fds

1. Determinants of capital structure
An empirical study of firms in manufacturing
industry of Pakistan
Nadeem Ahmed Sheikh
School of Management, Huazhong University of Science and Technology,
Wuhan, People’s Republic of China and
Institute of Management Sciences, Bahauddin Zakariya University,
Multan, Pakistan, and
Zongjun Wang
School of Management, Huazhong University of Science and Technology,
Wuhan, People’s Republic of China
Abstract
Purpose – The aim of this empirical study is to explore the factors that affect the capital structure
of manufacturing firms and to investigate whether the capital structure models derived from
Western settings provide convincing explanations for capital structure decisions of the Pakistani
firms.
Design/methodology/approach – Different conditional theories of capital structure are reviewed
(the trade-off theory, pecking order theory, agency theory, and theory of free cash flow) in order to
formulate testable propositions concerning the determinants of capital structure of the manufacturing
firms. The investigation is performed using panel data procedures for a sample of 160 firms listed on
the Karachi Stock Exchange during 2003-2007.
Findings – The results suggest that profitability, liquidity, earnings volatility, and tangibility
(asset structure) are related negatively to the debt ratio, whereas firm size is positively linked to the
debt ratio. Non-debt tax shields and growth opportunities do not appear to be significantly related to
the debt ratio. The findings of this study are consistent with the predictions of the trade-off theory,
pecking order theory, and agency theory which shows that capital structure models derived from
Western settings does provide some help in understanding the financing behavior of firms in
Pakistan.
Practical implications – This study has laid some groundwork to explore the determinants of
capital structure of Pakistani firms upon which a more detailed evaluation could be based.
Furthermore, empirical findings should help corporate managers to make optimal capital structure
decisions.
Originality/value – To the authors’ knowledge, this is the first study that explores the determinants
of capital structure of manufacturing firms in Pakistan by employing the most recent data. Moreover,
this study somehow goes to confirm that same factors affect the capital structure decisions of firms in
developing countries as identified for firms in developed economies.
Keywords Capital structure, Stock exchanges, Manufacturing industries, Pakistan
Paper type Research paper
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0307-4358.htm
The authors are thankful to Dr Don Johnson, Dr Muhammad Azeem Qureshi, and two
anonymous reviewers for their detailed comments and suggestions that substantially improved
the paper. They are also thankful to Ms Lisa Averill and Mr Javed Choudary for their
comprehensive editing of the manuscript.
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Managerial Finance
Vol. 37 No. 2, 2011
pp. 117-133
q Emerald Group Publishing Limited
0307-4358
DOI 10.1108/03074351111103668

2. 1. Introduction
Decisions concerning capital structure are imperative for every business organization.
In the corporate form of business, generally it is the job of the management to make
capital structure decisions in a way that the firm value is maximized. However,
maximization of firm value is not an easy job because it involves the selection of debt and
equity securities in a balanced proportion keeping in view of different costs and benefits
coupled with these securities. A wrong decision in the selection process of securities may
lead the firm to financial distress and eventually to bankruptcy. The relationship
between capital structure decisions and firm value has been extensively investigated
in the past few decades. Over the years, alternative capital structure theories have been
developed in order to determine the optimal capital structure. Despite the theoretical
appeal of capital structure, a specific methodology has not been realized yet, which
managers can use in order to determine an optimal debt level. This may be due to the fact
that theories concerning capital structure differ in their relative emphasis; for instance,
the trade-off theory emphasizes taxes, the pecking order theory emphasizes differences
in information, and the free cash flow theory emphasizes agency costs. However, these
theories provide some help in understanding the financing behavior of firms as well as
in identifying the potential factors that affect the capital structure.
The empirical literature on capital structure choice is vast, mainly referring to
industrialized countries (Myers, 1977; Titman and Wessels, 1988; Rajan and Zingales,
1995; Wald, 1999) and a few developing countries (Booth et al., 2001). However, findings
of these empirical studies do not lead to a consensus with regard to the significant
determinants of capital structure. This may be because of variations in the use of
long-term versus short-term debt or because of institutional differences that exist
between developed and developing countries.
The lack of consensus among researchers regarding the factors that influence the
capital structure decisions and diminutive research to describe the financing behavior of
Pakistani firms are few reasonsthathave evoked the need for this research. We hope that
findings of this empirical study will not only fill this gap but also provide some
groundwork upon which a more detailed evaluation could be based.
The rest of the paper is structured as follows. In Section 2, the most prominent
theoretical and empirical findings are surveyed. In Section 3, the potential determinants
of capital structure are summarized, and theoretical and empirical evidence concerning
these determinants are provided. Section 4 is the empirical part of the paper which
describes the data and methodology employed in this study. Section 5 is devoted to
results and discussion, and finally Section 6 presents the conclusions of this study.
2. Review of capital structure theories
The modern theory of capital structure was developed by Modigliani and Miller (1958).
They proved that the choice between debt and equity financing has no material effects
on the firm value, therefore, management of a firm should stop worrying about the
proportion of debt and equity securities because in perfect capital markets any
combination of debt and equity securities is as good as another. However, Modigliani
and Miller’s debt irrelevance theorem is based on restrictive assumptions which do not
hold in reality, when these assumptions are removed then choice of capital structure
becomes an important value-determining factor. For instance, considering taxes in their
analysis Modigliani and Miller (1963) proposed that firms should use as much debt
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3. as possible due to tax-deductible interest payments. Moreover, the value of a levered
firm exceeds that of an unlevered firm by an amount equal to the present value of the tax
savings that arise from the use of debt.
Miller (1977) has presented an alternative theory by incorporating three different tax
rates in his analysis (corporate tax rate, personal tax rate on equity income, and the
regular personal tax rate which applies to interest income). Miller proposed that net tax
savings from corporate borrowings can be zero when personal as well as corporate taxes
are considered. Since interest income is not taxed at the corporate level but taxed at the
personal level, whereas equity income is taxed at the corporate level but may largely
escape personal taxes when it comes in the form of capital gains. So the effective personal
tax rate on equity income is usually less than the regular personal tax rate on interest
income. This factor reduces the advantage of debt financing. In Miller’s analysis, the
supply of corporate debt expands as long as the corporate tax rate exceeds the personal
tax rate of investors absorbing the increased supply. The level of supply which equates
these two tax rates establishes an optimal debt ratio.
In contrast to the tax benefits on the use of debt finance DeAngelo and Masulis (1980)
proposed that companies have ways other than the interest on debt to shelter income
such as depreciation, investment tax credits, tax loss carry forwards, etc. The benefit
of tax shields on interest payments encourages firms to take on more debt, but also
increasestheprobabilitythatearningsinsomeyearsmaynotbesufficienttooffsetalltax
deductions. Therefore, some of them may be redundant including the tax deductibility of
interest payments. So firms with large non-debt tax shields relative to their expected
cash flow include less debt in their capital structure. This view suggests that non-debt
tax shields are the substitute of the tax shields on debt finance, and therefore, the
relationship between non-debt tax shields and leverage should be negative.
Although the benefit of tax shields mayencourage the firms toemploy more debt than
other external sources available to them, this mode of finance is not free from costs. Two
potential costs, namely, the bankruptcy costs and the agency costs are associated with
this source of finance. Bankruptcy is merely a legal mechanism allowing the creditors to
take over when the decline in the value of assets triggers a default. Thus, bankruptcy
costs are the costs of using this mechanism. The costs of bankruptcy discussed in the
literature are of two kinds: direct and indirect. Direct costs include fees of lawyers and
accountants, other professional fees, the value of the managerial time spent in
administering the bankruptcy. Indirect costs include lost sales, lost profits, and possibly
the inability of a firm to obtain credit or to issue securities except under especially
unfavorable terms. While analyzing the data of 11 railroad bankruptcies which occurred
between 1930 and 1955, Warner (1977) observed that the ratio of direct bankruptcy costs
to the market value of the firm appeared to fall as the value of the firm increased. The cost
of bankruptcy is on the average about 1 percent of the market value of the firm prior to
bankruptcy. Furthermore, direct costs of bankruptcy, such as legal fees,seem to decrease
as a function of the size of the bankrupt firm. Thus, these findings suggest that direct
bankruptcy costs are lessimportantforcapital structuredecisionsoflarge firms. Inorder
to investigate the impact of both direct and indirect bankruptcy costs, Altman (1984)
collected the data related to retail and industrial firms’ failure in the USA. Altman
observed that bankruptcy costs are not trivial. In many cases, bankruptcy costs
exceeded 20 percent of the value of the firm measured just before the bankruptcy and
even in some cases measured several years before. On average, bankruptcy costs ranged
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4. from 11 to 17 percent of the firm value up to three years before the bankruptcy. Moreover,
bankruptcy gobbles up a larger fraction of the assets’ value for small companies than for
large ones. These findings suggest that the financial distress costs differ with respect to
the size of the firm and are relevant in determining the capital structure of the firm.
The use of debt in the capital structure of a firm also leads to agency costs. The
agency costs refer to the costs generated as the result of conflicts of interest. Therefore,
agency costs stem as a result of the relationships between managers and shareholders,
and those between debt holders and shareholders (Jensen and Meckling, 1976). Conflicts
between managers and shareholders arise because managers hold less than 100 percent
of the residual claim. Owing to this, managers may invest less effort in managing the
firm’s resources and may be able to transfer the firm’s resources for their own personal
benefits. The managers bear the entire costs of refraining from these activities, but
capture only a fraction of the gain. As a result, managers overindulge in these pursuits
relative to the level that would maximize the firm’s value. This inefficiency is reduced
when a large fraction of the firm’s equity is owned by the managers.
According to Myers (2001), conflicts between debt holders and shareholders only
arise when there is a risk of default. If debt is totally free of default risk, debt holders have
no interest in the income and the value or risk of the firm. However, if the chance of
default is significant and managers also act in the interest of shareholders, then
shareholders can attain benefits at the expense of debt holders. The managers can bring
into play numerous options while transferring value from debt holders to shareholders.
For instance, managers can invest funds in riskier assets. The managers can borrow
more and pay out cash to shareholders. The managers can cut back equity-financed
capital investments. Finally, the managers may postpone immediate bankruptcy or
reorganization by obscuring financial problems from the creditors. However, debt
holders might also be aware of these temptations and strive to confine the opportunistic
behavior of managers by writing the debt contracts accordingly.
Bankruptcy and financial distress costs and agency costs constitute the basics of the
trade-offtheory.The trade-offtheory statesthatfirmsborrow uptothepointwherethe tax
savings from an extra dollar in debt are exactly equal to the costs that come from the
increased probability of financial distress. Under the trade-off theory framework, a firm is
viewed as setting a target debt to equity ratio and gradually moving toward it which
indicates that some form of optimal capital structure exist that can maximize the firm
value.Thetrade-offtheoryhasstrongpracticalappeal.Itrationalizesmoderatedebtratios.
It is also consistent with certain obvious facts, for instance, companies with relatively safe
tangible assets tend to borrow more than companies with risky intangible assets.
An alternative to trade-off theory is the pecking order theory of Myers and Majluf
(1984) and Myers (1984). The pecking order theory is based on two prominent
assumptions. First, the managers are better informed about their own firm’s prospects
than are outside investors. Second, managers act in the best interests of existing
shareholders. Under these conditions, a firm will sometimes forgo positive net present
value projects if accepting them forces the firm to issue undervalued equity to new
investors. This in turn provides a rationale for firms to value financial slack, such as
large cash and unused debt capacity. Financial slack permits the firms to undertake
projects that might be declined if they had to issue new equity to investors. More
specifically, pecking order theory predicts that firms prefer to use internal financing
when available and choose debt over equity when external financing is required.
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5. In summary, the trade-off theory underlines taxes while the pecking order theory
emphasizes on asymmetric information.
Another important conditional theory of capital structure is the theory of free cash
flow which states that high leverage leads to a rise in the value of a firm despite the threat
of financial distress, when a firm’s operating cash flow exceeds its profitable investment
opportunities (Myers, 2001). Conflicts between shareholders and managers over payout
policies are especially severe when a firm generates free cash flow. The problem is how
to motivate the managers to distribute the free cash among the shareholders instead of
investing it at below the cost of capital or wasting it on organizational inefficiencies.
According to Jensen (1986), debt can be used as a controlling device that commits the
managers to pay out free cash among shareholders that cannot be profitably reinvested
inside the firm. Grossman and Hart (1982) observed that debt can create an incentive for
managers to work harder, consume fewer perquisites, make better investment decisions,
etc. when bankruptcy is costly for them, perhaps they may lose the benefits of control
and reputation. These findings suggest that a high debt ratio may be dangerous for a
firm, but it can also add value by putting the firm on a diet.
Several studies have examined the empirical validity of the theories of capital
structure, but no consensus has been reached so far even within the context of developed
economies. This may be because of the fact that these theories differ in their emphasis,
for example, the trade-off theory emphasizes taxes, the pecking order theory emphasizes
differences in information, and the free cash flow theory emphasizes agency costs. Thus,
there is no universal theory of debt-equity choice and no reason to expect one (Myers,
2001). However, there are several useful conditional theories that can provide support in
understanding the financing behavior of firms.
3. Determinants of capital structure
This section briefly explains the attributes, suggested by the different conditional theories
of capital structure (as explained above), which may affect the firm’s capital structure
decisions. These attributes are denoted as profitability, size, non-debt tax shields,
tangibility (asset structure), growth opportunities, earnings volatility, and liquidity. The
attributesandtheirrelationshiptotheoptimalcapitalstructurechoicearediscussedbelow.
Profitability
The trade-off theory suggests a positive relationship between profitability and leverage
because high profitability promotes the use of debt and provides an incentive to firms to
avail the benefit of tax shields on interest payments. The pecking order theory postulates
that firms prefer to use internally generated funds when available and choose debt over
equity when external financing is required. Thus, this theory suggests a negative
relationship between profitability (a source of internal funds) and leverage. Several
empirical studies have also reported a negative relationship between profitability and
leverage (Toy et al., 1974; Titman and Wessels, 1988; Rajan and Zingales, 1995; Wald,
1999; Booth et al., 2001; Chen, 2004; Bauer, 2004; Tong and Green, 2005; Huang and Song,
2006; Zou and Xiao, 2006; Viviani, 2008; Jong et al., 2008; Serrasqueiro and Roga˜o, 2009).
Size
Several reasons are given in the literature concerning the firm size as an important
determinant of capital structure. For instance, Rajan and Zingales (1995) in their study
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6. of firms in G-7 countries observed that large firms tend to be more diversified and,
therefore, have lower probability of default. Rajan and Zingales’ argument is consistent
with the predictions of the trade-off theory which suggests that large firms should
borrow more because these firms are more diversified, less prone to bankruptcy, and
have relatively lower bankruptcy costs. Furthermore, large firms also have lower agency
costs of debt, for example, relatively lower monitoring costs because of less volatile cash
flow and easy access to capital markets. These findings suggest a positive relationship
between the firm size and leverage. On the other hand, the pecking order theory suggests
a negative relationship between firm size and the debt ratio, because the issue of
information asymmetry is less severe for large firms. Owing to this, large firms should
borrow less due to their ability to issue informationally sensitive securities like equity.
Empirical findings on this issue are still mixed. Wald (1999) has shown a significant
positive relationship between size and leverage for firms in the USA, the UK, and Japan
and an insignificant negative relationship for firms in Germany and a positive
relationship for firms in France. Chen (2004) has shown a significant negative
relationship between size and long-term leverage for firms in China. Several empirical
studies have reported a significant positive relationship between leverage and firm size
(Marsh, 1982; Bauer, 2004; Deesomsak et al., 2004; Zou and Xiao, 2006; Eriotis et al., 2007;
Jong et al., 2008; Serrasqueiro and Roga˜o, 2009).
Non-debt tax shields
Tax shields benefit on the use of debt finance may either be reduced or even eliminated
when a firm is reporting an income that is consistently low or negative. Consequently,
the burden of interest payments would be felt by the firm. DeAngelo and Masulis (1980)
proposed that non-debt tax shields are the substitute of the tax shields on debt financing.
So firms with larger non-debt tax shields, ceteris paribus, are expected to use less debt
in their capital structure. Empirical findings are mixed on this issue. Bradley et al. (1984)
have shown a strong direct relationship between leverage and the relative amount of
non-debt tax shields. Titman and Wessels (1988) have found no support for an effect
on debt ratios arising from non-debt tax shields. Wald (1999) and Deesomsak et al. (2004)
reported a significant negative relationship between leverage and non-debt tax shields.
Viviani (2008) has shown a significant negative relationship only between short-term
debt ratio and non-debt tax shields. Bauer (2004) has shown a negative but less
significant relationship between non-debt tax shields and the measures of leverage.
Tangibility
Myers and Majluf (1984) argued that firms may find it advantageous to sell secured debt
because there are some costs associated with issuing securities about which the firm’s
managers have better information than outside shareholders. Thus, issuing debt
secured by the property with known values avoids these costs. This finding suggests a
positive relationship between tangibility and leverage because firms holding assets can
tender these assets to lenders as collateral and issue more debt to take the advantage of
this opportunity. Furthermore, the findings of Jensen and Meckling (1976) and Myers
(1977) suggest that the shareholders of highly leveraged firms have an incentive to
invest suboptimally to expropriate wealth from the firm’s debt holders. However, debt
holders can confine this opportunistic behavior by forcing them to present tangible
assets as collateral before issuing loans, but no such confinement is possible for those
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7. projects that cannot be collateralized. This incentive may also induce a positive
relationship between leverage and the capacity of a firm to collateralize its debt. Several
empirical studies have reported a positive relationship between tangibility and leverage
(Wald, 1999; Chen, 2004; Huang and Song, 2006; Zou and Xiao, 2006; Viviani, 2008;
Jong et al., 2008; Serrasqueiro and Roga˜o, 2009).
However, the tendency of managers to consume more than the optimal level of
perquisites may produce a negative correlation between collateralizable assets and
leverage (Titman and Wessels, 1988). The firms with less collateralizable assets
(tangibility) may choose higher debt levels to stop managers from using more than the
optimal level of perquisites. This agency explanation suggests a negative association
between tangibilityandleverage.Boothetal.(2001)havereporteda negativerelationship
between tangibility and leverage for firms in Brazil, India, Pakistan, and Turkey. Some
other empirical studies have also reported a negative relationship between tangibility
and leverage (Ferri and Jones, 1979; Bauer, 2004; Mazur, 2007; Karadeniz et al., 2009).
Growth opportunities
According to trade-off theory, firms holding future growth opportunities, which are a
form of intangible assets, tend to borrow less than firms holding more tangible assets
because growth opportunities cannot be collateralized. This finding suggests a negative
relationship between leverage and growth opportunities. Agency theory also predicts a
negative relationship because firms with greater growth opportunities have more
flexibility to invest suboptimally, thus, expropriate wealth from debt holders to
shareholders. In order to restrain these agency conflicts, firms with high growth
opportunities should borrow less. Several empirical studies have confirmed this
relationship,i.e.Deesomsaketal.(2004),ZouandXiao(2006)andEriotisetal.(2007).Wald
(1999) has shown that the USA is the only country where high growth is associated with
lower debt/equity ratio. This finding confirms the predictions of Myers’s (1977) model
that ongoing growth opportunities imply a conflict between debt and equity interests.
This conflict also causes the firms to refrain from undertaking net positive value projects.
Earnings volatility
Several empirical studies have shown that a firm’s optimal debt level is a decreasing
function of the volatility of its earnings. The higher volatility of earnings may indicate
the greater probability of a firm being unable to meet its contractual claims as they come
due. A firm’s debt capacity may also decrease with an increase in its earnings volatility
which suggests a negative association between earnings volatility and leverage. Various
empirical studies have shown a significant negative relationship between leverage
and earnings volatility (Bradley et al., 1984; Booth et al., 2001; Fama and French, 2002;
Jong et al., 2008).
Liquidity
The trade-off theory suggests that companies with higher liquidity ratios should borrow
more due to their ability to meet contractual obligations on time. Thus, this theory
predicts a positive linkage between liquidity and leverage. On the other hand, the
pecking order theory predicts a negative relationship between liquidity and leverage,
because a firm with greater liquidities prefers to use internally generated funds while
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8. financing new investments. A few empirical studies have shown their results consistent
with the pecking order hypothesis (Deesomsak et al., 2004; Mazur, 2007; Viviani, 2008).
4. Data and methodology
Data
This study investigates the determinants of capital structure for manufacturing firms,
listed on the Karachi Stock Exchange (KSE) Pakistan during 2003-2007, using the data
published by the State Bank of Pakistan (SBP). The data published by SBP provides
useful information on key accounts of the financial statements of all non-financial firms
listed on KSE[1]. Moreover, it allows for the calculation of many variables that are known
to be relevant from studies of firms in developed countries. The final sample, after
considering any missing data, consists of a balanced panel of 160 firms over a period of
five years. Firms under analysis represent the driving industrial force in Pakistan, and it
is expected that the sample may do well in capturing aggregate leverage in the country.
On the basis of research objectives of this study, variables used in this study and their
measurements are largely adopted from existing literature, for the meaningful
comparison of our findings with prior empirical studies in developed and developing
countries. The dependent variable is the debt ratio; the explanatory variables include
profitability, size, non-debt tax shields, tangibility, growth opportunities, earnings
volatility, and liquidity. Their definitions are listed in Table I. All the variables are
measured using book values because the data employed in this study come from
financial statements only.
This study used the debt ratio as a measure of leverage, defined as book value of total
debt divided by the book value of total assets. The total debt is the sum of short-term and
long-term debt. Although, the strict notion of capital structure refers exclusively to
long-term debt, we have included short-term debt as well because of its significant
proportion in the make up of total debt. On average short-term debt represents 76 percent
of the total debt employed by the companies included in our sample[2]. The profound
dependenceofPakistanifirmsonshort-termdebtconfirmsthefindings ofDemirguc-Kunt
and Maksimovic (1999) that a major difference between developing and developed
countriesisthatdevelopingcountrieshavesubstantiallyloweramountsoflong-termdebt.
Variables Definition
Dependent variable
Debt ratio (DRit) Ratio of total debt to total assets
Explanatory variables
Profitability (PROFit) Ratio of net profit before taxes to total assets
Size (SIZEit) Natural logarithm of sales
Non-debt tax shields (NDTSit) Ratio of depreciation expense to total assets
Tangibility (TANGit) Ratio of net-fixed assets to total assets
Growth opportunities (GROWit) Ratio of sales growth to total assets growth (due to the absence of
data related to advertising expense, research and development
expenditures, and market-to-book ratio)
Earnings volatility (EVOLit) Ratio of standard deviation of the first difference of profit before
depreciation, interest, and taxes to average total assets
Liquidity (LIQit) Ratio of current assets to current liabilities
Table I.
Definition of variables
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9. Methodology
This study employed panel data procedures because sample contained data across firms
and overtime. The use of panel data increases the sample size considerably and is more
appropriate to study the dynamics of change. In order to estimate the effects of
explanatory variables on the debt ratio (a measure of leverage), we used three estimation
models, namely, pooled ordinary least squares (OLS), the random effects, and the fixed
effects. Under the hypothesis that there are no groups or individual effects among the
firms included in our sample, we estimated the pooled OLS model.
Since panel data contained observations on the same cross-sectional units over
several time periods there might be cross-sectional effects on each firm or on a set of
group of firms. Several techniques are available to deal with such type of problem but
two panel econometric techniques, the fixed and the random effects models, are very
important. The fixed effects model takes into account the individuality of each firm or
cross-sectional unit included in the sample by letting the intercept vary for each firm but
still assumes that the slope coefficients are constant across firms. The random effects
model estimates the coefficients under the assumption that the individual or group
effects are uncorrelated with other explanatory variables and can be formulated. This
study also employed the Hausman (1978) specification test to determine which
estimation model, either fixed or random effects, best explains our estimation.
The description of three estimation models – pooled OLS, the fixed effects, and the
random effects – is given below:
DRit ¼ b0 þ b1PROFit þ b2SIZEit þ b3NDTSit þ b4TANGit þ b5GROWit
þ b6EVOLit þ b7LIQit þ 1it
DRit ¼ b0i þ b1PROFit þ b2SIZEit þ b3NDTSit þ b4TANGit þ b5GROWit
þ b6EVOLit þ b7LIQit þ mit
DRit ¼ b0 þ b1PROFit þ b2SIZEit þ b3NDTSit þ b4TANGit þ b5GROWit
þ b6EVOLit þ b7LIQit þ 1it þ mit
where:
DRit ¼ debt ratio of firm i at time t.
PROFit ¼ profitability of firm i at time t.
SIZEit ¼ size of firm i at time t.
NDTSit ¼ non-debt tax shields of firm i at time t.
TANGit ¼ tangibility of firm i at time t.
GROWit ¼ growth opportunities of firm i at time t.
EVOLit ¼ earnings volatility of firm i at time t.
LIQit ¼ current ratio of firm i at time t.
b0 ¼ common y-intercept.
b1-b7 ¼ coefficients of the concerned explanatory variables.
1it ¼ stochastic error term of firm i at time t.
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10. b0i ¼ y-intercept of firm I.
mit ¼ error term of firm i at time t.
1i ¼ cross-sectional error component.
5. Empirical results and discussions
Empirical results
This section presents the various estimation results and discusses the implications of the
empirical findings. The summary statistics of the dependent and explanatory variables
over the sample period are presented in Table II, reflecting the capital structures of the
analyzed firms. The debt ratio indicates that 60.78 percent of the firms’ assets are
financed with total debt during the study period. This ratio, in comparison with firms in
G-7 and developing countries, indicates that Pakistani firms seem to be more leveraged
(Table III) than those in the Canada, the UK, the USA, Brazil, Jordan, Malaysia, Mexico,
Variables Observations Mean SD Minimum Maximum
DRit 800 0.607852 0.156759 0.115851 0.891286
PROFit 800 0.055274 0.110648 21.001851 1.240773
SIZEit 800 7.376455 1.178565 1.435085 11.01449
NDTSit 800 0.038546 0.032315 0.000699 0.201533
TANGit 800 0.518880 0.190491 0.020310 0.926522
GROWit 800 20.165196 72.85970 21705.662 1,008.796
EVOLit 800 0.547126 1.006701 0.008834 9.821189
LIQit 800 1.148879 0.665056 0.157232 6.666245
Table II.
Summary statistics
Country No. of firms Time period Total debt ratio (%)
Developing countries data
Brazil 49 1985-1991 30.3
India 99 1980-1990 67.1
Jordan 38 1983-1990 47.0
Malaysia 96 1983-1990 41.8
Mexico 99 1984-1990 34.7
South Korea 93 1980-1990 73.4
Thailand 64 1983-1990 49.4
Turkey 45 1983-1990 59.1
Zimbabwe 48 1980-1988 41.5
G-7 countries data
Canada 318 1991 56.0
France 225 1991 71.0
Germany 191 1991 73.0
Italy 118 1991 70.0
Japan 514 1991 69.0
UK 608 1991 54.0
USA 2580 1991 58.0
Source: Data of debt ratios of firms in developing countries are adopted from Booth et al. (2001),
whereas data of debt ratios of firms in G-7 countries are taken from Rajan and Zingales (1995)
Table III.
Debt ratios
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11. Thailand, Turkey, and Zimbabwe, while less leveraged than those in the France,
Germany, Italy, Japan, India, and South Korea. This comparison indicates that on
average Pakistani firms show similar financing behavior as observed for firms in
developing and G-7 countries.
Prior to estimating the coefficients of the model, the sample data were also tested for
multicollinearity. Results are presented in Table IV, which show that most
cross-correlation terms for the explanatory variables are fairly small, thus giving no
causeforconcern about the problem ofmulticollinearity among the explanatory variables.
Under the hypothesis that there are no groups or individual effects among the firms
included in our sample, we estimated the pooled OLS model. The estimation results are
presented in Table V, which indicates that profitability, size, non-debt tax shields,
tangibility, and liquidity proved to be significant in confidence level of 5 percent.
Earnings volatility found less significant while the variable growth opportunities found
highly insignificant. The OLS regression has high adjusted R 2
and appears to be able to
explain variations in the debt ratio. Furthermore, the F-statistic confirms the
significance of the OLS regression model.
Since our sample contained data across firms and overtime there might be
cross-sectional effects on each firm or on a set of group of firms. In order to deal with
those effects, two panel econometric techniques, namely, the fixed effects and random
effects estimation models, are employed. Results of these estimation models
are presented in Tables VI and VII. Under both estimations models profitability, size,
Variables DRit PROFit SIZEit NDTSit TANGit GROWit EVOLit LIQit
DRit 1.0000
PROFit 20.3222 1.0000
SIZEit 0.1382 0.2054 1.0000
NDTSit 20.0739 20.0281 20.0391 1.0000
TANGit 0.0692 20.3182 20.2681 0.1841 1.0000
GROWit 20.0195 0.0082 20.0134 20.0310 0.0005 1.0000
EVOLit 20.2316 0.0722 20.6007 0.0917 20.0154 0.0078 1.0000
LIQit 20.6302 0.3929 0.1351 20.0703 20.5182 0.0276 0.1014 1.0000
Table IV.
Pearson correlation
coefficient matrix
Variables Coefficient SE t-statistic Prob.
C 0.825937 0.040538 20.37416 0.0000
PROFit 20.223053 0.038392 25.809910 0.0000
SIZEit 0.020456 0.004402 4.647338 0.0000
NDTSit 20.299191 0.119903 22.495272 0.0128
TANGit 20.263211 0.024567 210.71404 0.0000
GROWit 7.17 £ 102 6
5.18 £ 102 5
20.138361 0.8900
EVOLit 20.007898 0.004972 21.588466 0.1126
LIQit 20.177752 0.000694 225.58635 0.0000
Notes: R 2
¼ 0.541291; mean dependent variable ¼ 0.607853; adjusted R 2
¼ 0.537236; SD- dependent
variable ¼ 0.156759; SE of regression ¼ 0.106638; sum of squared residual ¼ 9.006391;
F-statistic ¼ 133.5120; Prob. . F-statistic ¼ 0.000000
Table V.
The effect of explanatory
variables on the debt
ratio (DRit) using the OLS
estimation model
Determinants
of capital
structure
127

12. tangibility, earnings volatility, and liquidity proved to be significant with a confidence
level of 5 percent. Non-debt tax shields proved significant only under the random effects
estimation model. Growth opportunities remained highly insignificant under both
estimation models. The adjusted R 2
for the fixed effects estimation model is higher than
for the simple pooling model, indicating the existence of the omitted variables.
The results of the Hausman specification test are reported in Table VIII. The test is
asymptotically x 2
distributed with 7 df. Results indicate that the null hypothesis is
rejected and we may be better off using the estimation of the fixed effects model.
Variables Coefficient SE t-statistic Prob.
C 0.775204 0.049631 15.61935 0.0000
PROFit 20.165676 0.032329 25.124703 0.0000
SIZEit 0.020262 0.005608 3.612828 0.0003
NDTSit 20.192198 0.094844 22.026479 0.0431
TANGit 20.246056 0.030305 28.119214 0.0000
GROWit 23.14 £ 102 6
3.91 £ 1025
20.080284 0.9360
EVOLit 20.013829 0.006345 22.179607 0.0296
LIQit 20.143623 0.007102 220.22313 0.0000
Notes: R 2
¼ 0.392376; SE of regression ¼ 0.075322; adjusted R 2
¼ 0.387006; sum of squared
residual ¼ 4.493354; F-statistic ¼ 73.06263; Prob. . F-statistic ¼ 0.000000
Table VII.
The effect of explanatory
variables on the debt ratio
(DRit) using the random
effects estimation model
Variables Coefficient SE t-statistic Prob.
C 0.696930 0.067591 10.31093 0.0000
PROFit 20.149226 0.034256 24.356266 0.0000
SIZEit 0.031443 0.008405 3.741148 0.0002
NDTSit 20.134187 0.098235 21.365980 0.1724
TANGit 20.302437 0.043316 26.982158 0.0000
GROWit 21.10 £ 102 6
4.00 £ 1025
20.027499 0.9781
EVOLit 20.021170 0.009192 22.303169 0.0216
LIQit 20.121057 0.008192 214.77790 0.0000
Notes: R 2
¼ 0.825745; SE of regression ¼ 0.073519; adjusted R 2
¼ 0.780047; sum of squared
residual ¼ 3.421363; F-statistic ¼ 18.06989; Prob. . F-statistic ¼ 0.000000
Table VI.
The effect of explanatory
variables on the debt ratio
(DRit) using the fixed
effects estimation model
Variables Fixed effects Random effects Var. (Diff.) Prob.
PROFit 20.149226 20.165676 0.000128 0.1464
SIZEit 0.031443 0.020262 0.000039 0.0741
NDTSit 20.134187 20.192198 0.000655 0.0234
TANGit 20.302437 20.246056 0.000958 0.0685
GROWit 20.000001 20.000003 0.000000 0.6038
EVOLit 20.021170 20.013829 0.000044 0.2697
LIQit 20.121057 20.143623 0.000017 0.0000
Notes: Wald x 2
(7 df) ¼ 46.333298; Prob. . x 2
¼ 0.0000000
Table VIII.
Fixed and random effects
test comparison
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13. Discussion
According to empirical findings, profitability and liquidity have a negative and
significant relationship with the debt ratio, which confirms that firms finance their
activities following the financing pattern implied by the pecking order theory. Moreover,
high cost of raising funds might also restrict the Pakistani firms to rely on internally
generated funds because of relatively limited equity markets combined with lower levels
of trading. This finding also confirms that information asymmetry is especially relevant
in the capital structure decisions of the firms listed on KSE.
The variable size has a positive and significant impact on the debt ratio. This finding
is consistent with the implications of the trade-off theory suggesting that larger firms
should operate at high debt levels due to their ability to diversify the risk and to take the
benefit of tax shields on interest payments. The estimated coefficient of earnings
volatility has the predicted negative sign and is statistically significant. This finding
confirms the predictions of the trade-off theory which suggests that firms with less
volatile earnings should operate at high debt levels due to their ability to satisfy their
contractual claims on due date. Pakistani firms mainly rely on bank debt because of
small and undeveloped bond market. Furthermore, majority of these banks are
privatized and disinclined to issue loans on favorable terms particularly to firms with
volatile earnings. For this reason, firms with volatile earnings borrow less. This study
shows contradictory results concerning the variable non-debt tax shields. The total and
random effects estimation models accept this variable but the fixed effects model does
not. This controversy suggests that further analysis with a comprehensive data set
would be a promising area for future study. Growth opportunities found to be highly
insignificant in all estimation models.
Theoretically, the expected relationship between the debt ratio and tangibility (asset
structure) is positive. However, based on the results of this study, the relationship is
negative. Some empirical studies for developing countries, i.e. Booth et al. (2001), Bauer
(2004), Mazur (2007) and Karadeniz et al. (2009), have shown a negative relationship,
whereas empirical studies for developed countries have reported a positive relationship
between tangibility and leverage, include Titman and Wessels (1988) Rajan and
Zingales (1995) and Wald (1999). Although this result does not sit well with the trade-off
hypothesis, which suggests that companies with relatively safe tangible assets tend to
borrow more than companies with risky intangible assets. However, this finding is
consistent with the implications of the agency theory suggesting that the tendency of
managers to consume more than the optimal level of perquisites may produce an inverse
relationship between collateralizable assets and the debt levels (Titman and Wessels,
1988). The pecking order theory also predicts a negative relationship between tangibility
and short-term debt ratio (Karadeniz et al., 2009).
Although manufacturing firms in Pakistan heavily rely on short-term debt either
because of small and undeveloped bond market or due to high-cost long-term bank debt.
However, it is difficult to be certain that this negative relationship is the outcome of
profound dependency of firms on short-term debt, because short-tem debt ratio is not
employed independently in this study as an explained variable. This negative
relationship may possibly be the outcome of excessive liquidity maintained by the firms
which encourage managers to consume more than the optimal level of perquisites.
Consequently, firms with less collateralizable assets may choose higher debt levels to
limit their managers’ consumption of perquisites.
Determinants
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14. The agency explanation seems to be more valid for firms in Pakistan due to the fact
that firms uphold excessive liquidity that may encourage managers to consume more
than the optimal level of perquisites.
In summary, the difference in long-term versus short-term debt is much pronounced
in Pakistan; this might limit the explanatory power of the capital structure models
derived from Western settings. However, the results of this empirical study suggest that
some of the insights from modern finance theory are portable to Pakistan because
certain firm-specific factors that are relevant for explaining capital structures in
developed countries are also relevant in Pakistan.
6. Conclusions
This empirical study attempted to explore the determinants of capital structure of
160manufacturing firmslistedon the KSEPakistan during2003-2007.The investigation
is performed using panel econometric techniques, namely, pooled OLS, fixed effects, and
random effects. This study has employed the debt ratio (a measure of leverage) as an
explained variable. The debt ratio includes both long-term and short-term debt.
Although, the strict notion of capital structure refers exclusively to long-term debt, we
have includedshort-term debt as well becauseof its significant proportion in themake up
of total debt of the firms included in our sample.
Accordingtothe resultsofempiricalanalysis, profitabilityandliquidity arenegatively
correlatedwiththedebtratio.Thisfindingisconsistentwiththepeckingorderhypothesis
rather than with the predictions of the trade-off theory. The firm size is positively
correlated with the debt ratio. This finding supports the view of firm size as an inverse
proxy for the probability of bankruptcy. The debt ratio is negatively correlated with
earnings volatility, which is consistent with theoretical underpinnings of the trade-off
theory. The tangibility (asset structure) is negatively correlated with the debt ratio. This
finding is in contradiction with the predictions of the trade-off theory; however, it is in line
with the implications of the agency theory suggesting that firms with less collateralizable
assets may choose higher debt levels to limit the managers’ consumptions of perquisites.
Moreover, a significant negative impact of liquidity on the debt ratio indicates that firms
maintainedexcessiveliquiditywhichmayencouragemanagerstoconsumemorethanthe
optimal level of perquisites. Consequently, firms with less collateralizable assets borrow
more to confine the opportunistic behavior of the managers. Contradictory results are
found concerning the variable non-debt tax shields. The total and random effects model
accepts this variable with a negative sign but the fixed effects model does not.
No significant relationship is found between the debt ratio and growth opportunities.
Finally, the difference in long-term versus short-term debt might limit the
explanatory power of the capital structure models derived from Western settings.
However, the results indicate that these models provide some help in understanding the
financing behavior of Pakistani firms.
Notes
1. The publication entitled “Balance Sheet Analysis of Joint Stock Companies listed on Karachi
Stock Exchange 2002 2 2007” is prepared by the SBP on the basis of information given in the
annual reports, made by the companies at the end of each accounting period. This is
mandatory for every public limited company to make financial statements in accordance with
theapproved accountingstandards as applicable inPakistan.Approved accountingstandards
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15. comprise of such International Financial Reporting Standards issued by the International
Accounting Standard Board as are notified under the Companies Ordinance 1984.
2. The total debt is the sum of long-term and short-term debt. On average long-term debt
represents 24 percent while short-term debt represents 76 percent of the total debt employed
by the companies included in our sample. The reasons for heavy dependence of firms on
short-term debt include relatively high cost of long-term bank loans, and a limited and
undeveloped bond market in Pakistan.
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About the authors
Nadeem Ahmed Sheikh is a Senior Lecturer of Accounting and Finance at the Institute of
Management Sciences, Bahauddin Zakariya University, Multan, Pakistan. At present, he is
enrolled as Doctoral degree candidate, in the programme of Business Administration (Finance), in
School of Management, Huazhong University of Science and Technology, Wuhan (Hubei) People’s
Republic of China. He earned the degree of Bachelor of Commerce (BCom) in 1996 from
Government College of Commerce, Multan, Pakistan. He stood first in BCom Examination and
Bahauddin Zakariya University awarded him a Gold Medal in 1997. He has earned the degree of
Master in Business Administration (Finance) in 1999. He secured third position in finance
specialization and Department of Business Administration awarded him a Certificate of Honor. In
year 2000, on account of his excellent academic credentials, he attained a position as Lecturer of
Accounting and Finance at Department of Business Administration, Bahauddin Zakariya
University. In 2005, Bahauddin Zakariya University has recommended him for Star Excellence
Award (awarded by South Asia Publications) as a result of his ranking as the best teacher in the
institute. Nadeem Ahmed Sheikh is the corresponding author and can be contacted at:
shnadeem@hotmail.com
Zongjun Wang is University Professor at Huazhong University of Science and Technology,
Wuhan, People’s Republic of China. He is the Director of the Department of Management Sciences
and Technology, and the Director of the Institute of Enterprise Evaluation. He is also the Assistant
Dean of the School of Management. Zongjun Wang has earned his Bachelor degree in Computer
Science in 1985 from Beijing Institute of Technology, Beijing, China. He has earned the degree of
Doctor of Philosophy in System Engineering in 1993 from Hauzhong University of Science and
Technology, Wuhan, People’s Republic of China. He joined the Arizona State University as a
Senior Visiting Scholar during 2004-2005 under the assistanceship of Fulbright Foundation, USA
and the Montreal University, Canada in 2001 as a senior fellow. He has published more than
150 articles in different journals (Chinese and international journals) related to the field of system
engineering, integrated evaluation methodology and applications, corporate governance,
management, corporate finance, etc.
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