporting agencies, labor

unions, trade associations, business researchers, academicians and above all public at large

(Datt, 1999, p. 660).

The financial sector and capital market reforms over last one decade have resulted in

substantial growth in the capital market and at the same time brought transparency in the its

operations (Committee report on companies bill (1997), 2002, p. 23). Indian companies,

banks and financial institutions can no longer afford to ignore better corporate practices. As

India gets integrated in the world market, Indian as well as international investors demand

greater disclosure, more transparent explanation for major decisions and better shareholder

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value (CII report, 1998, p 1). It is the financial reporting behavior of publicly listed companies

that is of primary importance to international portfolio investors and creditors (Craig and

Diga, 1998, p.248).

A communication revolution is on the anvil. Published annual reports are used as a medium

for communicating both quantitative and qualitative corporate information to shareholders,

potential shareholders (investors) and other users. Although publication of an annual report is

a statutory requirement, companies normally voluntarily disclose information in excess of the

mandatory requirements. Company management recognizes that there are economic benefits

to be gained from a well-managed disclosure policy. Thus, information disclosure in itself is a

strategic tool, which enhances a companys ability to raise capital at the lowest possible cost

(Healy and Palepu, 1993; Lev, 1992).

Thus, disclosure is significant from the point of view of users, companies and the nation on

the whole. It reduces uncertainty in the market and helps the users in selecting the best

portfolio for their investments. So, corporate disclosure is an essential element for the

efficient functioning of the capital market.

REVIEW OF LITERATURE

Since, the 1960s there has been an increased interest in accounting disclosure studies. A

number of studies have been conducted the world over to see the impact of company specific

attributes on the extent of the disclosure practices of the companies. A synoptic view of these

studies has been presented in table 1:

Table 1. Studies on the extent of disclosure and its association with corporate attributes

Author Period

of study

Sample

size/Countr

y of the

study

No. of

disclosure

items in

the

disclosure

index

Independent

variables

Statistical

techniques

used

Significant

explanatory

variables

Cerf (1961) 1960 527

USA

31 Size, Listing

Status, andprofitability

Regression

Analysis

Size, Listing Status

Singhvi (1968) 1963-1965

45India

34 Size, rate of return,earnings margin,audit firm, type ofmanagement,number ofstockholders

Univariate Size, management,number ofstockholders

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Singhvi andDesai (1971)

1965 155USA

34 Size, number of shareholders,listing status, sizeof auditing firm,rate of return andearnings margin

Univariate &Multivariate.

Listing status

Buzby(1974)

1970-1971

88USA

39 No variablesidentified

Mean and t-test

No adequatedisclosure by smalland medium sizedfirms in sample.

Buzby (1975) 1970-1971

88USA

38 Size, listing status Univariate Size

Barrett(1976)

1963-1972

103USA, UK,

France,Germany,Sweden,

Japan, andNetherlands

17 No variablesidentified

DescriptiveStatistics

Disclosure improvedthroughout years ofstudy. Wide variancesexist betweendisclosure levels ofUSA, UK from otherfive nations.

Stanga (1976) 1972 -1973 80USA 79 Size, industry Univariate &Multivariate Size, industry

Firth (1979) 1976 180UK

48 Size, listing status,audit firm

Univariate Size, listing status

McNally et al.(1982)

1979 103New

Zealand

41 size, rate of return,growth, audit firm,industry

Univariate Size

Firth (1984) 1977 180UK

48 Stock market risk Linear regression

No significantrelation

Garg(1986)

1979 51India

Notspecified

No variablesidentified

DescriptiveStatistics

Extent of statutorydisclosure is morethan voluntarydisclosure

Chow andWong-Boren(1987)

1982 52Mexico 24 Size, leverage,proportion of assetsin place

Multivariate(linearregression)

Size

Cooke (1989) 1985 90Sweden

224 Listing status,parent companyrelationship, size,number ofshareholders

Multivariate,threeregressionmodels

Listing status, size

Tai et al.(1990)

1987 76Hong Kong

11 Size, industry,audit firm

Univariate Size

Cooke (1991) 1988 48Japan

106 Size, listing status,industry

Univariate &Multivariate.

Size

Chander

(1992)

1981-

1985

50 (Public

& Privatesector each)India

92

(public),98(private)

Size, profitability,

age of a company,and nature ofindustry

Multivariate Size, Profitability


165 Size, listing status,industry

Multivariate Size, listing status,industry


195 Listing status Univariate Listing status

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Malone et al.(1993)

1986 125USA

129 Size, listing status,leverage,profitability, auditfirm

Stepwiseregressionmodel

Listing status,leverage, size

Ahmed andNicholls

(1994)

1988 63Bangladesh

94 Size, leverage,audit firm,

multinationality,qualification of thechief accountant

Univariate &Multivariate

Multinationality,accountants

qualification, size

Hossain et al .(1994)

1991 67Malaysia

78 Size, ownershipstructure, leverage,assets in place,audit firm, listingstatus


Size, ownershipstructure, listingstatus

Wallace et al.(1994)

1991 50Spain

16 Size, listing status,leverage,profitability, auditfirm, liquidity

Multivariate Size (+), listing status(+), liquidity (-)

Ahmed (1996) 1987-88,

1992-93

118Bangladesh

150 Size, leverage,audit firm, relationwith parent,qualification ofaccountants

RegressionAnalysis

Audit,Multinationality

Hossain et al.(1995)

1991 55New

Zealand

95 Size, leverage,assets in place,audit firm, listingstatus

Multivariate Size, leverage, listingstatus

Meek et al.(1995)

1994 116 (US)64 (UK)

16(France)

12(Germany)

18(Netherland)

85 Size, countryorigin, industries,leverage,

multinationality,profitability, listingstatus

Linearregression

Size, country, listingstatus

Raffournier(1995)

1991 161Switzerland

30 Company size,leverage,profitability,ownershipstructure,internationality,auditor size,industry type

Univariate &Multiple linearregressions

Size, internationality

Wallace and

Nasser (1995)

1991 80

HongKong

142 Foreign registered

office, profitmargin, earningsreturn, liquidityratio, leverage,size, outsideshareowners,conglomerates,audit firm

Multivariate Size,

conglomerates, andprofits.

Marston andRobson (1997)

1983-1990

29India

17 Size, change intime

Univariate Size

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Giner (1997) 1989-91 138Spain

50 Size, listing status,profitability,leverage, auditfirm, industry,dividend payout

Multivariate Size, auditing, listingstatus, andprofitability

Patton and

Zelenka(1997)

1993 50

CzechRepublic

66 Size, performance,

risk factors, othermonitoring factors(listing status, bigsix auditing firms,industry)

Univariate &

Multiple linearregressions

Type of auditor,

number of employees

Owusu-Ansah(1998)

1994 49Zimbabwe

214 Size, ownership,age, multinationalaffiliation,profitability, audit,industry, liquidity

Multivariate Size, ownership, age,multinationalaffiliationprofitability

Chen andJaggi (2000)

1993,1994

87HongKong

142 Independent non-executive directors,family control,profitability,leverage, size,audit firm

OLSregression

Independent non-executive directors

Depoers(2000)

1995 102France

65 Firm size, foreignactivity, ownershipstructure, leverage,size of auditing,proprietary costsrelated tocompetition, laborpressure

Multiple linearregression.

Foreign activity andsize

Gelb andZerowin(2000)

1980-1993

82USA

AIMR-FAFdisclosurescores

Informativeness ofstock prices

Multipleregressionmodel ofCollins,Kothari,Shanken, andSloan (1994)

Stock prices

Jaggi and Low(2000)

1991 28(from 28countries)

90 Cultural, legal andfinancial variables


Common law, culture

Ho and Wong(2001)

1998 98Hong Kong

20 Independent non-executive directors,audit committee,dominantpersonalities,family + control

variables

Multivariate(linearregression)

Audit committee,family

Bujaki andMcConomy(2002)

1997 272Canada

25 Size, Financialcondition, leverage,share issue,unrelated directors,regulatedindustries.

Linearregression

Unrelated directors,leverage

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Chau and Gray(2002)

1997 62Hong KongSingapore

110 Ownershipstructure, size,leverage, auditfirm, profitability,multinationalty,industry

Multivariate Ownership structure

Ferguson et al.(2002)

1995/96 142Hong Kong

93 Firm type, size,leverage, industry,listing status


Firm type, leverage(type of disclosure)

Haniffa andCooke (2002)

1995 167Malaysia

65 Corporategovernance,cultural and firmspecific

Linearregression

Family memberssitting on board, non-executive chairman

ArchambaultandArchambault(2003)

1992,1993

621(From 33countries)

85 Cultural, national,financial systems

Multivariate Many factors

Eng and Mak

(2003)

1995 158

Singapore

84 Ownership

structure, boardcomposition

OLS

regression

Lower managerial

ownership,governmentownership, outsidedirectors, lower debt

Cahan,Rahman andPerera (2005)

1998 or1999

216(From 17Countries)

Botosans(1997)index

Globaldiversification

OLSregression

Globaldiversification,number of analystssize

Ahmed(2005)

2002 100(non

financiallisted

companies)India

12 Industry type Descriptivestatistics

Level of reportingvoluntary informationis low but variabilityin disclosure is wideamong all sectors inindustry.

Ahmed(2005)

2002 100(non

financiallisted

companies)Bangladesh

148 Companys tradingcategory

Descriptivestatistics

Companys tradingcategory

Alsaeed(2005)

2003 40SaudiArabia

20 Size of firm, age,debt ratio,ownershipdispersion, profitmargin, return onequity, liquidityratio, industry type,audit firm size.

Multivariate Size of firm

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Hossain andTaylor(2006)

1992-1993

261Bangladesh,India, andPakistan

94 Size, profitability,debt/equity ratio,presence ofdebenture in debt,international linkof the audit firm,

industry type,subsidiary of amultinationalcompany.

Multivariate Size (total assets),subsidiary of amultinationalcompany(Bangladesh),Presence of debenture

in debt, industry type,Size (total sales),profitability (ROA)(India) and assets-in-place, size (totalassets), presence ofdebenture in debt(Pakistan)

A perusal of review of literature reveals that the association between the level or quality of

disclosure in corporate annual reports and corporate attributes has been examined in several

countries using a disclosure index approach. The disclosure indices constructed to measure

the quality and extent of disclosure varies considerably among the different studies, although

all share the basic idea of usefulness for the investment decision process. In studies either

voluntary or mandatory or both mandatory and voluntary information has been considered.

There are some researchers who have measured the extent of disclosure longitudinally to

determine whether quality of disclosure has improved over time. Most studies are country

specific, although there are studies, which have measured the extent of disclosure among

countries. Most disclosure studies have focused on only one year. The numbers of the

companies included in the samples in these studies have varied from 28 to 621. No disclosure

study other than Malone et al. (1993) was industry-specific. The number of corporate

attributes that were examined by researchers as a predictor of the level of disclosure has

ranged from 2 to 11.

The companies attribute which has proved most popular determinant of corporate disclosure

is corporate size as measured by assets, sales and market capitalization. The size of a

company has been regularly found to be significantly associated with the extent of disclosurein majority of the studies. This has been followed by profitability ratios, listing status and

auditor type. A little used variable is dividend pay out ratio. Some studies have used weighted

disclosure indices (weights were assigned by the researchers subjectively or weights were

based on preferences elicited by the researchers from surveys of a group or groups of users),

whereas other researchers used unweighted disclosure indices.

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Most of the researchers have used ordinary least square (OLS) regression to establish the

relationship between the extent of disclosure and company attributes, while other researchers

have used a stepwise (OLS) regression. However, Lang and lundholm (1993), Wallace, Naser

and Mora (1994) and Wallace and Naser (1995) used rank (OLS) regression to cater for the

monotonic behavior of disclosure indexes following a change in some independent variables.

The variety of methods used and results produced are related.

The changing feature of prior studies, such as the number of the firms included in the sample,

the type and the number of firm characteristics examined, the number of information items

that formed the basis of the set of disclosure indices as a dependent variable, the different

statistical methodologies used to analyze the data and the different settings (i.e. countries) of

the study, have jointly contributed to the mixed results from these studies (Wallace, Naser and

Mora, 1994, p. 43).

NEED AND OBJECTIVES OF THE STUDY

The foregoing review of literature reveals that some studies have been conducted to analyze

the various aspects of corporate disclosure practices in India (For details, see Singhvi, 1968;

Garg, 1986; Chander, 1992; Marston & Robson, 1997; Ahmed, 2005; and Hossain and

Taylor, 2006). Hardly any study has been carried out to explore the research on industry

specific disclosure practices in India. This has been taken as only one of the corporateattribute affecting the disclosure practices of firms in a few studies. There has been a maiden

study carried out by Malone et al. (1993) in USA to study the disclosure practices in oil and

gas industry. Hence, the need to carry out this study was felt.

The following are the objectives of this study:

1. To study the extent of disclosure in annual reports of selected companies of Indian

software industry.

2. To test the impact of various corporate attributes such as- age, size, profitability,

market capitalization, listing status, leverage, ownership pattern, residential status of a

company, and audit firm size on the reporting practices of the firms in software

industry.

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DATA BASE AND METHODOLOGY

The study has been carried out to analyze the disclosure practices of Indian software industry.

This industry has been chosen because India is considered to be the most favored destination

for offshore IT service delivery. Consequently, global players are also stepping up their

presence in India, not only to use the local delivery centers to service their offshore business

but also to target the fast-paced Indian IT services market. (Annual report of Satyam

Computers Ltd., 2005, p. 40). India is a premiere destination for off shoring IT services.

According to NASSCOMs Strategic Review report 2005, the total Indian IT enabled services

export market is projected to grow to $ 48 billion by fiscal 2009. According to the June 2004

Gartner Strategic Analysis Report, titled India Maintains Its Offshore Leading Position,

India will remain the dominant offshore service provider through 2008. According to this

report, no other nation will have a double-digit share of global offshore service revenue

(Annual report of WIPRO Ltd., 2005, p. 150). Directionally, the overall trends in Indian

software industrys services have remained unchanged in fiscal 2005 as compared to fiscal

2004 (Annual report of Satyam Computers Ltd., 2005, p.40).

Data Collection

The universe of study constitutes the companies representing software industry sector,

selected on the basis of market capitalization, as on March 31, 2005 from PROWESS, the

database of CMIE. There were 394 companies representing software industry, to which

following filters were applied:

1. The companies whose annual report for the year 2004-05 was not available were

eliminated.

2. The company whose information with regard to market capitalization as on March 31,

2005 was not available was also eliminated.

3. The companies, whose information with regard to any financial or non-financial

variable was not available, were also eliminated.

4. The companies with financial year-end September 31, 2005 were also eliminated.

Thus, as a result of these filters, out of 394 companies, a resultant sample size of 50

companies was selected and studied.

The annual reports of the selected companies for the year 2004-05 were the major source of

data collection. All the selected companies were requested to mail their annual reports. Out of

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which only 15 companies responded. The annual reports of some companies were

downloaded from the websites of respective companies. The annual reports of companies,

which were not available on their websites, were downloaded from website www.sebi.gov.in.

The annual reports of financial year 2004-05 were chosen because they were relatively more

recent and easier to obtain. The data related to the corporate attributes was taken from

PROWESS database of the Center for Monitoring Indian Economy (CMIE).

SPSS version 10.05 was used for application of various tests.

Disclosure Index Construction

A disclosure index is taken as a yardstick to measure the level of disclosure by the listed

firms. The construction of the disclosure index is based on the information that firms supply

in their annual financial reports to shareholders. Annual financial report is taken as one of the

best media for dissemination of useful information relevant for economic decision making to

investor. The quantum of disclosure in the annual reports of the Indian software industry has

been studied by framing a disclosure index comprising of 90 items of information. The items

of information for constructing an index of disclosure was selected on the basis of review of

literature on corporate disclosure, criteria laid down by ICAI for selecting the best presented

published accounts and scanning the annual reports of the companies which have been

awarded by ICAI for their best presented published accounts in 2005.

The unweighted index was used for the purpose of present study. The contents of each annual

report were compared to items listed in disclosure index and coded as 1 if disclosed or 0 if not

disclosed. For each item, a disclosure index was computed as the ratio of the actual score

given to the firm divided by maximum score. Empirical studies also provide substantial

evidence in favor of usage of unweighted disclosure index (For details see, Cooke, 1989;

1992; Tai et al., 1990; Chander, 1992; Ahmed and Nicholas, 1994; Hossain et al., 1994;

Wallace et al., 1994; Hossain et al., 1995; Chen and Jaggi, 2000; and Archambault and

Archambault, 2003). Ahmed and Courtis (1999, p.36) write that the approach based on

unweighted items has become the norm in annual report studies, because it reduces

subjectivity. The disclosure score for each company has been calculated as follows:

DISCLOSURE SCORE (%) = (Actual Disclosure/Total Possible Disclosure) x 100

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Model Development

In order to study the impact of various corporate attributes, Multiple Regression Analysis has

been used. The model employed to test the relationship between specific-related variables and

level of disclosure is presented below:

Y = 0 + 1X1 + 2 X2 + 3 X3 + 4 X4 + 5 X5 + 6 X6 + 7 X7 + 8 X8 +

Where Y = Disclosure score;

X1 = Age of a company (from year of incorporation till March 2005);

X2 = Listing status of a company (A group company=1, others=0);

X3 = Shareholding Pattern (Promoters share in shareholding);

X4 = Leverage (Debt to Equity ratio);

X5 = Size of a Company;

X6 = Profitability of a Company;X7 = Audit firm size ( Big 6 audit firms = 1 & Others= 0);

X8 = Residential status of company (Foreign=1, Indian=0);

= Slopes of the independent variables while 0 is a constant or thevalue of Y when all values of X are zero;

= The error term, normally distributed about a mean of 0

Hypotheses Development

1. Size of the company

There are several studies which have found a significant association between the size of the

company and the extent of disclosure in the corporate annual reports in both developed and

developing nations (Singhvi and Desai, 1971; Buzby, 1974; Chow and Wong-Boren, 1987;

Cooke, 1989; Wallace, Naser and Mora, 1994). However Stanga (1976) found that the size of

the company did not significantly explain an association with the level of disclosure and its

variability.

Larger companies may be hypothesized to disclose more information in their company annual

reports than smaller companies for a variety of reasons. Firstly, the cost of disseminating and

accumulating detailed information may be relatively low for the larger corporation than the

smaller corporations (Cerf, 1961; Singhvi & Desai, 1971; Buzby, 1975; and Firth, 1979) and

large companies have the resources and expertise to produce more information in their

companys annual reports (Ahmed & Nicholls, 1994; and Hossain & Adams, 1995) and

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hence, little extra cost may be incurred to increase disclosure. In addition, larger corporations

may collect more information to be used for their internal management systems.

Secondly, larger firms tend to go to the stock market for financing more often than those

smaller firms and as a result may disclose more information in their annual reports for their

own interest. Thirdly, Wallace and Naser (1995) state the impacts that large companies can

have on the economy can be considerable as these companies account for a significant

proportion of goods and services produced, consumption of raw materials and number of

people employed. As such, large companies are likely to come under the scrutiny of various

interested parties and hence tend to disclose adequate information in their annual reports.

Fourthly, smaller firms may feel that their information disclosure activities could endanger

their competitive oppositions with respect to other larger firms in their industry. As a result,

smaller companies may tend to disclose less information than large companies.

Fifthly, it has been suggested that the annual reports of large corporation are more likely to be

scrutinized by financial analysts than those of smaller firms and investors may interpret non-

disclosure as bad news, which could adversely affect firm value. So, larger firms may have an

incentive to disclose more information than smaller firms.

Sixthly, larger corporations are likely to have a higher level of internal reporting to keep

senior management informed and therefore are likely to have relevant information available

(Cerf, 1961; Buzby, 1975; and Owusu-Ansah, 1998). Cerf (1961), however, notes that the

accumulation of such information is no guarantee that it will be presented in the annual report.

Finally, Firth (1979) argued that large firms tend to be in the public eye and attract more

interest from government bodies, and thus may disclose more information to enhance their

reputation and public image on one hand and to allay public criticism and government

intervention in their affairs on the other hand. This is analogous to arguments concerning

political visibility put forward by Watts and Zimmerman (1986) although the latter authors

are concerned not with disclosure but the choice of accounting policies.

There are several measures of size available. In this study, sales turnover, total assets, and

market capitalization are used as surrogates of a companys size. The foregoing discussions

lead to development of the following hypothesis:

H1: The size of a company as measured by assets, or sales, or market capitalization has a

positive impact on its disclosure score.

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2. Profitability of a company

Profitability has also been used by number of researcher as an explanatory variable for

differences in disclosure levels. Companies having higher profitability may disclose more

information in their corporate annual reports than the companies with lower profitability (or

losses) for a number of reasons. Firstly, if the profitability of a company is high, management

may disclose more detailed information in their corporate annual reports in order to

experience the comfort of communicating it, as it is a good news. On the other hand, if

profitability is low, management may disclose less information in order to cover up the

reasons for losses or lower profits. However, Cerf (1961) postulates that a company that is

less profitable may disclose more information to explain the reasons for the lower

profitability. The companies are interested in keeping the market informed to avoid the under

valuation of their shares. Secondly, for profitable companies, if the rate of return on

investment is more than the industry average, the management of a company has an incentive

to communicate more information, which is favorable to it as the basis of explanation of good

news and is likely to disclose more information in their corporate annual reports as a result.

Wallace and Naser (1995) argue that a profitable company is more likely to signal its good

performance to the market by disclosing more information in its annual report.

The empirical studies, however found mixed results. Among these researchers, Singhvi

(1967); Singhvi and Desai (1971); Wallace (1987); Wallace, Mora and Naser (1994); Wallace

and Naser (1995); and Raffournier (1995); found a positive association between profitability

and the extent of disclosure whereas Belkaoui and Kahl (1978) found a negative association

between variables. Spero (1979) found that there existed a positive association for French

companies and no significant association for the British and Swedish companies in that study.

Others, (McNally et al., 1982; Raffournier, 1995; and Owusu-Ansah, 1998) found no

significant relationship.

Researchers have used a number of measures to determine the associations between

profitability and disclosure levels. In the present study, return on assets, returns on sales,

return on net worth, and return on capital employed have been used as a determinant of

measuring the association between profitability and level of disclosure. The following specific

hypotheses have been formulated and tested:

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H2: The profitability of a company as measured by ROA, or ROS, or ROCE, or RONW has a

positive impact on its disclosure score.

3. Leverage of a company

Several studies investigated the relationship between leverage (book value of debt to

shareholders equity or book value of debt to total assets) and disclosure, with the general

view that companies with a higher level of leverage disclose more information. The general

agency relationship can also be applied to the relationship between managers and debt

providers. Debt providers may be concerned about possible wealth transfers to shareholders;

that is, managers are more likely to favor the interests of shareholders to the detriments of the

providers of debt (Francis & Wilson, 1988). Ahmed (1996) suggests that the agency costs of

debt are higher for companies with more debt in their capital structure and an increased level

of disclosure may reduce these costs. While increased disclosure may not necessarily be part

of a contractual agreement. Wallace et al., (1994) opine that a company with a higher gearing

level has a greater obligation to satisfy the needs of its long-term creditors for information and

may therefore provide more information in its annual reports than a more lowly geared

company. However, the empirical evidence has generally not supported this theory (e.g.

Chow & Wong-Boren, 1987; Wallace et al., 1994; Hossain & Adams, 1995; Raffournier,

1995; Wallace & Naser, 1995). A possible explanation for these findings might be that debt

holders are in a position to demand additional information other than that contained in the

annual report and are therefore not as reliant on the disclosures made in the annual report. As

these previous studies have considered different countries and utilized differing methods,

there is a value in considering leverage in this study. Therefore, the following hypothesis is

tested in this study:

H3: The leverage of a company has a positive impact on its disclosure score.

The Debt to Total Equity has been used as a surrogate to measure the leverage of a company

in the present study.

4. Audit Firm Size

A number of studies test the relationship between audit firm size and the level of disclosure.

Large audit firms are widely scattered across the world, while small audit firms operate

domestically. The classification of audit firms into two groups draws on the assumption that

large firms have more concern for their reputation and, therefore, are more willing to

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associate with firms that disclose more information in their published financial reports. On the

other hand, small audit firms do not possess the power to influence the disclosure practices of

their clients. Rather, they attempt to meet the needs of their clients in order to retain them

(Firth, 1979; Wallace and Naser, 1995). Empirical evidence on the relationship between audit

firm size and the disclosure extent is rather ambiguous. Naser et al. (2002) observed a

positively significant relationship. Wallace et al. (1994) found it positive but insignificant. In

contrast, Wallace and Naser (1995) noticed a significantly negative relationship between the

disclosure level and firm size. Therefore, the following hypothesis has been formulated and

tested in this study:

H4: The audit firm size of a company has a positive impact on its disclosure score.

Audit firms of 394 companies from software industry (PROWESS) were divided into large

(Big 6: Price Waterhouse, A F Furguson, S B Bilimoria, S R Batliboi, Delloitte, Haskins and

Sells, B S R & Co.,) and small firms (other than above Big 6). This variable has been used as

a dummy. The companies being audited by Big 6 audit firms were assigned 1 and others 0.

5. Age of a Firm

Camferrman and Cooke (2002) identified a number of new variables, such as the age of a

company to be investigated by future studies. The rationale for selecting this variable lies in

the possibility that old firms might have improved their financial reporting practices over

time. The older the firm, the scope for disclosure also broadens. It helps in understanding

variations among disclosure practices of different firms in same industry. Therefore, the

above arguments led to the formulation of following hypotheses:

H5: The age of a firm has a positive impact on its disclosure score.

The age of a firm is computed from the year of its incorporation till March 31, 2005.

6. Residential status of a firm

Subsidiaries of multinational corporations operating in developing countries are expected to

disclose more information and observe higher standards of reporting for a number of reasons;

Firstly, they have to comply with the regulations of not only their host country but also the

parent company where substantially higher standards of reporting and accounting are

maintained. Secondly, they are usually equipped with more advanced accounting software

tools, efficient audit staff, competent and efficient management and staff, and so, have the

potential to disclose more information without any incremental processing costs. Thirdly, they

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are under closer scrutiny of various political and pressure groups within the host country that

view them as sources of economic exploitation and agents of imperialist power (Ahmed and

Nicholls, 1994). Hence, they have an incentive to disclose more information in order to avert

any pressure for excessive control for exploitation.

Wallace (1987) and Ahmed and Nicholls (1994) used multinational company influence as an

explanatory variable in developing their models and the latter found it to be the most

significant variable explaining disclosure levels. Therefore, the following hypothesis has been

formulated and tested in this study:

H6: The residential status of a company has a positive impact on its disclosure score.

The influence of residential status is operationalized by means of dummy variable, with 1 for

multinational companies and 0 for domestic companies.

7. Listing Status of a firm

The listing status of a firm also influences the disclosure level of that firm. Every Indian

company listed on a stock exchange has to comply with its listing agreement. The companies

whose shares are actively traded have always been scrutinized sharply by the market as a

whole and investors in particular. Empirical evidence also suggests a significant association

between disclosure level and the listing status of a firm (Singhvi and Desai, 1971; Cooke,

1989; Cooke, 1992; Malone et al., 1993; and Wallace et al., 1994). So, the above discussions

led to the formulation and testing of the following hypothesis:

H7: The listing status of a firm has a positive impact on its disclosure score.

The companies trading on stock exchanges in India have been categorized as category A,

B1, B2, S, and T. The impact of listing status of a firm on extent of disclosure level has

been examined by introducing dummy variable, with 1 if firm falls under A category and 0

otherwise.

8. Shareholding Pattern

This variable has been selected on the ground that the extent of disclosure may differ among

firms in response to the proportion of shareholders interest. Shareholding pattern here means

the percentage of common shares held by promoters. Fama and Jensen (1983) theorized that a

low concentration of ownership causes conflict of interest between the principal

(shareholders) and the agent (management). To alleviate the potential for higher agency costs,

more disclosure of information is expected. McKinnon and Dalimunthe (1993) empirically

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examined the nature of relation and found support for this idea in a study covering some

Australian companies. So, the following hypothesis has been formulated and tested:

H8: The promoters interest in the shareholding of a company has a positive impact on its

disclosure score.

RESULTS AND DISCUSSIONS

The results and discussions have been divided into two parts. In the first part, the extent of

disclosure of companies in the software industry has been analyzed. The impact of corporate

attributes on corporate disclosure has been examined in the second part.

Part I) Extent of Corporate Disclosure of the Companies in the Software Industry

The extent of disclosure of companies in the software industry has been examined with the

help of disclosure score. The percentage of disclosure score has been computed for every

selected company from the software industry. The range of disclosure level of the companies

in the software industry varies between 32.2% and 71.1%. The picture of the extent of

corporate disclosure of companies in the software industry is highlighted in the table 2.

Table 2 examines that the highest level of the disclosure is maintained by Wipro Technologies

Ltd. And Infosys Ltd. (71.1%), followed by Rolta India, Info Tech Enterprises (67.8%) and I-

Flex solutions Ltd. (65.6%). The companies namely, Silicon Valley Info Tech Ltd (32.2%),

followed by Orient Information Technologies Ltd. (37.8%), T-Spiritual Ltd, Micro-Tech

(India) Ltd., I-Gate Global Solutions Ltd. (38.9%) and Pentamedia Graphics Ltd (41.11%) areat the lowest level of corporate disclosure ranks.

The variation in the disclosure level may be due to the fact that a few of the companies from

the Indian software industry are known for their wealth creation. They try to disclose the

information even beyond the level required by statutory provisions of Indian law. These

companies have large overseas operations and their shares are listed on the international stock

exchanges. So, in order to meet the regulatory requirements of listing agreements of other

nations, they have to widen the scope of disclosure level. That is why the level of disclosing

voluntary information is also high in the case of companies like Wipro Ltd., Satyam

Computers Ltd. and Infosys Ltd.

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Table 2 Extent of corporate disclosure of 50 Indian companies in Software Industry

Sr.

No.

Name of Company Disclosure Score

(%)

Sr.

No.

Name of Company Disclosure

Score (%)

1 Micro Technologies (India) Ltd. 38.89 2 CMC ltd 47.78

3 P S I Data Systems Ltd. 51.11 4 Sonata Software Ltd 51.11

5 Orient Information Technology Ltd. 37.78 6 Tata Consultancy ServicesLtd

53.33

7 Geodesic Information Systems Ltd. 53.33 8 I-Gate Global SolutionsLtd

38.89

9 B S E L Infrastructure Realty Ltd. 48.89 10 N I I T Ltd 51.11

11 Helios & Matheson InformationTechnology Ltd.

51.11 12 Rolta India Ltd 67.78

13 Kale Consultants Ltd. 50 14 Wipro Ltd 71.11

15 Four Soft Ltd. 50 16 Blue Star Infotech Ltd 53.33

17 N I I T Technologies Ltd. 47.78 18 Cranes Software Intl. Ltd 48.89

19 Nucleus Software Exports Ltd. 57.78 20 Visualsoft TechnologiesLtd

45.56

21 Cambridge Solutions Ltd. 50 22 Financial Technologies(India) Ltd

46.67

23 G T L Ltd. 48.89 24 Infotech Enterprises Ltd 67.78

25 Hinduja T M T Ltd. 58.89 26 Patni Computers Ltd 60

27 Datamatics Technologies Ltd. 48.89 28 Geometric SoftwareSolutions Co. Ltd

52.22

29 Megasoft Ltd. 45.56 30 T-Spiritual World Ltd. 38.89

31 Aztec Software & TechnologyServices Ltd.

50 32 Mphasis BFL Ltd 58.89

33 Spanco Telesystems & SolutionsLtd.

50 34 Zensar Technologies Ltd 50

35 H C L Technologies Ltd. 53.33 36 Ramco System Ltd 43.33

37 I-Flex Solutions Ltd. 65.56 38 Subex System Ltd 57.78

39 Polaris Software Lab Ltd. 58.89 40 Satyam Computers Ltd 62.22

41 Pentamedia Graphics Ltd. 41.11 42 Infosys Ltd 71.1143 Aftek Infosys Ltd 48.89 44 Hexaware Technologies

Ltd48.89

45 Aptech Worldwide Ltd 50 46 Flextronic SoftwareSystems Ltd

62.22

47 Silicon Valley Infotech Ltd. 32.22 48 Tata Elxci Ltd 47.78

49 Mascon Global Ltd 45.56 50 Tata Infotech Ltd 57.78

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Part II) Impact of the Corporate Attributes on the Corporate Disclosure

Since, wide variations have been observed in the disclosure score of the selected companies

from the Indian software industry. So, it becomes imperative to know the reasons of such

variations. The reasons might be company specific. So an attempt has been made to find the

effect of corporate specific variable on the disclosure score.

Assessing the validity of the model

Before proceeding to the results of regression analysis, it was instructive to check the

existence of multicollinearity among the explanatory independent variables. Multicollinearity

or collinearity, the situation where two or more of the independent variables are highly

correlated, can have damaging effects on the results of multiple regression. The correlation

matrix is a powerful tool for getting a rough idea of the relationship between predictors. The

suggested rule of thumb is that, if the pair-wise or zero-order correlation coefficient between

two regressors is high, say , in excess of 0.8, then multicollinearity is a serious problem.

(Gujarati, 2006, p. 359). The solution to it is to drop that variable and then run regression

analysis with rest of the variables. Another way to check the multicollinearity is to compute

the average VIF (Variance inflation factor). As a rule of thumb, if the VIF of a variable

exceeds 10, which will happen if R2 exceeds 0.80, that variable is said to be highly collinear

(Gujarati, 2006, p. 362).

Correlation Analysis

To examine the correlation between the dependent and independent variables and with the

dependent variables, Pearson product moment correlation (r) was computed. A correlation

matrix of all the values of r for the explanatory variables along with dependent variables was

constructed and is shown in table 3:

TABLE 3 Correlation Matrix

Independent variables Age ListingStatus

PromoterShare

MarketCap

Leverage Assets

ROS AuditFirm

ResidentialStatus

DIS

Age 1.00Listing status .316* 1.00

Promoter share .310* .102 1.00

Market cap .291* .25 .015 1.00

Leverage .407** .301* .407** .256 1.00

Assets -.113 .156 -.146 .124 -.117 1.00

ROS .264 .246 .040 .194 .125 -.234 1.00

Audit firm size .521** .409** .534** .183 .901** -.147 .152 1.00

Residential .630** .140 .161 .354* .269 -.033 .013 .306* 1.00

DIS -.05 -.172 -.134 -.007 -.106 -.109 -.04 -.100 .101 1.00

*, ** and # : significant at 1%, 5% level and 10% level (respectively).

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Table 3 shows that correlation exists between age, listing status, market capitalization,

residential status, audit firm, leverage, and shareholding pattern at 1% and 5% level.

Collinearity is an issue in case of leverage and audit firm size.

Regression Analysis

A regression analysis has been run in two stages. Firstly, multiple regression analysis was run,

wherein no concluding results could be found out or in other words, no variable except audit

firm size could significantly explain variations in the disclosure level. Afterwards, in the

second stage, step-wise regression analysis was run, wherein few variables were dropped

from the model and a combination of various variables were applied to see the effect of these

combinations on the disclosure level.

Multiple Regression AnalysisThe results from the multiple regression analysis have been presented in Table 4. Three

separate determinants of firm size (sales, assets, and market capitalization) as well as four

different measures of profitability (ROS, ROA, ROCE, and RONW) were used. Each

surrogate to represent size and profitability was used only once in a model. This led to the

creation of twelve regression equations, the results of which has been presented in table 4:

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TABLE 4 REGRESSION RESULTS (MULTIVARIATE ANALYSIS)

*, **, and #: significant at 1%, 5% level and 10% level (respectively).Constan

t

Age Listing Promote

r

Lev Mkt

Cap

Asset Sales ROA ROS ROC

E

RONW AUD RES R 2 Adj.

R2

F

(Sig)

DW

Dis 15.025 .91 .75 .24 -.18 X x 1.37 1.239 X x x 4.30* -2.8 54.7 44.5 0.000 1.997

Dis 14.915 1.50 .97 .00 -.59 X x .47 x 1.70# x x 4.50* -.28 52.8 43.6 0.000 2.041

Dis 16.193 .95 .96 -.072 -.28 X x 1.32 x X .856 x 4.68* -.43 55.1 46.4 0.000 2.069

Dis 15.093 1.61 1.01 -.128 -.43 X x .14 x X X 1.136 4.54* -.02 53.7 44.7 0.000 2.037

Dis 15.973 1.13 .49 .057 -.36 X 1.32 x 1.065 X x x 4.40* -.33 54.5 45.6 0.000 2.074

Dis 15.968 1.10 .461 .054 -.50 X 1.34 x x 1.67# x x 4.39* -.04 56.7 45.7 0.000 2.072

Dis 16.668 .648 .50 .003 -.20 X 1.82# x x X .822 x 4.60* -.47 55 48.3 0.000 2.082

Dis 16.107 1.17 .49 -.034 -.39 X 1.11 x x X X .789 4.39* -.26 52.61 46.2 0.000 2.07

Dis 14.808 1.71# 1.14 -.04 -.36 .142 x x 1.437 X x x 4.62* -.25 52.6 43.3 0.000 2.033

Dis 14.807 1.68# 1.11 -.033 -.59 .166 x x x 1.65# X x 4.60* -.25 52.6 43.3 0.000 2.033

Dis 16.032 1.17 1.13 -.079 -.35 1.033 x x x X 1.012 x 4.75* -.43 54.4 45.5 0.000 2.079

Dis 15.006 1.77# 1.14 -.156 -.39 -.214 x x x X X 1.004 4.60* -.13 53.7 44.7 0.000 2.028


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Table 4 reveals that for all models audit firm size was found to be significant at 1% level.

ROS was significant at 10% level when applied in combination with all surrogates of size.

Other profitability surrogates could not significantly explain variations in the disclosure level.

The age of a firm was found to be significant at 10% level in explaining variations in

disclosure, when applied in combination with market capitalization, ROA, ROS and RONW,

the surrogate of size and profitability. Other variables could not find any place in explaining

significant variations in the disclosure level. So, out of 12 models, the model, which is

satisfying validity requirements and having improved adjusted R2 has been chosen and

selected as a valid model. The model with combination of Age, Listing status, promoter share,

leverage, assets size, ROCE (measure of profitability), audit firm size and residential status

has 0.55 (Adjusted R

2

), F value is significant at 0.00 level of significance and DW is 2.082.But in this model, only audit firm size and firm with large asset size is found to be significant.

The firms with large assets size and being audited by big six audit firms have more extent of

disclosure. These are significant at 10% and 1% level of significance. Other variables were

found to be insignificant.

Step-wise Regression Analysis

The step-wise regression was applied by eliminating different independent variables having

insignificant effect on disclosure. The problem of multicollinearity between independent

variables namely, leverages and audit firm size was resolved by eliminating leverage (the

insignificant variable). A stepwise regression model separately applied showed that all size

measures are significantly influencing the level of disclosure. Size measured in terms of assets

is significant at 1% and other two measures at 5%. Of the four performance measures, only

ROS was found to be significant at 5% level of significance (see table 5). Rest of the specific

variables other than audit firm size could not statistically significantly influence the extent of

disclosure and hence have been excluded.


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TABLE 5 STEPWISE REGRESSION MODEL

*, **, and #: significant at 1%, 5% level and 10% level (respectively).

All the three models were found to be valid. But as the Adjusted R2 is improved in the first

step-wise regression equation, i.e. 0.528, so, this model has been chosen. The results of

stepwise regression analysis reveal that the F-ratio is significant at 5% level of significance.

The results statistically support the significance of the model. R2 (.547), which is a respectable

result, implies that independent variables explain 54.7 percent variance in disclosure score.

The multicollinearity doesnt exist if average VIF is 1 or is near about 1. The problem of

multicollinearity doesnt exist in the model, being satisfied by average VIF, which is

approximately 1. Additionally, to test the assumption of independent errors (autocorrelation),

the Durbin-Watson statistic was used. The value of this statistic closer to 2 is considered as

better, and for this data the value is 2.063, which is very close to 2. Hence, the assumption has

almost been accomplished. In sum, the diagnostics indicate the model to be valid and reliable.Testing the Hypothesis

The results from the step-wise regression analysis shows that firms with large assets size are

more in the eyes of general public and are required to disclose more information. Although in

the table 5, all size measures found to be significant in explaining the extent of disclosure, but

the total assets explain more variation in the disclosure practices of the firms in software

industry. So, H1 is accepted in favor of the hypothesis that all the surrogates of the size of a

company have a positive impact on their disclosure score.

Out of profitability measures, ROS explains more significant variations in disclosure than

firms with more ROA, RONW, and ROCE. So, H 2 is accepted in favor of the hypothesis that

the profitability of a company as measured by ROS has a positive impact on the disclosure

score. And it is rejected for other surrogates of the profitability. The companies in the

software industry have more extent of disclosure as these are globally recognized for their aim

DependentVariable

Constant

Mkt Cap Asset Sales ROS AUD R 2 Adj.R2

F(Sig)

Avg. VIF DW

Disclosure 30.654 x 3.143* X 2.083** 5.102* .

547

.

528

0.043 1.087 2.063

Disclosure 29.904 x x 2.527** 2.208** 5.154* .527

.496

0.000 1.074 2.002

Disclosure 29.374 2.096** x X 2.187** 5.270* .509

.477

0.042 1.064 1.995

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of wealth maximization. As wealth maximization depends on the market value of the share,

which in turn depends on the cost of equity and dividend policy of the company, which

depends on the profitability of a concern. All profitability measures found to be positively

associated with disclosure score. Hence, the wealth maximization objective is being achieved

by the companies in the software industry. But ROS found to have statistically positive

relationship with the disclosure level. It helps the management, providing insight into how

much profit is being produced per unit of sales. It indicates that the software industry is

growing more efficiently. So, the results move in hypothesized direction

The firms being audited by big six-audit firm, who are having international links too, disclose

more extent of information than others. H4 is accepted in favor of positive impact of audit firm

size on the disclosure score.

The residential status of a firm, leverage of a company has negative association (though

insignificant) with the level of disclosure. It shows that the Indian companies have to comply

with the legal provisions of Indian legislation and hence have more mandatory disclosure than

foreign companies. The companies having more debt content have policy of disclosing only

mandatory information because the companies disclose to the maximum extent only when

they have more share of public in the share capital. So, all other variables dont explain

significant variations in the level of disclosure except audit firm size.

Table 5 shows that the other variables like age of a company, listing status of firms and

shareholding pattern have positive association with extent of disclosure though not

significant. It explains that companies listed in A category at BSE, disclose more extent of

information. It appears that all the companies in software industry are young in age. So, age

did not emerge as a significant factor influencing the level of disclosure.

The companies in which the promoters have high stake in capital structure have less extent of

disclosure. Wallace et al. (1994) observed no significant association between shareholding

pattern and the level of disclosure. The results are evidenced by literature and are in

hypothesized direction.

So all hypothesis except H1, H2, H4 are rejected.

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CONCLUSION

This study provides an evidence of the extent of corporate disclosure in Indian software

industry. The analysis reveals that the extent of disclosure within the software industry varies

within 32.2% to 71.1% (approximately) for period of study. It implies that though all the

companies disclose mandatory information as required by law, but at the same time, a large

number of companies disclose more than required by legal provisions. These companies are

globally recognized and have overseas operations too. These companies are also known for

maximization of the shareholders wealth. That is why these companies try to be more

transparent in the eyes of domestic as well as foreign investors and have better disclosure

level.

It has also been observed that the extent of disclosure is influenced by size (as measured by

total assets), profitability (as measured by return on sales) and the audit firm size of acompany. The companies with large assets size, higher profitability and audited by big audit

firms have tendencies to be more transparent and hence disclose more information. However

age of a company, shareholding pattern, listing status, leverage and residential status dont

significantly influence the level of disclosure.

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