Do Financial Markets Care About Social And Environmental Disclosure?

Do Financial Markets Care About Social And Environmental Disclosure?
Further Evidence And Exploration From The Uk [1] , [2]
Alan Murray [3]
Donald Sinclair
David Power
Rob Gray
KEY WORDS: Financial Markets; Share Returns; Investors; Social and Environmental Disclosure; United Kingdom
DRAFT 4C: June 2005
Address for Correspondence: Professor R.H.Gray, Centre for Social and Environmental Accounting Research, School of
Management, The Gateway Building, North Haugh, University of St Andrews, St Andrews, Fife, KY16 9SS, Scotland. Fax: +44 (0)1334
462812; E.Mail: [email protected]
ABSTRACT
Financial markets are increasingly powerful at the global level. That power can manifest itself in many ways – including in the influence
that financial markets can have upon environmental degradation and social injustice. Furthermore, and equally important in the present
context, markets impose limitations on the ability of quoted companies to undertake activities which might be seen as experimental and
financially fragile despite their being seen as socially and environmentally responsible. The power of markets does not seem to be
balanced by an equivalent responsibility. Social and environmental disclosure may be one possible way in which markets may be
re-educated towards less un-sustainable modes of behaviour. It is in this context that this paper seeks to explore whether stock market
participants in the UK exhibit any discernible reaction to the social and environmental disclosures made by the largest 100 companies
selected from the Times 1000 on the basis of turnover. A series of tests are undertaken to explore any of the ways in which share price
behaviour might reflect large company disclosures about their environmental and other social activities. Whilst no relationship of any kind
is found in the more straightforward tests of association, 'coding' of the data does produce convincing evidence that the level of company
returns over time is associated with the level of certain types of disclosures over time. This association remains when adjustment is
made for size and industry. The paper concludes by exploring explanations for these findings with particular emphasis on the moral case
for greater and better quality disclosures and calls for further tests which might explore whether markets have historically impounded and
discounted for the predilection to disclose.
1. Introduction
The growing expansion, globalisation and, ultimately, power of financial markets is a matter of increasing concern to many, (see, for
example, Schmidheiny and Zorraquin, 1996; Rich, 1994; Korten, 1999; Suranyi, 1999). Not only is there a growing anxiety about the
re-distributional effects that such markets encourage but there is equal concern that they also act to limit the discretion and range of
options available to the management of quoted companies. In a short-term economic sense this may not be important but if companies
must be amongst the major institutions through which environmental responsibility, social justice and, eventually, sustainability are to be
delivered [4] , then companies need the ability to experiment, take longer perspectives and undertake actions of which financial markets
may disapprove (Schmidheiny, 1992; Hawken, 1993; Hawken et al., 1999) [5] .
Financial markets are variously seen as offering the biggest single impediment or the greatest possible opportunity for international
capitalism to re-invent itself in a new form which is compatible with the exigencies of sustainability. In the absence of an apparent will to
closely regulate financial markets, it must fall to incentive, cajolery and persuasion to encourage markets to act in a manner less
incompatible with the social and environmental aims of sustainability. A potentially major factor in achieving this ambitious re-direction
must inevitably be information and, in particular, information about organisations' social and environmental activities. This is a role
currently fulfilled – albeit inadequately [6] – by corporate social and environmental disclosure through, mainly, the corporate annual report,
(see, for example, Mueller et al., 1994) [7] .
Such disclosure, occurring as it does within the annual report, might well be assumed to have shareholders as its primary target
audience – and as hinted at above, they may well be the most important audience for this material, (see, for example, Neu et al., 1998;
Milne and Patten, 2002). However, in a recent review of the extant literature concerning the relationship(s) between corporate social
responsibility, social reporting and the stock market, Richardson et al. (1999) concluded that research in the field is still relatively
inconclusive and largely under-specified. Even without examining the ontological and epistemological assumptions of the literature, there
were sufficient problems of definition, measurement and under-specification of models, the authors argued, to require continuing debate
and examination of the issues. (See also Ullmann, 1985).
Although social and environmental disclosure may not yet be an obviously substantive part of mainstream corporate activity, it is a
growing area of concern to all parties and, more especially, has both significant instrumental potential (see, for example, Lehman, 1999)
and a strong moral force and potential (see, for example, Owen et al., 1997; Mathews, 1995). Given the increasing power and
importance of financial markets and their intrinsic indifference to non-financial matters, social and environmental disclosure becomes a
very important link between the financial hyper-reality and the lifeworld (Thielemann, 2000; Mackintosh et al., 2000) [8] . It is in this
context that the present study takes its moment [9] .
The present paper seeks to contribute to just one aspect of this continuing debate – that of the relationship between stock market
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behaviour and corporate social and environmental disclosure. More particularly, this paper seeks to present evidence on the
relationship(s), if any, between the data reported by large UK companies [10] on their social and environmental activities and the share
price returns of those companies. The evidence presented is derived from both cross-sectional and nine years' longitudinal data and
seeks to control for the two factors most typically associated with social and environmental disclosure - company size and industry sector
(see, for example, Gray et al., 2001).
The paper is structured as follows. The next section explores the motivation for the study (thereby, seeking to broaden the debate about
the importance of both financial markets and social and environmental disclosure) and then reviews the, surprisingly sparse, prior
literature and draws from here the motivation for the tests contained in this paper. Section 3 outlines the disclosure and share return data
employed in the tests. Section 4 describes the tests that are to be undertaken, delineates the models on which the tests are based and
explains why second tranche of tests based upon the "coding" of the data was undertaken. Section 5 provides the detailed results of the
tests and includes a non-technical [11] interpretation of the results. The final section summarises the key findings, discusses their
implications and looks forward to future research issues in this area.
2. Financial Markets and Social and Environmental Disclosure
Research into corporate social and environmental disclosure can be thought of having two principal branches. The first branch of the
research has sought to examine how social and environmental disclosure can be seen as reflecting and discharging the responsibilities
and subsequent accountabilities of the organisation. This research has taken a societal point of view and has been motivated (primarily)
by democratic concerns about rights to information and the means by which organisational behaviour might be controlled by society
(see, for example, Medawar, 1976; Gray et al., 1988; 1991 and 1996; Lehman, 1999; 2001; 2002; Cooper et al., 2003). The second
branch of research into social and environmental disclosure has been rather more managerialist in orientation and sought to explore (i)
how the company uses such disclosure to manage its stakeholders and (ii) how such disclosure might be used to secure the legitimacy
of, either, the individual corporation or, more broadly, corporate capitalism itself. (See Cooper, 1988; Arnold, 1990; Arnold and Hammond,
1994; Gray et al., 1995a; Deegan, 2002; for a discussion of these issues).
However, of more direct relevance in the present context, social and environmental accounting research has not entirely ignored the
traditional financial participant and, especially in more recent years, has sought to explore if financial markets might be interested in
social and environmental disclosures – and if so, why? Researchers have sought to establish whether investors find social and
environmental disclosures decision-useful. This research, in keeping with much research into financial reporting theory (see, for
example, Belkaoui, 1986), has employed a variety of methods to investigate the actions, attitudes and behaviours of the individual
investor (see especially Epstein and Freedman, 1994; Chan and Milne, 1999; Milne and Chan, 1999) as well as the more familiar
explorations of aggregate financial market response to such disclosures. There are several factors that commend this research to our
attention.
Despite fairly convincing evidence that investors often exhibit a more than passing interest in social and environmental disclosures (see,
for example, Benjamin and Stanga, 1977; Chenall and Juchau, 1977; Firth, 1978; 1979; 1984; Epstein and Freedman, 1994), it is still
traditional to assume that investors are only interested in maximising their risk-adjusted returns from investment, (see, for example,
Benston, 1982; Skogsvik, 1998; but see also Rivoli, 1995). Under such an assumption, there is no immediate or obvious reason for
shareholders to have any interest in the social and/or environmental aspects of their investment – except insofar as those aspects
represent potential risk to the investment or whose disclosure can be taken as signals about the competence of management (Neu et al.,
1998; Hufsted, 2000; Orlitzky and Benjamin, 2001; Milne and Patten, 2002). And yet, governments continue to increase the
requirements governing the disclosure of social and environmental data in corporate reports whilst corporate management, themselves,
continue to produce voluntary disclosures in the annual report [12] . Whilst a commentator wedded to a 'free market' perspective might
well find the apparently irrational imposition of additional information costs by the government on the corporation and its shareholders
unsurprising, they would probably be more concerned by the potential wastefulness of a corporate management engaging in voluntarily
producing non-price sensitive data.
This potential 'wastefulness' by corporate management would fly directly in the face of "conventional" market wisdom (and, see, for
example, Friedman's (1962; 1970) famous comments on the matter) unless it could be shown that such data has price relevance. Could
such data represent signals to the investor? Could the signal suggest that, for example, the company is aware of potential social or
environmental costs and has taken steps to manage them? Could it be that it is aware of the actions of pressure groups and has
responded to avoid potential problems? Perhaps it signals awareness of growing liabilities upon which the company is acting accordingly
or suggests that the company is managing and exploiting its high level of reputation with niche consumer groups.
As we shall see, although investors are apparently exhibiting an increasing demand for social and environmental disclosure, there is no
evidence (as far as we are aware) of proven links between the price sensitivity of the social and environmental data and the substantial
changes in economic circumstances that these data could be signalling. Thus it remains an open question as to whether or not corporate
management are exhibiting wastefulness in undertaking voluntary social and environmental disclosures or successfully signalling their
competence to the market. In essence, research has not advanced us much beyond Ullmann's (1985) often-repeated observation that it
'pays to be good but not too good' [13] .
The reasons it pays the company to be good(ish) are purely financial in nature [14] . As the apparent general awareness and concern in
society for such matters as environmental degradation, habitat destruction, global climate change, human rights, and stakeholder
involvement, continues to increase (see, for example, Brown and Flavin, 1999), it certainly seems likely that the number of potential
areas in which social or environmental activity can have relatively direct financial consequences must increase, (see, for example,
Preston and O'Bannon, 1997; and Griffin and Mahon, 1997; for reviews). These consequences can be of a cost-saving nature (see, for
example, McMillan, 1996); cost or liability avoidance (see, for example, Gunthorpe, 1997; Hughes, 2000); revenue-generating (see, for
example, McIntosh et al., 1998) or even simple signals of best-in-class management practices (see, for example, Stone, 2000). In such
a climate, social and environmental issues continue to rise as areas of potential risk requiring careful management by prudent
organisations.
The foregoing offers an a priori argument for why social and environmental data may have potential impact on shareholders' decisions
as to whether or not to buy, hold or sell shares. But, the crucial thing is that such an analysis presupposes that investors are only
interested in the financial aspects of their investment, (see also Richardson et al., 1999). And this, by default, produces the normative
moment - that is at the heart of most accounting and finance - that suggests (implicitly) that investors should only think of financial
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aspects of their investment decisions.
There is no evidence, as far as we are aware, that all investors are exclusively interested in a purely financial appraisal of their
investments. Indeed, the very significant growth in ethical investment funds (see, for example, D'Antonio et al., 2000) probably suggests
quite the reverse. Indeed, such evidence opens the door to the possible suggestion that investors become less obsessed by that
financial return when the (social, environmental, ethical) implications of the investment are made apparent. Therefore, as Belkaoui,
(1976) argues, there is no a priori reason why we should assume that all investments are always treated as purely economic events.
Consequently, social and environmental disclosures may well offer an important source of direct input to these 'ethical' investors'
decisions (Owen, 1990 and see also Miles et al., 2002).
There is a further normative element to this, however. Unless one takes the most primitive of ethical, economic and social reasoning, it
is probably impossible to argue that the only morality which attaches to the investor is to make the most economically effective
investment – as measured by personal financial returns. (See Jacobson, 1991; Thielemann, 2000; Collison and Frankfurter, 2000). To do
so takes us into the old chestnut that 'rich means good', 'richer means better', and any detrimental social and environmental effects
arising from the use to which the investment is put and from which the returns are derived are of no moral concern to the investor. (The
typical right-wing, 'free-market' view would be likely to suggest that this is a fault of the government to properly regulate the system
and/or the fault of those who suffer the detriment for not exercising their economic choice in an apposite manner). Consequently, social
and environmental disclosure can actually be seen as an educative process whose purpose is either to explain the social and
environmental complexities underlying the investment or to show the investor what moral choices are being made.
Finally, social and environmental disclosure may have to play a crucial role in moves towards sustainability (Leggett, 1996; Suranyi,
1999; Gray and Bebbington, 2000; and see also Case, 1999). That is, there is increasing recognition (see, for example, Schmidheiny
and Zorraquin, 1996) that moves towards sustainability (or, more realistically, moves away from un-sustainability) cannot be achieved if
financial markets remain as rapacious, self-serving and short-termist as there are currently (Tinker and Gray, 2003). There would appear
to be an absence of any international political will – or, perhaps international political ability (but see Bailey et al., 1994a; 1994b; Kolk et
al.,1999) - to control financial markets to a much greater degree than is currently the case. As a consequence, even the very best run,
well-intentioned and intelligently informed of companies - if quoted – currently has very little room for discretionary actions of a socially or
environmentally responsible nature. Any major activity by the company management which investors cannot see as being of a relatively
direct and foreseeable economic benefit to the organisation is, a priori, likely to be penalised by either the selling of shares or of motions
to remove this (enlightened) corporate management. The sorts of activities – and, indeed, experiments – that must be explored if we are
to discover if 'sustainable capitalism' is a possibility or a pipe-dream are unlikely to enamour themselves immediately to financial
markets. (See Cordeiro and Sarkis, 1997; Leggett, 1996)
Consequently, financial markets need to be 'educated' (see, for example, Schmidheiny and Zorraquin, 1996) about the social and
environmental challenges that sustainability presents to each and every company. Although social and environmental disclosure is, as
yet, not delivering this quality of educative disclosure, (see, for example, Gray, 2000) it seems inevitable that social and environmental
disclosure must play a major part in seeking out the possibilities of transformation that may exist in financial markets.
There has been a considerable body of research over the years into such matters as the social and environmental performance of
companies and financial indicators including share price response, (for relatively recent reviews of this literature see, for example,
Richardson et al., 1999; Gray et al., 2001; Orlitsky and Benjamin, 2001; Wagner, 2001; Toms, 2002; Patten, 2002; Lorraine et al., 2004).
However, we have been unable to discover more than a relatively few studies which have directly examined the relationship between
social and environmental disclosure and financial markets [15] .
That is, whilst a range of studies have examined share price responses to releases of information about the company, typically EPA [16]
or CEP [17] information releases, these studies have treated the information as a direct analogue for the underlying (social or
environmental) activity and investigated how investors might react to changes in social or environmental behaviour. (See, for example,
Jaggi and Freedman, 1992; Pava and Krausz, 1996; Edwards, 1998; and see also Wagner, 2001 for a comprehensive summary and
Lorraine et al., 2004; for an example of a UK based enquiry).
Of more direct interest to us here, is to look at the reaction to the disclosure process itself and, in particular, reaction to those
self-disclosures made by the individual company. What we find, as so often, is that the results – which are predominantly from the USA are inconclusive and, probably, not generalisable beyond the US. Belkaoui (1976) was explicitly looking for, what he called, the "ethical
investor" effect. The disclosure he examined was that of environmental fines. He claims to have found the ethical investor effect and
reports a positive and significant relationship between share returns and corporate disclosure. Frankle and Anderson (1978) challenge
Belkaoui's reasoning and research design and, reworking Belkaoui's data, report a negative relationship between disclosure and share
price performance. Anderson and Frankle (1980) went on to undertake their own analysis and report the outcome as inconclusive.
(Although there did appear to be some positive relationship between share returns and whether a company was disclosing or
non-disclosing, the results were not statistically significant). Ingram (1978) identified that there are different areas of disclosure and whilst
he reports there is no relationship between share returns and disclosure he does conclude that there may be a positive relationship in
the case of environmental disclosure. Finally, Jaggi and Freeman (1992) conclude that environmental disclosure in heavily polluting
companies does have information content.
All of these are US studies and the results are clearly inconclusive, (see also Richardson et al., 1999). There has been little further direct
investigation of this area (as far as we are aware) – presumably because the US Ernst and Ernst (1976 et seq) database of social
disclosures was discontinued after 1978 thus making data access a problem. Consequently, it seems apposite not only to try and look at
more recent data but also to undertake a test in a country, the UK, where the matter has not previously been investigated systematically.
The tests undertaken (outlined in the "Method" section) are directly influenced by the prior work in the field broadly and by the paucity of
prior work which specifically examines the relationship between disclosure and share price performance. That is, we first test for the
existence of any obvious relationship between social and environmental disclosures in the annual report of companies and the share
price performance of those companies in order to confirm (or rebut) expectations that any relationship is likely to be elusive, slight and, at
best, inconclusive. But we then develop the testing as a direct result of the guidance which we infer from the prior literature. That is, first,
throughout the testing we explicitly recognise difference between (i) mandatory and voluntary disclosure and (ii) between disclosures
concerning different subjects – most obviously social and environmental. Second, we take explicit cognisance of the likelihood that,
although a relationship between social/environmental disclosure and financial market participant behaviour is likely, it is an undertheorised relationship and is likely to be (currently at least) amongst the less significant influences upon the movement in share prices.
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We thus take the Gray et al. (2001) arguments concerning the improved likelihood of any relationship being more likely to reveal itself
over a period of time – rather than at single points in time - and we consequently undertake both cross-sectional and longitudinal
analyses of the data. Third, relatedly and more substantively, we are led to hypothesise that social and environmental disclosures and
share price performance do not articulate functionally and that a simple causal relationship is unlikely to obtain. We are led by the
literature to conjecture that companies may have predispositions to disclose and it may be this predisposition that bears a relationship
with financial market performance. We therefore test this predisposition hypothesis and identify results which are in keeping with it.
3. Data
The tests in this study are based on data from the UK's "Top 100" companies (chosen from the Times 1000) over a 10-year period
between 1988 and 1997 [18] .
The social and environmental disclosure data are stored in the Centre for Social and Environmental Accounting Research (CSEAR)
database of UK social and environmental disclosure by the top 100 UK companies [19] . This database, in keeping with the majority of
prior research which has examined such disclosure (see, for example, Gray et al., 1995a; 1996), concentrates on the largest companies
which tend to provide the most extensive and innovative disclosure. Furthermore, the database contains disclosures from the top
companies from 1988 to (at the time of the current tests) 1997. It, thereby, presents the opportunity to undertake both cross-sectional
and longitudinal tests. In addition, the database differentiates between areas of disclosure (that is, between, for example, environmental,
community, employee and customer related disclosure) as well as allowing distinctions to be drawn between mandatory and voluntary
disclosures. The prior literature (but see also Gray et al., 2001) has hinted that (i) environmental disclosures appear to be the most likely
to be of interest to financial markets [20] and (ii) that discretionary (i.e. voluntary) disclosure is far the more likely to represent a signal to
markets than those disclosures which are required of all firms. Consequently, it is upon: total (i.e. both mandated and voluntary)
disclosure (CSRTOT); and two of its components: total voluntary disclosure (VOLTOT); and total environmental disclosure (ENVTOT) [21]
; that we concentrate in what follows. The study investigates whether there is a statistical relationship between these variables and share
returns. The disclosure variables represent the number of pages in a company's annual report allotted to social and environmental
issues and were constructed using content analysis [22] .
As only annual reports from the "Top 100" companies each year are featured in the CSEAR database, the initial sample considered in
the present paper is restricted to 168 firms (i) as new companies with large market capitalisation were promoted into the list because of
changes in valuation from one year to the next and (ii) as a number of companies disappeared because of merger, takeover or a fall in
share value. Three further criteria were adopted when determining the final sample. First, companies had to be present in the database
for at least three of the nine years covered in order to perform some of the longitudinal tests conducted in the paper. (The ten years of
data permitted the calculation of nine years of returns). Second, share price data had to be available for each company in Datastream
both for the year before and the year in which the disclosure took place in the financial statements [23] . This additional restriction was
necessary so that share returns could be computed as follows:
where Ri,t is the return earned by company i in the year t, Pi,t is the price of share i at the end of year t, Pi,t –1 is the price at the start of
the year. Finally, details on company size (sales) and sector membership were necessary for some of the empirical analyses which were
undertaken and companies where such information was not obtainable were omitted from the investigation.
The final sample consisted of 660 (CSRTOT, VOLTOT and ENVTOT) instances of disclosures for (coincidentally [24] ) 100 firms over the
9-year period. Some 41 of the companies had 9 observations in the sample, 10 had 8 observations, 6 had 7 observations and the
remaining 43 had 6 or fewer observations respectively in the final analysis. Descriptive details for the sample are provided in Table 1.
Table 1: Descriptive Statistics for the Sample
SECTOR
No.
of
Firms
No.
of
Obs
TURN-OVER
Mean
VOLTOT
Mean
ENVTOT
Mean
CSRTOT
Mean
RETURN
Mean
RETURN
Std.
Dev.
No
Name
1
Food & drink, tobacco, brewing, meat, distilling
17
114
4701
1.75
0.56
5.69
0.064
0.210
2
Textiles, cloth, wool, footwear
4
30
1973
1.08
0.66
4.97
0.042
0.540
3
Mechanical and general engineering, motors, plant
4
33
3410
1.81
0.79
5.56
0.038
0.338
4
Electrical & electrical eng., IT., telecoms, computers
11
66
4837
1.54
0.55
6.14
0.080
0.255
5
Processing, building materials, paper, metallurgy,
printing
10
59
2269
1.28
0.67
5.74
0.019
0.264
6
Chemicals, oil & gas, coal, paint, plastics, detergents
7
59
13813
2.14
1.45
6.47
0.086
0.205
7
Financial and other services, publishing, property,
shipping
8
47
3514
1.17
0.57
5.10
0.099
0.288
8
Retail and leisure, motor distribution
17
122
4672
1.93
0.58
5.96
0.042
0.321
9
Pharmaceuticals
3
19
7377
2.81
1.96
8.09
0.068
0.264
10
General manufacturing, office equipment, misc.
industrial
2
13
2935
1.84
1.13
7.73
0.120
0.156
11
Contracting and building
7
35
2940
1.61
0.64
4.70
-0.097
0.390
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12
Extractive industries
2
18
3203
2.05
1.52
6.63
0.005
0.335
13
Aerospace & defence
2
15
6406
1.18
0.39
5.74
0.162
0.398
14
General
6
30
2010
0.97
0.59
5.62
0.005
0.336
100
660
4860
1.67
0.75
5.86
0.050
0.301
All
Note. This Table provides descriptive statistics for the variables employed in the analyses. In particular, the sector name and number are given as well as the size (average turnover value in £m). The mean number of
pages devoted to total corporate social disclosure for each company in a sector (CSRTOT) is shown. This total is split into the number of pages devoted to voluntary disclosure (VOLTOT) and the number devoted to
environmental disclosures (ENVTOT). Finally the mean share return and standard deviation of share returns is shown.
A visual inspection of this table reveals that the 100 companies in the sample are not evenly distributed between the 14 sectors
analysed; two sectors have 17 firms while three sectors have only 2 constituent companies. The size of company in each sector also
varies widely. It ranges from a low of £1.973m in the Textile industry to a high of £13.813m in the Chemicals, Oil & Gas sector while the
mean turnover figure was £4.860m for all firms. The typical company in the sample included 5.86 pages of corporate social reporting in
its annual report of which 1.67 pages related to voluntary data that were not required to be published under current legislation; most
disclosures therefore related to mandatory matters which companies are obliged to publish. This fairly low level of disclosure is common
across all sectors although firms in Pharmaceuticals and General Manufacturing had the highest average CSRTOT (8.09 and 7.73
pages respectively) among the groups studied. Environmental disclosure is fairly small for the sample companies at 0.75 pages and
only a few sectors (Chemicals, Oil and Gas; Pharmaceuticals; General Manufacture; and Extractive) have average disclosure levels of
more than 1.00 page devoted to this topic in their annual reports [25] . Finally, average annual returns for the sample firms varied from a
low of –0.097 for companies in the Contracting and Building sector to a high of 0.162 for companies in the Aerospace and Defence
industry, (although note the small sample size for this last sector). The tremendous variety in stock market performance for firms in the
different sectors is confirmed by an analysis of the standard deviation figures. Returns were particularly volatile in the Textile sector
(STDEV = 0.540) but remarkably stable for shares in the General Manufacturing industry (STDEV = 0.156). It is worthy of note that the
poor (financial) performance of contracting and building companies in the sample was associated with relatively high levels of risk
(STDEV = 0.390) suggesting that shareholders in these firms fared badly (in traditional financial terms) for the particular years which are
covered in the analysis.
Overall, this UK data set presents a new opportunity to examine the relationship between corporate social and environmental disclosures
and share returns (in both cross sectional and longitudinal contexts) and should provide a useful comparison with the US-based work in
the area. To date, the absence of a non-US database is probably one of the main reasons why there has been no substantial work on
this topic in the UK [26] .
4. Method
Five statistical tests are conducted to determine whether a link exists between corporate social and environmental disclosures and share
returns. These tests were conducted in three series. The first series comprised tests of the un-transformed data as an exploration of the
obvious hypotheses concerning the likely associations. The second series of tests involved grouped data with the companies
categorised into groupings based on the returns (i.e. high, medium and low) and the disclosure (e.g. small, medium or large). This
grouping procedure facilitated a test of whether any non-linear relationship existed between the share returns and social as well as
environmental disclosures. The third series comprised a set of tests of the data in coded form which more directly addressed the
question of the extent to which share return performance was related to a predisposition to disclose social and environmental
information. The tests are as follows [27] .
First, Pearson Correlation co-efficients are calculated which examine the degree of linear relationship between the variables being
studied. The correlations are estimated between returns and each of CSRTOT (Total Social and Environmental Disclosure), VOLTOT
(Total Voluntary – as opposed to Mandatory - Disclosure) and ENVTOT (Total Environmental Disclosure) across the whole sample, for
the different sectors and for every year from 1989 to 1997. [28] ,
[29]
Second, the analysis is extended by determining whether a non-linear relationship exists between social and environmental disclosures
and share returns. Specifically, returns are split into three categories – low, medium and high. Where the share return in the year is less
than –0.015 the company is placed in the "low" category, if the return is between –0.015 and 0.015 it is put in the medium category while
if the return is greater than 0.015, it is assigned to the high category. [30] These cut-off points were chosen to ensure that the number of
observations in each category was large enough to facilitate statistical testing. [31] They were also associated with breaks in the share
return distributions based on a visual inspection of the data set. Each of CSRTOT, VOLTOT and ENVTOT disclosures were also
grouped into three categories – small, medium and large – depending on the numbers of pages which were devoted to these issues in
the corporate report. For CSRTOT, the small category included those firms with up to 4.00 pages of social and environmental
information in their annual reports, the medium category included those companies with between 4.0 and 7.2 pages of social and
environmental disclosures in the annual reports and the large category included firms with more than 7.2 pages of such disclosures in
their annual report. [32] The cut-off points for the voluntary disclosures were different since such information only represented a small
fraction of the total corporate social disclosures provided by companies. In particular, if less than 0.6 of a page in the financial
statements was devoted to VOLTOT, the disclosure was categorised as "small", if between 0.6 and 2.08 pages were devoted to
VOLTOT, the disclosure was classed as "medium" and if more than 2.08 pages were devoted to VOLTOT, the disclosure was labelled
"large". [33] Finally, the environmental disclosures were split into three categories based on another set of cut-off points. If less than
0.10 of a page was given over to ENVTOT matters, the disclosure was termed "small", if between 0.10 and 1.00 pages contained
ENVTOT information, the disclosure was called "medium" and if more than 1.00 page of the annual report dealt with ENVTOT issues,
the disclosure was labelled "large". [34] Other cut-off points could have been selected but a graph of each data series suggested that
these points highlighted natural breaks which distinguished between different amounts of firms' disclosures.
With the three categories of disclosure – small, medium and large – a chi-square test of association was conducted with the different
share return groupings - low, medium and high –:
5 of 16
where On,m is the observed frequency for row and columns and En,m is the expected frequency for row n and column m, based on the
null hypothesis of no association. The test is repeated for the three disclosure types – CSRTOT, VOLTOT and ENVTOT and the null
hypothesis of no association examined. The strength of this test is that non-linear as well as linear relationships between variables can
be uncovered if they are present in the data.
Third, a General Linear Model was fitted to the share return data to investigate whether interactions between different types of
disclosures (CSRTOT, VOLTOT and ENVTOT) either as main effects or as interactions with years in conjunction with size and other
selected variables can explain returns. In particular, the following equation is estimated:
Where j is a constant term, qi is a dummy variable for each year, Xi,t is CSRTOT, Yi,t is VOLTOT, Zi,t is ENVTOT, Si,t is the natural log of
the turnover variable Si,t,
l, g, d and m are regression coefficients, (ql)t , (qg)t , (qd)t and (qm)t are the interaction coefficients, and ei,t
is the error term.
The output from this equation in terms of F-statistics and associated p-values should provide a comprehensive picture of whether
investors appear to respond to certain social and environmental disclosures for different sized companies in several sectors across
various time periods by changing their valuation of a company's share price and altering the return earned.
Recognising that the approach to categorising returns and disclosure employed in the chi-squared test (3) above would be likely to
swamp any relationships as a consequence of (for example) companies moving from being relatively high to relatively low disclosers and
to avoid any biases that might be introduced by dividing the returns for the various companies according to their average over several
possibly non-matching periods of years, the fourth and fifth tests were employed on a coded form of the data.
For the fourth test, the returns for each year were ranked, and the fractional rank of each company was expressed as a percentage. The
percentage fractional ranks for each company were averaged over the years during which returns were available for that company to
produce an average percentage rank. The average percentage ranks were coded into the variable ‘CPRET' [35] . This process was also
applied to the disclosure variables CSRTOT (Total Social and Environmental Disclosure), ENVTOT (Environmental Disclosure), VOLTOT
(Voluntary Disclosure) to produce coded variables CPCSR (Coded percentage total disclosure), CPENV (Coded percentage
environmental disclosure) and CPVOL (Coded percentage voluntary disclosure). The turnover measure was also classified in this
manner to yield CPTUR (Coded percentage turnover), a size variable coded into three levels. The Pearson Correlations between the
coded returns and coded social and environmental disclosure were then calculated to see whether a linear relationship existed.
Fifthly, the coded data were then categorised as follows, the lower third was classified as small (1), the middle third was classified as
medium (2) , and the upper third was classified as large (3). Thus the coded measure places a company in category 1 if, on average, it
earned a high return relative to the companies in the sample. The same categorisation process was also applied to the CPCSR, CPENV
and CPVOL and the non-linear relationships were investigated using the chi-squared test. Thus, this final test focuses on whether a
company's predisposition to disclose relatively large volumes of social and environmental information was associated with relatively high
share returns.
5. Results
The Pearson Correlation coefficients for the association between annual returns and the amount of corporate social reporting in total and
under the two sub-categories are reported in Table 2 [36] . Across the whole dataset, these correlations are positive but very small
ranging from a low of 0.021 for CSRTOT to a high of 0.043 for ENVTOT. The test of the null hypothesis that these correlations are equal
to zero cannot be rejected at conventional significance levels as the p-values are all greater than 0.05. The clear picture which emerges
from this scrutiny of the whole dataset therefore is that no linear association exists between share returns and the different social and
environmental disclosures being examined. [37]
Table 2: Pearson Correlation Coefficients Between Share Returns and the Amount of Corporate Social Disclosure.
Total
Sample
CSRTOT
(Total Disclosure)
VOLTOT
(Voluntary Disclosure)
ENVTOT
(Environmental Disclosure)
Correlation
Correlation
Correlation
p-value
p-value
p-value
0.021
0.588
0.032
0.418
0.043
0.266
1989
-0.185
0.122
-0.115
0.341
0.058
0.629
1990
0.121
0.306
0.103
0.388
0.091
0.442
1991
0.041
0.722
0.158
0.171
0.050
0.664
1992
0.175
0.137
0.105
0.375
0.085
0.471
1993
-0.032
0.780
0.031
0.789
0.029
0.799
1994
-0.034
0.771
-0.037
0.750
0.033
0.775
1995
0.070
0.549
-0.105
0.366
0.040
0.734
6 of 16
1996
-0.019
0.873
-0.038
0.750
-0.089
0.453
1997
-0.166
0.198
-0.046
0.724
-0.171
0.185
Note: This table shows the Pearson Correlation Co-efficients between share returns and corporate social and environmental disclosure and two of its components (CSRTOT, VOLTOT and ENVTOT). These correlations
are estimated for the whole sample and for each of nine years.
Table 2 also displays the correlations and p-values for each year from 1989 to 1997. Again, the overwhelming impression to emerge
from a visual scan of these data is that the correlations vary from year to year and across each type of disclosure; for example, they are
all positive in 1990, 1991 and 1992, all negative in 1996 and 1997 but both positive and negative in the other four years. The
co-efficients for 1989, 1990, 1992 and 1997 are slightly bigger than in the other rows of the Table ranging from –0.185 to 0.175 but still
fairly close to zero. Also, a sizeable number of the correlations are negative especially for the CSRTOT and VOLTOT variables which
suggests that an inverse relationship exists between share returns and these variables but none of the negative values are statistically
significant however.
The chi-squared statistics in Table 3 investigate whether a non-linear relationship is present among the whole data set being studied
which was not detected by the linear analysis in Table 2. The hypothesis that "large" disclosures of social and environmental information
in annual reports are associated with "high" returns because investors value such disclosures can be studied by looking at the different
chi-squared statistics. No relationship, either linear or non-linear, however, emerges from an analysis of the findings. The actual number
of observations in each cell does not differ significantly from its expected value under the null hypothesis of no relationship. The
chi-squared statistics are all low and below the limits necessary to reject the null. [38] A similar conclusion can be drawn when the data
are analysed for each year from 1989 to 1997. One chi-squared value (7.821) for CSRTOT in 1989 has a p-value that is just significant
but only at the 10 percent level [39] (p = 0.098) but with 27 chi-squared tests, one would expect just under 3 false positives for this
analysis. The remaining 26 chi-squared test statistics have p-values which suggest no relationship between share returns and the
disclosures being investigated in this paper.
Table 3 Chi-Squared Test Statistics For The Association Between Returns (Small , Medium, Large) and the Amount of Corporate Social Disclosure.
CSRTOT
(Total Disclosure)
VOLTOT
(Voluntary Disclosure)
ENVTOT
(Environmental Disclosure)
Chi-Squared
Chi-Squared
Chi-Squared
p-value
p-value
p-value
Total
Sample
2.934
0.569
1.191
0.880
6.050
0.195
1989
7.821
0.098
2.635
0.621
2.280
0.684
1990
0.875
0.928
1.472
0.832
3.002
0.558
1991
3.126
0.537
4.831
0.305
3.089
0.543
1992
6.364
0.174
1.697
0.791
2.559
0.634
1993
1.642
0.801
6.743
0.150
0.910
0.923
1994
2.035
0.729
3.202
0.524
4.192
0.381
1995
2.031
0.730
3.061
0.548
5.133
0.274
1996
3.383
0.496
3.856
0.426
5.089
0.278
1997
1.529
0.466
1.194
0.879
0.988
0.912
Note: This table summarises the results of Chi-squared tests of association between share returns and corporate social and environmental disclosures (CSRTOT, VOLTOT and ENVTOT), for the whole sample and for
each of nine years.
Table 4 contains the statistical output from estimating the General Linear Model in Equation [3]. The F-ratios for the main individual
effects are shown as well as the two factor interactions with a dummy variable for the year (YEAR). The main conclusion to be drawn
from this table is that the returns earned by our sample firms vary over time; the F-ratio for the year variable has a value of 2.347 and a
p-value of 0.017. None of the other main effects are significant since the F-ratios are small and the p-values greater than 0.05. Once
the interaction terms are studied the year of disclosure for CSRTOT is marginally significant (at the 10 per cent level) but it seems as if
the main influence on returns is still year and size. By adding the other disclosure variables and size the adjusted R2 for the model only
reaches 10.4 per cent indicating that some 89.6 per cent of the cross-sectional variation in the returns of the firms being studied remain
unexplained by the model [40] .
Table 4: Output from Fitting a General Linear Model to Explain the Share Return Data
Source
Sum of Squares
df
F ratio
p-value.
Intercept
0.134
1
1.651
0.199
YEAR
1.526
8
2.347
0.017
CSRTOT
0.042
1
0.522
0.470
VOLTOT
0.001
1
0.012
0.912
ENVTOT
0.028
1
0.343
0.558
SIZE
0.188
1
2.308
0.129
YEAR * CSRTOT
1.127
8
1.733
0.088
7 of 16
YEAR * VOLTOT
0.951
8
1.463
0.168
YEAR * ENVTOT
0.648
8
0.996
0.438
YEAR * SIZE
1.595
8
2.454
0.013
Error
49.889
614
Total
61.342
659
Note: This table presents the results from an analysis of co-variance of share returns on the factor YEAR, on the three covariates total corporate social reporting, voluntary disclosure, environmental disclosure, and on
the interactions between YEAR and each of these covariates. The adjusted R-squared value is 10.4 percent.
It will be recalled that a series of "Coded Percentile Rank" (CP) variables were also derived in order to mitigate any potential swamping
of the results from the method employed above. (It was anticipated that this approach might also bring us closer to some notion of
"predilection to disclose" and whether this predilection exhibited any relationship with a more general measure of the pattern of returns.)
Analyses were performed using these coded variables for returns (CPRET), for total disclosure (CPCSR), for voluntary disclosure
(CPVOL) and for environmental disclosure (CPENV). In particular, correlation analysis was undertaken between CPRET and the other
three coded disclosure variables (i) over the whole period and (ii) in each year, to see if a linear relationship existed. Also Chi-squared
tests were undertaken between the same pairs of variables to determine if any non-linear relationship was present. The results of both
analyses are summarised in Table 5.
Table 5: An Analysis of the Relationship between Coded Share Returns and the Coded Amount of Corporate Social Disclosure.
Panel A - Pearson Correlation Coefficients
CPCSR
(Coded Total Disclosure)
CPVOL
(Coded Voluntary Disclosure)
CPENV
(Coded Environmental Disclosure)
Correlation
Correlation
Correlation
p-value
p-value
p-value
Total
Sample
0.344
0.000
0.198
0.000
0.098
0.012
1989
0.404
0.000
0.306
0.009
0.124
0.302
1990
0.406
0.000
0.316
0.006
0.138
0.241
1991
0.343
0.002
0.231
0.044
0.097
0.399
1992
0.303
0.009
0.142
0.227
0.084
0.479
1993
0.327
0.004
0.136
0.240
0.097
0.399
1994
0.331
0.003
0.159
0.167
0.114
0.322
1995
0.287
0.012
0.140
0.228
0.080
0.493
1996
0.312
0.007
0.121
0.306
0.059
0.622
1997
0.392
0.002
0.236
0.065
0.072
0.580
Panel B - Chi- Squared
CPCSR
(Coded Total Disclosure)
CPVOL
(Coded Voluntary Disclosure)
CPENV
(Coded Environmental Disclosure)
Chi-Sq.
Chi-Sq.
Chi-Sq.
p-value
p-value
p-value
Total
Sample
87.532
0.000
41.704
0.000
18.490
0.000
1989
12.606
0.013
8.859
0.065
2.873
0.579
1990
12.985
0.011
8.989
0.061
2.628
0.622
1991
10.913
0.028
6.018
0.198
2.004
0.735
1992
8.564
0.073
4.690
0.321
2.524
0.640
1993
10.964
0.027
4.155
0.385
2.004
0.735
1994
9.463
0.051
4.369
0.358
1.631
0.803
1995
7.371
0.118
2.805
0.591
2.664
0.615
1996
8.377
0.079
2.462
0.652
2.026
0.731
1997
10.165
0.038
4.681
0.322
2.169
0.705
Note: This table shows the relationship between the coded average percentile rank share returns and coded average percentile rank corporate social and environmental disclosures (CPCSR, CPVOL and CPENV), (i)
8 of 16
for the whole sample and (ii) for each of nine years. Panel A shows the correlation coefficients, while Panel B shows the Chi-squared statistic. The p-values associated with each of these statistics are also shown.
In Panel A of Table 5, the linear relationship between CPRET and CPCSR, estimated over the whole period using the Pearson
correlation coefficient (0.344), is extremely significant; the correlation coefficient is significantly different from zero, and indicates a
positive relationship between the two variables. Therefore, this result suggests that there is a strong tendency for small CPRET firms to
disclose small amounts of CPCSR information and for large CPRET firms to publish relatively large quantities of CPCSR disclosures.
Similar results emerged from an analysis of CPRET and CPVOL, however the correlation between CPRET and CPENV over the whole
period (0.098) was significant to a much less extent. When the linear relationship between CPRET and CPCSR is estimated over each
one-year sub-period the correlation coefficient remains positive and statistically significant but varies in value from year to year. By
contrast a significant linear relationship between CPRET and CPVOL is encountered in only the first three one-year sub-periods
(1988-1991). No significant linear relationship between CPRET and CPENV is evident in any individual year [41] .
The association between categories of returns (in the coded form CPRET) and categories for each of the disclosure variables (in their
coded form CPCSR, CPENV, CPVOL) was also examined over the whole period using the chi-squared test (Table 5, Panel B). Again
each was found to be extremely significant [42] . The estimated Chi-squared values in Table 5 Panel B of 87.532, 41.704 and 18.490 all
had p-values which were less than 0.050.
Turning to the association between categories of coded returns and categories of coded social and environmental disclosures in each
one-year sub-period, we note that the association between CPRET and CPCSR is significant at the 5% level in five of the years (1989,
1991, 1993 and 1997). Moreover, in 3 of the other five years the chi-squared co-efficient is significant at the 10% level. The Chi-squared
results for CPVOL and CPENV are smaller, indicating that no significant association exists between these variables and the coded
returns for the sample firms over and above the linear relationship uncovered in Panel A. Also the relationships tend to become weaker
over time suggesting that the volume of disclosures measured by these variables declined in importance throughout the 1990s.
Finally the question of whether the associations identified above between CPRET and each of the disclosure variables (in their coded
form CPCSR, CPENV, CPVOL) could safely be attributed to a direct relationship between returns and disclosure, or whether the
association was largely due to the relationship between returns and company size, as measured by turnover was examined. To address
this issue the partial correlation between CPRET and each of the coded disclosure variables, is estimated while controlling for CPTURN
[43]
. The partial correlation results from this analysis are 0.303 for CPCSR (p = 0.000), 0.287 for CPVOL (p=0.000) and –0.012 for
CPENV (p=0.768). We therefore conclude that the very significant positive correlations between CPRET and the disclosure variables
CPCSR and CPVOL over the whole period are not diminished after allowing for the confounding effect of company size, but that the
marginally significant positive correlation between CPRET and the disclosure variable CPENV may be due to multi-collinearity among
the variables CPRET, CPTURN, and CPENV.
In summary, returns are related to CSRTOT, provided that we code the data to take account of yearly variation in both of these variables,
and this is not due to both variables being related to company size; returns were also related to VOLTOT, in the earlier years of the
study; however they were not related to ENVTOT.
This statistical exploration of whether or not there might be a relationship between social and environmental disclosure and stock market
behaviour can be usefully re-articulated in non-statistical language [44] .
We examined two data sets. The first data set was the volumes of (selected) social and environmental disclosures derived by content
analysis of the annual reports of the largest 100 UK companies for each of 10 years. (For reasons expressed in the text we concentrated
upon the values for: total social disclosure; total voluntary (as opposed to mandatory) disclosure; and environmental disclosure). The
second dataset was the stock market returns earned by the ordinary shares of those companies in each of those years. Because of the
way in which the (annual) returns are calculated, we ended up with only nine years of returns from this data.
This data was then subjected to fairly standard statistical testing. We sought to see if the data sets could be said to: demonstrate linear
numerical association (the Pearson Correlation tests); be capable of expression in a simple linear model in such a way that the returns
figure could be shown to be directly influenced by the disclosure figure (the regression analysis); demonstrate a non-linear relationship
(the chi-square tests); be capable of expression in a more complex general linear model such that returns could be shown to be
influenced by the disclosure values, the size of the company, the year of the disclosure and interaction between these; and be indicative
of a broad predisposition for those companies with higher returns to engage in higher levels of disclosure. (In this last case the measures
are coded into percentage ranks and subject to both Pearson Correlation and chi-square tests).
Each of the first four tests was repeated using monthly returns - as opposed to annual returns – in order to try and overcome the
crudeness of using only annual returns (which will be influenced by a great many factors of which annual disclosure is unlikely to be a
large part).
A priori it did not seem especially likely that there would be any particularly overwhelming, direct relationship between share returns and
social disclosure (as, if there was any such relationship, it would be obscured by many other issues) or that share returns would so
obviously and directly "reward" companies for making social and environmental disclosures. The previous literature was largely
inconclusive on these matters and, in our judgement, if anything a little optimistic. Although the first four types of tests (on both annual
and monthly returns) suggested the existence of some relationships (or probable relationships) in the data, these suggestions were
neither strong nor consistent and we are led to conclude that such relationships either do not exist or, if they do exist, they are different
from and/or more complex than these tests were able to detect.
However, a far more plausible scenario lies behind the fifth in the series of tests (in which the variables are "coded" into CPRET etc). In
crude terms this test does not examine the questions: "does x cause y?" or "is x directly associated with y?"; but rather: "over a period of
nine years does an average high (or low) of x seem to be associated with average high (or low) of y?". That is, do companies with high
(low) returns over a period of time tend to be the sorts of companies that also produce high (or low) volumes of social and environmental
disclosure. The answer to this seems to be a fairly persuasive "yes".
Now each of these results is, like all positivistic/statistical studies, dependent upon assumptions, measurements, samples and the like.
One tries to overcome these difficulties by a number of means such as applying different (potentially confirmatory) tests; subjecting the
data to sensitivity analysis and, for example, maintaining a high confidence level (i.e. ensuring that we are only persuaded by the most
persuasive of results). Each of these has been applied to a degree but, in the end, what is persuasive to the mind? To our mind the only
assumption that remains bothersome is that about the industry categorisation. Whilst size (clearly an important variable) can relatively
easily be controlled for, industry classification is really exceptionally untrustworthy and gets even more muddy when, as did we, the
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classifications are lumped together for the purposes of helping the statistics along. This remains a "maintained" hypothesis and it is not
clear to what extent the role of industry would confound or clarify these results. It is, like so much else, informed guess work. As a result,
analysis based on industry findings were omitted from the current paper.
6. Discussion
The relative paucity of published studies exploring the relationship between social and environmental disclosures and market
performance may partly be explained by the absence of data sets (such as the Ernst and Ernst data set), however, our experiences in
the first set of tests reported here suggest further reasons for this situation. Most obviously, it is not possible to undertake a conventional
events study to seek to establish responsiveness of returns to social and environmental disclosures – not least because of the plethora
of other announcements made by companies which are almost certain to have far greater price-sensitivity than the disclosures we have
examined. Consequently, we have sought to find ways in which to establish associations between the market returns and the
predisposition of companies to undertake social and environmental disclosure. We initially assumed that annual data might well be
sufficient to expose this relationship if, indeed, it exists. This proved not to be the case. However, the coding process through which
relative performances through time were examined brought us closer to the issue of interest and, indeed, produced some highly
significant results. The most important of these was that, over a period of time, total social and environmental disclosure is significantly
related to market returns even after adjusting for the size effect.
More formally, the relationships, such as they were, between share price returns and total social and environmental, voluntary social and
environmental and environmental disclosures varied from year to year, varied across different forms of disclosure and swung between
positive and negative over time (see Table 2). None of these relationships were significant. Equally, within the variables tested here, a
dummy variable for the year of analysis and an adjustment for size had far greater influences on returns than did any of the disclosure
variables - whose influence was, again, not significant, (Table 4). The key significant results arose as a result of coding the data (for both
returns and for disclosure) in terms of relative ranking over time in order to catch the companies' predisposition or predilection to
disclose. These results were arresting and we can conclude that companies within this sample with consistently lower returns are likely
to have consistently lower levels of total and voluntary social and environmental disclosure in their annual reports. Equally, companies
with consistently higher returns are likely to have consistently higher levels of total and voluntary social and environmental disclosure.
The result is maintained when size is adjusted for. These results are apparent for environmental disclosure. Equally, although the
relationship for the whole period is strong, the year on year results are insignificant, unstable and seem to get weaker over time. To what
extent such results are confounded by the growth in stand-alone environmental reporting over this period is a matter for further enquiry.
What these results highlight is the continuing lack of clear theory to explain the putative relationship between a company's market
performance and its social and environmental disclosure decisions. Whilst many theories could be adduced in an attempt to explain why
either investors do or do not respond to social and environmental disclosures or why higher disclosing companies are – or are perceived
to be – a better economic prospect by financial market participants there are no clear reasons to choose any one which might best
explain our findings. On the basis of our first set of tests, we would, indeed, be ambitious to draw any conclusions on the grounds that (a)
it is difficult to be certain that an absence of results means an absence of effect and (b) explaining an absence of results inevitably
involves a greater degree of speculation. On the evidence of the final tests, however, it seems that we cannot infer that such disclosures
are wastefulness on the part of management which are ignored or discounted by the market. Whether we might interpret this as
evidence of, for example, a growing social and environmental concern amongst investors, successful signalling by management or just
one manifestation of the practices of the better management teams is, at this stage, purely speculation.
Clearly further work is needed [45] and, as a final point, we would wish to stress that the interest in the – apparently still relatively marginal
– phenomena of social and environmental disclosure is not motivated by a concern to better explain share price movements and/or to
help enhance the returns of diversified investors [46] . In the absence of convincing evidence that social welfare (including sustainability)
will be best achieved by the self-serving short-term self-interest of market participants, our concern remains to explore how the
astonishingly powerful institutions that are financial markets can be persuaded to act in more socially and environmentally sensitive
ways. Such evidence as we have reviewed in the paper and have been able to garner from the analysis suggests that, at the margins at
least, this ambition is not entirely hopeless. If further evidence could be gathered to suggest that markets can be persuaded to start to
see the social and environmental implications of their financial decisions then a practical case can be added to the moral case that
substantive social and environmental disclosure needs to become a regular, significant and regulated part of corporate disclosure. Only
then might we see whether the optimism of, for example, Schmidheiny and Zorraquin (1996) that financial markets can be a major force
for global sustainability has any foundation at all.
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[1]
The work from which this paper draws is supported by the Institute of Chartered Accountants of Scotland (ICAS) whose financial
support of the Centre for Social and Environmental Accounting Research (CSEAR) to undertake research into the relationships between
social, environmental and financial matters affecting reporting is gratefully acknowledged.
[2]
The authors are very pleased to acknowledge the helpful comments received from colleagues at the University of Glasgow and at the
APIRA 2001 Conference at the University of Adelaide. In addition, the comments of Craig Deegan, John Holland, Rob Watson and two
anonymous referees are especially acknowledged.
[3]
Alan Murray is a Lecturer at the University of Sheffield. Donald Sinclair and David Power are respectively Senior Lecturer and
Professor at the University of Dundee, Scotland and Rob Gray is Professor of Social and Environmental Accounting, the University of St
Andrews.
[4]
We should record that the prospect of corporations and financial markets delivering sustainability is one which should be treated with
some considerable scepticism, (see, for example, Kovel, 2002). However, it is almost certainly the case that any solution aimed at
delivering the possibility of sustainable ways of organisation must directly and firmly address the role(s) of corporations and financial
markets.
[5]
This perspective is one which, obviously, does not accept that short term economic wealth seeking and maximisation leads to
long-term maximisation of social welfare. In short, that assumption is not accepted because, as far as we are aware, there is little
evidence in support of it and considerable evidence against it. In particular, as social welfare must, we would argue, embrace the
exigencies of sustainability (satisfaction of the needs of the present without impairing the ability of future generations to satisfy their own
needs, United Nations WCED, 1987) and there is no evidence that current forms of (relatively) unbridled international capitalism are
doing other than diminishing sustainability, the a priori case against the normal assumptions of liberal economics seems self-evident,
(see, for example, Gray and Bebbington, 2000; 2001; for an introduction).
[6]
The voluntary nature of most social and environmental disclosure currently makes the bulk of such disclosure relatively undemanding.
The disclosure is "inadequate" in that it fails to offer a complete picture of an organisation's social and environmental interactions and,
thus, does not hold the organisation accountable in this area. However, the more recent growth in production of stand-alone social and
environmental reports has demonstrated that some organisations are quite capable of producing substantial disclosure should they wish
to do so. It is not ability that is currently lacking but willingness.
[7]
There is, of course, considerable disclosure in stand alone social, environmental and sustainability (sic) reports from those companies
that produce such reports. This is not the place to explore the nature of that disclosure or to whom the disclosure is directed. Our focus,
for good or ill, in this paper is on disclosure through the annual report and , therefore, disclosure clearly directed towards financial market
13 of 16
participants.
[8]
The discussion here obviously simplifies the relationship between investor, morality and company (see, for example, Reilly and Kyj,
1990; Jackall, 1988) and the notion that we should hope to see any relationship between financial variables and such disclosure does
not go unchallenged (see, for example, Hines, 1984; Cooper, 1988).
[9]
The research in this paper seeks to appeal to colleagues in both the areas of finance and social and environmental accounting
research. The appeal is initiated by: an increasing recognition that financial markets are crucial to our understanding of the social and
environmental issues that exercise us; a concern to try and engage our finance colleagues to turn their attention to such issues; to
explore, however indirectly, the current rhetoric of the financial institutions about the commensurability of economic and
social/environmental goals (an issue whose context is the growth in ethical investment); and, finally, a direct concern to question the
amorality on which so much of the finance literature depends.
[10]
Selected from the Times 1000 on the basis of turnover.
[11]
This follows the recommendation of the editors – a recommendation with which we are glad to comply. Too many papers of a
quantitative nature seem, in amongst the delights of the detail, to lose both sight of the essential question they are seeking to address
and can lose their less statistically-excited readers.
[12]
There are, of course, possible explanations for these phenomena. Not least of these would be a political economy argument that
these disclosures are intended to legitimate the system of capitalism rather than to act as legitimating (or equivalent) devices at the level
of the individual firm.
[13]
This remark, although we would maintain it to be true in essence, is perhaps too dismissive of the efforts and development that gone
into this line of research – research which has often been prompted directly by Ullmann's comments (see, for example, Patten, 2002).
More especially, greater refinement has been brought to the examination of the issues raised by Ullmann (see, for example, Richardson
et al., 1999) and, at least from a managerialist stand point, linkages between certain elements of "socially responsible activity" and
financial performance have been identified, (see, for example, Liedtka, 1998; Friedman and Miles, 2001).
[14]
There is a potential tautology here in that something which 'pays' is more likely to be financial than not. See Gorz (1989) and
Thielemann (2000) for particularly good analyses of the colonisation of human values by the economic.
[15]
It is, of course, impossible to prove a negative and therefore to substantiate that there are few such studies is challenging. A review
of papers which have previously reviewed this literature would confirm that there appear to be few such studies. More substantively we
would note that (a) there has been no publicly available database of corporate social and environmental disclosures since the
termination of the Ernst and Ernst studies in the 1970s (until very recently in the UK - see below) and this would discourage large
statistical studies; and (b) as we will show, there are few statistically visible results that emerge from examining disclosure and share
price response and papers with no, or inconclusive, results can be difficult to publish, (see, for example, Booth et al., 1987).
[16]
Environmental Protection Agency – in this context typically the US EPA.
[17]
Council on Economic Priorities, a US NGO.
[18]
The choice of the UK "Top 100" companies is driven by the availability of data in the CSEAR database – which is, as far as we can
tell, a unique resource. The restriction to the Top 100 in that database is justified by practicability (to make the database manageable)
but also because this is the sample that is most comparable with other studies (where size is recognised as a key influential variable in
determining disclosure practices) and comprises the organisations most likely to undertake the most extensive and innovative social and
environmental disclosure (see, for example, Gray et al., 1995a)
[19]
See Gray et al (1995b) for a detailed discussion about how this database was constructed and a comprehensive overview of its
contents from 1988 to 1994. More detail about the database and the data itself can be downloaded from the CSEAR website at www.standrews.ac.uk/management/csear
[20]
A hint which is also plausible on an a priori basis in that environmental activities are the most likely to have direct financial impacts
on the company (see, for example, McMillan, 1996).
[21]
We would note that all environmental disclosure in the UK is voluntary at the time of writing.
[22]
Content analysis is a detailed method, drawn from semiotics, through which textual data can be "objectively" captured for further
analysis. See Gray et al, (1995a; 1995b) and the CSEAR website for more detail. Content analysis is used here as a data capture
process, the analysis of that data follows in the next section.
[23]
The share prices themselves are annual mid-market closing prices and they have all been obtained from Datastream.
[24]
That is, of the original 168 firms, 68 had to be removed due to the data requirements explained above.
[25]
An increasing number of companies produce stand-alone environmental (and, indeed, social) reports as the period of study
progresses. These are excluded from the analysis for a variety of reasons, not least being that the annual report is primarily targeted at
shareholders whilst the environmental report is not.
[26]
Broadly relevant and substantial work in the UK does exist – notably Toms, 2000; 2002 – but it does not address the same range of
issues as we seek here.
[27]
The tests reported here are based upon annual share price data. However, as will be seen below, the lack of persuasive results in
many of the tests commended to us a replication of these tests using monthly share price data as well. These tests proved to be largely
confirmatory. Only the conduct and broad results of these tests are reported here in footnotes at the appropriate points in the text.
[28]
Because of the relatively small numbers in several of the industries, we additionally explored the data through the construction of
three sectoral groups for the statistical analysis of the paper. These groups were based on estimations of the sectors' coherence and
14 of 16
"environmental profile" and, whilst broadly in line with other such groupings in the literature, must inevitably be treated as a maintained
hypothesis. Group A ("low environmental profile") includes Mechanical and general engineering; Food and drink; Retail and leisure;
Electrical and telecoms; and General sectors. Group B ("high environmental profile") includes Chemical, Oil and Gas; Pharmaceutical
and General Manufacturing companies. Group C ("medium environmental profile") includes all the other firms. These groupings
attempted to combine companies from similar industries together while facilitating a policy of differentiating between Groups to the
largest extent possible. This exploratory grouping did not add significantly to the results and, given inevitable doubts one might have
about such a maintained hypothesis, could have obscured the claims of the paper if they had done so. The results from this exploratory
sectoral grouping are reported briefly in footnotes where appropriate. The sectoral grouping resulted in 368 observations n Group A, 92
observations in Group B and 206 observations in Group C.
[29]
In addition, regression analysis was employed to determine whether there is a linear relationship between company disclosures and
share returns. The regression was estimated separately; namely for CSRTOT, VOLTOT and ENVTOT across the 14 different sectors
spanned by the data. The co-efficients bj were then examined and tested against the null hypothesis that no relationship exists between
the variables being examined. No rejections of the null hypothesis were uncovered.
[30]
Other cut-off points were tested for the low, medium and high categorisation but the results remained virtually unchanged. These
findings are available from the authors upon request.
[31]
Based on the cut-off points, 120 observations were classed as low return, 301 as medium return and 239 as high return firms.
[32]
These cut-offs resulted in 214, 248 and 198 observations being classified as small, medium and large CSRTOT disclosers.
[33]
With these cut-off points, some 217 observations related to relatively "small" amounts of VOLTOT information, 258 related to
"medium" amounts of VOLTOT data and 185 related to "large" amounts of VOLTOT news.
[34]
These cut-off points resulted in 193 small disclosures, 285 medium disclosures and 182 high disclosures.
[35]
CPRET is used as an abbreviation of Coded Percentage RETurns. The same convention is used for each of the coded variables
discussed here.
[36]
In addition to repeating the tests with monthly data, all the analysis was performed with lagged disclosures as well as with the actual
disclosures in the year of study. The correlation results with lagged disclosures were slightly better with three significant co-efficients
being observed (CSRTOT in 1991, VOLTOT in 1990 and ENVTOT in 1990) however one would expect 3.6 out of 36 p-values to be
significant at the 10 per cent level when the null hypothesis of "no relationship" holds.
[37]
This picture is confirmed when the correlations are calculated for the three sectoral groupings we introduced above. Indeed, four of
these nine correlations (that is, between each of the three sectoral groupings and each of CSRTOT. VOLTOT and ENVTOT) are negative
suggesting an inverse relationship between share price performance and the volume of disclosure. However, the correlations are small
and none are statistically significant. Interestingly, though the largest correlation is achieved by the Chemicals, Pharmaceuticals and Oil
& Gas firms grouping for the ENVTOT variable. These sectors in environmentally-sensitive industries have a positive correlation
between the volume of their environmental disclosures and share returns of 0.116 which is nearly twice the size of the next highest
correlation of 0.058 reported for CSRTOT. Again though, the p-value of 0.272 is still above the critical value of 0.05 thereby not allowing
the null to be rejected.
[38]
The same analysis was repeated for the observations in each the constructed sectoral grouping and the observations in each year.
For the three groupings, the chi-squared values range from 0.943 (with a p-value of 0.918) to 7.292 (with a p-value of 0.121) which all
fail to reject the null hypothesis of no (linear or non- linear) association between the return groups and the disclosure groups for each of
CSRTOT, VOLTOT and ENVTOT.
[39]
And this is even if we had not determined to retain the more cautious 5% level throughout the analysis.
[40]
These tests were repeated using monthly, as opposed to annual, share price data. As monthly data were not available for all firms the
sample was reduced (to 461 observations over 68 firms). This also had the effect of reducing the number of sectors represented and
somewhat further skewing the data. The results were broadly the same (as with the annual data) although, when we repeated the tests
on the sectoral groupings, there did appear to be a significant relationship between monthly share returns and CSRTOT for the (Group
B) Pharmaceuticals and the Chemicals, oil and gas sectors. Sectoral relationships on a year-by-year basis produced, where significant
at all, negative coefficients suggesting perhaps that investors are reacting negatively to CSR disclosure. Where statistically significant
relationships could be identified, they were isolated and tentative. As with the annual data, whilst the suggestion of a potential
relationship between social and environmental disclosure and share price returns is not beyond the bounds of credibility, these data and
tests do not encourage particular enthusiasm about such relationships.
[41]
Therefore, although no correlation between CPRET (the coded variable for share price returns) and CPENV (the coded variable for
environmental disclosure) is significant in any individual year, the overall correlation of 0.098 is significant with a p value of 0.012. Such a
result may be attributable to the larger sample size for the overall test as well as to the fact that each of the nine annual correlations is
positive and the combined evidence allows the null hypothesis to be rejected.
[42]
The chi-squared test statistic in this case has four degrees of freedom, one of which could be identified with a linear component and
would have a p-value similar to that of the correlation coefficient. The remaining three degrees of freedom component would focus on the
non-linear aspect of the relationship between the two variables.
[43]
These results are not shown in a table but provided in the body of the text. A more complete analysis of the partial correlations for
each year is available from the authors on request.
[44]
We are grateful to Lee Parker for the initial suggestion to include this section. However, the practice of articulating a bank of
statistical tests in simpler, or layperson, language is a useful one for a number of reasons. Not only does it seek to make the work more
accessible to those to whom statistical method is not a natural form of reasoning but it forces the authors to focus on the initial purposes
for the investigation itself and to clarify exactly where the weaknesses, assumptions and less-persuasive elements of the enquiry lie. We
found writing this section both useful – and challenging.
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[45]
And quite possibly, that further work might be better directed at field work and actually tracking reporting decisions on the ground.
(See, for example, Miles et al, 2002).
[46]
To paraphrase John Stuart Mill, it is a matter of some puzzlement why it should be a matter of congratulation that a man (sic) who
already has a great deal has acquired even more. And, in a more directly relevant sense, see Mathews (1987).
© CSEAR, School of Management - University of St Andrews The Gateway, North Haugh, St Andrews, KY16 9RJ. Scotland, UK
Tel: +44 (0)1334 46 2805; Email: [email protected]
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