Journal of Entrepreneurship and Public Policy
The capital constraint paradox in micro and small family and nonfamily firms
Anders Bornhäll Dan Johansson Johanna Palmberg
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JEPP
5,1
The capital constraint paradox
in micro and small family and
nonfamily firms
38
Received 19 October 2015
Revised 1 February 2016
Accepted 2 February 2016
Anders Bornhäll
HUI Research, Stockholm, Sweden;
Department of Economics, Dalarna University, Borlänge, Sweden and
Örebro University School of Business, Örebro, Sweden
Dan Johansson
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Örebro University School of Business, Örebro, Sweden and
HUI Research, Stockholm, Sweden, and
Johanna Palmberg
Swedish Entrepreneurship Forum, Stockholm, Sweden and
CESIS, KTH Royal Institute of Technology,
Stockholm, Sweden
Abstract
Purpose – The purpose of this paper is to investigate the importance of the entrepreneur’s quest for
independence and control over the firm for governance and financing strategies with a special focus on
family firms and how they differ from nonfamily firms.
Design/methodology/approach – The analysis is based on 1,000 telephone interviews with
Swedish micro and small firms. The survey data are matched with firm-level data from the Bureau van
Dijks database ORBIS.
Findings – The analysis shows that independence is a prime motive for enterprises, statistically
significantly more so for family owners. Family owners are more prone to use either their own savings
or loans from family and are more reluctant to resort to external equity capital. Our results indicate a
potential “capital constraint paradox”; there might be an abundance of external capital while firm
growth is simultaneously constrained by a lack of internal funds.
Research limitations/implications – The main limitation is that the study is based on crosssection data. Future studies could thus be based on longitudinal data.
Practical implications – The authors argue that policy makers must recognize independence and
control aversion as strong norms that guide entrepreneurial action and that micro- and small-firm
growth would profit more from lower personal and corporate income taxes compared to policy
schemes intended to increase the supply of external capital.
Originality/value – The paper offers new insights regarding the value of independence and how it
affects strategic decisions within the firm.
Keywords Tax policy, Family firms, Informal institutions, Ownership
Paper type Research paper
Journal of Entrepreneurship and
Public Policy
Vol. 5 No. 1, 2016
pp. 38-62
© Emerald Group Publishing Limited
2045-2101
DOI 10.1108/JEPP-10-2015-0033
JEL Classification — L210, G320, G340
The authors gratefully acknowledge the Confederation of Swedish Enterprise for financing the
survey. Financial support for Johanna Palmberg from the Smelink Foundation is gratefully
acknowledged. The authors are grateful for comments on earlier versions of the paper from Per-Olof
Bjuggren, Ana Castro, Niklas Rudholm, seminar participants at CESIS, KTH Royal Institute of
Technology, the Inaugural WINIR-conference in London, and Örebro University.
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1. Introduction
There is an extensive discussion of the idea that small-firm growth is hampered by a lack
of capital, which is expected to have significant economic and social costs (Abe, 2015;
Carpenter and Petersen, 2002; Didier et al., 2014; Gallo et al., 2004; Haynes et al., 1999).
Asymmetric information may make external investors more reluctant to supply capital to
smaller firms than to larger, more mature firms (e.g. De Massis et al., 2015; Hubbard, 1998;
Kon and Storey, 2003; Lee, 2014). Accordingly, various policy initiatives have been
implemented across the member countries of the European Union (EU) and the
Organization for Economic Cooperation and Development to facilitate access to external
finance by smaller firms, particularly firms that are potentially innovative and high growth
(Brown et al., 2014; European Commission, 2012; Mason and Brown, 2013; OECD, 2010).
However, previous studies have shown that small firms are characterized by
governance attributes that influence financing decisions and restrict the demand for
external capital (Davidsson, 1989; Gómez-Mejía et al., 2007; Romano et al., 2001)[1].
This observation is especially true of family firm owners, for whom the quest to remain
independent and maintain control over their firms often serves as a norm that
ultimately restricts financial and investment decisions (Blanco-Mazagatos et al., 2007;
Gallo et al., 2004). External investors presumably require influence over their
investments and thereby over firm governance. Thus, there may be a tradeoff between
independence and firm growth. Seizing a business opportunity and expanding a
business may require external funding, which might come at the cost of a loss of
control, causing the owner to refrain from growth.
The purpose of this paper is to obtain additional insight into financing decisions of
micro and small firms, particularly family firms. We investigate three related issues: is
independence a stronger motive for enterprise among family owners than nonfamily
owners? Is the control premium higher in family firms compared with nonfamily firms?
Do preferences toward internal and external capital differ in family vs nonfamily
firms?[2] The analysis is grounded in research that recognizes the fundamental role of
institutions in economic growth. These institutions are of both a formal and informal
character, and economic development benefits when such institutions are aligned and
conducive to productive entrepreneurship (Campbell, 2012). The idea underlying the
paper is that norms – an informal institution – may encourage family firms to value
independence to a greater degree than nonfamily businesses. Family firms thus exhibit
a lower demand for external capital and a higher preference for internal funds.
Our study is based on a representative sample of the total population of Swedish
private micro (1-9 employees) and small (10-49 employees) limited stock companies. Data
were gathered through 1,000 telephone interviews with controlling owners matched with
register data that enable us to distinguish family from nonfamily firms and to explore
differences between the two. In the survey (conducted in 2013) we asked questions that
allow for an investigation of the influence of family ownership on financial and investment
decisions, controlling for personal features of the owner (e.g. gender, education, and age),
firm characteristics (e.g. size, age, and industry affiliation) and capital structure
(e.g. gearing and profitability). The data from the survey is matched with firm-level data
from the comprehensive Bureau van Dijks database ORBIS. The combination of survey
and register data is well-suited for the purpose of this study since it enables us to account
for both owner attitudes and firm-specific characteristics in the empirical analysis.
Although previous research has examined motivational forces among business
owners, control premiums, and attitudes toward internal and external capital, few
empirical investigations, using larger samples, have examined these issues with respect
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to micro and small family firms. Empirical analyses of family firms are frequently more
difficult to conduct because official register-based databases often do not recognize family
ownership or the involvement of families in firm governance[3]. The poor availability of
data has directed empirical research on family firms toward studies of large listed firms,
for which ownership data are more readily available and of better quality (Dyer, 2006;
Fernando et al., 2014; Mazzi, 2011; Sciascia and Mazzola, 2008; Westhead and Howorth,
2006)[4]. Romano et al. (2001), who examined financial decision making in Australian
family firms, including smaller firms, is an important exception[5]. Recently, Koropp et al.
(2014) applied planned behavior theory to study financial choices in 118 larger (sales
required to exceed Euro 750,000 to be included) German family firms[6].
Our study adds to previous literature by focussing on micro and small firms,
identifying both family and nonfamily firms and thus enabling a comparison of these two
categories of firms in various respects. Adding to previous studies, we investigate whether
there are statistically significant differences between family and nonfamily owners.
For example, are family owners largely motivated by independence, and do they have
stronger preferences for own equity? We also seek to estimate the control premium in
these firms and examine whether it differs between family and nonfamily firms. We argue
that this is of interest for research as well for economic policy because family firms are
estimated to be the most common business form around the world and make notable
contributions to entrepreneurship, innovation, employment, and economic growth
(Andres, 2008; Astrachan and Shanker, 2003; Barca and Becht, 2001; Claessens et al., 2002;
Claessens and Fan, 2002; Isakov and Weisskopf, 2014; La Porta et al., 1999; Villalonga and
Amit, 2010). Additional knowledge of family firms’ financial and investment decisions and
how they differ from those of nonfamily firms are therefore of importance for researchers
in understanding economic development and for policy makers in conducting efficient
economic policy. The focus on micro and small firms is motivated by three considerations.
First, the literature shows that lack of capital is firm size dependent; simplified, the smaller
the firm and the less established the business idea, the more difficult it is to finance
investment, and the larger the firm and the more established the business idea, the easier it
is to access capital. Second, financial decision making in micro and small family and
nonfamily firms is a less explored field of research. Third, research suggests that a
fraction of smaller and younger firms with growth ambitions are critical to job generation
and economic growth and help explain country differences with respect to job creation
(Anyadike-Danes et al., 2015; Daunfeldt et al., 2014; Henrekson and Johansson, 2010).
Additionally, family businesses are associated with entrepreneurship. It may be difficult
to identify entrepreneurs and entrepreneurial firms (Campbell and Mitchell, 2012), but
firms established by entrepreneurs have probably been, and perhaps in many cases
remain, family firms in terms of the definition based on family control and participation in
governance[7]. Indeed, Schumpeter (1934) argued that founding a family dynasty was
a motive for many entrepreneurs[8].
Our results are in line with previous research and provide new insights with a
bearing on economic policy. Nearly all of the respondents – approximately 90 percent –
indicate that independence is an important or very important motive for enterprising.
As found in previous research, we observe that family owners are significantly more
likely than nonfamily owners to answer that they find independence “very important.”
Also similarly to other studies, we find support for the “pecking-order theory,”[9] which
asserts that both family and nonfamily firms most prefer to finance growth with company
profits, followed by bank debt and equity from current owners, while equity from external
investors is less preferred. Additionally, we find that family firms are significantly more
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prone to use the equity of current owners and loans and equity of new family members
than are nonfamily firms. Furthermore, such firms are less willing to use equity of external
investors than are nonfamily firms, although the latter result is not statistically significant.
We also observe that the control premium for the survey firms largely exceeds estimates
for listed firms. Approximately one-third of respondents are unwilling to sell shares that
give an external investor major influence when they are offered the market value of the
shares plus 70-100 percent. Unexpectedly, we find no statistically significant difference
between family and nonfamily owners in this respect. One possible explanation for this
result is that both family and nonfamily owners highly value control and that the scale
should have been set even higher to detect potential differences.
This study has a number of policy implications relevant to the contemporary debate on
capital as a constraint on productive entrepreneurship and firm growth. We argue that
smaller firms, and particularly family firms, may face a “capital constraint paradox,”
whereby the supply of external capital might be sufficient, but firm owners might refrain
from accessing it due to fear of losing control of their companies. This suggests a conflict
between policy schemes directed toward increasing the supply of external capital and the
informal institution of independence as a norm. Thus, lack of retained cash flows and
private wealth would hinder investment in profitable projects and constrain firm growth.
Our results indicate that policy schemes that aim to increase the supply of external capital
will be less effective, due to low demand from business owners, compared with other
programs directed toward increasing internally generated funds. As business owners
appear to be willing to forgo business opportunities to avoid losing control over their
businesses, our study suggests that firm growth would be enhanced by stimulating private
savings and internally generated funds. Lowering personal and corporate income taxes are
two reforms that would increase such funding, which could be used to finance innovation
and growth (cf., Bruce et al., 2014; Gurley-Calvez and Bruce, 2014; Yakovlev and Davies,
2014). Lower tax levels could also be expected to lead to a higher demand for external equity
because the after-tax compensation for giving up independence and control would increase.
The remainder of this paper is organized as follows. The next section presents
the theoretical framework of the study and develops the hypotheses tested in the empirical
analysis. The third section presents our definitions, the survey, supplementary firm data,
and summary statistics. The econometric model and the results of the empirical analysis
are reported in Section 4. The final section discusses the results and concludes the paper.
Appendix 1 presents the questionnaire used in the telephone interviews, and Table AI
describes the Eurostat Industry classification used in the econometric analysis.
2. Theoretical framework and hypotheses
Institutions are recognized as fundamental to economic growth and development because
they provide the basic rules of human interaction for people in their use of scarce resources.
Institutions can broadly be categorized as either formal or informal. Formal institutions are
composed of constitutions, statutes, common law, and other governmental regulations,
whereas informal institutions are syntheses of traditions, customs, moral values, beliefs,
religion, and other norms of behavior that have endured over time. Formal institutions are
policy variables for the expression of collective preferences and the realization of the
programs of political parties. In contrast, informal rules are not policy variables over which
the state has control. They are enforced by society through sanctions, such as expulsion
from the community, ostracism by friends and neighbors, loss of reputation, and dishonor.
These sanctions can be efficient enforcement mechanisms because human beings are social
creatures who depend on social networks (Kasper et al., 2013).
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42
In particular, research has shown that independence and control are strong
norms that motivate and guide business owners. It is plausible that these norms are
stronger in family than in nonfamily firms because they are foundations upon which
family ownership rests (Romano et al., 2001; Sirmon and Hitt, 2003; Wyrwich, 2015).
We therefore hypothesize that family owners in general value independence and
control more highly than do owners of firms with dispersed ownership:
H1. Independence is a stronger motive for enterprising among family owners than
among nonfamily owners.
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H2. The control premium is higher in family firms than in nonfamily firms.
Moreover, it is plausible that norms toward independence and control affect behavioral
intention to use different sources of finance, which in turn affects financing behavior
(Koropp et al., 2014). This is in line with empirical findings observing that family owners
often appear to have a stronger aversion to external capital to maintain control over the
firm and thus are more dependent on private savings and internally generated funds than
are nonfamily firms (Gómez-Mejía et al., 2007; Romano et al., 2001). Thus, they might
overlook innovation, investment, and growth opportunities due to capital constraints
caused by dependence on internally generated cash flows, such as retained earnings and
family wealth (De Massis et al., 2015)[10]. Many family firms are small and take the form of
close corporations. Both of these traits imply further limitations on access to external
capital markets (Akyüz et al., 2006; Beck and Demirguc-Kunt, 2006; Sirmon and Hitt, 2003).
Accordingly, we theorize that family owners more strongly prefer to rely on internal
financing and personal wealth to finance investments and firm growth. To analyze
funding preferences among family and nonfamily owners, we draw on the pecking-order
theory and distinguish among six sources of funding: company profits, loans from
family, loans from banks and others, equity of owners, equity of new family members,
and equity of new external investors[11]. Theoretically, family firms should be more
reluctant than nonfamily firms to use equity of external investors (and loans from banks
and others because such funding threatens their independence). Similarly, family firms
should be more prone than nonfamily firms to use other sources of funding because they
“guarantee” family control. Thus, we formulate the following hypotheses:
H3. Family firms are more prone than nonfamily firms to use company profits to
finance growth.
H4. Family firms are more prone than nonfamily firms to use equity of owners to
finance growth.
H5. Family firms are more prone than nonfamily firms to use equity of new family
owners to finance growth.
H6. Family firms are more reluctant than nonfamily firms to use equity of new
external investors to finance growth.
H7. Family firms are more prone than nonfamily firms to use loans from family to
finance growth.
H8. Family firms are more reluctant than nonfamily firms to use loans from banks
and others to finance growth.
The results have a bearing on theory as well on economic policy, in particular on the
discussion of access to capital for entrepreneurial firms and the taxation of
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entrepreneurial profits. Tax theory is inconclusive regarding the effects of taxation of
firm owners. According to one line of argumentation, taxation of owners has limited
effect on investments because the loss of funds due to taxation can easily be
compensated by new equity or loans from international capital markets. According to
another line of argumentation, entrepreneurs may be reluctant to use international
capital markets, due to fear of loss of control (Henrekson and Sanandaji, 2016).
Economic policy will get opposite design depending on which argument the legislator
relies on.
Sweden can, in this regard, be considered an interesting policy experiment. The
strive for an egalitarian society and a belief in the efficiency of large firms because of
economies of scale coincided with an ideological aversion against capitalists and a
confidence in a tax theory advocating the first line of argument. This resulted in very
high taxation of entrepreneurs and poor incentives to start and grow entrepreneurial
firms after Second World War, especially during the 1970s and 1980s when taxation
could have confiscatory effects. Tax policy was drastically reformed in the beginning
of the 1990s in connection with a severe economic crisis caused by misconducted
economic policy. This reform and further reforms of tax policy has been pointed out as
an important explanation to the recovery of the Swedish economy. Though much
improved, taxation of Swedish entrepreneurs remain high in an international
perspective (Henrekson, 2005; Henrekson and Johansson, 2009, 2010; Heshmati et al.,
2010; Johansson et al., 2015).
3. Method
3.1 Definition of family firms
There is no universally accepted definition of what constitutes a family firm.
However, most empirical studies use a definition that considers ownership,
control and/or participation in executive management (Astrachan and Shanker,
2003; Miller et al., 2007; Villalonga and Amit, 2006, 2009). The European Commission
(2009, p. 9) identifies more than 90 definitions, most of which are not operational and
thus not applicable to empirical research[12]. In this paper, we use the definition
proposed by the European Commission (2009) and define non-listed family firms as
follows[13]:
A firm, of any size, is a family business, if:
i) The majority of decision-making rights is in the possession of the natural person(s) who
established the firm, or in the possession of the natural person(s) who has/have acquired
the share capital of the firm, or in the possession of their spouses, parents, child or
children’s direct heirs. The majority of decision-making rights are indirect or direct.
ii) At least one representative of the family or kin is formally involved in the governance of
the firm.
3.2 Survey and data
The empirical analysis is based on a telephone survey of owners of Swedish limited
liability corporations with 1-49 employees, where employees are defined as anyone who
receives a salary from the company, including the owners. The upper limit of 49
employees derives from the fact that smaller firms generally have greater difficulty
sourcing external capital and that, for comparative purposes, we wish to follow the EU
definition of micro (0-9 employees) and small (10-49 employees) firms. The survey
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covers all industries and the firms are categorized according to the Eurostat industry
classification, see Appendix 2. Corporations with no employees are excluded because
they generally report low (or no) economic activity (European Recommendations, 2003).
In total, 3,984 firm owners were contacted to ensure 1,000 complete responses to our
survey[14]. The firms were selected through a randomized stratified sample.
The sample was stratified over micro and small firms: 918 of the interviews were
conducted with firms with 1-9 employees, and 82 were conducted with companies with
10-49 employees. All of the interviews were conducted in 2013 by a professional market
research firm in Sweden. The largest controlling owner of each firm was asked to
respond to the survey.
The survey consists of 11 questions (see Appendix 1 for an English version of the
survey). Three of the questions concern the owner’s attitudes toward independence,
control, and financing strategy (questions 5-7). The survey also includes four questions
to identify family and nonfamily firms, e.g., the number of owners and their shares of
decision-making rights (questions 1-4), and four questions addressing background
facts about the owners (questions 8-11). The following questions in the survey
correspond to the hypotheses formulated in the previous section.
3.3 Variables
Independence. To investigate whether independence is a stronger motive for family
owners than for nonfamily owners, we presented respondents with the statement,
(question 5) “To be independent is very important to me,” with possible answers
ranging from “totally disagree” ¼ 1 to “totally agree” ¼ 5. The questions is inspired by
Davidsson (1989) and Wiklund et al. (2003) who both have conduct surveys to examine
the importance of independence as a motive for enterprising among Swedish business
owners. Combining three telephone interview studies, with 440, 400, and 630
respondents, they find that noneconomic factors may be more important than financial
outcomes in explaining business managers’ attitudes toward growth. The studies do
not distinguish between family and nonfamily firms.
Control premium. For larger, often listed, firms, there are two ways to estimate the
control premium (Dyck and Zingales, 2004a). The first is to estimate cross-country
variations in the price of decision-making rights compared with cash-flow rights, given
that decision-making rights do not entail inferior dividend rights (Barclay and
Holderness, 1989; Villalonga and Amit, 2006; Zingales, 1995). If there is a positive price
difference, one can assume that controlling investors identify a control value that is not
available to minority shareholders. The second way to estimate the value of control for
listed firms is to compare the price of shares in private negotiations for controlling
blocks with the share price after the market has absorbed the knowledge of a new
controlling owner. The difference in price should reflect the value that the new block
owner places on both cash flows from the investment and the value of the private
benefits of control generated as a result of being a block holder. Dyck and Zingales
(2004b) apply this method and find that the average value of control[15] across
countries is 14 percent. Sweden, together with the USA and the UK, report relatively
low values (7, 1, and 1 percent, respectively). Nenova (2003) applies the first method in
a cross-country analysis of 18 countries, reporting quite similar values as Dyck
and Zingales.
Our study focusses on micro and small non-listed firms; thus, we cannot observe
firms’ market values. Instead, we estimate the control premium as the price at which the
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owner would be willing to sell shares that would give an external investor major
influence in the company. We asked (question 6): “At what price would you be willing to
sell shares of your company that would give an external investor a major influence in the
company?” The fictitious example offers an interval between the company’s estimated
market value and an additional 10 percent up to 70-100 percent over the market value.
Attitudes toward different sources of funding. Question 5 was used to test H3:
“Regardless of whether your company plans to grow, with which of the following
sources of finance would you prefer to finance growth?” The answers range from “not
preferred” ¼ 1 to “most preferred” ¼ 5. Respondents could choose between equity of
owners, company profits, equity of new family owners, equity of new external
investors, loans from family, and loans from banks and others[16].
Studies of control aversion and the propensity to use external capital to finance
investments in small Swedish firms have previously been published by Berggren et al.
(2000) and Cressy and Olofsson (1997). In both studies, surveys were mailed to firms
with 5-199 employees; more than 500 firms were included in the sample, and the
response rate was approximately 50 percent. The two studies conclude that business
owners highly value control, that the demand for external capital is low, and that
internally generated funds are preferred when making new investments. The studies
do not distinguish family from nonfamily firms or estimate the control premium.
Control variables. The survey data are matched with firm-level data for 2012 from
the Bureau van Dijks database ORBIS, which contains balance sheet and income
statement data along with information on firm age, firm size, and industry affiliation.
The key variable of interest is a dummy variable that equals one if a firm is defined as a
family firm and zero otherwise, where a family firm is defined in terms of a combination
of equity ownership and active participation in governance. We also include a set of
control variables for owner, firm, and financial characteristics commonly used in
previous research. Variables for owner characteristics, education, gender, nationality,
number of owners, and owner’s age, are seen as critical for understanding owners’
motives for enterprising and decision making, for instance education has shown to
impact entrepreneurial decisions (Block et al., 2013), females’ investment and financing
decisions are suggested to be influenced by them being more risk avert than males
(Du Rietz and Henrekson, 2000), entrepreneurship may differ between natives and
immigrants (Constant and Zimmermann, 2006), concentrated and dispersed ownership
are expected to have an effect (as discussed in this paper) and owners’ age seems to be
negatively correlated with debt and outside participation in firms (Romano et al., 2001).
Firm variables relate to firm age, firm size, and industry affiliation, and have been
shown to impact enterprising in a number of aspects (Coad et al., 2014; Cucculelli and
Marchionne, 2012). Financial variables on profitability and capital structure (EBIT,
gearing ratio, operating revenues, profit margin, solvency ratio, and total assets) are
also included since they also are considered to have an influence (see, e.g. Romano et al.
(2001) for further discussion). Table I presents the variables used in the analysis.
4. Results
4.1 Descriptive statistics
Table II presents descriptive statistics for the variables. The sample consists of
53 percent family firms and 47 percent nonfamily firms. The firms are relatively young,
with an average age of 14 years. The oldest firm is 100 years old, and the youngest firm
is one year old. The average firm has five employees and 1.36 million USD in assets.
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Variables
Definition
Panel A: firm variables
Family firm
A dummy variable that takes the value of one if a family controls the majority
of the decision-making rights and at least one representative of the family or
kin is formally involved in the governance of the firm and zero otherwise
Firm age
Number of years of incorporation
Firm size
Number of employees
High and medium
High and medium high-technology manufacturing as defined by Eurostat
high-tech
(2014)
Medium low-tech
Medium low-technology manufacturing as defined by Eurostat (2014)
Low-tech
Low-technology manufacturing as defined by Eurostat (2014)
KIS
Knowledge-intensive services as defined by Eurostat (2014)
Less-KIS
Less knowledge-intensive services as defined by Eurostat (2014)
Other industries
Industries not classified as manufacturing, KIS or less-KIS by Eurostat (2014)
Panel B: financial variables
Gearing ratio
(Non-current liabilities+loans)/shareholders funds (%)
Operating revenues Revenues generated by everyday business activity (1,000,000 USD)
Profit margin
Net profit divided by revenues (%)
Solvency ratio
Shareholder funds/total assets (%)
Total assets
Total value of the firm’s assets (1,000,000 USD)
Table I.
Definitions: firm,
financial, and
owner variables
Panel C: owner variables
Education
A set of dummy variables that takes the value zero for primary education
( grundskola), and one for secondary education ( gymnasium) and tertiary
education (högskolestudier and forskarutbildning)
Female
A dummy variable that equals one if the controlling owner is female and zero
otherwise
Nationality
A set of dummy variables for the place of birth of the controlling shareholder
that equals zero for Sweden, one for Nordic countries exclusive of Sweden, one
for Europe exclusive of Nordic countries, and one for Africa and Asia. There
are no controlling shareholders from America or Australia in the sample,
reflecting the low immigration to Sweden from these continents
Number of owners
Number of owners, including family owners
Owner age
Owner’s age
Notes: See Appendix 2 for the Eurostat (2014) industry classification. We have combined high
technology and medium high technology in our empirical analysis because of the low number of
observations in these groups. The combined group is denoted high and medium high-tech
Sources: Survey data, ORBIS and own calculations
The variance is quite high, with the largest firm having 47 employees and total assets
of 295 million USD. The profitability measures (profit margin) illustrate that the sample
firms are profitable on average. Relatively few of the surveyed firms are high or
medium high-tech (2 percent), medium low-tech (4 percent) or low-tech (4 percent)
manufacturing firms, whereas a larger share (29 percent) are active in knowledgeintensive services (KIS). Most firms (43 percent) are active in less-KIS.
The average owner in the sample is a 50-year-old male born in Sweden with a
secondary school education. One-fifth of the firms have a female as the largest owner.
In total, 8 percent of the business owners are non-Swedish; 4 percent originate from
Europe, and 2 percent originate from Africa and other Nordic countries. In total, 10
percent of the respondents have a primary education, and 42 percent have a tertiary
education. The correlation table reports no problem with collinearity[17].
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Variable
Mean
SD
Min
Panel A: firm variables
Family firm (%)
Firm age (years)
Firm size (employees)
High and medium high-tech (%)
Medium low-tech (%)
Low-tech (%)
KIS (%)
Less-KIS (%)
Other industries (%)
53.30
13.92
4.54
2.30
4.40
3.60
28.70
43.30
17.70
49.91
12.84
6.06
15.00
20.52
18.64
45.26
49.57
38.19
0
1
1
0
0
0
0
0
0
Panel B: financial variables
Gearing ratio (%)
Operating revenues (1,000,000 USD)
Profit margin (%)
Solvency ratio (%)
Total assets (1,000,000 USD)
87.50
13.94
6.02
41.20
1.36
161.95
4.09
15.50
28.79
10.90
0
0
−86.68
−84.90
0.01
Max
1
100
47
1
1
1
1
1
1
Capital
constraint
paradox
47
998.08
90.42
99.16
99.24
295.32
Panel C: owner variables
Education (%)
Primary
10.00
30.02
0
1
Secondary
47.90
49.98
0
1
Tertiary
41.60
49.31
0
1
Female (%)
18.70
39.01
0
1
Nationality (%)
Swedish
91.10
28.48
0
1
Nordic
2.00
14.01
0
1
Europe
3.70
18.89
0
1
Africa/Asia
2.40
15.31
0
1
Number of owners
1.44
0.58
1
3
Owner age (years)
49.97
11.18
21
85
Notes: See Table I for definitions. There are 1,000 observations. Variables taking a minimum value of
Table II.
zero and a maximum value of one are dummy variables
Summary statistics –
Sources: Survey data, ORBIS, and own calculations
all firms
Table III presents descriptive statistics comparing mean values for family and nonfamily
firms, including t-values to determine whether there are significant differences between
the two types of firms. On average, family firms are slightly older than nonfamily firms
(14.04 and 13.78 years, respectively), but the difference is not statistically significant.
The average family firm has fewer employees but is larger in terms of total assets; both
differences are statistically significant. The two measures of profitability show that
family firms are less profitable than nonfamily firms; however, the differences are not
statistically significant. Family firms exhibit significantly smaller mean operating
revenues. The average family firm also has higher levels of debt (the gearing ratio is
significantly higher in family firms) and lower, but not significantly lower, solvency ratio
levels (i.e. the probability of meeting debt obligations is lower in family firms).
There are no statistically significant differences in the levels of firms operating in
different industries, with the exception of KIS industries, where family firms are
slightly less likely to be active (the t-value is 1.96).
The descriptive statistics exhibit interesting features with respect to governance
structure. Family firms have significantly fewer owners (1.38 compared to 1.51 for
JEPP
5,1
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48
Variable
Panel A: Firm variables
Firm age (years)
Firm size (employees)
High and medium high-tech (%)
Medium low-tech (%)
Low-tech (%)
KIS (%)
Less-KIS (%)
Other industries (%)
Panel B: financial variables
Gearing (%)
Operating revenues (1,000,000 USD)
Profit margin (%)
Solvency (%)
Total assets (1,000,000 USD)
Table III.
Summary statistics
for family and
nonfamily firms
Family firms
Mean
SD
Nonfamily firms
Mean
SD
Diff. in mean
t-value
14.04
4.03
2.25
3.75
3.75
26.08
45.21
18.94
12.49
4.97
14.85
19.02
19.02
43.95
49.82
39.23
13.78
5.14
2.36
5.14
3.42
31.69
41.11
16.27
13.25
7.07
15.18
22.10
18.21
46.58
49.26
36.95
0.26
−1.11***
−0.10
−1.39
0.33
−5.61*
4.10
2.68
(0.32)
(−2.90)
(−0.11)
(−1.07)
(0.28)
(−1.96)
(1.31)
(1.11)
100.99
1.11
5.81
39.95
1.56
167.16
2.57
15.73
30.37
14.44
72.86
1.70
6.25
42.59
1.14
155.01
5.27
15.25
26.91
4.37
28.13**
−0.59**
−0.44
−2.64
0.41
(2.43)
(−2.09)
(−0.41)
(−1.32)
(0.55)
Panel C: owner variables
Education (%)
Primary
9.94
29.95
10.06
30.12
−0.12
(−0.06)
Secondary
50.84
50.04
44.54
49.75
6.30**
(1.99)
Tertiary
38.84
48.78
44.75
49.78
−5.92*
(−1.90)
Female (%)
22.14
41.56
14.78
35.52
7.36***
(3.00)
Nationality (%)
Swedish
91.93
0.27
90.15
0.30
−0.02
(−0.99)
Nordic
1.88
13.58
2.14
14.49
−0.27
(−0.30)
Europe
3.19
17.59
4.28
20.27
−1.09
(−0.91)
Africa/Asia
2.44
15.44
2.36
15.18
0.08
(0.09)
Number of owners
1.38
0.52
1.51
0.63
−0.12***
(−3.32)
Owner age (years)
50.56
11.14
49.30
11.20
1.26
(1.77)
Notes: See Table I for definitions. There are 1,000 observations; 533 family firms and 467 nonfamily
firms. *,**,***Significant at 10, 5 and 1 percent level, respectively
Sources: Survey data, ORBIS, and own calculations
nonfamily firms). The share of female owners is significantly higher in family firms than
in nonfamily firms, at 22 and 15 percent, respectively. Nonfamily owners have higher
educational levels than family owners. Owners of family firms are significantly less likely
to have tertiary degrees and significantly more likely to have only secondary school
degrees. There are no differences in nationality between family and nonfamily firms.
4.2 Econometric model and results
We use a two-step procedure to test the first hypothesis that independence is a stronger
motive for enterprising for family owners than for nonfamily owners; first, we apply a
t-test. Table IV reports two different measures of independence based on respondents’
answers. The first measure is equal to one if a respondent answered “agree” or “totally
agree.” The second measure employs a stricter definition, taking a value of one only
if the respondent answered “totally agree.” In total, 92 percent of the family
firms answered “agree” or “totally agree,” and 73 percent answered “totally agree.”
The corresponding numbers for nonfamily firms are 85 and 65 percent, respectively.
The differences between groups – 7 and 8 percent, respectively – are statistically
significant at the 1 percent level.
Second, we estimate a linear probability model (LPM) according to the following
equation:
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PrðY t ¼ 1Þ ¼ aþ b familyt þ g1 X 1;t þ g2 X 2;t þ g3 X 3;t1 þ ϵ
Capital
constraint
paradox
(1)
49
where Y is a dummy variable that takes a value of one if independence is deemed
important, family is a dummy variable that takes a value of one for family firms, X1 and
X2 denote vectors of owner and firm characteristics, respectively, and X3 is a set of
financial control variables. β, γ1, γ2, and γ3 are the corresponding coefficient vectors, and
∈ is an error term. The null hypothesis is:
H0 : βW 0;
H1: β ⩽ 0; Y ¼ 1 if independence is deemed important and 0 otherwise.
Models 1 and 2 in Table V show the estimation results for the LPM, using the
stricter definition of independence, i.e., Y equals one if the respondent answered “totally
agree” to the statement that independence is a very important motive for enterprising.
Financial control variables are included in the second model to test for the robustness
of the estimated effect of being a family firm. We also estimate Equation (1) with
non-linear models without any significant difference in the estimated marginal effects,
which one would expect (Angrist and Pischke, 2008)[18]. Therefore, we present the
marginal effects from the LPM which have a more direct interpretation than their nonlinear counterparts.
Table V shows the marginal effects from the estimation of Equation (1) using a
LPM. The calculated marginal effects for family firms in the second column show that
family firm owners are 10.7 percent more likely to state that independence over the
firm’s decisions and activities are very important, a result that is statistically
significant. The estimated effect increases in magnitude when the financial control
variables are included. Thus, we do not reject H1.
To determine whether family firms and nonfamily firms place different premia on
control, respondents were presented with a hypothetical offer to sell shares that would
give an external investor major influence over the company (Figure 1). For each possible
answer (estimated market value +10 percent, estimated market value +10-20 percent, etc.),
we apply Equation (1). The null hypothesis is as follows:
H0: β o 0;
H1: β ⩾ 0; Y ¼ 1 if the respondent accepts the offered price and 0 otherwise (the
control variables are defined as in Equation (1)).
Variable
Family firms
Mean
SD
Nonfamily firms
Mean
SD
Diff. in mean
t-value
“Agree” or “totally agree” (%)
91.74
27.55
85.22
35.52
6.52***
(3.26)
“Totally agree” (%)
72.80
44.54
65.10
47.72
7.70***
(2.64)
Notes: The scale used was 1 ¼ totally disagree and 5 ¼ totally agree, with the table providing
percentages answering in the top two categories. There are 1,000 observations in total: 533 of family
firms and 467 of nonfamily firms. *,**,***Significant at 10, 5 and 1 percent level, respectively
Sources: Survey data and own calculations
Table IV.
t-test: independence
is very important
to me
JEPP
5,1
OLS
Variables
1
2
0.092***
0.107***
(0.035)
(0.030)
Firm age
0.001
0.002
(0.001)
(0.001)
50
Firm size
−0.003
−0.001
(0.003)
(0.003)
High and medium high-tech
-0.017
0.001
(0.105)
(0.113)
Medium low-tech
0.045
0.001
(0.079)
(0.085)
KIS
0.035
-0.019
(0.047)
(0.056)
Less-KIS
0.098**
0.074
(0.040)
(0.045)
Female
0.055
0.013
(0.040)
(0.048)
Secondary
0.174***
0.135***
(0.044)
(0.050)
Tertiary
0.149***
0.096*
(0.050)
(0.057)
Nordic
−0.040
−0.017
(0.108)
(0.126)
Europe
0.145*
0.211**
(0.080)
(0.103)
Africa/Asia
0.132
0.175
(0.100)
(0.152)
Number of owners
0.014
0.008
(0.025)
(0.030)
Owner age
0.008***
0.008***
(0.001)
(0.001)
Financial controls
No
Yes
Table V.
Notes: Standard errors are in parentheses. Models 1 and 2 are estimated by a linear probability model
Regression results,
dependent variable: (OLS). The regression analyses are based on 1,000 observations. *,**,***Significant at 10, 5 and 1
independence is very percent level, respectively
Sources: Survey data, ORBIS and own calculations
important to me
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Family firm
The analysis reveals two interesting findings[19]. First, owners of micro and small
firms are highly reluctant to sell to external investors. Approximately 30 percent of
owners are unwilling to sell their firms despite the hypothetical offer of market value
plus 70-100 percent. This supports previous research findings that independence and
control are important attributes of entrepreneurship. Second, and unexpectedly, there is
no statistically significant difference between the willingness of family firms and
nonfamily firms to sell shares. Thus, we reject H2[20].
Finally, the respondents were asked to state their preferences regarding how to finance
expansion. Again, the respondents are divided into two groups, family firms and nonfamily
firms, allowing for a two group mean comparison (t-test). Table VI summarizes the results.
The results show that company profits are the most preferred source of finance,
followed by loans from banks and others, and finally by equity of owners, which lends
support to the pecking-order theory[21].
Capital
constraint
paradox
0.80
Non-family firms
0.70
Family firms
0.60
51
0.50
0.40
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0.30
0.20
0.10
0.00
+ 10%
+ 10-20%
+ 20-40%
+ 40-70%
+ 70-100%
Estimated market value
Source: Survey data and own calculations
Figure 1.
The share of owners
who are willing to
sell shares of their
companies that
would give an
external investor a
major influence in
the company (%)
Regardless of whether your company plans to grow, with which of the following sources of finance
would you prefer to finance growth?
Family (%) Nonfamily (%) Difference (ppta)
t-value
Company profits
80.11
76.66
3.45
1.32
Loans from banks and others
45.97
41.11
4.86
1.54
Equity from the owners
38.65
30.19
8.46***
2.82
Loans from family
12.57
5.35
7.22***
4.06
Equity from new external investors
12.01
14.56
−2.56
−1.18
Equity from new family owners
10.13
5.78
4.35**
2.56
Notes: aPercentage points. The scale used was 1 ¼ not preferred, 5 ¼ most preferred, with the table
providing percentages answering in the top two categories, i.e, “preferred” and “most preferred.” The
respondents could give multiple answers. There are 1,000 observations, with 533 family firms and 467
nonfamily firms. *,**,***Significant at the 10, 5 and 1 percent level, respectively
Source: Survey data and own calculations
To test the first hypothesis concerning independence, the question about financing is
used to specify a dependent variable. We use Equation (1) to test whether there is a
higher/lower probability that family firms use a particular source of funding. We test
the hypothesis for the six sources of funding. The econometric analysis confirms the
t-tests; therefore, to save space, we do not show the results[22].
Family firms prefer to use company profits and bank loans as a financing source to
a greater extent than nonfamily firms. However, the differences in mean values are
statistically insignificant, and thus, we reject H3 and H8. Financing through new
external owners is less likely to be used by family firms than by nonfamily firms;
Table VI.
Mean comparison
tests for family
and nonfamily firms
(ranked after
family firms)
JEPP
5,1
however, this result is not statistically significant. Thus, we reject H6. However, family
firms more strongly prefer the use of equity of owners and loans from family than
nonfamily firms. Because these findings are significant, we do not reject H4 and H7.
Family firms are also more willing than nonfamily firms to engage new family owners
in the financing of an expansion. We therefore do not reject H5. Table VII summarizes
the hypothesis tests.
52
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5. Concluding discussion
The present study aims to further our understanding of financing and investment
decisions of micro and small firms, particularly family firms. Our central question is:
does the supply or demand of external capital and/or access to internal funds constrain
firm growth? The study is based on 1,000 phone interviews with controlling owners.
The survey included questions regarding attitudes toward independence and various
types of internal and external funding. The idea underlying the study is that external
financing may impose a tradeoff between independence and the exploitation of
business opportunities, a tradeoff that may be particularly relevant for family firms,
characterized by concentrated ownership, the mixing of family and business life, and
the incorporation of non-financial goals into decision making. Our findings bear on
other research fields – for instance, small business economics, finance, and corporate
governance – that have shown increasing interest in family business.
The analysis shows that for both family and nonfamily owners, independence is a
primary motive for enterprising, although it is of significantly greater importance for
family owners than for nonfamily owners. Both family and nonfamily firm owners also
highly value control, measured as the price they would require for shares that would
give an external investor major influence in the company. In line with the pecking-order
theory, a majority of firms, both family and nonfamily, prefer to use company profits,
bank loans, and own equity to finance growth, whereas few would consider using
equity financing of new investors. There are statistically significant differences
between the two types of firms: family firms more strongly prefer own equity, loans
from family, and equity of new family owners than do nonfamily firms.
The present study sheds light on the current policy debate regarding the effects of
capital constraints on small-firm growth. Our findings suggest that policy initiatives
Table VII.
Summary of the
hypotheses testing
H1: Independence is a stronger motive for enterprising for family owners than for
nonfamily owners
H2: The control premium is higher for family firms than for nonfamily firms
H3: Family firms are more prone than nonfamily firms to use company profits to
finance growth
H4: Family firms are more prone than nonfamily firms to use equity from the owners to
finance growth
H5: Family firms are more prone than nonfamily firms to use equity from new family
owners to finance growth
H6: Family firms are more reluctant than nonfamily firms to use equity from new external
investors to finance growth
H7: Family firms are more prone than nonfamily firms to use loans from family to
finance growth
H8: Family firms are more reluctant than nonfamily firms to use loans from banks and
others to finance growth
Source: Own table
Not
rejected
Rejected
Rejected
Not
rejected
Not
rejected
Rejected
Not
rejected
Rejected
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directed toward increasing the supply of external capital are largely ineffective because
they transfer control to external investors and therefore conflict with informal
institutional independence as an entrepreneurial norm. Instead, our results indicate a
possible capital constraint paradox: there may exist a surplus of external capital even
as firms – family firms more so than nonfamily firms – forgo growth opportunities due
to a lack of internally generated funds and own equity. A more effective policy would
then be to increase the supply of own equity and internal funds – preferred sources of
funding for investment and growth – by reducing capital income taxes. This would
foster a better alignment between formal and informal institutions. Additionally, the
capital tax that shields the price of shares that a new investor is prepared to pay and
the amount that the entrepreneur receives should be reduced. Given that the
entrepreneur can be compensated adequately for lost control over the corporation,
welfare-generating transactions can occur. Indeed, small losses of tax revenues could
finance substantial tax cuts, as capital taxes contribute little to total tax revenues,
especially in high-tax countries such as Sweden.
Notes
1. Throughout this paper, we denote capital from the family, including profits from the family
firm, new equity from the family and loans from the family, as “internal capital.” Capital
invested by external investors, i.e., investors outside the family, will be referred to as
“external capital.”
2. In line with Cressy (1995) and Cressy and Olofsson (1997), we refer to control as the right to
make decisions about the firm without the involvement of external stakeholders and
lenders. Similarly, we refer to control aversion to describe aversion to outside lenders and to
equity stake holding by external investors. The term “control” is part of “independence,”
which can loosely be referred to as “being one’s own boss” with respect to customers,
external investors, suppliers, and others (Davidsson, 1989).
3. We use the definition of family firms proposed by the European Commission (2009), which
includes both control of the majority of decision-making rights and family involvement in
firm governance (see Section 3 for further discussion). Swedish register data identify family
ownership but not family governance (Bjuggren et al., 2011).
4. See Dyck and Zingales (2004a, b) and Nenova (2003) for cross-country estimations of the
control premium and private benefits of control in large listed firms. See Benavides-Velasco
et al. (2013), Bird et al. (2002), Casillas and Acedo (2007), Dyer and Sánchez (1998) and Zahra
and Sharma (2004) for surveys and discussions of research on family ownership and control.
5. Their analysis was based on a questionnaire mailed to 5,000 business owners; the valid
response rate was a bit less than one-third. They found, among other things, that family
control has a significant impact on capital structure decisions, for instance that external
equity is less likely to be used by family firms who prefer to retain control.
6. Based on a mail survey, they found that family norms and attitudes had an effect on
behavioral intention and the use of different sources of finance. For instance, perceived
behavioral control, was shown to negatively affect behavioral intentions to use external
equity and was positively related to the use of internal funds.
7. See, for instance, Mathews et al. (2012) who argue that family business and nascent
entrepreneurship are intertwined.
8. Although entrepreneurial firms probably have been, or remain, family firms, most family
firms are probably not entrepreneurial (Cucculelli, 2012).
Capital
constraint
paradox
53
JEPP
5,1
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54
9. Pecking-order theory, in its simplest form, posits that because of transaction costs, firms
will most prefer to finance investment with internal funds, followed by debt, and finally by
new equity (Donaldson, 1961; Myers and Majluf, 1984). Empirical studies suggest that the
theory needs to be modified to a larger extent take into account the special circumstances of
small- and medium-sized enterprises (Fama and French 2002). Zoppa and McMahon (2002),
for instance, study the financial structure of 871 manufacturing small and medium-sized
enterprises based on data from the Australian federal government’s Business Longitudinal
Survey and argue that the broad categories of internal funds, debt and new equity should be
divided into more narrow categories, e.g., new equity from family and new equity from yet
uninvolved partners, to reveal further insights about the preferences of various kinds of
SMEs toward different sources of finance.
10. As Penrose (1959, p. 31) already concluded: “In many industries and areas there are a
considerable number of firms which have been operating successfully for several decades under
competent and even imaginative management, but have refrained from taking full advantage of
opportunities for expansion. Many of these are family firms whose owners have been content with
a comfortable profit and have been unwilling to exert themselves to make more money or to raise
capital through procedures that would have reduced their control over their firms” (our italics).
11. According to the pecking-order theory of capital, firms prefer internally generated funds to
debt and share issuance when financing investments because asymmetric information and
other transaction costs raise the costs of external capital (Donaldson, 1961; Myers, 1984;
Myers and Majluf, 1984).
12. See Garcia-Castroa and Aguilera (2014) for a recent overview of the literature on family
firms and how they are defined.
13. “Listed companies meet the definition of family enterprise if the person who established or
acquired the firm (share capital) or their families or descendants possess 25 percent of the
decision-making rights mandated by their share capital. The requirement of family
involvement, however, makes it impossible to identify family firms in the official statistics,
since this information is not collected.” (European Commission, 2009, p. 9)
14. In total, 1,000 interviews were required to obtain precise estimates, i.e., the response rate
was 25 percent (Koropp et al., 2014, report 16 percent). For ethical reasons, no information
was saved about firms that did not wish to participate in the survey. Comparing the
variables observable in register data (see main text below for definitions) to the total
population of Swedish private limited liability firms with 1-49 employees, we only find
minor differences with regard to gearing ratio, solvency ratio, and the share of firms in
knowledge-intensive services. The differences do not influence our main conclusions.
No differences exist with regard to firm age, firm size, EBIT, operating revenues, profit
margin, total assets, share of firms in less knowledge-intensive services, high and medium
high-tech, medium low-tech, low-tech, or other industries. There is no indication that the
variables in our sample that are not identified in register data (family ownership, number
of owners, education, gender, nationality, and owner age) should differ from the
population. We therefore judge that we have a representative sample and that our
results are generalizable to the total population of Swedish private limited liability firms
with 1-49 employees.
15. The control premium is an estimate value of private benefits of control. Dyck and Zingales
(2004b) measure it as the difference in share price of a control block and the market share
price the day following the announcement of the block trade.
16. A similar question regarding past financing decisions was also included, but the results
were similar, and we therefore do not comment upon them.
17. The correlation table is available from the authors upon request.
18. We have also checked the robustness for other model specifications, estimators, etc.
The results are robust and are available from the authors upon request.
19. As with the first hypothesis, we conducted a number of robustness checks, finding that the
results are robust. To save space, we do not report the results here. They are available from
the authors upon request.
20. One explanation for this result could be that both family and nonfamily owners highly value
control and that the scale should have been set even higher to detect potential differences.
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21. The internal preference ordering among sources of capital was tested using a t-test.
The results are available from the authors upon request.
22. The null hypothesis is formulated as H0: bW0, and the alternative hypothesis is formulated
as H1: b ⩽ 0. In the case of new equity from external investors and loans from banks and
others, the hypothesis is H0: β ⩽ 0. In line with previous analysis, we conducted a set of
robustness checks, finding that the results are robust. The results are available from the
authors upon request.
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(The Appendix follows overleaf.)
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constraint
paradox
59
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JEPP
5,1
60
Appendix 1. Telephone survey (conducted in Swedish)
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Appendix 2
Capital
constraint
paradox
Manufacturing industries
Knowledge-based services
High technology
21 manufacture of basic pharmaceutical products
and pharmaceutical preparations
26 manufacture of computer, electronic, and
optical products
Knowledge-intensive services (KIS)
50-51 water transport, air transport
Medium high technology
20 manufacture of chemicals and chemical
products
61
58-63 publishing activities, motion picture, video
and television program production, sound
recording and music publishing activities,
programming and broadcasting activities,
telecommunications, computer programming,
consultancy and related activities, information
service activities (section J)
64-66 financial and insurance activities (section K)
69-75 legal and accounting activities, activities of
head offices, management consultancy activities,
architectural and engineering activities; technical
testing and analysis, scientific research and
development, advertising and market research,
other professional, scientific and technical
activities, veterinary activities (section M)
78 employment activities
27-30 manufacture of electrical equipment,
manufacture of machinery and equipment n.e.c.,
manufacture of motor vehicles, trailers and semitrailers, manufacture of other transport equipment
Medium low technology
80 security and investigation activities
19 manufacture of coke and refined petroleum
84-93 public administration and defense,
products
compulsory social security (section O), education
(section P), human health and social work
activities (section Q), arts, entertainment and
recreation (section R)
22-25 manufacture of rubber and plastic products, Less knowledge-intensive services
manufacture of other non-metallic mineral
products, manufacture of basic metals,
manufacture of fabricated metal products, except
machinery and equipment
33 repair and installation of machinery and
45-47 wholesale and retail trade, repair of motor
equipment
vehicles and motorcycles (section G)
33 repair and installation of machinery and
49 land transportation and transport via pipelines
equipment
Low technology
52-53 warehousing and support activities for
transportation, postal, and courier activities
10-18 manufacture of food products, beverages, 55-56 accommodation and food service activities
tobacco products textiles, wearing apparel, leather (section I)
and related products, wood and products of wood,
paper and paper products, printing and
reproduction of recorded media
68 real estate activities (section L)
31-32 manufacture of furniture, other
77 rental and leasing activities
manufacturing
(continued )
Table AI.
Industry
classification
according to
Eurostat 2014
JEPP
5,1
Manufacturing industries
79 travel agency, tour operator reservation service,
and related activities
81 services to buildings and landscape activities
82 office administrative, office support, and other
business support activities
94-96 activities of membership organizations,
repair of computers and personal and household
goods, other personal service activities (section S)
97-99 activities of households as employers of
domestic personnel, undifferentiated goods and
services-producing activities of private
households for own use (section T), activities
of extraterritorial organizations and bodies
(section U)
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62
Table AI.
Knowledge-based services
Source: Eurostat (2014)
Corresponding author
Johanna Palmberg can be contacted at: [email protected]
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