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This is the accepted manuscript for the publication:
Rees, W., & Rodionova, T. (2015). The Influence of Family Ownership on Corporate Social
Responsibility: An International Analysis of Publicly Listed Companies. Corporate
Governance: an International Review. 10.1111/corg.12086
The Influence of Family Ownership on Corporate Social
Responsibility: An International Analysis of Publicly Listed
Companies
William Rees and Tatiana Rodionova
* Address for correspondence: Tatiana Rodionova, The University of Edinburgh
Business School, 29 Buccleuch Place, Edinburgh EH8 9JS, UK. Tel.: +44(0)131
6503789; E-mail: [email protected].
Acknowledgements
The authors greatly appreciate helpful feedback received at the paper development
workshop of the Family Business Conference 2014 in Singapore. The authors are also
thankful to the participants of British Accounting and Finance Association (BAFA)
Annual Conference 2014, to workshop participants at the universities of Amsterdam
and WHU and to Prof. Jo Danbolt and Susan Hancock for helpful comments and
advice. Finally, the authors would like to particularly thank the Associate Editor of
the special issue and three anonymous reviewers for their insightful and useful
suggestions.
The Influence of Family Ownership on Corporate Social
Responsibility: An International Analysis of Publicly Listed Companies
Manuscript Type: Empirical
Research Question/Issue: We investigate the impact of family equity holdings on
three indicators of corporate social responsibility: environmental, social and
governance (ESG) rankings. We further evaluate how firm governance mediates the
effect of family ownership on environmental and social improvements and how
national governance systems influence the response of family holdings to ESG.
Research Findings/Insights: Based on a sample of 23,902 firm year observations
drawn from 2002 to 2012 covering 46 countries and 3,893 firms, our findings show
that both closely held equity and family ownership are negatively associated with
ESG performance. When we control for governance, closely held equity is no longer
associated with environmental and social rankings but family ownership retains a
significant negative association. These results are strong and consistent across liberal
market economies (LME) whereas coordinated market economies (CME) exhibit
generally weaker results and considerable diversity. Japan stands out as different from
the other countries examined in depth.
Theoretical/Academic Implications: Our results are consistent with agency
relationships driving decisions concerning ESG commitment in LMEs. They also
emphasize the role of institutional differences given the weak and variable association
between ownership and ESG in CMEs. We show that families may be able to
2
influence decisions, possibly through participation in management, despite normally
effective governance constraints. As the impact of ownership and governance varies
across economies and ownership type this implies that both agency and governance
should be evaluated in the context of the economic environment.
Practitioner/Policy Implications: Our results offer insights to regulators and policy
makers who intend to improve ESG performance. The results suggest that
encouraging diversified ownership is particularly important in LMEs, that
improvements in governance may benefit social and environmental performance
where equity is closely held by institutions, but that governance may be less effective
in the presence of family ownership.
Key words: Corporate Governance; Corporate Social Responsibility; Environment;
Family Firms; Closely Held Equity.
3
INTRODUCTION
We examine the impact of closely held equity, and in particular family held equity, on
corporate social responsibility as reflected in publicly available scores of the
environmental, social and governance (ESG) performance of firms. These issues have
been receiving increased attention from regulators, investors and businesses, and the
question of what drives or hinders environmental, social and governance performance
is gaining prominence (Aguilera, Rupp, William, & Ganapathi, 2007; Campbell,
2007). Prior work has addressed this question mostly from an institutional (Aguilera
& Jackson, 2003; Campbell, 2007; Ioannou & Serafeim, 2012; Kang & Moon, 2012;
McWilliams & Siegel, 2001) or a resource perspective (Arora & Dharwadkar, 2011).
However, much of the influence on ESG investment comes from the shareholders of
the firm, particularly influential blockholders who monitor management (Barnea &
Rubin, 2010; Shleifer & Vishny, 1986). While there is some evidence of the negative
impact of blockholdings on corporate social responsibility, little attention has been
given specifically to the influence of family equity holdings (Barnea & Rubin, 2010;
Mackenzie, Rees, & Rodionova, 2013; Rees & Rodionova, 2013). This is potentially
important as family owners often retain control of the company management thereby
increasing their influence on decision-making (Faccio & Lang, 2002; La Porta,
Lopez-de-Silanes, & Shleifer, 1999; Le Breton-Miller & Miller, 2006; Silva &
Majluf, 2008).
This paper aims to fill a gap in the literature by directly investigating how
family ownership affects the ESG practices of firms. We expect families to differ
from other closely held blockholders as they have their personal wealth invested in
the firm and have both financial and socio-emotional incentives with regards to the
4
firm’s performance and viability (Kappes & Schmid, 2013). Further, we are interested
to see whether and how corporate governance and the national economic system
influence the relationship between family ownership and environmental and social
performance. Corporate governance aims to balance interests of different shareholders
and stakeholders of the firm and has been shown to influence corporate social
responsibility (Aguilera, Williams, Conley, & Rupp, 2006; Jo & Harjoto, 2011). It can
therefore affect the power that family owners have over the decision-making in the
firm, and may alter the impact of family equity on environmental and social
investments. We also investigate the impact of differences in the national economic
systems that have been shown to influence corporate behavior with regards to social,
environmental and ethical issues (Campbell, 2007; Kang & Moon, 2012). Whilst the
national governance systems may influence the base line ESG performance in an
economy, we also investigate whether these differences influence the impact of equity
ownership on ESG.
Our sample consists of 23,902 firm/years drawn from 2002 to 2012 for 46
countries, mainly representing developed economies. The initial results are based on
conventional regression techniques where the social, environmental or governance
performance is modelled against the test variable identifying the closely held equity
and a set of control variables accounting for year, industry, country, leverage,
profitability, market-to-book and capitalization. We find closely held equity, and even
more so family shareholdings, to be associated with lower ESG levels.
However, simply demonstrating an association between blockholdings and
ESG scores does not show that the ownership structure causes the low ESG levels. In
the case of family ownership reverse causality would imply that low levels of ESG
attract family investors (or would encourage them to retain their family ownership)
5
while high ESG levels prompt family owners to reduce their positions in the
company. The latter implies that high ESG expenditures (expressed in high ESG
ratings) could not be countered by direct action from powerful entrenched owners.
We argue that in the case of influential and entrenched family ownership this is
unlikely. We also address the causality issue empirically by using quantile regressions
to investigate the relationship between ownership and ESG levels for cases where the
ESG level is high. Here we obtain a stronger negative impact of family ownership on
ESG rankings for firms with relatively high ESG scores. This is inconsistent with the
argument that low ESG levels attract family ownership. Our results from the
regression models are confirmed when we use a propensity score matching (PSM)
approach that attempts to mitigate the endogeneity difficulty inherent in conventional
regression modelling (Rosenbaum & Rubin, 1983).
This study offers several contributions. Firstly, we add to the literature that
seeks to understand the relationship between ownership, governance and social
responsibility. In particular, investor influence on corporate social responsibility is a
growing but still an under-researched area, with most attention hitherto paid to
institutional ownership (Cox, Brammer, & Millington, 2004; Sjöström, 2008). Our
analysis highlights the role of closely held ownership, and in particular family
ownership, as an important influence on ESG investments across an internationally
diverse sample of firms.
Further, we contribute to the literatures on family governance and the
interaction between internal governance, national governance and influential
monitoring owners. Emerging literature suggests that there is an increasing trend for
corporate governance to reflect the interests of stakeholders rather than solely
shareholders of the firm (Jo & Harjoto, 2012; Ricart, Rodriguez, & Sanchez, 2005;
6
Spitzeck, 2009). Here our findings highlight that family owners differ from other
blockholders. While high levels of internal governance counterbalance the influence
of the closely held equity on environmental and social investment, family owners are
able to circumvent governance and preserve their influence regardless of the
governance system. We also show that the impact of ownership on ESG varies
depending on economic and institutional environments. In particular the negative
impact of ownership on ESG is concentrated in LMEs. These findings are consistent
with recent arguments suggesting that more attention should be paid not to a
particular governance mechanism per se but to its relationship with other internal
governance provisions and the national governance system (Aguilera et al., 2006;
Yoshikawa, Zhu, & Wang, 2014).
From the theoretical perspective, our study enriches understanding of the
motivations of family ownership. Family owners are thought to be extremely long-
term in outlook and to be particularly concerned about the relationships with
stakeholders to ensure firm survival and well-being (Le Breton-Miller & Miller, 2006;
Le Breton-Miller & Miller, 2009; Yoshikawa et al., 2014). Our results, however,
indicate that, when it comes to investments that foster social good but do not
guarantee financial returns, families tend to act as financial wealth maximizers and
tend to hinder such expenditures.
PRIOR RESEARCH AND HYPOTHESES
Closely Held Ownership and ESG Performance
Improving environmental, social and governance performance has become a major
challenge for the corporations. Some ESG developments may advance operational
7
performance (Berry & Rondinelli, 1998; Edmans, 2011), and academic evidence
suggests that excellent ESG performance can be a source of competitive advantage
(Aguilera et al., 2006; McWilliams & Siegel, 2001; Porter & van der Linde, 1995).
For example, ESG projects may bring strategic benefits by improving relationships
with stakeholders, including consumers, suppliers and employees (Becker-Olsen,
Cudmore, & Hill, 2006; Bénabou & Tirole, 2010; Brekke & Nyborg, 2008;
McWilliams & Siegel, 2001; Siegel & Vitaliano, 2007; Turban & Greening, 1997).
Such developments have been shown to increase the market value of the firm (Jo &
Harjoto, 2011; 2012). However, ESG projects require substantial investment, e.g.
where a company aims to reduce toxic pollution or restrain the use of pesticides in the
supply chain. Chatterji and Toffel (2010) argue that companies are particularly likely
to improve their environmental practices where they offer ‘low-hanging fruit’
opportunities. However, many ESG developments may be negative NPV investments,
e.g. withdrawal from drilling in an ecologically sensitive area, or price restraint by
pharmaceutical firms. Agency theory suggests that managers may overinvest in such
projects to serve their personal interests including a ‘warm-glow effect’ and favorable
professional reputation (Barnea & Rubin, 2010; Bénabou & Tirole, 2010).
Consequently, whether or not the firm invests in ESG improvements becomes a
source of the conflict of interest between managers, shareholders and broader
stakeholders of the firm (Cespa & Cestone, 2007; Orlitzky, Schmidt, & Rynes, 2003).
Academic evidence has argued that blockholders have the incentives and
ability to monitor management to ensure that their interests are satisfied (Burkart,
Gromb, & Panunzi, 1997; Demsetz & Lehn, 1985; Jensen & Meckling, 1976; Shleifer
& Vishny, 1986). These large owners bear the cost of investment in ESG projects
(Cox et al., 2004) and have the influence to constrain ESG initiatives. Prior literature
8
offers some, albeit inconclusive, evidence of this negative relationship (Barnea &
Rubin, 2010; Ioannou & Serafeim, 2012; Rees & Rodionova, 2013). Our main aim is
to isolate the influence of family holdings specifically and compare it to the influence
of other closely held equity, but we first revisit the question of the relationship
between all closely held stock and corporate ESG levels.
Hypothesis 1. There is a negative relationship between closely held equity and
ESG scores.
Families and ESG Performance
Family ownership is thought to be the most common ownership structure (La Porta et
al., 1999). Faccio and Lang (2002) find that 44.29 percent of firms in 13 Western
European countries are family firms while one third of public US firms can be
regarded as controlled by families (Anderson & Reeb, 2003). Families and business
groups are also seen to dominate corporate control in emerging markets (Silva &
Majluf, 2008). Family owners are unique as they have very long investment horizons,
they are undiversified and often occupy senior management positions (Anderson &
Reeb, 2003). They also have a complex nexus of economic and personal motives with
regards to the firm (Andres, 2008).
We argue that family block ownership will have a stronger negative impact on
environmental, social and governance performance of firms than closely held equity
in general. Our main rationale is that, as families have large and long-term ownership
stakes in the firm, they will be particularly opposed to excessive ESG investment
because it may not bring personal benefits. Firstly, this is consistent with the agency
theory suggesting that large powerful owners channel the firm’s activity towards their
benefits (Shleifer & Vishny, 1986). For example, families may prioritize stable cash
flow in order to sustain a privileged lifestyle and ensure high dividend payments
9
(Barth, Gulbrandsen, & Schone, 2005; Kappes & Schmid, 2013). Further, DeAngelo
and DeAngelo (2000) find that family preferences for special dividends may influence
their investment plans.
Secondly, families may oppose ESG investments as being value destroying
(Barnea & Rubin, 2010; Rees & Rodionova, 2013). For example, the entrenchment
view suggests that activities related to corporate social responsibility may be used by
the entrenched management to advance their agenda by appealing to non-financial
stakeholders (Cespa & Cestone, 2007). Given their large equity positions and
financial interest in the firm, family owners may then be expected to constrain these
developments.
Thirdly, family owners may consider themselves to be better monitors and to
have better knowledge of the business. Indeed, their long historical presence in the
firm and personal attachment can give them unique knowledge of the business and
can make them well-placed to monitor decision-making (Anderson & Reeb, 2003; Le
Breton-Miller & Miller, 2006; Sraer & Thesmar, 2007). In order to keep control and
ensure family participation in management, family owners may forgo governance
improvements (Andres, 2008; Hillier & McColgan, 2009).
Finally, although we previously argued that closely held equity in general will
be associated with lower ESG performance, we argue that this effect will be less
strong than in the case of families. Indeed, some blockholders may have motivations
to resist ESG developments to a lesser extent. For example, the state has to address
the issues of the quality of life and environmental concerns and may therefore not
entirely oppose the efforts of the corporations regarding ESG improvements (Dam &
Scholtens, 2012; Rees & Rodionova, 2013). More diversified equity holders, such as
investment institutions, rely on multiple markets and may be affected by the economic
10
consequences of political and social instability or environmental damage caused by a
weak ESG position (Gjessing & Syse, 2007). Further, they have to preserve their
reputation to sustain competition for funds, and exhibiting higher ESG involvement is
an important way to improve corporate image (Godfrey, Merrill, & Hansen, 2009).
Finally, pension funds are facing increasing pressure from their beneficiaries for
socially responsible investment (Cumming & Johan, 2007). Conversely, family
owners typically invest their wealth in the firm (Anderson & Reeb, 2003).
Consequently, they do not have the reputational pressure for social and environmental
responsibility from the beneficiaries.
Based on the evidence above, we argue that, as families have private wealth
invested in the firm and have long-term commitment to this investment, they will be
guided by personal benefits and will have less motivation to take ESG issues into
consideration. We then predict the following relative relationships between ownership
and ESG:
Hypothesis 2. The negative relationship between closely held ownership and
ESG scores is stronger for family shareholdings than for those of other
blockholders.
The Mediating Impact of Internal Governance
Agency theory suggests that internal governance aims to align interests of managers
and investors, and to ensure that corporate decisions are made to offer shareholders
the return on their investment (Gillan & Starks, 2007). Such a view implies that
management would not support excessive ESG (Barnea & Rubin, 2010). More
recently, it has been suggested that good governance serves (or should serve) the
interests of various stakeholders (Aguilera et al., 2007; Spitzeck, 2009). Strong
11
governance would then prevent corporations from having a detrimental impact on
their stakeholders, e.g. via lost pensions or social instability, and improve their
corporate social responsibility. Jo and Harjoto (2011; 2012) tested the relationship
between corporate governance and corporate social responsibility and found support
for the stakeholder interpretation of governance. Their rationale suggested that
engaging in corporate social responsibility ensures favorable relationships between
the company and its stakeholders and helps to avoid costly conflicts (Jo & Harjoto,
2012).
When a company has powerful blockholdings, these owners are likely to resist
excessive ESG, viewing it as a costly investment with uncertain benefits to the
company (Barnea & Rubin, 2010). Strong governance, however, is argued to prevent
large blockholders from imposing their agenda and ensures that the power of different
investors in the company is balanced (Shleifer & Vishny, 1986). Many investment
funds are increasingly viewing corporate social responsibility as a fiduciary duty
towards their trustees (Aguilera et al., 2007). Other diversified investors may view
environmental and social programs as an important risk-management tool or they may
favor reputational benefits of enhanced environmental and social performance
(Gjessing & Syse, 2007). Consequently, if the governance system is strong, managers
have more opportunities to take the interests of other financial and non-financial
stakeholders into consideration, and the influence of large owners with closely held
equity decreases:
Hypothesis 3. Higher levels of internal governance reduce the negative impact
of closely held equity on environmental and social scores.
However, we predict that the impact of governance will be weaker for family
owners than for other blockholders. Indeed, personal relationship of family owners
12
with the firm and undiversified ownership gives them a strong incentive to remain in
control of their firms (Burkart et al., 2003; Hillier & McColgan, 2009; Rees &
Rodionova, 2013; Shleifer & Vishny, 1986). Family owners are argued to often
occupy diverse positions in the firm and to be involved in management (Arregle, Hitt,
Sirmon, & Very, 2007; Birley, 2001). They are also shown to use informal control
mechanisms, e.g. recruiting and promoting employees whose values are closely
aligned with those of the family owners (Arregle et al., 2007; Coffee & Scase, 1985).
This reduces the manager-owner agency conflict but increases the power of family
ownership to directly influence decision-making and weakens the role of corporate
governance. Consistent with this argument, Yoshikawa et al. (2014) show that in
family-owned firms the role of outside directors is primarily related to providing
resources to managers rather than performing monitoring activities. Given families’
capture of control, we predict that their influence on ESG investment will remain
strong regardless of the governance system:
Hypothesis 4. Higher levels of internal governance do not reduce the negative
impact of family equity on environmental and social scores.
Institutional Differences and Family Ownership
Campbell (2007) has shown that national institutions influence the propensity of firms
to behave in a socially responsible way. Country-wide governance systems also define
the way that firms communicate with various stakeholders and take their interests into
consideration (Aguilera & Jackson, 2003). One categorization of institutional systems
is the liberal market economy (LME) and coordinated market economy (CME)
dichotomy proposed by Hall and Soskice (2001). Although this characterization
includes many dimensions, LMEs are crucially seen as focusing on the interests of
13
investors and managers as key stakeholders (Kang & Moon, 2012). In these systems
the stock market is the main source of capital and therefore there is greater pressure
for businesses to deliver financial returns to the equity providers. Corporate managers
are encouraged to respond to the demands of non-financial stakeholders if these
demands are consistent with long-term shareholder value creation (Jackson &
Apostolakou, 2010). LMEs are argued to have higher level of investor protection, and
other stakeholders usually have to advance their agendas via market mechanisms such
as stakeholder activism. Consistent with this setting, many of the environmental,
social and governance practices are voluntary, and the strategic use of ESG practices
and their implications for investors and financial performance are emphasized (Kang
& Moon, 2012). Given the voluntary nature of ESG and the focus on the financially
beneficial investments, families in LMEs are likely to have more incentive and power
to restrain ESG expenditures where the profits are uncertain. Further, management in
LMEs has a relative autonomy with regards to decision-making and may tend to
overinvest in ESG projects for a personal ‘warm-glow’ effect or with the strategic aim
of balancing interests of other stakeholders (Barnea & Rubin, 2010; Jackson &
Apostolakou, 2010; Jo & Harjoto, 2011). However, as families often have influential
executive representation, they are likely to have the power to obstruct these ESG
initiatives in LMEs.
In the case of CMEs more emphasis is placed on the welfare of the society in
general so firms have to respond to various stakeholders (La Porta et al., 1997; Judge,
Gaur, & Muller-Kahle, 2010). In this governance system, firms have to rely more on
networks and cooperation, e.g. with labor unions (Midttun, Gautesen, & Gjølberg,
2006). Campbell (2007) argues that firms are more likely to adopt socially responsible
practices if they are involved in the institutionalized dialogue with employees, unions,
14
community, investors and other stakeholders of the firm. Companies in CMEs,
therefore, face significant relational pressure to engage in environmental and social
practices (Aguilera et al., 2007; Young & Marais, 2012). For example, powerful labor
unions may prompt companies to act on issues that are related to employee health and
safety or their communities (Ioannou & Serafeim, 2012). Consequently, family
owners have to take these environmental and social demands into account. Further,
many ESG issues in CMEs are embedded in business practice by regulation, as
opposed to the voluntary policies and programs in LMEs (Kang & Moon, 2012).
Families may then have less scope to restrain ESG expenditures. Based on the
differences in the stakeholder power in these two institutional systems and the way
national governance can constrain family owners’ influence, we predict the following
relationship:
Hypothesis 5. The negative influence of family ownership on ESG is weaker in
coordinated market economies than in liberal market economies.
There is some consistency across LMEs in that, for example, they tend to have
large stock markets, given their GDP, high levels of investor protection and a
common law basis for their legal system; there is more heterogeneity within the CME
classification. Indeed many commentators have attempted to identify sub-groups such
as Jackson and Apostolakou’s (2010) Central, Nordic and Latin classification of
European LMEs. Whilst we recognize this diversity within the CME category, we will
use it as an initial classification to segment our sample into two clearly different sub-
samples. We also acknowledge that this will not produce homogenous groups and we
will therefore subject our results to a sensitivity analysis based on an analysis of
individual countries.
15
RESEARCH METHOD
OLS Regression Models
The initial results are based on a pooled time-series and cross-sectional sample of
international firms, based on Jo and Harjoto (2012), where we control for sample
selection bias and pool the sample across countries, industries and years. We differ
from Jo and Harjoto (2012) in that we control for countries, unnecessary in their
single economy setting, for years and for the firm-level clustering of error terms. If we
omit year dummies, we find statistically significant relationships driven by sample-
wide time trends that can appear to suggest firm-specific causal relationships where
none exist. If we omit controls for the firm-specific clustering of error terms we find
that standard errors are inflated and our t-statistics are approximately twice those
estimated when using clustering. Thus our initial models are:
ESG Scoreit = 0 + 1Closelyit + 2Familyit +
3Leverageit + 4Profitabilityit + 5MTBit + 6Log(MV)it + 7Industryit +
8Countryit +9Millsit + ylYit + eit
where ESG Score is the firm-specific assessment provided by ASSET41 for
environmental, social or governance practices, Closely2 is the percentage of equity
reported by Worldscope as being closely held by different blockholders including
employees and families, pension funds and financial institutions, individuals and other
corporations, Family3 is the percentage of equity held by family or employee
shareholders as provided by Datastream, Leverage, Profitability, MTB and Log(MV)
are the percentiles of long-term debt over equity, net income over book value of
equity, market value of equity over book value of equity and the log of the US$ value
of market capitalization respectively. We express the leverage, profitability and MTB
16
ratios as a percentile of the sample distribution to scale them in a similar way to the
dependent variables that are all calculated on a scale from zero to one hundred. Mills
is the inverse Mills ratio included to control for sample selection bias, Industry and
Country are the relative means for the dependent variables, and Y are year dummies.
We also run the model with country and industry dummies replacing the mean of the
variable for each category and find that the results are not significantly changed. The
version of the model using country and industry dummies is used for the estimation of
the inverse Mills ratio. The standard errors are clustered for firm effects.
Endogeneity and OLS Models
The model specified above is threatened by potential endogeneity. We have
incorporated the conventional control for sample selection bias, which is based on the
probability that a firm included in the ASSET4 universe is also included in our
sample. This requires that both ASSET4 ESG scores and control variables are
available and we model this using a probit version of the OLS regression with
industry and county scores replaced by dummy variables. Whilst the inverse Mills
ratio is usually statistically significant in our models, the impact of its inclusion on the
significance of the other variables is modest. This represents a standard method of
controlling for sample selection bias.
More problematic is the potential threat from omitted correlated variables.
Here we postulate that factors not included in our model, or not correctly specified in
our model, could impact on both ESG scores and family ownership. A common
approach to dealing with this is to include firm fixed effects and, if we ignore the
issues relating to strict endogeneity, which requires inter-temporal endogeneity
between the variables in the model, this could provide an informative set of results.
17
However, for our sample the inclusion of firm fixed effects cancels all significant
relationships between the explanatory variables and the dependent variable. Running
a between-effects model confirms that the explanatory power of the model is driven
almost entirely by the differences between firms and not differences within firms.
This is not unexpected given the stable nature of the variables in our model. ESG
performance and equity ownership change only slowly. Nevertheless, it is worth
retaining the panel data approach, as there are many firms in our sample for which we
only have results for some years, and using a pooled time-series and cross-section
allows us to control for year differences.
There remains the possibility that omitted factors are correlated with both our
test variable, family-held equity, and the dependent variables, ESG scores. As we
have a control variable which measures all closely held equity, that factor would have
to be related to family ownership and not to other closely held equity. Even so, it is
worth considering what other factors might have an impact on the model.
Commentators on earlier versions of this paper have suggested that the direction of
causality is an issue. Indeed, it is quite possible that investors might be attracted to or
repelled by ESG performance, and hence ESG performance may drive closely held
ownership. Our results are consistent with closely held equity being associated with
low ESG performance. This argument is tenable if investors believe that ESG projects
include at least a proportion of value-decreasing investments. It may seem less likely
for family investors. They are typically making a decision to stay with, rather than
invest in, a firm. Even here, family investors may be happier to stay with a firm that
does not invest in value-reducing projects. Therefore we investigate the possibility of
reverse causality.
18
In order to investigate the direction of causality, Jo and Harjoto (2012)
estimate their model with lagged measures of their test variables, which in our model
would be closely held, or family held, equity, and then replace the dependent variable
with the test variable and use the lagged measure of the ESG score as an explanatory
variable. They interpret their results as demonstrating that governance causes
corporate social responsibility and not the reverse. However, in our study we will find
that ESG scores and equity holdings, and indeed the governance element of ESG and
the two ‘social’ components (i.e. social and environmental), each appear to predict the
others with a significant negative coefficient on the lagged explanatory variable in
each case. This is consistent with mean reverting measures of all three variables.
Consequently, we develop an alternative method of investigating causality.
Quantile Regressions. Our approach assumes that if we find a negative relationship
between closely held stock and ESG scores this could be caused by the stockholders
influencing ESG performance or by ESG performance attracting such stockholders.
The second possibility can be reliably ruled out if we can show that firms with high
ESG scores are also adversely affected by family equity holdings. It is not clear how,
under these circumstances, it can be argued that the family stockholders have been
attracted to make, or encouraged to retain, an investment by poor ESG performance if
the ESG is, in fact, good. Conditioning the sample on the dependent variable would
be unreliable but we use quantile regressions to test the relationship between the
explanatory variables and ESG scores at different quantiles of the dependent variable.
If we find that the response between family firms and ESG is stronger at low levels of
ESG, that would be consistent with low levels of ESG attracting family ownership.
Conversely, if we find a consistent or a stronger relationship between family
19
ownership and ESG at higher levels of ESG, that contradicts the reverse causality
argument but is consistent with family ownership impacting on ESG performance.
Propensity Score Matching. Our previous discussion acknowledges that omitted
correlated variables may remain a source of endogeneity. We use propensity score
matching (PSM) as a sensitivity test that will help to rule out such explanations as
unlikely. PSM attempts to simulate random allocation between treated and control
cases by matching treated firms, i.e. those with family equity holdings, against control
firms, i.e. those without such holdings but where the control and treated firms are
equally likely to have had a family holding. By construction we will expect to find
that both groups will be equally matched with regards to the variables included in the
matching equation. Given that the control firms are a selection from the population of
untreated firms with explicit matching on a set of variables, there is no a priori reason
to expect that the treatment and control firms will be unbalanced with regards to any
omitted correlated variable from the OLS regressions. This does not ensure
independence from omitted variables but such contamination is less likely. It also
does not prove the direction of causality – only that treated firms have different
‘outcomes’ from the control firms. This difference may be because the outcome has
caused the treatment; our use of quantile regressions is designed to test whether or not
this is the case.
Sample and Descriptive Statistics
Our sample is drawn from the full international universe of firms for which ASSET4
provides ESG data4. Over the period 2002 to 2012 this is a population of 43,692
firm/years of which 25,454 have all available ESG scores. Within this sample there
20
are 1,552 instances where we are unable to identify all control variables leaving a
final sample of 23,902 cases. These omitted cases could be correlated with the
dependent and test variable causing endogeneity and, as discussed above, we control
for this by estimating and including an inverse Mills ratio in our models. Table 1
contains the descriptive statistics from our sample for which we have available data.
This sample includes 3,893 separate firms with 883 cases from 2002 rising to 3,450 in
2010 and tailing off to 1,275 in 2012. As social, environmental and governance
scores, leverage, profitability and market-to-book are all calculated to fall between 0
and 100, the means close to 50 are to be expected. The mean of closely held equity is
24.99 percent and the mean family shareholding is 3.42 percent. If we restrict the
sample to the 3,759 cases with family holdings, the value of the ESG variables all
show a clear decline, the control variables are broadly similar, the mean for closely
held equity rises slightly to 35.92 percent and the mean family holding rises to 22.91
percent. Thus, the firms with family ownership, which are the focus of our study, have
an average of 23 percent held by the family and these firms have on average another
13 percent of equity with other closely held investors.
We also present the mean for a) Japan and b) the United States (these two
being the largest country samples and representing two very different economic and
social models), c) other coordinated market economies excluding Japan and d) other
liberal market economies excluding the US (country-by-country statistics are
presented in the appendices.) Here we see the expected divergence between country
characteristics, with the US recording a high governance score and relatively low
levels of closely held stock and Japan recording a high environmental score but low
governance. Further, LMEs show relatively high governance and CMEs exhibit a high
social score, high environment and high levels of closely held stock. Family
21
ownership appears high in LMEs and CMEs but low in both the US and Japan. In our
pooled analysis we control for country differences but these are obviously important.
We therefore also present individual results for each country for which we have a
sample in excess of three hundred firm/years.
Insert Table 1 about here
Table 2 reports the correlation matrix for the variables used in our tests. We
include product moment correlations beneath the diagonal and Spearman rank
correlations above, but as most of our variables are constructed so as to rule out
outliers there is barely any difference between the two sets of correlations. The
ASSET4 social and environmental scores are highly correlated (0.76), but the
governance score is relatively modestly correlated with the social score (0.31) and the
environmental score (0.16). All three scores are negatively correlated with closely
held and family holdings, and the correlations between the ESG outcome variables
and the control variables are quite varied apart from the stable relationship between
leverage and all three measures of ESG performance. The differing responses of the
ESG scores to the other control variables and to the test variables suggest that the
social, environmental and governance scores are rather different constructs.
Insert Table 2 about here
RESULTS
Panel Data Tests of Association
Table 3 reports our initial results of the panel data analysis of the social,
environmental and governance performance of our sample. In models 1 to 3 we
investigate the impact of closely held stock on ESG scores and find a strong and
22
significant negative relationship (Model 1: =-0.07, p<0.001, Model 2: =-0.07,
p<0.001, Model 3: =-0.21, p<0.001). In models 4, 5 and 6 we add the family holding
variable to investigate whether family holdings have an association with ESG
performance beyond that explained by closely held equity. The slope coefficients on
close held equity are slightly reduced but remain negative and statistically significant
(Model 4: =-0.05, p<0.001, Model 5: =-0.06, p<0.001, Model 6: =-0.19, p<0.001)
whilst the additional impact of family holdings is strongly negative and statistically
significant in all three models (Model 4: =-0.15, p<0.001, Model 5: =-0.14,
p<0.001, Model 6: =-0.12, p<0.001). It should be noted that the full relationship
between the ESG variables and family holdings is the sum of the slope coefficients on
both closely held equity, which includes family holdings, and on the family holding
itself. Table 1 shows the mean percentage of family ownership is 22.91 percent for a
sample restricted to the firms with family ownership. This implies that firms with
family ownership typically have 4.6 points fewer on their social score (23*(-.05-.15)),
4.6 points fewer on the environmental score (23*(-.06-.14)) and 7.8 points fewer on
the governance score (23*(-.19-.15)) than firms with diversified shareholders. This
translates to a very similar impact on the ranking of firms on the three ESG
dimensions, i.e. the typical family holding for firms with family holdings would cause
a decline in a firm’s rank in the ASSET4 scores of approximately 5 to 8 percentage
points.
Insert Table 3 about here
In the final two models in Table 3 we examine whether governance intervenes
between the ownership characteristics and the social and environmental performance
by including governance as an explanatory variable. Thus we hypothesize that
ownership may impact on governance which in turn impacts on social and
23
environmental performance, but it is unclear whether ownership will impact on
performance beyond its influence via governance. Family owners are argued to
influence most important strategic decisions, often by being involved in management,
occupying diverse positions in the firm or using informal control techniques (Arregle
et al., 2007; Birley, 2001; Coffee & Scase, 1985). If family owners are more likely
than other closely held equity holders to be involved in management of the firm, we
expect a stronger relationship between ownership and social and environmental
performance for family owners, after controlling for governance, than for other
closely held shareholders. In models 7 and 8 we observe a strong positive relationship
between governance and social and environmental performance (Model 7: =0.28,
p<0.001, Model 8: =0.28, p<0.001), a now positive relationship between closely
held equity and either social (Model 7: =0.10, p<0.001) or environmental (Model:
=0.09, p<0.001) scores, but a continuing strong negative association between family
ownership and both social and environmental performance (Model 7: =-0.14,
p<0.001, Model 8: =-0.14, p<0.001). Although all other results are robust to our
sensitivity analyses, in this instance the positive coefficients on closely held stock in
models 7 and 8 are insignificant if we use an alternative model of concentrated
ownership (Datastream’s assessment of strategic holdings) or decompose the
governance variable into five components reported by ASSET4 (board function,
board structure, compensation policy, shareholder rights and vision and strategy).
This does not impact on our hypotheses but does suggest that the potentially
interesting switch in sign for closely held equity may not be robust.
The results reported in Table 3 show a clear negative association between
family shareholdings and a firm’s social, environmental and governance performance
after controlling for closely held equity in total, industry, country and year differences
24
and firm-specific estimates of leverage, profitability, market-to-book and
capitalization. These offer support for hypothesis one, that closely held equity reduces
ESG performance, hypotheses two, that family holdings have a stronger negative
impact than general closely held ownership, hypothesis three, that allowing for the
influence of governance reduces the direct impact of closely held stock holdings on
social and environmental scores, and hypothesis four, that such mitigating impact is
less strong for the influence of family holdings. However, such tests cannot
demonstrate the direction of causality nor rule out the possibility of omitted correlated
variables. In the following sections we investigate the impact of causality and then
that of omitted variables.
Testing Causality Using Quantile Regressions
We have argued that it is unlikely that family investors would be attracted by low
ESG performance. Typically, family investors gradually reduce their investment but
even then it is possible that they could be less likely to do so if the firm has low ESG.
But for those firms with higher than normal ESG we cannot argue that low ESG is
attracting or retaining family investors. Whilst testing causality may be an innovative
use of quantile regressions, we are able to estimate the relationship between family
ownership and ESG performance at different percentiles of ESG scores. We estimate
the model at each tenth percentile between and including the 10th and 90th.
Insert Figure 1 about here
We present the results graphically in Figures 1a and 1b (detailed results are
available on request). The estimated coefficients are plotted for both closely held
(Figure 1a) and the incremental effect of family held (Figure 1b) equity on social,
environmental and governance scores. This represents re-estimates of models 1 to 6
25
reported in Table 3. The coefficients for social scores are represented by a solid line,
for environmental scores by a dashed line and for governance scores by a dashed-and-
dotted line. The important result for our analysis is that in Figure 1b there is no
significant evidence of a declining response to family ownership for higher levels of
the dependent variable. For the social and environmental scores the response increases
from left to right whereas the decline for governance is minor and statistically
insignificant. It is interesting, but not directly relevant to our hypothesis testing, that
in Figure 1a the impact of closely held stock on governance declines steeply from low
to high levels of governance.
Thus, we find no evidence that the impact of family firms on ESG
performance is stronger for low levels of ESG. This is inconsistent with low levels of
ESG attracting family ownership. Further, the marginally stronger impact of family
ownership on ESG scores at higher levels of ESG suggests that the causality is from
ownership to ESG. Although it is not the focus of this study, the declining response of
governance to closely held stock at high levels of governance is interesting. Whilst
closely held stock is associated with lower governance scores, as hypothesized, this
effect is stronger for cases with low governance and is consistent with low
governance attracting closely held ownership.
Propensity Score Matching Tests of Association
Unlike our quantile regressions, propensity score matching cannot comment on the
direction of causality. However, the test attempts to simulate a randomized
experiment that explicitly equalizes the distribution of those variables used in the
calculation of the propensity scores. We find that the firm-specific variables used do
indeed have similar means across our treatment and control groups (results available
26
on request). Further, advocates of propensity score matching suggest that we can
expect other variables to be randomly distributed between the two groups. We also
find that industry, country and year averages of the dependent variables are
indistinguishable between our treatment and control groups, and these values have not
been used in the construction of the propensity scores. Thus we have no reason to
suppose that there are correlated omitted variables excluded from our model. We find
that treatment firms (with family shareholdings of more than 10 percent) and control
firms (with family shareholdings of less than 10 percent) are indistinguishable on all
other observable variables. The PSM results are reliably consistent with the OLS
results reported in Table 3. We have not included the detailed PSM results but these
are available from the authors on request.
Sensitivity Analysis
We test whether our results are robust to alternative metrics and models. In particular,
we experiment with replacing the Worldscope computation of closely held equity
with Datastream’s calculation of total strategic shareholdings. The results are very
similar and the conclusions regarding the hypotheses unchanged. In retaining closely
held equity we lose approximately 5 percent of the sample but prefer to avoid the
potential same-source bias that might arise from obtaining family holding and total
strategic holding from the same data provider. We also re-estimate the regression
models using a dummy variable to identify 10 percent closely held and family
shareholdings rather than the percentage held. Again, the results were unchanged by
the alternative approach.
To examine whether our results are driven by particular elements of the
ASSET4 ESG metrics, we investigate the robustness of our results by replacing the
27
main environmental, social and governance scores with their components. Whilst we
have access to many elements used to compute the ESG scores, we prefer to use the
main scores published by ASSET4, which are presumably designed to meet demand
from investment institutions, and avoid any possible data-mining bias that might arise
from arbitrarily selecting from the components. The social score has seven
dimensions: community, diversity and opportunity, employment quality, health and
safety, human rights, product responsibility, and training and development. All seven
dimensions have a significant negative association with closely held equity and all
have an additional significant negative relationship with family holdings. Similarly,
the environmental score has three components: emission reduction, product
innovation and resource reduction. All three are significantly negatively associated
with both closely held and family ownership.
Corporate governance has five components: board structure, board functions,
compensation policy, shareholder rights, and vision and strategy. All are significantly
negatively associated with closely held equity and all but shareholder rights are
additionally significantly negatively associated with family holdings. When used as
explanatory variables in place of the total governance score, all components have a
significant and positive impact on the social score and all but board function and
compensation policy have a significant positive impact on the environmental score.
However, in allowing the coefficient to vary across governance elements the impact
of closely held equity changes. In Table 3, where governance was used as an
explanatory variable, closely held equity had a positive impact on both social and
environmental scores. Here the coefficient on closely held is insignificant. This has no
impact on the hypotheses tested in this paper. They may, however, be important in
28
any subsequent analysis of the interaction of governance, ownership and social or
environmental performance.
Taken together, these sensitivity results suggest that the main findings
reported in Table 3 are supported by more detailed analysis. There are differences in
the strength of the relationship across components, and although Rees and Rodionova
(2013) have conducted a preliminary analysis, it would be interesting to investigate
these relationships further. However, the overall story remains the same: closely held
equity is associated with lower ESG scores in general and family holdings have an
additional negative impact. Indeed, the responses to all sensitivity checks are such that
our conclusions on hypotheses one through four are unchanged.
Country Analysis
We start by running country-specific regressions for the thirteen countries with the
largest samples, the smallest of which is 334 firm/years. This is the most direct
approach to investigate country differences and it also acts as a powerful sensitivity
analysis of the pooled results. Table 4 contains the estimated slope coefficients on our
test variables for the impact of closely held and family held equity on social,
environmental and governance performance, and on social and environmental after
including governance as a control variable. Although the slope coefficients for a
number of countries are not individually significantly different from zero, these
country-specific regressions confirm the overall statistical significance of our full
sample tests. We report t-statistics for each coefficient, chi-squared tests for the
statistical significant of the sum of closely held and family held equity and F-statistics
for the collective significance of each variable across the thirteen countries. The
estimated models are as before using the same control variables plus year dummies
29
but with country averages omitted. All statistical tests are adjusted for firm level
clustering.
Insert Table 4 about here
Of the thirteen countries the coefficient on closely held is positive for only
Italy and Spain when predicting social performance and environmental performance.
Family held exhibits a positive coefficient for only France and Germany when
modelling social performance, and for only France, Germany and Sweden when
modelling environmental performance; only Germany has a positive coefficient on
family for governance. Thus, of the 78 individual slope coefficients estimated on
closely held and family held stock 68 are negative. We estimate the collective
significance using an F-test across the 13 countries, and both closely held and family
held stock are significantly different from zero – as would be expected given our
earlier pooled results. We also cumulate the effect of closely held stock and the
additional impact of the family-held portion of it. We find that 27 of the 39 estimates
for social, environmental and governance scores are individually statistically
significant, although in one instance (the impact of closely and family held stock on
the social score in Germany) it is positive and significant.
In the models where governance is included as an explanatory variable we
expect lower levels of statistical significance. Governance is always positively and
significantly associated with both social and environmental scores. In many cases
closely held stock is positively and significantly associated with social and
environmental performance after allowing for the effect of governance. However,
family retains a negative impact on social performance in 10 instances, significantly
so in 6, and in 9 cases family is significantly and positively associated with the
environmental score, significantly so in 7.
30
Taken together, the country-by-country analysis strongly supports the general
results of the pooled tests. However, it is also clear that a) where the samples are
smaller it is difficult to generate country-specific statistically significant results and b)
there are considerable inter-country differences. This is to be expected and we have
hypothesized that we should be able to identify differences between those countries
that have a liberal market economy and those that have a coordinated market
economy. In Figure 2 we plot the country-by-country impact of family ownership (the
combined response to closely held and family variables) on governance and an
average of the response for social and environmental scores, as the individual graphs
are very similar.
Insert Figure 2 about here
Our first conclusion from Figure 2 is that Australia, Canada, Hong Kong,
Singapore, the UK and the US have a very similar and strong negative response to
family ownership. These common law countries, with large stock markets and
relatively good investor protection, seem to respond in similar ways despite obvious
social, cultural and geographical differences. Our interpretation is that the strong
agency incentives caused by the shared stock market orientation and effective investor
protection override other differences.
The second conclusion is that there is little agreement amongst the results for
the European based CMEs. These are all code law countries with relatively low
investor protection rights and, apart from Switzerland, relatively small stock markets.
The response of both social and environmental scores to family ownership is typically
weak, although strongest for Switzerland, but the response of governance is very
varied. For France, Sweden and Switzerland it seems strong, and stronger than that for
the LMEs, yet for Italy, Germany and France it seems relatively weak. A possible
31
explanation lies in the absence of the dominant influence of any single factor such as
the influential stock market effect in the LMEs and so the diversity in country
institutional and economic circumstances comes out.
Finally we should note the unique response of the Japanese sample. It is clear
that the Japanese environment is rather different to others that might be designated as
CMEs but even so the results for Japan stand out as particular. The governance
response to family ownership is similar to that for Germany and Italy; however the
association of both social and environmental scores with family ownership is
particularly strong even in comparison with the LME countries in our sample. A
possible explanation could be that Japan has a relatively large stock market which has
been a major source of financing for firms (Kang & Moon, 2012), and relatively high
investor protection when compared with other CMEs. Consequently, investors,
including families, are able to effectively resist environmental and social expenditure.
We use the results reported in Table 4 to test the hypothesis that the response
to ownership differs between LME and CME countries. Here we use classifications
from prior literature that treat Australia, Canada, Hong Kong, Singapore, the UK and
the USA as LMEs and Italy, France, Germany, Japan, Spain, Sweden and Switzerland
as CMEs (Djankov, La Porta, Lopez-de-Silanez, & Shleifer, 2008; Jackson &
Apostolakou, 2010). In validating this classification we note that all LMEs are
common law whilst all CMEs are code, that all LMEs have better investor protection,
as measured by the anti-directors rights index, than all CMEs and, apart from
Switzerland, all LMEs have relatively larger stock markets, adjusted for GDP, than all
CMEs. We do not assert that the two groups are homogenous but that there are clear
general differences between the groups (van Essen, Engelen, & Carney, 2013).
32
We find that the average response of social performance in LME countries to
the sum of the family and closely held ownership coefficients is significantly greater
(more negative) than for CME (Chi2 10.16, p<0.01), and is somewhat stronger if we
remove Japan from the analysis (Chi2 14.44, p<0.001). These results are slightly
weaker but still significant if we examine the additional impact of family ownership
alone. The result including Japan is significant at 95 percent (Chi2 4.26, p<0.05) and,
when excluding Japan from the CME sample, the result is significant at 99 percent
(Chi2 7.49, p<0.01). This is consistent with hypothesis 5.
The average response of environmental performance to the impact of family
plus closely held ownership is less robust, with the difference between LME and
CME countries insignificant if Japan is included (Chi2 0.36, insignificant) but
significant if it is omitted (Chi2 5.02, p<0.05). If we restrict our analysis to family
ownership alone our results are insignificant if Japan is included (Chi2 0.09,
insignificant) and marginally significant if not (Chi2 3.51, p<0.10). This is weakly
consistent with hypothesis 5 only if Japan is excluded from the CME sample. Finally
we are unable to demonstrate a statistically significant difference between the
responses of governance to ownership for CME versus LME countries whether or not
Japan is included, i.e. hypotheses 5 is not supported for governance.
Overall, our results suggest the need for further research. The LME countries
all respond to closely held and family ownership in similar ways. However, among
the CME countries there is considerable diversity. Japan’s social and environmental
response to ownership is much stronger than the other CME countries, and the
governance response is very diverse, with Germany, Italy, Japan and Spain exhibiting
a modest negative response, weaker than the LME countries, and France, Sweden and
Switzerland displaying a strong negative response, and stronger than the LMEs. That
33
Japan is different from the European CMEs is unsurprising given its particular
institutional and cultural characteristics (Buchanan, 2007; Kang & Moon, 2012;
Solomon, Solomon, & Suto, 2004). Interestingly, the Asian LMEs behave very much
like the other LMEs whilst the European CMEs reveal quite disparate responses of
governance to closely held and family ownership.
DISCUSSION AND CONCLUSION
It can be argued that undiversified shareholders, such as family equity holders, will
oppose ESG investment as at least a proportion of that investment may be value-
destroying. Thus, significant family shareholders may have both the influence and
incentive to resist ESG. Using a large and recent international sample we show that
closely held stock is associated with lower ESG performance as assessed by ASSET4
and that this is particularly true for family shareholdings. This is consistent with
family shareholders discouraging ESG investment but it is also consistent with low
ESG performance encouraging family investors to retain their shareholding. In a panel
data regression model, where the variables of interest are stable within firms across
time, it is difficult to demonstrate that the models are not contaminated by
endogeneity. In particular it is difficult to demonstrate the direction of causality.
Firstly we control for sample selection bias. Our propensity score matching
tests are less likely to be affected by omitted variables as they represent an attempt to
mimic random allocation. Whilst not definitively free of contamination, they offer
support for the prediction that there is a negative relationship between family equity
holdings and ESG scores. Furthermore, we use quantile regressions to test the
influence of family equity on ESG for firms that have high ESG rankings, and again
34
find a negative relationship. Thus, we show that the negative relationship holds even
where low ESG cannot have encouraged family stockholders to retain their holding.
Some limitations to our study should be noted. Firstly, throughout the analysis
we have assumed that the ASSET4 social, environmental and governance measures
are indicative of underlying performance. While we cannot directly assess whether
this is the case, previous work has shown ASSET4 scores to be highly correlated with
other measures on ESG performance such as FTSE4Good or MSCI (previously KLD)
(Semenova, 2010). Jackson and Apostolakou (2010) argue that it is an advantage
when an ESG database includes policy indicators as well as performance measures,
e.g. greenhouse gas emissions or water use. In the case of ASSET4, its scores are
based on a variety of indicators reflecting both disclosed policies and more objective
metrics. Examples of the latter in the environmental dimension include reported CO2
emissions, produced amount of hazardous waste, recycled water and energy use.
Examples of performance metrics in the social theme include percentage of revenues
generated from tobacco or gambling, number of controversies in the media linked to
public health and safety, use of employee stock options. Governance dimension
includes metrics such as board size, CEO/Chairman duality, and use of performance-
based executive compensation. In our study, we have used the aggregated
environmental, social and governance scores and tested sensitivity of the findings to
using theme subscores (e.g. instead of overall governance score we used board
structure, board function, compensation policy, shareholder rights and vision and
strategy subscores). Our results regarding the influence of family ownership on all
three dimensions remained robust to these alternative ESG measures. We have used a
variety of data sources and empirical methods and our results are clearly consistent
with the premise that closely held equity holders in general, and family shareholders
35
in particular, are associated with lower ESG performance. Future research could look
closer into the influence of family ownership on more specific ESG projects, in
particular what types of projects family firms do invest in. Prior evidence suggests
that long-term nature of family ownership and the emotional attachment of the owners
to the firm increase the propensity to invest in relations with stakeholders, such as
employee, customers and wider community (Le Bretton-Miller & Miller, 2006). Yet
empirical evidence suggests that the response of family ownership to activities in
environmental and social areas is strong and negative. Consequently, establishing the
ways that families perceive to be important to improve stakeholder environment is a
relevant issue to investigate further.
A second important caveat of our study is the ownership measure. Following
prior studies, we used the percentage of equity held by employees/families (Anderson
& Reeb, 2003; Andres, 2008; Miller, Minichilli, & Corbetta, 2013). We acknowledge
that there are other dimensions of family firms reflecting commitment to and
involvement in the firm, e.g. number of family generations or governance by a
founding member (Kuo & Hung, 2012; Maury, 2006; Miller et al., 2013). However,
ownership stake reflects both the interest in the financial performance of the firm and
the ability of the owner to monitor management decisions (Shleifer & Vishny, 1986).
Consequently, our chosen measure serves the aim of the paper to investigate how
family owners with substantial equity positions act towards environmental, social and
governance activities of the firm and how their influence is different from other
blockholders with closely held equity.
Our study has also investigated the relationship between environmental and
social scores and closely held equity via corporate governance. In the main we find
that closely held equity does not have a reliable impact on social and environmental
36
performance once governance has been accounted for. Thus, closely held ownership
may impact on social and environmental performance but mainly via its impact on
governance. Conversely, we find that family shareholdings may impact on social and
environmental scores even after allowing for the intervening effect of governance.
This result is less robust than the direct impact estimated without an intervening
governance variable but is consistent with family equity holders influencing the social
and environmental performance directly.
We are also able to use the wide international distribution of our sample to
examine how the institutional differences impact on the relationship between closely
held stock and ESG. The results for the six LME countries examined are remarkably
consistent. Ownership significantly effects ESG and in all countries. Conversely, we
find considerable diversity in the results for our seven CMEs. In all but Japan closely
held stock has little impact on social and environmental scores, and the impact on
governance varies widely with a strong response in France, Switzerland and Sweden
and a weak response in Germany, Italy, Spain and Japan. Previous studies have
argued that CME is a less coherent classification than LME (Jackson, 2005;
Yoshikawa & Rasheed, 2009) and our results are consistent with that notion. They
have also proposed that Japan cannot be readily classified with other countries, and
the particularly strong response of social and environmental scores to closely held
stock and the weak response of governance to the same confirm Japan’s uniqueness.
Our findings have practical implications. The threat from environmental
degradation is clear, the social performance of firms is an issue of increasing
importance and the failures of corporate governance are cited as partly responsible for
the recent and continuing economic crisis. Under these circumstances regulators,
governments and stakeholders will be concerned to improve corporate ESG
37
performance. Our results suggest that particular attention may need to be paid to firms
with substantial closely held ownership and particularly in economies that could be
classified as LMEs. The implications of our results are that, should we wish to
improve ESG performance, diversified shareholding should be encouraged or
regulations and institutions established to improve the performance of firms with
substantial closely held ownership. Good governance seems to limit the impact of
closely held stock on social and environmental performance in general but not in the
case of family ownership. This is unsurprising where undiversified family ownership
provides both incentive and influence. This influence would be directly applied when
family members participate in management and may explain the limited impact of
governance on the influence of family ownership regarding social or environmental
performance.
38
ENDNOTES
1 ASSET4 is an ESG database from Thomson Reuters which uses publicly available
information including CSR and annual reports, company websites, proxy filings,
NGO information and Carbon Disclosure Project. The environmental, social and
governance scores are computed using over 750 indicators. In particular, the
environmental score includes metrics covering resource reduction, emission reduction
and product innovation; social score includes employment quality, health and safety,
training and development, diversity, human rights, community and product
responsibility; and governance includes board structure, compensation policy, board
functions, shareholder rights and vision and strategy. More detail on ASSET4
methodology is available at http://extranet.datastream.com/ data/ASSET4%20ESG/
documents/ASSET4_ESG_Methdology_FAQ_0612.pdf.
2,3 According to Worldscope definition, closely held equity includes shares held by
insiders, e.g. directors and their families, any other corporations and financial
institutions, and individual blockholdings over 5 percent. The Datastream family
ownership variable represents strategic equity of 5 percent or more held by employees
or (typically) family members. Given the broad definition, we have also randomly
selected a sample of firms that were identified as having large family shareholding,
and checked company websites. We found Datastream data to be overall consistent,
with almost all companies having family members in control, e.g. on the board of
directors.
4 ASSET4 database covers a universe of over 4,000 companies from all major stock
indices such as S&P 500, NASDAQ 100, MSCI World, MSCI Emerging Markets,
CAC40, DAX, FTSE250, STOXX600, ASX 300, SMI and Bovespa.
39
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TABLE 1 Descriptive Statistics
Social Environment Governance Closely Family Leverage Profitability MTB Log(MV)AllMean 50.76 50.53 53.04 24.99 3.42 51.95 51.01 50.45 15.38Std. Dev 30.79 31.92 30.07 23.58 10.92 28.67 28.43 28.83 1.34p25 20.99 17.43 24.01 2.98 0.00 29.00 27.00 25.00 14.54p50 50.03 47.67 61.00 18.34 0.00 53.00 51.00 51.00 15.31p75 81.31 84.50 79.43 40.95 0.00 76.00 76.00 75.00 16.20N 23902 23902 23902 23902 23680 23902 23902 23902 23902If Family >0Mean 45.17 43.72 45.82 35.92 22.91 48.87 53.52 53.64 15.05N 3759 3759 3759 3759 3537 3759 3759 3759 3759
US (7,360) 44.87 40.75 73.63 12.83 1.41 54.72 53.16 57.02 15.78Japan (3,172) 46.41 63.13 11.99 28.72 1.35 45.63 35.92 37.71 15.33LME (ex-US, 6,700) 51.30 48.71 62.55 25.54 3.96 49.49 53.21 51.26 14.83CME (ex-Japan, 5,908) 61.61 59.75 40.16 36.53 6.30 55.21 54.38 48.64 15.54Descriptive statistics are presented for the full sample, for a sub-sample for which closely held equity is assessed as greater than zero and a second sub-sample for which family equity holdings are assessed as greater than zero. The Social, Environment and Governance variables are the ASSET4 assessment of the firms’ performance on each of those dimensions, Closely and Family are respectively the Worldscope and Datastream measures of closely held stock in total and those holdings attributable to family or employees. Leverage, Profitability and Market-to-book (MTB) are the cross-sample percentiles of each variable where the original ratios are calculated as long-term debt over long-term debt plus equity, net income over equity and market value of equity over book value of equity. The log of market capitalization (log(MV)) is calculated using US$ values.
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TABLE 2 Correlation Matrix
Social Environment Governance Closely Family Leverage Profitability MTB Log(MV)Social 1.00 0.75*** 0.35*** -0.12*** -0.07*** 0.12*** 0.13*** 0.03*** 0.41***Environment 0.76*** 1.00 0.20*** -0.09*** -0.09*** 0.10*** 0.03*** -0.06*** 0.34***Governance 0.31*** 0.16*** 1.00 -0.48*** -0.12*** 0.11*** 0.11*** 0.14*** 0.18***Closely -0.08*** -0.07*** -0.45*** 1.00 0.25*** -0.10*** -0.02*** -0.05*** -0.11***Family -0.06*** -0.08*** -0.13*** 0.28*** 1.00 -0.05*** 0.04*** 0.05*** -0.10***Leverage 0.12*** 0.12*** 0.11*** -0.09*** -0.04*** 1.00 -0.06*** -0.09*** 0.08***Profitability 0.12*** 0.03*** 0.11*** 0.01 0.05*** -0.06*** 1.00 0.55*** 0.25***MTB 0.03*** -0.08*** 0.14*** -0.04*** 0.05*** -0.09*** 0.55*** 1.00 0.21***Log(MV) 0.41*** 0.35*** 0.16*** -0.07*** -0.06*** 0.08*** 0.26*** 0.21*** 1.00The correlation matrix presents the product moment (beneath the diagonal) and Spearman (above the diagonal) correlation statistics between the variables as used in our regression and propensity score matching models. †p<.10*p<.05**p<.01***p<.001
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TABLE 3Tests of Association Between Closely Held and Family Equity and Social, Environmental and Governance Performance
Model 1 Model 2 Model3 Model 4 Model 5 Model 6 Model 7 Model 8DV = Social Environment Governance Social Environment Governance Social EnvironmentIntercept -145.12*** -143.65*** -68.18*** -142.58*** -140.84*** -66.58*** -146.01*** -167.07***
(30.08) (29.22) (19.32) (29.49) (28.51) (18.87) (31.88) (35.61)Governance 0.28*** 0.28***
(21.73) (22.64)Closely -0.07*** -0.07*** -0.21*** -0.05*** -0.06*** -0.19*** 0.10*** 0.09***
(5.23) (5.19) (19.18) (3.73) (3.88) (16.63) (6.90) (5.97)Family -0.15*** -0.14*** -0.12*** -0.14*** -0.14***
(5.23) (4.91) (5.27) (5.13) (5.36)Leverage 0.05*** 0.07*** 0.04*** 0.05*** 0.06*** 0.04*** 0.03* 0.04**
(4.60) (5.60) (5.16) (4.47) (5.44) (5.24) (2.46) (3.24)Profitability 0.03*** 0.03** -0.00 0.04*** 0.03** 0.00 0.02* 0.02
(3.31) (2.95) (0.01) (3.44) (3.14) (0.54) (2.26) (1.90)MTB -0.05*** -0.10*** -0.01 -0.05*** -0.09*** -0.01 -0.08*** -0.11***
(4.25) (7.40) (0.98) (3.74) (7.02) (0.84) (6.93) (9.23)Log(MV) 7.80*** 7.44*** 3.59*** 7.64*** 7.30*** 3.49*** 6.99*** 7.08***
(27.45) (26.40) (17.92) (26.97) (25.87) (17.39) (25.77) (26.26)Industry 0.61*** 0.76*** 0.19*** 0.60*** 0.75*** 0.20*** 0.62*** 0.77***
(15.53) (26.27) (6.07) (15.41) (26.01) (6.16) (16.56) (27.67)Country 0.88*** 0.84*** 0.92*** 0.90*** 0.85*** 0.93*** 0.88*** 1.07***
(29.98) (27.18) (83.02) (30.61) (27.45) (83.13) (32.54) (36.19)Mills -7.68*** -6.51*** 0.80 -8.60*** -7.45*** 0.01 -8.57*** -3.11**
(6.62) (5.72) (0.92) (7.56) (6.81) (0.01) (7.91) (3.03)N 23902 23902 23902 23680 23680 23680 23680 23680R-sq 0.363 0.400 0.647 0.368 0.404 0.651 0.423 0.453This table presents the results of OLS regressions of ESG performance for the period 2002 to 2012 where the dependent variable is the social, environmental and governance score as assessed by ASSET4 and the test variables are closely held equity, family equity holdings (models 4 to 8 only) and governance (models 7 and 8 only). Control variables are leverage, profitability, market-to-book and the log of capitalization, industry and country averages of the dependent variable, the inverse Mills ratio and year dummies (unreported). T-statistics are calculated
50
using company clustered standard errors.†p<.10*p<.05**p<.01***p<.001
51
TABLE 4 Country Results
Australia Canada France Germany Hong Kong
Italy Japan Singapore Spain Sweden Switzer-land
UK USA AllF-test
SocialClosely -0.05† -0.09* -0.07* -0.09* -0.10† 0.25*** -0.04 -0.12† 0.10† -0.09 -0.04 -0.16*** -0.08*** 36.48***
(1.89) (2.53) (2.40) (2.19) (1.86) (4.32) (1.44) (1.96) (1.90) (1.44) (0.72) (6.37) (4.59)Family -0.32*** -0.41*** 0.05 0.21*** -0.13† -0.14* -0.45*** -0.37* -0.04 -0.02 -0.14* -0.15*** -0.27*** 54.10***
(4.81) (5.20) (1.02) (3.73) (1.85) (2.11) (4.85) (2.11) (0.48) (0.20) (2.11) (3.90) (5.39)Both Chi2
32.23*** 47.43*** 0.13 4.09* 7.60** 2.00 29.68*** 7.17** 0.61 1.19 8.18** 85.23*** 53.29*** 99.12***
EnvironmentClosely -0.03 -0.17* -0.04 -0.02 -0.03 0.17 -0.05 -0.06 0.03 -0.20 -0.02 -0.13* -0.05 27.87**
(0.79) (2.10) (0.68) (0.37) (0.27) (1.41) (0.79) (0.54) (0.39) (1.60) (0.16) (2.41) (1.49)Family -0.19* -0.33* 0.02 0.08 -0.24* -0.30** -0.78*** -0.21 -0.02 0.20 -0.17 -0.18* -0.18 76.45***
(2.34) (2.60) (0.16) (0.76) (2.45) (2.83) (4.58) (0.79) (0.19) (0.61) (0.97) (2.58) (1.87)Both Chi2
8.10** 19.42*** 0.03 0.26 5.53* 1.04 23.67*** 0.97 0.00 0.00 1.46 31.05*** 5.40* 116.27***
GovernanceClosely -0.13** -0.17** -0.36*** -0.31*** -0.21* -0.07 -0.10*** -0.14 -0.22* -0.07 -0.37*** -0.22*** -0.26*** 284.21***
(3.21) (3.22) (7.05) (7.16) (2.08) (0.77) (4.68) (1.62) (2.59) (0.90) (4.07) (3.94) (9.61)Family -0.22* -0.24* -0.07 0.11† -0.13 -0.04 -0.07 -0.22 -0.05 -0.50** -0.11 -0.12 -0.10 36.75***
(2.55) (2.09) (0.72) (1.85) (1.63) (0.46) (1.48) (1.24) (0.47) (3.39) (1.07) (1.63) (1.22)Both Chi2
17.51*** 12.99*** 17.57*** 9.82** 10.33** 1.08 13.31*** 4.24** 3.72* 16.93*** 16.97*** 47.09*** 19.59*** 191.90***
Social (governance included)Closely 0.01 0.01 0.09** 0.11** 0.05 0.33*** 0.07* -0.05 0.25*** -0.04 0.13* -0.05* 0.07*** 44.52***
(0.61) (0.23) (2.86) (2.73) (1.11) (6.25) (2.43) (0.81) (5.52) (0.62) (2.53) (2.15) (4.41)Family -0.23*** -0.26*** 0.09 0.14** -0.04 -0.11† -0.38*** -0.24 -0.01 0.17 -0.06 -0.09** -0.21*** 39.07***
(3.84) (3.62) (1.86) (2.78) (0.75) (1.91) (4.60) (1.56) (0.15) (1.60) (1.04) (2.66) (4.72)Both Chi2
13.18*** 13.81*** 12.22*** 19.54*** 0.01 8.91** 14.85*** 3.08* 12.00*** 1.72 1.54 21.05*** 9.99** 53.57***
52
Environment (governance included)Closely 0.04† -0.07* 0.06† 0.08† 0.08 0.28*** -0.01 0.07 0.18*** -0.12 0.09 -0.06* 0.10*** 35.37***
(1.72) (2.19) (1.76) (1.77) (1.50) (4.75) (0.45) (1.09) (3.95) (1.63) (1.62) (2.19) (5.15)Family -0.19** -0.18* 0.05 0.03 -0.18** -0.28*** -0.97*** -0.12 0.02 0.33* -0.06 -0.11** -0.17** 69.87***
(3.16) (2.57) (0.88) (0.44) (2.73) (4.40) (11.09) (0.68) (0.29) (2.53) (0.87) (2.74) (3.28)Both Chi2
6.13* 14.54*** 3.58* 2.68 1.63 0.01 131.37*** 0.07 8.07** 2.86* 0.36 22.17*** 1.96 66.30***
This table presents the results of OLS regressions of ESG performance for the period 2002 to 2012 for thirteen countries separately. The dependent variable is the social, environmental and governance score as assessed by ASSET4 and the test variables are closely held equity and family equity holdings. Control variables are leverage, profitability, market-to-book and the log of capitalization, industry averages of the dependent variable, the inverse Mills ratio and year dummies. T-statistics are calculated using company clustered standard errors. Only the slope coefficients of the key variables, Closely and Family, are reported plus the Chi2 test that the sum of both slope coefficients is significantly different from zero. In the final column we report the F-test that the individual slope coefficients are collectively different from zero.†p<.10*p<.05**p<.01***p<.001
53
APPENDIX 1Distribution and Characteristics of the Sample by Country
Country Sample Social Environment Governance Closely Family Leverage Profitability MTB Log(MV)
Australia 1,329 40.57 40.92 61.60 32.05 3.03 46.51 46.84 49.59 14.42Belgium 213 46.46 51.61 45.78 42.29 6.63 56.24 51.86 41.10 15.33Brazil 157 70.38 56.15 27.41 47.88 1.86 54.92 63.57 48.71 16.16Canada 1,139 39.49 38.66 72.72 13.17 2.63 49.04 44.91 48.83 14.82Chile 58 49.14 47.79 11.09 60.46 11.36 62.79 61.72 60.14 15.83China 259 27.99 28.87 25.83 57.86 5.77 40.10 59.65 47.47 15.64Colombia 12 43.17 38.96 38.02 55.69 0.00 42.50 53.17 43.33 16.59Chech Rep. 12 71.58 55.89 16.63 66.03 0.00 42.00 72.50 54.75 16.30Denmark 191 52.43 57.94 32.74 30.29 1.93 49.09 60.76 56.11 14.98Egypt 8 28.87 11.56 10.43 74.15 0.00 31.13 58.00 32.75 15.11Finland 224 66.75 72.72 56.03 20.29 2.53 46.03 55.80 47.64 15.05France 770 76.18 75.31 51.46 34.36 6.46 59.05 48.71 46.30 16.07Germany 557 66.48 66.57 31.34 35.20 8.92 57.22 48.41 45.76 15.69Greece 105 51.16 48.37 19.26 46.12 10.74 59.33 53.97 42.59 14.20Hong Kong 450 41.24 36.62 30.74 50.74 8.09 37.85 56.89 44.25 15.64Hungary 13 82.66 76.45 43.28 32.20 2.69 59.77 46.46 25.92 15.35India 179 63.71 56.72 30.54 53.95 10.34 51.58 69.69 69.13 16.22Indonesia 63 61.81 42.58 23.98 60.99 0.32 31.68 81.98 77.24 15.81Ireland 151 39.78 41.74 61.30 19.11 4.90 69.31 58.92 54.05 14.66Israel 39 44.58 39.82 35.91 33.12 3.54 66.67 63.13 62.36 15.61Italy 415 61.63 51.34 36.67 39.61 10.18 69.68 44.15 41.84 15.62Japan 3,172 46.41 63.13 11.99 28.72 1.35 45.63 35.92 37.71 15.33Korea 196 60.33 66.23 18.36 33.04 5.17 48.76 52.40 39.07 15.72Malaysia 106 46.69 40.39 42.86 47.85 2.38 51.87 55.90 55.87 15.45MAR 8 68.29 23.43 5.19 67.49 0.00 47.75 83.38 80.75 16.14Mexico 37 48.59 41.67 14.96 58.30 13.11 52.30 69.11 55.62 16.40Missing 762 36.95 37.12 41.47 32.76 4.59 47.93 47.57 46.78 15.18Netherlands 283 76.38 68.48 66.49 20.96 4.54 60.72 53.95 48.64 15.78
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Norway 203 59.44 55.97 51.65 31.53 0.98 57.89 54.57 58.50 14.93New Zealand 84 42.57 46.92 54.30 44.32 0.00 56.69 48.62 47.88 14.21Austria 152 53.57 53.76 30.96 43.77 6.98 56.97 50.07 42.33 14.96PER 4 38.64 27.49 48.26 35.88 28.00 21.50 76.75 83.00 15.96Philippines 27 43.21 36.73 30.76 63.61 9.19 65.81 69.30 62.78 14.99Poland 61 37.99 30.76 17.65 55.59 3.13 34.97 49.98 37.90 15.11Portugal 108 75.45 67.14 49.23 52.06 2.19 84.88 54.66 51.43 15.21Russia 101 58.17 44.99 24.70 66.23 3.69 44.05 56.57 38.02 16.44South Africa 158 79.14 65.14 62.65 33.36 0.87 39.37 63.59 60.30 15.58Singapore 334 36.48 34.20 38.84 53.71 1.72 45.49 59.37 45.98 15.02Spain 394 73.58 68.66 45.59 42.46 8.53 65.68 59.11 55.24 15.62Sweden 462 63.02 65.56 51.38 20.68 3.54 57.10 57.35 46.89 15.15Switzerland 474 57.69 59.00 48.23 24.90 12.09 43.15 55.39 57.51 15.45Thailand 47 53.62 39.38 45.57 51.41 1.96 52.11 72.19 61.87 15.52Turkey 67 52.97 45.50 15.34 65.46 8.07 49.82 70.73 46.27 15.60Taiwan 186 41.93 48.47 13.97 25.38 1.71 37.70 53.45 47.71 15.37UAE 2 23.81 35.61 33.75 80.45 0.00 70.50 32.00 3.00 15.84UK 2,770 63.40 59.60 69.97 16.65 4.44 52.52 56.41 52.94 14.75USA 7,360 44.87 40.75 73.63 12.83 1.41 54.72 53.16 57.02 15.78
Total 23,902 50.76 50.53 53.04 24.99 3.42 51.95 51.01 50.45 15.38The sample represents all firm year observations in the ASSET4 universe for which ESG scores, closely held equity and family held equity measures and control variables are available during the period 2002-2012. The Social, Environment and Governance variables are the ASSET4 assessment of the firms’ performance on each of those dimensions, Closely and Family are respectively the Worldscope and Datastream measures of closely held stock in total and those holdings attributable to family or employees. Leverage, Profitability and Market-to-book (MTB) are the cross-sample percentiles of each variable where the original ratios are calculated as long-term debt over long-term debt plus equity, net income over equity and market value of equity over book value of equity. The log of market capitalization (log(MV)) is calculated using US$ values.
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FIGURE 1
Quantile analysis of the impact of closely held equity and family equity on social,
environmental and governance scores
The horizontal scale represents the quantiles of the dependent variable and the vertical
scale the estimated slope coefficient for each quantile. Figure 1a contains the
estimated coefficients for closely held equity and Figure 1b the estimates for family
held stock. The solid line represents social performance, dashed environmental and
dash-dot governance.
Figure 1a. Social, environmental and governance response to closely held equity.
Figure 1b. Social, environmental and governance response to family held equity.
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FIGURE 2
Comparisons of country-specific impact of family ownership on social,
environmental and governance scores
The scatter plots contrast the total impact of family ownership (i.e. closely held plus
family) averaged across social and environmental vs. governance scores. The impact
calculations are based on the results reported in Table 4.
Social and environmental (horizontal axis) vs governance (vertical axis). The social
and environmental scores have been merged for simplicity as the two separate graphs
give broadly the same results.
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