AN INVESTIGATION OF THE INITIAL VOLUNTARYENVIRONMENTAL DISCLOSURES MADE IN KOREAN

SEMI-ANNUAL FINANCIAL REPORTS

Jong-Seo Choi

School of Commerce, Department of Accounting

Professor of Accounting, Pusan National University

Pusan, Korea

INTRODUCTION

The voluntary disclosure of social and environmental information by business firms has been the subject

of substantial academic interest for the past several decades. Surveys in a number of countries show an

increasing trend of disclosing such information in corporate reports. There has been an upsurge of

empirical studies on reporting practices in recent years, which provide insights into the number of

companies disclosing environment-related information, the subject matter included in those disclosures,

the trend in overall disclosure over time and the general relationship between corporate characteristics and

the propensity to disclose environmentally relevant information.

However, much of the literature to date has been focused on the experience of companies in the

industrialised countries, mostly of Europe and the United States. In a developing economy like Korea,

which has been experiencing rapid economic growth, the improvement of material welfare still tends to

receive top priority. On the other hand, the growth of the Korean economy in recent years has accelerated

the expansion and globalization of business enterprises, which in turn, has induced increased societal

demands for a cleaner environment. A few cases of river pollution caused by effluents discharged by some

Korean firms during the early 1990s have caused even greater concern about the undesirable

environmental outcomes of unregulated development.

Increasing pressure from a variety of sources including a number of private pressure groups led to

extensive environmental legislation during the early 1990s, which includes the Basic Environment Policy

Act (BEPA hereafter) of 1990, the Liability for Environment Improvement Expenses Act (LEIEA) of 1991,

the Environmental Pollution Damage Dispute Adjustment Act (EPDDAA) of 1990, and the Natural

Environment Preservation Act (NEPA) of 1991 among others. Specifically, article 5 of the BEPA stipulates

that all enterprisers shall take for themselves measures necessary for preventing any environmental

pollution caused by their industrial activities, and are required to participate in and cooperate with the

environmental preservation policy of the state or local government.1

1 Article 7 of the same act stipulates as the liability of person causing pollution for expenses as follows: any

person who causes an environmental pollution due to his act or business activities, shall in principle bear theexpenses for the prevention of such pollution, recovery of the contaminated environment and relief of damages,which is in line with the PPP (Polluters Pay Principle) in vein.

The Korean Securities Exchange Commission (KSEC) followed suit by enacting in 1996 a provision

in the Corporate Accounting Standards (CAS) which requires the inclusion of environmental information

in the form of accompanying footnote to the corporate financial reports. The amendment of CAS was

mainly intended to incorporate the International Accounting Standards (IAS) into the Korean CAS so that

the comparability of financial statements can be enhanced. From the viewpoint of corporate social

responsibility, the most noteworthy aspect of the amended CAS is that it provided a valuable momentum

for the Korean companies to incorporate social and environmental perspectives into their formal financial

statements for the first time in the public accounting history of Korea. Article 90 of the amended CAS

recommends the voluntary disclosure of the following information in the footnotes attached to the financial

reports.2

Clause 21: The company's environmental standards and policies, safety and

accident related matters, environment-related investments,

consumption of resources and energy, and matters related to

occurrence and treatment of by-products and scraps.

In June 1997, a group of companies listed on the Korean Stock Exchange (KSE) provided

environmental and employee information in their 1997 audited semi-annual financial statements, which

was to be recorded as the first incidence of corporate social and environmental disclosure (CSED

hereafter) in Korea. This incidence of initial disclosures, however, draws attention in that it was initiated

by only a small group of companies (64 out of 770 companies listed on the KSE as of 1997) from a limited

number of industries (14 out of 37 intermediate level of KSE industry classifications).

The purpose of this study is to examine the nature of this first environmental disclosure by Korean

corporations in terms of quantity and quality of the disclosure. It thus provides the first empirical evidence

in Korea regarding the environmental disclosure in corporate financial statements. Furthermore, initial

disclosures made in semi-annual financial reports provide unique information vis-a-vis ritual annual

reporting. This is because the disclosure is made under less attention and scrutiny. Once a new accounting

practice is broadly accepted and exercised, it is likely that individual members of the accounting society

will follow industry convention and are more likely to be exposed to many external confounding

influences. As firms are exposed to a broader range of constituencies, they are more likely to be subject to

interlocking factors affecting their accounting policies in various ways.

It is therefore conjectured that the semi-annual financial reports provide more purified information

wherein the underlying motivators are more closely related to the voluntary CSED decisions. In this sense,

another contribution of this study lies in investigating contextual implications surrounding the often

controversial voluntary disclosure issues on the basis of a semi-annual financial reports. Although annual

2 Korean CAS rules footnote disclosures in a dual system. A considerable amount of footnotes should be

disclosed on a mandatory basis, while some others are up to the individual company's disclosure policy, whichis commonly referred to as "additional footnotes". A number of items have been added to the inventory of theadditional footnotes by the 1996 amendments, which notably include two other clauses with social connotation.For example, clause 18 of the same article refers to the inclusion of names of accounts and amounts ofmanufacturing costs and selling and administrative expense which are necessary in calculating "value added".Clause 23 mentions employee welfare and contributions to society. Therefore the amendment made in 1996,from the viewpoint of social and environmental accounting, was dominated by employee welfare issues alongwith environmental consideration in tenor.

disclosures have been a topic of interest for a number of years, few studies have dealt with semi-annual

disclosures to my knowledge.

Specifically this study addresses three questions. First, what is the general nature of the voluntary

environmental disclosure made in 1997? This evidence may indicate the degree of willingness and

initiatives exercised by Korean companies on the environmental disclosure issue. Second, what corporate

characteristics are significant in distinguishing a disclosing firm from its non-disclosing counterpart?

Third, what corporate characteristics are either positively or negatively related to the amount and/or the

degree of specificity of disclosure? The answers to the second and third questions would provide an

additional clue to the long unsettled issue of the determinants of voluntary CSED. Moreover, this study on

semi-annual corporate reporting would hopefully provide an insight to the issue of CSED that

complements the related studies on annual corporate reporting.

The rest of the paper is organized as follows. The following section provides an overview of the

corporate environmental reporting issue including related previous research. Next, the sample of firms and

the methodology employed are discussed, where a systematic method for quantifying the content of firms'

disclosures is developed. Results of both the measured content and the statistical analyses are then

presented. The final sections of the paper contain a general discussion of the results, followed by a

summary of the conclusions. The implications for Korean environmental accounting practices,

recommendation for further research, and limitations of the study are also discussed.

PREVIOUS RESEARCH

The theory of social and environmental accounting has recently been the subject of much debate among

researchers. By articulating various theoretical perspectives including agency theory, legitimacy theory,

political economy of accounting theory and stakeholder theory, a number of researchers have studied why

corporations should and do disclose social information. However, there does not exist a universally

accepted theoretical framework for corporate social and environmental accounting.3

Gray et al. (1995) recently classified and discussed much of the literature in three groups: decision

usefulness studies, economic theory studies, and social and political theory studies. Each of these three

groups relies on different theoretical arguments and implies different motives for the corporate social and

environmental disclosures. It is not clear, however, whether these three groups of theories offer

overlapping or competing explanations. As Hackston and Milne (1995) point out, serious doubts exist

whether the empirical evidence available to date is enough to establish the superiority of one theory over

the others.

The basic argument for the decision usefulness approach is that companies release information on their

social and environmental activities because traditional user groups, mostly shareholders and creditors, find

it useful for their investment decision making.4 For the economic theory approach, the basic argument

relies on Watts and Zimmerman's (1978) agency theory. To avoid potential pressure from government

regulatory agencies which enforce corporate social responsibility, companies increase voluntary corporate

3 One of the reasons for the lack of theoretical coherence would be that CSED is not practiced systematically by

organizations nor able to claim either universal recognition or universal definition, presumably because it is notsupported by legislation equivalent to Companies Acts.

4 See for example, Spicer (1978), Belkaoui (1980, 1984), Dierkes and Antal (1985), etc.

social disclosures.5 Government regulation is seen as costly and restrictive on business decision making.

Watts and Zimmerman (1978) suggest that these restrictions adversely affect management's wealth by

imposing the political costs of reduced flexibility in the adoption of potentially profit maximizing policies.

Corporations respond by employing a number of devices including social responsibility disclosure

campaigns to counter these government interventions.

In the social and political theory group, Gray et al. (1995) include stakeholder theory, legitimacy theory,

and political economy theory. They see these three theories not as separate nor competing. Rather

stakeholder theory and legitimacy theory are viewed as overlapping perspectives within the framework

of political economy assumptions (Gray et al., p. 11). The social and political theory seeks to explain the

organization-society relationship including social disclosure from a perspective different from that of

economic theory. Corporations make social disclosures not just for their own economic self-interests, but

because they are pressured to exhibit social responsibility by employees, customers, suppliers, the general

public and other social activist groups. Such disclosures can be viewed as a medium for managing,

negotiating or manipulating stakeholders without whose support and approval the organization can no

longer exist (Roberts, 1992). Such disclosures can also be viewed as a means of establishing or protecting

the legitimacy of an organization by influencing public opinion and the public policy process (Preston and

Post, 1975; Patten, 1991, 1992). Changes in society have rearranged priorities and the social impact of

corporations has become increasingly important to the public. Rather than adding to the debate on the most

appropriate method of accounting for social information, this study attempts to provide empirical evidence

supporting or rejecting some operational hypotheses derived from various existing studies. As this is the

first study of the kind undertaken in the Korean context, it is purely exploratory, avoiding to favour any

normative stance.

Based on the survey of studies on corporate social disclosure in the U.S., the U.K., Australia and New

Zealand, Hackston and Milne (1995) describe a general pattern in corporate social disclosure. The pattern

of disclosure appears to be consistent across all countries, with human resources, environment, and

community receiving most attention in the disclosure. The amount of disclosure is reasonably consistent

across companies in the US, the UK, and Australia. On the other hand, a number of studies focused on the

determinants of social disclosure. The determinants typically studied include company size, profitability,

industry, country of ownership, reporting country, capital intensity, senior executive attitudes, company age,

and the existence of company social responsibility committees. In reviewing these studies, Gray et al.

(1995) tentatively concluded as follows (Gray et al., 1995, pp. 49-50). CSED is not related to profitability

in the same period6, but it may be related to lagged profits.7 CSED does appear to be related to company

size.8 Industry appears to affect CSED, but the studies are not clear or consistent enough to precisely

determine such effects.9 The country in which the company reports, and the country of company ownership

5 See for example, Epstein et al. (1976), Trotman and Bradley (1981), Belkaoui and Karpik (1989) etc.6 A number of studies failed to find a statistically significant relationship between profitability and CSED, which

include Abbott and Monsen (1979), Belkaoui and Karpik (1989), Cowen et al. (1987), Freedman and Jaggi(1988), Ingram (1978) and Singh and Ahuja (1983), among others.

7 The evidence has been provided in Roberts (1992) for instance.8 When other factors were taken into consideration, however, the results were not without some reliability. See

for example, Andrews et al. (1989), Belkaoui and Karpik (1989), Cowen et al. (1987), Singh and Ahuja (1983),and Trotman and Bradley (1981).

9 See for example, Aupperle (1984), Beresford and Cowen (1979), Cowen et al. (1987), Freedman and Jaggi(1988), Singh and Ahuja (1983), and Zeghal and Amed (1990).

appear to be related to CSED.10 In addition, capital intensity (Belkaoui and Karpik, 1989), age (Roberts,

1992), senior executive attitudes, and social responsibility committee (Cowen et al., 1987; Roberts, 1992;

Trotman and Bradley, 1981) may be related to CSED.

DISCLOSURE PATTERNS

Sample and Methodology

The initial population of firms comprised all of the 64 companies in the 14 industries that disclosed

some amount of environmental information in the supplementary footnotes of their 1997 audited semi-

annual financial statements. The data gathered from the 64 firms were used to evaluate the pattern of

disclosure. At the same time, a pair of firms from the same industry were selected randomly, each pair

consisting of a discloser firm and a non-discloser. Data for evaluating voluntary environmental disclosure

were collected from the footnotes to the financial statements of the 64 discloser firms and the data on firm

specific charateristics of total 128 firms were obtained from the Handbook on Korean Listed Companies,

1997 Fall edition.

Content analysis was used to provide an evaluation of the disclosers' environmental disclosures. Content

analysis is a method of codifying the text or the content of a piece of writing into various groups or

categories based on selected criteria (Weber, 1988). It involves the selection of analytical categories within

the context of the content material.11 Variables are defined by identifying criteria which will allow any item

to be judged as either belonging or not belonging to a particular category. Categories must be defined as

precisely as practicable so that different researchers could be expected to apply them to the same messages

and arrive at the same results. Systematic categories result from the consistent application of a set of rules

so that results could be replicated. Each set of related categories should be exhaustive and mutually

exclusive and defined in such a way that identifying an item with a category is not a discretionary process.

Following coding, quantitative scales are derived for further analysis. An indexing procedure based on the

content analysis similar to ones used by Wiseman (1982) was constructed to evaluate the content of

environmental disclosure. The purpose of this procedure was to objectively measure the information

contained in the disclosure and to provide a systematic numerical basis for comparing companies'

disclosures across different firm characteristics.

Items of information to be included in the index were selected from Wiseman (1982), which were

considered essential for complete environmental disclosure.12 From the list of essential categories and

items of information compiled by Wiseman (1982), 16 items of information were selected for inclusion in

the index.13 A rating sheet was developed to measure the extent of disclosure of the 16 index items. The

10 See for example, Gray et al. (1987), Guthrie and Parker (1989, 1990).11 In one form or another, content analysis has been widely adopted in many previous social responsibility

disclosure studies. See for example, Abbot and Monsen (1979), Guthrie and Mathews (1985), Guthrie andParker (1990), etc. This study borrows from the indexing procedure adopted by Wiseman (1982) and Ingramand Frazier (1980) in particular.

12 Wiseman included those items of information in the index selected through a review of the environmentalreporting literature (Dierkes and Preston, 1977; Estes, 1976; CEP, 1975), which provided proposed formats forenvironmental reports including items considered essential for complete environmental disclosure.

13 Wiseman (1982) selected 18 items of information for inclusion in the index. Of the 18 items, however, 2 itemsrelating to environmental litigation were omitted in this study, because no data on these items were availablefrom the sample data.

items on the rating sheet were classified into three categories. Category one represented items directly

related to economic factors. Category two represented items related to pollution abatement. Category three

represented other environmentally relevant items which did not fall into any of the previous categories. A

list of the 16 items by category is presented below:

(1) Economic factors (EF)

Past and current expenditure for pollution control equipment and

facilities.

Past and current operating costs of pollution control equipment and

facilities.

Future estimates of expenditure for pollution control equipment and

facilities.

Future estimates of operating costs for pollution control equipment and

facilities.

Financing for pollution control equipment or facilities.

(2) Pollution abatement (PA)

Air emission information.

Water discharge information.

Solid waste disposal information.

Control, installations, facilities or processes described.

Compliance status of facilities.

(3) Other general information (GI)

Discussion of regulations and requirements.

Environmental policies or company concern for the environment.

Conservation of natural resources.

Awards for environmental protection.

Recycling.

Departments or offices for pollution control.

Rating of the disclosure was based on the presence or absence of the degree of specificity of each of the

information items. A score of three was assigned to an item if it was present in the disclosure and was

described in monetary or quantitative terms. A score of two was assigned to an item if it was present in the

disclosure with company specific information, but in non-quantitative terms. A score of one was assigned

to items mentioned only in general terms. A score of zero was assigned if the item was not present in the

disclosure. The scores of individual items in each category were added for three category scores (EF, PA

and GI), which in turn were added to yield the total score for each firm (SCORE). Since any rating

procedure is subject to a certain degree of arbitrariness, a rating sheet was completed independently by the

author and two other coders. Any disagreement was thoroughly examined and reconciled by careful re-

evaluation of the disclosure in question.14

14 The objectivity criteria for the categories can be verified by computing computing the coefficient of reliability

(Holsti, 1969), which is the ratio of the number of interjudge agreements to the total number of judgementsmade. Also, the index of reliability (Scott, 1955) can be used as a refinement of the the Holsti's coefficient. Theindex of reliability is computed as: IR=(OA-EA)/(1-EA), where OA is the percentage of observed agreement,

Also, as an alternative measure of the degree of sufficiency of disclosure, an ordinal scale was

developed. Based on the quantification, specificity and the amount of disclosure, a score between zero and

three was assigned to an individual firm as an overall measure for the evaluation of disclosure. A score of

three was assigned if the disclosure provided detailed factual information in monetary terms. The firms

belonging to this category are hereafter referred to as excellent disclosers. A score of two was assigned to

the disclosure which is quantitative in nature but lacks specificity. This category is referred to as good

discloser group. A score of one was assigned if the disclosure was qualitative overall but includes highly

condensed quantified measures. These firms are grouped as intermediate disclosers. A score of zero was

assigned if the disclosure is declarative and reflects only personal opinion, which is classified as poor

disclosure. This score is used as an alternative measure of disclosure and is referred to as LEVEL

throughout the paper. More specific definitions of the content categories used for this index are provided

below:

(1) Monetary (LEVEL=3): a disclosure expressing factual information concerning

a firm's environmental activities expressed in monetary terms.

(2) Quantitative (level=2): a disclosure expressing factual information

concerning a firm's environmental activities expressed in quantitative terms.

(3) Qualitative (level=1): a disclosure expressing factual information concerning a firm's environmental

activities expressed in qualitative terms.

(4) Declarative (level=0): a disclosure of opinion or unsupported declaration

concerning a firm's environmental activities.

Finally, the amount of disclosure per company is measured by the number of lines. In many earlier

studies, the total amount of disclosure per company was measured in numbers of pages, paragraphs,

sentences, words or by the proportion of the absolute amount of social disclosure to the total amount of

reports. However, Korean language differs from English in its sentence structure and/or the amount of

information conveyable by each word, sentence, or paragraph. Moreover the sample firms used in this

study disclosed only meager amount of information in general so that the absolute number of line counts

was considered adequate for objective inter-firm comparison purposes. This variable will be referred to as

LINES.

Evaluation of the Contents

The results from the descriptive analysis of the various measures defined in the previous section are

presented in Table 1 by industry type. The industry classification used for this study was based on the KSE

industry classifications. Following many earlier studies, I have divided the KSE industry categories into

high-profile and low-profile industries. Those industries identified as high profile include food and

beverage, pulp and paper, chemical, petroleum, rubber and plastics, non-metallic mineral, and basic metals

industries. The low profile category includes textile, leather, publishing, fabricated metal, machinery,

and EA is the percentage of expected agreement computed as the sum of squared proportion of the total itemsin each category. The coefficient was calculated to be 0.831, and the index of reliability was calculated as0.801. These results indicate that the categories selected for analysis were objective in the sense thatindependent judges could use them to arrive at similar decisions.

electronics, and wholesale industries.15 The columns labeled 'Mean' show individual category scores (EF,

PA, and GI), the total environmental disclosure index scores (SCORE) and the line count scores (LINES)

for each industry. The frequency of reporting incidence is shown in the columns labeled 'LEVEL'.

(Insert Table 1 About Here)

Several observations are immediate from Table 1. First, there appears to be a systematic relationship

between the nature of industry and CSED: the values of various measures of environmental disclosure are

consistently higher in high-profile than in low-profile subsample. This is consistent with common belief

that some industries are considered to feel greater pressure from government to provide information in

certain areas of social responsibility and thus are more likely to disclose in those areas to avoid attention

and scrutiny. Similarly, industries whose businesses have direct bearings upon environment such as those

in the high-profile category may be considered more likely to disclose environmentally relevant

information.

Second, there is a distinct lack of specificity in disclosed information. This is reflected not only in the

low frequency found in excellent (LEVEL=3) and good (LEVEL=2) categories but also in the extremely

low mean scores observed across the board. Since the highest score assigned to each of the 16 items used

for indexing was three, the maximum possible scores for the index categories of EF, PA, and GI are 15, 15,

and 18 respectively, and the maximum possible total score is 48 for SCORE. The mean values of SCORE

hardly exceed 7, with the highest score of 7.3 found in pulp and paper industry.

Third, the length of environmental disclosure is deemed to represent the quality of information disclosed.

This can be seen by comparing the values of LINES and SCORE. In terms of the amount disclosed, the

line counts exhibited a mean value of 7, which is roughly equivalent to one third of a page in typical

Korean semi-annual reports. The mean line counts for pulp and paper industry was 12.7, and the total

index score for the same industry had a mean value of 7.3, which was the highest of all industries. The

shortest disclosure was found in textile, publishing and fabricated metal industries, where the total index

scores were also relatively lower. This pattern of rough association between the length and the index score

of disclosure is consistent for firms in other industries as well.16

For a more formal comparison of the two industry categories, a parametric t-test and a non-parametric

Wilcoxon rank sum test were conducted. The results from these tests are provided in Table 2. The

association between the nature of industry and CSED is again confirmed. Table 2 shows that the scores for

various measures are significantly higher for high profile industries. A direct implication from this analysis

is that the industry type is an essential factor influencing CSED. Therefore a resonable basis for inference

would be to treat industry type as an inherent controller variable rather than as one of the potential

motivator variables when one investigates the determinants of the CSED.

(Insert Table 2 About Here)

15 This classification of industries is not without subjectivity. But the author made best efforts to reflect the

Korean context in terms of which industries can be expected to exhibit greater concern with environmentalissures when compared to the others.

16 Although not reported in Table 1, past and current expenditure for pollution control equipment and facilitieswas the item most frequently reported, followed by solid waste disposal information, and then environmentalpolicies or company concern for the environment.

DETERMINANTS OF ENVIRONMENTAL DISCLOSURE

HYPOTHESES AND VARIABLES

This section studies the relationship between environmental disclosure and corporate characteristics in

two steps. First, a series of tests are conducted to see if there is a significant difference in selected

attributes between discloser and non-discloser companies. Both parametric and nonparametric two sample

tests as well as logistic regressions are used. Second, for discloser companies, multiple sample tests and a

variety of regression models are adopted to test the association between relevant variables and various

index scores developed in the previous section.

Many of the previous studies on the determinants of CSED identify at least four groups of corporate

characteristics as having a certain degree of relationships with CSED. These are corporate financial

performance, firm size, stakeholder power and others. These motivator groups, however, may not

necessarily be mutually exclusive nor completely free from ambiguity. Nonetheless, in this exploratory

attempt to search for possible determinants of CSED, I choose these frequently used determinants along

with some additional variables deemed to reflect the Korean corporate disclosure context fairly well.

Coporate Financial Performance

The relationship between corporate financial performance and CSED is arguably one of the most

controversial issues yet to be resolved. Various arguments suggest conflicting implications. On the one

hand, some argue that there are significant additional costs and foregone profit opportunities to being

especially responsible, so that profitability is depressed.17 On the other hand, many contend that pursuing a

proactive social policy requires superior management and so more responsible companies are likely to

have more skillful management, hence better economic performance.18 Empirical research to date on the

profitability-CSED relationship also shows very mixed results. Bowman and Haire (1975), for instance,

report significant differences for a five year average return on equity between disclosing and non-

disclosing companies. Preston (1978) also finds a higher single-year return on equities for high disclosers

than for others. On the other hand, Cowen et al. (1987) failed to support any profitability-CSED

relationship. Belkaoui and Karpik's (1989) findings are more intriguing. They report a significantly

positive pairwise correlation, yet an insignificant, negative regression coefficient for return on assets and

disclosure. While Roberts (1992) has found evidence for a positive relationship between lagged profits and

CSED, Patten (1991) fails to find any relationship between profitability and CSED when multiple

measures of profitability including lagged profits are used.

In this study, financial performance was measured using various accounting and market indicators: (1)

net margin (NM: net profit before extraordinary items and taxes, as a percentage of sales), (2) return on

equity (ROE: after-tax profit as a percentage of the book value of stockholders' equity), (3) earnings per

share (EPS: after-tax profit divided by average number of common stocks outstanding), (4) cash flow per

share (CFPS: sum of after-tax profit and depreciation divided by average number of outstanding common

17 See for example, Bragdon and Marlin (1972), Vance (1975), Ullman (1976), Aupperle et al. (1985) among

others.18 See for example, Moskowitz (1972), Bowman and Haire (1975), Alexander and Buchholz (1978), and Spicer

(1978) etc.

stocks), (5) average price earnings ratio (PER: average of the highest and the lowest stock prices divided

by EPS), (6) sales growth rate (SGR: current year's sales minus previous year's sales as a percentage of

the latter), (7) profit growth rate (PGR: current year's after-tax profit minus previous year's profit as a

percentage of the latter). (8) reserve ratio (RES: cumulative retained earnings as a percentage of paid-in

capital). Following previous studies it is initially hypothesized that the higher the financial performance,

the more likely the company will disclose environmental information.

(H1) Profitability Hypothesis: Other things being equal, there is a positive

association between financial performance of a company and the propensity to

disclose environmental information.

Corporate Size

Various theories suggest a positive relationship between the firm size and CSED.19 Eilbert and Parket

(1973) argued that larger firms may simply be or feel themselves to be targets of attention and thus find it

necessary to make visible efforts to establish social responsibility credentials. According to the agency

theory of Watts and Zimmerman (1978), social responsibility disclosure campaigns can be used to reduce

political costs which otherwise could reduce management wealth. As the magnitude of political costs is

highly dependent on firm size, it is inferred that there will be a positive size-CSED relationship. Not all

empirical studies have supported a positive size-CSED relationship, however. Roberts (1992) found no

relationship with a U.S. sample nor did Davey (1982) and Ng (1985) with a sample from New Zealand.20

In previous studies, firm size has been typically measured by the number of employees, total asset value,

sales volume, or an index rank such as Fortune 500 although the former three are highly correlated. Given

that there is no theoretical reasoning in favor of any particular measure of size in disclosure studies, I have

chosen the following two variables: (1) number of employees (EMP: total number of employees including

executives as of the latest financial reporting date). (2) sales volume (SALE: net sales during the first

semi-annual accounting period of 1997 measured in 100 million won).

(H2) Size Hypothesis: Other things being equal, there is a positive association

between the size of a company and the propensity to disclose environmental

information.

Stakeholder Influence

A stakeholder is defined as any group or individual who can affect or is affected by the achievement of

the firm's objectives (Freeman, 1984). Stakeholders of the firm include stockholders, creditors,

employees, customers, suppliers, public interest groups and governmental bodies. The stakeholder theory

as initiated by Ansoff (1965) contends that the major objective of the firm is to attain the ability to balance

19 See for example, Kelly (1981), Trotman and Bradley (1981), Pang (1982), Cowen et al. (1987), Belkaoui and

Karpik (1989), Patten (1991, 1992), etc.20 Cowen et al. (1987) argues on the other hand, that larger companies (1) may have more shareholders

interested in corporate social activity, and (2) are more likely to use formal communication channels to relateresults of social endeavors to interested parties.

the conflicting demands of various stakeholders in the firm, a dynamic implication of which has been

further developed by Freeman (1983). Ullman (1985) proposed a conceptual model for studying

corporate social responsibility activities in a stakeholder framework, concluding that stakeholder theory

provides an appropriate justification for incorporating strategic decision making into studies of corporate

social responsibility activities. Based on the stakeholder theory, one could argue that, if social

responsibility activities including CSED are useful for satisfactory relationships with stakeholders, then

developing corporate reputation as being socially responsible through performing and disclosing social

responsibility activities is part of a strategic plan for managing stakeholder relationships.

This study considers four sources of stakeholder influence: owners, creditors, governmental bodies, and

auditors. The proxy variables used in this study to capture these stakeholder influence are as follows: (1)

owners' influence (OWN: percentage of outstanding common stocks held by major stockholders who own

1% or more of the stocks); (2) creditors' influence (LEV: total liability as a percentage of owners'

equity; INT: interests as a percentage of sales); (3) regulators' influence (SECT: assumes the value of 1 if

the company belongs to section 1 of KSE, and 0, otherwise; CHBL: assumes the value of 3 if the company

belongs to top 10 conglomerates, 2 if 11-30th largest conglomerates, 1 if remaining conglomerates, and 0

if independent); (4) auditors' influence (CPA: the relative size of the auditing firm in terms of the number

of client companies as of June 1997. The numbering scheme follows: 1 = Samil, 2 = Ankeon, 3 = Chungun,

4 = Sandong, 5 = Younghwa, 6 = Samdeok, 7 = Seidong, 8 = Sinhan, 9= Ahnjin, and 10 = others). For

each of these proxy variables, hypotheses regarding the relationship with CSED are developed below.

Keim (1978) augues that, as the distribution of ownership of a corporation becomes less concentrated,

the demands placed on the corporation by shareowners become broader. Disperse corporate ownership,

especially by investors concerned with corporate social activities, increases pressure for management to

disclose social responsibility activities. Therefore it is hypothesized that the wider the dispersion of

corporate ownership, the better the corporation's social responsibility disclosures.

(H3) Owner's Influence Hypothesis: Other things being equal, there is a negative

association between percentage of ownership held by principal shareholders and

the propensity to disclose environmental information.

Creditors control access to financial resources that may be essential for continued operation of a

corporation. This is especially true in Korea as the long history of fund shortage has had significant

influence on its accounting practice. It could be argued then that the greater the corporation's reliance on

debt financing, the greater the degree to which corporate management would be expected to respond to

creditor expectations concerning the corporation's role in social responsibility activities (Ullman, 1985).

Under the assumption that creditors exhibit serious concern about the social and environmental

responsibility of Korean companies, the variables LEV and INT are expected to have a positive

relationship with the level of CSED.

(H4) Creditors' Influence Hypothesis: Other things being equal, there is a

positive association between creditors' influence and the propensity to

disclose environmental information.

Whether one relies on the stakeholder theory of Freeman (1984) or the political costs theory by Watts

and Zimmerman (1978), one can reach a general conclusion that firms may use social responsibility

disclosures to satisfy government demands. While Korea had a long tradition of close and mutually

beneficial relationship between large corporations and government, such implicit entitlements are

gradually disappearing. Since the early 1990s, the larger corporations in Korea, or chaebols became to be

pointed at as a major culprit for the unfair distribution of wealth and a stumbling block to the restructuring

of domestic economy. Accordingly, a certain degree of tensions and conflicts cave in between the

government and businesses, justifying either of the above theories to describe the government-business

relationship. In many previous studies, corporate size has often been used as a proxy for political exposure,

but subject to criticism that it is correlated with many other corporate characteristics. Therefore this study

uses the relative size of the chaebol group to which an individual company belongs as a proper proxy for

political exposure. As a supplementary proxy for the degree of political exposure, SECT variable is also

used - companies belonging to the first section of KSE are in general under tougher regulation than those

in the second section. It could then be hypothesized that CHBL and SECT are expected to have a positive

relationship with the level of CSED.

(H5) Government's Influence Hypothesis: Other things being equal, there is a

positive association between a government's regulatory influence and the

propensity to disclose environmental information.

It is needless to say that auditors play an important role for a company's accounting policy, especially in

initiating new accounting practices. Moreover, it is believed to be an important responsibility of auditors to

recommend their client companies to practice socially responsible accounting policies. For fair and

impartial audit opinions, the auditor independence is crucial. Since the auditor-firm match in Korea is

generally determined by a free choice contracting system whereby firms can choose auditors or audit firms

freely, it is often criticized to have negative impact on auditor independence. The fixed audit fee often

determined by the asset size of a client company, it is argued, may further impair the audit quality. If we

accept that larger audit firms are less subject to the influence from clients, then one could argue that larger

audit firms are in a position to exercise more discretion over the accounting policies of their client firms. It

is thus hypothesized that companies under the contract with larger audit firms are likely to disclose more

environmental information.

(H6) Auditor's Influence Hypothesis: Other things being equal, there is a positive

association between the auditor's relative independence as measured by the

size of audit firm and the propensity for a client company to disclose

environmental information.

This study also considered several other control variables used in a number of previous studies and

deemed relevant for the enhancement of interpretability. The first one is the systematic risk measured by

market-model measure of beta (BETA). Corporations with lower systematic risk are expected to have

higher levels of CSED for at least two reasons. First, a lower systematic risk implies a more stable pattern

of stock market returns, which could enhance a firm's involvement in social responsibility endeavors.

Second, because social responsibility activities may improve a firm's access to capital and increase

employee morale and productivity (Moskowitz, 1972; McGuire et al., 1988), market participants may view

socially responsible firms as better managed and thus, less risky (Roberts, 1992).

(H7) Systematic Risk Hypothesis: Other things being equal, there is a negative

association between the systematic risk of companies and the propensity to

disclose environmental information.

The second one is the age of corporation as measured by the number of years of operation since

foundation (AGE). The more mature a corporation is, the higher can be the value of reputation and the

history of involvement in social responsibility activities. As the opportunity cost of socially irresponsible

activities could be dear for mature firms, it thus follows that AGE is expected to be positively related to

CSED.

(H8) Corporate Age Hypothesis: Other things being equal, there is a positive

association between a corporation's age and the propensity to disclose

environmental information.

The last variable is foreign customers' influence as measured by the amount of sales exported as a

percentage of total sales realized during the first half of 1997 (EXP). As the larger proportion of sales is

exported, the company is exposed to a broader spectrum of stakeholder influences from abroad. Given the

ever intensifying trend of pro-environmental international regulations, the influence from foreign

customers is likely to lead to more proactive corporate initiatives with respect to the environmental issues.

(H9) Foreign Influence Hypothesis: Other things being equal, there is a positive

association between foreign influence and the propensity to disclose

environmental information.

A complete description of the variables used in the subsequent analyses is in Table 3.

(Insert Table 3 About Here)

ANALYSES AND RESULTS

Discriminating Disclosers from Non-disclosers

The first step of analyses is the dichotomous comparison of corporate characteristics between discloser

and non-discloser samples. Two procedures were used to test whether the selected corporate characteristic

variables are associated with the voluntary CSED decisions of the sample firms. First, both parametric and

non-parametric two sample tests were carried out to determine statistical significance of the differences in

mean raw and rank scores between discloser and non-discloser samples. Second, logistic regression

analyses were used to determine whether the decision to disclose was related to selected corporate

characteristic variables. The dependent variable used in these procedures is defined as follows:

DISC=1 if a discloser, 2 if a non-discloser.

Following the hypotheses developed in previous sections, the disclosing companies are expected to have

on average (1) better financial performance, (2) larger company size, (3) more stakehoders' influence, (4)

lower systematic risk, and (5) longer corporate history than their non-disclosing counterparts. Two

complementary univariate tests were used initially to test these hypotheses: (1) a parametric two sample t-

test for the statistical significance of the difference in means of the variables for the two samples in

question; (2) a non-parametric Wilcoxon rank sum test for the comparison of the magnitude of the rank

sums of the variables for the two samples. Additional preliminary studies of the independent variables

showed that the distributions of most size variables and profitability-related variables were markedly

nonnormal as confirmed by Shapiro Wilks' W statistics. Given this nonnormality and the presence of

ordinally scaled variables such as SECT, CPA, and CHBL, nonparametric test results are presented along

with parametric test results in all subsequent analyses. If these two statistical tests yield essentially

equivalent results, then greater confidence can be placed upon the results of the tests than if only one test

was used. In those cases where they produce inconsistent results, priority will be given to the

nonparametric evidence, considering the existence of possible outliers.

Table 4 presents the t statistics as well as Z statistics obtained by comparing the relative magnitude of

the independent variables between the two subsamples. The significance level associated with each

statistic is represented by the superscript asterisk symbol. With a few exceptions, most of the hypothesized

relationships were confirmed, although it was not possible to reject the null hypothesis of no difference in

many cases. The variables SGR, EMP and SALE exhibited siginificance in the predicted direction,

whereas the CPA variable showed an opposite sign in the t-test. However, the results for EMP, SALE and

CPA are not consistently significant across the parametric and nonparametric tests. This evidence suggests

that, relative to non-disclosing counterparts, the disclosers have higher sales growth rates and are larger in

size as measured by the number of employees and sales volume. However, the relative size of audit firms

are, on average, smaller for the discloser firms than nondisclosers.

(Insert Table 4 About Here)

Multiple logistic regressions were used next to examine the multivariate association between the

dichotomous disclosure variable and potential determinant variables. The first step in this procedure,

however, was to reduce the set of independent variables to a set of uncorrelated variables. Multicollinearity

would not be a problem in analyzing the descriptive statistics to determine the significant predictor

variables, but could diminish the statistical significance of individual variables under the context of

hypothesis testing. Using varimax rotated factor analysis, six factors with the eigen values greater than 1.0

were identified which significantly explained intercorrelations in the 19 variables, accounting for 74.2

percent of the total variance. Factor loadings greater than 0.40 are shown in Table 5. It is apparent that

factors 1 through 6 represent profitability, size, financial stability, export, growth and outsider influence,

respectively. The highest loading variable in each factor, as are indicated by superscipt asterisk symbols -

ROE, SALE, RES, EXP, SGR, and CPA -, was used in the subsequent multiple logistic analysis.

(Insert Table 5 About Here)

Table 6 shows the results of the logistic regression analysis. Three sets of regression models were run

which included regressions based on original scores, rank scores and factor scores. The regression results

presented in the table were obtained first by including all six variables as predictors (M1, M6, and M11),

then by including profitability and size-related variables in three possible combinations (M2, M7, M12

include both; M3, M8, M13 include profitability only; M4, M9, M14 include size only), and finally by

performing stepwise procedure for variable selection (M5, M10). Special attention has been paid to the

profitability and size variables, as these were among the most frequently examined variables in earlier

studies. The results presented in the three panels of Table 6 are not always consistent, however. As

mentioned earlier, more emphasis is thus given to the results based on rank scores test which is essentially

nonparametric. Parameter estimates are accompanied by corresponding chi-square statistics in the brackets

below each variable. The -2 log likelihood chi-square statistics evaluating the overall significance of the

model are shown in the last column.

The noteworthy variables are SALE, SGR and CPA, each representing corporate size, financial

performance, and auditor's influence respectively. Again, size and financial performance as measured by

sales volume and sales growth rate are significantly positively associated with DISC as hypothesized, but

audit firm's size is negatively associated contrary to the hypothesis. The traditional profitability variable

ROE only weakly supports the positive profit-CSED relationship. One possible explanation for the results

might be that sales rather than profits tend to play a major role as an important indicator for financial

success of companies in Korea. Therefore it might be concluded that financial performance, especially

when a company is growing rather than stable, affects environmental disclosure decisions in some ways.

Size effect looks relatively evident, even though size could act as a surrogate for many other factors. It is

not clear, however, whether or not this is because of greater public pressure upon larger firms as suggested

by legitimacy theory and/or political cost theory. The propensity of larger firms to disclose more

environmental information might be a reflection of superior system and quality of management or simply

due to inertia to provide whatever information more. One needs, therefore, to exercise due caution to

interpret the above results as a confirming evidence in favor of either agency or stakeholder theories.

The results from CPA variable warrant explanations. Given that Korean business society still tends to

emphasize the importance of immediate material wealth rather than social issues, the winners in the

Korean business arena might well be those placing more importance on economic performance. And

corporate social concerns are likely to be monitored through public-policy arena rather than through the

market place. Moreover, larger audit firms are the winners in this highly competitive Korean audit service

market under the free choice contracting system. The negative impact on auditor independence of the

Korean audit practice together with the short history of environmental disclosure practice could imply that

the major audit firms might have tended to neglect the potential importance of social and environmental

responsibility of business enterprises. This explanation, of course, is subject to the limitation that the

current analysis dealt only with the initial environmental disclosure in semi-annual reports. Being a little

bit slow in responding may not necessarily mean a lack of understanding nor willingness.

(Insert Table 6 About Here)

Association of Corporate Characteristics with the Level of Environmental Disclosure

The next step of analysis consists basically of replicating the first step using only the discloser

subsample. In the initial phase of the analysis, LEVEL instead of DISC was used as the dependent variable

to determine the univariate association between firm specific characteristics and the level of environmental

disclosure. Since LEVEL has four ordinal levels, parametric one-way ANOVA and nonparametric

Kruskal-Wallis tests were used in lieu of the two sample tests. The results from both tests are shown in

Table 7. However, there does not exist any clear evidence supporting hypothesized relationships between

the potential determinants and the level of disclosure. One exception was the nonparametric test results for

PER of which value monotonically decreased as the level of disclosure declined. None of the remaining

variables showed statistical significance nor were the patterns consistent with hypotheses.

(Insert Table 7 About Here)

In order to apply multiple regressions as the next phase of the analysis, varimax rotated factor analysis

was applied to reduce the set of independent variables as in the previous analysis. The results of the factor

loading pattern are presented in Table 8. Again six factors were identified by the selection criterion of

minimum eigen value of 1.0 or greater. They explained 76.5 per cent of the intercorrelations in the 19

variables included in the analysis. Factors 1 through 6 were interpreted to represent profitability, size,

financial structure, growth, reserve, and stakeholder influence respectively. The highest loading variable

from each factor - ROE, SALE, LEV, SGR, RES, and CPA - was used in a variety of subsequent regression

analyses. While the other variables were highly correlated with one or another of these six, the six

variables were not intercorrelated, thus avoiding the potential multicollinearity.

(Insert Table 8 About Here)

A couple of multiple regression approaches were employed as follows. First, based on both the original

scores and rank scores, generalized logit models were estimated for the dichotomous PROFILE variable

and the variables representing each factor as suggested from the above factor analysis. For these

regressions, LEVEL was used as a dependent variable. The inclusion of PROFILE as an extra independent

variable was to recheck the industry effect. Next, OLS stepwise regression models were estimated by high

and low-profile industry types. For these regressions, SCORE, LINES and LEVEL were used as

alternative dependent variables while all of the 19 independent variables were transformed into rank scores.

Rank transformation was intended to avoid possible violation of classical OLS regression assumptions due

to the skewness of the sample distribution or the existence of outliers in the original variables included.

The results from the logistic tests are provided in Table 9, and those from stepwise regressions are shown

in Table 10.

From Table 9, it is evident that the industry classification is a significant explanatory variable. High-

profile industries reveal consistently better environmental information vis-a-vis low-profile industries. The

results for all other variables are either mixed or ambiguous, however. SALE exhibits only a weak support

for the size hypothesis while RES is significant in the direction opposite to the hypothesized relationship.

This ambiguity could have been due to the inadequacy of LEVEL as a proxy for the quality of disclosure.

It thus seems necessary to have further evidence based on a variety of other variables as a proxy for the

level of disclosure.

(Insert Table 9 About Here)

A stepwise regression is a shortcut in arriving at a parsimonious model when one has to choose a best

possible combination of independent variables in the absence of well-specified theoretical foundation. It is

generally believed that the stepwise regression provides an optimal regression model by selecting relevant

independent variables from a large set of candidates in a way to minimize the loss of information while

simplifying the model specification. As noted earlier, industry type was deemed to serve as an inherent

controller rather than as an independent variable. Thus the discloser subsample was further partitioned into

high and low-profile subgroups for each of which a stepwise regression was run independently. The results

are summarized in Table 10.

For the high-profile subgroup, LEV and CPA are found to be the best possible choice of independent

variables among 19 variables considered. The coefficient estimates exhibit expected signs and the

regression model resulted in the highest statistical significance when line counts were used as the

dependent variable. The significance of LEV supports the contention that environmental disclosures may

be viewed by management as a way of fulfilling creditor expectations. Also, the significance of CPA,

albeit weak, supports the proposition that, in high-profile industries at least, larger audit firms are aware of

the importance of environmental issues, presumably in light of more pressures from creditors. It might well

be that the creditors of the companies in pollution-prone industries are more sensitive to potential

environmental contingencies and as such, the auditors of these companies may have tendency to

recommend their clients to provide improved environmental disclosure.

The regression results obtained from low-profile industries depict different picture. The variables LEV

and AGE, along with the two economic performance variables RES and EPS are found to be statistically

significant. While the same line of logic may hold for LEV, the significance of AGE may be explained in

part by the argument that age is a macro-level proxy for stakeholder influence, or economic performance.

As for RES and EPS, the results are conflicting, which needs further exploration. In sum, one important

finding from the above results is that the high and low-profile industries exhibit differential behaviour with

respect to the relationship between the firm characteristics and the amount and/or the specificity of

environmental disclosures.

(Insert Table 10 About Here)

SUMMARY AND DISCUSSIONS

Using the initial voluntary CSED experience in Korea, this paper has studied the relationship between

various firm characteristics and the quality and quantity of environmental disclosure. Three main findings

emerged: (1) Although no attempt has been made in this study to compare the index measures of

environmental disclosure with the actual environmental performance evaluated by any reliable outside

parties, the initial voluntary environmental disclosure was largely incomplete, providing self-serving,

inaccurate accounts of corporate environmental performance. Consistent with many other studies, however,

the type of industry was shown to be significantly related to both the quality and the quantity of

disclosure. The firms in high profile industries disclosed systematically more and better information than

their counterparts in low-profile industries.

(2) When the type of industry was controlled to discriminate discloser firms from nondisclosers, it was

found that firm size and auditors' influence are significantly associated with disclosure decisions, while

financial performance showed only weak and sporadic evidence in support of the positive relationship.

Corporate size was found to be positively associated with the propensity to disclose, whereas the relative

size of auditing firms was negatively associated, which contradicts the implication of the stakeholder

theory. Sales growth rate was also found to be moderately associated with the disclosure decisions.

(3) When the analysis was confined within the discloser group only, financial leverage and corporate age

emerged as significant variables for the level of environmental disclosure. As for high-profile industries,

leverage ratio was found to be the single most important explanatory variable, implying that the creditors'

influence matters for corporate environmental disclosure in this type of industry. In low profile industries,

it was found that as corporate age increases, the quality of environmental disclosure tends to improve as

well.

It is to be cautioned, however, that these findings are subject to the limitations of this study. Not only

was only a limited amount of sample available, but also the fact that this was the first voluntary CSED

experience in Korea might have resulted in poor quality and quantity of overall disclosure. The latter is

even more confounded by the voluntary nature of disclosure. It is conceivable that a majority of Korean

listed firms decided to wait rather than take proactive measures from the very inception. Earlier studies on

the experience of other countries suggest similar difficulties. For example, in their study of environmental

disclosure practice in earlier periods of the U.S., Ingram and Frazier (1980) found only a weak association

between quantitative measures of disclosure content and independent measures of performance. They

argued that because management is free to use its own discretion in selecting information to be reported, it

is possible for poorer performers to bias their selections in order to appear like the better performers.

Similarly, Wiseman (1982) concluded that voluntary environmental disclosures were incomplete,

providing inadequate information for most of the environmental performance items, and that no

relationship existed between the measured contents of the firm's environmental disclosure and

environmental performance. It may be thus rash to assume that the findings from these study may be

generalized to future experience.

It is also important to note that the interpretation of the results is conditional on the assumption that the

proxy variables used are reliable indicators of the determinants underlying corporate environmental

disclosure decisions. Despite extensive efforts made to enhance the accuracy of proxy variables, data

availability might have limited their validity. For example, Herremans at al. (1993) suggest that they have

found a positive relationship between reputation for social responsibility and profitability over an extended

period of time rather than over a contemporaneous period. Roberts (1992) reports a lagged relationship

between economic performance and the level of social disclosure. These problems are hoped to be

resolved in future research as more data become available.

A final point is the discrepancy between empirical findings and theoretical predictions. While

considerable efforts were made to derive testable hypotheses from various theories, a closer look at the

theories and empirical evidence reveals a significant gap between them. For example, size appears to be

related to environmental disclosure, yet as argued by Hackston and Milne (1995), it is not clear whether

this is evidence for agency theory, legitimacy theory, both theories or neither of these. Therefore, this study

did not attempt to draw any inference from empirical evidence in support of or against existing

explanations for social and environmental disclosures.

Despite these limitations, this study could provide some preliminary evidence on corporate

environmental reporting practice. A continued research in this line based on further evidence seems

essential for any generalized picture about the long-term trend of the CSED practice and the possible

association between potential determinants and the level of CSED practice in Korea.

REFERENCES AND FURTHER READING

Abbott, W. F. and Monsen, R. J. (1979), "On the measurement of corporate social responsibility: self-reported disclosures as a method of measuring corporate social involvement", Academey ofManagement Journal, Vol. 22 No. 3, pp. 501-515.

Alexander, G. and Buchholz, R.. (1978), "Corporate social responsibility and stock marketperformance", Academy of Management Journal, pp. 479-486.

Andrews, B. H., Gul, F. A., Guthrie, J. E. and Teoh, H. Y. (1989), "A note on corporate socialdisclosure practices in developing countries: the case of Malaysia and Singapore", BritishAccounting Review, Vol. 21 No. 4, pp. 371-376.

Ansoff, I. (1965), Corporate Strategy, New York, McGraw-Hill.Aupperle, K. E. (1984), "An empirical measure of corporate social orientation", Research in Corporate

Social Performance and Policy, Vol. 6, pp. 27-54.Aupperle, K. E., Carrol, A. R., Archie, B. and Hatfield, J. D. (1985), "An empirical examination of

the relationship between corporate social responsibility and profitability", Academy ofManagement Journal, pp. 446-463.

Belkaoui, A. (1980), "The impact of socio-economic accounting statements on the investmentdecision: an empirical study", Accounting, Organizations and Society, Vol. 5 No. 3, pp. 263-283.

Belkaoui, A. (1984), Socio-economic Accounting, Quorum Books, Connecticut.Belkaoui, A. and Karpik, P. G. (1989), "Determinants of the corporate decision to disclose social

information", Accounting, Auditing & Accountability Journal, Vol. 2 No.1, pp. 36-51.Beresford, D. R. and Cowen, S. S. (1979), "Surveying social responsibility disclosure in annual

reports", Business, Vol. 29 No. 2, pp. 15-20.Bowman, E. H. and Haire, M. (1975), "A strategic posture towards corporate social responsibility",

California Management Review, Winter, pp. 49-58.Bragdon, J. H. Jr. and Marlin, A. T. (1972), "Is pollution profitable?", Risk Management, April, pp. 9-

18.Council on Economic Priorities (1975), The CEP Report, New York: CEP.Cowen, S. S., Ferreri, L. B. and Parker, L. D. (1987), "The impact of corporate characteristics on

social responsibility disclosure: a typology and frequency-based analysis", Accounting,Organizations, and Society, Vol. 12 No. 2, pp. 111-122.

Davey, H. B. (1982), "Corporate social responsibility disclosure in New Zealand: an empiricalinvestigation", Unpublished Working Paper, Massey University, Palmerston North, NewZealand.

Dierkes, M. and Antal, A. B. (1985), "The usefulness and use of social reporting information",Accounting, Organizations and Society, Vol. 10 No. 1, pp. 29-34.

Dierkes, M. and Preston, L. (1977), "Corporate social accounting reporting for the physicalenvironment: a critical review and implementation proposal", Accounting, Organizations andSociety, pp. 3-22.

Eilbert, H. and Parket, I. R. (1973), "The current status of corporate social responsibility", BusinessHorizons, Vol. 16 No. 4, pp. 5-14.

Epstein, M. and Flamholtz, E., and McDonough, J. J. (1976), "Corporate social accounting in theUnited States of America: state of the art and future prospects", Accounting, Organizationsand Society, Vol. 1 No. 1, pp. 23-42.

Estes, P. (1976), "Standards for corporate social reporting", Management Accounting, November, pp.19-22.

Freeman, R. (1983), "Strategic management: a stakeholder approach", Advances in StrategicManagement, pp. 31-60.

Freeman, R. (1984), Strategic Management: A Stakeholder Approach, Marshall, MA: Pitman.Freedman, M. and Jaggi, M. (1988), "An analysis of the association between pollution disclosure and

economic performance", Accounting, Auditing & Accountability Journal, Vol. 1 No. 2, pp.43-58.

Gray, R. (1992), "Accounting and environmentalism: an exploration of the challenge of gently

accounting for accountability, transparency and sustainability", Accounting, Organizations andSociety, Vol. 17 No. 3, pp. 399-425.

Gray, R., Owen, D. and Maunders, K. (1987), Corporate Social Reporting: Accounting &Accountability, Prentice-Hall, Hemel Hempstead.

Gray, R., Owen, D. and Maunders, K. (1988), "Corporate social reporting: emerging trends inaccountability and the social contract", Accounting, Auditing & Accountability Journal, Vol. 1No. 1, pp. 6-20.

Gray, R., Kouhy, R. and Lavers, S. (1995), "Corporate social and environmental reporting: a reviewof the literature and a longitudinal study of UK disclosure", Accounting, Auditing &Accountability Journal, Vol. 8 No. 2, pp. 47-77.

Guthrie, J. and Mathews, M. R. (1985), "Corporate social accounting in Australasia" in Lee, E.Preston (ed), Research in Corporate Social Performance and Policy, Vol. 7, pp. 251-277.

Guthrie, J. and Parker L. D. (1989), "Corporate social reporting: a rebuttal of legitimacy theory",Accounting and Business Research, Vol. 19 No. 76, pp. 343-352.

Guthrie, J. and Parker L. D. (1990), "Corporate social disclosure practice: a comparative internationalanalysis", Advances in Public Interest Accounting, Vol. 3, pp. 159-175.

Hackston, D. and Milne, M. J. (1995), "Some determinants of social and environmental disclosures inNew Zealand companies", paper presented at the First Asian Pacific InterdisciplinaryResearch in Accounting Conference, Sydney, Australia.

Herremans I. M., Akathaporn, P. and McInnes, M. (1993), "An investigation of corporate socialresponsibility reputation and economic performance", Accounting, Organizations and Society,Vol. 18 No. 7/8, pp. 587-604.

Holsti, O. R. (1969), Content Analysis for the Social Sciences and Humanities, London, Addison-Wesley.Ingram, R. W. (1978), "An investigation of the information content of (certain) social responsibility

disclosure", Journal of Accounting Research, Vol. 16 No. 2, pp. 270-285.Ingram, R. W. and Frazier K. B. (1980), "Environmental performance and corporate disclosure",

Journal of Accounting Research, Vol. 18 No. 2, pp. 614-622.Keim, G. (1978), "Managerial behavior and the social responsibilities debate: goals versus

constraints", Academy of Management Journal, pp. 57-68.Kelly, G. J. (1981), "Australian social responsibility disclosure: some insights into contemporary

measurement", Accounting and Finance, Vol. 21 No. 2, pp. 97-104.Lewis N. R. and Mangos, N. C. (1995), "Investigating the relationship between social disclosure and

corporate economic performance in Australia: environmental stakeholder power andUllmann'a contingency framework", paper presented at First Asian Pacific InterdisciplinaryResearch in Accounting Conference, Sydney, Australia.

Mangos, N. C. and Lewis, N. R. (1995), "A socio-economic paradigm for analysing managers'accounting choice behaviour", Accounting, Auditing & Accountability Journal, Vol. 8 No. 1, pp.38-62.

McGuire, J., Sundgren, A. and Schneeweis, T. (1988), "Corporate social responsibility and firmfinancial performance", Academy of Management Journal, December, pp. 854-872.

Moskowitz, M. R. (1972), "Choosing socially responsible stock", Business and Society Review, pp.71-75.

Ng, L. W. (1985), "Social responsibility disclosures of selected New Zealand companies for 1981,1982 and 1983", Occasional Paper No. 54, Massey University, Palmerston North, NewZealand.

Pang, Y. H. (1982), "Disclosures of corporate social responsibility", The Chartered Accountant inAustralia, July, pp. 32-34.

Patten, D. M. (1991), "Exposure, legitimacy, and social disclosure", Journal of Accounting and PublicPolicy, Vol. 10, pp. 297-308.

Patten, D. M. (1992), "Intra-industry environmental disclosures in response to the Alaskan oil spill: anote on legitimacy theory", Accounting, Organizations and Society, Vol. 17 No. 5, pp. 471-475.

Preston, L. E. (1978), "Analysing corporate social performance: methods and results", Journal ofContemporary Business, pp. 135-149.

Preston, L. E. (1981), "Research on corporate social reporting: directions for development",

Accounting, Organizations and Society, Vol. 6 No. 3, pp. 95-111.Roberts, R. W. (1992), "Determinants of corporate social responsibility disclosure", Accounting,

Organizations and Society, Vol. 17 No. 6, pp. 595-612.Rubenstein, D. B. (1992), "Bridging the gap between green accounting and black ink", Accounting,

Organizations and Society, Vol. 17 No. 3, pp. 501-508.Scott, W. A. (1955), "Reliability of content analysis: the case of nominal scale coding", Public

Opinion Quarterly, Vol. 19, pp. 321-325.Singh, D. R., and Ahuja, J. M. (1983), "Corporate social reporting in India", International Journal of

Accounting, Vol. 18 No. 2, pp. 151-170.Spicer, B. H. (1978), "Investors, corporate social performance and information disclosure: an

empirical study", The Accounting Review, Vol. 53 No. 1, pp. 94-111.Spicer, B. H. (1980), "The relationship between pollution control record and financial indicators

revisited: further comment", The Accounting Review, Vol. 55 No. 1, pp. 178-185.Teoh H. Y. and Thong, G. (1984), "Another look at corporate social responsibility and reporting: an

empirical study in a developing country", Accounting, Organizations and Society, Vol. 9 No. 2,pp. 189-206.

Tilt, C. A. (1994), "The influence of external pressure groups on corporate social disclosure: someempirical evidence", Accounting, Auditing & Accountability Journal, Vol. 7 No. 4, pp. 47-72.

Tilt, C. A. (1995), "Corporate environmental policies: Australian evidence", paper presented at FirstAsian Pacific Interdisciplinary Perspectives in Accounting Conference, Sydney, Australia.

Trotman, K. T. and Bradley, G. W. (1981), "Associations between disclosure and characteristics ofcompanies", Accounting, Organizations and Society, Vol. 6 No. 4, pp. 355-362.

Ullman, A. E. (1976), "The corporate environmental accounting system: a management tool forfighting environmental degredation", Accounting, Organizations and Society, pp. 71-79.

Ullman, A. E. (1985), "Data in search of a theory: a critical examination of the relationships amongsocial performance, social disclosure and economic performances of US firms", Academy ofManagement Review, Vol. 10 No. 3, pp. 540-557.

Vance, S. C. (1975), "Are socially responsible corporations good investment risks?" ManagementReview, August, pp. 18-25.

Watts, R. L. and Zimmerman, J. L. (1978), "Towards a positive theory of the determination ofaccounting standards", The Accounting Review, Vol. 53 No. 1, pp. 112-134.

Weber, R. P. (1988), Basic Content Analysis, Sage University Paper Series on QuantitativeApplications in the Social Sciences, Series No 07-049, Beverley Hills and London, SagePublications Inc.

Wiseman, J. (1982), "An evaluation of environmental disclosures made in corporate annual reports",Accounting, Organizations and Society, Vol. 4 Nos 1/2, pp. 123-133.

Yamagami, T. and Kokubu, K. (1991), "A note on corporate social disclosure in Japan", Accounting,Auditing & Accountability Journal, Vol. 4 No. 4, pp. 32-39.

Zeghal, D. and Ahmed, S. A. (1990), "Comparison of social responsibility information disclosuremedia used by Canadian firms", Accounting, Auditing & Accountability Journal, Vol. 3 No. 1,pp. 38-53.

TABLE 1. Environmental Disclosure Index Scores by Industry TypeIndustries Proportion of

disclosersEF PA GI SCORE LEVEL LINES

Mean(S.D.)

Mean(S.D.)

Mean(S.D.)

Mean(S.D.)

3 2 1 0 Mean(S.D.)

Panel A: Low-Profile Industriestextile 1/49 0.0

(n.a)3.0

(n.a.)0.0

(n.a.)3.0

(n.a.)0 0 1 0 2.0

(n.a.)leather 2/11 1.5

(2.12)2.5

(2.12)0.0

(0.00)4.0

(0.00)0 0 2 0 5.0

(1.41)publishing 1/3 0.0

(n.a.)0.0

(n.a.)1.0

(n.a.)1.0

(n.a.)0 0 0 1 2.0

(n.a.)fabricated

metal3/14 2.0

(1.73)1.0

(1.00)0.3

(0.58)3.3

(2.52)0 0 2 1 3.7

(2.89)machinery 6/28 1.0

(1.55)1.5

(0.84)1.3

(1.21)3.8

(2.56)0 1 4 1 9.0

(4.64)electronics 5/59 2.4

(2.51)1.0

(1.41)1.0

(0.71)4.4

(3.20)0 1 4 0 9.0

(4.64)wholesale 2/36 1.5

(2.12)1.0

(1.41)2.0

(2.83)5.0

(5.66)0 1 0 1 7.0

(5.66)Subtotal 20/248 1.5

(1.82)1.4

(1.23)1.0

(1.15)3.9

(2.64)0 3 13 4 6.0

(3.90)Panel B: High-Profile Industries

foods &beverages

11/48 2.9(1.94)

2.3(2.10)

1.4(1.36)

5.4(3.88)

2 1 8 0 8.0(7.99)

pulp & paper 6/27 1.7(1.51)

4.0(3.46)

1.7(1.63)

7.3(4.46)

2 1 2 1 12.7(9.35)

chemicals 10/90 1.8(2.10)

2.1(2.51)

1.0(1.15)

4.9(5.02)

2 1 4 3 6.4(6.82)

petroleum 2/6 0.0(0.00)

2.0(1.41)

1.5(0.71)

3.5(2.12)

0 0 2 0 4.0(0.00)

rubber &plastics

6/19 3.0(1.90)

0.5(0.84)

1.5(1.05)

5.0(2.45)

0 1 5 0 6.3(3.20)

non-metalicmineral

3/27 2.0(1.73)

2.7(3.79)

1.3(1.53)

6.0(6.24)

1 0 2 0 13.7(17.67)

basic metals 6/42 3(1.9)

2(1.79)

1.17(1.47)

6.17(3.25)

1 1 3 1 7.3(4.68)

Subtotal 44/211 2.1(1.88)

2.2(2.41)

1.3(1.25)

5.5(3.97)

8 5 26 5 8.2(7.75)

Total 64/459 1.9(1.87)

1.9(2.14)

1.2(1.22)

5.0(3.68)

8 8 39 9 7.5(6.83)

Table 2. Comparison of Index Scores between High vs Low-Profile Industry

Indexes Firm Level Comparisons Industry Level Comparisons

High Low T-test Wilcoxon High Low T-test Wilcoxon

Mean

(S.D.)

Mean

(S.D.)

t-stat

(sig. t)

Z-stat

(sig. Z)

Mean

(S.D.)

Mean

(S.D.)

t-stat

(sig. t)

Z-stat

(sig. Z)

EF 2.14

(1.88)

1.50

(1.82)

1.27

(0.209)

1.31

(0.190)

1.95

(1.01)

1.20

(0.93)

1.44

(0.175)

1.48

(0.139)

PA 2.20

(2.41)

1.35

(1.23)

1.88*

(0.065)

0.98

(0.325)

2.22

(1.04)

1.43

(1.02)

1.44

(0.175)

1.16

(0.248)

GI 1.32

(1.25)

0.95

(1.15)

1.12

(0.268)

1.22

(0.224)

1.36

(0.23)

0.80

(0.74)

1.90*

(0.098)

1.74*

(0.082)

SCORE 5.55

(3.97)

3.85

(2.64)

2.02**

(0.049)

1.66*

(0.098)

5.47

(1.20)

3.50

(1.29)

2.95**

(0.012)

2.37**

(0.018)

LINES 8.16

(7.75)

5.95

(3.90)

1.52

(0.135)

0.92

(0.358)

8.34

(3.55)

4.93

(2.59)

2.05*

(0.062)

1.79*

(0.073)

LEVEL 1.36

(0.92)

0.95

(0.60)

2.14**

(0.037)

1.57

(0.116)

1.40

(0.34)

0.84

(0.40)

2.84**

(0.015)

2.55**

(0.011)

*** significant at 0.01 level; ** significant at 0.05 level; * significant at 0.10 level

Table 3. Description of Variables

Name Description Operational definitions

NM(+) net margin ordinary income/sales * 100

ROE(+) return on equity net income/capital * 100

EPS(+) earnings per share net income/avg(# of common stocks)

CFPS(+) cash flow per share (net income+depreciation)/avg(# of common stocks)

PER(+) price earnings ratio avg(stock price)/EPS

SGR(+) sales growth rate (salest -salest-1)/salest-1 * 100

PGR(+) profit growth rate (net incomet - net incomet-1)/net incomet-1 * 100

RES(+) reserve rate retained earnings/capital * 100

EMP(+) employee number total # of full-time employees inc. executives

SALE(+) sales volume net sales during the first half accounting period 1997

OWN(-) owners' share major stockholders' share/capital * 100

LEV(+) leverage total liability/capital * 100

INT(+) interest charge interest expenses/sales * 100

SECT(+) section in KSE SECT=1 if in section 1; 0 otherwise

CHBL(+) chaebol ranking CHBL=3 if top 10; 2 if top 30; 1 if others; 0 if none

CPA(+) auditor firm ranking AUD=1 if the largest; 2 if the second etc.

BETA(-) beta coefficient market model beta using monthly return'93 thru '96

AGE(+) corporate age age of corporation as of 1997

EXP(+) foreign influence sales exported/sales * 100

Table 4. Descriptive Statistics of Independent Variables for Two Sample Comparisons

Variable Discloser(DISC=1)

(n=64)

Non-discloser(DISC=2)

(n=64)

T-test Wilcoxon

Test

Mean(S.D.) Mean rank Mean(S.D.) Mean rank t-stat. Z-stat.

NM 2.5(8.6) 64.27 -5.3(47.7) 61.90 1.32 0.81

ROE 8.6(17.2) 65.47 -18.3(140.8) 57.91 1.51 1.18

EPS 2867.3(7832.8) 68.31 1239.2(3065.9) 62.77 1.55 0.84

CFPS 4134.6(8508.8) 69.77 2461.9(4812.7) 61.36 1.37 1.27

PER 34.0(66.7) 51.37 31.0(36.5) 55.79 0.28 -0.74

SGR 13.8(23.8) 72.02 5.4(25.8) 57.21 1.91* 2.26**

PGR 49.8(252.7) 52.51 12.6(191.5) 44.32 0.81 1.44

RES 369.0(596.9) 66.56 285.7(309.6) 64.47 1.25 1.26

EMP 2563.6(5287.6) 71.83 1805.7(7497.8) 59.36 0.67 1.88**

SALE 3722.0(8296.3) 72.98 3260.2(11991.4) 58.24 0.26 2.23**

OWN 31.0(16.4) 66.63 29.8(14.1) 64.41 0.45 0.33

LEV 288.0(265.2) 61.92 666.9(1823.1) 62.08 -1.64 -0.02

INT 7.4(5.1) 65.88 10.1(16.9) 65.14 -1.23 0.11

SECT 1.6(0.56) 66.08 1.6(0.56) 64.94 0.18 0.20

CHBL 1.18(1.07) 69.05 0.9(1.03) 62.05 1.08 1.12

CPA 3.6(2.43) 61.27 4.7(3.31) 69.60 -2.02** -1.27

BETA 1.0(0.4) 56.80 1.1(0.5) 63.25 -1.33 -1.02

AGE 31.6(12.6) 69.74 28.9(12.0) 61.39 1.25 1.26

EXP 24.7(27.1) 67.30 21.5(25.0) 62.73 0.68 0.69*** significant at 0.01 level; ** significant at 0.05 level; * significant at 0.10 level

Table 5. Independent Variables Rotated Factor Loadings (Total Sample)

Variables Factor1 Factor2 Factor3 Factor4 Factor5 Factor6

NM 64

ROE 89*

EPS 83

CFPS 71

PER -86

SGR 89*

PGR 64

RES 73*

EMP 91

SALE 93*

OWN 67

LEV 58 -54

INT -52

SECT 71

CHBL 81

CPA 77*

BETA -42

AGE -58

EXP 87*

Eigenvalue 3.67 3.55 2.46 1.69 1.36 1.36

Table 6. Logistic Regression Results for the Environmental DisclosureDependent Variable: DISC=1 if a discloser, 2 if a non-discloser

Panel A: Results Based on Original Scores

Model ROE SALE RES EXP SGR CPA Chi-square

M1 0.02(2.50)* -0.00(0.34) 0.00(1.89) 0.00(0.05) 0.01(0.15) -0.21(8.01)*** 18.56***

M2 0.01(2.03) 0.00(0.04) 4.68**

M3 0.01(2.03) 4.64**

M4 0.27(1.60) 1.63

M5 -0.12(3.89)** 4.03**

Panel B: Results Based on Rank Scores

Model Rk(ROE) Rk(SALE) Rk(RES) Rk(EXP) Rk(SGR) Rk(CPA) Chi-square

M6 0.01(1.94) 0.01(2.83)* 0.00(0.15) -0.0(0.09) 0.01(1.75) -0.01(4.02)** 12.32***

M7 0.01(1.99) 0.01(5.0)** 6.62**

M8 0.01(1.39) 1.41

M9 0.01(4.90)** 5.07**

M10 0.01(4.12)** -0.01(4.62)** 9.98***

Panel C: Results Based on Factor Scores

Model Factor1 Factor2 Factor3 Factor4 Factor5 Factor6 Chi-square

M11 0.11(0.25) 0.29(0.75) 0.30(1.74) 0.35(2.36) 0.43(3.57)* 0.03(0.02) 9.76*

M12 0.10(0.23) 0.27(1.61) 1.87

M13 0.10(0.23) 0.23

M14 0.27(1.60) 1.63

*** significant at 0.01 level; ** significant at 0.05 level; * significant at 0.10 level

Table 7. Descriptive Statistics of Independent Variables for Multiple Sample Comparisons

Variables LEVEL One-way

ANOVA

Kruskal-

Wallis Test

3(n=8) 2(n=8) 1(n=37) 0(n=9)

Mean(S.D.) Mean(S.D.) Mean(S.D.) Mean(S.D.) F-stat. Chi-square

NM 1.5(9.2) 2.7(1.9) 2.1(9.3) 5.2(9.1) 0.34 2.51

ROE 5.2(9.0) 7.0(0.5) 9.7(19.0) 6.4(22.5) 0.18 0.75

EPS 671(1773) 3651(6613) 2289(7963) 6627(10859) 1.00 3.13

CFPS 2418(2468) 5175(8669) 3449(8581) 7703(11338) 0.75 0.51

PER 89.2(166.7) 33.3(62.3) 29.4(38.6) 6.2(4.5) 1.85 8.15**

SGR 6.1(13.1) 10.2(7.2) 16.6(29.1) 11.9(12.3) 0.53 1.11

PGR 91.4(134.4) -15.6(45.3) 58.8(310.9) 44.5(89.8) 0.20 3.54

RES 314.3(202.7) 393.4(492.1) 313.1(460.3) 637.9(1205) 0.74 0.55

EMP 2351(4299) 5302(11633) 2473(3943) 710(531) 1.10 2.67

SALE 4450(7163) 7253(14957) 3464(7665) 1052(967) 0.82 1.50

OWN 37.3(42.3) 26.8(17.1) 30.7(16.5) 30.4(17.8) 0.56 2.83

LEV 369.9(373.0) 279.2(116.0) 277.0(284.4) 262.8(167.8) 0.29 1.30

INT 8.3(4.1) 6.5(4.5) 7.8(5.8) 5.8(2.2) 0.56 1.88

SECT 1.8(0.5) 1.8(0.5) 1.6(0.5) 1.8(0.5) 0.80 2.42

CHBL 1.4(1.2) 1.1(1.4) 1.1(1.1) 0.7(0.9) 0.65 1.91

CPA 3.1(2.2) 4.4(2.7) 3.6(2.2) 3.8(3.6) 0.38 1.59

BETA 1.0(0.3) 0.9(0.3) 1.0(0.5) 1.0(0.6) 0.38 1.37

AGE 37(12.9) 34.1(9.4) 30.1(14.1) 31.6(5.7) 0.78 3.97

EXP 9.9(11.8) 27.3(24.6) 27.6(29.9) 22.9(25.2) 0.97 2.51

*** significant at 0.01 level; ** significant at 0.05 level; * significant at 0.10 level

Table 8. Independent Variables Rotated Factor Loadings (Discloser Sample)

Variables Factor1 Factor2 Factor3 Factor4 Factor5 Factor6

NM 82

ROE 87*

EPS 84

CFPS 70

PER -85

SGR 84*

PGR 64

RES 71*

EMP 89

SALE 93*

OWN -41

LEV 73*

INT 63

SECT 70

CHBL 80

CPA 78*

BETA 50

AGE -63

EXP -65

Eigenvalue 3.95 3.67 2.31 1.69 1.54 1.38

Table 9. Logistic Regression Results for the Level of Environmental DisclosureDependent Variable: LEVEL=0 if excellent, 1 if good, 2 if medium, 3 if poor

Panel A: Results Based on Original Score

Model Profile ROE SALE LEV SGR RES CPA Chi-

square

(+) (+) (+) (+) (+) (+) (+)

M1 1.9(7.0)*** -0.0(0.0) 0.0(3.1)* 0.0(0.7) -0.0(0.1) -0.0(4.3)** 0.2(2.0) 13.04*

M2 1.0(3.1)* -0.0(0.1) 0.0(1.4) 4.20

M3 0.9(2.6) -0.0(0.1) 2.76

M4 1.0(2.9)* 0.0(2.0) 4.59

Panel B: Results Based on Rank Score

Model Profile Rk(ROE

)

Rk(SALE) Rk(LEV) Rk(SGR) Rk(RES) Rk(CPA) Chi-

square

(+) (+) (+) (+) (+) (+) (+)

M5 1.3(3.4)* 0.0(0.0) 0.0(0.0) 0.0(0.4) -0.0(0.5) -0.0(0.5) 0.0(0.6) 5.70

M6 0.9(2.5) -0.0(0.9) 0.0(0.0) 2.73

M7 0.9(2.5) -0.0(0.0) 2.70

M8 0.9(2.3) 0.0(0.9) 3.41

*** significant at 0.01 level; ** significant at 0.05 level; * significant at 0.10 level

Table 10. OLS Regression Results Using Models Selected by Stepwise Procedure with DependentVariables: SCORE(Total index score), LINES(Number of line counts) LEVEL=3 if excellent, 2 if

good, 1 if medium, 0 if poor

Dep. Var. Rk

(LEV)

Rk

(CPA)

Rk

(AGE)

Rk

(PER)

Rk

(RES)

Rk

(EPS)

Rk

(BETA)

Rk

(NM)

F-stat.

(+) (+) (+) (+) (+) (+) (-) (+)

Panel A: Results based on High-Profile Sample

SCORE 0.09

(9.24)***0.05

(3.31)*5.72***

LINES 0.22

(8.59)***8.59***

LEVEL 0.02

(4.29)**4.29**

Panel B: Results Based on Low-Profile Sample

SCORE 0.11

(7.31)**0.09

(2.82)

3.68*

LINES 0.26

(22.23)***0.29

(12.87)**

*

-0.15

(7.15)**-0.07

(2.90)

8.93***

LEVEL 0.02

(4.02)*-0.02

(2.98)

2.94*

*** significant at 0.01 level; ** significant at 0.05 level; * significant at 0.10 level