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Corporate governance and failure
risk: evidence from Estonian
SME population
Virgo Süsi and Oliver Lukason
School of Economics and Business Administration, University of Tartu,
Tartu, Estonia
Failure risk
703
Received 6 March 2018
Revised 2 September 2018
Accepted 11 December 2018
Abstract
Purpose – The purpose of this study is to find out how corporate governance is interconnected with failure
risk in case of small- and medium-sized enterprises (SMEs).
Design/methodology/approach – The study is based on Estonian whole population of SMEs, in total
67,058 observations, and data are obtained from Estonian Business Register. Failure risk (FR) is portrayed
with a well-known Altman et al. (2017) model, while seven variables reflecting corporate governance (CG)
based on previous studies have been selected. As the method, logistic regression (LR) is applied with FR in the
binary form as a dependent variable and seven CG variables as independent. The effect of firm size and age is
studied with two separate LR models.
Findings – The results indicate that with the growth in manager’s age and the presence of managerial
ownership, failure risk reduces. In turn, the presence of larger boards and managers having directorships in
other firms leads to higher failure risk. Gender heterogeneity in the board, board tenure length and ownership
concentration by means of having a majority owner are not associated with failure risk. The obtained results
vary with firm size and age.
Originality/value – Unlike this study, research published on this topic earlier has used a much narrower
definition of failure, mostly focused on large and listed companies, been sample based and information about
corporate governance variables has often been obtained through questionnaires. All these limitations are
relaxed in this population level study.
Keywords SMEs, Estonia, Corporate governance,
Entrepreneurship and small business management, Private firms, Failure risk
Paper type Research paper
1. Introduction
The purpose of firms is value creation in a sustainable manner so that they could be successful
in the long-run, and thus, the leadership of companies should strive to operate the firm at the
minimum in a way it would not fail. Therefore, it is vital to study, how management of firms is
linked to their failure. This also enables to interconnect two mainstream areas in the business
literature, i.e. corporate governance and failure risk, in a novel setting.
Literature focused on firm failure has emerged decades ago and the core of this research
stream since the piloting studies by Beaver (1966) and Altman (1968) has been the
composition of failure prediction models. Since then, a myriad of different failure prediction
models have been composed (Dimitras et al., 1996; Bellovary et al., 2007; Sun et al., 2014).
This research stream started in finance domain and therefore most of these studies initially
The authors acknowledge financial support from Estonian Ministry of Education and Research grant
IUT20-49 “Structural Change as the Factor of Productivity Growth in the Case of Catching up
Economies”.
Management Research Review
Vol. 42 No. 6, 2019
pp. 703-720
© Emerald Publishing Limited
2040-8269
DOI 10.1108/MRR-03-2018-0105
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42,6
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relied only on financial variables. As the field matured, various corporate governance
variables were also included in the models to improve their accuracies (Chaganti et al., 1985;
Daily and Dalton, 1994; Platt and Platt, 2012; Iwanicz-Drozdowska et al., 2016; Chan et al.,
2016). Until recently, though, the studies about failure risk have mainly focused on large
public firms and private small- and medium-sized enterprise (SME) segment has been
relatively unexplored.
However, majority of firms globally are private SMEs and some authors (Altman and
Sabato, 2007; Elshahat et al., 2015) argue that the prediction models developed on the
example of large public firms are not very effective in case of SMEs, and therefore, separate
models are required for that segment. Thus, recent focus in this literature domain has
shifted to studying private SMEs (Altman et al., 2017). Still, the available SME failure
prediction models mostly cover only financial variables (Pompe and Bilderbeek, 2005;
Mselmi et al., 2017), although it is argued that the inclusion of corporate governance
variables is particularly important in the SME segment, among others due to the fact that it
is difficult to compose high-accuracy prediction models for SMEs based on financial ratios
only (Ciampi, 2015). There exist a few studies that have included some non-financial
compliance and “event” variables such as delays in filing company reports, existence and
contents of audit reports, legal actions by creditors (Altman et al., 2010). Still, there are only a
few studies that include specifically corporate governance variables such as owner and
board characteristics into failure risk modeling (Ciampi, 2015; Ciampi, 2017). Thus, the
effectiveness of corporate governance variables in case of private SME segment is largely
unexplored.
In general, corporate governance is a system by which companies are directed and
controlled (Huse, 2007). It deals with how shareholders of a company can ensure the survival
and success of a company given the separation of ownership and control. The directing part
deals with creating possibilities for the management to do a better job. It starts with forming
a management team that is capable, with complementary skills and effective, but it also
means appropriate co-operation with and support for the management team. Upper echelons
theory (Hambrick and Mason, 1984; Hambrick, 2007) posits that organizational performance
is influenced by the characteristics of its top executives: their personalities, beliefs,
capabilities, but also the interactions among the top executives. It could therefore be
assumed that failure risk also depends on the characteristics of firm’s upper echelons, i.e. the
top managers. The control part of corporate governance stems from agency theory (Jensen
and Meckling, 1976; Fama and Jensen, 1983), where owners/principals need to monitor and
motivate managers/agents to discourage shirking, self-interested behavior and other actions
that might destroy value, and thus, increase the risk of failure.
This study is directed to merge these two main areas in business research (i.e. firm failure
and corporate governance), therefore aiming to study how corporate governance is
interconnected with failure risk in case of SMEs. The selected topic is novel in several
aspects. While the association of corporate governance and failure has so far been mainly
studied by using a very narrow subset of failure, i.e. bankruptcy or permanent insolvency,
we take a broader approach and use failure risk as a dependent variable. This enables to
provide the study with remarkably wider scope, rather than focusing only on failure
reflected through the legal proceedings. As failure risk measure selected for this study
incorporates all important financial domains like liquidity, profitability and leverage, this
study is also strongly linked to the stream focusing on the interconnection of corporate
governance and firm performance. While past research has mainly focused on large and/or
listed firms, this study focuses on a relatively underexplored segment of SMEs. Our data set
represents the whole population of SMEs in one country, being therefore free from sampling
bias. Finally, the information about corporate governance variables is procured from official
business register and therefore factual, while previous research has mainly focused on
questionnaires.
Section 2 outlines the most widely used corporate governance variables having potential
effect on firm failure from past studies and sets research questions for the empirical portion
of the paper. Section 3 outlines the failure risk and corporate governance variables
implemented in this study and also describes the whole population of Estonian SMEs used.
Section 4 focuses on study’s empirical results, and Section 5 focuses on discussing them. The
study classically ends with a conclusion including limitations, implications and some future
research directions in Section 6.
2. Literature review
We have systemized the previous literature about the interconnection of failure with board
and owner characteristics into seven subsections. These subsections focus on the most
widely used variables in the previous studies. As noted earlier, only a few previous studies
exist that explore corporate governance variables specifically in the SME context. Therefore,
beside SME-specific studies, we have in the literature review section mostly relied on similar
studies in the large firm segment and discussed the relevance of their findings in the SME
context.
When generally the viewed studies have empirically considered different contexts of firm
failure, then some theoretical studies and research focusing on firm performance have been
referenced as well. The latter is especially topical, when previous evidence about the
interconnection of failure risk and specific variable is absent. Each subsection ends with a
research question (RQ), which will be studied in the empirical portion of the paper. As specifically
in the context selected for this study previous results are either lacking or controversial, we do not
set hypotheses indicating the expected behavior of independent variables. Instead, we rely on an
exploratory study design to discover the phenomena in the context of SMEs.
2.1 Board size
The link between board size and firm failure is often discussed in the literature. However,
the topic is controversial and related to the theoretical perspective applied. From the
resource dependence point of view (Pfeffer and Salancik, 1978), boards with larger number
of members add various competences, networks, relationships and resources to the firm, and
thus, improve the chances of its survival. Accordingly, some studies have concluded that
larger boards decrease the failure risk (Chaganti et al., 1985). On the other hand, larger
boards are more susceptible to power games and coalition buildings, which may hamper the
speed of decision-making during crisis. Therefore, smaller boards are more effective in that
sense. Accordingly, some studies have found that smaller boards improve firm performance,
and thus, decrease the failure risk (Yermack, 1996; Eisenberg et al., 1998; Bennedsen et al.,
2008; Fich and Slezak, 2008; Paniagua et al., 2018). To explain such discrepancy, some
studies point out that whether small or large boards increase or decrease bankruptcy risk,
depends on firm characteristics such as size and complexity (Darrat et al., 2016) or industry
characteristics such as high or low growth sector (Dowell et al., 2011). Ciampi (2015) studied
the effect of board size specifically in the SME context. He hypothesized that board size has
a positive correlation with small company failure, however that hypothesis was not
confirmed. Based on previous studies the increase in board size could either lead to an
increase or decrease in failure risk, and stemming from this, the first research question is:
RQ1. How are board size and failure risk interconnected in case of SMEs?
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2.2 Board gender heterogeneity
Upper echelons theory (Hambrick and Mason, 1984; Hambrick, 2007) predicts that actions of
board members are influenced by their experiences, values and cognitive frames. Thus,
board gender heterogeneity is likely to broaden the information, knowledge and values that
are used in decision-making. Furthermore, Post and Byron (2015) argue that having women
on boards influences not only what information is used in decision-making but also how this
is being done – females are more likely to value interdependence, benevolence and tolerance
(Adams and Funk, 2012). Studies have shown that female directors tend to have more
university degrees than male directors (Hillman et al., 2002; Carter et al., 2010), they are more
likely to be successful in marketing and sales (Groysberg and Bell, 2013), they bring
different experiences and understandings about consumer markets (Carter et al., 2003;
Campbell and Minguez-Vera, 2008) and their path to board tends to be different from that of
males (Hillman et al., 2002; Singh et al., 2008). As a result, board gender heterogeneity is
likely to impact firm performance (Carpenter, 2002).
Post and Byron (2015) have summarized studies about board heterogeneity and found in
their meta-analysis of 140 papers that the relationship between female representation in
board and firm financial performance is generally positive, although there are differences
between countries stemming from their legal and regulatory context (namely, shareholder
protection strength) and socio-cultural background (namely, gender parity in society). Their
analysis predicts that having women on board has more positive effect on firm financial
performance in countries with higher shareholder protection regulations, because corporate
governance processes are considered to be more important in these countries, while weak
shareholder protection laws may lessen the focus on corporate governance practices. Gender
parity in society influences how seriously women are taken in the board and high gender
parity as a contextual factor increases the impact of board heterogeneity on firm
performance. Previous studies have not come to a clear conclusion about how board’s
gender diversity affects failure risk in case of larger firms.
To our knowledge there are no previous studies that analyze the impact of gender
diversity on firm failure risk specifically in the SME segment. However, as upper echelons
theory is not specific to large firms only, it could be expected that the broader range of
views, experiences and cognitive frames that gender diversity creates among the key
decision makers could also impact SME performance, and thus, the failure risk. Therefore,
the second research question is:
RQ2. How are gender heterogeneity and failure risk interconnected in case of SMEs?
2.3 Board tenure
Board tenure – time spent in the board of a specific firm – is expected to increase director’s
knowledge about the firm and its business environment (Vafeas, 2003) and commitment
toward the firm (Buchanan, 1974). As a result, it is expected that directors with a long tenure
at a specific firm should improve firm performance, and thus, decrease the risk of failure. On
the other hand, some studies have discovered that extensive board tenure may be associated
with corporate governance problems (Berberich and Niu, 2011) that ultimately may lead to
poorer firm performance, and thus, increase the risk of failure. The third type of studies has
found some contingency factors that influence the relationship between board tenure and
firm performance. For example Henderson et al. (2006) found that in stable industries (such
as food manufacturing) firm performance improves with longer board tenure, while in
dynamic industries (such as computers’ manufacturing) the opposite happens.
Compared to large firms SMEs have less resources to spend on larger boards and several
layers of management. This means that fewer people have to handle more aspects of the
business. In case of large firms, many board members can divide the responsibility areas
(e.g. finance, marketing, operations). SME boards have fewer members and less support
from several layers of management, so each SME board member should be fairly well
informed about all aspects of the firm. The longer a board member stays with the firm, the
more he or she learns about the firm and its environment. Furthermore, SMEs tend to have
less codified knowledge compared to large firms, so it takes more time for new board
members to get familiar with all relevant details about the firm. Therefore, it could be
expected that board tenure has impact on SME failure risk. Thus, the third research
question aims to explore the role of board tenure:
RQ3. How are board tenure and failure risk interconnected in case of SMEs?
2.4 Age of top managers
Age of top managers can be used as a proxy for how experienced board members are. When
the previous variable – board tenure – expresses the firm-specific experience, the age
variable relates to a more general life and business experience. Upper echelons theory
argues that board characteristics, including the age of board members, manifest in firm
actions and therefore influence firm performance. Prior studies have yielded mixed results in
respect to the link between age of top managers and firm performance. For example Wang
et al. (2016) conclude based on a meta-analysis of 308 studies that CEO age correlates
positively with firm performance. On the other hand, it has been found that although the age
influences manager’s decisions regarding risk-taking propensity, the result of that on firm
performance could be either positive or negative (Bertrand and Schoar, 2003). The direction
of correlation also depends on how to measure performance. For example Peni (2014) found
that there is a positive relationship between executive age and firm performance when it is
measured with ROA, but the relationship is insignificant when measured with Tobin’s Q.
To the best of our knowledge there are no prior studies exploring the link between age of
top managers and SME failure risk. Given the exploratory nature of this paper we seek to
shed light in this matter and therefore the fourth research question is:
RQ4. How are top manager’s age and failure risk interconnected in case of SMEs?
2.5 Multiple directorships
Board members may hold director positions in several firms at the same time. Having
several director positions may signal director quality and superior performance (Fama and
Jensen, 1983; Ferris et al., 2003), and thus, should decrease the failure risk of a company.
Such positive correlation between firm performance and multiple directorships of board
members has been established in several prior studies (Geletkanycz and Boyd, 2011;
Carpenter and Westphal, 2001). On the other hand, being involved in many companies at the
same time may fragment director’s focus and may create a potential for shirking (Core et al.,
1999; Jiraporn et al., 2008; Berberich and Niu, 2011), and as a result, multiple directorships
may increase the failure risk. It is sometimes also a practice for defaulting (SME) firms to
hire a new board member to go through the bankruptcy process so that the original ownermanager can save their face and have a clean track record. Thus, a person with a very large
number of simultaneous directorships may also indicate a potential failure risk. To resolve
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the controversial issue of how holding multiple director positions and failure risk are
associated in case of SMEs, the fifth research question is:
RQ5. How are multiple directorships and failure risk interconnected in case of SMEs?
708
2.6 Ownership concentration
Firms with concentrated ownership have one or a few large shareholders that own majority
of shares in the firm. Such large shareholders in private firms tend to have most of their
wealth and income connected to the firm (Ciampi, 2015). That makes them especially
interested in the performance of the specific firm. They monitor activities of managers and
performance of the firm more actively and effectively than in case of dispersed ownership
(Shleifer and Vishny, 1986). Such scrutiny reduces shirking and self-serving behavior of
managers (Jensen and Meckling, 1976) and thus reduces potentially value destructive
activities, i.e. decreases failure risk.
Previous studies provide mixed evidence regarding the link between ownership
concentration and failure risk. Some studies find that concentrated ownership is positive for
firm performance, i.e. it reduces failure risk (Perrini et al., 2008; Kapopoulos and Lazaretou,
2007; Pursey et al., 2009; Paniagua et al., 2018). Other studies (Thomsen and Pedersen, 2000;
De Miguel et al., 2004) have established a bell-shaped non-linear association between
ownership concentration and performance. A third set of studies (Demsetz and Villalonga,
2001) has concluded that the relationship between ownership structure and firm
performance is insignificant. In his study of 934 Italian SMEs, Ciampi (2015) found that in
case of SMEs there is a significant negative correlation between ownership concentration
and company default.
Our dependent variable – failure risk – is broader than Ciampi’s firm default. Logically, it
could be expected that ownership concentration also has influence on the broader failure
risk, and to disclose this phenomenon, our sixth research question is:
RQ6. How are ownership concentration and failure risk interconnected in case of SMEs?
2.7 Managerial ownership
Two separate forces are expected to influence the relationship between managerial
ownership and failure risk. Convergence-of-interest hypothesis posits that as the portion of
shares owned by managers increases, their interests with other shareholders converge,
which should result in avoidance of value destructive behaviors predicted by agency theory
(Morck et al., 1998), i.e. higher proportion of shares held by managers should decrease the
failure risk. Entrenchment hypothesis, however, states that when the proportion of shares
held by managers is substantial to give them enough voting power or influence, they might
start to maximize their personal objectives at the expense of other shareholders, which could
be harmful for the firm as the whole, and thus, increase its failure risk (Morck et al., 1998).
Previous studies have established a non-linear relationship between managers’
shareholding proportion and firm performance. Some studies (McConnell and Servaes, 1990;
Han and Suk, 1998; Coles et al., 2012) have found a quadratic relationship between the size of
managerial ownership and firm performance, i.e. initially firm performance improves as
managerial ownership increases due to the convergence-of-interest effect and after a certain
point the performance decreases due to the entrenchment effect.
Other studies (Morck et al., 1998; Short and Keasey, 1999; De Miguel et al., 2004) have
found the relationship between firm performance and managerial ownership to be more
complex (in the cubic form), where initially the performance improves as the managerial
ownership increases, at a certain point the performance starts to decrease and at very high
managerial ownership levels starts to increase again.
The relationship between managerial ownership and failure risk has not been studied
specifically in case of SMEs, and thus, to disclose the connection between managerial
ownership and failure risk, the seventh research question is:
RQ7. How are managerial ownership and failure risk interconnected in case of SMEs?
3. Data, variables and method
The analysis is based on 67,058 Estonian SMEs, using data procured from the Estonian
Business Register (EBR), which contains firms’ annual reports and up to date information
about firms’ boards and owners.
Estonian Commercial Code (2018) permits several legal forms for firms. Two main legal
forms are Private Limited Company (in Estonian “osaühing”, i.e. OÜ, later referred to as
PrLC) and Public Limited Company[1] (in Estonian “aktsiaselts”, i.e. AS, later referred to as
PuLC). Other types (General Partnership, Limited Partnership and Commercial Association)
are relatively rare in practice. Our sample consists of 64,561 PrLC-s (96.3 per cent of sample)
and 2,497 PuLC-s (3.7 per cent of sample).
In terms of corporate governance, PrLCs have a very simple structure where the firms
are governed by a one-tier board, which is subject to firms’ owners. The board members
have legal right to do transactions on behalf of the firm. PuLC type of firms have a two-tier
board with a clear separation of supervisory board and management board. The
management board is responsible for daily management of the firm. It reports to the
supervisory board and not directly to shareholders. The role of supervisory board is to plan
the activities and organize the management of the firm and supervise the activities of the
management board. The consent of supervisory board is required for transactions beyond
the scope of everyday activities of the firm. Members of one board cannot be members of the
other board at the same time (which eliminates one of the key variables usually analyzed in
corporate governance analyses, namely the CEO-duality).
Estonia is a member of European Union (EU) since 2004, which means that Estonian
legislative system and key institutions are harmonized with overall EU regulations, which
increases the comparability of Estonian SMEs to firms with comparable sizes from other EU
countries. Globally, Estonia ranks high in several business rankings, for example in World
Bank (2018) Doing Business rankings Estonia has 12th place in “Ease of doing business”
and “Starting a business”, 11th place for “Enforcing contracts” and 14th place for “Paying
taxes”. These rankings place Estonia in the same range with countries like Finland, Sweden
and Norway. So also in terms of general business environment Estonia is quite comparable
to other Northern European countries.
The focus in this study is on private SMEs (not exceeding the EU set size limits for these
firms[2]). The median SME in the population of 67,058 Estonian SMEs used in the analysis
is a very small firm, with total balance sheet of e33,000 and age 7.5 years at the balance
sheet closing date. For 98 per cent of firms total assets remain below e2m; thus, these firms
are classified as micro firms. The largest firm in the analysis has total assets e40.2m. The
age distribution of firms indicates that a 1st percentile firm is 0.65 and 99th percentile firm
19.6 years old, the first and third quartiles being 3.59 and 13.08 years, respectively. The
highly aggregate sectoral breakdown of observations is as follows: 7.1 per cent primary, 9.5
per cent manufacturing, 18.4 per cent construction, 18.8 per cent sales and 46.2 per cent
service sector firms.
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The variables used in the analysis with their coding and calculation details have been
presented in Table I. Seven independent variables are applied, which reflect the domains
outlined in the literature review. Most of the independent variables have been calculated
based on their common usage in the literature, although we acknowledge that some domains
are used less in the literature, and thus, the specific variables portraying them (e.g.
BTENURE and MDIRECT) are not as frequent as others.
For calculating the dependent variable portraying failure risk, we will use the most
universally applicable failure prediction study by Altman et al. (2017). This multisector study included millions of European firms for estimation and has a high
classification accuracy in Estonia, thus being directly applicable for this study.
Moreover, there are no multi-sector models available in the Estonian scientific
literature. We will apply Model 2 from Altman et al. (2017) study, which is the only logit
model without control variables (see Table AI for this model). For each firm, we have
detected whether the failure risk is over 0.5 (i.e. 50 per cent) based on this model,
leading to the binary dependent variable SCORE. The firms with failure risk >0.5 will
be coded with 1, the opposite situation with 0 respectively. Unlike previous failure
prediction studies, we use a broader term of failure (i.e. having >50 per cent of failure
risk, not for instance the bankruptcy fact), which enables better linking of the results
with the research focusing on firm performance. Altman et al. (2017) model includes all
main financial domains, such as liquidity, profitability (annual and accumulated) and
leverage. Thus, when a firm has failure risk over 50 per cent, it is evident that it is
performing poorly at least in one of these domains.
In the sample of 67,058 Estonian SMEs, 12,219 firms have SCORE = 1, i.e. failure
risk over 50 per cent based on Altman et al. (2017) model. From EBR we use all firms in
analysis, for which the dependent and independent variables could be calculated. Thus,
the sample represents the majority of Estonian active firm population, which according
to Statistics Estonia for the selected year was 79,668. We have chosen year 2015 for
Variable domain
Variable coding
Calculation
Board size (IV)
Board gender
heterogeneity (IV)
Board tenure (IV)
BSIZE
BGENDER
Number of board members in the firm
If both genders are present in the board then 1, otherwise 0
BTENURE
Ratio of tenure’s time of the longest serving board member
and firm agea
Biological age of the oldest board member
Age of top
managers (IV)
Multiple
directorships (IV)
Ownership
concentration (IV)
Managerial
ownership (IV)
Failure risk (DV)
MAGE
MDIRECT
OCONC
MOWN
SCORE
The number of board memberships the board members
altogether have in other firmsb
If one owner has over 50% of the shares then 1, otherwise 0
Ratio of share capital owned by board members to total share
capital
0 if Altman et al. (2017) Model 2 transformed logit score #0.5,
1 if Altman et al. (2017) Model 2 transformed logit score >0.5
Notes: IV – independent variable, DV – dependent variable; athe maximum of the ratio is 1, indicating that
Table I.
the longest serving board member has been in the firm for the whole firm lifetime. bIf a firm has, for
Variables used in the instance, two board members, and both of them are board members in another firm as well, the value for the
analysis
variable is 2
analysis, as this is the last year during the study’s composition about which we could
obtain information. In such study design, we can use only a single year, as the boards
and owners of SMEs do not change often, making the values of independent variables
repeat in case of using multiple years.
As binary dependent variable (SCORE) is concerned, we will use logistic regression
method with other variables listed in Table I as independent variables. Logistic regression is
the most widely used method in case of binary dependent variables, therefore suiting for this
study well. Marginal effects of independent variables and multicollinearity statistics are also
provided. Firm size and age effects on corporate governance variables are considered with
two separate logistic regression models. Namely, the firm population is divided into two
based on either firm size (total assets in 2015) or age (time from foundation to the end of year
2015) and additional logistic regression models are composed (see Table AII and Table AIII).
As 98 per cent of the firms are micro firms by size, the usage of for instance quartiles in
dividing the population is not reasonable.
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4. Empirical results
Descriptive statistics (see Table II) indicate that the median firm in the data set has one 45year-old board member, who has been in the board for the whole firm’s lifetime and is also
the majority owner of the firm. Concerning BSIZE, 74 per cent of firms have single-person
boards, while 22.1 per cent of boards have two persons. Thus, a vast majority of boards are
non-heterogeneous and only in case of 11.6 per cent of boards BGENDER = 1. Board
members have mostly no or a few other business ties, namely MDIRECT = 0 for 44.9 per
cent of observations, 1 for 23.1 per cent and 2 for 12.2 per cent. For 81.1 per cent of firms
there is a majority owner (OCONC = 1). The median age of oldest board member (MAGE) is
45 years, the first and third quartiles being 37.3 and 54.2 years, respectively. In 80 per cent of
firms, the oldest serving board member (BTENURE) has been there at least for 90 per cent of
firm’s lifetime and owns (MOWN) 100 per cent of the firm. Preliminary statistical tests
(Table II) for studied seven variables indicate, that two of them (BGENDER and BTENURE)
SCORE
0, (N = 54839)
Statistic
Mean
Std. deviation
Median
Minimum
Maximum
1, (N = 12219)
Mean
Std. deviation
Median
Minimum
Maximum
Total, (N = 67058) Mean
Std. deviation
Median
Minimum
Maximum
BSIZE BGENDER MAGE MDIRECT BTENURE OCONC MOWN
1.30
0.56
1.00
1.00
7.00
1.32
0.58
1.00
1.00
6.00
1.31
0.57
1.00
1.00
7.00
0.12
0.32
0.00
0.00
1.00
0.12
0.32
0.00
0.00
1.00
0.12
0.32
0.00
0.00
1.00
46.22
11.70
45.24
17.62
93.60
45.77
11.59
44.75
18.93
92.28
46.14
11.68
45.14
17.62
93.60
1.47
2.16
1.00
0.00
10.00
1.57
2.28
1.00
0.00
10.00
1.49
2.18
1.00
0.00
10.00
0.90
0.22
1.00
0.03
1.00
0.90
0.22
1.00
0.03
1.00
0.90
0.22
1.00
0.03
1.00
0.81
0.39
1.00
0.00
1.00
0.80
0.40
1.00
0.00
1.00
0.81
0.39
1.00
0.00
1.00
0.89
0.27
1.00
0.00
1.00
0.87
0.30
1.00
0.00
1.00
0.88
0.28
1.00
0.00
1.00
Notes: For BSIZE, MAGE, MDIRECT, MOWN the Brown-Forsyth ANOVA test (p-value < 0.01) for
BTENURE 0.589 (with SCORE as factor). For BGENDER Pearson chi-square test p-value 0.941, for OCONC
0.000 (with SCORE as other variable in contingency test)
Table II.
Descriptive statistics
of variables
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712
do not associate with failure risk[3]. Thus, it could be suspected that these variables are not
significant in the follow-up logistic regression analysis.
The logistic regression analysis conducted (Table III) indicates that as expected based
on the statistical tests, BGENDER and BTENURE, but also ownership concentration
(OCONC) do not associate with failure risk. In turn, four variables out of seven are
significant, namely the rise in two variables (board size, i.e. BSIZE, and multiple
directorships, i.e. MDIRECT) increases failure risk, and in turn, the rise in two variables
(manager’s age, i.e. MAGE, and manager’s ownership, MOWN) decreases failure risk.
The resulting logit model is significant and free from multicollinearity (VIF values in
Table III are below 2.00). The robustness of the initial model is tested with bootstrapping
(Table III, final columns), which indicates that the coefficients of all significant variables
remain with the same signs.
We also tested a model in case of multiple person boards (i.e. BSIZE > 1), which excludes
the majority of “single person” firms. With such restriction, less than half (46.8 per cent) of
the firms have a majority owner. All variables remain (in)significant and with same signs
similarly to the base model in Table III, except for BSIZE. The latter is a logical result, as in
the model presented in Table III, the significance of the variable is determined by the
difference in between single- and multi-person boards. Moreover, the multi-person board
sample is dominated by two-person board observations (84.8 per cent).
When the firm population is divided into two based on size and separate logistic
regression models composed, it can be seen that size has an effect on the performance of
independent variables. Larger boards are unfavorable only for the smaller firms, while the
variable is insignificant in case of larger SMEs. Multiple directorships increases failure risk
in both size groups, the negative effect being stronger in case of larger SMEs. Managerial
ownership decreases failure risk in both size groups, whereas with growth in firms’ size the
variable’s risk reduction effect becomes remarkably larger. Board heterogeneity, ownership
concentration and top manager’s age are insignificant in both size groups, while the latter
variable was significant in the base model. Board tenure is insignificant in case of larger
SMEs, while it is decreasing failure risk in the smaller size group, but the variable is not as
significant as others.
The analysis of two firm age groups indicates that likewise with size, age has an effect on
the performance of independent variables. Larger boards are unfavorable only for younger
firms, while the variable is insignificant in case of older firms. Multiple directorships
variable acts in the same way, increasing failure risk for younger firms, but being
insignificant in case of older firms. Managerial ownership decreases failure risk in both age
Variable
Table III.
Logistic regression
model
BSIZE
BGENDER
MAGE
MDIRECT
BTENURE
OCONC
MOWN
CONSTANT
B
0.066
0.042
0.004
0.015
0.037
0.035
0.258
1.187
S.E.
Wald
0.024
7.486
0.037
1.308
0.001 23.792
0.005 10.680
0.047
0.619
0.030
1.318
0.037 49.043
0.072 270.967
Sig.
dy/dx VIF Lower BS interval Higher BS interval BS Sig.
0.006
0.253
0.000
0.001
0.431
0.251
0.000
0.000
0.010
0.006
0.001
0.002
0.006
0.005
0.038
1.98
1.39
1.05
1.10
1.07
1.46
1.15
0.017
0.116
0.006
0.006
0.061
0.089
0.328
1.325
0.116
0.031
0.003
0.024
0.133
0.025
0.183
1.045
0.008
0.260
0.001
0.001
0.452
0.234
0.001
0.001
Notes: Model LR chi-square 107 (p-value = 0.000) and log likelihood 31,781. Bootstrapping (BS) results
obtained with 1,000 bootstrap samples. Dependent variable SCORE
groups, the effect being stronger in case of younger firms. Board heterogeneity, board
tenure, ownership concentration and top manager’s age are insignificant in both age groups,
while the latter variable was significant in the base model.
5. Discussion of findings
Our analysis deals specifically with SMEs and the findings should be interpreted with that
contingency in mind. Looking at the independent variables either separately or in groups,
allows outlining some important trends (see Table IV for the summary of findings about the
research questions).
The results show that SMEs have higher (lower) failure risk when their boards are larger
(smaller). This finding supports the strand of literature (Yermack, 1996; Eisenberg et al.,
1998; Bennedsen et al., 2008; Fich and Slezak, 2008) that stresses the importance of faster
decisions and warns about the risks of power games that might be characteristic to larger
boards. Different viewpoints, larger networks and relationships that the proponents of
larger boards promote, seem to have less importance in the SME segment. In case of larger
and older firms, board size is insignificant, i.e. deeper board discussions enabled by larger
boards start to balance the value of faster decisions that smaller boards bring. As board
gender heterogeneity is not associated with SME failure risk, it also indicates that different
perspectives that come from having both genders represented in the board have lower
importance in the SME segment. Gender heterogeneity variable remains insignificant also
when controlling for firm size or age. Although large and heterogeneous boards could
provide more balanced decisions, these can be slower due to longer time requirements for
harmonizing different views, and thus, in case of SMEs the speed of decisions that comes
from smaller boards irrespective of gender composition seems to matter. Also, as the base
risk of failure is higher for SMEs than for large firms (Altman et al., 2017), SMEs are more
frequently in crisis situation and often need prompt decisions for survival.
Variables reflecting board tenure and age of top managers both deal with experience
factor in running the firm. While the former shows the specific firm-related experience, the
latter is related to a more general life and business experience of top managers. Our analysis
shows that in case of SMEs, only the general experience (as represented by CEO age) is a
significant determinant of failure risk. Specifically, more life and business experience
Research question
Result
RQ1. Board size
RQ2. Board gender
heterogeneity
RQ3. Board tenure
Failure risk increases with the increase in board size
Failure risk is irrelevant to whether boards are gender homo- or
heterogeneous
Failure risk is irrelevant to how long from firm lifetime the longest serving
board member has been on its position
Failure risk decreases with the increase in the biological age of oldest
manager
Failure risk increases with the increase in the number of other board
memberships
Failure risk is irrelevant to whether there is a majority owner
RQ4. Top manager’s age
RQ5. Multiple
directorships
RQ6. Ownership
concentration
RQ7. Managerial
ownership
Failure risk decreases with the increase of share capital owned by board
members
Note: The results of the research questions rely on the results in the base model presented in Table III
Failure risk
713
Table IV.
Results of research
questions
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714
decreases the failure risk. Specific firm experience, on the other hand, is insignificant in that
respect. Interestingly still, when analyzing the issue in size groups, then in case of the
smaller SMEs the managerial general life and business experience (MAGE) seems not to
matter that much, but the firm-specific experience (as measured by BTENURE) is more
relevant. The explanation could be, that in very small firms it matters more, whether the
manager is competent in the specific business area, rather than having a more broader and
general knowledge.
Multiple directorships have two-fold effect on the firm. Being involved with many firms
equips the manager with a broader network, new ideas and possibilities to gain wider
experience. At the same time it leaves the manager less time to deal with any single firm it is
associated with. Our results show that in case of SMEs, multiple directorships increases the
failure risk, which has been proposed in previous studies (Core et al., 1999; Jiraporn et al.,
2008; Berberich and Niu, 2011). This finding indicates that in case of SMEs the focus factor
might be more important than gathering wider experience and network from other firms.
Given that SME boards tend to be much smaller than the ones of large firms (in our sample,
the median board size was one person), the price of distraction is much higher for SMEs
because there are less board members to compensate for the lost time of that board member
who is dealing with the issues of another firm. The analysis by size groups shows that the
negative impact of multiple directorships is stronger in the bigger SME group, which could
be explained by the need to contribute more time in case of larger firms, where the business
process is more elaborate and properly managing the firm needs stronger focus. An
additional interesting aspect rises from the analysis by age groups. Namely, multiple
directorships increases failure risk only in case of younger firms, while it is insignificant in
case of older firms. The underlying logic for this could be that younger firms need more
managerial focus to get the business running, processes established, resource base built and
clients won. At a certain point the firm is sufficiently set up so that the top manager can
start delegating more and spend more time on other firms, but the latter does not transfer in
any way to the wellbeing of the firm under question.
Ownership concentration and managerial ownership variables deal with the role of
owners in running the firm. More specifically, concentrated ownership variable indicates
whether or not there is a single majority owner who can have substantial impact on the
decisions that the managers take (for example by single-handedly hiring and firing the
managers). Managerial ownership takes it one step further and shows the overlap between
owners and managers. If the overlap is large (88 per cent in our data set), it means that the
classical agency problem between owners and managers is reduced and the convergence-ofinterest hypothesis (Morck et al., 1998) prevails. Our results show that while ownership
concentration is an insignificant determinant of failure risk, the managerial ownership
variable is significant, meaning that high overlap between managers and owners reduces
failure risk in case of SMEs. The analysis by size and age groups shows that the failure risk
reduction from having managerial ownership is relatively stronger in case of larger and
younger SME groups. In terms of firm age, the possible interpretation could be that younger
firms need a clear focus from the founder (owner) to get up and running. Having separate
non-owner managers might create a potential divergence of interests between owners and
hired managers, which in turn makes the decision process slower and thus increases the
failure risk. When SMEs get older and more established, the negative effect of having nonowner managers decreases. This logic bears resemblance to the speed versus balanced
decisions discussion above in case of board size and heterogeneity variables. The
interpretation of size groups’ results could in a way be similar to the logic of multiple
directorships discussion. The larger SME group benefits relatively more from the focused
and well-motivated owner-managers, as the business is more complex in that group than in
the smaller SME group.
6. Conclusions
The aim of this study was to explore how corporate governance variables are interconnected
with failure risk in case of SMEs. We applied a sample of 67,058 Estonian SMEs to calculate
seven different corporate governance characteristics and failure risk based on a well-known
universal Altman et al. (2017) failure prediction model. The results indicate, that with the
growth in manager’s age and the presence of managerial ownership, failure risk reduces. In
turn, larger boards and managers having directorships in other firms lead to a higher failure
risk. Gender heterogeneity in the board, board tenure length and ownership concentration
by means of having a majority owner are not associated with failure risk. Firm size or age
can have an effect on how the corporate governance variables impact failure risk.
This study makes several important contributions to the literature. Firstly, it focuses on
the relationship between corporate governance variables and firm failure specifically in the
SME context, which is a relatively underexplored area, even despite the importance of SMEs
in the world economy. Secondly, our study uses a very large whole population data set
(67,058 firms) giving more weight to the statistical validity of the results. Thirdly, both the
corporate governance and financial data used in the analysis are retrieved from the official
agency, i.e. Estonian Business Registry. This further improves the validity of our results by
eliminating an important limitation many previous studies suffer from, namely data
collection via surveys and the resulting self-reporting bias.
We would also like to highlight some of the practical implications from our analysis for
owners and managers of SMEs. It appears that SMEs that are run by owner-managers
(where the managerial ownership is high) tend to have lower failure risk. Therefore,
entrepreneurs who are planning to start a small business or already own one, should be
cautious when aiming to hire an outside CEO. Most likely the owner of the small business
should be ready to act as the executive of the firm for an extended period of time. Also, it
seems that smaller boards tend to have lower failure risk, but only in case multiple
directorships are avoided. The latter means that if a small firm owner plans to establish
additional firm(s), he will have to fragment the focus between those firms, or hire an outside
CEO, both of which scenarios increase the failure risk.
There are also some implications for external institutions such as legislators and
financiers. For legislators it would be important to note that firm size and age moderate the
impact of certain corporate governance variables on SME performance. This means that it
might be beneficial for the society to have different regulations for firms depending on their
size and/or age. For example, legislators could encourage larger firms to have larger boards
while not requiring smaller firms to have such large boards (as that would increase their
failure risk). Similarly, external finance providers (in the case of SMEs most likely banks or
other trade credit providers) might benefit from including corporate governance variables
together with firm size and age information in their decision algorithms as these improve the
accuracy of the performance forecast models of SMEs. The latter is especially important in
case (timely) financial information about the firm is not available.
This study is subject to several limitations. First, it focuses on a single country, so further
research is needed in other environments to validate the results on an international scale.
Second, even though our analysis covers specifically the SME segment, it should be noted
that the segment itself is fairly heterogeneous in terms of size ranging from really tiny
micro-firms to relatively established firms of up to 250 employees and assets of e43m. Due
to the economic structure of Estonia, the majority of firms in our data set are very small
Failure risk
715
MRR
42,6
716
(micro firms). It is possible that different factors are prevalent in the larger end of SME
spectrum and further research should test and verify this in different data sets consisting of
bigger SMEs. Third, several SMEs in our sample are likely to be family firms where (some
of) the owners and board members are relatives. This could moderate the linkages between
various corporate governance variables and failure risk. Unfortunately, information about
family ties was not present in our data; thus, exploring the effect of family relations could be
an interesting avenue of future research.
Notes
1. Not to be confused with public firm in the sense of being traded at the stock market. Majority of
PuLC type firms are private, i.e. they are not traded at the stock market (there were only 15 firms
listed on Tallinn Stock Exchange main list in August 2018).
2. Less than 250 workers and balance sheet total # 43 million euros.
3. To enhance the textual flow of the results and discussion part, we will use in these sections
increase/decrease failure risk, instead of the longer version increase/decrease the probability of
belonging to the group of firms in failure risk.
References
Adams, R.B. and Funk, P. (2012), “Beyond the glass ceiling: does gender matter?”, Management Science,
Vol. 58 No. 2, pp. 219-235.
Altman, E.I. (1968), “Financial ratios, discriminant analysis and the prediction of corporate
bankruptcy”, Journal of Finance, Vol. 23 No. 4, pp. 589-609.
Altman, E.I. and Sabato, G. (2007), “Modeling credit risk for SMEs: evidence from the US market”,
Abacus, Vol. 43 No. 3, pp. 332-357.
Altman, E.I., Sabato, G. and Wilson, N. (2010), “The value of non-financial information in SME risk
management”, The Journal of Credit Risk, Vol. 6 No. 2, pp. 95-127.
Altman, E.I., Iwanicz-Drozdowska, M., Laitinen, E.K. and Suvas, A. (2017), “Financial distress
prediction in an international context: a review and empirical analysis of Altman’s Z-score
model”, Journal of International Financial Management and Accounting, Vol. 28 No. 2,
pp. 131-171.
Beaver, H.W. (1966), “Financial ratios as predictors of failure”, Journal of Accounting Research, Vol. 4,
pp. 71-111.
Bellovary, J.L., Giacomino, D.E. and Akers, M.D. (2007), “A review of bankruptcy prediction studies:
1930 to present”, Journal of Financial Education, Vol. 33 No. 4, pp. 3-41.
Bennedsen, M., Kongsted, H.C. and Nielsen, K.M. (2008), “The causal effect of board size in the
performance of small and medium-sized firms”, Journal of Banking and Finance, Vol. 32 No. 6,
pp. 1098-1109.
Berberich, G. and Niu, F. (2011), “Director business, director tenure and the likelihood of encountering
corporate governance problems”, CAAA Annual Conference 2011, available at: https://papers.
ssrn.com/sol3/papers.cfm?abstract_id=1742483
Bertrand, M. and Schoar, A. (2003), “Managing with style: the effect of managers on firm policies”, The
Quarterly Journal of Economics, Vol. 118 No. 4, pp. 1169-1208.
Buchanan, B. (1974), “Building organizational commitment: the socialization of managers in work
organizations”, Administrative Science Quarterly, Vol. 19 No. 4, pp. 533-546.
Campbell, K. and Minguez-Vera, A. (2008), “Gender diversity in the boardroom and firm financial
performance”, Journal of Business Ethics, Vol. 83 No. 3, pp. 435-451.
Carpenter, M.A. (2002), “The implications of strategy and social context for the relationship between
top management team heterogeneity and firm performance”, Strategic Management Journal,
Vol. 23 No. 3, pp. 275-284.
Carpenter, M.A. and Westphal, J.D. (2001), “The strategic context of external network ties: examining
the impact of director appointments on board involvement in strategic decision making”,
Academy of Management Journal, Vol. 44 No. 4, pp. 639-660.
Carter, D.A., Simkins, B.J. and Simpson, W.G. (2003), “Corporate governance, board diversity, and firm
value”, The Financial Review, Vol. 38 No. 1, pp. 33-53.
Carter, D.A., D’Souza, F., Simkins, B.J. and Simpson, W.G. (2010), “The gender and ethnic diversity of
US boards and board committees and firm financial performance”, Corporate Governance: An
International Review, Vol. 18 No. 5, pp. 396-414.
Chaganti, R.S., Mahajan, V. and Sharma, S. (1985), “Corporate board size, composition, and corporate
failures in retailing industry”, Journal of Management Studies, Vol. 22 No. 4, pp. 400-417.
Chan, C.-Y., Chou, D.-W., Lin, J.-R. and Liu, F.-Y. (2016), “The role of corporate governance in
forecasting bankruptcy: pre- and post-SOX enactment”, The North American Journal of
Economics and Finance, Vol. 35, pp. 166-188, available at: www.sciencedirect.com/science/
article/pii/S1062940815000959
Ciampi, F. (2015), “Corporate governance characteristics and default prediction modeling for small
enterprises. an empirical analysis of Italian firms”, Journal of Business Research, Vol. 68 No. 5,
pp. 1012-1025.
Ciampi, F. (2017), “The potential of top management characteristics for small enterprise default
prediction modeling”, WSEAS Transactions on Business and Economics, Vol. 14 No. 1,
pp. 397-408.
Coles, J.L., Lemmon, M.L. and Meschke, J.F. (2012), “Structural models and endogeneity in corporate
finance: the link between managerial ownership and corporate performance”, Journal of
Financial Economics, Vol. 103 No. 1, pp. 149-168.
Core, J., Holthausen, R. and Larcker, D. (1999), “Corporate governance, chief executive compensation,
and firm performance”, Journal of Financial Economics, Vol. 51 No. 3, pp. 371-406.
Daily, C.M. and Dalton, D.R. (1994), “Bankruptcy and corporate governance: the impact of board
composition and structure”, Academy of Management Journal, Vol. 37 No. 6,
pp. 1603-1617.
Darrat, A.F., Gray, S., Park, J.C. and Wu, Y. (2016), “Corporate governance and bankruptcy risk”,
Journal of Accounting, Auditing and Finance, Vol. 31 No. 2, pp. 163-202.
De Miguel, A., Pindado, J. and de la Torre, C. (2004), “Ownership structure and firm value: new evidence
from Spain”, Strategic Management Journal, Vol. 25 No. 12, pp. 1199-1207.
Demsetz, H. and Villalonga, B. (2001), “Ownership structure and corporate performance”, Journal of
Corporate Finance, Vol. 7 No. 3, pp. 209-233.
Dimitras, A.I., Zanakis, S.H. and Zopounidis, C. (1996), “A survey of business failures with an emphasis
on prediction methods and industrial applications”, European Journal of Operational Research,
Vol. 90 No. 3, pp. 487-513.
Dowell, G.W.S., Shackell, M.B. and Stuart, N.V. (2011), “Boards, CEOs, and surviving a financial crisis:
evidence from the internet shakeout”, Strategic Management Journal, Vol. 32 No. 10,
pp. 1025-1045.
Eisenberg, T., Sundgren, S. and Wells, M.T. (1998), “Larger board size and decreasing firm value in
small firms”, Journal of Financial Economics, Vol. 48 No. 1, pp. 113-139.
Elshahat, I., Elshahat, A. and Rao, A. (2015), “Does corporate governance improve bankruptcy
prediction?”, Academy of Accounting and Financial Studies Journal, Vol. 19 No. 1, pp. 107-119.
Estonian Commercial Code (2018), available at: www.riigiteataja.ee/en/eli/ee/Riigikogu/act/519122017001/
consolide (accessed 08.08.18).
Failure risk
717
MRR
42,6
718
Fama, E. and Jensen, M. (1983), “Separation of ownership and control”, The Journal of Law and
Economics, Vol. 26 No. 2, pp. 301-325.
Ferris, S.P., Jagannathan, M. and Pritchard, A.C. (2003), “Too busy to mind the business? Monitoring by
directors with multiple board appointments”, Journal of Finance, Vol. 58 No. 3, pp. 1087-1111.
Fich, E.M. and Slezak, S.L. (2008), “Can corporate governance save distressed firms from bankruptcy?
An empirical analysis”, Review of Quantitative Finance and Accounting, Vol. 30 No. 2,
pp. 225-251.
Geletkanycz, M.A. and Boyd, B.K. (2011), “CEO outside directorships and firm performance: a
reconciliation of agency and embeddedness views”, Academy of Management Journal, Vol. 54
No. 2, pp. 335-352.
Groysberg, B. and Bell, D. (2013), “Dysfunction in the boardroom”, Harvard Business Review, Vol. 91
No. 5, pp. 89-97.
Hambrick, D.C. (2007), “Upper echelons theory: an update”, Academy of Management Review, Vol. 32
No. 2, pp. 334-343.
Hambrick, D.C. and Mason, P.A. (1984), “Upper echelons: the organization as a reflection of its top
managers”, Academy of Management Review, Vol. 9 No. 2, pp. 193-206.
Han, K. and Suk, D. (1998), “The effects of ownership structure on firm performance: additional
evidence”, Review of Financial Economics, Vol. 7 No. 2, pp. 143-155.
Henderson, A.D., Miller, D. and Hambrick, D.C. (2006), “How quickly do CEOs become obsolete?
Industry dynamism, CEO tenure, and company performance”, Strategic Management Journal,
Vol. 27 No. 5, pp. 447-460.
Hillman, A.J., Cannella, A.A. and Harris, I.C. (2002), “Women and racial minorities in the boardroom:
how do directors differ?”, Journal of Management, Vol. 28 No. 6, pp. 747-763.
Huse, M. (2007), Boards, Governance and Value Creation, Cambridge University Press, Cambridge.
Iwanicz-Drozdowska, M., Laitinen, E.K., Suvas, A. and Altman, E.I. (2016), “Financial and nonfinancial
variables as long-horizon predictors of bankruptcy”, The Journal of Credit Risk, Vol. 12 No. 4, pp. 49-78.
Jensen, M.C. and Meckling, W.H. (1976), “Theory of the firm: managerial behaviour, agency costs and
ownership structure”, Journal of Financial Economics, Vol. 3 No. 4, pp. 305-360.
Jiraporn, P., Kim, Y.S. and Davidson, W.N. (2008), “Multiple directorships and corporate diversification”,
Journal of Empirical Finance, Vol. 15 No. 3, pp. 418-435.
Kapopoulos, P. and Lazaretou, S. (2007), “Corporate ownership structure and firm performance: evidence
from Greek firms”, Corporate Governance: An International Review, Vol. 15 No. 2, pp. 144-154.
McConnell, J. and Servaes, H. (1990), “Additional evidence on equity ownership and corporate value”,
Journal of Financial Economics, Vol. 27 No. 2, pp. 595-612.
Morck, R., Shleifer, A. and Vishny, R. (1998), “Management ownership and market valuation: an
empirical analysis”, Journal of Financial Economics, Vol. 20 No. 1, pp. 293-315.
Mselmi, N., Lahiani, A. and Hamza, T. (2017), “Financial distress prediction: the case of French small
and medium-sized firms”, International Review of Financial Analysis, Vol. 50, pp. 67-80.
Paniagua, J., Rivelles, R. and Sapena, J. (2018), “Corporate governance and financial performance: the
role of ownership and board structure”, Journal of Business Research, Online First Version,
Vol. 89, pp. 229-234.
Peni, E. (2014), “CEO and chairperson characteristics and firm performance”, Journal of Management
and Governance, Vol. 18 No. 1, pp. 185-205.
Perrini, F., Rossi, G. and Roverra, B. (2008), “Does ownership structure affect performance? Evidence
from the Italian market”, Corporate Governance: An International Review, Vol. 16 No. 4,
pp. 312-325.
Pfeffer, J. and Salancik, G.R. (1978), The External Control of Organizations: A Resource Dependence
Approach, Harper and Row Publishers, New York, NY.
Platt, H. and Platt, M. (2012), “Corporate board attributes and bankruptcy”, Journal of Business
Research, Vol. 65 No. 8, pp. 1139-1143.
Pompe, P.P.M. and Bilderbeek, J. (2005), “The prediction of bankruptcy of small- and medium-sized
industrial firms”, Journal of Business Venturing, Vol. 20 No. 6, pp. 847-868.
Post, C. and Byron, K. (2015), “Women on boards and firm financial performance: a meta-analysis”,
Academy of Management Journal, Vol. 58 No. 5, pp. 1546-1571.
Pursey, P., Heugens, R., Essen, M. and Oosterhout, J. (2009), “Meta-analyzing ownership concentration
and firm value in Asia: towards a more find-grained understanding”, Asia Pacific Journal of
Management, Vol. 26 No. 3, pp. 481-512.
Shleifer, A. and Vishny, R.W. (1986), “Large shareholders and corporate control”, Journal of Political
Economy, Vol. 94 No. 3 Part 1, pp. 461-489.
Short, H. and Keasey, K. (1999), “Managerial ownership and the performance of firms: evidence from
the UK”, Journal of Corporate Finance, Vol. 5 No. 1, pp. 79-101.
Singh, V., Terjesen, S. and Vinnicombe, S. (2008), “Newly appointed directors in the boardroom: how do
women and men differ?”, European Management Journal, Vol. 26 No. 1, pp. 48-58.
Sun, J., Li, H., Huang, Q.-H. and He, K.-Y. (2014), “Predicting financial distress and corporate failure: a
review from the state-of-the-art definitions, modeling, sampling, and featuring approaches”,
Knowledge-Based Systems, Vol. 57, pp. 41-56.
Thomsen, S. and Pedersen, T. (2000), “Ownership structure and economic performance in the largest
european companies”, Strategic Management Journal, Vol. 21 No. 6, pp. 689-705.
Vafeas, N. (2003), “Length of board tenure and outside director independence”, Journal of Business
Finance & Accounting, Vol. 30 No. 7, pp. 1043-1064.
Wang, G., Holmes, R.M., Oh, I.-S. and Zhu, W. (2016), “Do CEOs matter to firm strategic actions and
firm performance? A meta-analytic investigation based on upper Echelons theory”, Personnel
Psychology, Vol. 69 No. 4, pp. 775-862.
World Bank (2018), “Doing business 2018. Reforming to create jobs”, available at: www.doingbusiness.
org/reports/global-reports/doing-business-2018 (accessed: 08.08.18).
Yermack, D. (1996), “Higher market valuation of companies with small board of directors”, Journal of
Financial Economics, Vol. 40 No. 2, pp. 185-211.
Corresponding author
Oliver Lukason can be contacted at: oliver.lukason@ut.ee
Failure risk
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Appendix
Variable
Coefficient
720
(Current assets – current liabilities)/total assets (i.e. WCTA)
Retained earnings/total assets (i.e. RETA)
Earnings before interest and taxes/total assets (i.e. EBITTA)
Book value of equity/total debt (i.e. BVETD)
Constant
Table AI.
Altman et al. (2017)
Model 2 used to
calculate failure risk
Note: For each firm, failure risk has been calculated as follows and coded as 1, when p > 0.5, and 0
1
otherwise: p ¼ 1þe1 L ¼ 1þeðConstant0:495WCTA0:862RETA1:721EBITTA0:017BVETD
Þ
Source: Altman et al. (2017; p. 154)
Variable
Table AII.
Two logistic
regression models to
portray the effect of
firm size on the
results
BSIZE
BGENDER
MAGE
MDIRECT
BTENURE
OCONC
MOWN
Constant
B
0.159
0.114
0.001
0.031
0.181
0.029
0.221
0.974
Total assets # e32,921
S.E.
Wald
0.034
0.048
0.001
0.007
0.065
0.040
0.050
0.096
22.375
5.629
0.225
17.680
7.809
0.505
19.220
102.337
Sig.
B
0.000
0.018
0.635
0.000
0.005
0.477
0.000
0.000
0.019
0.018
0.001
0.072
0.059
0.001
0.416
1.685
Total assets > e32,921
S.E.
Wald
0.036
0.058
0.002
0.006
0.072
0.047
0.055
0.114
0.277
0.092
0.130
129.596
0.670
0.001
56.543
220.169
Sig.
0.599
0.761
0.719
0.000
0.413
0.978
0.000
0.000
Notes: The initial firm population is divided into two, the median firm size (total assets in the year 2015)
being the breakeven point. Both subpopulations include an equal number of 33,529 firms
Variable
Table AIII.
Two logistic
regression models to
portray the effect of
firm age on the
results
0.495
0.862
1.721
0.017
0.035
BSIZE
BGENDER
MAGE
MDIRECT
BTENURE
OCONC
MOWN
Constant
B
0.131
0.028
0.001
0.029
0.062
0.069
0.285
1.264
Age # 7.50 years
S.E.
Wald
Sig.
B
0.035
0.052
0.001
0.007
0.086
0.042
0.051
0.113
0.000
0.591
0.257
0.000
0.475
0.105
0.000
0.000
0.012
0.055
0.001
0.005
0.135
0.022
0.215
1.436
13.864
0.289
1.282
19.711
0.511
2.634
31.369
125.167
Age > 7.50 years
S.E.
Wald
Sig.
0.034
0.052
0.001
0.007
0.059
0.043
0.054
0.102
0.730
0.291
0.463
0.501
0.022
0.615
0.000
0.000
0.119
1.117
0.540
0.454
5.209
0.253
15.874
200.077
Notes: The initial firm population is divided into two, the median age being the breakeven point.
Subpopulation of younger firms includes 33,531 and older firms 33,527 observations