The Increase of Capital Cost
and Firm Development Restriction
Master Thesis Finance
Supervisor: Prof. P. de Goeij
Co-assessor: Prof. C.A.R. Schneider
Author: Babette Vugs – U1275414, ANR: 399214
Abstract
Governments focus on economic development, which requires firm development within their
countries. Firm development is measured as firm size and –productivity difference between currentand previous year. The level of capital of cost for both debt and equity can create obstacles for this
firm development, while external capital is essential for firms to benefit from growth opportunities
through investment. In order to draw economically relevant conclusions, interaction terms between
firm dependency and -cost for both debt and equity are estimated. These interaction terms make it
possible to conclude whether dependent firms experience more restrictions to firm development when
the cost of capital increases than less dependent firms encounter. The results show a negative relation
between the interaction terms of equity- and debt and firm size. This suggests that firm size
development of external capital dependent firms is suppressed more when the cost of debt and equity
increases compared to less dependent firms. However, in order to draw general conclusions about firm
development, this trend should also be found for firm productivity. Furthermore, the results are not the
same across different market capitalization categories (i.e. small-, mid and large market cap firms) and
between regions due to exposure differences.
Keywords: firm development, cost of capital, external capital dependency
I.
Introduction
The phenomenon that economies of some countries grow faster than others has been a popular
research subject for decades. A stimulating business environment in terms of innovation, creativity
and human capital development plays a large role in answering this question (Henisz, 2000). The most
important determinant of the business environment, government regulation, has a significant influence
The Increase of Capital Cost and Firm Development Restriction on economic development (Levine, 1998). Economic growth reforms the legal environment, which
leads to financial development. This in turn affects long-term firm development (Levine, 1999).
Indicating that in order for economies to grow, firm development is necessary (Levine, 1999).
Established firms rely more on external capital markets than less developed firms (Goldsmith,
1969). These external funds are essential for companies to react upon opportunities of growth created
by a fast changing economic environment, while it facilitates firms to finance their investments that
could not be financed internally. Furthermore, these external funds come at a cost, generally called the
cost of capital, which is defined as ‘the expected rate of return that market participants require in order
to attract funds to a particular investment’ (Pratt and Grabowski, 2008). The cost of capital is also the
factor used in the valuation process of a firm. Future cash flows are discounted by this rate and added
up to come at the market value of the firm. The cost of capital has in turn a direct impact on the value
of a business and in turn the overall economy (We and Dhanraj, 2007). In order to maximize firm
value, the cost of capital should be minimalized (Messbacher, 2004), which requires a perfect
distribution between debt and equity (Chowdhury and Chowdhury, 2010).
The rate of return is determined by the market, based on a risk analysis, which consists of two
main components; the risk-free rate and equity premium. More risky investments require a higher
return than low risk investments (Ghysels et al., 2005). In time of economic downturns and after
negative news announcements, the wave of stock market pessimism creates a higher demand of risk
premiums (Bondt and Thaler, 1985; Mitchell and Mulherin, 1994). This creates an increase in the
required return and equivalent to the cost of capital.
The ease of borrowing money, dependent on the associated costs, influences the amount invested
by the firm, which is necessary for firm development (Beck and Levine, 2000). Investment
possibilities increase when the cost of capital of a firm decreases (Henry, 2003; Gilchrist and
Zakrajsek, 2007). Firm development based on new investments is created when investment returns
exceed the cost of investment capital (Bernardo et al., 2007). This shows the importance of the cost of
capital within economic- and firm developments. This thesis fills the gap in existing literature about
the direct relation between the cost of capital and firm development.
1.1 Short overview
Firm development, or stagnation, is measured in twofold, based on firm size and –productivity.
Combined they give a well-established overview of development effects. In order to draw an
economic relevant conclusion, the dependency on respectively debt- and equity capital is included in
the model, while the singular variables face problems concerning reverse causality. Firms more
dependent on external capital experience arguably more negative effects on firm development due to
higher cost of capital, compared to less dependent firms. This interaction term makes it possible to
look at the moderator effect, which tackles the problem of reverse causality. The required
2 The Increase of Capital Cost and Firm Development Restriction dependencies are based on the ratios used by Rajan and Zingales (1996). Cost of equity (i.e. the
required rate of return for equity capital) is based on the dividend growth model and the cost of debt is
equal to the interest paid per dollar of the firm’s net debt. Data required to test these hypotheses is
obtained from the Worldscope Global Database.
The four examined hypotheses are the following:
(1) Firms experience larger restriction to firm development when the cost of debt increases.
(2) Firms experience larger restriction to firm development when the cost of equity increases.
(3) Firms more dependent on external finance experience a relatively larger restriction to firm
development when the cost of debt increases relative to firms that are less dependent on external
capital.
(4) Firms more dependent on external equity finance experience a relatively larger restriction to firm
development when the cost of equity increases relative to firms that are less dependent on external
equity capital.
The main results show a negative significant relation between the interaction term of cost- and
dependency on external capital and firm size in terms of employment. Cost of debt and –equity show a
coefficient of -0,003 and -0,005 respectively. Indicating that dependent firms experience a higher
restriction to firm development in terms of employment compared to less dependent firms. This
relation is not significant for firm productivity, which means that no clear conclusion about overall
firm development can be drawn. Furthermore, it should be mentioned that the impact differs across US
regions, due to the exposure to industries. When splitting the sample according to market
capitalization categories (i.e. small-, mid- and large market cap firms) it becomes clear that the results
are not the same across the three categories. This indicates that variance in firm development is
sensitive to the firm’s market cap, which means that conclusions on firm development should not be
made for all firms in general. Lastly, the regressions are also estimated for established firm growth.
These results show that the cost- and dependency of external capital does not have a significant
influence on established firm growth. This indicates that the increase of external capital cost
influences future development of economies.
Section II will discuss the theoretical background between the cost of capital and firm
development. Section III will describe the measurement method used to examine the hypotheses and
section IV defines the required data for the model. The results will be interpreted and tested for
robustness in section V and section VI concludes and discusses the limitations of this thesis.
3 The Increase of Capital Cost and Firm Development Restriction II.
Literature Review
There are many articles written about economic growth and determinants of firm development.
However, existing literature does not cover the direct connection between overall firm development
and cost of capital. In order to give a theoretical background, several relations discussed in literature
are summarized in this section. In section 2.1, the relation between economic growth and firm
development is discussed. Thereafter, the connection with the overall capital markets is made. Section
2.2 examines factors affecting the firms’ cost of capital. Lastly, the relation between cost of capital
and firm’s development is discussed, which results in the contribution and hypothesis of this thesis.
2.1 Economic Growth, Firm Development and Capital Markets
This section discusses determinants of economic growth and firm development. Thereafter, these two
developments are linked to capital markets. These relations show the economic relevance of firm
development.
2.1.1
Economic Growth
Economic growth is a broad definition covering economic developments in several areas, such as the
income-, prosperity-, human capital-, life expectancy- and technology level (Barro, 1996). One of the
main goals of economic growth is the improvement of living standards within countries. This can be
improved through employment channels and in turn consumption possibilities. There are two views on
approaching economic growth; the assimilation- and accumulation view. The first view approaches
economic growth through economic specialization. A healthy business environment stimulates firms
to expand their technical knowhow and specialize in more productive sectors, which leads to an
efficient allocation of resources across the economy. This theory in turn creates long-term economic
growth (Nelson and Pack, 1999). The effect of this reallocation from low productive to highproductive sectors can be seen in the ‘Asian Miracle’, where Korea, Taiwan, Singapore and Hong
Kong have become modern developed economies in less than forty years. Their specialization into
capital-intensive sectors reallocated labour into a more productive sector than for example the
agricultural sector, which increased the countries’ overall productivity level. The second approach is
the accumulation view by Solow (1956). He states that improvement in the Total Factor Productivity
(TFP), which is the amount of output that cannot be explained by the input used for production
(Comin, 2006), cause long-term income per capita growth. TFP is improved by efficient accumulation
of physical- and human capital. Chanda and Dalgaard (2003) and Isaksson (2007) state that the most
important determinants of these improvements are national institutions, while institutions affect the
composition of the economy between agriculture and non-agriculture. Welfare improvements caused
by aggregate TFP difference within a country do not occur when markets are characterised by
4 The Increase of Capital Cost and Firm Development Restriction imperfect market conditions (i.e. information asymmetries, taxation- and regulation differences
between sectors). Hsieh and Klenow (2009) and Inklaar et al. (2015) emphasise the fact that TFP will
be negatively affected in the case of resource misallocation. Hskieh and Klenow (2009) state that
when firms become more productive and grow, they need more inputs to facilitate this growth. In the
case of misallocation, in their article caused by policy distortions, this unavailable growth of inputs
causes firms to stay small and to invest less than necessary to sustain this firm growth.
To summarize, economic growth can be stimulated with effective resource allocation across industries
and TFP improvements, which should be facilitated by government policy.
2.1.2 Firm Development
Economic growth is closely related to firm development (Levine, 1999), which makes development of
firms a key objective for policy makers in market economies. The objectives of growth differ between
individual businesses and policy makers. Individual businesses are more interested in the increase of
sustainable sales while policy makers are more interested in job creation. This requires a diverse
measurement method to estimate accomplished firm development. The first firm characteristic to
estimate firm development is size. Firm size in absolute terms is the most used measure of firm
development, which can be expressed in employment, market capitalization and/or sales (Coad and
Holzl, 2010). The second characteristic, firm productivity, is used to estimate relative firm
development and represents more efficient use of inputs. A third measure is firm investment, which
indicates the degree in which firms take advantage of evolving growth opportunities (Lan et al., 1995).
These three firm characteristics are closely related and can therefore not be seen separately. Firm size
and -productivity, in both absolute terms and TFP, are positively related (Leung et al., 2008).
Furthermore, in the long run investment in positive NPV projects results in an increase in productivity
and in turn in firm size (Lang et al., 1996). This can also be argued the other way around; more
established and productive firms are often larger and have therefore the ability to invest more.
2.1.3 Capital Markets
Economic developments within emerging markets and the wave of globalization facilitated a large and
integrated capital market for international investors (Demirquc-Kunt and Levine, 1996). Benefits from
globally diversified portfolios can be categorised in two broad types; security specific risks and market
specific risks (Frontier Investment Management, 2008). Indicating that macro-economic risks due to
laws and regulation can be reduced by geographic diversification.
There are three theories in existing literature about the connection between financial
development and economic growth, based on the position of the bank-based view, market-based view
and financial services view (Arestis et al., 2005). These views are based on the fundamental economic
differences between economies. The bank-based view (Germany and Japan) assumes that banks
5 The Increase of Capital Cost and Firm Development Restriction improve capital allocation and investment efficiency through the acquiring of firm information.
Furthermore, they exploit economies of scale by mobilizing capital. The market-based view (UK and
US) is the contrary to the first view and emphasises the importance of capital markets by stimulating
individual research by firms and easing regulation regarding mergers and takeovers. This view
stimulates firms and banks to become more efficient due to market pressure (Arestis et al., 2005). The
third view, is in line with both previously mentioned views. However, it emphasises the importance of
an environment that stimulates efficient and established financial services. This indicates the
importance of both well functioning banks and markets (i.e. components of financial services), rather
than one component. It is important to keep these economic-specific differences in mind, when
interpreting cross-country conclusions about economic development.
Goldsmith (1969) investigated the relation between economic development and the firm’s
financial structure. He concludes that less developed economies mainly focus on self-financed capital
and more advanced economies develop into bank-intermediated debt and finally give emergence to
equity markets to raise external investment funds. Advanced economies in turn rely more on equity
markets and less on commercial banks and financial institutions (Demirque-Kunt and Levine, 1996).
Walter Bagehot (1873) argued that the corporate financial system has had a strong influence on the
industrialization in Great Britain. The mobilization of capital is an important determinant of economic
growth. The financial market facilitates this resource distribution in an uncertain environment (Merton
and Bodie, 1995). Information asymmetry and transaction costs have created the need for financial
markets. King and Levine (1993) have investigated the overall connection between the financial
system and economic growth. They find, based on a cross-country comparison between 1960 and
1989, a positive relation between financial development and the average rate of per capita GDP
growth, physical capital accumulation and economic efficiency. They define ‘financial development’
as the market size of financial intermediaries and the degree of domestic asset distribution (i.e. credit
allocated to private sector). This positive correlation remains after the inclusion of industry- and
country fixed effects for both developed and developing countries. This conclusion is also supported
by Levine (1997) where he states that well-functioning financial regulation is positively linked to
economic growth.
Most studies in existing literature have focussed on the ease of acquiring external finance for
individual firms. When firms are able to finance their investments with external debt- or equity
finance more easily, the economy grows through firm development in terms of innovation, efficiency
and output (Beck and Levine, 2000). Rajan and Zingales (1998) show that firms within industries that
are more dependent on external finance experience more growth when located in financial-developed
countries. They furthermore state that financial development (i.e. rise of external finance relative to
GDP) reduces the costs of external finance to firms. This is in line with Khan (2001), who argues that
6 The Increase of Capital Cost and Firm Development Restriction firms with access to investment loan possibilities experience more growth due to a higher return to
production. This higher return is caused by lower financing cost due to financial development.
To summarize, economic growth and firm development are positively related. Firm development can
be measured through three firm characteristics; firm size, -productivity and –investment. These
characteristics are closely related with each other and combined give a good overview of established
firm development. Financial development, which connects economic growth and firm development,
has created an international capital market where investors search for the optimal globally diversified
portfolio. More developed and established firms depend more on external equity capital. Providers of
this capital require a return generally called the cost of capital, which is discussed in more detail in the
next section.
2.2 Firm Cost of Capital
External capital made available by equity markets and commercial banks come at a cost. This cost of
capital is influenced by many firm specific characteristics. The appropriate cost of capital is mainly
explained by the perceived risk of the externally financed investment, while risk is determined by
several factors.
A problem when analysing investment risk is the existence of asymmetric information
between investors and institutions. The costs of adverse selection (i.e. investors with better private
information about the quality of the investment are able to make a better judgement than investors
with less inside information) are higher in equity issues compared to debt issues (Myers and Majluf,
1984). This is one of the reasons why managers apply the pecking order theory. Managers seek
sources to finance their investments based on a cost hierarchy: first internal funds are preferred (i.e.
this is the cheapest form of capital for firms), then debt issue and finally equity issuance. Equity is the
least favourable source of finance, while it is the most expensive sort of capital. Due to these large
costs, an equity increase creates a wealth delusion for existing shareholders, which creates discontent
by the original shareholders. The adverse selection problem is translated into the bid-ask spread
(Amihud and Meldelson, 1986). Securities with larger bid-ask spreads create larger transaction costs,
which in turn increases the cost of equity capital. Francis et al. (2005), Li and Yang (2012) and
Botosan (1997) find that a higher level of voluntary disclosure (i.e. decrease the level of private
information), often present by firms that experience a high dependency on external finance, lowers the
cost of both equity and debt.
Investment risk can be estimated based on several factors; firm size, firm age, industry and macroeconomic characteristics. These factors are discussed below.
7 The Increase of Capital Cost and Firm Development Restriction The first factor is firm size. Larger firms are more capable of internally finance their
investments, while smaller firms are more dependent on external finance (Audretsch and Elston,
2000). Furthermore, smaller sized firms are more risky, while they can bear external shocks less easily
then large and more diversified firms. Fazzari et al. (1988) provide empirical evidence that smaller
sized firms experience more difficulty in obtaining external finance in cases of macroeconomic
downturns like a financial crisis. However, it is also shown in financial literature that diversification
should not matter in determining the cost of capital, while this idiosyncratic risk can be diversified
way by investors themselves. They can diversify on a firm level (invest in an individual firm that
operates within different product- or geographical markets) or within their asset portfolio (invest in
multiple firms).
The second factor affecting investment risk is firm age. Younger firms have to cope with
shortages in managerial knowledge and financial management abilities (Thornhill and Amit, 2003).
This makes it harder for younger firms to obtain sufficient resources in terms of capital. Many early
stage firms go bankrupt when their initial resources and assets are depleted. These relatively younger
firms go bankrupt compared to more established, older firms. This is reflected in the cost of capital,
while a higher risk of default is translated into a higher risk premium for equity holders. Fortin and
Pittman (2004) have also found that younger firms also experience more information asymmetry
problems, while they are not yet familiar with the market and do not have an established reputation.
The third factor affecting the cost of capital through the amount of risk is the industry in which the
firm operates (Gebhardt et al., 2000). The risk premium is lower for firms in for instance the real
estate and financial services industries, compared to firms operating in the sports and leisure-,
electronic technology- and commercial lending industries. Furthermore, the risk premium is also
positively related with ‘higher book-to-market ratios, higher forecasted growth rates and lower
dispersion in analyst forecasts’ (Gebhardt et al., 2001).
Macro-economic characteristics are the fourth factor affecting the amount of investment risk.
Country specific characteristics, such as regulation, indirectly affect the cost of capital. More
established legislation about investor protection decreases the level of risk and in turn the cost of
capital. Also general macro economic conditions determine the cost of capital level (Mirea et al.,
2013). Demand and supply of capital on the capital markets partly explains the rate of return of riskfree investments, which is a component of the cost of equity. When demand of money increases more
than supply, the required rate of return for equity capital increases. This rate lowers when the market is
relatively stable.
To summarize, investment risk is difficult to estimate and the factors affecting the amount of risk are
interrelated with one another.
8 The Increase of Capital Cost and Firm Development Restriction 2.3 Firm Development and Cost of Capital
There is no stream in existing literature about the direct connection between firm development and the
cost of capital within all kind of industries in the US. Alberts and Archer (1973) have examined the
effect of firm size on equity capital. They conclude that, for 540 US companies, the return on equity
decreases when firm size increases. This implies reverse causality when examining the single variable
of cost of capital in this thesis. However, only the firm characteristic size does not represent overall
firm development and it does not include for both cost of debt and -equity. Furthermore, it only
concludes based on US companies.
The indirect connection, representing the link between cost of capital and the amount of
investment and investment possibilities is examined in existing literature. The ease of borrowing
money, dependent on the amount of cost, influences the amount invested by the firm, which is
necessary for firm development (Beck and Levine, 2000). Firms can react on growth opportunities
created by a fast changing economic environment based on these investment possibilities. Firm
development based on these new investments is created when investment returns exceed the cost of
investment capital (Bernardo et al., 2007).
For a sample of US manufacturing firms, Hall (1992) shows a strong correlation between the
increase of debt and the decrease of investment. This can be explained through an increase in the cost
of capital, because firm’s internal funds are not available (i.e. a higher debt level is present). This
increase in cost of capital can reduce further investment possibilities. Hall (1992) furthermore
describes the positive relation between firm profits, the availability of funds and the increase of
investments. He also points out the problem of reverse causality in this relation. It can also be argued
that the increase of investment leads to profit improvements, due to for example process-, efficiencyor product improvements. Hall (1992) argues the opposite by Modigliani and Miller (1958). The
Modigliani-Miller investment theorem states that investment levels should be indifferent of the firm’s
capital structure. Furthermore, they state that the cost of investment should have the same rate of
return for both internal- and external capital. However, it should be noted that they made many
assumptions regarding the simplicity of the market. They re-examined their theorem in Modigliani and
Miller (1963) where they included market imperfections such as information asymmetry and taxation.
These inclusions increased the cost of external capital relative to internal capital and also affected the
optimal financial structure of a firm. This inclusion rejects the investment indifference statement.
Gilchrist and Zakrajsek (2007) have examined the relation between investment and the cost of
capital and conclude than a percentage point increase in the cost of capital paid by the firm reduces the
investment rate of 0,5% to 75 basis points. They even find a 1% reduction in capital stock after the 1%
increase in the cost of capital. Investment possibilities are needed to created sustainable growth in the
modern turbulent economy. Firms have to adapt quickly to environmental changes and steps made by
their competition. However, it can also be argued that more established larger firms experience lower
9 The Increase of Capital Cost and Firm Development Restriction cost of capital. For this reason a moderator effect should be examined through the inclusion of an
interaction term. Dependency plays an important role in explaining the effect of the cost of capital.
When the cost of capital is an important determinant of firm development, less dependent firms should
experience a smaller impact due to an increase in the cost of capital. Taking this into account, Baker et
al. (2002) find that equity dependent firms have three times higher sensitivity between investment and
stock prices than low equity dependent firms. In other words, low stock prices increase the effective
cost of equity capital and therefore investment is restricted within equity dependent firms.
The cost of debt and equity can be combined within the Weighted Average Cost of Capital
(WACC), which is weighted average of the after tax cost of debt and the required return to equity
(Fernandez, 2011). Frank and Shen (2012; 2013) have examined the effect of WACC on the incentive
to investment, which is measured using Tobin’s Q (‘the ratio of the market value of a firm’s assets to
the replacement value of these asstes’; Wolfe and Sauaia, 2003). When Tobin’s Q is above 1, there is
an incentive to invest while profits would exceed the investment costs. Frank and Shen (2012; 2013)
find a negative relation between the WACC and the amount of investment. They conclude that firms,
which are charged higher cost of debt, invest less compared to firms experiencing lower cost of debt.
The conclusions for the cost of equity are highly sensitive to the measurement method used. Indicating
no clear conclusion for the cost of equity.
In conclusion, the direct relation between the cost of capital (debt and equity) and overall firm
development is, to the best of my knowledge, not yet examined in existing literature. Furthermore,
articles that cover part of this relation are concentrated on specific industries (i.e. mainly focussed on
the manufacturing sector). This results in four hypotheses examined of this thesis.
(1) Firms experience larger restriction to firm development when the cost of debt increases.
(2) Firms experience larger restriction to firm development when the cost of equity increases.
(3) Firms more dependent on external finance experience a relatively larger restriction to firm
development when the cost of debt increases relative to firms that are less dependent external capital.
(4) Firms more dependent on external equity finance experience a relatively larger restriction to firm
development when the cost of equity increases relative to firms that are less dependent external equity
capital.
The first two hypotheses are singular and are arguably subject to reverse causality. For this reason
hypothesis 3 and 4 consist of an interaction term with firm dependency on external capital, this solves
the problem regarding reverse causality. The methodology used is discussed in the next section.
10 The Increase of Capital Cost and Firm Development Restriction III.
Methodology
3.1 Model description
In order to effectively measure the firm development, two variables are used: firm size and firm
productivity. Firm investment, which was the third characteristic mentioned in the literature review, is
excluded as a dependent variable in this thesis, because this characteristic focuses on tools to achieve
firm development instead of established development. Furthermore, the positive relation between the
cost of capital and firm investment is already examined in existing literature. The combination of firm
size and -productivity is important, because combined they capture the most important firm
characteristics for firm development in absolute and relative terms (Beck and Levine, 2000). A
combination is needed due to their shortcomings and because they are subject to many other factors
than the cost of capital. The first characteristic, firm size, can be calculated with the use of
employment and profit (Dang et al., 2015). Profit is highly dependent on the definition used and is
therefore not used in this thesis (i.e. improvements can be caused by margin- or price adjustments,
which is not related with firm development). Employment is highly dependent on the type of products
made, while labor intensity differs among industries. The beneficial factor of this measurement is that
it is not expressed in monetary terms and therefore does not need to be corrected for currency
differences or inflation, which makes cross-country comparison possible. In finance the firms’ market
capitalization is often used to measure size, however, this measure does not change within a relative
small timespan. The second characteristic, firm productivity, is calculated as sales per employee. This
indicator gives a perspective of a firm’s development in terms of relative performance.
Combined this indicates positive development; a productivity increase (higher sales per
employee) and size increases (the number of employees) represents overall firm development.
Development is estimated based on a two-year difference in these firm characteristics:
Δ 𝐹𝑖𝑟𝑚 𝐷𝑒𝑣𝑒𝑙𝑜𝑝𝑚𝑒𝑛𝑡!,! = 𝐹𝑖𝑟𝑚 𝑠𝑖𝑧𝑒!,!!! − 𝐹𝑖𝑟𝑚 𝑠𝑖𝑧𝑒!,!
Δ 𝐹𝑖𝑟𝑚 𝐷𝑒𝑣𝑒𝑙𝑜𝑝𝑚𝑒𝑛𝑡!,! = 𝐹𝑖𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦!,!!! − 𝐹𝑖𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦!,!
These firm characteristics are measured for firm i, in industry j, located within state s in year t.
As stated in the contribution to existing literature it is important to distinguish between firms that are
more or less dependent on the specific external capital. This inclusion results in a more specific policy
recommendation with respect to firm development. An interaction term between the dependency on
debt- and equity capital (discussed into more detail in section 3.2) and the associated costs also tries to
tackle the problem of reverse causality, while this interaction term makes it possible to examine the
moderation effect (in contrary to the simple effect) (Kenny, 2015; Berger, 2015). The problem of
reverse causality contains that it can be argued that larger and more established firms provide a more
secure investment opportunity to investors, which results in lower costs of capital for developed firms.
11 The Increase of Capital Cost and Firm Development Restriction When capital dependencies are combined with the cost of capital, regression coefficients for the
interaction effects can be calculated. When beta of this interaction term is negative, the hypothesis that
more dependent firms experience a larger restriction to firm development when the cost of capital
increases compared to firms less dependent on external capital is supported. In order to include US
region-, industry- and year specific fixed effects on firm size and –productivity, dummy variables are
included.
This results in the following model:
(1) Δ 𝐹𝑖𝑟𝑚 𝐷𝑒𝑣𝑒𝑙𝑜𝑝𝑚𝑒𝑛𝑡!,!
= 𝛼!,! + 𝛽! 𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦 𝑜𝑛 𝐸𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝐹𝑖𝑛𝑎𝑛𝑐𝑒!,! + 𝛽! 𝐶𝑜𝑠𝑡 𝑜𝑓 𝐷𝑒𝑏𝑡!,!
+ 𝛽! 𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦 𝑜𝑛 𝐸𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝐹𝑖𝑛𝑎𝑛𝑐𝑒!,! × 𝐶𝑜𝑠𝑡 𝑜𝑓 𝐷𝑒𝑏𝑡!,!
+ 𝛽! 𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦 𝐸𝑞𝑢𝑖𝑡𝑦 𝐹𝑖𝑛𝑎𝑛𝑐𝑒!,!
+ 𝛽! 𝐶𝑜𝑠𝑡 𝑜𝑓 𝐸𝑞𝑢𝑖𝑡𝑦!,! + 𝛽! 𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦 𝐸𝑞𝑢𝑖𝑡𝑦 𝐹𝑖𝑛𝑎𝑛𝑐𝑒!,! × 𝐶𝑜𝑠𝑡 𝑜𝑓 𝐸𝑞𝑢𝑖𝑡𝑦!,!
+ 𝛽! 𝐷! 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 + 𝛽! 𝐷! 𝑅𝑒𝑔𝑖𝑜𝑛 + 𝛽! 𝐷! 𝑌𝑒𝑎𝑟 + 𝜀!,! 3.2 Measure of Financial Dependency
Dependency on both external debt and -equity finance are incorporated in the model. Both dependency
rates are based on the method used by Rajan and Zingales (1996). Dependency on external finance is
defined as:
(2) 𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦 𝑜𝑛 𝐸𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝐹𝑖𝑛𝑎𝑛𝑐𝑒!,! =
!"#$%"& !"#$%&'()*$+!,! !!"#! !"#$ !"#$ !"#$%&'()*!,!
!"#$%"& !"#$%&'()*$+!,!
Capital expenditures is capital used for firm investments and is defined as; ‘an amount spent to acquire
or upgrade productive assets (such as buildings, machinery and equipment, vehicles) in order to
increase the capacity or efficiency of a company for more than one accounting period’ (Business
Dictionary, 2016). This results in the rate of desired investment that cannot be financed through
internal cash flows generated by the business itself. Dependency on equity finance is measured by the
ratio:
(3) 𝐷𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦 𝑜𝑛 𝐸𝑥𝑡𝑒𝑟𝑛𝑎𝑙 𝐸𝑞𝑢𝑖𝑡𝑦 𝐹𝑖𝑛𝑎𝑛𝑐𝑒!,! =
!!" !"#$%& !" !"#$%& !""#$"!,!
!"#$%"& !"#$%&'()*$+!,!
These required dependencies for the model are calculated on a firm level basis, in contrast to Rajan
and Zingales, who use these ratios on industry-level data. By calculating this ratio firm specific, it
becomes possible to conclude in very concrete and micro level implications due to cost of capital
fluctuations. When firms have no capital expenditures, the dependency is set equal to 0, while they are
not dependent on this form of external finance in a positive or negative way.
12 The Increase of Capital Cost and Firm Development Restriction 3.3 Cost of Equity and Debt
3.3.1. Cost of Equity
The amount of implied cost of equity capital can be measured based on several models. The most
traditional model used in literature, which is the model used for this thesis, is the Gordon Dividend
Growth Model (Gordon, 1959). This model is used while it is based on stock information, which is
publicly available and does not require much data simplifications. The model determines the intrinsic
stock value based on future dividend that grows at a constant rate (Cuthbertson and Nitzsche, 2004).
This model has two key assumptions. First, the existence of a constant growth rate (g) for the annual
dividends and second, the possibility of a higher cost of capital compared to the annual growth rate. In
calculating the cost of capital, each year the expected dividend growth rate within year t is equal to g,
which represents the growth rate from year t+1 until infinity. The original equation determining the
intrinsic stock value is as follows (Cuthbertson and Nitzsche, 2004):
(4) 𝑆𝑡𝑜𝑐𝑘 𝑃𝑟𝑖𝑐𝑒!,! =
!"#! (!!!!,! )
!"#$ !" !"#$%&!,! !!!,!
=
!"#!!!
!"#$ !" !"#$%&!,! !!!,!
After rearranging the terms, the cost of capital can be determined according to:
(5) 𝐶𝑜𝑠𝑡 𝑜𝑓 𝐸𝑞𝑢𝑖𝑡𝑦!,! =
!"#$% !"# !!!
!" !"#$%!
+ 𝑔!
The total amount of dividend paid in the future is divided by the market capitalization of the firm. This
is added to the dividend growth rate, giving the relatively amount paid for equity capital. Market
capitalization is defined as ‘the aggregate valuation of the company based on its current share price
and the number of outstanding stocks' (Economic Times). Another way of calculating the cost of
capital is the Capital Asset Pricing Model (CAPM) (Sharpe, 1964; Lintner, 1965). Even though this is
a commonly used model, it fails empirical tests (Bornholt, 2012; Dempsey, 2013). Furthermore, the
advantage of the Dividend Growth Model is the allowance to calculate the cost of capital based on
empirical values, while dividend figures, growth rates and market value of shares are all available for
publicly traded firms (Accaglobal, 2016).
3.3.2. Cost of Debt
Cost of debt can be determined without a model or additional assumptions, by looking at the
total interest expenses on debt dividend by the net amount of debt of the firm.
(6) 𝐶𝑜𝑠𝑡 𝑜𝑓 𝐷𝑒𝑏𝑡!,! =
!"#$% !"#$%$&# !" !"#$!,! !"# !"#$%& !" !"#$!,!
This relative measure is necessary while it can be argued that larger firms have higher absolute debt
levels. This relation would create a bias, while the cost of debt is in this case correlated with the
dependent variable firm development. The cost of debt can result in a negative value, while the
amount of net debt can become a value below zero. Net debt is calculated as the amount of debt (shortand long term) minus cash, cash equivalents and other liquid assets (Business Dictionary, 2016). Total
interest paid on debt can by definition not drop below zero.
13 The Increase of Capital Cost and Firm Development Restriction IV.
Data
4.1 Data Source
Firm level data is collected from the Worldscope Global Database, which is a fundamental of
Datastream since 1987. It provides detailed financial statement data on publicly quoted companies
worldwide in developed-, emerging- and frontier markets. Closed-end investment companies and
exchange-traded funds are not part of the Worldscope database. The most unique characteristic of the
database is the coverage of companies outside the United States, while most databases, for example
Compustat, only focus on US originated companies. Data is collected from primary source documents
and news statements. They take accounting differences into consideration when specifying the firm’s
financials, which facilitates comparability across firms and countries. There are two main reasons that
create accounting differences; valuation (i.e. cost base differences) and disclose or presentation (i.e.
terminology differences). Thomson states that their analysts ‘use standard data definitions in the
coding of financial accounts and by closely examining the nature and components of financial
statements, footnotes and related disclosures, differences in accounting terminology, presentation and
language are minimized’ (Thomson, 2013). Furthermore, all figures are subject to many balance tests
to make sure that the figures add up to the wright totals and ratios. The database represents
approximately 95% of the global market capitalization with 37.450 currently active companies
(Thomson, 2013). It contains both active and inactive companies, while historic information about
currently inactive companies remains accessible. Most data is collected from the financial statements:
the balance sheet, income statement and cash flow statement. The required data to estimate the model
(1) is discussed below.
4.2 Sample Selection
The database requires specific company selection before constructing the selected firm data. For this
reason it is necessary to specify a company sample list. The S&P Composite 1500 index is used as a
sample list (1506 companies). This index combines all firms in the S&P 500, S&P 400 and S&P 600
and covers 90% of the market capitalization of the US stock market. It contains small-, mid- and large
market cap firms. Firms for which data was not available are excluded from the sample. While the
economic crisis has had a large influence on firm’s financials, it is important to only compare
companies from 2008. Furthermore, data is available until 2015, while the financial reports are not yet
available for 2016. For this reason the sample period is from 2008 until 2015 resulting in 12.049
observations. Firms for which data was not complete are excluded from the sample. Two additional
selection criteria’s should be met, due to the use of the Dividend Growth Model. First, the model
assumes that firms pay annual dividends. Firms that do not pay dividend are dropped from the sample.
Secondly, negative values for the cost of equity can arise due to two causes; when dividends become
14 The Increase of Capital Cost and Firm Development Restriction smaller than 0, in the case of negative growth rates, and when the required return (dividend per share)
is less than the growth rate of dividend per share. Observations with negative values for the cost of
equity capital are dropped.
This results in a US sample of 6773 observations between 2008 and 2015 (Table 1). The
sample is geographically located across four US regions (West, Mid West, North East and South) (US
Census Bureau, 2016) as can be seen in Table 2. The observations of firms are well distributed across
years and the four regions.
Total Sample Description Years
Year
2008
2009
2010
2011
2012
2013
2014
2015
Total
Table 1: Total Sample Description; Years
Observations
784
655
750
862
883
928
963
948
6773
Total Sample Description Regional
Regions
Observations
West US
1736
Mid-West US
1132
North East US
1812
South US
2093
Total
6773
Table 2: Total Sample Description; Regional. Distribution of sample across 4 regions; West, Mid-West, North
East and South US.
In Table 3 the distribution across operating industries is displayed according to SIC codes (Companies House, 2016). The main industry group of each company is determined by the amount of
revenue generated within each industry, based on the Worldscope Global Database1. It can be seen
that most observations are from the manufacturing industry (2.522 firms) and the least from the
construction industry (85 firms). However, all industries are represented in the sample. The
distribution of industries across the four regions is included in Figure 1.
Grouped within main industry groups; Mining (SIC 1000-1499), Construction (SIC1500-1799), Manufacturing (SIC 2000-3999),
Transportation ect. (SIC 4000-4999), Wholesale Trade (SIC 5000-5199), Retail Trade (SIC 5200-5999), Finance ect. (SIC 6000-6799) and
Services (SIC 7000-8999). 1
15 The Increase of Capital Cost and Firm Development Restriction Total Sample Description Industries
Industries
Observations
Mining
232
Construction
85
Manufacturing
2522
Transportation, Communication, Electric, Gas and Sanitary
828
Wholesale Trade
212
Retail Trade
477
Finance, Insurance and Real Estate
1713
Services
704
Total
6773
Table 3: Total Sample Description; Industries. Based on the SIC Industry Code given in the Worldscope
Global Database. Displays the main industry for each company in terms of revenue.
Distribution of Industries
across US Regions
Services
Finance ect.
Retail Trade
South
Wholesale Trade
Mid-West
West
Transportation ect
North East
Manufacturing
Construction
Mining
South 0
Mid-­‐West 200
400
600
West 800
1000
North East Figure 1: Distribution of industries across US regions. Calculated in absolute terms (above) and relative
terms (below).
16 The Increase of Capital Cost and Firm Development Restriction Figure 1 shows that industries are not evenly distributed across regions. Manufacturing is most
represented in all regions. Furthermore, comparing the regions, most firms are located in the South.
However, this difference is respectively small (Table 2). In North East US, firms are mostly operating
in the manufacturing-, financial and service industries. Mining, construction and transportation firms
are mainly located within the South. Overall, this emphasises the importance to interpret the results
separately across regions in order to include the exposure to different industries.
Data requirements for the independent- and dependent variables are discussed and summarized
below.
4.3 Data Independent Variables
Data requirements for the cost of capital can be found in the Worldscope database (codes are included
in the Appendix). Next year dividends per share are calculated as the dividends for the current year
multiplied by the one-year annual dividends expected growth rate. Total expected future dividends can
be determined by multiplying the number of shares outstanding by the expected future dividends per
share. The cost of equity is found by dividing expected future dividend by the firms’ market
capitalization and finally added to the expected dividend growth rate. Cost of debt is equal to the total
interest expenses on debt divided by the net amount of debt.
Table 4 displays the characteristics of the cost of debt and –equity. The table shows that the
average annual cost per $1 of net debt are on average the highest within the Mid-West ($0,19) and the
lowest in the West ($0,03). Negative values for cost of debt indicate that firms have on average more
liquid assets than debt, resulting in a negative value of net debt. As mentioned in Section 3, the interest
costs on debt cannot drop below zero. The cost of equity shows a slightly different pattern. The
highest costs per dollar equity capital borrowed are required in the South (0,26) and the lowest in the
West (0,19). The table shows that there are no negative values for the cost of equity, as constructed by
the assumptions made in Section 3.
The numbers show large differences between firms. When comparing the cost of debt and
equity, the table shows that cost of $1 debt is lower than $1 equity. Which is well known in existing
literature through the pecking order theory (The Brattle Group). Furthermore, the standard error values
for the cost of debt differ substantially between regions. The Mid-West has the highest cost of debt
and shows the greatest standard error equal to 3,95 dollar. The uneven distribution of industries across
US regions can partly explain why the cost of capital differs between regions (Figure 1). These
exposure differences should be incorporated in the conclusions drawn from the estimated regressions.
17 The Increase of Capital Cost and Firm Development Restriction Cost of Debt
Cost of Equity
Continent
Obs. Mean Std. Dev.
Min.
Max. Obs. Mean Std. Dev.
Min.
Max.
West US
1669 0,032
0,547 -11,393
6,015 1599 0,191
0,696 0,000 17,000
Mid-West US
1043 0,191
3,953 -14,857 122,143
972 0,244
0,664 0,000 12,500
North East US
1745 0,069
0,662
-3,130 24,622 1676 0,217
0,723 0,000 12,500
South US
1966 0,034
0,522
-9,800 12,249 1858 0,264
0,948 0,000 28,600
Total US
6429 0,068
1,678 -14,857 122,143 6111 0,229
0,784 0,000 28,600
Table 4: Sample Distribution Cost of Debt and Cost of Equity across Regions. Cost of debt is given in
amount of US dollars and cost of equity is the return an investor gets for each dollar borrowed to the firm. Based
on formula (5) and (6).
Dependency on external equity finance is based on capital expenditures, cash flow from operations
and equity issues. The distributions of these dependencies within the sample are displayed in Table 5,
showing that firms located in West US are the least independent form external finance (-4,05).
However, all values of external capital dependency (debt) are negative, indicating that on average net
debt is negative (i.e. cash equivalents are greater than the amount of debt). Dependency on external
equity finance shows on average only positive rates, with on average most dependent firms located in
Mid-West US (6,51), which is drastically more dependent than the average firms within the US (1,72).
An average global firm depends for -6,05 on external finance and 1,72 on external equity finance.
Dependency External Finance
Dependency External Equity Finance
Continent
Obs. Mean Std. Dev.
Min.
Max. Obs. Mean Std. Dev.
Min.
Max.
West US
1655 -4,052
62,827
-190,251 2466,750 1651 1,196
9,185
-0,118 239,732
Mid-West US
1068 -5,431
62,189
-931,901 1437,136 1068 6,513
112,595
0,000 2661,167
North East US
1740 -6,590
41,772 -1061,756
16,157 1738 0,473
2,589
-0,030
85,667
South US
1970 -7,607
94,922 -3661,612
151,478 1969 0,659
4,339
-0,061 128,428
Total
6439 -6,050
69,886 -3661,612 2466,750 6432 1,718
46,231
-0,118 2661,167
Table 5: Sample Distribution Dependency External Finance and –Equity Finance across continents. Based
on formula (2) and (3).
4.4 Data Dependent Variables
As mentioned above, firm development is the dependent variable in the model and is measured based
on two firm characteristics. The first characteristic is firm size, which is measured with the total
number of employees employed by the firm. This data is collected from the Worldscope Global
Database. The second characteristic firm productivity is calculated as generated revenue per employee.
The Worldscope Global Database transforms all monetary values from local currencies to US dollars
(if needed).
Table 6 shows the firm characteristics for the sample. It shows that the average firm in de
sample consists of 27.922 employees, which is relatively large. The average firm generates $935,51 of
revenue per employee employed by the firm. Revenue has a large spread between $0 and $486
million, with an average of $10,6 million. There are large differences within the sample based on
absolute and relative characteristics.
18 The Increase of Capital Cost and Firm Development Restriction Firm Characteristics
Variable
Obs.
Mean
Std. Dev.
Min.
Max.
Firm Size
Employment
6314
27.922
94.168
0
2.300.000
Firm Productivity
Productivity
6313
935,51
2.682,04
18,97
48.552,00
Revenue
6616 10.600.000 29.300.000
0 486.000.000
Table 6: Sample Distribution Firm Characteristics. The rows display the variables needed to calculate the
firm characteristics. Employment is given in number of employees. Productivity and revenue are displayed in
US dollars.
To measure firm development, difference between current- and previous year is used. This difference
represents the increase or decrease in firm characteristics and in turn development the firm has made
within the current year. This is displayed in Table 7. The table shows that the average firm in the
sample developed positively with a yearly average increase of 320 employees and a productivity
improvement of $25,06 per employee. Again, there are large differences between companies. The
variables are transposed into logs, in order to represent a normal distribution (Figure 2).
Firm Development
Variable
Obs. Mean Std. Dev.
Min.
Max.
Firm Size
Employment
6319
320
5.552
-125.000
100.000
Firm Productivity
Productivity
6308 25,06
693,05 -14.898,45 32.541,07
Table 7: Sample Distribution Firm Development. Development is measured as the difference between two
years. Employment is given in number of employees. Productivity is displayed in US dollars.
Figure 2: Distributions dependent variables firm size (left) and –productivity (right). Variables are
expressed as logs.
19 The Increase of Capital Cost and Firm Development Restriction 4.5 Sample Examination
When the total sample is split, based on the cost of capital, it becomes possible to predict which signs
the regression coefficients will show and in turn to examine the stated hypothesis in a straightforward
and empirical manner. Three dummy variables are created for both cost of debt and –equity, displayed
in Table 8, in such a manner that the sample is split in equal size groups.
Dummies Threshold for Sample
Examination
Dummies Cost of Debt Cost of Equity
D1
<0,03
<0,05
D2
0,03-0,08
0,05-0,25
D3
>0,08
>0,25
Table 8: Dummy Threshold for Sample Examination. Based on the cost of capital. Cost of debt is expressed
in US dollars and the cost of capital is expressed as a return for each dollar borrowed.
Figure 3 and 4 show firm characteristics for each dummy variable group of debt- and equity costs
respectively. The simplified hypotheses (1) and (2) predict that when cost of capital increases, firm
development decreases. This means that the dummy variable group representing the highest cost of
capital (D3) should show lower values for firm size and –productivity compared to the dummy group
representing the smallest cost of capital (D1). Indicating a negative relation between D and the firm
characteristics. The first two characteristics (above) are expressed as absolute terms within the current
year and development is expressed as a difference between the current and previous year (below). The
last two characteristics represent the stated hypothesis.
Figure 3 shows the same pattern across all four measurements, which is not in line with the
stated hypothesis. The increase in cost of debt first increases (D2) and then decreases (D3) firm size
and –productivity. This suggests no linear relationship between the cost of debt and firm development.
40.000 30.000 20.000 10.000 0 1.500 1.000 500 D1 D2 0 D3 D1
Firm Size D3
Firm Productivity
600 60 40 20 0 400 200 D1 0 -­‐200 D2
D1 D2 D3 Development Firm Size D2 D3 Development Firm Productivity Figure 3: Firm Characteristics per Dummy Group for Cost of Debt. Cost of debt is expressed in US dollars.
Firm size is expressed in the number of employees productivity is the amount of US dollar revenue generated per
employee in the firm. The two characteristics above are calculated as yearly absolute figures and the two
characteristics below are calculated as developments (yearly differences).
20 The Increase of Capital Cost and Firm Development Restriction 40.000 30.000 20.000 10.000 0 1.100,00 1.000,00 900,00 800,00 D1 D2 D3 D1 Firm Size D2 D3 Firm Productivity 600 60,00 40,00 20,00 0,00 400 200 0 D1 D1 D2 D3 Development Firm Size D2 D3 Development Firm Productivity Figure 4: Firm Characteristics per Dummy Group for Cost of Equity. Cost of equity is as ratio, the return
required for each unit local currency borrowed. Firm size is expressed in the number of employees and US dollar
profit. Productivity is the amount of US dollar revenue generated per employee in the firm. The two
characteristics above are calculated as yearly absolute figures and the two characteristics below are calculated as
developments (yearly differences).
Figure 4 covers the effects of the cost of equity. Three measurements show the opposite direction as
stated in the hypothesis. Higher cost of equity (D3) shows higher firm productivity, development in
firm size and –productivity, compared to lower cost of equity (D1). This direction is the contrary to
what we would expect based on existing literature. Existing literature states that business risk is lower
for more established firms, because the chance to repayment increases. This should lead to lower risk
premiums and in turn lower required equity returns. One possible explanation for the opposite relation
can be found in the represented industries within the dummy groups. When industries with higher cost
of equity are overly represented within one dummy group, it is possible that this influences the
average firm characteristics. Some industries have more employees (production industries) and higher
per employee productivity (high-tech industries) compared to other industries. The distribution of
industries across dummy groups is displayed in Figure 5 and 6.
Figure 5 shows the number of firms located within the different dummy groups per industry category.
This figure shows that each dummy group does not consist of the same number of firms of each
industry, but that there are more firms operating in the manufacturing- and financial industry. This
means that the exposure to these industries is greater compared to wholesale and constructions. Figure
6 displays the distribution of market share across dummy groups. This shows that dummy group 1
consists of the largest market share in mining-, construction, transportation- and financial industries.
Dummy group 2 consists of relatively more firms operating in the retail- and wholesale trade and
manufacturing industries. The combination of Figure 5 and 6 emphasises that the exposure to the
different industries differs between dummy groups.
21 The Increase of Capital Cost and Firm Development Restriction Distribution of Industries
across Dummy Groups
Services
Finance ect.
Retail Trade
Wholesale Trade
%D3
Transportation ect
%D2
Manufacturing
%D1
Construction
Mining
0%
10%
%D1
20%
30%
40%
%D2
50%
%D3
Figure 5: Distribution of Industries across Dummy Groups. Grouped for industries (above) and for dummy
groups (below).
Market share
across Dummy Groups
Services
Finance ect.
Retail Trade
%D3 Wholesale Trade
%D2 Transportation ect
%D1 Manufacturing
Construction
Mining
0% 20% 40% 60% Figure 6: Distribution of Industry Market Shares across Dummy Groups. Assuming that combining D1, D2
and D3, represent the entire market.
As stated in the previous sections, a clear pattern across both firm characteristics is needed in order to
draw an overall conclusion about firm development. Both tables show in empirical terms that the
simplified version of the stated hypothesis is not supported. This suggests that firms charged higher
cost of capital do not experience more restriction to firm development. Furthermore, as stated earlier,
it is important to examine the interaction effect with dependency in order to deal with reverse
causality. In the next section the empirical findings are presented.
22 The Increase of Capital Cost and Firm Development Restriction V.
Empirical Results
For each dependent variable there are several regressions estimated. The first regressions are singular
regressions, which only contain the cost- and dependency on both debt and equity (hypotheses 1 and
2). The interaction terms are included in the second regressions, but the control variables are not
included yet. The third regressions estimated are based on the model introduced in Section 2 and
contains both the interaction terms and the control variables (hypotheses 3 and 4).
In interpreting the results it is important to emphasise that both indicators should be examined
combined instead of separately, as explained in the literature review. The stated hypothesis would
expect a negative sign for the coefficient of the interaction terms between the cost of capital and the
dependency on external finance, which means that more dependent firms on external capital
experience a larger restriction to firm growth when the cost of capital increases compared to less
dependent firms. The results are displayed in Table 9 and Table 19 in the Appendix.
The results show different conclusions for both firm characteristics. Regression (1) shows the results
for hypothesis (1) and (2), examining the relation between the singular variables of cost of debt and –
equity and firm development. Both firm size and –productivity show no significant results for the
singular variables of cost of debt and equity. Furthermore, the values of R-squared show very low
explanatory power of the stated regressions. For both firm characteristics only 1% of the variation can
be explained by the cost- and dependency of external capital. This suggests that more control variables
should be included in the model in order to increase the explanatory power of the model estimated.
Regressions (2) show significant, yet inconsistent, results for both firm characteristics. Firm
size, measured as change in employment, shows a significant relation for both interaction terms. This
indicates the presence of a significant relation between dependency- and cost of both equity- and debt
finance and firm development. This is in line with stated hypothesis (3) and (4); more dependent firms
on external capital experience a larger restriction to firm development when the cost of capital
increases, compared to less dependent firms. However, these coefficients are not significant for firm
productivity, which means that no clear conclusion about firm development can be drawn.
Furthermore, it is noteworthy to mention that the singular variables for the cost of debt- and equity
show no significant relations with firm development. This is not in line with existing literature, while
it is expected that larger and more established firms are charged lower cost of capital compared to
smaller and younger firms. It should be kept in mind that the control variables are not included in
these regressions.
23 The Increase of Capital Cost and Firm Development Restriction Firm Characteristics
Firm Size Employment
Variables
Constant
Dep. Debt
Cost of Debt
(1)
(2)
Firm Productivity
(3)
(1)
(2)
(3)
5,698***
5,694***
2,183
3,156***
3,156***
0,001*
0,001
0,000
0,000
0,000
0,000
0,003
-0,008
-0,011
-0,005
-0,007
-0,007
-0,003**
-0,003**
0,000
0,000
Dep.Debt#Cost of Debt
2,008
Dep. Equity
-0,002
0,006
0,010**
0,006*
0,007
0,004
Cost of Equity
-0,025
-0,017
-0,009
-0,008
-0,008
-0,010
-0,005**
-0,005***
0,000
0,001
2916
2916
2909
2909
Dep. Equity#Cost of Equity
Observations
Groups
R-squared
2916
2909
878
878
878
898
898
898
0,010
0,005
0,220
0,010
0,005
0,177
Table 9: Regression Results Firm Characteristics. The dependent variables are expressed in logs. Cost of
capital and dependency are calculated according to formula (2), (3), (5) and (6). The second regressions include
the interaction terms and the third regressions include the control variables. Note: *** p<0,01; ** p<0,05; * p<0,1.
The coefficients found in regressions (2) for firm size are robust against the inclusion of the
control variables as is shown in regressions (3). In order to interpret the coefficients in economic
terms, the difference in firm development between the average characteristics (from Table 4 and 5)
and the averages plus one standard deviation should be examined. The results show that an increase in
the cost of debt of 1 standard deviation (+1,678) makes firm value increase with 0,055%, keeping the
other variables constant2 (Table 10). This is based on a firm that is independent on external capital,
while an average firm is independent (-6,050). When the dependency on external capital also increases
with 1 standard deviation (+69,886), firm size decreases with -16,12% compared to the average and 16,57% compared to less dependent firms. This supports the hypothesis, while more dependent firms
on external capital experience a greater restriction to firm development in terms of firm size when the
cost of debt increases, compared to less dependent firms. The same conclusion can be drawn for the
cost of equity. When the cost of equity increases with 1 standard deviation (+0,784) firm size
decreases with -0,63% for an average dependent firm. When dependency also increases with 1standard
deviation (+4,339) firm size increases. This is caused by the fact that the coefficient of the cost of
equity is smaller than the dependency coefficient. However, it should be kept in mind that not all
coefficients are significant.
The stated hypotheses (3) and (4) are not supported for firm development in terms of firm
productivity. The R-squared of regressions (3) are improved by the inclusion of the control variables,
up to an explanatory power of the variance in firm development of 22% and 17,7% respectively.
2
Note: all coefficients of Table 9 are included in the regression, also not significant coefficients
24 The Increase of Capital Cost and Firm Development Restriction As stated above it is not possible to draw an overall conclusion concerning firm development,
while not both firm characteristics show the same significant pattern. However, it can be concluded
that the cost- and dependency of capital has a significant relation with firm size in terms of
employment.
Change in Firm Size
Firm Size
% Change with avg
Average
2,197
Cost of Debt +1sd
2,209
0,55%
Cost of Debt and Dependency +1sd
1,843
-16,12%
Cost of Equity +1sd
2,182
-0,63%
Cost of Equity and Dependency +1sd
2,410
9,76%
% Change higher dep
-16,57%
10,45%
Table 10: Change in Firm Size. Based on averages in cost of capital and dependency (row 1). Caused by an
increase of 1 standard deviation in the cost of debt (row 2) or equity (row 4) and both cost- and dependency on
debt (row 3) and equity (row 5)
As stated in Section 4.5 there are large differences in terms of industry exposure within US regions.
For this reason it is important to interpret the results for each region separately. This can be done with
the same method as mentioned above; the regression is based on the average figures mentioned in
Table 4 and 5, but this time for each region. Only the significant results for firm size are displayed in
Figure 7.
Change in Firm Size
per US Region
Change in Firm Size
per US Region
10,00%
30,00%
25,00%
0,00%
-10,00%
West Mid West North
East
20,00%
South
% Firm Size (Cost of
Debt+1sd)
-20,00%
-30,00%
-40,00%
% Firm Size (Cost of
Equity+1sd)
15,00%
10,00%
% Firm Size (Cost of
Equity & Dep +1sd)
5,00%
% Firm Size (Cost of
Debt & Dep +1sd)
0,00%
-5,00%
West
Mid West North
East
South
Figure 7: Change in Firm Size due to Cost of Debt (left) and Equity (right). Compared to averages in cost
of capital and dependency. Caused by an increase of 1 standard deviation in the cost of debt (left, blue) and both
cost- and dependency on debt (left, red). Increase of 1 standard deviation in the cost of equity (right, blue) and
both cost- and dependency on equity (right, red).
The left side of Figure 7 shows the effect for the cost of debt and shows that the effect of dependency
on external capital after an increase in the cost of debt has the largest negative effect in the Mid West.
Figure 1 shows that the Mid West has the largest exposure to the manufacturing industry, which can
argue that the effect on dependent firms is the largest in this industry.
The right side of Figure 7 shows a large percentage increase in firm size in the Mid West. This
is caused by the positive dependency coefficient of 0,01, which creates an increase in firm size when
25 The Increase of Capital Cost and Firm Development Restriction the dependency increases largely. However, the increase of the cost of equity creates a small decrease
in firm size (blue). Overall, the effect is greater after an increase in the cost- and dependency of debt
compared to equity.
5.2 Market Capitalization
The S&P 1500 captures small-, mid- and large market capitalized firms. It can be argued that the
results found for the overall sample are not representative for the three market cap groups separately.
Both cost- and dependency of capital can be fundamentally different between firm sizes. Small firms
can experience higher cost of capital, because they have a worse liquidity position than larger firms,
which can result in a lower possibility of loan repayment. Furthermore, while less information is
available for smaller firms, information asymmetry and transparency problems are larger for these
firms. This is translated into a higher required return on capital. Lastly, smaller firms arguably have
lower internal funds available for investment, which makes dependency on external capital higher.
This means that the results for low market cap firms can be different compared to large market cap
firms. In this case no general conclusion across all 3 market cap groups can be made. To examine
whether the results are robust against this separation, a dummy group for each market capitalization
category is made. Table 10 shows that the groups are approximately the same and are therefore
representative for each firm size.
Dummies Categorization Robustness Check
Dummies
Market Capitalization
Number of firms
D1 – Small
<2 billion
1.951
D2 – Mid
2 billion-10billion
2.609
D3 – Large
>10 billion
2.219
Table 10: Dummy categorization robustness check. Based on the firm’s market capitalization in US dollars.
The dummy groups represent respectively small-, mid- and large market cap firms.
The model that examines the interaction between cost- and dependency of capital is estimated for all
three dummy groups separately; regressions (1) estimate the model for small cap firms (D1),
regressions (2) for mid cap firms (D2) and regressions (3) for large cap firms (D3).
The regression results of firm size in terms of employment show a remarkably different
pattern as displayed in Table 9. Where the total sample shows a significant interaction coefficient for
both the cost of debt and –equity, Table 11 shows that only small market cap firms have a significant
interaction coefficient between the dependency- and cost of debt. The other market cap groups show
no longer a significant relation between the interaction terms and firm size. The interaction terms
show no significant relation with firm productivity for all market cap categories.
26 The Increase of Capital Cost and Firm Development Restriction Firm Characteristics
Firm Size Employment
Variables
(D1)
Constant
5,042***
3,301**
0,000
-0,003
-0,010
0,000
0,000
0,002
-0,051
-0,019
0,155
0,063
-0,014
-0,076
Dep. Debt
Ln Cost of Debt
Dep.Debt#Cost of Debt
(D2)
(D3)
Firm Productivity
(D1)
6,995 1,906***
(D2)
1,578
(D3)
2,303***
-0,003**
-0,006
0,012
0,000
-0,002
-0,004
Dep. Equity
0,001
0,019***
0,031
0,013
-0,049*
-0,028
Ln Cost of Equity
0,030
-0,058
0,014
0,039
-0,050
0,002
-0,002
765
253
0,258
0,612
0,013
1.153
342
0,321
0,620
-0,017
998
283
0,245
0,524
-0,002
741
262
1,164
0,440
0,167**
1117
344
0,193
0,477
-0,220**
1.051
292
0,227
0,505
Dep. Equity#Cost of Equity
Observations
Groups
R-squared
Rho
Table 11: Regression Results Firm Characteristics. The dependent variables are expressed in logs. Cost of
capital and dependency are calculated according to formula (2), (3), (5) and (6). Regression (1) is separately estimated for D1, D2 and D3 respectively (i.e. only values equal to 1 are included in the regression).
This difference is important when interpreting the results based on the total sample, while this
indicates that the results found for firm size are not representative for the three market cap categories
separately. This can possibly be explained by a data bias, while market cap is included in the
calculation of the cost of equity. This means that large market cap firms could have lower cost of
equity since the denominator of formula (5) increases (only true if nominator is held equal). When this
is the case, a part of the variation in the dependent variable firm size is explained by the creation of
groups, which results in non-significant coefficients of the interaction terms. The overall sample and
the separate subsamples, however, do not show a significant relation between the value of market cap
and the cost of equity capital. Furthermore, the cost of equity across the dummy groups show not the
expected decrease of costs as the market cap increases (D) (Table 12). Even though these two
explanations are not supported by the data, it shows that the results should be interpreted with caution,
while the overall results are not representative for the market cap groups separately.
Cost of Equity across Market Cap Groups
Variable
Obs.
Mean
Std. Dev. Min. Max.
D1 – Small
1.630
0,250
0,803
0
12,5
D2 – Mid
2.356
0,213
0,768
0
28,6
D3 – Large
2.125
0,230
0,787
0
17,0
Table 12: Cost of Equity across Market Cap Groups. Cost of equity is expressed in US dollars.
The opposite results are found for firm productivity. Where the overall sample shows no
significant results, the separation of market cap groups does. The interaction between the dependencyand cost of external equity capital becomes significant for mid- and large market cap firms.
Remarkably, mid market cap firms show a positive relation (0,167), while large market cap firms
show a negative relation (-0,220). This positive relation is not in line with existing literature, while this
27 The Increase of Capital Cost and Firm Development Restriction would indicate that more dependent firms on external equity capital experience an improvement in
firm productivity as the cost of equity increases, compared to less dependent firms. When examining
development in firm productivity across different market cap groups, it should be noted that there are
large differences between market cap groups as can be seen in Table 13. Small market cap firms
experience on average more development in firm productivity (57,77) compared to large market cap
firms (-1,14). This can be explained by the fact that smaller firms have more room for productivity
improvements than established large market cap firms. This difference can explain why the separation
of the model results in significant coefficients of the interaction terms, while the overall sample does
not.
Firm Productivity Development
across Market Capitalized Groups
Variable
Obs. Mean
Std. Dev.
Min.
Max.
D1 – Small
1.717 57,77
692,28
-4406,74 11784,31
D2 – Mid
2.437 25,16
878,65 -14898,45 32541,07
D3 – Large
2.154 -1,14
387,34 -11479,39
3256,69
Table 13: Firm Productivity across Market Cap Groups. Firm productivity is expressed as development (i.e.
new year minus previous year) in US dollars of sales earned per employee.
When these results are tested with a Least Squares Dummy Variable, which incorporates fixed effects
for each year, the results are unchanged. Furthermore, when using the Hausman Test, the regression
shows that the random effects hypothesis cannot be rejected with a p-value equal to 0,3745. This
means that it is not shown that fixed effects influence the regressions estimated.
5.3 Robustness Check
Firm size is often measured as the firm’s market cap. However, there are two reasons why market cap
is not used as dependent variable in the estimated model. First, market cap is used to measure the cost
of equity, which creates a bias when also included as a dependent variable. Second, market cap does
not differ in the short time span used for the estimated model. For this reason it is not possible to
estimate development in firm size. However, to test whether the results are robust against changes,
market cap as a static yearly firm characteristic is used as a control variable. The results displayed in
Table 14 show that there are no differences in the coefficients after including market cap as a control
variable. This suggests that the inclusion of market cap as a control variable has no influence on the
results displayed in Table 9.
28 The Increase of Capital Cost and Firm Development Restriction Firm Characteristics
Variables
Firm Size
Constant
-6,625***
Dep. Debt
Dep. Equity
1,071
0,000
0,000
-0,013
-0,007
-0,003**
0,000
Ln Cost of Debt
Dep.Debt#Cost of Debt
Firm Productivity
0,010**
0,004
0,001
-0,009
Ln Cost of Equity
Dep. Equity#Cost of Equity
-0,004**
0,000
Market cap
0,626***
0,067**
2916
2909
Observations
Groups
878
898
R-squared
0,428
0,179
Within
0,017
0,004
Between
0,493
0,206
Table 14: Regression Results Firm Characteristics. The dependent variables are expressed in logs. Cost of
capital and dependency are calculated according to formula (2), (3), (5) and (6). Market cap is added as a control
variable to Model (1) estimated.
While market cap cannot be used as a firm characteristic of development, the static yearly amount can
be used as an indicator of established development. For this reason Model (1) is estimated for market
cap, firm size and –productivity to explain established firm development. Results in Table 15 show a
remarkably different pattern than Table 9 and 14. The coefficients determining the amount of market
cap are all equal to 0, which indicates that they have no explanatory power. Furthermore, the
interaction terms of dependency- and cost of capital are no longer significant for firm size. This means
that the interaction explains firm development in yearly firm development, but does not explain static
established firm growth.
Firm Characteristics
Variables
Constant
Dep. Debt
Ln Cost of Debt
Dep.Debt#Cost of Debt
Dep. Equity
Ln Cost of Equity
Dep. Equity#Cost of Equity
Observations
Groups
R-squared
Within
Between
Market Cap
13,970***
0,000
0,000
0,000
0,000
0,000
0,000
5909
963
0,027
0,002
0,026
Firm Size Firm Productivity
7,726***
5,631***
0,000
0,000
-0,002
-0,001
0,000
0,000
0,000
0,000***
-0,010***
0,004
-0,001
0,000
5783
5782
959
959
0,266
0,227
0,092
0,070
0,249
0,226
Table 15: Regression Results Firm Characteristics. The dependent variables are expressed in logs and are
calculated as; 𝑀𝑎𝑟𝑘𝑒𝑡 𝐶𝑎𝑝!,! , 𝐹𝑖𝑟𝑚 𝑆𝑖𝑧𝑒!,! and 𝐹𝑖𝑟𝑚 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦!,! . Cost of capital and dependency are
calculated according to formula (2), (3), (5) and (6).
29 The Increase of Capital Cost and Firm Development Restriction VI.
Conclusions
This thesis examines the effect of cost of capital on firm development. This direct effect is not yet
examined in existing literature, but is a vital relation for businesses with respect to future
development. High cost of capital can restrict the possibility for firms to grow to their optimal size.
This restriction of firm development in turn affects economic developments within countries. In order
to give an economically relevant conclusion and to solve causality problems, an interaction term is
included. By separating the sample in firms that are more and less dependent on external finance, it
becomes possible to investigate whether more dependent firms experience more restriction to firm
development compared to less dependent firms. A US dataset is constructed from the Worldscope
Global Dataset made available through Datastream. The sample consists of the S&P 1500 company
list, which represents small-, mid- and large market capitalized firms in the US.
In order to examine whether more dependent firms experience more restriction to firm development,
several regressions are estimated. The main results found in these regressions show that there is a
negative significant relation between the interaction term and firm development in terms of size. This
relation is shown for both cost of debt and –equity. In economic terms this means that overall, a
external capital dependent firm experiences a larger decrease in firm size when the cost of debt and
equity increases, compared to a less dependent firm. This is in line with stated hypotheses (3) and (4).
However, while this relation is not found for firm productivity, a general conclusion concerning
overall firm development cannot be drawn. For this reason, it can only be concluded that this relation
is significantly negative between debt- and equity capital and development in firm size. Furthermore,
the effect of capital cost changes differ between regions, while the exposure to specific industries are
not the same across the four US regions. Furthermore, the results are not the same after a separation of
the sample between small-, mid- and large market cap firms. This indicates that a general conclusion
for overall market should be interpreted with care. Furthermore, it is examined whether the model also
explains established firm growth compared to yearly firm development (i.e. firm characteristics
measured within the current year instead of the difference between current and previous year). The
results show that there are no significant relations between the cost- and dependency of external
capital and established firm growth.
Overall, this suggests that it is not possible to draw a general conclusion about firm
development. Indicating that the level of capital cost that the capital market charges combined with
dependency does not directly influence the firm’s development. This would suggest that firms are not
discouraged by higher required rates of return and still invest in opportunities of growth. However, it
should be noted that this conclusion might not hold for drastic increases in these costs of external
capital. It can be argued that larger firms are able to adapt to small changes, but smaller cannot. When
30 The Increase of Capital Cost and Firm Development Restriction firms are not able to borrow capital and in turn are not able to keep up with the fast changing
economic developments through necessary investments, this can eventually lead to firm bankruptcies
and economic stagnation. For this reason it is necessary to be aware of the possible influences of
external capital costs with respect to firm development.
6.1 Future Research
To conclude, several limitations to the method and data used in this thesis should be mentioned.
The largest one contains the problem of reverse causality that is present in the variable cost of
capital. This problem is mainly present in the single variables representing cost of capital. The
interaction terms try to tackle this problem, however, it cannot be excluded entirely. Furthermore, data
limitations have led to several possible biases. The sample only contains US companies; therefore a
global conclusion cannot be drawn.
The second limitation is the fact that the sample is tilted towards larger firms, while it only
contains publicly traded firms. However, this bias cannot be fully solved, because the required data is
only available for publicly traded firms, which are already larger companies than private firms. This
should be kept in mind when interpreting the results, because it is shown in literature that private firms
are fundamentally different compared to public firms in terms of financing decisions (Brav, 2009).
Public firms are more likely to acquire equity instead to debt compared to private firms. Furthermore,
access to the equity market is costly and therefore more in reach of public firms. Lastly, public firms
face fewer problems concerning asymmetric information and transparency than private firms. This
means that the results cannot be drawn for firms generally, but only for publicly traded firms.
The third limitation that should be mentioned is that the cost of equity is based on the
Dividend Growth Model. Section 2 already mentioned some limitations of this model. The largest
limitation for this model is that the cost of equity capital cannot be calculated for firms that do not pay
dividends. Also, when firms do not exercise extra equity shares, the dependency on external equity
finance is set equal to 0.
These limitations should be kept in mind when drawing conclusions from this thesis and can
be an inspiration for further research. Also, the combination between the cost of debt and –equity (i.e.
the Weighted Average Cost of Capital) can be a subject for future literature, while this rate is often
used to judge investment opportunities. The relation between this rate and firm development can give
insight into the firms’ perspective regarding growth possibilities.
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36 The Increase of Capital Cost and Firm Development Restriction Appendix
Table 16: Datasteam Worldscope Codes
Datastream - Worldscope Codes
Variables
Code
Dividends current year
WC5101
One-year annual dividends expected growth rate WC08611
Nr of shares outstanding
WC05301
Market capitalization
WC08005
Interest expenses on debt
WC01251
Net Debt
WC18199
Capital expenditures
WC04601
Cash flow from operations
WC04860
Equity issues
WC04251
Revenue
WC07240
Number of employees
WC07011
Table 16: Datastream Worldscope Codes for dependent- and independent variables
Table 17: Firm Characteristics per Dummy Group for Cost of Debt
Variable
Firm Size
Firm Characteristics Cost of Debt According to Dummy Groups
Obs. Mean
Std. Dev. Min.
Max.
D1 2.154
D2 2.689
D3 1.471
20.404
33.483
28.767
47.611
132.871
48.265
0
0
7
434.246
2.300.000
539.000
D1 2.151
D2 2.678
D3 1.471
614,67
1.261,19
811,75
1.395,28
3.658,94
1.799,06
24,36
18,97
21,33
24.199,62
48.552,00
35.580,95
D1 2.121
D2 2.667
D3 1.531
316
514
-10
4.187
6.592
5.205
-117.900
-125.000
-57.597
37.680
100.000
88.000
Firm Productivity
Development Firm Size
Development Firm Productivity
D1 2.119
9,23
310,43 -6.858,17
4.913,96
D2 2.658
46,24
972,99 -14.898,45 32.541,07
D3 1.531
10,18
448,50 -4.509,29 10.566,31
Table 17: Firm Characteristics per Dummy Group for Cost of Debt. Cost of debt is expressed in US dollars.
Firm size is expressed in the number of employees productivity is the amount of US dollar revenue generated per
employee in the firm. The first two characteristics are calculated as yearly absolute figures and the last two
characteristics are calculated as developments (yearly differences).
37 The Increase of Capital Cost and Firm Development Restriction Table 18: Firm Characteristics per Dummy Group for Cost of Equity
Variable
Firm Size
Firm Characteristics Cost of Equity According to Dummy Groups
Obs. Mean
Std. Dev. Min.
Max.
D1 2402
D2 2548
D3 1364
18.966
37.793
25.256
61.239
123.656
74.576
0
10
0
2.300.000
2.200.000
2.100.000
D1 2348
D2 2548
D3 1360
888,53
915,44
1.055,74
2.583,38
2.489,09
3.157,33
26,66
22,19
18,97
42.649,73
36.767,69
48.552,00
D1 2389
D2 2529
D3 1401
135
388
514
4.790
6.390
5.110
-57.597
-125.000
-78.000
100.000
100.000
78.000
Firm Productivity
Development Firm Size
Development Firm Productivity
D1 2380
20,75
789,08 -11.479,39 32.541,07
D2 2529
21,70
443,62 -5.874,83
9.294,43
D3 1399
38,45
866,75 -14.898,45 12.153,05
Table 18: Firm Characteristics per Dummy Group for Cost of Equity. Cost of equity is as ratio, the return
required for each unit local currency borrowed. Firm size is expressed in the number of employees and US dollar
profit. Productivity is the amount of US dollar revenue generated per employee in the firm. The first two
characteristics are calculated as yearly absolute figures and the last two characteristics are calculated as
developments (yearly differences).
38 The Increase of Capital Cost and Firm Development Restriction Table 19: Regression Results Firm Characteristics
Firm Characteristics
Firm Size Employment
Variables
(1)
Constant
Dep. Debt
Cost of Debt
(2)
Firm Productivity
(3)
(1)
(2)
(3)
5,698***
5,694***
2,183
3,156***
3,156***
0,001*
0,001
0,000
0,000
0,000
0,000
0,003
-0,008
-0,011
-0,005
-0,007
-0,007
-0,003**
-0,003**
0,000
0,000
Dep.Debt#Cost of Debt
2,008
Dep. Equity
-0,002
0,006
0,010**
0,006*
0,007
0,004
Cost of Equity
-0,025
-0,017
-0,009
-0,008
-0,008
-0,010
-0,005**
-0,005***
0,000
0,001
Dep. Equity#Cost of Equity
Industry
Mining
-0,787**
2,136***
Construction
-0,571
1,435***
Manufacturing
-0,052
0,818***
Transportation ect.
-0,705***
1,244***
Wholesale Trade
-0,145
1,464*
Retail Trade
1,035***
-0,403***
Finance ect.
-1,970***
1,551
4,214**
-0,109
Services
Continent
North East
West
0,379
Mid-West
4,227**
South
4,244**
2009
-0,460***
0,034
2010
-0,162**
0,186**
2011
-0,059
0,240***
2012
-0,164**
0,071
2013
-0,082
0,062
2014
-0,121*
0,027
0,245
Year
2015
Observations
2916
2916
2916
2909
2909
2909
878
878
878
898
898
898
R-squared
0,010
0,005
0,220
0,01
0,005
0,177
Within
0,000
0,003
0,017
0,000
0,000
0,004
Between
0,025
0,009
0,239
0,007
0,008
0,201
Rho
0,741
0,738
0,686
0,562
0,560
0,484
Groups
F-value
Table 19: Regression Results Firm Characteristics. The dependent variables are expressed in logs. Cost of
capital and dependency are calculated according to formula (2), (3), (5) and (6). The regressions are stated as;
(2) 𝑙𝑛 𝑓𝑖𝑟𝑚 developmenti,y = 𝛼i + 𝛽1 Dep. External Fini,y + 𝛽2 Cost of Debti,y + 𝛽3 Dep. Equity Fini,y + 𝛽4 Cost of Equityi,y + 𝜀i, (2) 𝑙𝑛 𝑓𝑖𝑟𝑚 development,y = 𝛼i + 𝛽1 Dep External Fini,y + 𝛽2 Cost of Debti,y + 𝛽3 (Dep. External Fin.i,y× Cost of Debti,y) + 𝛽4 Dep. Equity Fini,y + 𝛽5 Cost of Equityi,y + 𝛽6 (Dep. Equity Fin.i,y× Cost of Equityi,y)+ 𝜀i and (3) 𝑙𝑛 𝑓𝑖𝑟𝑚 development,y = 𝛼i + 𝛽1 Dep External Fini,y + 𝛽2 Cost of Debti,y + 𝛽3 (Dep. External Fin.i,y× Cost of Debti,y) + 𝛽4 Dep. Equity Fini,y + 𝛽5 Cost of Equityi,y + 𝛽6 (Dep. Equity Fin.i,y× Cost of Equityi,y)+ 𝛽7𝐷j 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 +𝛽8𝐷c 𝐶𝑜ntinent + 𝛽9𝐷y Year+ 𝜀i. Note: *** p<0,01; ** p<0,05; * p<0,1.
39 The Increase of Capital Cost and Firm Development Restriction Table 20: Regression Results Firm Characteristics For each Market Capitalization
Category:
Firm Characteristics
Firm Size Employment
Variables
D1
Constant
5,042***
3,301**
6,995
1,906***
1,578
2,303***
0,000
-0,003
-0,010
0,000
0,000
0,002
Dep. Debt
Ln Cost of Debt
D2
Firm Productivity
D3
D1
D2
D3
-0,051
-0,019
0,155
0,063
-0,014
-0,076
-0,003**
-0,006
0,012
0,000
-0,002
-0,004
Dep. Equity
0,001
0,019***
0,031
0,013
-0,049*
-0,028
Ln Cost of Equity
0,030
-0,058
0,014
0,039
-0,050
0,002
-0,002
0,013
-0,017
-0,002
0,167**
-0,220**
2,316***
Dep.Debt#Cost of Debt
Dep. Equity#Cost of Equity
Industry
Mining
-0,583
-1,636***
-0,995**
0,826
2,128***
Construction
-0,172
-0,038
-0,853
1,660***
0,893
2,197*
Manufacturing
-0,211
-0,539
0,095
0,951***
0,763***
0,648**
Transportation ect.
-0,008
-1,818***
-0,796**
0,767**
1,598***
0,928***
Wholesale Trade
0,153
-0,266
-0,371
1,201**
1,466***
1,839***
Retail Trade 0,413***
0,699**
1,868***
0,002
-0,577
-0,848**
-2,524*** -1,531***
1,591***
1,572***
1,537***
0,596**
0,636
0,300
0,324
0,461
0,079
0,433*
0,339
0,652
0,028
-0,451*** -0,017***
-0,156
0,026
0,218
-0,236
0,186
0,463***
Finance ect.
-1,810
Services
Continent
North East
0,000
3,299**
0,420
West
Mid-West
South
0,285
0,345
3,571**
3,434**
-0,227
Year
2009
-0,307
2010
-0,021
-0,177
2011
0,001
-0,022
-0,176
0,016
0,274*
0,370***
2012
-0,094
-0,129
-0,294**
-0,107
0,128
0,187
2013
-0,016
-0,069
-0,207
-0,107
0,208
0,057
2014
-0,071
-0,029
-0,278**
-0,286*
0,171
0,103
765
1153
998
741
1117
1051
-0,264*
2015
Observations
Groups
253
342
283
262
344
292
R-squared
0,258
0,321
0,245
1,164
0,193
0,227
Within
0,022
0,022
0,029
0,009
0,014
0,026
Between
0,267
0,395
0,296
0,178
0,220
0,271
Rho
0,612
0,620
0,524
0,440
0,477
0,505
Table 20: Regression Results Firm Characteristics Robustness Check. Cost of capital and the firm
characteristics are expressed in logs. Cost of capital and dependency are calculated according to formula (2), (3),
(5) and (6). D1, D2 and D3 represent small-, mid- and large market capitalization firms. The regressions are
estimated for each dummy group separately as; 𝑙𝑛 𝑓𝑖𝑟𝑚 development,y = 𝛼i + 𝛽1 Dep External Fini,y + 𝛽2 ln Cost of Debti,y + 𝛽3 (Dep. External Fin.i,y× ln Cost of Debti,y) + 𝛽4 Dep. Equity Fini,y + 𝛽5 ln Cost of Equityi,y + 𝛽6 (Dep. Equity Fin.i,y× ln Cost of Equityi,y)+ 𝛽7𝐷j 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 +𝛽8𝐷c 𝐶𝑜ntinent + 𝛽9𝐷y Year+ 𝜀i. Note: *** p<0,01; ** p<0,05; * p<0,1. 40 The Increase of Capital Cost and Firm Development Restriction Table 21: Regression Results Firm Characteristics Introduction Market Capitalization
as Control Variable, Robustness Check 1:
Firm Characteristics
Variables
Firm Size
Firm Productivity
Constant
-6,625***
1,071
Dep. Debt
Ln Cost of Debt
Dep.Debt#Cost of Debt
Dep. Equity
0,000
0,000
-0,013
-0,007
-0,003**
0,000
0,010**
0,004
0,001
-0,009
Dep. Equity#Cost of Equity
-0,004**
0,000
Market cap
0,626***
0,067**
-1,128***
2,107***
Ln Cost of Equity
Industry
Mining
Construction
-0,275
1,473***
Manufacturing
-0,284*
0,793***
Transportation, Communication, Electric, Gas and Sanitary
-1,121***
1,196***
Wholesale Trade
-0,158
1,464***
Retail Trade
0,892***
-0,416**
Finance, Insurance and Real Estate
-2,018***
1,543***
North East
3,420**
-0,197
West
3,076**
0,293
Mid-West
3,624***
-0,073
Services
Continent
South
Year
2009
-0,472***
0,031
2010
-0,158**
0,178**
2011
-0,067
0,232***
2012
-0,170**
0,066
2013
-0,092
0,055
2014
-0,115
0,020
2916
2909
878
898
R-squared
0,428
0,179
Within
0,017
0,004
Between
0,493
0,206
2015
Observations
Groups
Table 21: Regression Results Firm Characteristics Robustness Check. Cost of capital and the firm
characteristics are expressed in logs. Cost of capital and dependency are calculated according to formula (2), (3),
(5) and (6). The regressions are stated as; 𝑙𝑛 𝑓𝑖𝑟𝑚 development,y = 𝛼i + 𝛽1 Dep External Fini,y + 𝛽2 ln Cost of Debti,y + 𝛽3 (Dep. External Fin.i,y× ln Cost of Debti,y) + 𝛽4 Dep. Equity Fini,y + 𝛽5 ln Cost of Equityi,y + 𝛽6 (Dep. Equity Fin.i,y× ln Cost of Equityi,y)+ 𝛽7𝐷j 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 +𝛽8𝐷c 𝐶𝑜ntinent + 𝛽9𝐷y Year+ 𝛽10 Market Capitalization 𝜀i. Note: *** p<0,01; ** p<0,05; * p<0,1. 41 The Increase of Capital Cost and Firm Development Restriction Table 22: Regression Results for Static Firm Characteristics, Robustness Check 2:
Firm Characteristics
Variables
Market Cap
Firm Size
Firm Productivity
Constant
13,970***
7,726***
5,631***
Dep. Debt
0,000
0,000
0,000
Ln Cost of Debt
0,000
-0,002
-0,001
Dep.Debt#Cost of Debt
0,000
0,000
0,000
Dep. Equity
0,000
0,000
0,000***
Ln Cost of Equity
0,000 -0,010***
0,004
Dep. Equity#Cost of Equity
0,000
-0,001
0,000
Industry
0,511* -0,835***
1,327***
Construction
Mining
-0,381
-0,625
1,048***
Manufacturing
0,384**
-0,087
0,571***
Transportation, Communication, Electric, Gas and Sanitary
0,765***
-0,236
0,980***
Wholesale Trade
-0,023
-0,171
1,185***
Retail Trade
0,189
1,236***
-0,255**
0,174 -0,171***
1,169***
Finance, Insurance and Real Estate
Services
Continent
North East
1,237
1,486
-0,331
West
1,246
0,954
-0,125
Mid-West
0,994
1,446
-0,318
2009
0,000 -0,035***
-0,073***
2010
0,000
0,002
-0,029***
2011
0,000
0,048***
0,007
2012
0,000
0,077***
0,022**
2013
0,000
0,100***
0,040***
2014
0,000
0,120***
0,076***
5909
5783
5782
963
959
959
R-squared
0,027
0,266
0,227
Within
0,002
0,092
0,070
Between
0,026
0,249
0,226
South
Year
2015
Observations
Groups
Table 21: Regression Results Firm Characteristics Robustness Check. Cost of capital and the firm
characteristics are expressed in logs. Cost of capital and dependency are calculated according to formula (2), (3),
(5) and (6). The regressions are stated as; 𝑙𝑛 𝑓𝑖𝑟𝑚 development,y = 𝛼i + 𝛽1 Dep External Fini,y + 𝛽2 ln Cost of Debti,y + 𝛽3 (Dep. External Fin.i,y× ln Cost of Debti,y) + 𝛽4 Dep. Equity Fini,y + 𝛽5 ln Cost of Equityi,y + 𝛽6 (Dep. Equity Fin.i,y× ln Cost of Equityi,y)+ 𝛽7𝐷j 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦 +𝛽8𝐷c 𝐶𝑜ntinent + 𝛽9𝐷y Year+ 𝛽10 Market Capitalization 𝜀i. Note: *** p<0,01; ** p<0,05; * p<0,1. 42