38. the relationship between disclosure and firm characteristics in developing

1

THE RELATIONSHIP BETWEEN DISCLOSURE AND FIRM CHARACTERISTICS IN DEVELOPING COUNTRIES: A

COMPARATIVE STUDY OF BANGLADESH, INDIA AND PAKISTAN

2

THE RELATIONSHIP BETWEEN DISCLOSURE AND FIRM

CHARACTERISTICS IN DEVELOPING COUNTRIES: A COMPARATIVE STUDY OF BANGLADESH, INDIA AND

PAKISTAN

Dr. Monirul Alam Hossain (Rajshahi University) and Peter J. Taylor (Liverpool University)*

Abstract The study is an attempt to examine empirically the association between a number of corporate

attributes and levels of disclosure in corporate annual reports of listed non-financial companies

in three developing countries, India, Pakistan and Bangladesh. A disclosure index comprising

94 items of information which are expected to be disclosed in corporate annual reports in the

sample companies has been developed. Both weighted and unweighted disclosure indices were

applied to the corporate annual reports for a sample of 78 Bangladeshi companies, 80 Indian

companies and 103 Pakistani companies for the 1992-1993. The association between the extent

of disclosure and various corporate characteristics was examined using multiple linear

regression models. It was hypothesised that for the sample companies in these three developing

countries, corporate variables reflecting size (assets and sales), profitability (rate of return on

assets and net profit margin), debt-equity ratio, presence of debenture in debt, international link

of the audit farm, industry type, subsidiary of a multinational company would be positively

associated with the extent of disclosure. A variable for assets-in-place was hypothesised to be

inversely related to the extent of disclosure. It was found for the Bangladeshi companies that

size (total assets) and subsidiary of a multinational company were significantly associated with

the extent of disclosure. In the case of Pakistani companies, the results showed that assets-in-

place, size (total assets) and presence of debentures in debt structure were significantly

associated with the extent of disclosure. The results for Indian companies, showed that extent of

disclosure was significantly related to presence of debentures in debt structure, industry type,

size (sales) and rate of return on total assets. No significant differences were found for the

weighted disclosure index and unweighted disclosure index, The results were consistent with

some previous studies whilst conflicting with others. Assets-in-place is a new explanatory

variable in relation to developing country disclosure index studies and a close and inverse

relationship between the variables and the extent of disclosure was observed for companies in

Pakistan. Further work is underway to refine this variable. In addition, this is the first study on

disclosure data for developing countries to examine a debenture variable which seeks to proxy

for a relationship between access to public debt and the extent of disclosure.

* Correspondence Address:

Dr. Monirul Alam Hossain, Assistant Professor, Department of Accounting, Rajshahi University

Rajshahi-6205, Bangladesh. Email: [email protected]

3

The Relationship between Disclosure and Firm

Characteristics in Developing Countries: A Comparative Study of Bangladesh, India and Pakistan

1.1 Introduction

It is well known that financial reporting practices of a country depend on several factors. The legal, economic, political,

cultural and historical background forms the basis of the financial reporting environment of a country. The extent of

information disclosure, its adequacy, relevance and reliability are important characteristics of financial reporting

practices prevalent in a country. Financial reporting is not an end itself but is intended to provide information that is

used in making reasoned choices among alternative uses of scarce resources in the conduct of business and economic

activities. Some users of financial reports have a direct interest in the firm, while others have an indirect interest. Those

who are directly interested in financial reports are owners, managers, creditors, present and prospective investors,

customers and the government. Indirect users of financial reports include financial analysts, trade unions, researchers and

the general public.

Disclosure of information in corporate annual reports is an area of research in both developed and developing countries.

There is a large accounting literature relating to studies which have used disclosure indexes to measure the extent of

disclosure made by the companies in corporate annual reports. Disclosure indexes are based upon extensive lists of

selected items of accounting information which may be disclosed in corporate annual reports and seek to measure the

extent of disclosure by using numerical weights on items of accounting information. Disclosure indexes may be

unweighted (with items of information valued 0 or 1 for non-disclosure or disclosure respectively) or weighted (where

various weights are applied to reflect perceptions of the importance of items of information which are disclosed).

This paper examines empirically the relationship between selected company characteristics and the level of

disclosure of accounting information of the listed non-financial companies in three developing countries,

Bangladesh, India and Pakistan. In order to measure the extent of disclosure made by sample companies, a

disclosure index was developed containing a list of mandatory and voluntary items of information. Several

hypotheses and company characteristics were derived from similar previous studies1. The association between the

extent of disclosure and these company characteristics was then measured using multiple regression models. In

some previous studies it was found that there was no significant relationship between the level of disclosure and

debt-equity ratio (Chow and Wong-Boren, 1987; Ahmed and Nicholls, 1994 and Hossain et al., 1994). A new

variable, presence of debentures in company debt structures has been developed which might be used addition to the

debt-equity ratio to assess the potential impact of access to public debt markets on disclosure.

1 The hypotheses developed by researchers in disclosure studies are derived from the positive

accounting literature (see Inchausti, 1997 and other sources).

4

1.2 Rationale of the Study

Appropriate disclosure of financial data relevant to users is a key issue in financial reporting (Prodhan, 1986). In recent

years, research into accounting practices in emerging economies has received more attention by researchers. These

researchers have emphasised the role of the accounting profession, accounting education and financial reporting

practices in the developing countries in research and there are few studies regarding disclosure of information made by

the companies in corporate financial reports in developing countries. Very few such studies can be found in the context

of South Asian countries.

The core of this study is financial disclosure in Bangladesh, India and Pakistan. A comparative study of financial

disclosure requirements between countries is useful if all countries under study follow similar financial reporting

practices. For example, the disclosure requirements of a country can be comparable with another country if the former

adopts the procedures which the latter country follows and vice versa. However, the situation is very rare in practice.

Nevertheless, if the origin of laws and regulations governing financial reporting are the (in this case British Companies

Acts ) and the social, economic and political characteristics of the countries differ to some extent, then comparison is

possible. The three countries studied are developing, politically similar (ruled by democratic governments),and are

broadly economically comparable (economies mostly characterised by private ownership of property). The accounting

education, accounting profession and the financial and industrial institutions of the sample countries are also quite

similar.

The systems of financial reporting and auditing in Bangladesh, India and Pakistan are also similar. Before 1947, India,

Pakistan and Bangladesh had been under British rule for approximately 200 years and the Indian Companies Act, 1913

was the basis for the financial reporting requirements in all three countries. The three countries followed the same

disclosure regulations for corporate annual reports until 1956. Bangladesh was a part of Pakistan until 1971 before its

independence and both the countries adopted the Indian Companies Act, 1913. India replaced its Companies Act, 1913

by the Indian Companies Act, 1956, Pakistan by the Companies Ordinance, 1984 and Bangladesh by the Companies

Act, 1994. Consequently, the Indian Companies Act, 1956, the Companies Act, 1994 of Bangladesh, and the Companies

Ordinance, 1984 of Pakistan are the main bases for corporate disclosure requirements in these countries.2 These acts or

ordinances were themselves based on various British Companies Acts. In the case of Bangladesh and Pakistan there are

Securities and Exchange Rules for companies listed on stock exchanges in those countries which require more disclosure

requirements than the provisions laid down in the respective company act or companies ordinance. In the case of India,

the Securities and Exchange (Board of India) Act 1992 does not require any more disclosure requirements than the

provisions laid down in the Companies Act, 1956. In addition to these regulations, the accounting professions of the

three countries have adopted accounting standards which are expected to be followed by companies in each country in

2 As this paper considers the annual reports of the companies for the year 1992-93, the corporate

annual reports of Bangladesh were prepared as per the provisions laid down in the Companies

Act, 1913.

5

preparing their financial statements. Thus, the laws and regulations of the three countries are not identical and as a result,

the level of disclosure of financial information is expected to differ.

It has been said that the experience of one developing country may help to clarify the nature of corporate financial

reporting problems for other developing countries (Wallace, 1988; p. 352). The use of disclosure indexes to carry out

international comparisons of corporate disclosure has been relatively neglected. No comparative study has been

undertaken which focuses on the disclosure of financial information of companies in developing countries using a

disclosure index approach. Only four such studies have used a disclosure index approach to compare disclosure levels

among companies in different developed countries (Barrett, 1977; Choi,1973; Spero,1979 and Khal and Belkaoui, 1981).

This paper seeks to examine the relationship between the extent of disclosure and twelve corporate attributes compared

across three developing countries.

1.3 Literature Review

The association between the level or quality of disclosure in corporate financial reports and corporate attributes has

been examined in several countries using a disclosure index approach. Such studies undertaken in developed include

those of Cerf (1971), Singhvi (1967), Singhvi and Desai (1971), Buzby (1972, 1974 and 1975), Choi (1973 and

1974), Barret (1975, 1976 and 1977), Stanga (1976, Belkaoui and Kahl (1978), Spero (1979), Firth (1978 and 1979),

Belkaoui and Kahl (1978), Kahl and Belkaoui (1981), McNally et al. (1982), Cooke (1989, 1991 and 1992),

Malone, Fries and Jones (1993), Wallace, Naser and Mora (1994), Raffournier (1995) and Inchausti (1997).

Disclosure studies in developing countries include those of Chow and Wong-Boren (1987), Wallace (1987 and

1988), Benjamin et al. (1990), Ahmed and Nicholls (1994), and Hossain et al (1994), Wallace and Naser (1995).

The disclosure indexes constructed to measure the quality and extent of disclosure vary considerably among the

different studies, although all share the basic idea of usefulness of information for the investment decision process

(Inchausti, 1997). In some studies only compulsory or mandatory information is considered (Ahmed and Nicholls,

1994; Wallace, Naser Mora, 1994 and Wallace and Naser, 1985), while there are studies which have considered only

voluntary information (Firth, 1979; Chow and Wong-Boren, 1987; Spero, 1979; Hossain et al, 1994 and

Raffournier, 1995). In some studies researchers have included both mandatory and voluntary information in their

disclosure indexes (Singhvi, 1967; Singhvi and Desai, 1971, Choi, 1973, Barrett, 1976; Wallace, 1987; Cooke, 1989

and Inchausti, 1997). There are researchers who have measured the extent of disclosure longitudinally to determine

whether quality of disclosure has improved over time (Barrett, 1976; Spero, 1979 and Inchausti, 1997). The number

of items included in the disclosure index vary from researcher to researcher. Most studies are country specific, although

there are studies which have measured the extent of disclosure among countries (Singhvi, 1967; Choi, 1973; Barrett,

1976; Spero, 1979 and Kahl and Belkaoui, 1981). Most disclosure studies have focused on only one year. The

number of the companies included in the samples in these studies have varied from 14 to 527. No disclosure study

6

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.

Amongst these researchers who have tried to establish the relationship between corporate attributes and the extent of

disclosure in corporate annual reports, some have found corporate attributes which have shown significant

relationships with the level of disclosure while other researchers have found no such relationships. The company

characteristics which has proved most popular variable is corporate size (proxied by assets, sales and market

capitalization) as predictor of the extent of disclosure and has been regularly found to be significantly associated

with the extent of disclosure. 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 indexes (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 indexes.

Most researchers have used multiple ordinary least square (OLS) regression to establish the relationship between the

extent of disclosure and company variables, 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 behaviour of disclosure indexes following a change in some

independent variable. The variety of methods used and results produced are related:

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

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

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

statistical methodologies used to analyse 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).

Appendix A identifies the corporate attributes used by researchers and indicates what relationships have been

established with respect to disclosure in a particular country or countries.

1.4 The Disclosure Index

1.4.1 Information Items Included in the Disclosure Index

The quality of financial reporting in a country depends on the legal requirements governing disclosure together with

professional recommendations which may have a varying degree of effectiveness depending on the influence of the

professional bodies concerned (Marston, 1986). In addition, national and international accounting standards and

stock exchange requirements may have an impact on the disclosure of information in corporate annual reports.

Companies usually disclose information in a number of ways, such as through annual report and accounts, interim

and quarterly reports, prospectus, employee reports and announcements to the stock exchange. It may be strongly

argued that the most important medium of external financial disclosure is the corporate annual report.

7

The major task of the present research is to develop a suitable disclosure index comprising items

of information that are expected to be disclosed in corporate annual report from the view point of

developing countries. The resulting disclosure index has been used for the evaluation of

disclosure of listed non-financial companies in the three developing countries being studied.

Marston and Shrieves (1991) are of the opinion that the usefulness of the disclosure index as a

measure of disclosure is dependent on the selection of items to be included in the index. The

selection of items included in the disclosure index is a major task in the construction of any

disclosure index (Marston and Shrieves, 1991). There is no generally accepted theory to predict

users information needs and there is an absence of an appropriate generally accepted model for

the selection of the items of information to be included in a disclosure index to judge the quality

of information of a corporate annual report. As one notable researcher observes to the extent

that research foci amongst researchers, there is no theory on item selection (Wallace, 1988; p.

354). An item of information may be of great importance to a particular interested user group

while it may have little importance to other user groups. Most of the previous studies have

included items of information of interest to a particular group. In the present study, items of

information have been included keeping in mind their relevance to a broad range of users. In

most previous studies, the number of items selected were relatively small. In this study the

disclosure index has been developed by extensively following Wallaces (1987) disclosure index

which included a wide range of major disclosure items that might be found in the corporate

annual report3 which is not directed at a particular group of users in the context of general

purpose financial reports that should serve the needs of all users (Wallace, 1988; p. 354)4. Thus,

the items of information included in the disclosure index have been considered from the view

point of a general purpose context rather than a specific user group context. At the same time

3 Wallace (1987) included 187 items of information in his disclosure index for the Nigerian

companies in his sample. Similarly, Spero (1979) developed this type of wide ranging disclosure

index consisting of 289 items of information. 4 The disclosure index used by one researcher and consequently adopted by other researchers is

not uncommon. For example, Parry and Groves (1990) argued that their model was originally

developed by Singhvi index (applied in the Indian context) and they applied the same in the

context of Bangladesh (a very similar in terms of both industrial framework and level of

development in India). However, Parry and Groves (1990) dropped 10 items of information

because those were not realistic information expectations in Bangladesh and added other six

items of information in their disclosure index.

8

attention has been given to both mandatory and voluntary items of information in the sample

countries.

In addition to reliance on the comprehensive study by Wallace (1987) of Nigerian companies,

other information items selected for the disclosure index were selected from a careful review of

other studies of financial disclosure, whilst others were selected after a review of recent annual

reports of listed companies in the sample countries. The disclosure requirements of the respective

companies acts and ordinances, stock exchange requirements and income tax laws have also

been taken into the account. In addition, the disclosure requirements relating to accounting

standards adopted by the sample countries have been considered and taken into account in

selecting items of information that ought to be disclosed by the companies in the sample

countries and as such, where relevant, have been included in the disclosure index. The disclosure

index considered both quantitative and qualitative items in the corporate annual reports of the

sample companies.

To summarise, the items of information included in the disclosure index have been developed

based on the following criteria:

i) Items of information commonly required by the statutes of the three developing countries

studied.

ii) Disclosure items identified in other studies examining disclosure in the sample countries

which used the disclosure index methodology (e.g. the study of Singhvi, 1967; Marston,

1986; Parry and Groves, 1990 and Ahmed and Nicholls, 1994).

iii) Disclosure indices generally used in developing countries other than the sample countries

(e.g. the study of Benjamin et al, 1990; Wallace, 1987; Chow and Wong-Boren, 1987 and

Abayo and Roberts, 1993 and Hossain et al, 1994).

iv) Disclosure requirements suggested by the (international) accounting standards adopted in the

sample countries.

The disclosure index constructed for this study included 94 items which were used in both unweighted and weighted

index formulations.

1.4.2 Scoring in the Disclosure Index

9

There are various approaches available to develop a scoring scheme to determine the disclosure level of corporate annual

reports from the works of other researchers. Wallace (1988), Cooke (1991 and 1992), Roberns and Austin (1986),

Hossain et al. (1994) and Ahmed and Nicholls (1994) adopted a dichotomous procedure in which an item scores one if

disclosed and zero if not disclosed. The approach used by Courtis (1979), Barret (1976 and 1977) and Marston (1986)

was for a weighted disclosure index to be employed. In some cases the weights were predetermined by the researchers

subjectively. Alternatively, Buzby (1974), Stanga (1979) and Firth (1979) have used average weights derived from

questionnaire surveys of users' perceptions of the importance of disclosure items. In the present study, analysis has been

based upon both weighted and unweighted indexes.

10

1.4.2.1 Scoring Disclosure Items under the Unweighted Disclosure Index

In the unweighted disclosure index disclosure of individual items has been treated as a dichotomous variable. Here, the

only consideration is whether or not a company discloses an item of information in its corporate annual report. If a

company discloses an item of information in its annual report it will be awarded `1' and if not it will be awarded `0'. The

disclosure model for the unweighted disclosure thus measures the total disclosure (TD) score for a company as additive

as follows:

TD= dii

n

1

Where,

d = 1 if the item di is disclosed

0 if the item di is not disclosed

n = number of items

An unweighted index is the ratio of the value of the number of items a company discloses divided by total value that it

could disclose. Under an unweighted disclosure index, all items of information in the index are considered equally

important to the average user. The unique advantage of using an unweighted index is that it permits an analysis

independent of the perception of a particular user group (Chow and Wong-Boren, 1987; p.537). If various users of

accounting information are asked to weigh the importance of different items of information in the disclosure index, they

may attach different weights to the same items of information. Despite the attractions of reflecting users perceptions, the

perceptions of different groups of users vary due to subjective judgement and interests, subjective judgements may

average each other out (Cooke, 1992; p.233) or neutralise the relative importance of each disclosure item to all members

of a user group (Wallace, 1987; p.355). The choice of an unweighted index over a weighted one does not produce

substantially different results (e.g. Chow and Wong-Boren, 1987; p.537) and there are researchers who favoured the use

of unweighted indexes (e.g. Spero, 1979; p.57 and Rubbins and Austin, 1986).

11

1.4.2.2 Scoring Disclosure under the Weighted Disclosure Index

Using a weighted index (WDI) may seem attractive because it allows distinctions to be made for the relative importance

of items of information to the users of annual reports (Inchausti, 1997; p.49). It has already been mentioned that many

disclosure studies have followed a weighted disclosure index approach. As all items of information under such an

approach are not of equal weight, it is necessary to develop a weighting scheme where a mean importance weight can be

attached to each of the disclosure items. The objective behind developing such a weighting scheme is to discriminate

between more important items and less important items. However, this presents difficult problems for any researcher

since the importance of an item may vary not just from one user to another, but the importance of a particular item of

information may vary from one company to another as well as one industry to another.

In some earlier studies, weights were assigned to individual item of information based on the subjective judgement of the

researcher. In order to reduce the impact of their own subjective judgement other subsequent researchers have conducted

questionnaire surveys among user groups to determine how they perceive an item of information to be important based

on a predetermined scale of rating each item of information. The rating scales used have varied although most have

followed either 4-0 or 5-1 Likert scales5. Such researchers have used the mean scores received by each item of

information as weights to individual item of information to be applied in the disclosure index. Under a WDI, each

company is awarded the mean score of that particular item of information if it discloses an item of information and a

zero for not disclosing the item. Care must be exercised in using the WDI approach. Cooke and Wallace (1989) were

of the opinion that `any scaling method for assigning weights to individual disclosure items has the potential to mislead

(p.51). They argued that the level of importance which is attributable to a disclosure item varies according to the

entities, transactions/accounts, the users, company, industry, country and the time of the study (Cooke and Wallace,

1989; p.51).

The researchers conducted a questionnaire surveys in Bangladesh, India and Pakistan among a sample of 300 users.

Appendix A shows the various respondent groups, sample size of the respondents and the response rate of the

questionnaire survey among different groups in the sample countries. For the weighted index in this study, the mean

importance score applied by the users surveyed to individual items in the user survey have been averaged and a mean

importance score has been calculated to provide weights to be used in the weighted disclosure index. The scale of rating

for each item of information was a 5-1 Likert scale.

In the present study, both weighted and unweighted indexes have been considered separately, and weighted and

unweighted indexes have been analyzed to see whether the weighted disclosure index could provide any significant

5 Buzby (1974) used a 4-0 scale, while Firth (1978), McNally, Eng and Hasseldine (1991), and

Wallace (1987) used a 5-1 scale. Chow and Wong-Boren (1987) used a 7-1 scale.

12

deviation from the unweighted disclosure index in examining the relationship between the extent of disclosure and

various corporate attributes.

1.5 Sample of Companies

The sample covers the annual reports of companies in the sample countries for the year 1992-93. The planned size

of the sample represented approximately 100 companies from each of Bangladesh, India and Pakistan which were

non-financial in nature, and listed on the respective stock exchanges in those countries. Lists of companies available

for inclusion in the sample were obtained from address books of the companies listed on the respective stock

exchanges. The companies were selected by using a mixture of judgemental and stratified random sampling

approaches. There are several reasons for using this mixed approach. The companies to be analyzed have been

identified keeping in mind the objectives of the study (e.g., the companies have been grouped according to type of

industry, size, local ownership vs. multinationality, etc.).

Samples were constructed by filtering companies in two phases. All the companies in the sample countries were not

entirely suited to the needs of this research work. In the first phase of filtering, listed financial enterprises (e.g. bank

and insurance companies) were excluded from the population of Bangladesh, India and Pakistan, since financial

companies are different from non-financial or manufacturing companies and they prepare their annual reports under

different statutes and have specialised nature of operations and accounting. For Bangladesh, the sample represents

the whole population of the non-financial companies listed on the Dhaka Stock Exchange. The total number of such

companies is 98 among which 10 companies are multinationals. The populations of listed non-financial companies

in each of India and Pakistan was divided into two sub populations, one for multinational companies and another for

local companies. From the sample of non-financial companies in India and Pakistan, 12 companies and 108

companies were selected at random from the first stratum (multinational companies) and second stratum (domestic

companies) using stratified random sampling.

The researchers collected the address books of companies listed on the Dhaka Stock Exchange (DSE), the Bombay

Stock Exchange (BSE) and the Karachi Stock Exchange (KSE) in Bangladesh, India and Pakistan respectively. The

sample of the listed companies from the DSE was prepared and letters were sent to the 98 non-financial companies

13

requesting them to send a copy of their annual report for the year 1992-93. Out of 98 companies, 78 companies sent

their annual report. The sample of the Indian companies was chosen from the Address Books of Companies on the

BSE. Letters were sent to the sample of 120 Indian non-financial companies listed on BSE requesting them to send

their annual reports. Of the 120 companies contacted, the researchers received 98 company annual reports.

However, 18 companies sent abridged annual reports which were considered to be unsuitable for the study and

hence were not used. As a result, the number of Indian non-financial company annual reports used in the study was

80. From the address book of the companies listed on the KSE, a sample of 120 companies was chosen and a

request was placed with the librarian of KSE to supply the researchers with company annual reports for the year

1992-93. However, only 103 company annual reports were supplied. Thus, the actual samples include 78 companies

from Bangladesh, 80 companies from India and 103 companies from Pakistan. The number of subsidiaries of

multinational companies included in the Pakistani, Bangladeshi and Indian samples are 13, 8 and 7 respectively.

1.6 The Dependent Variables, Explanatory Variables and Hypotheses

The dependent variables used in this study are Weighted Aggregate Disclosure Index (WADI) and Unweighted

Aggregate Disclosure Index (UADI) and the two disclosure indexes have been calculated for each of the companies

studied. The explanatory variables used in the study have taken into the account previous studies undertaken by

other researchers. These researchers have tested these variables in respect of both developed and developing

countries, but no researcher has formally considered whether these variables might be different in the case of

developed countries rather than developing countries such as Bangladesh, India and Pakistan. The corporate

attributes considered are size (proxied by sales and assets), profitability (proxied by rate of return on assets and net

profit margin), debt-equity ratio, multinationality (subsidiaries of the multinational companies), assets-in-place,

industry type, presence of debenture and international link of the audit firm. The following paragraphs provide a

rationale for taking into consideration the corporate variables chosen as explanatory variables:

1. Size of the company

There are several studies which have been found that a significant association between the size of the company and

the extent of disclosure in the corporate annual report in both developed and developing countries (Singhvi and

Desai, 1971; Buzby, 1974; McNally et al., 1982; Chow and Wong-Boren, 1987; Cooke, 1989; Wallace, 1987;

Ahmed and Nicholls, 1994, Hossain et al, 1994; Wallace, Naser and Mora, 1994; Wallace and Naser, 1995;

Raffournier, 1995 and Inchausti, 1997). However, other researchers like Spero (1979) and Stanga (1976) found that

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

14

Larger companies may be hypothesised 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 corporation, and large companies have the resources and

expertise to produce more information in their company annual reports and 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 do smaller

firms and as a result may disclose more information in their annual reports for their own interest. Since all the

companies in the samples used in this study are listed this influence per se cannot be expected to exert an effect on

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

competitive position with respect to other larger firms in their industry. As a result, smaller companies may tend to

disclose less information than large companies. Fourthly, it has been suggested that the annual reports of large

corporations are more likely to be scrutinised by financial analysts than those of smaller firms and non-disclosure

may be interpreted by investors as bad news which could adversely affect firm value. So, larger firms may have an

incentive to disclose more information than smaller firms. Fifthly, large companies receive far greater press

coverage and demands for more information are an almost inevitable results. Since companies like to have as

favourable a share price as possible greater disclosure may be felt to give more confidence to investors (Firth,

1979). 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 and total assets will be used as the

measures of company size. The following specific hypotheses have been tested regarding size of the firm:

H1(a): firms with greater total assets disclose financial information to a greater extent than do those firms with fewer

total assets.

H1(b): firms with greater sales turnover disclose financial information to a greater extent than do those firms with

lower sales turnover.

2. Debt-equity ratio

The debt-equity ratio has been studied empirically by several researchers to assess whether it bears any relationship

to disclosure level. Researchers such as Chow and Wong-Boren (1987), Ahmed and Nicholls (1994), Hossain et al

(1994), Wallace, Mora and Naser, (1994), Wallace and Naser (1995) and Inchausti (1997) found no significant

association between the debt-equity ratio and the extent of disclosure. Belkaoui and Kahl (1978) observed a

significant negative relationship between the extent of disclosure and the leverage ratio.

15

The nature of the relationship between the level of disclosure and gearing is ambiguous. Companies having more

debt in their financial structure, can be argued to disclose more as well as less information in their annual reports.

Relatively highly geared companies may disclose more information to suit the needs of lenders and thus bear

increased monitoring costs in the form of more public disclosure. In addition, such companies may disclose more

information to reassure equity holders in order that they might reduce risk premiums in required rates of return on

equity. On the other hand, there is a possibility that the companies with higher debt-equity ratios may want to

disguise the level of risk and may disclose less information in their corporate annual reports.

In India, Pakistan and Bangladesh, Development Financial Institutions (DFIs) typically ask companies who wish to

borrow to fulfil a number of requirements for information provision and the submission of annual reports are

important in this respect. Companies with relatively large borrowings can expect to be monitored more closely by

financial institutions and may be required to furnish information more frequently than companies having smaller

amounts of debts (Ahmed and Nicholls, 1994). As a result, it is likely that companies with large borrowings will

provide more detailed information in their annual reports than companies with small borrowings. Several measures

of leverage have been used in previous studies, including debt to total assets, total debt as well as the debt-equity

ratio. The debt-equity ratio will be used as measure of leverage in this study. The following specific hypothesis has

been tested regarding the debt-equity ratio:

H2: firms with higher debt-equity ratios disclose financial information to a greater extent than do firms with lower

debt-equity ratios.

3. Profitability

Profitability was used by a number of researchers as an explanatory variable for differences in disclosure level.

Among these researchers Cerf (1961), Singhvi (1967), Singhvi and Desai (1971), and Wallace (1987), Wallace,

Mora and Naser (1994), Wallace and Naser (1995), Raffournier (1995) and Inchausti (1997) found a positive

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

association between the 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. Researchers have used a number

of profitability and profit-related measures in their studies, such as net profit to sales, earnings growth, dividend

growth and dividend stability (Cerf,1961), rate of return and earnings margin (Singhvi and Desai, 1971; Wallace,

Mora and Naser, 1994 and Wallace and Naser, 1995), and return on assets (Belkaoui and Kahl, 1978; Raffournier,

1995 and Inchausti, 1997).

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. If the profitability of a company is high,

management may disclose more detailed information in the corporate annual report in order to experience the

comfort of communicating it as it is good news. On the other hand, if profitability is low management may disclose

16

less information in order to cover up the reasons for losses or lower profits. For profitable companies if the rate of

return or return on investment is more than the industry average, the management of a company has an incentive to

communicate more information which is favourable to it as the basis of explanations of good news and is likely to

disclose more information in their corporate annual reports as a result.

In the present study, net profit to sales and rate of return on assets have been used as the measures of profitability.

The following specific hypotheses have been tested regarding profitability:

H3(a) : firms with higher net profit to sales disclose financial information to a greater extent than do those firms with

lower net profit to sales ratios.

H3(b): firms with higher rates of return on assets disclose financial information to a greater extent than do those

firms with lower rates of return on assets.

4. Internationality (subsidiaries of multinational companies)

The subsidiaries in developing countries of parent multinational companies from developed countries are likely to

disclose more information than their local counterparts. Several justifications may be offered for the inference this

multinationality variable. First, the parent companies of these multinationals subsidiaries usually operate their

businesses in developed countries where standards of reporting are higher than in developing countries. The

subsidiaries in developing countries can be expected to have to generate more information to comply with more

stringent internal accounting standards of their parent multinational (Ahmed and Nicholls, 1994) and at the same

time have to fulfil the disclosure requirements of the host countries. Parent company multinationals may require the

preparation of their subsidiaries accounts on international or developed country GAAP for purposes of

consolidation or may require the use of standardised accounting principles for internal performance measurement or

control purposes. As a result, the subsidiaries of multinational companies may disclose more information than local

companies without incurring any additional costs. Second, it has been argued that the political costs for these

subsidiaries may be more in developing countries than in developed countries as there are political pressure groups

who perceive the multinational companies as a source of economic exploitation and view them as agents of Western

imperialism and keep a close eye on the subsidiaries of these multinational companies as a consequence. In addition,

subsidiaries of multinational companies in developing countries may be considered as significant in the economies

of their host countries and such companies may risk the threat of government control, even the threat including

nationalisation. There is evidence that subsidiaries of multinational companies have an incentive to increase the

level of disclosure in order to reduce such political costs (Rahman and Scapens, 1988)6. Wallace (1987) and Ahmed

and Nicholls (1994) found that there was a significant positive association between the mutinationality of the

companies and the level of disclosure.

6 In addition, there may be a possibility that such multinational companies subsidiaries may

have incentives to manipulate their accounting policies to reduce reported profits.

17

The following specific hypothesis has been tested regarding the multinationality:

H4: firms with the mutinationality connections (subsidiaries of multinational companies) disclose financial

information to a greater extent than do with those of their domestic counterparts.

5. Audit firm

Several studies have examined empirically the relation between the characteristics of the audit firm (size of audit

firm or international link of the auditing firm) and the extent of disclosure (Singhvi and Desai, 1971; Ahmed and

Nicholls, 1994; McNally et al, 1982 and Hossain et al, 1994; Wallace and Naser, 1995; Raffournier, 1995 and

Inchausti, 1997) and found positive association between the audit firm size and the level of disclosure. However,

there is also empirical evidence of no significant relation between the size of the firm and the extent of disclosure

(Malone et al, 1993 and Tan et al, 1990; Wallace, Mora and Naser, 1994;). It may be argued that audit firms are

concerned with the minimum disclosure that is required by law and other aspects of GAAP. However, it is more

likely that the larger audit firms have a stronger incentive to produce high quality audits in order to maintain their

reputation than do smaller audit firms. If clients prepare financial reports in which disclosure is inadequate or

erroneous, larger audit firms may be more likely to report adversely on the position of the company (Ahmed and

Nicholls, 1994). Although, the primary responsibility for preparing the annual report rests with the company, the

companys auditors may exercise some influence or provide advice regarding the level of disclosure to give. It has

been argued that larger, more well known audit firms may be able to exercise greater influence and they may be

associated with higher disclosure levels (Firth, 1979). As a result, larger audit firms may have more influence over

their clients to disclose more information than the minimum which is adequate. The client company may attempt to

improve the appearance of its financial position and results of operations and errors and inadequate disclosure which

support such motives may be considered to be purposely caused by the management of the company. If clients

prepare financial reports in which disclosure is inadequate or erroneous, audit firms have to face two problems.

First, the audit firm can disclose the fact that there is disagreement with the contents of the client companys

accounts in the audit report. In that case the audit firm may loose its client company in future. Second, if the audit

firm does not specify the fact that the accounts are faulty, legal action may be taken for negligence against the audit

firm. It is possible for large audit firms to absorb the risk of loosing their clients on the grounds that clients

financial reports receive criticism from the large audit firm.

The following specific hypothesis has been tested regarding the audit firm size or international link of the audit firm:

H5 : firms that engage larger international audit firms disclose financial information to a greater extent than do

those firms that engage domestic audit firms.

6. Industry Type

18

Industry type has been used by a number of researchers as an explanatory variable for differences in disclosure level.

Among them Belkaoui and Kahl (1978), Cooke (1991) and Stanga (1976) found a positive association between

industry type and the extent of disclosure whereas Wallace (1987), Wallace, Mora and Naser (1994), Raffournier

(1995) and Inchausti (1997) did not find any positive association between the variables.

It is possible that disclosure in corporate reports in India, Bangladesh and Pakistan may not be identical throughout

different industries. The existence of a dominant firm with a high level of disclosure in a particular industry may

produce a bandwagon effect on levels of disclosure adopted by other firms in the same industry (Cooke, 1991). No

other firm may wish to be outscored by the leader firm and as a result, a particular industry may have similar

disclosure policies because of the follow the leader effect (Wallace, 1987; Belkaoui and Kahl, 1978). In addition, the

adoption of different industry-related accounting measurement, valuation and disclosure techniques and policies

may lead to differential disclosure in financial reports published by enterprises within a country (Wallace, 1987).

One industry may disclose certain items of information while others may not. Furthermore, it is sometimes

customary to expect manufacturing industries to communicate more with the environment than is the case with other

business types (Wallace, 1987).

The following specific hypotheses will be tested regarding industry type:

H6 : firms falling with in a specific industry type disclose different amounts of financial information than do those

firms falling with in other industry types.

7. Proportion of assets-in-place

Myers (1977) suggests that the value of a firm is composed of two elements. The first element represents real

assets, the market values of which are independent of the firms investment strategy (called assets in place). The

second element represents real options, the value of which depends upon future discretionary investments (called

assets yet to be acquired or growth opportunities). Wealth transfers are more difficult (hence agency costs are lower)

with assets that are already owned than assets to be acquired (Chow and Wong-Boren, 1987). Wealth transfers from

debt-holders to shareholders are less likely to occur in firms with a larger proportion of assets in place, since lenders

can more easily write covenants restricting shareholders use of those assets in debt agreements (Myers, 1977). This

implies that the extent of voluntary disclosure will be inversely related to the proportion of assets in place in a firm

(Hossain et al, 1994). However, the results are contradictory. Chow and Wong-Boren (1987), Hossain et al (1994)

and Raffournier (1995) found no significant positive relationship between assets in place and the level of disclosure.

In the absence of market value data for the sample companies the proportion of assets in place is computed by

dividing the book value of fixed assets, net of depreciation, by total assets.

The following specific hypotheses will be tested regarding assets-in-place:

19

H7 : firms with a relatively lower proportion of assets-in-place disclose financial information to a greater extent

than do those firms with a relatively higher proportion of assets-in-place.

8. Presence of public debentures in companies debt

Companies may raise debt finance in public markets or privately from financial institutions. Borrowings requires

bounding and monitoring activity on the part of the corporate borrowing. Bounding may involve the pledging of

security by the borrower or the giving of covenants in debt contracts to offer protection to the lender. Other aspects

of bounding involve promises to supply accounting information which is used by the lender to monitor the borrower.

Private debt agreements are not generally observable but we may expect firms which borrow in public markets by

raising debt through debentures to adopt disclosure policies consistent with the requirements of monitoring by

lenders. Thus, to reduce debt contracting costs, we may agree that firms issuing debentures tend to make more

public disclosure than those which borrow in private.

The following specific hypotheses will be tested regarding presence of public debentures in companies debt:

H8 : firms with public debenture(s) disclose financial information to a greater extent than do those without any

public debentures.

20

1.7 Correlation Analyses

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

Pearson product moment correlation coefficients (r) were computed. A correlation matrix of all the values of r for the

explanatory variables along with the dependent variables was constructed and is shown in Table 2, Table 3 and Table

4 for the Bangladeshi, Indian and Pakistani samples respectively. For Bangladeshi companies, the Pearson product-

moment coefficients of the correlation between disclosure indexes and assets, sales and subsidiaries of multinational

companies variables are higher than the coefficient of the correlation between disclosure indexes and every other

corporate attributes. Table 2 suggests that for the Bangladeshi sample assets, sales and subsidiaries of multinational

companies correlation between variables may be an issue while collinearity across the other variable is not. Table 2

shows a reasonable amount of significant collinearity ( p 0.01) among some variables (between sales and total

assets .4320 and between sales and subsidiaries of multinational companies .4230).

Table 3 suggests that for the Indian sample correlation between variables assets, sales, debt-equity ratio, rate of

return on total assets and net profit margin variables may be an issue while collinearity across the other variable are

not. Table 3 shows a large amount of significant collinearity (p0.01) among some variables (between sales and

total assets .9751 and between net profit margin and debt-equity ratio -.7935). Other significant but relatively weaker

coefficients are reported for the correlation between debt-equity ratio and rate of return on total assets -.3955. These

significant correlations suggest that multicollinearity may be a problem.

Table 4 suggests that for the Pakistani sample correlation between variables assets, sales, debt-equity ratio, rate of

return on total assets and net profit margin, presence of debenture in debt structure, assets-in-place, international link

of the audit firms and subsidiaries of multinational companies variables may be an issue while collinearity across the

other variable are not. Table 4 shows a large amount of significant collinearity ( p 0.01) among some variables

(between sales and total assets .3570, between net profit margin and debt-equity ratio -.7935 and between debt-equity

ratio and assets in-place .4622, between international link of the audit firms and debt-equity ratio .4795, between

assets-in-place and presence of debenture in debt structure .3599, between subsidiaries of multinational companies

and, international link of the audit firms .7419 and between rate of return on total assets and net profit margin .8518).

Other significant but relatively weaker coefficients are reported for the correlation between sales and total assets

.3570 and between debt-equity ratio and assets in-place .4622, and between international link of the audit firms and

debt-equity ratio .4795, between assets-in-place and presence of debenture in debt structure .3599. These significant

21

correlations suggest that multicollinearity may be a problem. The reasons for inclusion and/or exclusion of a

variable has been detailed in the preceding section.

25

Table 2

Correlation matrix for Bangladeshi sample companies

variables assinpla deratio indutype inlink roassets npmargin assets sales multicom deben uadi wadi

assinpla 1.0000

deratio -.1556 1.0000

indutype ..0606 -.0476 1.0000

inlink .0630 -.1195 .1437 1.0000

roassets -.2307* -.3733 .0284 .0602 1.0000

npmargin -.0976 -.1772* .0764 -.2157* -.0125 1.0000

assets .1756 .0071 .2458* .2798* .0657 .0540 1.0000

sales .0712 -.1422 .0447 .2846* .0383 .0337 .4320** 1.0000

multicom -.0021 -.1224 .0921 .3775* .0360 .0360 .1256 .4230** 1.0000

deben -.1756 .2244* .0390 .2322* .0461 -.2816* .0455 -.0647 -.1272 1.0000

uadi -.0287 -.1701 .2638* .0584 .1810 .0254 .2274* .2060* .2920* -.0612 1.0000

wadi -.0267 -.1925 .2440* .0661 .1656 .0164 .2314* .2065* .3073* -.0593 .9947* 1.0000

** coefficient of correlation significant at 1% level or better (p 0.00)

*coefficient of correlation significant at 5% level or better (p 0.05)

26

Table 3

Correlation matrix for Indian sample companies


assinpla 1.0000

deratio .0193 1.0000

indutype .0416 -.1924 1.0000

inlink -.0934 -.2073* -.1573 1.0000

roassets .0709 -.3955** .1517 .0427 1.0000

npmargin .2109* -.7935** .0960 .0754 .3154* 1.0000

assets .2034* .0320 -.1210 .0604 -.0477 .0270 1.0000

sales .1435 -.0018 -.1337 .0827 -.0490 .3154 .9751** 1.0000

multicom .0918 .0035 .0984 .2364* -.0757 .0384 .0025 .2226 1.0000

deben .0228 .1565 -.1885* .1535 -.2968* -.0987 .2524* .2892* .1340 1.0000

uadi .0214 -.3143* -.1817 .3526* .1711 .2105* .3585* .4157* .2156* .4687* 1.0000

wadi 0005 -.3041* .0984 .2364* .1870* .1910* .3600* .4145* .2226* .4687* .9959** 1.0000



27

Table 4

Correlation matrix for Pakistani sample companies


assinpla 1.0000

deratio .4622** 1.0000

indutype -.1588 -.1770* 1.0000

inlink -.4795** -.2832* .1366 1.0000

roassets .0675 -.0097 -.2446* .1338 1.0000

npmargin .0592 .0244 -.2857* .0490 .8518** 1.0000

assets .0205 .2515* -.1417 .1296 .1613 .0799 1.0000

sales -.1637* -.0633 -.0058 .1441 .1040 .0407 .3570** 1.0000

multicom -.4137* -.2552* .3000* .7419** .1291 .0410 .1982* .1845* 1.0000

deben .3559** .3136* -.1193 -.1529 .0491 .0467 .1655* -.0342 -.1045 1.0000

uadi -.2803* -.0259 -.0721 .3516* .2267* .1345 .3788** .1511 .3579** .1836* 1.0000

wadi -.2857* -.0339 -.0815 .3212* .2206* .1296 .3556** .1442 .3331* .1833* .9885** 1.0000



28

1.8 Multiple Regression Models

Multiple linear regression techniques are used to test two alternative reasons of each hypothesis. Two models

are created one using UADI and the other using WADI as the dependent variable. Model 1.1 is based on the

unweighted index and Model 1.2 is based on the weighted index.

UADI= ROASSETS + NPMARGIN + MULTICOM + INDUTYPE

+ DERATIO + ASSINPLA + ASSETS + DEBEN+ INLINK

+ SALES +

where UADI = total score received each sample company under unweighted disclosure index;

the constant, and

the error term.

WADI= ROASSETS + NPMARGIN + MULTICOM + INDUTYPE

+ DERATIO + ASSINPLA + ASSETS + DEBEN+ INLINK

+ SALES +

where WADI = total score received each sample company under weighted disclosure index;

the constant, and

the error term.

The description of the ten independent variables, their labels and expected signs and relationships are present in

Table 5.

29

Table 5

List of independent variables, their labels and expected signs and relationships in the regression

Variable Labels

in the OLS

Variables Expected sign and relationship

INTLINK International link of auditing firms INLINK has a significant positive relationship

with the level of disclosure

SALES Total of sales SALES has a significant positive relationship with

the level of disclosure

NPMARGIN Net profit margin NPMARGIN has a significant positive

relationship with the level of disclosure

ROASSETS Rate of return on total assets ROASSETS has a significant positive relationship


MULTICOM Multinationality of companies

(Subsidiary of a multinational

company)

MULTICOM has a significant positive

relationship with the level of disclosure

ASSETS Total assets ASSETS has a significant positive relationship


ASSINPLA Assets-in-place ASSINPLA has a significant negative relationship


DEBEN Presence of Debentures in the

companies debt

DEBEN has a significant positive relationship


INDUSTRY Industry Type INDUSTRY a significant positive relationship


DERATIO Debt to equity ratio DERATIO has a significant positive relationship


Thus, It was expected that for the sample companies in these three developing countries, size (sales and assets),

profitability (rate of return on assets and net profit margin), debt-equity ratio, presence of debenture in debt,

international link of the audit firm, industry type and multinationality (subsidiaries of multinational companies)

should be positively associated with the extent of disclosure and assets-in-place should be inversely related to

the extent of disclosure. Whereas Industry Type variable has no indicated sign with the level of disclosure.

30

1.9 Results of regression analyses

Because assets and sales variables were correlated, OLS regression using assets as the proxy for the size

variable (but excluding sales) were estimated for both unweighted and weighted models. Then, a second OLS

regression using sales as a proxy for the size variable (but excluding sales) were estimated for both the

unweighted and unweighted models. In case of the Bangladeshi and Pakistani samples the results of the

regression that included assets (but not sales) showed a higher R2

than the results of the regression which

included sales (but not assets). In the case of the Bangladeshi sample companies, the R2 of the first regression

model which included sales (but not assets) is .20467 whereas the R2

of the second regression model which

included assets (but not sales) is .22575. In the case of the Pakistani sample companies, the R2 of the first

regression model which included sales (but not assets) is .30755 whereas the R2

of the second regression model

which included assets (but not sales) is .35820. However, in the case of the Indian sample companies the results

of the regression showed that the R2

of the regression model which included sales (but not assets) is higher than

the results of the regression models which included assets (but not sales). In the case of Indian sample

companies, the R2

of the first regression model which included sales (but not assets) is .50819 whereas the R2

of

the second regression model which included assets (but not sales) is .49558.

For Bangladesh and Pakistan, the regression model using assets as the surrogate of the size of the companies

showed better explanatory power than the regression models which included sales as the proxy of the size

variable. In the case of the Indian sample companies, however, the regression model using sales as the surrogate

of the size of the companies showed better explanatory power than the regression models which included assets

as the proxy of the size variable. The results of such regression models using both weighted and unweighted

models for each of Bangladeshi, Indian and Pakistani sample has been discussed in the following sections7.

7 An analysis of R square using weighted models produced similar results.

31

1.9.1 Results of Regression Analyses for Bangladeshi Sample Companies

The results of the model explaining UWDI is presented in Table 6.1. For Bangladeshi companies, a summary of

the regression output using for the model 1.1 and model 2.1 are shown in Table 6.1 and Table 6.2 respectively.

It was expected that for Bangladeshi companies, size (assets), profitability (rate of return on assets and net profit

margin), debt-equity ratio, presence of debenture, international link of the audit firm should be positively

associated with the extent of disclosure and assets-in-place should be inversely related to the extent of

disclosure. It was found that for in Model 1.1, only the relation between the extent of disclosure and the

mutinationality variable (subsidiaries of the multinational companies) was significant at 5% level (see Table

6.1). However, the relation between the extent of disclosure and industry type variable is found to be significant

only at 10% level both in the unweighted and weighted models.

The variables that were found to be insignificant included profitability (rate of return on assets and net profit

margin), debt-equity ratio, presence of debenture, international link of the audit firm, industry type and assets-

in-place.

A stepwise regression model separately applied showed that multinationality and industry type variables are

significant at 5% level in both the models8. It was also found that for Bangladeshi sample companies, in Model

1.2, the only the relationship between the level of disclosure and mutinationality variable was significant at the

5% level (see Table 6.2). There are no significant differences between the two models regarding the

performance of the independent variables. The R2

under the weighted model was .23441 and the R2

under the

unweighted model was .22575, which indicate that the unweighted and weighted models are capable of

explaining 22.58% and 23.44% of the variability in the disclosure of Bangladeshi companies respectively. The

adjusted R2 indicate that 12.32 percent of the variation in the dependent variable under unweighted model is

explained by variations in the independent variables.

8 The results have been shown in Appendix B.

32

Table 6.1

Summary of the regression output for UWDI

(Results of Bangladeshi sample companies)

Model 1.1

Coefficient of multiple regression (Multiple R) .47513

Coefficient of determination (R2) .22575

Adjusted R2 .12328

Standard Error 6.20479

Analysis of Variance

D.F. Sum of Squares Mean Squares

Regression 9 763.33512 84.81510

Residual 68 2617.95975 38.49941

F ratio = 2.20302

------------------ Variables in the Equation ------------------

Variable B SE B Beta T Sig T

ASSETS 2.55992E-09 1.5429E-09 .193912 1.652 .1031

ASSINPLA -1.533417 3.460431 -.041406 -.443 .6591

DEBEN -.130621 2.295900 -.006905 -.057 .9548

DERATIO -.314148 .237859 -.149579 -1.321 .1910

INDUTYPE .579380 .308909 .208733 1.876 .0650

INLINK -2.767511 2.065389 -.173536 -1.340 .1847

MULTICOM 6.684031 2.750142 .290153 2.430 .0177

NPMARGIN -1.523266E-05 2.1770E-05 -.082398 -.700 .4865

ROASSETS 6.12332E-05 4.3020E-05 .157487 1.423 .1592

(Constant) 33.655215 1.933736 17.404 .0000

33

Table 6.2

Summary of the regression output for WDI

(Results of Bangladeshi sample companies)

Model 1.2

Coefficient of multiple regression (Multiple R) .48415


Adjusted R2 .13308

Standard Error .13308



Regression 9 14905.38039 1656.15338

Residual 68 48682.58143 715.92032

F ratio = 2.31332



ASSETS 1.16044E-08 6.6806E-09 .202701 1.737 .0869

ASSINPLA -6.373516 14.922291 -.0492271 -.427 .6706

DEBEN .029858 9.900527 3.640E-04 .003 .9976

DERATIO -1.557489 1.025710 -.170988 -1.518 .1335

INDUTYPE 2.221030 1.332096 .184517 1.667 .1001

INLINK -12.269325 8.906503 -.177409 -1.378 .1729

MULTICOM 30.603692 11.859336 .306350 2.581 .0120

NPMARGIN -7.47469E-05 9.3879E-05 -.093238 -.796 .4287

ROASSETS 2.74681E-04 1.8551E-04 .162907 1.481 .1433

(Constant) 136.806301 8.338779 16.406 .0000

1.9.2 Results of Regression Analyses for Indian Sample Companies

For Indian companies, a summary of the regression output using for the two models are shown in Table 7.1 and

Table 7.2 respectively. It was found that for India model 1.1, size (sales), presence of debenture and rate of

return on assets variables were significant at the 5% level (see Table 7.1). . However, the international link of

the auditing firm variable was significant only at the10% level using enter method in both unweighted and

weighted models. The variables that were found to be insignificant included the size (assets), profitability (net

34

profit margin), debt-equity ratio, industry type, multinationality of the companies and assets-in-place. A

stepwise regression model separately applied showed that the relationships between size (sales), presence of

debenture, rate of return on assets, and the international link of the auditing firm variables and the extent of

disclosure were significant at the 5% level in both the models. For Indian companies model 1.2 produced

essentially the same results as model 1.1 index (see Table 7.2). The R2 for the unweighted model was .49558 and

that for the R2 for the weighted model was .50599.

35

Table 7.1


(Results of sample Indian companies)

Model 1.1

Coefficient of multiple regression .71287


Adjusted R2 .44496




Regression 9 1957.53417 217.50380

Residual 70 1894.45333 27.06362

F ratio = 7.64158



SALES 3.09666E-10 9.9515E-11 .277631 3.112 .0027

ASSINPLA -2.104404 3.126640 -.062167 -.673 .5031

DEBEN 5.919617 1.308926 .424408 4.522 .0000

DERATIO -.281643 .832333 -.052567 -.338 .7361

INDUTYPE -.268993 .218587 -.111614 -1.231 .2226

INLINK 2.639718 1.439091 .174329 1.834 .0709

MULTICOM 3.351037 2.076177 .144878 1.614 .1110

NPMARGIN 3.18197E-04 4.0606E-04 .114487 .784 .4359

ROASSETS .333156 .114963 .277943 2.898 .0050

(Constant) 10.988279 1.946480 21.058 .0000

36

Table7.2


(Results of sample Indian companies)

Model 1.2



Adjusted R2 .45472




Regression 9 21865.41082 2429.49009

Residual 70 20440.72862 292.01041

F ratio = 7.96638



SALES 1.03654E-09 3.2689E-10 .280416 3.171 .0023

ASSINPLA -9.160464 10.270322 -.081656 -.892 .3755

DEBEN 20.035911 4.299534 .433451 4.660 0000

DERATIO -1.104770 2.734032 -.062220 -.404 .6874

INDUTYPE -.910990 .718011 -.114060 -1269 .2087

INLINK 7.964041 4.727095 .158703 1.685 .0965

MULTICOM 12.255066 6.819784 .159875 1.797 .0767

NPMARGIN 7.77702E-04 .001334 .084434 .583 .5617

ROASSETS 1.214799 .377628 .305811 3.217 .0020

(Constant) 133.433124 6.693757 20.869 .0000

37

1.9.3 Results of Regression Analyses for Pakistani Sample Companies

For Pakistani companies, a summary of the regression output using for model 1.1 and model 1.2 are shown in

Table 8.1 and Table 8.2 respectively. It was found for the unweighted aggregate disclosure index (UADI) total

assets, presence of debenture and assets-in-place variables were significant at the 5% level (see Table 8.1). The

variables that were found to be insignificant included the profitability ( net profit margin and rate of return on

assets), debt-equity ratio, industry type, multinationality of the companies and international link of the auditing

firms. A stepwise regression model separately undertaken showed that the relationships between the level of

disclosure and size (assets), presence of debenture, assets-in-place and the international link of the auditing firm

variables were significant at the 5% level in both weighted and unweighted aggregate disclosure models.

Model 1.2 produced essentially the same results as in case of model 1.1 (see Table 8.2). The R2 for the

unweighted model was .35820 that for the weighted model is .33893.

38

Table 8.1


(Results of sample Pakistani companies)

Model 1.1



Adjusted R2 .29609




Regression 9 1179.64892 131.07210

Residual 93 2113.61322 22.72702

F ratio = 5.76724



ASSETS 1.64211E-09 5.9876E-10 .254465 2.743 .0073

ASSINPLA -8.095447 2.851386 -.30929 -2.839 .0056

DEBEN 3.734948 1.330690 .256194 2.807 .0061

DERATIO .177148 .680716 .026115 .260 .7953

INDUTYPE -.213845 .257917 -.078763 -.829 .4092

INLINK 1.480549 1.981532 .099434 .747 .4568

MULTICOM 2.310223 2.325454 .135680 .993 .3231

NPMARGIN -.001296 .001624 -.130311 -.798 .4270

ROASSETS .055572 .036170 .254931 1.536 .1278

(Constant) 48.120722 1.645153 29.250 .0000

39

Table 8.2

PAKISTAN


(Results of sample Pakistani companies)

Model 1.2



Adjusted R2 .27496




Regression 9 14938.26103 1659.80678

Residual 93 29135.97611 313.29007

F ratio = 5.29799



ASSETS 5.55004E-09 2.2231E-90 .235094 2.497 .0143

ASSINPLA -31.747768 10.586637 -.329026 -2.999 .0035

DEBEN 14.022955 4.940591 .262933 2.838 .0056

DERATIO .500964 2.527369 .020188 .198 .8433

INDUTYPE -.884047 .957594 -.089006 -.923 .3583

INLINK 4.164931 7.357039 .076461 .566 .5727

MULTICOM 7.730688 8.633955 .124108 .895 .5727

NPMARGIN -.005233 .006030 -143836 -.868 .3877

ROASSETS .212637 134292 .26638 1.583 .1167

(Constant) 179.641853 6.108132 29.410 .0000

40

1.10 Discussion of the results

The regressions carried out in this paper have some interesting aspects. First, the sample of companies provides

a fair representation of the corporate structure of Bangladesh, India and Pakistan.. The companies covered by

the sample are non-financial in nature and listed on the respective stock exchanges in Bangladesh, India and

Pakistan. Also the sample includes major subsidiaries of multinational companies functioning in the sample

countries.

In the case of Bangladesh and Pakistan, asset size was preferred to sales as the size variable because the former

has a higher correlation with the dependent variable and yields a higher R2 (see Table 6.1 & 6.2 and Table 8.1 &

8.2 respectively) while in the case of India sales was preferred to assets for the same reason( see Table 7.1 and

7.2).

In case of Bangladesh, both the weighted and unweighted disclosure index is found to be significantly positively

influenced by the subsidiary of a multinational while the industry type variable is significant at the 10% level.

The industry type variable is also significant at 5% level as suggested by stepwise regression both in the

weighted index model and unweighted model. All other variables were insignificant for both the weighted

index model and unweighted models.

In the case of Indian companies, size (sales), presence of debenture and rate of return on assets variables were

significant at the 5% level both in the weighted index model and unweighted model. However, the international

link of the auditing firm variable is also significant at 5% level as suggested by stepwise regression. All other

variables were insignificant for both the weighted index model and unweighted models.

In the case of Pakistani companies, size (assets), presence of debenture and assets-in place were significant at

the 5% level both in the weighted index model and unweighted model. However, the international link of the

auditing firm variable is also significant at 5% level as suggested by stepwise regression. All other variables

were insignificant for both the weighted index model and unweighted model.

41

As already mentioned above that the weighting scheme plays a part in measuring the extent of disclosure in

models based on weighted indexes. Thus, two companies disclosing 45 different items of information would

have the same level of disclosure in unweighted models while in unweighted models their relative extent of

disclosure may well be different depending on the importance of the particular items disclosed by the two

companies as determined by the weights. So, it is surprising that the weighted and the unweighted models

produce only slightly different results in terms of the significant and insignificant variables.

Tables 1-9 (a)-(c) provide summarise of the relative influence of some corporate attributes on corporate

disclosure as revealed by the results of multiple regression analyses. In Hossain and Taylor (1998) it was

suggested a general relationship (positive) for the whole sample of Bangladeshi companies, between variable

multinationality subsidiary of a multinational company and the extent of disclosure under both indices. As

well as being associated with sophistication in financial reporting, multinationality may connote size and the

presence of a separate size variable effect in Bangladesh. Profitability is not a statistically significant

determinant of disclosure across the whole sample of Bangladeshi companies as suggested in the discussion

Hossain and Taylor (1998).

Table 1-9 (a)

Determinants of disclosure in Bangladesh

Significance level Unweighted disclosure

index

Weighted disclosure

index

5% or better Multinationality of companies

Size (assets)

Multinationality of companies

Size (assets)

20% or better

Industry Type

Debt-equity ratio

Industry Type

International Link of audit firm

Debt-equity ratio

Multiple R 0.455 0.477

While discussing Indian companies in chapter seven reduced importance for multinationality amongst the

highest disclosers was observed. However, the increased significance of a variable indicating the nature of the

disclosing companys auditor introduces external, developed country influences into disclosure in another way.

This auditor variable is partitioned between international and domestic audit firms and the regressions show a

positive association between having an international audit firm as auditor and an increased level of disclosure.

Size of auditee may also be reflected in this association. The significance of the variables relating to profitability

and financing suggests an important role for stakeholder monitoring factors in determining disclosure

differences in India. These two variables were also found to be important for Pakistan, as table 10.6 (c) shows,

although with somewhat less strength in the case of profitability.

Table 1-9 (b)

42

Determinants of disclosure in India

Significance level Unweighted disclosure index

Weighted disclosure index

5% or better Size (Sales)

Profitability of the company

(Return on assets)

Presence of public debentures in

debt

Industry type

Size (Sales)

Profitability of the company

(Return on assets)

Presence of public debentures

in debt

Industry type

10% or better International link of audit firm

Multinationality of company

International link of audit firm

Multinationality of company

Multiple R 0.738

0.745

The observation of a possible importance of stakeholder monitoring in India and Pakistan is consistent with

these countries having more developed and sophisticated economies and financial systems relative to their

neighbour Bangladesh. The variable assets-in-place is significant only in Pakistan and seeks to capture the

influence of a companys investment opportunities as an indicator of risk and bonding opportunities for outside

financiers.

43

Table 1-9 (c)

Determinants of disclosure in Pakistan

Significance level Unweighted disclosure index

Weighted disclosure index

5% or better Assets-in place

Size (assets)

Presence of public debentures in

debt

Assets-in place

Size (assets)

Presence of public debentures

in debt

20% or better Profitability (Return on assets)

Profitability (Return on assets)

Multiple R 0.596

0.579

1.11Comparison with other studies

Wallace (1987) examined the association between the extent of disclosure and several corporate attributes such

as size, profitability, liquidity, type of management, parent country, and type of business. He developed a

disclosure index by including the statutory and voluntary disclosure items. He developed two disclosure index

models: one being a 'statutory disclosure index' and the other using an 'overall disclosure index'.

Wallace (1987) found that transnational enterprises and assets were two variables which were positively

significant with the extent of disclosure at the 5% scale. The rest of the variables were insignificant at 5% level.

Again, the R2 was very low: only 0.087, showing that only 9% of the variability in the overall disclosure index

can be explained by the impact of transnational enterprises and assets variables.

His regression models suffered from serious multicollinearity problems in the sense that he used three proxies

for the measurement of size: assets, sales and number of shareholders. It was found that these variables were

positively correlated: the correlation coefficient between assets and sales was 0.911, between assets and number

of shareholders was 0.904 and between sales and number of shareholders was 0.785. It is not legitimate to

include more than one proxy for the measurement of size in the same regression model. In the above

circumstances, it can be argued that in order to avoid multicollinearity problem, he should develop three

different models for each proxy for the measurement of size as in Cooke (1987). In the case of Bangladesh, the

size variable which is found insignificant in the current study is inconsistent with Wallaces findings for his

Nigerian sample but consistent with the findings for the Indian and Pakistani companies in this study. In

44

addition, Wallace undertook a questionnaire survey and calculated mean values for the perceived importance of

items of information assigned by each of his respondent groups. However, he did not construct a weighted

disclosure index model based on these findings.

Ahmed and Nicholls (1994) analysed a sample of Bangladeshi companies and examined the relationship

between the extent of disclosure and a number of corporate attributes such as total debt, size (as measured by

annual sales and total assets), multinational company influence, qualification of principal accounts officer of the

38. the relationship between disclosure and firm characteristics in developing

Documents

extent of disclosure

levels of disclosure

disclosure data

unweighted disclosure

unweighted disclosure

developing countries

sample companies

size assets