itiri, idam okpara idam okpara... · model to test the hypotheses of the study. financial structure...
TRANSCRIPT
Ugboaku, Edith J
FACULTY OF
PERFORMANCE OF QUOTED FIRMS IN NIGERIA
Digitally Signed by: Content manager’s
DN : CN = Webmaster’s name
O = University of Nigeria, Nsukka
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boaku, Edith J.
FACULTY OF BUSINESS ADMINIS
DEPARTMENT OF DEPARTMENT OF DEPARTMENT OF DEPARTMENT OF BANKINGBANKINGBANKINGBANKING AAAANNNNDDDD FFFFIIIINNNNAAAA
IMPACT OF FINANCIAL STRUCTURE ON THE
PERFORMANCE OF QUOTED FIRMS IN NIGERIA
ITIRI, IDAM OKPARA
PG/M.Sc/10/55102
i
: Content manager’s Name
Webmaster’s name
a, Nsukka
STRATION
AAAANNNNCCCCEEEE
IMPACT OF FINANCIAL STRUCTURE ON THE
PERFORMANCE OF QUOTED FIRMS IN NIGERIA
ii
IMPACT OF FINANCIAL STRUCTURE ON THE PERFORMANCE OF QUOTED
FIRMS IN NIGERIA
BY
ITIRI, IDAM OKPARA
PG/M.Sc/10/55102
DEPARTMENT OF BANKING AND FINANCE
FACULTY OF BUSINESS ADMINSITRATION
UNIVERSITY OF NIGERIA
ENUGU CAMPUS
NOVEMBER, 2014
iii
IMPACT OF FINANCIAL STRUCTURE ON THE PERFORMANCE OF QUOTED
FIRMS IN NIGERIA
BY
ITIRI, IDAM OKPARA
PG/M.Sc/10/55102
AN M.Sc. DISSERTATION PRESENTED TO THE
DEPARTMENT OF BANKING AND FINANCE
FACULTY OF BUSINESS ADMINSITRATION
UNIVERSITY OF NIGERIA
ENUGU CAMPUS
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF
MASTER OF SCIENCE DEGREE IN BANKING AND FINANCE
SUPERVISORS: ASSOC. PROF. E. CHUKE NWUDE
DR. B. E. CHIKELEZE
NOVEMBER, 2014
iv
APPROVAL PAGE
This is to certify that this Dissertation by Itiri Idam Okpara with registration number
PG/M.Sc/10/55102 is submitted to the Department of Banking and Finance in partial fulfillment
for the award of the Master of Science (M.Sc) degree of the University of Nigeria in Banking and
Finance.
........................................................... .........................
ASSOC. PROF. E. CHUKE NWUDE DATE
(SUPERVISOR)
.............................................................. ………………..
ASSOC. PROF. E. CHUKE NWUDE DATE
(HEAD OF DEPARTMENT)
v
DECLARATION
I, Itiri Idam Okpara, with registration number PG/M.Sc/10/55102 hereby affirm that this
dissertation is original and has not been submitted for the award of any degree or diploma either in
part of full in this or any other tertiary institution.
........................................ ...........................
Itiri Idam Okpara DATE
vi
DEDICATION
This Dissertation is dedicated to Almighty God.
vii
ACKNOWLEDGEMENTS
I wish to acknowledge the Almighty God, the Supreme Being for His help and inspiration in the
course of production of this research work. My sincere appreciation goes to my Supervisors;
Assoc. Prof. E. Chuke Nwude and Dr. B. E. Chikeleze for their mentoring, tireless and scrupulous
supervision which led to the successful completion of this Research Work. Also my
unquantifiable gratitude goes to the Head Department of Banking and Finance, Prof. J. U. J.
Onwumere, whom contributed immensely to the success of this work. Special thanks to Dr. B.
Onah, Dr A. Ujunwa, Dr. C. OKoyeuzu, Dr. N. Modebe and Dr. E. K. Agbaeze for directing and
energizing me. I must say a big appreciation to all academic and administrative staff of Banking
and Finance Department, University of Nigeria Enugu Campus.
My profound appreciation goes to librarian Nigerian Stock Exchange Abuja and Onitsha branch
for their co-operation extended to me during the course of the study.
My gratitude goes to my mother Mrs U. I. Okpara, my brothers; Dr. Chukwu I. Okpara, Mr. Okoh
I. Okpara, Mr. Azubuike I. Okpara, Engr. Martins I. Okpara, Mr. Okechukwu I. Okpara and also
my sister Mrs. Esther A. I. for their support, prayers and encouragement. May Almighty God
reward you abundantly.
I remain grateful to my mentors, friends and colleagues who have contributed immensurable to
completion of this study such as Dr. Eleje, Mr. Imoh, Mr. Charles, Mrs. Elizabeth, Mr. Frank, Mr.
Norbert, Mr. Cyril, Mrs Nwamaka, Kingsley, Ajufo, Chinasa, and among others. I am sincerely
grateful to you all for your support and prayers.
viii
ABSTRACT
Financial structure is financing decision undertaken by a firm on the course of funding its
corporate investment. This entails the combination of debt and equity capital to finance firm’s
assets. The impact of financial structure on firm performance has been ambiguous due to
extensive arguments from diverse perceptions. The subsisting empirical study to prove the
impact of debt and equity mix on firm performance in Nigeria is narrowed to capital structure
measures with established contradictory views inferred from the inconsistencies among their
findings. Thus, the results and conclusions on the studies may be misleading. Financial structure
measures have a better chance to acquiesce unbiased result, because of different empirical
implications in regard to different types of debt instruments. However, in underdeveloped debt
market peculiar to Nigeria, most firms’ external debt finance is majorly short term finance,
imposing extra burdens at very exorbitant costs on the firms. It is on the premise of the foregoing
arguments that this study sought to evaluate the impact of financial structure on the performance
of quoted firms in Nigeria. By examining the impact of : (i) total debt ratio on performance of
quoted firms in Nigeria, (ii) long term debt ratio on performance of quoted firms in Nigeria and
(iii) short term debt ratio on performance of quoted firms in Nigeria. The study adopted ex-post-
facto research design. Panel data collated from the annual reports of 51 sampled firms and
Nigeria Stock Exchange factbooks over a 12 year period (2001-2012) were employed. Data were
subjected to pool Ordinary Least Square (OLS), Fixed Effects, and Random Effects regression
model to test the hypotheses of the study. Financial structure proxied by total debt ratio (TDR),
long term debt ratio (LTDR) and short term debt ratio (STDR) were adopted as independent
variables. Firm performance as the dependent variable was proxied by return on asset (ROA).
Results emanating from the tests of the three hypotheses reveal that total debt ratio have
negative and significant (coefficient of TDR = -0.0776, p < 0.05) impact on the performance of
Nigerian quoted firms; Long term debt ratio have negative and significant (coefficient of LTDR
= -0.0479, p < 0.05) impact on the performance of Nigerian quoted firms; and short term debt
ratio have negative and significant (coefficient of STDR = -0.0804, p < 0.05) impact on the
performance of Nigerian quoted firms. Based on these findings, the study concludes that
financial structure is relevant in explaining variations in the performance of Nigerian quoted
firms. Accordingly, the study therefore recommends among other things that government should
pursue genuinely a policy measures targeted at developing the security market to ensure high
volume of corporate debt issue, liquidity of market and market efficiency in order to guarantee
easy mobilization and allocation of funds. As a strategy, they should aim at reviewing existing
restrictions which are detrimental to corporate debt issue and rather provide assistance in
raising long term capital via capital schemes and loan subsidies that will in turn drive market
interest rate of external debt capital. This will in turn drive positively the financial structure
decisions of firms’ agents.
ix
TABLE OF CONTENTS
Title Page ………………………………………………………………………………………….i
Declaration ………………………………………………………………………………………..ii
Approval …………………………………………………………………………………………iii
Dedication ………………………………………………………………………………………..iv
Acknowledgements ………………………………………………………………………………v
Abstract ………………………………………………………………………………………….vi
List of Tables ……………………………………………………….…………………………….x
List of Figures ……………………………………………………………………………………xi
CHAPTER ONE: INTRODUCTION
1.1 Background of the Study ……………………………………………………………….1
1.2 Statement of the Problem …………………………………………………………………4
1.3 Objectives of the Study …………………………………………………………………...5
1.4 Research Questions ……………………………………………………………………….6
1.5 Research Hypotheses ……………………………………………………………………..6
1.6 Scope of the Study …………………………………………………………………...…..6
1.7 Significance of the Study ………………………………………………………………...7
References …………………………………………………………….………………….8
CHAPTER TWO: LITERATURE REVIEW
2.1.1 Concept of Financial Leverage ……………………………....………………………….12
2.1.1.1 Total Debt Ratio ………………………………………………………………………...13
2.1.1.2 Debt Equity Ratio ……………………………………………………………………….13
2.1.1.3 Long Term Debt Ratio …………………………………………………………………..14
2.1.1.4 Short Term Debt Ratio …………………………………………………………………..14
2.1.1.5 Times Interest Earned Ratio …………………………………………………………….15
2.1.1.6 Fixed-Charge Coverage Ratio …………………………………………………………..16
2.1.2 Concept of firm Performance …………………………………………………………...16
2.1.2.1 Return on Assets ………………………………………………………………………..18
2.1.2.2 Return on Equity ………………………………………………………………………..18
2.1.2.3 Earnings per Share ………………………………………………………………………19
2.1.2.4 Tobin’s Q ………………………………………………………………………………..20
2.1.2.5 Price Earnings Ratio …………………………………………………………………….20
x
2.1.3 Theories of Financial Structure …………………………………………………………21
2.1.3.1 Modigliani – Miller Theorems ……………………………………………………..……21
2.1.3.2 Static Trade – off Theory ………………………………………………………..........…23
2.1.3.3 Dynamic Trade-off Theory …………………………………………………………..….25
2.1.3.4 Pecking Order Theory ………………………………………………………………..…26
2.1.3.5 Agency Cost Theory …………………………………………………………………….27
2.1.3.6 Signalling Hypothesis …………………………………………………………………...30
2.1.3.7 Neutral Mutation Hypothesis ……………………………………………….………...31
2.1.3.8 The Market Timing Theory ……………………………....………………………….….32
2.1.4 Determinants of financial Structure ………………………………….................................33
2.2 Empirical Review ……………………………………………..…………………….……….37
2.2.1 Financial Structure and Firm Performance ………………………………………………..37
2.2.2 Financial Structure and Tax Effect ………………………………………………………..42
2.3 Summary of Review of Related Literature …………………...……………………………..43
References ………………………………………………………….…………….………….46
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 Research Design …………………………………………………………………………55
3.2 Nature and Sources of Data ……………………………………………………………..55
3.3 Population and Sample Size ……………………………………………………………..55
3.4 Description of Research Variables ……………………………………………………....56
3.4.1 Dependent Variable ……………………………………………………..………………56
3.4.1.1 Return on Asset (ROA) ……………………………………...…………………………..57
3.4.2 Independent Variables ………………………………………………………………..…58
3.4.2.1 Total Debt Ratio (TDR) ………………………………………………..………...……58
3.4.2.2 Long Term Debt Ratio (LTDR) ……………………………………………………...….59
3.4.2.3 Short Term Debt Ratio (STDR)………………...………………………..………………59
3.4.3 Control Variables …………………………...…………...…………………………….…..60
3.4.3.1 Size of a Firm ………………………………………..………………………………..…60
3.4.3.2 Age of a Firm ………………………………………………..……………...……...……61
3.4.4 Random Variables (Stochastic)…………………..…………………………………...….61
3.5 Technique for Analysis ………………………………………….……………………....62
xi
3.6 Model Specification …………………………………………………..………...………63
References ………………………………………………………………………………64
CHAPTER FOUR: DATA PRESENTATION AND ANALYSIS
4.1 Data Presentation ……………………………………………..…………………………67
4.2 Data Analysis …………………………………………….…….………………………..75
4.2.1 Result of Correlation ……………………………………….……………......…………..75
4.3 Hypothesis Test ………………………………...…………….……….………..………..76
4.3.1 Hypothesis one …………………………………………………………………..………76
4.3.2 Hypothesis Two ……………………………………………………………….……...…78
4.3.3 Hypothesis Three ………………………………………………………………………..79
4.3.4 Discussion of Results ……………………………………………………………………81
4.4 Robustness Test …………………………………………………………………………82
References ……………………………………………………………………………….84
CHAPTER FIVE: SUMMARY OF FINDINGS, CONCLUSIONS, AND
RECOMMENDATIONS
5.1 Summary of Findings ……………………………………………………………………87
5.2 Conclusion ………………………………………………………………………………87
5.3 Recommendations ……………………………………………………………………….88
5.3.1 Recommendations for Selected Stakeholders ……………………………......………….88
5.3.2 Recommended areas for further research …………..……………………..…………….90
5.4 Contributions of the Findings of the Study ……………………………………………...91
References ……………………………………………………………………………….93
Bibliography …………………………………………………………………………….94
Appendix ……………………………………………………………………………….104
xii
LIST OF TABLES
Table 4.1.1 Summary of the Aggregate Value of Research Variables ………....……………67
Table 4.1.2 Summary of the Average Values of Research Variables ………………………..71
Table 4.1.3 Descriptive Statistics …………………………………………………………….74
Table 4.2 Pearson Correlation Matrix ……………………………………………………...74
Table 4.3.1 Regression Results of Hypothesis One ………………………………………….76
Table 4.3.2 Regression Results of Hypothesis Two …………………………………………78
Table 4.3.3 Regression Results of Hypothesis Three ………………………………………..79
Table 4.3.4 ROA vs Financial Structure Measures …………………………………………..80
Table 4.4 ROE vs Financial Structure Measures …………………………………………..82
xiii
LIST OF FIGURES
Figure 4.1.1 Graphical Presentation of the Summary of Aggregate Values of Research Variables ……...70
Figure 4.1.2 Graphical Presentation of the Summary of Average Values Research Variables ………….73
1
CHAPTER ONE
INTRODUCTION
1.1 Background of the Study
Financial structure is financing decision undertaken by a firm on the course of funding its
corporate investment. This entails the combination of debt and equity capital to finance firm’s
assets. The inherent risks in business environment has contributed to every corporate organization
aligning its’ financing decision towards achieving supreme objective. Abu-Rub (2012) contends
that financing decision vary according to the rate of risk related to each financing options as well
as the relationship between risk and return. Firm seek to adopt a mixed financial structure that
guarantees minimum cost to achieve the main goal of maximizing firm’s performance. The impact
of financial structure on performance of a firm has been ambiguous due to extensive debate from
diverse perceptions. The core argument among scholars is in two fold; irrelevance and relevance
theories of financial structure. The former argue that under very restrictive assumptions of perfect
capital markets, investors’ homogenous expectations, symmetric information and no bankruptcy
cost, financial structure does not determine performance of a firm. While, relevance theories with
imperfect capital markets assumptions have modeled and evidently revealed negative and positive
significant relationship between financial structure and performance of a firm (see for example,
Zeitun and Tian, 2007; Onaolapo and Kajola, 2010; Skopljak and Luo, 2012).
Nevertheless, Modigliani and miller (1958) argue that “the market value of any firm is independent
of its financing decision and is given by capitalizing its expected return..., and average cost of
capital to any firm is completely independent of its financing decision and is equal to the
capitalization rate of a pure stream of its class”. The unrealistic nature of MM propositions
coupled with their subsequent work in 1961 and 1963 triggered controversial arguments. This
however, spawned the interest of many scholars who looked at diverse dimension to examine the
effects of less restrictive assumptions on the relationship between financial structure and value of a
firm (Eriotis, 2007). Subsequent work of Miller (1977), presented a new challenge by pointing that
under certain conditions, the tax shield benefit of debt financing at the firm level is exactly off set
by the tax disadvantage of debt from personal income tax. Modigliani and Miller theorems
however, assumed that investors and firms have equal access to financial markets, which allows
for homemade leverage (Brealey and Myers, 1996). As argued, investors can create any leverage
2
they wanted but not offered, or the investors can get rid of any leverage that the firm took on but
was not wanted. Hence, firms’ leverage decisions do not influence its’ value (Afrasiobi and
Ahemadina, 2011). The advocates of Modigliani and Miller theorem have provided empirical
evidence that capital structure is insignificant (for example, Adelegan, 2007, pratheepkanth, 2011)
amongst others.
Conversely, most recently held theories with their varying predictions are evident in the world of
imperfect capital markets where internal and external capital is not perfectly substituted. Thus
relevance theories suggest that many factors such as tax effects, agency effects, bankruptcy costs,
signalling effects, market timing and asymmetric information influence financing decisions and in
turn the value of the firm (Jensen and Meckling, 1976; Myers and Mauflis, 1984; Myers, 1984;
Ross, 1977; Leland and Pyle, 1977; Kim et al., 1977; Fama, 1980 and Fama and French, 1998).
Specifically, these theories that have been advanced to explain the financial structure of firms
include the pecking order theory, tradeoff theory, the agency cost theory, signalling hypothesis,
market timing hypothesis, neutral mutation hypothesis, among other. Although various schools of
thought emphasize on different elements, it is probably fair to say that a consensus is emerging
(Kim and Babbel, 1995).
In this view, the key issues among the theories can be narrowed down to maximization of
shareholders’ value. The separation of ownership and control in a professionally managed firm as
assumed by agency cost theory may result in managers exerting insufficient work effort, indulging
in perquisites, choosing inputs or outputs that suit their own preferences, or otherwise failing to
maximize firm value (Jensen and Meckling, 1976). Consequently, the agency costs of outside
ownership equal the lost value from professional managers maximizing their own utility, rather
than the value of the firm. Theoretical body of knowledge suggests that the choice of financial
structure may help mitigate these agency costs. Debt finance act as a controlling tool to restrict the
opportunistic behaviour for personal gain by managers. It reduces the free cash flows with the firm
by paying fixed interest payments and forces managers to avoid negative investments and work in
the interest of shareholders. But if an investment yields large returns, shareholders capture most of
the gain. If, however, the investment fails, debt holders bear the consequences. As a result,
shareholders may benefit from investing in very risky projects, even if they are value-decreasing
“asset substitution effect” (Jensen and Meckling, 1976). Apparently, when leverage becomes
relatively high, further increases generate significant agency costs of outside debt; including higher
3
expected costs of bankruptcy or financial distress, arising from conflicts between bondholders and
shareholders. In the same view, trade-off theory advocates that firm leverage ratio is driven by
three competing forces such as tax benefits, bankruptcy cost and agency costs (Nosa and Ose, 2010
and Huang and Ritter, 2004). Also at high leverage the value of shareholders may not be enhanced
when restrictive covenants included in debt financing agreements limit the ability of firms to fully
harness the potentials of the firm’s resources (Onwumere et al., 2011). Thus firm maximize their
values by maximizing the use of debt. Regarding the possibility of financial structure influence on
firm performance due to agency costs and other cost of debt, several researchers have conducted
empirical studies that aim to examine the impact of financial structure on the firm performance
over the last decades (see Zeitun and Tian, 2007; Onaolapo and Kajola, 2010; Skopljak and Luo,
2012; Akbarpour and Aghabeygzadeh, 2011; Berger and Patti, 2002; Ebaid, 2009) among others.
The trade off theory states that in choosing leverage ratio, firms seek to balance the benefits of
debt against the potential costs of financial distress that is made more likely at high debt levels
(Bunn and Young, 2004). While, pecking order theory argued that firms do not try to reach the
“optimal” capital structure, as the trade-off theory claims, because firms employ least resistance
and least costly financing mix (Kasozi and Ngwenya, 2010). Thus, the latter gives no consideration
to any benefit accrued from the use of debt against bankruptcy cost but look at debt as alternative
due to insufficient internally generated funds. Also the pecking order theory assumes leverage ratio
to be negatively related to firm performance. This relationship has been confirmed in many
empirical works (see Lemmon and Zender, 2008; Onaolapo and Kajola, 2010). On the other hand,
the former assumes leverage ratios are positively related to firm performance, which also has been
confirmed in many empirical studies (see Sola, 2010; Nosa and Ose, 2010). However, signaling
theory states that managers have incentives to use various tools to send signals to the market about
the difference that exist between them and weaker firms. One of the key tools to send these signals
is the use of debt. Employment of debt in financing decision shows that managers have better
expectations about the future performance whereas equity sends a bad news about the firm
performance in the future. Thus, most of the arguments of relevancy theories are held on risks and
returns inherent in employment of each financing mix available to the firm. Conventionally, the
primary aim of financial structure decisions via employment of equity and debt is to maximize the
market value of a firm at minimal overall cost of capital (Khrawish and Khraiwesh, 2008). Hence,
utilization of different levels of debt and equity in the firm’s financial structure is one of the firm-
specific strategies used by managers in the search for improved performance.
4
Although, the assumptions of irrelevance theory is based on the perfect capital market, such as; no
taxes, rational investors, perfect competition, absence of bankruptcy costs and market efficiency.
This led to Modigliani and Miller (1958) argument that “in a world of sure returns, the distinction
between debt and equity funds reduces largely to one of the terminology”. Thus, whether a firm is
financed by debt or by equity, market value of any firm is independent of its financial structure.
But in the world of imperfect capital market that exists in reality, financial structure may be
relevant. The underlining argument of traditional theories of financial structure is underscored on
frictionless nature of MM theorem that holds the theory incomplete. Ross (1977) points “...if MM
theory is complete and thought to be correct, then capital structure is indeterminate or random in
actuality, and this a somewhat inhibiting basis on which to develop an explanation of financial
structure. One possible approach to the problem is to modify the MM theory to take account of the
structural features of the real world”. Ross (1977) stressed further that since interest payment on
debt are deductable in computing corporate income tax; the value of the firm should rise with the
substitution of debt for equity financing. Therefore, high profitability could be associated with high
target debt ratio, which may arise for a number of reasons such as potentially higher tax savings
from debt, lower probability of bankruptcy, and potentially higher overinvestment, and other
things equal (Hovakimian et al., 2004). The inherent unrealistic nature of MM theorem; and
subsequent work by Jensen and Meckling (1976) regarding the influence of financial structure on
firm performance due to agency costs of a firm and other factors has spawned numerous empirical
tests as highlighted earlier. Notwithstanding the importance of most of the underscored factors,
there is varied empirical evidence on the impact of financial structure on the performance of a firm
in Nigeria. Test of the agency theory typically regress measures of financial structure on firm
performance indicators and some control variables (Allen and Emilia, 2002). The researcher
therefore, will employ these measures on panel data regression models to examine the impact of
financial structure on the performance of Nigerian quoted firms using recent available data of
quoted firms to fill the research gap.
1.2 Statement of the Problem
The impact of financial structure decision on firm performance has been ambiguous due to
extensive arguments from diverse perceptions. The subsisting empirical studies to prove the impact
of debt and equity mix on firm performance in Nigeria is narrowed to capital structure measures
with established contradictory views inferred from the inconsistencies among their findings. Thus,
5
the results and conclusions on the studies may be misleading. For instance, Adelegan (2007)
demonstrated negative insignificant relations between firm performance and leverage. While,
survey on the impact of capital structure on the firm performance by Onaolapo and Kajola (2010)
established that capital structure has a negative and significant impact on the firm performance.
Also, in studying capital structure and performance in Nigerian petroleum industry, Dare and Sola
(2010) documented positive significant relationship between leverage ratio and corporate
performance.
Nevertheless, financial structure measures (total debt ratio, long term debt ratio, and short term
debt ratio, among others) have a better chance to acquiesce unbiased result, because of different
empirical implications in regard to different types of debt instruments. However, in
underdeveloped debt market peculiar to Nigeria, most firms’ external debt finance is majorly short
term finance, imposing extra burdens at very exorbitant costs on the firms. For example, Titman
and Wessels (1988) contend that significant results are good reason for adoption of different
measures of leverage ratios because some of the theories of financial structure have different
implications for not adopting the narrow definition of leverage ratios. Similarly, it is interesting to
differentiate short- term debt, long- term debt and total debt effects since they have different risk
and return profiles (Zuraidah, et al., 2012). This disclosure raises an important research question
on the effectiveness of financial structure, in enhancing performance of quoted firms in Nigeria.
To fill this important knowledge gap, this study therefore sought to examine the impact of
financial structure on the performance of Nigeria quoted firms by employing various measures of
financial structure.
1.3 Objective of the Study
In line with the research problems, the study sought to examine the impact of financial structure on
firm performance, using data from Nigerian quoted firms. The specific objectives of this study are
as follows; to
i. Ascertain the impact of total debt ratio on the performance of quoted Nigerian firms.
ii. Determine how long term debt ratio is impacting on the performance of quoted Nigerian firms.
iii. Examine the impact of short term debt ratio on the performance of quoted Nigerian firms.
6
1.4 Research Questions
Based on the specific objectives as highlighted in the study, the researcher postulates the following
research questions:
i. To what extent does total debt ratio influence performance of quoted firms in Nigeria?
ii. How does long term debt ratio impact on performance of quoted firms in Nigeria?
iii. To what extent does short term debt ratio impact on performance of quoted firms in
Nigeria?
1.5 Research Hypotheses
In order to achieve the objectives as highlighted in the study, the following hypotheses were
formulated;
i. Total debt ratio does not have positive and significant impact on firm performance.
ii. Long term debt ratio does not positively and significantly impact on firm performance.
iii. Short term debt ratio does not have positive and significant impact on firm performance.
1.6 Scope of the Study
This research work covered Nigerian quoted firms that fall within non financial sectors
classification. Hence, financial sector such as commercial banks, merchant banks, insurance
companies, and other specialized financial institutions are excluded in the study. The justification
for this is that financial sectors are highly regulated; there are restrictions placed on them by the
regulatory authorities, which in turn influence their financial structure relatively to performance.
This study covers the period 2001-2010. The year 2001 was chosen as the base year because it
was the year universal banking was introduced in the banking sector. Since bond markets are
underdeveloped and inactive, commercial banks and other financial institutions play an important
role in providing loans to Nigerian firms. This period, 2001- 2010 also witnessed some significant
policy reviews. Notable among the policy are resuscitating of Domestic Debt Market in 2003;
Personal Income Amendment Act, and Amendment of Companies Income Tax 2007 (Act No.11)
etc.
7
1.7 Significance of the Study
Empirical investigation on the relevance and irrelevance of financial structure on firm value has
been carried out in different jurisdictions by prominent financial economist. Their findings so far
have been significantly relevant to both learning and development. As observed by the researcher,
most studies in Nigeria are majorly on the impact of capital structure on the firm performance with
narrow definition of financial structure. This study sought to fill the research vacuum in Nigeria by
exploring the impact of financial structure on the performance of Nigerian quoted firms.
Consistently, this study will make robust contribution on the literature “financial structure and firm
performance”. It will also expose firms financing pattern and its impact on the financial
performance. To be precise this study will have immense benefit to the followings;
Financial Analyst
The study will aid financial analyst to infer the nature of equity and debt position of the sampled
firms and also reveal the risk of interest bearing assets. In turn, may enable decision makers to
restrained unwholesome practices in financing pattern of most firms when the analyst can establish
the real class of firm’s assets.
Investors and Firms
Investors are not left out to benefit from this study, as this would enable them to ascertain risk
nature of their investment in sampled firms’ financial instruments. It will also give in-depth
knowledge to firms on the way to reduce the price of their floating assets relatively to inherent risk
of the assets, in turn lowering the volatility of their earnings.
Regulators
To regulators and other participants in the financial and real sector, it will provide some insight on
the need to enhance development in the sectors.
8
REFERENCES
Abor, J. (2008), “Determinants of the Capital Structure of Ghanaian Firms”, African Economic
Research Consortium, Research Paper 176.
Abu-Rub, N. (2012), Capital Structure and Firm Performance: Evidence from Palestine Stock
Exchange, Journal of Money, Investment and Banking, Issue 23: 109-117.
Adelegan, O. (2007), Effect of Taxes on Business Financing Decisions and Firm Value in Nigeria,
International Research Journal of Finance and Economics, Issue12.
Adeyemi, S. B. and Oboh, C. S. (2011), Perceived Relationship Between Corporate Capital
Structure and Firm Value in Nigeria, International Journal of Business and social Science,
2(19).
Afrasiabi, J. and Ahmadinia, H. (2011), How Financing Effect on Capital Structure, Evidence from
Tehran Stock Exchange (TSE), International Journal of Academic Research, 3(1).
Afza, T. and Hussiain, A. (2011), Determinants of Capital Structure across Selected Manufacturing
Sectors of Pakistan, International Journal of Humanities and Social Science, 1(12).
Ahmed, N., Ahmed, Z. and Ahmed, I. (2010), Determinants of Capital Structure: A Case of Life
Insurance Sector of Pakistan, European Journal of Economics, Finance and Administrative
Sciences, Issue 24: 7-12.
Akintoye, I. R. (2008), Sensitivity of Performance to Capital Structure, European Journal of
Social Science, 7(1): 23-31.
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12
CHAPTER TWO
LITERATURE REVIEW
2.1.1 Concept of Financial Leverage
In this section we look at theoretical review of concept of financial structure. The body of
theoretical literature contends that leverage ratios are suitable quantitative measures of firms’
financial structure. Leverage ratio is a portion of firm assets financed with any type of fixed-charge
financing such as debt or leases. Thus, leverage is a tool if prudentially employed increase earnings
potential of the residual owners. Goldsmith and Lipsey (1963), contend that leverage ratio is a
measure of potential, rather than actual, capital gain. Therefore, leverage ratio suggest the effects
of possible changes in price-pointing out which groups might be vulnerable to, or favoured by,
price changes of various type. Leverage ratio indicates the firm’s risk exposure in meeting debt
service charges. A high leveraged firm faces a higher risk that its equity capital can be wiped out
when outcomes from its exposure to risky assets are unfavourable. Higher leverage magnifies
market risk as leverage firm may be forced to sell assets in order to reduce exposure under adverse
market conditions. Thus, firm that is heavily financed by debt offers creditors less protection in
the event of bankruptcy. For example, if a firm’s assets are financed with 75 percent debt, the
value of the assets when decline by only 25 percent, creditors’ funds are endangered. In contrast, if
only 25 percent of a firm’s assets are debt financed, assets value can drop by 75 percent before
jeopardizing the creditors’ funds.
On the other hand, leverage ratios also are of concern to owners of the firm because it influences
the rate of return they can expect to realize on their investment and the degree of risk involved.
Nwude (2003) postulate that higher leveraged firm is faced with greater fixed charge interest rate,
decrease in profit and cash flow is limited by financial leverage resulting to reduced dividends or
no dividends and, in turn fall in share price. This however, can increase the probability of default
in interest payments, thereby increasing the chances of corporate failure. Thus, the level of
leverage ratio employed by a firm is paramount to potential earnings of the firm.
However, measures of financial structure used in most empirical studies are debt ratio, debt equity
ratio, long term debt ratio, short term debt ratio, long term debt to market value equity, short term
debt to market value equity, convertible debt to market value equity, long term debt to book value
13
equity, short term debt to book value equity, convertible debt to book value equity, times interest
earned ratio, fixed-charge coverage ratio (Titman and Wessels, 1988; Majumdar and Chhibber,
1999; Zeitun and Tian, 2007; Tze-Sam and Heng, 2011; Zambuto et al., 2011; Hatfield et al.,
1994; Onaolapo and Kajola, 2010; Baker and Wurgler, 2002; Staking and Babbel, 1995;
Schiantarelli and Sembenelli, 1997; Long and Malitz, 1985; Booth et al., 1999; Almazan et al.,
2007; Ju et al., 2004; Olatundum and Ademola, 2008; Kasozi and Ngwenya, 2010; and Muradoglu
and Sivaprasad, 2008; Khan, 2012; Azhagaiah and Gavoury, 2011) among others.
2.1.1.1 Total Debt Ratio
Total debt ratio measures the amount of a firm’s total assets that is financed with external debt.
This measure encompasses all short term liabilities and long-term liabilities. Nwude (2003)
contend that this measures portion of the firm’s assets that is financed by creditors. As the total
debt ratio increase, so do a firm’s fixed-interest charges, if the total debt ratio becomes too high,
the cash flow the firm generates during economic recessions may not be sufficient to meet interest
payments. In terms of its significance to a firm, theoretical literatures predict that debt is positively
correlated with level of investment. For example, long and Malitz (1985) found a significant
positive relationship between the rate of investment in fixed plant and equipment and level of
borrowing. The total debt ratio is measured by dividing total debt with the total assets of the firm.
This proxy variable remained most notable measure of leverage ratio of a firm as adopted in many
empirical studies (Zeitun and Tian, 2007; Onaolapo and Kajola, 2010; Tze-Sam and Heng, 2011;
Kasozi and Ngwenya, 2010; Baker and Wurgler, 2002; Ju et al., 2004; and Booth et al., 1999;
Khan, 2012; Azhagaiah and Gavoury, 2011).
Total Debt ratio = AssetsTotal
DebtTotal
2.1.1.2 Debt Equity Ratio
Debt equity ratio is similar to the debt ratio and relates the amount of a firm’s debt financing to the
amount of equity financing. Actually, this measure of leverage ratio is not actually a new measure;
it is simply the debt ratio in a different format. Debt equity ratio is the quantitative measures of the
proportion of the total debt to residual owners’ equity (Nwude, 2003). Thus, it is an indicator of
company’s financial structure and whether the company is more reliant on borrowing (debt) or
14
shareholders capital (equity) to fund assets and activities. Many empirical studies in different
jurisdictions have employed this measure of financial structure in their various studies (Zeitun and
Tian, 2007; Majumdar and Chhibber, 1999; Azhagaiah and Gavoury, 2011) among others.
Debt equity ratio = FundsrsShareholde
DebtTotal
'
2.1.1.3 Long Term Debt Ratio
Although this measure is incorporated in the last two measures highlighted above, some analysts
generally use this measure because most interest costs are incurred on long-term borrowed funds,
and because long-term borrowing places multi-year, fixed financial obligations on a firm. Titman
and Wessels (1988) contend that significant results are good reason for employment of different
measures of leverage ratio because some of the theories of financial structure have different
implications for not combining them as aggregate “debt ratio”. Long term debt ratio is measured
by dividing long term debt with the total assets of the firm, and has been adopted in several
empirical studies (Titman and Wessels, 1988; Zeitun and Tian, 2007; Tze-Sam and Heng, 2011;
Long and Malitz, 1985; Booth et al., 1999).
Long term debt ratio = AssetsTotal
DebtTermLong
2.1.1.4 Short Term Debt Ratio
Short term debts are debt obligation that matured within one accounting year. This measure is very
appropriate to be included in the measures of leverage ratio due to implication it normally revealed
when there is occurrence of mismatch of funding by a firm. This may be one of the reasons that led
to adoption of different measures of leverage ratio rather than narrow measure of financial
structure by some scholars. Titman and Wessels (1988) contend that theories have different
empirical implications in regard to different types of debt instruments. Thus, mismatching funds is
a situation when long term investments are financed by short term debt rather than long term debt.
Apparently, the occurrence of this is prone to default as payment of interest and repayment of
principal may fall due when the proceeds (cash inflow) from the investment are not readily
available. The inability of the firm to repay the principal will expose it to the embarrassments
resulting from legal actions. This measure however, indicates the magnitude of current liabilities
15
(obligations) to changes in the value of overall assets of a firm. Schinasi (2000) contends that
leverage is the magnification of the rate of return whether positive or negative on a position or
investment beyond the rate obtained by a direct investment of own funds in the market. The body
of theoretical literatures have argued that short term measure is a good measure of leverage ratio in
transition economy with less developed debt market where most firms’ external debt finance are
majorly commercial bank loans. Lucey and Zhang (2011) are of the view that market liberalization
at the country level decreases the use of long-term debt, and debt maturity shifts to short term.
Empirical investigation by Khan (2012) revealed that engineering sector firms in Pakistan are
largely dependent on short debt but debts are attached with strong covenants which affect the
performance of the firm. A good number of authors have employed this measure in their empirical
studies (Timan and Wessels, 1988; Zeitun and Tian, 2007; Long and Malitz, 1995; Khan, 2012)
among others. This is measured thus;
Short term debt = AssetsTotal
DebtTermShort
2.1.1.5 Times Interest Earned Ratio
Times interest earned ratio is one of the measures of leverage ratio that employs income statement
data to measure financial structure. This measure tells the financial analyst the extent to which the
firm’s current earnings are able to meet current interest payments. The earnings before interest and
tax of the firms are used because the firm makes interest payments out of operating income.
Theoretical literatures contend that when the times interest earned ratio falls below 1.0, the
continued viability of the firm is threatened because the failure to make interest payments when
due can lead to bankruptcy. Olatundum and Ademola (2008) point out that when times interest
earned declines; the firm is likely to face a high premium. The times interest earned ratio is
measures by dividing the earnings before interest and tax with the interest charges. This has
remained the used standard to ascertain the ability of the current earnings of the firm to offset its
current obligations. Olatundum and Ademola (2008) employed this measure in their empirical
study.
Time interest earned ratio = esChInterest
TaxesandInterestBeforeEarnings
arg
16
2.1.1.6 Fixed-Charge Coverage Ratio
Fixed-charge coverage ratio measures the number of times a firm is able to cover total fixed
charges, which include (in addition to interest payments) preferred dividend and payments required
under long term lease contracts. Firms in some time are require to make sinking fund payments on
bond issues, these are annual payments aimed at either retiring a portion of the bond obligation
each year or providing for the ultimate redemption of bonds at maturity. Under most sinking fund
provisions, the firm either may make these payments to the bondholders’ representative (the
trustee), who determines through a lottery process which of the outstanding bonds will be retired,
or deliver to the trustee the required number of bonds purchased by the firm in the open market.
Either way, the firm’s outstanding indebtedness is reduced.
In calculating the fixed-charge coverage ratio, an analyst must consider each of the firm’s
obligations on before-tax basis. However, because sinking fund payment and preferred stock
dividends are not tax deductible and therefore must be paid out of after-tax earnings, a
mathematical adjustment has been made. Nwude (2003) contend that this measure the extent to
which earnings may fall without causing problem to firm as regards the payment of interests and
other fixed charges. A high coverage ratio is preferred and suggests strength.
2.1.2 Concept of firm Performance
In this section, we look at concept of firm performance. The concept of performance in finance is a
controversial issue largely due to its multi-dimensional meanings. Santos and Brito (2012) posits
that the definition of firm performance and its measurement continues to challenge scholars due to
its complexity. This theoretical literature has spawned the interest of numerous studies.
Performance measures are either financial or organizational (Zeitun and Tian, 2007). Citing the
work of Chakravarthy (1986) and Hoffer and Sandberg (1987) by Zeitun and Tian (2007) point
that financial performance such as value maximization, maximizing profit on investment, and
maximizing residual owners equity are at the core of the firm’s effectiveness, while, operational
measures, such as growth in sales and growth in market share, essentially emphasizes wide range
of performance as they focus on the factors that specifically result to financial performance. There
are statutory requirements to provide information for performance of publicly traded companies by
the regulatory authorities. And also information asymmetries between management and other
contracting parties create a demand for an internally generated measure of firm performance to be
17
reported over finite intervals. This however, provide source of information to investors and
creditors on the firm’s cash generating ability (Dechow, 1994). Financial statement is the
instrument that conveys information to the users of financial information. Market efficiency is
based on the theory of competition in which prices are competitively set and decisions reflect
available economic information (Dastgir and Velashani, 2008). Advocates of the “all-inclusive
concept” argue that comprehensive income statement provide better measures of firm
performance, than other summary income measures. On the other hand, those who advocate
“current operating performance” view of income argue that net income without inclusion of
extraordinary and non-recruiting items get better ability to reflect the firm’s cash flows (Dastgir
and Velashani, 2008).
The usefulness of a measure of performance may be affected by the objective of a firm and stock
market development relatively to the choice of performance measures (Zeitun and Tian, 2007).
Agency cost theory argues that self objectives (interests) of the company’s managers and
objectives of the firm (shareholders’ value maximization) are not perfectly aligned (Jensen and
Meckling, 1976). They opined that managerial share-ownership may reduce managerial incentives
to consume perquisites, expropriate shareholders’ wealth or to engage in other sub-optimal
activities and thus helps in aligning the interests of managers and shareholders and consequently
lowers agency costs and increase firm performance. Thus, the convergence of interest hypothesis
predicts that larger managerial ownership stakes should lead to better firm performance.
Depending on one’s view of performance measures, one can look at a firm and find it either
efficiently organized or not and that can lead to better performance. But there are established
theoretical literatures on the measures (indicators) of firm performance, although these have not
been adequately explored compare to other areas in finance. The most measure that proxies firm
performance are Return on Assets (ROA), Earnings per Share (EPS), profit margin, Return on
Equity (ROE) or Return on Investment (ROI), Tobin’s Q, P/E, etc (Zeitun and Tian, 2007, Booth
et al., 1999). The first four performance measures highlighted above merely represent accounting
measures of firm performance based on historical activities of the firm to generate financial ratios
from balance sheet and income statements. Several notable researchers have employed these
measures in their empirical studies (Zeitun and Tian, 2007; Booth et al., 1999; Tze-Sam and Heng,
2011; Onaolapo and Kajola, 2010; Kajola 2008; Zeitun, 2009; Skopljak and Luo, 2012; Khan,
2012; Azhagaiah and Gavoury, 2011). While, some body of theoretical literatures has established
18
converse view on the measures of firm performance. They argued that rather than focusing on
accounting data that is merely historical, a firm performance is better obtain with the use of market
value. The market measures of firm performance are Tobin’s Q, price earnings ratio, and others.
Lang and Stulz (1994) contend that the use of Tobin’s q rather than performance over time, avoid
some of the problems of the earlier literature.
2.1.2.1 Return on Assets
Return on Assets (ROA) is measures of firm performance that reveals to the users of financial
statement how well a company uses its assets to generate income. A higher ROA denotes a higher
level of firm performance. A rising ROA, for instance, may initially appear good, but turn out be
unimpressive if compare with other companies in same line of activities or industrial average.
Hence, if company’s ROA is below industrial average the company is not utilizing its full capacity.
Booth et al. (1999) posits that this measure was used in their study because it was the only variable
that can be calculated across countries. They conclude that country comparisons of profitability are
therefore difficult. Among other authors that adopted this measure in their empirical studies are
Zeitun and Tian (2007), Zeitun (2009), Tze-Sam and Heng (2011), Onaolapo and Kajola (2010)
and Khan (2012). The ROA ratio may thus be more useful when compared to the risk free rate of
return to be rewarded for the additional risk involved. If a firm’s ROA is equal or even less than
the risk free rate, investors will be indifferent and better off just purchasing a bond with a
guaranteed yield.
ROA = AssetTotal
TaxandInterestBeforeofitPr
2.1.2.2 Return on Equity
Return on equity is another measure of firm performance that shows how well a company has used
the capital from its shareholders to generate profits. Investors use ROE as a measure of how well a
company is using its money. Evidently, numerous empirical studies have employed this measure in
quest to observe the predicted relationship between financial structure and firm performance (Tze-
Sam and Heng, 2011; Zeitun and Tian, 2007; Onaolapo and Kajola, 2010; Kajola 2008; Zeitun,
2009; Skopljak and Luo, 2012; Khan, 2012).
19
That is; ROE = FundsrsShareholde
TaxandInterestBeforeofit
'
Pr
2.1.2.3 Earnings per Share
Earnings per share is a ratio that measure earnings in relation to every share on issue. This is
measured by dividing the profit before interest and taxes with the outstanding number of shares of
the firm. This indicates how much each one share of the firm will earn from the yearly proceed.
The earnings for every share represent shareholders slice of the pie. As earnings go up over time,
the value of that piece of the firm becomes more valuable and this is why the price will be bid up.
Whilst there are not many truisms when it comes to share investment, one is that if earnings rise
consistently over the long term, then the share price will follow. Apparently, issue of shares that
increases the number of outstanding share dilutes the equity owners’ residual value. Tze-Sam and
Heng (2011) provide empirical investigation using EPS as a proxy for corporate performance to
establish its relationship with financial structure. The measure is derived thus;
EPS = SharesdingOutsofNo
TaxandInterestBeforeofit
tan
Pr
2.1.2.5 Tobin’s Q
Tobin’s Q is the market value of assets (market value of equity plus market value of debt) divided
by estimated replacement cost (Brealey and Myers, 1996). Lang and Stulz (1994) assert that no
risk adjustment or normalization is required to compare Tobin’s Q across firms in contrast to
comparisons of stock return or accounting performance measures. Although, Tobin’s Q has been
employed in many empirical studies as a major indicator of firm performance but many
researchers have agreed it is noisy signal (Zeitun and Tian, 2007; Onaolapo and Kajola, 2010).
Similarly, Lang and Stulz (1994) posit that the problem with Tobin’s Q is that it reflects what the
market thinks, whether illusory or not. They suggest that to be able to adopt Tobin’s Q, financial
markets must assume to be efficient and firm’s market value is an unbiased estimate of the present
value of its cash flows. With this assumption, the ratio of the market value of the firm to the
replacement value of its assets is a measure of the contribution of the firms’ intangible assets to its
market value. Although, Tobin’s Q as market performance has been extensively used as a proxy
for firm performance but there is difficulties in getting required information relating to market
20
value of debt issued in most emerging economy like Nigeria, since these are not usually disclosed
in their financial statement (Kajola, 2008). He noted that most researchers used modified Tobin’s
Q that seems to be subjective, because the modification usually influences the outcome of the
study. Booth et al. (1999) using Tobin’s Q as a proxy for performance in their empirical study
found that market-to-book ratio is imperfectly correlated with Tobin’s Q and arrived at the
conclusion that the degree of correlation will differ across countries according to the accounting
principles adopted. Another empirical study by Khan (2012) revealed that Tobin’s Q as firm
performance is significantly negatively related to capital structure.
This measure can be derived as follow;
Tobin’s Q = CostplacementEstimated
AssetsofValueMarket
Re
2.1.2.6 Price Earnings Ratio
The price to earnings ratio (P/E) measures the number of times the share price covers the earnings
per share. It is measured by taking firm’s current share price and dividing it with the earnings per
share (EPS). However, a firm’s P/E ratio should not be analyzed as a standalone number. It may be
interpreted in many ways depending on whether it is being compared with the firm’s historical
P/E, the industry P/E or even the market P/E. This measure as market performance measure was
used in empirical work of Zeitun and Tian (2007), which documented that the regression model
using price per share to earnings per share (P/E) is not significant using any measure of capital
structure. They gave the following reasons that have contributed to the insignificance of the
results; (i) that the share price does not reflect the actual situation of the firm, (ii) that most
investors still depend on the accounting measure of performance rather than the P/E measure due
to inactivity of the stock market, (iii) inclusion of default firms in the studies that have a low or
even negative P/E affects the validity of the P/E as a measure of performance.
P/E = shareperEarnings
iceShareCurrent Pr
21
2.1.3 Theories of Financial Structure
The firm’s mix of different securities is known as its financial structure (Brealey and Myers, 1996;
Dare and Olorunfeme, 2010). These theories have generated intense interest and criticism, thus
leading to different views on theoretical and empirical literature. Within these theories; the static
trade – off theory, agency cost theory, the pecking order theory and other theories are well
established (Brounen et al. 2005). According to Titman and Wessels (1988), a number of theories
have been proposed to explain the variation in debt ratio across firms. In the work of Myers
(1984), “the capital structure puzzle is tougher than the dividend one”. Modigliani and Miller
(1958) preposition assumed in a world of perfect capital market and no taxes, a firm financial
policy is irrelevant. Berens and Cuny (1995) submit that enormous academic effort has gone into
identifying the relevance of capital structure to a firm. As noted by Long and Malits (1985) and
Masulis (1980) later studies by Modigliani and Miller (1963), Baxer (1967), and Miller (1977)
introduced taxes and/or bankruptcy costs in an effort to explain capital structure.
Myers (1984) postulate that there is inadequate understanding of corporate financing behaviour,
and of how this behaviour affects security returns. The result of the enormous arguments in
theoretical literature can be adduced to have been attempted to reconcile Miller model with the
balancing theory of optimal capital structure (Bradley et al., 1984). According to Myers (1984),
“our theories don’t seem to explain actual financing behavior, and it seems presumptions to advise
firms on optimal capital structure when we are so far from explaining actual decisions”.
Nevertheless, the notable financial structure theories that explain the financial structure decision of
the firm includes; the Modigliani – Miller Theorems, Static Trade – off Theory, Dynamic Trade –
off Theory, Pecking Order theory, Agency Cost Theory, Ownership Structure Theory, Signaling
Hypothesis, Neutral Mutation Hypothesis, Market Timing Theory and other notable theories of
financial structure.
2.1.3.1 Modigliani – Miller Theorems
Modigliani and Miller theorems holds that when capital markets are perfect (frictionless and
perfectly competitive), no taxes and investment policy is fixed; financial structure is irrelevant to
firm value. That is, they postulate that when there are no taxes and perfect capital market, it makes
no difference whether the firm borrows or individual shareholders borrow. Therefore, the market
value of a firm is independent of its financial structure. The basic assumptions of the theorems
22
were of perfect capital markets, no taxes, and no effect on management incentives (khadka, 2006;
Majumdar and Chhibber, 1999; Breadley and Myers 1996; Tze – Sam and Heng, 2011; Miller,
1988; Suhail and Wan Mahmood, 2008).
Modigliani and Miller proposition I posit that if capital markets are doing their job, firms cannot
increase value by tinkering with financial structure (Brealey and Myer, 1996). And proposition II
argued that weighted average cost of capital would remain the same no matter what combination of
financing mix the firm actually employed (Modigliani and Miller, 1958; Miller, 1988). Thus, these
propositions are held in the world of perfect capital market where value is invariance to financial
structure of a firm. In the work of Miller (1988),
our value – invariance proposition I was in a sense only the application of this
macroeconomic intuition to the microeconomics of corporate finance; and the
arbitrage proof we gave for our proposition I was just the counterpart at the
individual investor level of the consolidation of accounts, and the washing out of the
debt/equity ratios at the sectoral level. In fact, one blade of our arbitrage proof had
the arbitrager doing exactly that washing out. If levered firms were undervalued
relative to unlevered firms, our arbitrager was called on to “undo the leverage” by
buying an appropriate portion of both the levered firm’s debt and its shares. On a
consolidated basis, the interest paid by the firm conceals against the interest received
and the arbitrager thus owned a pure equity stream.
However, this theorem argued that with well functioning markets, no taxes and rational investors,
who can ‘undo’ the corporate financial structure by holding positive or negative amounts of debt,
the market value of a firm depends only on the income stream generated by its assets (Bailey,
2010). In the same vein, the future operating cash flows are unaffected by firm’s choice of
financial structure (Yany, 2009), and Suhaila and Wan Mahmoon (2008) documented that this
theory argues that “it does not matter how the size of the pie is sliced but what matters is the level
and risk of its future cash flows”. Accordingly, in a world with corporate taxation, tax deductible
interest payments subsidies the issuance of debt. Modigliani and Miller (1963) second seminal
paper argued that firm value is an increasing function of leverage due to the tax deductibility of
interest payments at the corporate level (Berens and Cuny, 1995 and Hull, 1999). Hence, in tax
environment interest expenses are tax deductible due to the income tax law, firms decreases the tax
23
liability and increases the after tax cash flows (Awan et al. 2011). The unrealistic proposition of
Modigliani and Miller theorems with the assumptions of frictionless markets, and zero bankruptcy
cost which contributed disagreement of Miller (1977) on the issue of optimal capital structure, and
thus, the impact of such costs depends on size of the firm relatively to the value of assets
transferred. In view of that, Miller (1977) demonstrated that variations in debt ratio also reflected
primarily the recurring movements of the economy, in expansions debt ratios tended to fall, partly
because the place of dividends behind earnings built up internally generated equity; and partly
because the ratio of equity to debt in sight financings tended to rise when the stock market was
flourishing. As with many aspect of the Modigliani – Miller theorems coupled with Miller model
that owners of corporation reap no gain, whatever from their use of tax-deductable debt rather than
equity capital when even personal income tax and corporate tax are applicable; there is room for
disagreement (Bailey, 2010). In the work of Berens and Cuny (1995), the “comer solution” implied
by Modigliani and Miller (1963) model is very much at odds with empirical observations of firm
behavior. Many researchers preceding Modigliani and Miller theorems have considered a variety
of wealth effects linked to leverage including bankruptcy and agency effects but disparity in
relation to the strength of these effects and tax shield advantage still prevail (Hull, 2007).
2.1.3.2 Static Trade – off Theory
Prominent authors have explicitly argued against irrelevancy theory. According to Myers (1984)
“static trade off framework is a situation in which a firm set a target – to – value ratio and
gradually moves towards it”. The theory viewed financial structure of a firm by adding various
imperfections including taxes, cost of financial distress and agency costs, but retains the
assumptions of market efficiency. And thus suggest that firm target leverage is driven by three
competing forces such as tax benefits, bankruptcy cost and agency costs (Nosa and Ose, 2010;
Huang and Ritter, 2004). In the static trade – off theory, the value of the levered and unlevered
firm is not the same (Awan et al., 2011). The authors pointed that debt financing firm can save the
amount of interest payments on the debts from tax purposes.
However, the theory holds that a firm borrows to the point where the marginal value of tax shields
on additional debt immediately offset the increase in the present value of bankruptcy cost (Mayer,
2001; Yang, 2009 and Baurer, 2004). This body of knowledge challenged the assumptions of
irrelevance theory with the argument that optimal capital structure of a firm is a trade – off
24
between the benefit from tax advantage (tax shield) and cost of financial distress (bankruptcy
costs) from employing external capital (debt), holding the firm’s assets and investment plan
constant (Bas et al., 2009; Myers, 1984; Bradley et al., 1984; Zambuto et al., 2011; Sayilgan et al.
2006). Hence, value maximizing firms attain an optimal capital structure by offsetting the
corporate tax benefits of debt against the personal income tax, bankruptcy cost and agency cost
associated with debt. Masulis (1980) opines that unique optimal capital structure do exist in tax
environment whereas at margin, there is balance between corporate tax advantage and personal tax
disadvantage of holding debt. Firms target debt ratio is driven by tax shield, bankruptcy costs of
debt and agency cost (Suhaila and Wan Mahmood, 2008). Thus, most significant benefit of debt
financing is the tax shield from interest payments.
Nevertheless, static trade-off theory argues that firms balance beneficial tax shields with
bankruptcy costs when determining the appropriate leverage (Brounen et al., 2005). They reported
that firms that act along the lines of the static trade – off paradigm are expected to have a target
debt ratio. According to this theory, Bunn and Young (2004) states that in choosing financial
structure, firms seek to balance the benefits of debt against the potential costs of financial distress
that is made more likely at high debt levels. Similarly, this theory argues that there is an
equilibrium level of debt in which any further raise in leverage will increase the expected costs of
financial distress by more than the accrued benefit of that subsequent borrowing (Bunn and Young,
2004).
While, Ahmed et al. (2010) opines that firms set its target debt ratio in accordance to the nature
and requirements of business, and in turn moves gradually to achieve it. And firm’s performance
affects its target debt, which in turn is reflected in the firm’s choice of securities issued and its
observed debt ratios (Hovakimian et al., 2004). Shahjahanpour, et al. (2010) contributed that firm
maximize their values by maximizing the use of debt. Other authors like Manos and Ah-Hen
(2002) contend that each firm has an optimal debt ratio that maximizes firm’s value, although this
level varies between firms. Huany and Ritter (2004) report that static trade-off theory suggests that
firm should issue equity when their leverage is above the desired target leverage, issue debt when
their leverage is below the target or issue debt and equity proportionately to stay close to the target.
25
2.1.3.3 Dynamic Trade-off Theory
Extensive theoretical literature has established dynamic nature of firms’ capital structure. But
dynamic trade-off theory is not as popular as static trade-off theory leading to many authors
categorizing the two theories as one (trade-off theory). Although the distinction between these two
theories are not well established. Hull (1999) and Ju et al. (2004), postulate that dynamic trade-
off theory corresponds with traditional trade-off approach in the pursuit of an optimum capital
structure but not static. They assert that factors affecting financial structure are tax shields and
bankruptcy costs. This suggests that some managers make financial structure decisions with the
objective of maximizing the total value of the levered firm. Optimal capital structure is the point at
which the financing costs and the Weighted Average Cost of Capital (WACC) are minimized,
thereby maximizing returns (Onaolapo and Kajola, 2010 and Tz-Sam and Heng, 2011). In other
words, this theory argues that firms chose capital structure base on the attributes that determine the
costs and benefits associated with debt ratio, which can be maintain or revert to predetermine debt
to equity ratio that maximizes firm value and /or minimized risk of default (Kasozi and Ngwenga,
2010).
Thus, firm with different types of assets will have different bankruptcy and agency costs coupled
with optimal debt ratios. Berens and cuny (1995) argue that capital structure can be obtained by
moving to a dynamic multi-period setting. They assert that given set of interest payments over
time, a firm’s current debt ratio can vary with its debt maturity structure, reflecting different
default risks. This implies that there may be multiple optimal debt ratios even if the set of interest
payment is unique.
Bhamra et al. (2008) posit that firms optimally choose not only the amount of debt but also the
timing of refinancing in dynamic trade-off theory. Thus, optimal financial structure of a firm varies
over time implying an optimal range rather than static. Fisher et al. (1989) and Leland (1989)
argues that in dynamic trade-off theory firms let their leverage fluctuate overtime reflecting
accumulated earnings and losses and do not adjust it toward the target as long as the adjustment
costs exceed the value lost due to suboptimal capital structure in (Hovakimian et al. 2004). Hence,
firm’s rational decisions make target leverage ratio to be dynamic due to adjustment to hedge
against suboptimal financial structure. The dynamic trade-off theory implies that the optimal target
capital structure of firms adjusts over time and is a function of changing exogenous and
26
endogenous factors (Getzmann et al., 2010). Another contribution by Hovakimian et al. (2004),
firms that follow a dynamic trade-off strategy will chose the amounts of new debt and equity that
the deviation from the target is induced by accumulation of earnings and losses. Thus, offsetting
the accrued benefits and losses lead to dynamic nature of financial structure, thereby results in the
debt ratio close to the target.
2.1.3.4 Pecking Order Theory
Traditional views of financial structure have taken different dimension with priority to internal
funding. According to Shahjahanpour et al. (2010) pecking order theory was first observed by
Donaldson (1961) and thereafter was supported by Myers (1984), working on agency theory of
Jensen and Meckling (1976), and also by Myers and Majluf (1984), working on information
asymmetry. In Myers (1984), contrast to the static trade-off theory with a competing popular story
based on a financing pecking order, firms prefer internal finance and if external finance is required,
firms issue less risk debt and equity as a last resort. This theory is looking at the least cost of
financing mix, as it argues that firms do not try to reach the “optimal” capital structure, as the
trade-off theory claims, because firms employ least resistance and least costly financing mix
(Kasozi and Ngwenya, 2010). Zambuto et al. (2011) report that this theory argues that information
asymmetry problem between insiders and outsider of a firm lead to increases in the cost of external
capital. Brounen et al. (2005) contends that the degree of asymmetric information determines the
relative costs of each source of finance. As they stressed further, firms that adopt this pecking
order of finance do not have a target debt ratio, because the ordering determines their choice of
issuance of new capital. Moreover, the more severe the asymmetric information, the more riskier
the investment for investors, invariably the higher the price of the security (Octavia and Brown,
2008). Hence, with the presence of asymmetric information, a firm is better financed by internally
generated funds than external funds. This was supported in the work of Hovakimian et al. (2004),
managers do not attempt to maintain a particular capital structure, rather financing decision are
driven by the costs of adverse selection that arise because of information asymmetry between
better – informed managers and less – informed investors. They further noted that because these
costs are incurred only when securities are issued by the firm and are lower for debt than for
equity, firm prefer internal financing and prefer debt to equity when external funds have to be
raise. For example, in internally generated funds, the firm will have more information about the
27
firm than new equity holders who will expect a higher rate of return due to asymmetric
information (Abor, 2008).
Kim et al. (2006), and Afrasiabi and Ahmadinia (2011) explicitly stressed that a firm tends to draw
on firstly internal financing and later on external financing by issuing corporate bonds when there
is insufficient internally generated funds. Sundaram (2008) contends that managers may prefer
internal financing because it relieves them from the disciplining effects on the security markets. In
attempt to explain the observed corporate finance patterns this theory suggests that firms do not
issue stock and their choice is to hold large cash reserves and other forms of “financial slack”
(Chen, 2004).
In the same vein, pecking order theory argues that firm should follow specific hierarchy of assets
financing. Notably, internally generated funds from retained earnings should been employ first
then debt when internally equity are exhausted and external equity as last resort if need be (Kasozi
and Ngwenya, 2010; Afza and Hussain, 2011; and Ahmed et al., 2010). Eriotis (2007) and Abor
(2008) report that the theory argues that highly profitable firms that generate high retain earnings
are expected to use less debt capital than those that do not generate high earnings.
Pecking order theory of capital structure argues that the primary determinant of capital structure of
a firm is the problem of asymmetric information between firm insiders and outsiders (Agca and
Mozumdar, 2004). Firms’ managers are reluctant to issue equity when the firm is undervalued and
investors rely on managers’ actions as signals regarding the true value of the firm. Hence, issue of
equity by the firm is likely to be interpreted as a bad signal, which must be avoided by relying
primarily on internally generated equity (Manos and Ah-Hen, 2002). According to Dincergok and
Yalciner (2011), “pecking order theory states that there is no optimal capital structure since debt
ratio occurs as a result of cumulative external financing requirements”. Huang and Ritter (2004)
assert that optimistic entrepreneurs are not willing to issue external equity because they think their
stock is undervalued. Thus, pecking order theory expects equity issues to be rare.
2.1.3.5 Agency Cost Theory
Agency cost theory was first incorporated in financial structure argument in the work of Jenson
and Meckling (1976); this theory was incorporated in financial structure because of agency
relationship between the principal (shareholders) and agent (manager) when there is separation of
28
ownership and control. This theoretical literature argues that agency costs arise because of interests
of the principal and agent resulting from personal utility maximization does not align (Kim, et al.,
2006 and Siddiqui and Shoaib, 2011). Eisenhardt (1989) asserts that agency theory is directed at
the ubiquitous agency relationship, in which one party (the principal) delegates work to another
(the agent), who performs that work. While, Berger and Patti (2002) posits that agency costs of
outside ownership equal the lost value from professional managers maximizing their own utility,
rather than the value of the firm due to separation of ownership and control. In the work of
Eisenhardt (1989), agency theory is concerned with resolving two problems that can occur in
agency relationships. The first is the agency problem that arises when (i) the desires or goals of the
principal and agent conflict (ii) it is difficult or expensive for the principal to verify what the
agents is actually doing. The problem here is that the principal cannot verify the agent has behaved
appropriately. The second is the problem of sharing that arises when the principal and agent have
different attitudes toward risk. The problem here is that the principal and the agent may prefer
different actions because of the different risk preferences.
Similarly, Barcley et al. (2006) noted that conflicting of interest between managers and
shareholders can take a variety of forms. In their model, managers receive private benefits from
investment, which relatively increase with the projects’ NPV and apparently optimal for manager
to invest. Therefore, agency cost discretion depends on the allocation of control rights within the
firm. Eisenhardt (1989) contend that the focus of the theory is on determining the most efficient
contract governing the principal-agent relationship given assumptions about (eg, self-interest,
bounded rationality, risk aversion), organization (eg. Goal conflict among members), and
information (eg, information is a commodity which can be purchased). The domain of agency
theory is relationships that mirror the basic agency structure of a principal and an agent who are
engaged in cooperative behavior, but have differing goals and differing attitudes toward risk. The
theory advocate that when the contract between the principal and agent is outcome based, the agent
is more likely to behave in the interests of the principal and also when the principal has
information to verify agent behaviour, the agent is more likely to behave in the interests of the
principal. Thus the focus of the principal-agent literature is on determining the optimal contract
behaviour versus outcome between the principal and the agent. That is the trade-off between; the
cost of measuring behaviour and the cost of measuring outcomes and transferring risk to the agent
(Eisenhardt, 1989).
29
Nevertheless, agency theory is most relevant in situations in which contracting problems are
difficult. The choice of financial structure may help mitigate these agency costs. High leverage
ratio reduces the agency costs of outside equity and increases firm value by constraining or
encouraging managers to act more in the interests of shareholders (Berger and Patti, 2002).
Moreover, the given incentives to the firm will benefit shareholders at the expense of debt-holders.
Thus, debt-holders need to restrict and monitor the firm’s behaviour. Onwumere et al. (2011)
contend that the use of debt finance which is linked to assets of the firm create a problem for the
firm because management may not want to run the risk of having conflicts with debt holders.
Hence, costly monitoring devices of contractual covenants are incorporated into debt agreements
to protect the debt-holders, it should increase the cost of capital offered to the firm. And also,
Heland and Pyle (1977) noted that firms with riskier returns will have lower leverage ratio even
when there are no bankruptcy costs.
In addition, Masulis (1980) posits that when manager own less stake in a firm, agency costs
increase relatively to optimal monitoring of managerial decisions and the level of perquisite
consumption by manage. He opined that agency cost model predicts financial structure of a firm
affects management incentives to make particular firm related decisions. Almazan and Molina
(2004) stressed that for agency conflict to shapes a firm’s financial structure will depend on the
manager’s attributes and on the firm’s ability to reduce managerial influence. Long and Malitz
(1985) opine, “firm’s unobservable growth opportunities reduce the effectiveness of bond
covenants, the only way in which owners of a firm with a high proportion of intangible investment
opportunities can control the agency cost of debt is by limiting the amount of risk debt
outstanding”. In the spirit of Fama and French (1998), profitable firms with strong growth
opportunities and thus high market value can avoid agency problems by choose lower leverage.
Thus, high leverage increases agency problem, firm needs to balance the cost and benefit of debt
because negative information in debt about profitability overwhelms any tax (or other) benefits of
debt.
In the work of Suhaila and Wan Mahmood (2008) and Dincergok and Yalciner (2011), agency cost
arises due to conflict of interest between shareholders and managers, or between shareholders and
bondholders. Brounen et al. (2005) and Octavia and Brown (2008) postulate that agency problem
between shareholders and bondholder arise due to asset substitution, in which shareholders prefer
high risk projects, because they can fully benefit from high earnings, while bondholders that have a
30
fixed claim prefer low risk projects. The adjustment of leverage ratio to attain optimal financial
structure may lead to high agency cost if not rationally employed. As documented, the optimal
financial structure decision has to do with balancing the trade-off between the benefit of debt and
agency costs arising from mitigating the agency cost of managerial discretion against the agency
cost of debt arising from “asset substitution effect” (Octavia and Brown, 2008 and Shahjahanpour
et al. 2010). Also high leverage ratio increases the bankruptcy cost and agency cost of the firm as
well rises, and it is through this argument that agency costs can be incorporated into the financial
structure decision (Kim et al., 2006).
Manos and Ah-Hen (2002) pointed that agency consideration assume debt is valuable in reducing
the agency costs of equity but at the same time debt is costly as it increase the agency cost of debt.
While Ahmed et al. (2010), report that shareholders of a firm incur agency cost in attempt to
discourage self interest of the managers by means of monitoring and control actions. Eriotis (2007)
pointed out that managers of firms typically act as agents of the principal (owners). The principal
hire the agents and give them the power to manage the firm for the owners’ benefit. Hence,
manager is mainly interested in accomplishing their own targets which may differ from the
maximization of the firm value which is the maximization of the owners’ benefit. Finally, firms are
expected to set their financial structure in such a way the potential conflicts of interest between
managers, shareholders and debt holders are minimized (Sayilgan et al., 2006).
2.1.3.6 Signalling Hypothesis
The last two theories in the previous sections gave consideration to the information the policy
decision of the firm may convey to the market. This section also incorporates this information
dissemination and inference of the outsider. Signalling hypothesis argues that different levels of
information between insiders and outsiders are such that insider behaviour passes information
about firm value to outsiders (Hull, 1999). He posits that this theory predicts that a change in
firm’s financing mix contains information about stock value. In the work of Ross (1977) and
Leland and Pyle (1977), managers (insider) possess the true information of firm’s returns, but
investors (outsiders) do not. Molinari et al. (2009) noted that problems of asymmetric information
might raise the cost of external finance and lead to credit rationing. In this case, the ability to
generate cash flow becomes important for financing investment. Suhaili and Wan Mahmoon
(2008) and Brounen et al. (2005) shed light that if managers decide to issue more debt, outsiders
31
interpret it as a signal of high future cash flows and management confidence towards firm’s future
prospect. Suhaili and Wan Mahmood (2008) contributed further that issue of new equity is signal
of management lack of confidence towards firm’s future prospect. Due to asymmetric information
investor tend to undervalue new equity issuance, which increase the attractiveness of debt relative
to equity finance (Bunn and Young, 2004). Awan et al. (2011) posit that issuance of equity instead
of debt financing for new projects, investors will interpret the signal negatively. Therefore, since
managers have superior information about the firm than investors, they might issue equity when it
is overpriced.
The trade-off between the benefits of signalling and bankruptcy costs implies that a firm chooses
debt ratio at certain proportion to be better off. That is a good firm need large debt to act as an
incentive compatible signal and bad firm need not (Bauer, 2004). Ross (1977), signalling models
suggest that inside managers use leverage to signal growth prospect to outside investors who
believe in these signals due to information asymmetry. Managers of most corporations make
financing decision with dubious motive to secure their job and decisive investors and owners of the
firm. If a firm is undervalued due to information asymmetry problems, the insiders of the firm can
stimulate the share prices to rise by increasing debt, which in turn triggers investors believe of
future prospect (Dincergok and Yalciner, 2011). Eriotis (2007) posits that firms avoid issuing
undervalued stock unless the value transfer from “old” to new shareholders are more than offset by
the net present value of the growth opportunity. Theoretical literature by Sayilgan et al. (2006)
supported that managers of a firm maximizes his incentive return by employing finance mix that
trades off the current value of the signal given to the market against the incentive consequences on
that return.
2.1.3.7 Neutral Mutation Hypothesis
Neutral mutation hypothesis is not well established in literature when compared with other
extensively investigated theories in this field of study. This argues that sometime firm employs
financing decisions that cannot be predicted, and also doesn’t have any significant effect on the
firm value. Therefore, firm has undefined pattern or habit that can influence the value of a firm.
Myers (1984) posits that firm manager who identifies these habits and adopts them to predict
financing behavior would not be explaining anything important (meaningful). Thus, neutral
mutation ideal is important as a warning. Myers (1984) noted reasons for not embracing neutral
32
mutation as a strict null hypothesis makes the game of research too tough to play, if a firm can
identify costs that explain firms’ financing behaviour that can yield optimal returns. And also the
information effect of the financing choice of the firm. In the same vein, outside investors are
interested in the firm’s financing decisions, because they result to changes in the stock price when
the decisions are made public. According to Myers (1984), “…as a one-on-one competition of the
static trade-off and pecking order stories. If neither story explains actual behaviour, the neutral
mutations story will be there faithfully waiting”. Hence, this hypothesis essentially explains
undefined financing pattern in a firm financing decisions.
2.1.3.8 The Market Timing Theory
Market timing theory argues that firms issues equity when their market performance is high
(Hovakimian et al., 2004). Thus, if conditions on markets are unfavorable firms rarely go to the
market, there is possibility to delay investments. This is supported by a body of knowledge that
asserts that firm delay issuing securities due to expectation of growth opportunities. Apparently,
firms that mostly issue securities at peak (growth) period is expected to obtain this funds at low
price resulting to high expected rate of return. Hence, financial structure only depends on equity
market returns and conditions on the bond markets and a target financial structure does not exist
(Getzmann et al., 2010).
Afrasiabi and Ahmadinia (2011) posit that market timing theory of financial structure argues that
issuance of equity by the firm are timed, in such a way that when the stock prices are perceived to
be overvalued, they in turn issue new equity and buy back when they are undervalued. They
further stressed that fluctuations in stock prices affect firm’s capital structure. And also the theory
assumes economic agents (managers) to be rational and irrational. Managers issue equity when
they believe their cost is irrationally low and repurchase equity when they believe their cost is
irrationally high. Thus, manager does not predict stock returns but they believe they can time the
market.
Huang and Ritter, (2004) supported the view of rational and irrational manager with argument that
firms prefer external equity when the cost of equity is low, and prefer debt otherwise. The theory
believes that windows of opportunity exists as long as the relative cost of equity varies over time
for either rational or irrational reasons, and has important implications for financial structures
33
choices. Therefore, the condition in the market determines the position of the firm to be either
equity finance or debt finance, which invariably influences the value of the firm.
2.1.4 Determinants of financial Structure
There are many determinants of financial structure of a firm which if not properly taken into
consideration in financing decisions of a firm may hinder its performance. These factors can be
separated in two broad categories; internal or company characteristics and external determinants.
On one hand, company specific determinant comprises internal factors that influence the leverage
ratio of a firm such as tangibility, growth rate, current profitability, firm’s financial risk, firm’s
size, firm’s age, non tax shield, asset turnover, etc (see Titman and Wessels, 1988; Ahmed, et al.,
2010; Barel, 2004; Bauer, 2004; Abor, 2008) among others. On the other hand, external
determinants comprise exogenous factors that is uncontrollable by the firm such as prevailing
interest rate, tax rates, exchange rate, volatility and liquidity of capital markets, etc (Graham and
Harvey, 2002). Although, Barney (2001) asserts that success of a firm significantly depends on the
strategic resources under its control. Our major concern here is narrowed to internal factors, which
are firm specific factors that affect the financial structure and firm performance of a firm. The
followings have been identified as the theoretical determinants of financial structure of a firm
(Baral, 2004, Bauer, 2004, Abor, 2008, Gaud et al. 2003 and Shahjahanpour et al. 2010).
� Size of the firm
The size of a firm determines the level of leverage at any point in time. Bauer (2004) asserts that
the effect of size on leverage is ambiguous. Large firms are more diversified and less vulnerable to
bankruptcy. The size of a firm is likely to have positive relationship with leverage (Baral, 2004 and
Bauer, 2004). Abor (2008) contributed to the literature with the view that debt of large firms are
likely to be redeemed than the debt of smaller firms, reducing the agency costs associated with the
debt of larger firms. Thus, smaller firms are less diversified and more vulnerable to bankruptcy,
therefore there is a need for low debt ratio. The bankruptcy cost theory suggests the lower debt
level, the lower bankruptcy cost, and the higher debt level, the higher bankruptcy cost resulting
from higher volatile cash flows, (Baral, 2004). Converse view was documented in the work of
Jensen and Meckling (1976), the larger the firm becomes, the larger are the total agency costs due
34
to likelihood that the monitoring function is inherently more difficult and expensive in a large
organization compare to smaller organization.
� Growth opportunities
According to Baral (2004), “the agency cost theory and pecking order theory explains the
contradicting relation between growth and capital”. Firms with high growth opportunities
apparently, should be finance with equity source, which in turn reduces agency costs between
shareholders and managers. Agency cost theory suggests that equity controlled firms have the
motive to undertake assets substitution investment thereby investing sub-optimally to expropriate
wealth from the bondholders (Baral, 2004). Thus, firms with high growth opportunities not
financed by equity effectively transfers dividend from stock holders to debt holders. There is
contrary idea on the relationship between growth opportunities and financial leverage. The use of
debt is limited in firms with growth opportunities as in the case of bankruptcy, the value of growth
opportunities will be close to zero (Gaud et al., 2003). Some scholars argued that growth
opportunities are positively related to leverage, while others contend an inverse relationship.
Several empirical studies have documented an inverse and verse relationship between growth and
leverage ratio (see for example, Abor, 2008; Bauer, 2004; Baral, 2004; Khrawish and Khraiwesh,
2008). Bauer (2004) posits negative relationship between growth opportunities and leverage. On
the other hand, pecking order theory argues that growth firms with robust financing needs will
issue securities (external financing through debt issue) (Gaud et al., 2003 and Baral, 2004). Thus,
pecking order theory predicts positive relationship between growth opportunities and leverage.
� Profitability
This determinant of financial structure is in twofold. The first is on the side of static trade-off
theory that predicts positive relationship between profitability and leverage. This essentially
implies that the higher the profitability of a firm, the higher the debt capacity in relation to less
risky to the debt holders (Baral, 2004). While, the second fold is the pecking order theory that
predict inverse relationship, all things being equal (Myers, 1984).
The trade-off theory argues that more profitable firms should have higher debt ratio because of tax
benefit from the use of debt finance. Jensen and Meckling (1976) on their paper work contributed
immensely with the explicitly expression that one factor which encourage the use of debt is the tax
35
subsidy on interest payments. The gains from the tax subsidy will accrue entirely to the equity and
will provide an incentive to utilize debt to an end where the marginal wealth benefits of the tax
subsidy are presently equal to the marginal wealth effects of the agency costs associated with the
use of debt. The argument from free cash-flow theory predicted positive relations with the
suggestion that high profitable firms should use more debt as a disciplinary tool to managers, to
induce them to pay out cash instead of spending money on inefficient projects (Bauer, 2004).
According to pecking order theory firm prefer internal finance, adapt their target dividend payout
ratio, which are adjustable to the extent of valuable investment opportunities and if unpredictable
fluctuations in profitability and investment opportunities occurs that internally generated funds are
exhausted, firms issue the safest security first and external equity as a last resort (Myers, 1984).
Thus, profitable firms with sufficient earnings will rely more on internally generated funds as
oppose to external debt and equity source of finance.
� Tax
Trade-off theory suggests that a firm with a higher tax rate should employ more debt financing mix
due to more income from tax shield (Bauer, 2004). There are enormous studies on the tax effect
and financing decisions of a firm (Miller, 1977, Myers, 1984, Graham, 1999). Therefore, change in
the firms’ tax bracket has a significant implication on its financing decisions.
Myers (1984), given significant differences in effective marginal tax rate,
and given that the static trade-off theory works, we would expected to find a
strong tax effect in any cross-sectional test, regardless of whose theory of
debt and taxes you believe.
Therefore, marginal rate of company’s tax influences the financing behaviour of such company.
Gaud et al. (2003) contend that due to tax benefits accruing from the use of tax, companies have an
incentive to employ debt to their financing need. The author stressed further that firms with large
non-debt tax shields have a lower incentive to use debt as accord by tax shield. Firms with more
taxes is expected to have high tax shields benefit that accrued from debt, thus a positive
relationship between effective tax and leverage is predictable (Shahjahanpour et al., 2010).
36
� Business risk
Leverage ratio of a firm indicates firm’s risk exposure and its’ vulnerability to bankruptcy. A firm
that is highly levered apparently has high volatile net profit. Thus, leverage influences the rate of
return for an investment relatively to magnitude of unsystematic risk. Gaud et al. (2003) suggest
that firms with high business risk can lower the volatility of the net profit by reducing the level of
debt, which in turn will decrease bankruptcy risk and probability of expected benefit from the tax
shield will increase as well. The more volatile the firm’s earning stream, the greater the chance of
the firm defaulting and being exposed to bankruptcy costs (Abor, 2008). The advocate of agency
cost theory and bankruptcy theory predict significant relationship between financial structure and
business risk. The bankruptcy cost theory posits that the higher the volatility of firm’s stream of
cash inflows, the greater its’ chance of business failure relative to the degree of bankruptcy costs
(Baral, 2004). He contends further that relatively, as the probability of bankruptcy increases, the
agency problems related to debt become more severe similar to predictions underscore by other
scholars.
� Tangibility
Tangibility as determinant of financial structure is essentially concern with the type of assets
owned by the firm. Titman and Wessels (1988) contend that most capital structure theories argue
that the type of assets owned by a firm in some way affects its financing decision. Apparently,
these assets are used to secure debt issued by the firm and the value relatively to leverage ratio
determines the risk exposure of the investors. Bauer (2004) opines that the higher collateral value
of firm’s assets, the greater their ability to issues secured debt, which in turn lowers the risk of the
bondholders and increases the value of the assets in the case of bankruptcy. Thus, tangibility also
determines the risk of loan contract relatively to interest rate. That is, firm that has high tangible
assets which can be pledge to secure debt resulting to low default risk invariably induce low
interest rate and in turn lead to high leverage since the firm can borrow at low cost (Bradley et al.,
1984). Gaud et al. (2003) assert that tangible assets of firms in contrast to intangible assets have a
greater value in the case of bankruptcy and they are less subject to asymmetries. Cost associated
with adverse selection and moral hazard risks are reduced when the firm pledges tangible assets as
collateral (Abor, 2008, Gaud et al., 2003). However, firms with tangible assets that have greater
liquidation value relatively have easier access to external finance at lower cost, consequently
37
leading to higher debt ratio (Abor, 2008). Thus, tangibility resulting to greater liquidation value is
positive related to leverage.
� Payout ratio
Payout ratio is one of the determinants of financial structure predicted by pecking order theory to
have positive relationship with leverage. Baral (2004) viewed that bankruptcy costs theory pleads
for adverse relationship between dividend payout ratio and leverage. Low dividend payout means
increase in the internally generated funds (retain earnings) and low exposure to financial distress.
Firms however, avoid using external funding means whenever the internal funds are available and
firms adjust their dividend payout ratio in consideration to their investment opportunities and
profitability (Shahjahanpour et al., 2010). As highlighted in pecking order theory firms prefer
internally generated funds than external funding reflecting low income distribution as dividend
(low payout ratio) and high retention ratio (high retain earnings), consequently low leverage ratio
of the firm.
2.2 Empirical Review
2.2.1 Financial Structure and Firm Performance
The unrealistic assumptions and vague empirical evidence of the Modigliani and Miller value-
invariance propositions and paradox indifference in cost of financing propositions II contributed to
numerous empirical investigations on capital structure and firm performance. Adelegan (2007)
found negative insignificant relations between values and leverage in pooled regression and
negative significant relations between debt and change in leverage in the small-size sample. The
finding is in line with Miller (1977) hypothesis that debt has no net tax benefit because personal
income taxes on interest affect the corporate tax savings. Examining capital structure and financial
performance of selected business companies in Colombo Stock Exchange, Paratheepkanth (2011)
confirmed insignificant negative relationship between capital structure and financial performance.
Another study based on empirical research on the effects of capital structure change on security
prices in USA by Masulis (1980) revealed that stock price changes have the same qualitative
relationship to announced leverage changes regardless of the direction of the change.
Majumdar and Chhibber (1999) investigating the relationship between capital structure and
performance for a sample of Indian firms, found significant and inverse relationship between debt
38
equity ratio and corporate performance. Introducing several control variables in the study; Size,
Diversity, Advertising and Liquidity were found to been positively related to performance. While,
age, group, time and excise are negatively and significantly related to performance. However, the
inverse relationship between capital structure and firm performance as concluded may be due to
high cost of borrowing (rate of interest) in Indian capital market as well highly-leverage firm are
considerably less profitable than firms with a greater level of equity in their capital structure. Many
empirical studies using panel data regression estimation confirmed the inverse relations between
capital structure and firm performance (Schiantarelli and Sembenelli, 1997; Ebaid, 2009;
Adelegan, 2007; Zeitun and Tian, 2007; Cheng and Tzeng, 2011; and Onaolapo and Kajola, 2010;
Uremadu and Efobi, 2012; Azhagaiah and Gavoury, 2011; Mubashar et al., 2012).
Schiantarelli and Sembenelli (1997) empirically investigate the determinants and consequences of
the maturity structure of debt using data from a panel of UK and Italian firms. Including leverage
as a regressor to control for the impact of general financial pressure on productivity, evidence from
Italy shows negative and significant effect of leverage on firms’ performance. This means that
being under financial pressure does not lead to greater productivity. The result is not in line with
theoretical framework that is embedded on the role of financial pressure inducing managers to
undertake prudent decisions. Accordingly, they pointed that a high leverage may also weaken the
incentive to pursue efficiency, since borrowers, relative stake in the firm is smaller. However, the
impact of capital structure choice on firm performance based on a sample of non-financial
Egyptian listed firms from 1997-2005 by Ebaid (2009), using OLS multiple regression analysis,
revealed that capital structure measured by total debt to total assets and short term debt to total
assets impacts negatively on the firm performance measure by return on asset. On the other hand,
the study showed that capital structure measured by short term debt to total assets, long term debt
to total assets and total debt to total assets has no significant impact on firm’s performance
measured by return on equity and gross profit margin. Ebaid (2009) thereby conclude that capital
structure choice in general terms, has weak or no influence on the financial performance of listed
firms in Egypt.
Investigating the impact of capital structure on performance of Nigerian firm by Onaolapo and
Kajola (2010), debt ratio as a measure for capital structure was found to be negatively and
significantly related to two measures of firm performance (ROA and ROE). Studying the impact
of capital structure and liquidity on corporate returns in Nigeria by Uremadu and Efobi (2012), the
39
study covered 10 manufacturing firms for period of 2002-2006. Using OLS regression estimate the
study established that high corporate income tax regimes combined with high inflation rates in
Nigerian business environment may not have enabled firms to optimize use of long term debts to
maximize profitability. The authors posit that increasing proportion of long term debts compared
to equity in the capital structure mix of Nigeria firms will contribute to increases in corporate
profits of companies. Also it was noted that increasing proportion of both short term debts and
long term debts on the overall liability of the firm reduces corporate profitability. The study
however, showed that log linear analysis of the value of long term debts assumed a negative but
the result were found inconsistent with the prediction made earlier. Hence, the implication of this
according to the authors is that either inadequate long term debts were mobilized by corporate
entities in Nigeria or serious distortions may have existed in the economic and financial systems of
the economy within the period covered.
Cheng and Tzeng (2011) studying leverage and efficiency of Taiwan Manufacturing firms from
2000-2009, employed technical efficiency instead of financial accounting measure and found that
leverage is negatively related to technical efficiency in all industries but more significantly in
Textile industry. Co-alignment among corporate strategy, financial structure and firm performance
in non-financial sector of Pakistan by Mubashar et al. (2012), using panel data methodology
revealed that financial structure measured by debt ratio proved to have significantly negative
impact on firm performance measured by return on asset and free cash flow per share. The authors
concluded that their study has proved the implication of pecking order theory by Pakistani non-
financial listed firms. Thus, suggesting that if firms want to increase their profitability then, they
should avoid debt, if they are in need then, they have to sacrifice their profitability thereby
equipping themselves for future consequences. Also using pooled ordinary least square regression
to study the relationship between capital decisions and firm performance, Khan (2012) applied 36
engineering Sector firms in Pakistani listed on the Karachi Stock Exchange (KSE) during the
period 2003-2009. He however observed that financial leveraged measured by short term debt to
total assets (STDTA) and total debt to total assets (TDTA) has a significantly negative relationship
with the firm performance measured by return on assets (ROA), gross profit margin (GM) and
Tobin’s Q. But the relationship between financial leverage and firm performance measured by the
return on equity (ROE) is negatively insignificant. The author further concludes that firms in the
40
engineering sector of Pakistan are largely dependent on short term debt but debts are attached with
strong covenants which affect the performance of the firm.
Similarly, cross sectional regression analysis by Fama and French (1998) revealed that firm value
is negatively related to leverage and concludes that this inverse relationship is attributed to the
negative correlations of leverage with the proxies for profitability. And also, impact of financial
structure on firm’s performance in chemical sector of Pakistan by Amjed (2008) revealed
significant negative relationship between leverage and firms’ performance. Specifically, the results
revealed that long term debt of the industry is significantly low in turn portray significant negative
relationship with the financial performance of the firm.
On the other head, Tze-San and Heng (2011), Margaritis and Psillaki (2009), Nosa and Ose (2010),
Adeyemi and Oboh (2011), Dare and Sola (2010), Chowdury and Chowdhury (2010), Abu-Rub
(2012), and Skoljak and Luo (2012) provide empirical support for the body of theoretical literature
that argue capital structure to be positively related to firm performance. Margaritis and Psillaki
(2009) studied capital structure, equity ownership and firm performance using a sample of French
firms from low and high growth industries, which documented that higher leverage ratio, is
associated with improved efficiency over the entire range of observed data. Tze-San and Heng
(2011) using Malaysian construction sector from 2005 - 2008 with sample of 49 construction
companies confirmed this dividing the company into big, medium and small sizes based on the
paid up capital. The results specifically indicate that corporate performances of large companies
are partly affected by their changes in capital structure. The results of medium and small
companies are also partly affected by the changes in capital structure but the portion is lesser
compare to large companies.
Consistent with prior empirical evidence, Abu-Rub (2012) investigated capital structure and firm
performance using panel data procedure for a sample of 28 listed companies in Palestinian Stock
Exchange over the period of 2006 – 2010. The study showed that return on equity, return on assets,
earnings per share, market value of equity to the book value of equity and Tobin’s Q as a measure
of firm performance is positively related to capital structure measured by short term debt, long
term debt and total debt to total assets, and total debt to total equity at very significant level. Also,
Studying the impact of capital structure on firm’s value, Chowdury and Chowdhury (2010)
analysed 77 firms from different dominant sectors of Bangladesh capital market. The study
41
revealed significant positive relationship between capital structure and firm value. Thus, it was
observed that a change in current ratio, operating leverage, EPS, dividend payout ratio or share
capital of a firm may increase its value in the market. The study however, suggests that
maximizing the wealth of shareholders requires a perfect combination of debt and equity.
Similarly, Dare and Sola (2010) employing panel data regression analysis of Nigerian Petroleum
Industry found significant positive relationship between leverage ratio and corporate performance
and suggest the need for petroleum industry in Nigeria to improve on their leverage ratio.
Adopting different measures such as growth opportunity, non-debt tax shield, tangibility,
profitability, and earnings volatility as proxies for leverage ratios, Nosa and Ose (2010) in their
study showed a significant positive relation with corporate performance except volatility. But
empirical investigation by several authors adopted these measures as control variables not as
proxies for leverage ratios (for example, see; Majumdar and Chhibber, 1999; Zeitun and Tian,
2007; and Onaolapo and Kajola, 2010; Cheng and Tzeng, 2011; and Adeyemi and Oboh, 2011).
Adeyemi and Oboh (2011) incorporating control variables in their study found positive relation
with control variables and firm performance as well as leverage ratio with market value. Skopljak
and Luo (2012) studying capital structure and firm performance in financial sector using explicitly
Australian data, found that increase in leverage ratio lead to increase in bank performance at
relatively low levels of leverage while at relatively high levels of leverage, the effect of financial
distress exceeds the beneficial effects of debt. Previous empirical study by Pratomo and Ismail
(2007) using Malaysia data to survey Islamic Bank performance and capital structure confirmed
the result that the more levered bank is better than the less or unlevered bank as regard to profit
efficiency.
Also in conformity with relevance theory, Zuraidah et al. (2012) studying capital structure effect
on performance of Malaysian firms employed ROA and ROE as performance measure, while short
term debt (STD), long term debt (LTD) and total debt (TD) as capital structures. The study
covering 58 firms from 2005 to 2010 showed that only STD and TD have significant relationship
with ROA while ROE has significant relationship on each debt level. However, model estimation
for lagged variables revealed that non of lagged values for STD, LTD and TD has significant
relationship with performance. Likewise Mojtaba and Shahoo (2011) examined the relationship
between financial structure and firms performance in firms traded on the Tehran stock exchange,
the study revealed significant relationship between financial structure and ROA as performance
42
measure, but insignificant relationship was found between financial structure and ROE as
performance measure.
2.2.2 Financial Structure and Tax Effect
DeAngelo and Masulis (1980) cite Miller and Modigliani (1966) study of 63 electric utility firms
that documented a significant positive relationship between market values of the firm and the debt
tax shield. They conclude that the evidence may justifiably be criticized because of limitations in
the statistical methodology as well as the inherent difficulties involved in controlling for cross-
sectional differences in firms’ underlying asset values and biases associated with studying a
regulated industry. DeAngelo and Masulis (1980) observation on offer announcement effects on
preferred stock revealed that the corporate tax effect exceeds the bankruptcy cost and distribution
effects for these preferred stock issues. Another study by Long and Malits (1985) shows positive
relationship between; tax shield and long term debt, and capital expenditures and financial
leverage. Given that a firm must seek an outside source of funds, it choice between debt and equity
will depend in part on the magnitude of potential agency costs of debt. They conclude that the
findings provide direct empirical evidence that the moral hazard problem is important and that
investment and financing decisions are not independent. Similarly, Graham (1996) paper titled
“debt and the marginal tax rate”, tests whether the incremental use of debt is positively related to
simulated firm-specific marginal tax rates that account for net operating losses, investment tax
using annual data from more than 10,000 firms from 1980-1992. The result showed that positive
influence of Marginal Tax Rate (MTR) on debt policy is robust to purely cross-sectional analysis,
although there is a noticeable deterioration in the relation between debt policy and Marginal Tax
Rate (MTR) in 1986. The outcome as the author reported may be possibly due to the tax Reform
Act 1986. He further concludes that the effects of Marginal Tax Rate (MTR) are generally
significant when data are aggregated over three or 12 years. Hence, the study provides robust
empirical evidence in favour of relationship between leverage decisions and tax status. Adelegan
(2007) researched on effect of taxes on business financing decisions and firm value in Nigeria and
found negative relationship between debt and value, which is consistent with information
asymmetry model of Myers and Majluf (1984) and Myers (1984). Thus, this is as a result of
information conveyed by firm’s financing decision. This model predicts that a change in a firm’s
financing decisions contains information about stock value. Investors know that firms tend to issue
43
risky securities when they are overvalued. Consequently, firms follows pecking order theory as a
result that new issues meet with price discounts.
In addition, Barclay et al. (2006) studied on the debt capacity of growth options and showed robust
empirical support for the prediction that the relation between growth options and book leverage
ratios should be negative. The result is consistent with previous empirical evidence (Faulkender
and Peterson, 2006). In attempt to study the effect of firm and industry debt ratios on market value,
Hatfield et al. (1994) found that relationship between a firm’s debt level and that of its industry
does not appear to be of concern to the market. The result shows that high debt firms has
significant negative market reactions for several intervals, but the difference between this high and
the low debt firm was not statistically significant. The authors inferred that the market does not
consider industry average for leverage as discriminators of firms’ financial leverage. Sen and Oruc
(2008) testing pecking order theory in Istanbul Stock Exchange Market from 1993-2007, find a
significant negative relationship between total asset, profitability, current ratio, the ratio of fixed
assets to total assets and leverage ratio. Their result support the view that, although there is tax
shield benefit from the use of debt but information asymmetry problem and bankruptcy costs may
outweigh this benefit and in turn deteriorate net present value of the firm. The methodologies
adopted by some of the studies reviewed in this chapter, will be employ in this study, to enable the
researcher critically investigate the impact of capital structure on firm performance.
2.3 Summary of Review of Related Literature
Financial structure is the combination of debt and equity capital by a firm on the course of funding
its corporate investment. The relevance and irrelevance of financial structure theory in explaining
variation of firm performance has been ambiguous due to extensive arguments from diverse
perception. Within the established theories of financial structure; the static trade-off theory, agency
cost theory, pecking order theory and other theories are well established (Brounen et al., 2005). In
the spirit of Myers (1984), “the capital structure puzzle is tougher than the dividend one”.
Modigliani and Miller theorems argued that with well functioning markets, no taxes and rational
investors, can ‘undo’ the corporate financial structure by holding positive or negative amounts of
debt, the market value of a firm depends only on the income stream generated by its assets (Bailey,
2010). Thus market value of a firm is independent of its financial structure. Incorporating tax in
their subsequent studies, the theory argued that firm value is an increasing function of leverage due
44
to the tax deductibility of interest payments at the corporate level (Berens and Cuny, 1995 and
Hull, 1999). Invariably owners of corporation reap no gain, whatever from their use of tax-
deductable debt rather than equity capital when even personal income tax and corporate tax is
applicable (Bailey, 2010). Theoretical and empirical body of knowledge emanating from MM
theorems have considered a variant of wealth effects linked to leverage including bankruptcy and
agency effects but disagreement about the strength of these effects and tax shield advantage still
prevail (Hull, 2007).
Ross (1977) points that the irrelevance theory assumes the existence of symmetric information
with the suggestion that there will be no systematic relationship between the financing decision
and the value of the firm. But the conventional view assumes the existence of asymmetric
information where financing decision affects market value (Leland and Pyle, 1977). The authors
assumed statistical positive but not causal relationship between debt and value of “seemingly
similar” projects. In the same spirit, Jensen and Meckling (1976) argue that the net effect of the
increased use of external debt increases the total agency costs and increases optimal fraction of
external debt obtained from the sale of external equity. Desai et al. (2003) posit that the use of
debt rather than equity finance grows as the corporate tax rates rises. Therefore, high corporate tax
rates may lead to greater corporate indebtedness owing to firm’s need to enjoy debt tax shield
benefit. Similar argument was demonstrated in the work of Miller (1977) that the year to year
variation in debt ratio reflected primarily the cyclical movement of the economy.
However, trade-off theory established that optimal capital structure of a firm is a trade-off
between the benefit from tax advantage (tax shield) and cost of financial distress (bankruptcy
costs) from employing external capital (debt), holding the firm’s assets and investment plan
constant (Myers, 1984, Bradley et al., 1984, Zambuto et al., 2011). Hence, value maximizing firms
attain an optimal capital structure by offsetting the corporate tax benefits of debt against the
personal income, bankruptcy cost and agency cost associated with debt. While, firms that adopt
pecking order of finance do not have a target debt ratio, because the ordering determines their
choice of issuance of new capital. The degree of asymmetric information determines the relative
costs of each source of finance. The more severe the asymmetric information, the more riskier the
investment for investors, invariably the higher the price of the security (Octavia and Brown, 2008).
With the presence of asymmetric information a firm is better finance by internally generated funds
than external funds.
45
On the other hand, agency theory argues that the choice of financial structure may help mitigate
agency costs that arise as a result of separation of ownership and control. High leverage ratio
reduces the agency costs of outside equity and increases firm value by constraining or encouraging
managers to act more in the interests of shareholders (Berger and Patti, 2002). But the given
incentive to the firm will benefit shareholders at the expense of debt-holders. The adjustment of
leverage ratio to attain incremental value may lead to high agency cost if not rationally employed.
The market timing of financial structure decision as argued by market timing theory is another
rational for value maximization. Accordingly, a firm issue equity when the stock prices are
perceived to be overvalued and buy back when there are undervalued. Financial structure decisions
are determine by the fluctuations in the stock price.
There are many determinants of financial structure which can be categorically classifies as internal
and external determinants. Macroeconomic indicators such as tax policy of government, inflation
rate, capital market condition, among others are the major external factors that affect the financial
structure of a firm. The internal determinants which are major focused of a firm and specific
factors (firm characteristics) that affect the financial structure and firm performance of a firm
relatively. Thus internal factors are size of the firm, growth opportunities, profitability, business
risk, tangibility and payout ratio. Financial liberalization results in the development of capital
market and overall financial system, however, corporate investment depends mostly on output and
profits than macroeconomic and other policy variables (Mahmud et al., 2009). Thus, firm’s
performance in most cases reflect its’ corporate decisions in developed and most emerging
financial system. Stock market development leads to substitution of equity for debt, the effect
would be a decline in the debt-equity ratio (Bokpin and Isshap, 2008). According to Afrasiabi and
Ahmadina (2011) “an issue that is strictly connected with the choice of financing sources is risk
and return”. Therefore, in financial structure decisions there is need to ensure that marginal benefit
accrued from employment of external capital outweigh bankruptcy cost and agency costs resulting
from the use of this funds. A proper balancing of debt and equity is imperative in order to ensure a
trade-off between risk and return to the shareholders (Khadka, 2006). Thus, this financing decision
in turn leads to value maximization.
Majumdar and Chhibber (1999) attribute high cost of borrowing (rate of interest) to negative and
significant relationship between capital structure and firm performance. Highly levered firms are
considerably less profitable than firms with a greater level of equity in their capital structure. In
46
addition, high leverage may also weaken the incentive to pursue efficiency, since borrowers,
relative stake in the firm is small. This is consistent with the observation of Khan (2012) that
financial leverage has a significantly negative relationship with the firm performance. Engineering
sector studied by the author is observed to be largely dependent on short term debt but debts are
attached with strong covenants which affect the performance of the firm. Fama and French (1998)
also confirmed that firm value is negatively related to leverage which is attributed to the negative
correlations of leverage with the proxies for profitability.
Empirical body of knowledge on the other hand have showed that higher leverage ratios are
associated with improved efficiency (firm performance) over the entire range of observed data
(Margaritis and Psillaki, 2009; Tze-San and Heng, 2011; Dare and Sola, 2010, Nosa and Ose, 2010
and Adeyemi and Oboh, 2011). Skopljak and Luo (2012) established that improvement in firm
performance induce by leverage ratios is attributed to low levels of leverage while, at a relatively
high levels of leverage, the effect of financial distress exceeds the beneficial effects of debt. Given
that a firm must seek an outside source of funds, it choice between debt and equity will depend in
part on the magnitude of potential agency costs of debt (Long and Malitz, 1995). The test of
pecking order theory by Sen and Oruc (2008), confirmed the existence of tax shield benefit from
the use of debt but information asymmetry problem and bankruptcy costs may outweigh this
benefit and in turn deteriorate net present value of the firm.
47
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CHAPTER THREE
RESEARCH METHODOLOGY
3.1 Research Design
Research design essentially concerns the specification of procedures, which connect theoretical
predictions to the inquiry strategies and empirical material collection methods to address research
problem. In other words, research design involves a format on systematic method of data
gathering, procedures and method of analyzing necessary data (Onwumere, 2005 and Ibe, 2003).
Thus, it is the master plan upon which the statement of problems is addressed. The nature of the
problem under investigation and the corresponding objectives however, determine the approach
and method to be employed.
The study being an empirical analysis of the impact of financial structure on firm performance,
secondary data were used. Ex-post facto research design was employed in obtaining, analyzing and
interpreting the relevant data for hypotheses testing. The rationale for the variety is that ex-post
facto research design allows the researcher the opportunity of observing one or more variables
over a period of time (Uzoagulu, 1998). Specifically, panel data were adopted in data analysis.
3.2 Nature and Source of Data
The secondary data employed in this study have been adopted in previous studies with regard to
financial structure and firms’ performance, and other related studies. There are several studies
performed in the area and the researcher has gathered information from these studies to enhance
this research work and to proffer solution to the research problem. The dataset employed in this
study were generated from Nigeria Stock Exchange factbook and annual reports and statement of
accounts of quoted firms in Nigeria. Firm annual statements and reports are deemed to be reliable
because they are statutorily required to be audited by a recognized auditing firm before publication
(CAMA, section 331-335) in Onwumere et al. (2011). The items of interest in the financial
statement are assets, liabilities, shareholders’ funds, and earnings for each financial year.
3.3 Population and Sample Size
Data for statistical analysis in this study were gathered from financial statement of sampled firms.
Owen and Jones (1977) contend that most statistical information is obtained by examining the
56
sample which is truly representative of the population. These financial statements as expected from
the quoted firms are prepared and published in compliance with the accounting practice, which
include balance sheet and income statement of selected firms for the period of 2001-2012. The
dataset contains detailed financial information about each firm for each financial year. Sampled
firms were selected based on availability of data for the period and also financial sector firms are
excluded from the study. The researcher put many factors into consideration in the selection of the
sample firms. Such factors as highlighted by the researcher includes: firms that were listed in NSE
before the year of inception of the study, firms that change their financial accounting year-end
within the period of the study were excluded in the sample, firms that ceased operation at any point
during the period of the study were also be excluded, and as well as firms that had problems with
NSE and Securities and Exchange Commission (SEC) within the period under review. These
criteria were adapted in order to guide against data omission and ensure uniformity in the
presentation. Apparently, the selection of 51 firms was randomly sampled thereby ensuring that
most sectors of the industrial classification according to NSE are well represented.
3.4 Description of Research Variables
The variables used in this study are largely adopted from existing literature, in line with the
research problem and research objectives. The difference and similarities for the measurement of
financial structure and performance ratios were compared among the literature. Thus, dependent
and explanatory variables of the study have been determined according to the approach used by the
previous studies and how far data will be available for measurement purposes. Chen (2004) posits
that book value is used for the calculation of variables whenever applicable due to the fact that
only about 30% of the shares issued are tradable and there are extraordinary capital gains resulting
from secondary share trading. Miller (1977) contends that book value measures might give better
insight to corporate capital structure objectives than market value measures of leverage, which is
highly sensitive to changes in the level of stock prices. Consequently, the study employed only
book value measures of financial structure and firm performance. They are explained below as
follows:
3.4.1 Dependent Variable
Firm performance as the dependent variable of the study has different measures. According to
Ujunwa (2012) unbiased performance measurement is necessary for both strategic and diagnostic
57
purposes. This study employed Return on Assets (ROA) as firm performance measure. Wahla et
al. (2012) revealed that firm’s market value is based not on its investment projects only but other
factors such as dividend policy, its governance/control and ownership structure which also add
value to the firms. However Tobin’s Q as a market performance measure was not considered. The
market value of debt, which is required in the measurement of Tobin’s Q is not readily provided in
the annual reports and statement of accounts of the selected firms. In order to ease this problem
many scholars employed modified form of Tobin’s Q, which are considered to be subjective and in
turn may influence the outcome of the study (Kajola, 2008). Zeitun and Tian (2007) pointed that;
as agreed by many researchers; Tobin’s Q as a market performance measure is a noisy signal and
not a good performance measure due to its limitations. Performance is either financial or
organizational. Zeitun and Tian (2007) citing Chakravarthy (1986) and Hoffer and Sandberg
(1987), financial performance which involve maximizing profit on assets and maximizing
shareholders’ wealth shows the firm’s effectiveness. While operational performance measures such
as growth in sales and market share provides a broad definition of performance as they focus on
the factors that ultimately lead to financial performance. According to Onaolapo and Kajola (2010)
and Zeitun and Tian (2007) ROA and ROE are the most commonly measures of firm performance.
3.4.1.1 Return on Asset (ROA)
Return on Asset (ROA) as accounting measure of performance is derived by dividing profit before
interest and tax with total assets of the company.
That is, ROA = AssetTotal
TaxandInterestBeforeofitPr
This proxy variable has been employed by many researchers as performance indicator (Ujunwa,
2012; Zeitun and Tian, 2007; Onaolapo and Kajola, 2010; Tze-Sam and Heng, 2011; Azhagaiah
and Gavoury, 2011, Zeitun , 2009, and Khan, 2012). Ujunwa (2012) and Onaolapo and Kajola
(2010) posits that ROA can be viewed as a measure of management efficiency in utilizing all the
assets under its control, which ultimately belong to shareholders irrespective of its source of
financing. This is a widely accepted measure of financial performance. We predict that ROA is
positively and significantly related to financial structure.
58
3.4.2 Independent Variables
Explanatory variables of the study are financial structure. This is portion of firm’s asset financed
by any type of fixed charge such as loan facilities, overdraft facilities, lease, etc. The management
of financial structure measures the degree to which firms are employing financial leverage and, as
such are of interest to creditors and owners alike, as argued by many scholars to invariably
influence firm’s value (Brealey and Myers, 1996). Both long and short-term creditors are
concerned with the proportion of leverage a firm employs, because it indicates the firm’s risk
exposure in meeting debt service charges (that is interest and principal repayment). A firm that is
heavily financed by debt offers creditors less protection in the event of bankruptcy. And also the
expected indirect and direct bankruptcy costs offset the other benefits from leverage. This view has
been confirmed by bankruptcy cost theory. There are several types of financial structure, but we
adopted three measures of financial structure. These are Total Debt Ratio (TDR), Long Term Debt
Ratio (LTDR) and Short Term Debt Ratio (STDR). As highlighted earlier, these measures were
based on book values of the firm. These measures are used based on two reasons which may be
highlighted as such: the payment of debt depending upon the book value of the loans and not on
the market value of debt. Also short term debt ratio is adopted because the financial structure of
firm in developing countries like Nigeria is primarily based on the short-term debt as compared to
the long term debt (Booth et al., 1999 and Awan et al., 2011).
3.4.2.1 Total Debt Ratio (TDR)
We adopted this variable from many scholars, it is measured as the ratio of total debt to total
assets (Kasozi and Ngwenya, 2010; Onaolapo and Kajola, 2010; Zeitun and Tian, 2007; Tze-Sam
and Heng, 2011; Awan et al., 2011; Baral, 2004; Bauer, 2004; Chen,2004; Gaud et al., 2003;
Khrawish and Khraiwesh, 2010; Khan, 2012; Azhagaiah and Gavoury, 2011).
That is; Total Debt Ratio = AssetsTotal
DebtTotal
This constitutes overall (aggregate) fixed-charge external capital employed by the firm to finance
its assets. Khrawish and Khraiwesh (2010) point that total debt ratio demonstrates the relationship
between total liabilities and total assets. It measures the proportion of a firm’s total assets that is
financed with creditors’ funds. As used here, the term debt encompasses all short-term liabilities
59
and long-term liabilities. Some scholars prefer to use a narrower definition of debt considering
only interest-charging liabilities such a long-term debt or bonds, notes payable, and lines of credit.
3.4.2.2 Long Term Debt Ratio (LTDR)
Long term debt ratio as accounting (book value) measures the long term debt employed by the
firm. That is, an obligation having a maturity more than one year from the date it was issued. It is
measured as the ratio of long term debt to total assets.
That is; LTDR = AssetsTotal
DebtTermLong
The adoption of this proxy variable as a measure of financial structure has been applied by many
researchers (Chen, 2004; Timan and Wessels, 1988; Zeitun and Tian, 2007, Tze-Sam and Heng,
2011, Long and Malitz, 1985).
Hence, it has been noted that LTDR is a good measures of leverage ratio in developing countries
like Nigeria due to fund miss-match constrained by limited long term debt.
3.4.2.3 Short Term Debt Ratio (STDR)
Short term debt constitutes short term liabilities accrued to the firm. This is debt obligation of the
firm payable within one year. Short term debt ratio is measured as short term debt divided by total
assets.
That is; STDR = AssetsTotal
DebtTermShort
This measure of leverage ratio has been employed by numerous researchers such as Titman and
Wessels (1988), Zeitun and Tian (2007), Long and Malitz (1995), and Khan (2012).
Apparently, it has been noted as a good measure of financial structure in developing countries like
Nigeria where the proportion of this ratio constitutes mostly entire amount of the firm’s total debt
ratio. Lucey and Zhang (2011) asserts that in emerging market firms invariably obtain additional
debt finance owing to credit market integration, but primarily at short maturities. They stressed
further that the main reason for high proportion of short debt is that the weak financial and legal
60
institutions in developing countries will force creditors to use short term debt to monitor and
discipline borrowers’ behaviour.
3.4.3 Control Variables
Control variables are factors that influence firms’ performance in one way or other. Majumdar and
Chhibber (1999), Zeitun and Tian (2007), Onaolapo and Kajola (2010), and Cheng and Tzeng
(2011) contend that there are a number of factors which impact on firm performance. Majumdar
and Chhibber (1999) stressed further that these factors may be firm-related, industry related or
related to aspects of institutional environment and have to be controlled. Due to the scope of this
study, the interest of the researcher is narrowed down to firm related factors, as the endogenous
factors, most policy makers of the firm can control as intrinsic factors which impact on
performance. Barney (2001) contends that success of a firm significantly depends on the strategic
resources under its control.
3.4.3.1 Size of a Firm
Several authors have suggested that performance of a firm is related to firm size. Zeitun and Tian
(2007), Majumdar and Chhibber (1999), Cheng and Tzeng (2011), Onaolapo and Kajola (2010),
Zeitun (2009), Pratomo and Ismail (2007), and Khan (2012) provide empirical evidence that the
size of a firm appear to determine a larger proportion of firms’ performance. Titman and Wessels
(1988) asserts that relatively large firms tend to be more diversified and less prone to bankruptcy.
This supports the arguments that large firms should be more highly leveraged. The size of a firm
determines economies of scale enjoyed by the firm. Larger firms that have a greater variety of
capabilities and can utilize the high leverage ratio efficiently with relative positive returns.
Conversely, larger size, if not efficiently utilized leads to negative returns. Titman and Wessels
(1988) opines that the cost of issuing debt and equity securities is related to firm size. Apparently,
small firms pay high cost to finance their investment needs than large firms. The size of a firm is
measured by natural logarithm of total assets (Zeitun and Tian, 2007, Onaolapo and Kajola, 2010)
and alternative measures of firm’s size are the natural logarithm of sales (Titman and Wessels,
1988; Majumdar and Chhibber, 1999; Zeitun and Tian, 2007 and Zeitun, 2009 ) and quit rates
(Titman and Wessels, 1988). Zeitun (2009) posits that logarithm of total sales has lower
explanatory power than total assets. This study will employ natural logarithm of total assets as a
61
measure of firm size. The introduction of the proxy variable SIZE as an indicator of firm size is
expected to be positively related to firm performance.
3.4.3.2 Age of a Firm
Different authors have considered the age of a firm as an important determinant of firm’s
performance. Thus, the introduction of the control variable AGE is measured as the log of number
of years since inception to the date of observation. Majumdar and Chhibber (1999), and Onaolapo
and Kajola (2010) citing the work of Stinchcombe (1965) contends that older firms can acquire
experience based economies and mitigate the liabilities of newness. Durand and Coeurderoy
(2001) studying age, order of entry, strategic orientation, and organizational performance found
that a first-mover advantage in terms of organizational performance. In the same vein, Hajipour
and Gholamzadeh (2010) studying the effects of market entry strategy dimensions on the
performance with a sample of 118 manufacturing firms found that order of entry and product
positioning affect performance. They stressed further that pioneers gain advantages in terms of
stronger competitive position and higher customer satisfaction, which in turn do increase
profitability. Prominent authors in their empirical study have employed this measure as control
variable in the study of this nature and similar studies (for example, Majumdar and Chhibber,
1999; Zeitun, 2009 and Onaolapo and Kajola, 2010). The researcher predicts firm’s age to be
positively related to the firm’s performance.
3.4.4 Random Variables (Stochastic)
As highlighted earlier, there are other control variables that impact on the performance of the firm.
Stochastic variables are those variables that can also affect on firm’s performance. Koutsoyiannis
(1977) asserts that random variable in a correctly specified model, absorbs primarily stochastic
variations in the dependent variable produced by omitted variables in the equation and possibly
errors of measurement. These variables may be firm’s related factors (endogenous) and
institutional environment related factors. The latter factors are exogenous factors that cannot be
controlled by the firm. Koutsoyiannis (1977) pointed out that the values of the disturbance variable
are independent of the values of the regressors. In this study the random variables are firm’s
Diversification, Financial Openness, prevailing interest rate, rate of inflation, Foreign Ownership,
Firm’s Coverage and Excise and Imports duties.
62
3.5 Technique for Analysis
To obtain the observed values on the expectation of the impact of financial structure on firm
performance, panel data surveyed over a ten year period was employed. Panel data structure allows
us to take into account the unobservable and constant heterogeneity, that is, the specific features of
each quoted firm. The researcher employed pooled Ordinary Least Square (OLS), Fixed Effects
and Random Effects regression models to test the various hypotheses. Pooled OLS regression
technique is popular in financial studies owing to its ease of application and precision in prediction
(Alma, 2011). In addition, OLS method has been employed in a wide range of economic
relationships with fairly satisfactory results (Koutsoyiannis, 1977). Citing the work of Gaur and
Gaur (2006), Ujunwa (2012) stressed that fixed effects and random effects models will aid to
observe variations among cross-sectional units simultaneously with variations within individual
units over time. It assumes that variables are strictly time disparity or time invariant. This
undermines an exploration of the effect of slow changing within individual firms’ factors. Hence,
the rational for adopting Fixed Effects and Random Effects models estimator as additional test is to
enable the researcher control time contrast and time invariant variables, and thereby control for the
effect of the unobserved heterogeneity in the dataset. Ujunwa (2012) opines that coefficient of
estimations are reliable when regression parameters do not change over time and do not differ
between various cross-sectional units. Therefore, when the regression estimation differ widely
between the two models (Fixed and Random Effects models), the adoption of Hausman test will be
essential. Panel data over the period from 2001-2010 is used and in line with notable literature,
such as the work of Majumdar and Chhibber (1999), Zeitun and Tian (2007), and Onaolapo and
Kajola (2010), firm’s performance measure was regressed on each of the variants of financial
structure and other control variables holding other factors that may affect firm’s performance not
included in the equation constant. These analytical techniques will enable the researcher attain
justifiable and robust results.
y = b0 + b1xit + b2zit + µ
Where: y = dependent Variable
b0 = Constant (intercept) of y
xit = Independent Variables
63
zit = Control Variables
b1 and b2 = Coefficient of Independent and Control Variables.
µ = Random (stochastic) variables
3.6 Model Specification
The empirical models estimated in the study were proxied as follows:
ROA = Return on Asset
TDR = Total Debt Ratio
LTDR = Long term Debt Ratio
STDR = Short term Debt Ratio
SIZE = Firm’s Size
AGE = Firm’s Age
Hypothesis i
Looking at the first hypothesis which states that total debt ratio does not have positive and
significant impact on firm performance;
ROA = b0 + b1TDR + b2SIZE + b3AGE + µ…………………………………….………….…(3.6.1)
Hypothesis ii
The second hypothesis of the study states that long term debt ratio does not positively and
significantly impact on firm performance;
ROA = b0 + b1LTDR + b2SIZE + b3AGE + µ…………………………………...……….…(3.6.2)
Hypothesis iii
Our third hypothesis states that short term debt ratio does not have positive and significant impact
on firm performance;
ROA = b0 + b1STDR + b2SIZE + b3AGE + µ……………………………………………....…(3.6.3)
64
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67
CHAPTER FOUR
DATA PRESENTATION AND ANALYSIS
4.1 Data Presentation
The data presented below are those deemed necessary for the analysis of the various objectives
formulated in the study. The financial structure indicators used in the analysis were delineated into
total debt ratio, long term debt ratio and short term debt ratio, while firm performance measure
employed in the analysis is return on asset. The aggregate ratios of the dataset from the sample
firms obtained for analysis purpose are show in the tables below.
Year ROA TDR LTDR STDR
2001 7.007 32.063 4.318 27.817
2002 6.327 32.567 5.333 26.744
2003 6.175 32.048 5.434 26.487
2004 6.375 31.439 5.676 25.768
2005 4.3823 33.49 7.352 26.149
2006 4.459 33.205 7.183 26.025
2007 5.5768 33.193 7.739 26.193
2008 7.004 32.076 7.5021 24.662
2009 5.954 32.45 8.128 24.325
2010 6.518 30.037 8.541 21.473
2011 6.396 30.110 9.749 20.392
2012 4.124 26.825 8.004 18.698
Source: computed from financial statement of the sample firms
The summary of aggregate values of research variables of the sample firms as defined over a ten
years period are presented in table 4.1.1 above. While figure 4.1.1below represents the graphs of
the trend of the variables. The graphs allow simultaneous examination of the employed data, while
clearly displaying the behaviour of the sample firms’ overtime as a reflection of quoted firms. A
cursory look at the graph revealed that the variables fluctuated over the period covered, ROA over
the period of study revealed remarkable fluctuations. The trend is apparently attributable to change
in financial structure of the selected companies and other significant government policies and
changes in macro-economic variables (Izedonmi and Abdullahi, 2011). The highest aggregate ratio
recorded in 2001 could be attributed to dividend of socio-political stability occasioned by the
inception of democracy in 1999. This has also brought about more advancement in technology and
Table 4.1.1: Summary of the Aggregate Value of Research Variables
68
other technical knowledge which in turn enhanced performance of the firms (World Bank, 2002).
Similarly, the steep downward and upward fluctuation for ROA revealed in fig. 4.1 is attributed to
internal and external characteristics of the firms (Barney, 2001). While, between 2005 and 2007
recorded a significant slope in the graph pointing to reforms in financial and real sectors of the
economy.
Furthermore, a glance at the graph shows that sample firms aggregate TDR over the period
exhibited steep upward and downward movement. It can be deduced that the above effects is an
indication of underdeveloped nature of debt market where major proportion of total debt ratio is
made of short term debt ratio that are redeemable within a short duration (Mubashar, et al., 2012).
Thus induce regular payment of debt (principal and interest) to avoid liquidation effects. There was
an occasional hike in the TDR in 2002 but preceded immediately by drop in 2003 and 2004, which
later revealed persistent upward movement in the subsequent year because of landmark reforms
across banking, insurance and pension sectors. However, TDR as at 2006-2008 indicated
downward movement. The rational for the downward movement is attributed to growth in
Nigerian Stock Market brought about by remarkable policies in financial sector more especially
bank consolidation in 2005 and 2007 transformation in Nigerian Capital Market (Iganiga, 2010).
Hence 2005/2007 recapitalizing banking and insurance companies encouraged companies in the
real sectors to approach the stock market, which encouraged investment in equity market leading
to high market capitalization and liquidity resulting to high turnover ratio (Ayadi and Adegbite,
2008). In 2007 Standard & Poor’s (S&P) described the Nigeria equity market as the fastest
growing in the emerging markets universe. Increase in capitalization of the Stock Exchange was
significant in the year. Thus, it was recorded that capital based of the consolidated banks led to
growth in stock market activities (Adegbaju and Olokoyo, 2008). On the other hand, upward slope
in TDR as at 2009 is attributed to global financial crisis that crippled economic activities thereby
stimulating companies’ leverage ratio to ensure sustainability. However, the tempo dropped
tremendously in the subsequent years owing to numerous policies introduced by regulatory bodies
to relieve the effect of financial meltdown (Nwankwo, 2011, Sanusi, 2011). Apparently, there was
improvement in overall macroeconomic environment and socio-political stability manifesting in
enhanced corporate governance, high market liquidity (arising from increased portfolio and foreign
direct investment) and increased attractiveness of investment opportunities in Nigeria (Otch, 2010,
Sanusi, 2011).
69
Long Term Debt Ratio (LTDR) over the period of study shows a persistent upward movement
confirming a gradual growth in capital market activities. This is evident in table 4.1.1 and figure
4.1.1c. The reason for this could be attributed to regulation that mandated increases in capital and
the subsequent voluntary capital sourcing by banks and insurance companies (Iganiga, 2010).
Occasional drop were only observed in 2006 and 2008 as well as 2012. While in conformity with
enhancement in capital market activities as noted earlier, short term debt ratio (STDR) exhibited
downward movement. This change is attributed to the growing efficiency of market operators, a
growing investment culture in the country, as well as encouraging economic environment being
nurtured by the democratic government (World Bank, 2002). Table 4.1 and figure 4.1d reveals
that little upward fluctuation in 2005 and 2007 were recorded in STDR, while downward
movement were recorded in other subsequent years. This is attributed to gradual development in
debt market brought about by market deregulation and market determined pricing as well as other
macroeconomic policy such as commencement of T3 trading cycle in 2000, the repealed and re-
enacted of Investment and Securities Act No. 45 amongst others (Nwankwo, 2011, Izedonmi and
Abdullahi, 2011, Iganiga, 2010)
70
0
1
2
3
4
5
6
7
8
2000 2005 2010 2015
ROA
0
5
10
15
20
25
30
35
40
2000 2005 2010 2015
TDR
0
2
4
6
8
10
12
2000 2005 2010 2015
LTDR
0
5
10
15
20
25
30
2000 2005 2010 2015
STDR
Fig. 4.1.1 Graphical Presentation of the Summary of Aggregate Values of Research Variables
Source: Estimated from table 4.1.1 Using Microsft Excel Computer Statistics (Version 2010)
a b
c d
71
Year ROA TDR LTDR STDR
2001 0.137392 0.628686 0.084667 0.545431
2002 0.124059 0.638569 0.104569 0.524392
2003 0.121078 0.628392 0.106549 0.519353
2004 0.125 0.616451 0.111294 0.505255
2005 0.085927 0.656667 0.144157 0.512725
2006 0.087431 0.651078 0.140843 0.510294
2007 0.109349 0.650843 0.151745 0.513588
2008 0.137333 0.628941 0.1471 0.483569
2009 0.116745 0.636275 0.159373 0.476961
2010 0.127804 0.588961 0.167471 0.421039
2011 0.131537 0.614497 0.198968 0.416165
2012 0.093721 0.609658 0.181910 0.424963
Source: computed from financial statement of the sample firms
Table 4.1.2 above and figure 4.1.2 below are schedule and chart representing the summary of the
average values of the variables employed in the study. Firm performance proxy by return on asset
(ROA) and variants of leverage ratios such as total debt ratio (TDR), long term debt ratio (LTDR)
and short term debt ratio (STDR) were proxies for financial structure. A cursory look at the charts
depicts different behaviours among the variables. Steep downward and upward fluctuations
exhibited by ROA is attributed to internal and external characteristics of the firms (Barney, 2001),
while, between 2005 and 2007 recorded a significant slope in the graph pointing to reforms in
financial and real sectors of the economy as noted earlier. Specifically, average performance of
Nigerian quoted firms in 2001 was 13.73% and decrease to 12.4% and 12.1% in 2002 and 2003
respectively. But latter appreciate slightly to 12.5% in 2004 which is attributed to campaign of
2005 banking consolidation that led to pool of money into capital market. Performance of Nigerian
quoted firms were drastically poor with 8.59% and 8.74% average value in 2005 and 2006
respectively, while improvement were recorded in the remaining years of the study with varying
average value of 10.93%, 13.73%, 11.67%, 12.78%, 13.15% and 9.37% but apparently at very low
performance rate.
A mere look at the chart below revealed high leverage ratio of the sample firms, average total debt
ratio of 62.87% in 2001 revealed that Nigerian quoted firms were highly geared exposing fixed
interest investors to high risk. Consequently, the ratio is an indication that any depletion of total
Table 4.1.2: Summary of the Average Values of Research Variables
72
assets of the firms above 37.13% incorporate debt holders’ funds that is any risk investment
undertake by the firms is covered by 37.13% equity capital of the firms. The leverage ratio of the
firms over the years were at a very high rate with varying rate as specifically indicated by 2002
total debt ratio of 63.86%. Thus implies that risk investment undertaken in that year was only
covered with 36.14% owners’ equity. Total debt ratio as at 2003 was 62.84% and equity holders’
capital investment was 37.16% and this is a reverse of bondholders as the risk taker in the firm.
However, average total debt ratio of the sample firms remained high at slightly decreasing and
increasing rate over the subsequent years, accordingly recorded as such; 61.65%, 65.67%,
65.11%, 65.08%, 62.89%, 63.63%, 58.9%, 61.45% and 60.97% in 2004, 2005, 2006, 2007, 2008,
2009, 2010, 2011 and 2012 respectively. Apparently, the total debt ratio of the sample firms over
the duration of the study revealed high leverage ratio which in turn exposes firms to high risk,
financing constraint, high cost of financing and agency cost among other costs.
Long term debt ratio shows obligation of Nigerian quoted firms that are made to be repayable after
more than one year as indicated in table 4.1.2 above. In 2001 8.47% average value was recorded
and thus indicates moderate rate when compare with total assets of the firms but this increased to
10.46%, 10.65%, 11.13%, 14.42% in 2002, 2003, 2004 and 2005 respectively, which implies that
this measure was at an increasing rate (upwards slope) right from 2001-2005. Accordingly, the
remaining years from the period of study recorded downwards and upwards slope as recorded in
2006 where average ratio decreased to 14.08% but latter increased to 15.17% in 2007 with
subsequent decreased and increased such as 14.71%, 15.94%, 16.75%, 19.90% and 18.19% in
2008, 2009, 2010, 2011 and 2012 respectively. Short term obligations payable within one
accounting period showed that average short term debt ratio of the sample firms was 54.54% in
2001. Thus revealing high leverage ratio and exorbitant cost to the firms where total investment of
the firm is financed with 54.54% short term capital and the reminder financed with long term
capital comprising of owners equity and long term liabilities of the firm. Apparently, this is sign of
regular refinancing imposing high weighted average cost of capital to the firms, high risk
investment due to mismatch of funds resulting to relatively high agency cost to the firms. The
following three accounting year recorded downward slope with average value of 52.44%, 51.94%
and 50.53% in 2002, 2003 and 2004 respectively. Conversely, 2005 revealed upward slope with
average value of 51.27% but downward slope in 2006 with 51.03% and latter increased in 2007
with average value of 51.36%. The remaining period of the study indicated a downward slope with
73
average short term debt ratio of 48.36%, 47.7%, 42.1%, 41.62% and 42.50% in 2008, 2009, 2010,
2011 and 2012 respectively.
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
2000 2005 2010 2015
ROA
0.58
0.59
0.6
0.61
0.62
0.63
0.64
0.65
0.66
0.67
2000 2005 2010 2015
TDR
0
0.05
0.1
0.15
0.2
0.25
2000 2005 2010 2015
LTDR
0
0.1
0.2
0.3
0.4
0.5
0.6
2000 2005 2010 2015
STDR
Fig. 4.1.2 Graphical Presentation of the Summary of Average Values Research Variables
Source: Estimated from table 4.1.2 Using Microsft Excel Computer Statistics (Version 2010)
a b
c d
74
Variables Mean Median Maximum Minimum Std Dev. Skewness Kurtosis P-value
ROA 0.117 0.109 0.669 -0.583 0.127 -0.197 7.370 0.000
TDR 0.628 0.596 3.069 0.029 0.319 3.078 21.795 0.000
LTDR 0.141 0.095 1.008 0.000 0.140 1.98 8.605 0.000
STDR 0.487 0.431 2.573 0.000 0.291 2.635 16.709 0.000
SIZE 21.151 21.509 26.963 13.267 2.726 -0.799 3.339 0.000
AGE 3.735 3.807 4.369 1.946 0.367 -1.435 6.254 0.000
Source: Descriptive Statistics Results using E-View 7.0
The mean of ROA for the sample firms is 11.7%, this indicates that for every N100 worth of total
assets of the firms, mere N11.7 was earned as profit before interest and tax. Thus implies that
Nigerian Quoted firms using this accounting measure of firm performance have a very low
performance rate. The lower returns on ROA may have also been affected by firm’s leverage ratio.
For example, the TDR recorded a mean of 62.80%, which implies that little depletion in assets of
Nigeria quoted firms will affect bondholders’ funds since owners stake in the firm cover only
37.20% of the firm’s assets and thus contributing to high agency cost and reorganization cost
reflecting low returns. LTDR having lower mean value of 14.10% compare to STDR value of
48.70% confirmed high cost of debt financing incurred by the sample firms due to refinancing
cost. Firm size and age was 2115.1% and 373.5% respectively. The consequences and implication
of the result obtained so far is well revealed by the median, maximum, minimum, standard
deviation, among other measures in the results. This result is acceptable as was confirmed with P-
value less than 0.05 in all the indicators.
Table 4.1.3: Descriptive Statistics
75
4.2 Data Analysis
4.2.1Result of Correlation
Tables 4.2.1 below presents the Pearson correlation matrix among the variables investigated in this study.
ROA TDR LTDR STDR SIZE AGE
ROA Pearson correlation
Sig. (2-tailed)
1 -.186**
.000
-.055
.177
-.170**
.000
.176**
.000
.018
.653
TDR Pearson correlation
Sig. (2-tailed)
-.186**
.000
1 .396**
.000
.899**
.000
.048
.241
.044
.280
LTDR Pearson correlation
Sig. (2-tailed)
-.055 .177
.396**
.000
1 -.018 .661
-.013 .746
-.051 .210
STDR Pearson correlation
Sig. (2-tailed)
-.170**
.000
.899**
.000
-.018 .661
1 .071
.082
.066
.108
SIZE Pearson correlation
Sig. (2-tailed)
.176**
.000
.048
.241
-.013
.746
.071
.082
1 .078 .057
AGE Pearson correlation
Sig. (2-tailed)
.018
.653
.044
.280
-.051 .210
.066
.108
.078
.057
1
**correlation is significant at the 0.01 level (2-tailed).
Source: Pearson Correlation Matrix Results using SPSS 21.0
The result of correlation matrix for the variables is reported in order to examine the correlation
between the dependent and explanatory variables. The results show that there is a negative
relationship between ROA and financial structure measures (TDR, LTDR and STDR), while
positive relationship was revealed between ROA and firm characteristics measures (firm size and
age). This implies that financial structure does not improve firm performance which may be
attributed to high cost of debt capital making sample firms vulnerable to agency problem. The
results obtained so far may be also be attributed to mismatch of funds by firms’ agents (managers),
which is considered to be detrimental to shareholders’ earning. Meanwhile, the above correlation
results agree with studies including Khan (2012), San and Heng (2011), Onaolapo and Kajola
(2010), Ebaid (2010) among others. It is however inconsistent with the findings of Mojtaba and
Shahoo (2011), Zuraidah et al., 2012 among others.
The result in table 4.2.1 above shows that none of our correlations (both negative and positive
coefficients) are high enough to warrant any problem of multicollinearity. Hence, the result of our
regression estimates is less likely to be biased by the problem of multicollinearity. This appears to
indicate that it may be statistically tolerable to use pooled ordinary least square regression
technique to estimate the specified model.
Table 4.2 Pearson Correlation Matrix
76
4.3 Hypothesis Test
The three hypotheses formulated in chapter one of the study were tested along the lines of the
model specified for empirical verification of the hypotheses in chapter three (3.5). Employing
panel data of the quoted Nigerian firms, pool Ordinary Least Square (OLS), Fixed Effects (FE),
and Random Effects (RE) regression estimation were adopted. Furthermore, as revealed earlier in
the previous chapter, dependent variable of this study is ROA. This was tested on the financial
structure measures and reported accordingly. The hypotheses were postulated in null and
alternative form. To this end, all the operation was performed with the aid of E-View version 7.0
and the results were analysed as follows:
4.3.1 Hypothesis One
The hypothesis is restated in null and alternative forms as follows;
H0: Total debt ratio does not have positive and significant impact on firm performance.
H1: Total debt ratio has positive and significant impact on firm performance.
Table 4.3.1: Regression Results of Hypothesis One
Dependent Variable: ROA
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.031984 0.008666 -3.690838 0.0002
TDR -0.077609 0.002194 -35.37209 0.0000
SIZE 0.008563 0.000257 33.29180 0.0000
AGE 0.004361 0.001902 2.293021 0.0219 R-squared 0.068956 Mean dependent var 0.116661
Adjusted R-squared 0.068865 S.D. dependent var 0.126603
S.E. of regression 0.122166 Akaike info criterion -1.366741
Sum squared resid 457.3923 Schwarz criterion -1.365654
Log likelihood 20949.99 Hannan-Quinn criter. -1.366393
F-statistic 756.6067 Durbin-Watson stat 0.938699
Prob(F-statistic) 0.000000
Source: Regression Analysis Results using E-View 7.0
Note: (1) Regression significant at 5% level of significance.
(2) The Larger the value of t (t > P-value) the stronger the evidence that the coefficient is significant.
(3) The closer the value of R is to one (1), the stronger the agreement.
77
ROA = - 0.032 – 0.0776TDR + 0.0086SIZE + 0.0044AGE
The result above revealed that the intercept (constant) of the equation is -0.032. This value is
negative and statistically significant since P-value is less than 0.05 level of significant, indicating
that ROA will decrease by 0.032 unit when there is no change in explanatory variables. However,
the negative coefficient of TDR (-0.0776) indicates that a unit increase in TDR of the Nigerian
quoted firms resulted to 0.0776 unit decrease in firm performance. The P-value of 0.000 less than
significant level of 0.05 confirms significance result. As also revealed by the coefficient of
determination (R2), which is the proportion of variation in the dependent variable explained in the
regression model. The R2 of 0.0689 indicates that 6.89% of the variation in the dependent variable
(ROA) was explained by the independent variable, while the remaining 93.11% was due to other
factors not presumed in the variation model. R2 was again adjusted to 6.88% to eliminate any form
of error that could result in biasness.
The control variables introduced indicates that while firm size had positive and significant impact
on firm performance (coefficient of SIZE = 0.0086, p-value = 0.000), firm age had positive and
significant impact on performance of Nigerian quoted firms within the period under review
(coefficient of AGE = 0.0044, p-value = 0.0219).
Decision Rule
The results showed that total debt ratio has negative and significant impact on firm performance.
Hence, we reject the alternative hypothesis and accept the null hypothesis. The study thus conclude
that total debt ratio has negative and significant impact on firm performance. This is very
consistent with existing propositions that Nigerian debt market is underdeveloped; most firms’
external debt finance is majorly short term finance, imposing extra burdens at very exorbitant costs
on the firms. The adjustment of leverage ratio to attain optimal financial structure may lead to
high agency cost if not rationally employed. As documented, the optimal financial structure
decision has to do with balancing the trade-off between the benefit of debt and agency costs arising
from mitigating the agency cost of managerial discretion against the agency cost of debt arising
from “asset substitution effect” (Octavia and Brown, 2008 and Shahjahanpour et al. 2010). Also
high leverage ratio increases the bankruptcy cost and agency cost of the firm as well rises.
78
4.3.2 Hypothesis Two
The hypothesis is restated in null and alternative forms as follows;
H0: Long term debt ratio does not positively and significantly impact on firm performance.
H1: Long term debt ratio does positively and significantly impact on firm performance.
Table 4.3.2: Regression Results of Hypothesis Two Dependent Variable: ROA
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.045827 0.008903 -5.147416 0.0000
LTDR -0.047893 0.005095 -9.400469 0.0000
SIZE 0.008082 0.000262 30.84888 0.0000
AGE -0.000395 0.001947 -0.202876 0.8392 R-squared 0.033247 Mean dependent var 0.116878
Adjusted R-squared 0.033152 S.D. dependent var 0.126596
S.E. of regression 0.124480 Akaike info criterion -1.329216
Sum squared resid 474.0918 Schwarz criterion -1.328127
Log likelihood 20341.00 Hannan-Quinn criter. -1.328867
F-statistic 350.7390 Durbin-Watson stat 0.921497
Prob(F-statistic) 0.000000
Source: Regression Analysis Results using E-View
Note: (1) Regression significant at 5% level of significance.
(2) The Larger the value of t (t > P-value) the stronger the evidence that the coefficient is significant.
(3) The closer the value of R is to one (1), the stronger the agreement.
ROA = -0.0458 – 0.0479LTDR + 0.0081SIZE – 0.0004AGE
The above table showed that the intercepts is -0.0458. The value is negative and statistically
significant as justified by the p-value which is less than 0.05. The implication is when no change
occurs in long term debt ratio, ROA decrease by 4.58%. The coefficient of LTDR revealed
unexpected on the direction but expected on the magnitude. From the result, 1 unit increase in
LTDR of Nigeria quoted firms resulted in 0.0479 unit decrease in ROA. The p-value of 0.000 less
than 0.05 indicates significant result. The coefficient of determination which measures the
goodness of fit of the model as revealed by R-square (R2) indicates that 3.32% of the variations
observed in the dependent variable were explained by variations in independent variable. The test
of goodness of fit as indicated by R2 was adjusted by the Adjusted R-Square to 3.31%. This is
79
relatively tiny, indicating that there are other variables apart from the independent variable that
have impact on firm performance. The control variables introduced indicates that firm size had
positive and significant impact on firm performance (coefficient of SIZE = 0.0081, p-value =
0.000), while firm age had negative but insignificant impact on performance of Nigerian quoted
firms within the period under review (coefficient of AGE = -0.0004, p-value = 0.839).
Decision Rule
The regression results showed that long term debt ratio had negative and significant impact on firm
performance. Thus, the null hypothesis is accepted while the alternate hypothesis is rejected.
Accordingly, the study concludes that long term debt ratio have negative and significant impact on
firm performance. Manos and Ah-Hen (2002) pointed that agency consideration assume debt is
valuable in reducing the agency costs of equity but at the same time debt is costly as it increase the
agency cost of debt. Thus, high leverage increases agency problem, firm needs to balance the cost
and benefit of debt because negative information in debt about profitability overwhelms any tax
(or other) benefits of debt (Fama and French, 1998).
4.3.3 Hypothesis Three
The hypothesis is restated in null and alternative forms as follows;
H0: Short term debt ratio does not have positive and significant impact on firm performance.
H1: Short term debt ratio has positive and significant impact on firm performance.
80
Table 4.3.3: Regression Results of Hypothesis Three
Dependent Variable: ROA
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.049060 0.008653 -5.669903 0.0000
STDR -0.080427 0.002418 -33.25529 0.0000
SIZE 0.008725 0.000258 33.80175 0.0000
AGE 0.005466 0.001908 2.864582 0.0042 R-squared 0.064697 Mean dependent var 0.116661
Adjusted R-squared 0.064605 S.D. dependent var 0.126603
S.E. of regression 0.122445 Akaike info criterion -1.362177
Sum squared resid 459.4849 Schwarz criterion -1.361089
Log likelihood 20880.04 Hannan-Quinn criter. -1.361828
F-statistic 706.6369 Durbin-Watson stat 0.940749
Prob(F-statistic) 0.000000
Source: Regression Analysis Results using E-View
Note: (1) Regression significant at 5% level of significance.
(2) The Larger the value of t (t > P-value) the stronger the evidence that the coefficient is significant.
(3) The closer the value of R is to one (1), the stronger the agreement.
ROA = -0.0491 – 0.0804STDR + 0.0087SIZE + 0.0055AGE
Again, the trend value of the above hypothesis testing is negative (-0.0491) but statistically
significant at 0.05. The trend value of -0.0491 is the regression line intercept showing that ROA of
Nigerian quoted firms decreased by 4.91% when there is no change in the independent variable.
The negative coefficient of STDR (-0.0804) is inconsistent as expected. It means that 1 unit
increase in STDR of Nigerian quoted firms induce a decrease in ROA by 0.0804 unit, and the p-
value is significant wherein 0.000 is less than 0.05. The coefficient of determination which
measures the goodness of fit of the model as revealed by R-square (R2) indicates that 6.47% of the
variations observed in the dependent variable were explained by variations in the independent
variable. The test of goodness of fit as indicated by R2 was adjusted by the Adjusted R-Square to
6.46%. As observed from the table, the control variables introduced indicates that firm size
(coefficient = 0.0804 and p-value = 0.000) had positive and significant impact on firm
performance within the period under review, while firm age (coefficient = 0.0055 and p-value =
0.0042) had negative and significant impact on firm performance within the period of study.
81
Decision Rule
The results showed that short term debt ratio had negative and significant impact on firm
performance. Therefore, the null hypothesis is again accepted while the alternate hypothesis is
rejected. The study thus concludes that short term debt ratio have negative and significant impact
on firm performance attributed to high short term debt and mismatch of fund. Apparently, when
leverage becomes relatively high, further increases generate significant agency costs of outside
debt; including higher expected costs of bankruptcy or financial distress, arising from conflicts
between bondholders and shareholders (Jensen and Meckling, 1976). Also at high leverage the
value of shareholders may not be enhanced when restrictive covenants included in debt financing
agreements limit the ability of firms to fully harness the potentials of the firm’s resources
(Onwumere et al., 2011). Thus firm can only maximize their values by maximizing the use of debt.
4.3.4 Discussion of Results
This section is devoted to ascertain whether the objectives set out in the research are actually
achieved. The results from the three hypotheses are compared with the objectives of this study.
Again, the panel data study results of the three regression estimations (OLS, Fixed Effects and
Random Effects) are compared among others.
Apparently, there exists strong evidence from the results which point to the achievement of the
objectives originally established for the study. As revealed from table 4.3.4 below, the three
hypotheses had negative and significant impact in the three adopted regression estimations.
Ordinary Least Square (OLS) Fixed Effects (FE) Random Effects (RE)
Variables Coeff t-Stat P-Value Coeff t-Stat P-
Value
Coeff t-Stat P-
Value
TDR (hyp. 1) -0.078 -35.372 0.000 -0.078 -35.343 0.000 -0.078 -35.343 0.000
LTDR (hyp. 2) -0.048 -9.400 0.000 -0.048 -9.393 0.000 -0.048 -9.393 0.000
STDR (hyp. 3) -0.080 -33.255 0.000 -0.107 -0.080 0.000 -0.080 -33.228 0.000 Source: Regression Analysis Results using E-View
Note: (1) Regression significant at 5% level of significance.
(2) The Larger the value of t (t > P-value) the stronger the evidence that the coefficient is significant.
To ascertain the impact of total debt ratio on performance of quoted firms in Nigeria. The results
proceeding from the descriptive statistics and test of hypothesis one established that this objective
was achieved. The results from the three regression estimation showed that total debt ratio had
Table 4.3.4 ROA vs Financial Structure Measures
82
negative and significant impact on firm performance. The negative effect is associated with high
leverage ratio of Nigerian quoted firms as confirmed in descriptive analysis, and also frequent
changes in debt capital of Nigerian quoted firms are highly associated with systematic depreciation
of firms’ assets attributed to high cost of debt financing. The findings as revealed in the regression
results is consistent with the findings of Khan (2012), San and Heng (2011), Onaolapo and Kajola
(2010), Ebaid (2009), Zeitun and Tian (2007), Abor (2008), amongst others, but in contradiction
with that of Mojtaba and Shahoo (2011), Zuraidah et al. (2012), amongst others.
To determine how long term debt ratio impacts on performance of quoted firms in Nigeria. Using
panel data, the study showed that long term debt had negative and significant impact on firm
performance. This is attributed to inconsequential financing pattern of most of the sampled firms
due to the under developed security market which overwhelmed the conventional element of
financial leverage. To examine the impact of short term debt ratio on performance of quoted firms
in Nigeria. The three regression estimation confirmed that short term debt ratio had negative and
significant impact on firm performance. The result is in line with the findings of Zeitun and Tian
(2007), Zuraidah et al.(2012), Khan (2012), Ebaid (2012) among others.
However, theoretical body of knowledge argues that debt provide tax shield, thus debt is cheaper
source of financing than equity to certain extent. After certain level, the cost of debt outweighs the
tax benefits. From the analysis, we observed that the sample firms are highly levered. This
confirmed the contention that at low levels of debt, substitution effects are likely to become
vanishingly small. Indeed, when debt claims remain riskless, both the asset substitution and under
investment problems disappears but at high level of debt, reverse is the case (Cuny and Pirinsky,
2004).
4.4 Robustness Test
To test for robust of our regression results, we conducted additional test using alternative measure
of firm performance such as return on equity (ROE). Regression results from the three adopted
regression estimation were recorded in table 4.4 below.
83
Ordinary Least Square (OLS) Fixed Effects (EF) Random Effects (RE)
Variabl
es
Coeff t-Statistics P-Value Coeff t-Statistics P-
Value
Coeff t-Statistics P-
Value
TDR 0.435 7.968 0.000 0.435 7.961 0.000 0.435 7.961 0.000
LTDR 3.909 32.1698 0.000 3.909 32.144 0.000 3.909 32.144 0.000
STDR -0.377 -6.333 0.000 -0.377 -6.328 0.000 -0.377 -6.328 0.000 Source: Regression Analysis Results using E-View
Note: (1) Regression significant at 5% level of significance.
(2) The Larger the value of t (t > P-value) the stronger the evidence that the coefficient is significant.
Testing from the standpoint of Return on Equity (ROE), the study revealed that total debt ratio had
positive and significant impact on return on equity as alternative measure of firm performance.
This outcome also compare favorably with the findings of Ebaid (2012). It is also consistent with
cost-benefit argument of trade-off theory and tax shield benefit found by Miller (1977) to
contribute to incremental value of shareholders’ earnings when debt capital is employed.
Again, the study showed that Long Term Debt Ratio had positive and significant impact on return
on equity of Nigerian quoted firms under the period of study. The outcome here again is consistent
with our prediction and priori findings (Zuraidah et al., 2012).
Lastly, comparing STDR with ROE, the regression results showed that the impact of short term
debt ratio on return on equity as alternative measure of firm performance was negative and
significant. The negative and significant relationship documented between short term debt and
return on equity is consistent with the findings of Amjed (2008); Zuraidah et al., (2012). This
confirmed the argument that significant and justifiable results are better obtain with narrow
definition of leverage ratio in compliment of the cumulative. It is remarkable that this is a basis to
ascertain actual impact of leverage on returns that is “impact base” on the periodic employment of
debt that hedge against fund mismatch. The observation is consistent with Titman and Wessels
(1988) assertion that significant results are good reason for employment of different measures of
leverage ratio because some of the theories of capital structure have different implications for not
combining them as aggregate “debt ratio”. The negative effect is an implication of under
developed debt market where major debt financing of most Nigerian quoted firms are short term in
nature placing high burden and cost on the firm, thereby decreasing returns on their equity capital.
Table 4.4 ROE vs Financial Structure Measures
84
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87
CHAPTER FIVE
SUMMARY OF FINDINGS, CONCLUSIONS, AND RECOMMENDATIONS
5.1 Summary of Findings
Based on the regression results of the hypotheses tested, the following are the summary of our
findings:
1. Total debt ratio have negative and significant impact on the performance of Nigerian
quoted firms.
2. Long term debt ratio have negative and significant impact on the performance of Nigerian
quoted firms.
3. Short term debt ratio have negative and significant impact on the performance of Nigerian
quoted firms.
5.2 Conclusion
This study as one of the empirical investigations of the impact of financial structure on the
performance of Nigerian quoted firms. The ultimate goal of the firm is to ensure optimal
employment of capital, which in turn triggers long run value maximization of owners’ equity.
Agent(s) of the firm is left with financial structure decision and other corporate financing decisions
that most be align to attain “value maximization”. These decisions are very crucial one in
transitory economies peculiar to Nigeria couple with underdeveloped debt market and numerous
intrinsic market risks. The impact of financial structure on the firm performance has been
significantly verified in the study.
To this end, the impact of financial structure (total debt ratio, long term debt ratio and short term
debt ratio) on the performance of Nigerian quoted firms has established negative and significant
results, thus being consistent with agency cos theory. This confirmed that Nigerian quoted firms
borrows to point where the marginal value of tax shields benefits on additional debt could not
offset the incremental cost of debt capital thereby contributing negatively to firms’ earning. And
also the findings of the study are in line with other previous empirical studies as already
highlighted in the main discussion of the findings. The above implication revealed that value
88
maximization firm in Nigeria needs to maintain financial structure that tax benefits of debt
overwhelmed bankruptcy cost and agency cost associated with debt.
Meanwhile, in determining the extent of the influence of financial structure on the performance of
Nigerian quoted firms using alternative measure of firm performance (ROE), some of the
indicators (financial structure variables) showed diverse outcomes due to different implications of
maturity rate of debt finance and mismatch of fund. Total debt ratio and long term debt ratio were
found to have positive and significant impact on return on equity of Nigerian quoted firms, while
short term debt ratio had negative and significant impact on return on equity of Nigerian quoted
firms. The sign on short term debt ratio is an indication of mismatch of funds as well as high cost
burden of short term finance on quoted firms attributed to underdeveloped security market living
no option but bank loans at high interest rate.
Above all, the regression results provide strong support for the proposition that financial structure
is relevant in explaining performance of Nigerian quoted firms. In view of this caveat and
indistinct nature of financing decision spawning the gap among researchers on the relevance of
financial structure on firm performance, the results of this study should not be view as conclusive
empirical evidence, but rather as an additional motivation for further research in this area.
5.3 Recommendations
The findings of this research have provided enough evidence to advocate that financial structure of
Nigerian quoted firms have relevance role to play on their performance. Irrespective of detrimental
influence of the security market subjecting financing decision of most firms, the influence was
convincing one. Much therefore needs to be done to put the security market in the right
standard/track for efficient and effective mobilization and allocation of funds, and firm agents on
the other side have a major role to play. To achieve this requires the unceasing efforts of all
stakeholders.
5.3.1 Recommendations for Selected Stakeholders
i. One significant outcome of this study is that unexpected disparity in some of the findings is
attributed to high cost of funding and mismatch of funds. Therefore, there is need for change in
the attitude of banks towards manufacturing firms so that they can provide easier access to long
89
term bank financing. This will encourage growth of manufacturing and the subsequent
development of the real sector of the economy as a whole.
ii. The study found that Nigerian security markets are not efficient in location of funds. Therefore,
that government should pursue genuinely a policy measures targeted at developing the security
market to ensure high volume of corporate debt issue, liquidity of the market and market
efficiency in order to guarantee easy mobilization and allocation of funds.
iii. The study also found that agents of the firms were not balancing the tax shield benefit of debt
against agency cost of debt resulting to depletion in firm earnings. Therefore, there is need to
ensure policies that will enjoin Nigerian quoted firms on corporate governance to achieve
efficient financial structure. Inefficient corporate governance structures exacerbate the prevailing
agency problems, with managers taking advantage of the situation.
iv. Measures directed towards elimination of restrictions of the public sector on issuance of debt
finance which would result in an increase in economic activity and improving efficiency of
Nigerian quoted firms should be strictly stipulated. These flexible by-laws should be in form of
real sector resuscitation that will tend to boost the economy afterward. An example of such
legislation is government intervention by means of bail-outs of the real sectors. Ensuring
effectiveness and efficient implementation of the policy formulation that will improve the
performance of Nigerian quoted firms.
v. Owners of the firm and/or agent(s) of the firm need to ensure optimal employment of debt and
equity finance. This suggests that a firm should borrow to the point where the marginal value of
tax shields on additional debt immediately offset the increase in the present value of bankruptcy
cost.
vi. There is need to ensure value maximization of shareholder funds by the agent(s) of the firm. This
can only be achieve by aligning investment decision of the firm with the appropriate financing
decision given consideration to maturity structure of external debt capital. Taking cognizance of
this by the firm policy makers will result to minimal mismatch of funds, in turn low risk, low
cost of funds and high returns to the firm.
vii. Bank loans as observed from the financial statement of the sample firms which is responsible for
corporate performance is at present not performing to expectation due to dearth of long term
finance in the security market. Thus, the excessive liquidity in the Nigerian money market
prompt the need for capital market instruments that extend for long maturity period to bridge the
gap between the excess liquidity and the scarce investment funds.
90
5.3.2 Recommended areas for further research
The findings of this study have exposed other areas of research that will help the understanding of
the effect of the mix of debt and equity finance phrased “financial structure” on the performance of
Nigerian quoted firms.
i. The study found that marginal value of leverage on additional debt capital could not offset
the long run incremental cost of debt capital when firms are highly levered. This prompt
the need to design model and determine optimal financial structure of Nigerian quoted
firms.
ii. It was inferred from the study that there is evidence of mismatch of funds among the
Nigerian quoted firms resulting to high risk and cost of funds. It will make a good research
sense if future research should investigate debt maturity and performance of Nigerian
quoted firms.
iii. Although, the study sheds light on the role of security market in determining the risk and
cost of finance and in turn returns on the invested capital. And also, it was noted that apart
from internal efficiency that determine the variation of financial structure and performance,
there are external determinants that could explain such variation. Further research could
incorporate important macro-economic factors, for instance non debt tax shield could be
adjusted for inflation to find out the actual economic depreciation.
iv. Notwithstanding concrete evidence established by the study, this study can be improved
upon if the cross-section dimension (number of firm) and time dimension (timeframe) are
increased to have greater number of observation. Also adoption of market performance
measures could strengthen the deduction on the impact of financial structure on firm
performance.
v. Finally, small and medium scale firms that is vulnerable to financial constraint in
developing nation. The focus of the impact of financial structure on the performance of this
class of firms could strengthen the relevance and/or irrelevance arguments.
91
5.4 Contributions of the Findings of the Study
The results of this research work have provided a basis for a better understanding and appreciation
of the impact of financial structure on performance of Nigerian quoted firms. Among other things,
the study has revealed the effect of firm characteristics on the firm performance measures. As a
result, the above research outcomes are expected to contribute to both overall development and
knowledge in significant manner.
A. Contribution to development
Information to stakeholders in the security market.
This research work is of great relevance to all stakeholders in the security market. Apparently, the
study will aid investors in the debt market to deduce the intrinsic value of their financial assets as
appropriate risk are readily available based on the established leverage ratio of the sample firms.
Precisely, it has suggested to these stakeholders, the need to ascertain owners’ stake on the firm
given the ratio of external and internal capital of the firm which is the major pricing factor as well
as risk determinant of the investment. On the other hand, the study is relevant to the owners of the
firm or agent of the firm on the way to reduce the price of their external fixed capital thereby
ensuring minimal inherent risk of the assets to improve their earnings ratio.
Policy guide to regulators and agencies
The study has provided required empirical and theoretical base concerning the impact of financial
structure on the performance of quoted Nigerian firms and working of Nigerian security market.
Such insight will offer useful guide to these regulators in designing appropriate workable device
for efficient regulation of the market. Besides, it will provide useful platform that could assist these
policy makers enunciate favourable means of mitigating aberration in the market and in turn
ensure efficient market.
Inducement and mobilization of investment funds
Capital as the bedrock for economic growth and development. The evidence established in this
research has revealed the revelation of security market stipulation on the earnings of the firm.
Therefore, it provides useful information for firms and financial intermediaries to stimulate growth
by participating and ensuring smooth running of the market.
92
Financial analyst and other market agent
This research is relevant to financial analyst and other market agent to infer the nature of equity
investment and position of Nigerian quoted firms at minimal variation of projection and actual
outcome as well as the risk of interest bearing assets. And also enable market agents to restrained
unwholesome practice in financing pattern of most firms when the real class of firm’s assets is
obtainable.
B contributions to knowledge
Above all, this research has assisted in broadening the frontier of knowledge in various ways. First,
the study has exposit a unique modeling framework for financial structure and performance of
Nigerian quoted firms which captured major definition of financial structure giving consideration
to maturity effect of debt, given incremental cost relatively to intrinsic risk.
Secondly, this research has also contributed to the enrichment of literature on funding decision by
developing countries in which external fixed capital are highly short term in maturity thereby
possessing various attribute and relative influence on the firm. Thirdly, it has empirically
suggested ways to ensure efficient market and minimum market risk and variation in projection
and actual returns. Lastly, the study has provided vital information to guide future researchers.
93
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104
APPENDIX 1
Descriptive statistics for the variables used in the study
ROA TDR LTDR STDR SIZE AGE
Mean 0.116879 0.628157 0.140942 0.487355 21.15094 3.735284
Median 0.109000 0.596000 0.095000 0.431000 21.50900 3.806662
Maximum 0.669000 3.069000 1.008000 2.573000 26.96306 4.369448
Minimum -0.583000 0.029000 0.000000 0.000000 13.26683 1.945910
Std. Dev. 0.126700 0.319082 0.139981 0.290918 2.726275 0.367310
Skewness -0.196644 3.078447 1.981350 2.635207 -0.798541 -1.434604
Kurtosis 7.369739 21.79541 8.605197 16.70912 3.338832 6.254171
Jarque-Bera 481.2323 9779.374 1178.031 5392.931 66.63699 470.5496
Probability 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000
Sum 70.12710 376.8940 84.56510 292.4130 12690.56 2241.170
Sum Sq. Dev. 9.615611 60.98605 11.73724 50.69517 4452.111 80.81504
Observations 601 601 601 601 601 601
Correlations
ROA TDR LTDR STDR SIZE AGE
ROA Pearson Correlation 1 -.186** -.055 -.170
** .176
** .018
Sig. (2-tailed) .000 .177 .000 .000 .653
N 601 601 601 601 601 601
TDR Pearson Correlation -.186** 1 .396
** .899
** .048 .044
Sig. (2-tailed) .000 .000 .000 .241 .280
N 601 601 601 601 601 601
LTDR Pearson Correlation -.055 .396** 1 -.018 -.013 -.051
Sig. (2-tailed) .177 .000 .661 .746 .210
N 601 601 601 601 601 601
STDR Pearson Correlation -.170** .899
** -.018 1 .071 .066
Sig. (2-tailed) .000 .000 .661 .082 .108
N 601 601 601 601 601 601
SIZE Pearson Correlation .176** .048 -.013 .071 1 .078
Sig. (2-tailed) .000 .241 .746 .082 .057
N 601 601 601 601 601 601
AGE Pearson Correlation .018 .044 -.051 .066 .078 1
Sig. (2-tailed) .653 .280 .210 .108 .057
N 601 601 601 601 601 601
**. Correlation is significant at the 0.01 level (2-tailed).
105
APPENDIX 2
Regression results
Hypothesis 1: ROA vs TDR
Dependent Variable: ROA
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.031984 0.008673 -3.687826 0.0002
TDR -0.077609 0.002196 -35.34322 0.0000
SIZE 0.008563 0.000257 33.26464 0.0000
AGE 0.004361 0.001903 2.291150 0.0220
Fixed Effects (Cross) Effects Specification Cross-section fixed (dummy variables) R-squared 0.068956 Mean dependent var 0.116661
Adjusted R-squared 0.067343 S.D. dependent var 0.126603
S.E. of regression 0.122266 Akaike info criterion -1.363479
Sum squared resid 457.3923 Schwarz criterion -1.348802
Log likelihood 20949.99 Hannan-Quinn criter. -1.358774
F-statistic 42.75692 Durbin-Watson stat 0.938699
Prob(F-statistic) 0.000000
Dependent Variable: ROA
Method: Pooled EGLS (Cross-section random effects)
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651
Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-Statistic Prob. C -0.031984 0.008673 -3.687826 0.0002
TDR -0.077609 0.002196 -35.34322 0.0000
SIZE 0.008563 0.000257 33.26464 0.0000
AGE 0.004361 0.001903 2.291150 0.0220
Random Effects (Cross) Effects Specification
S.D. Rho Cross-section random 0.000000 0.0000
Idiosyncratic random 0.122266 1.0000
106
Weighted Statistics R-squared 0.068956 Mean dependent var 0.116661
Adjusted R-squared 0.068865 S.D. dependent var 0.126603
S.E. of regression 0.122166 Sum squared resid 457.3923
F-statistic 756.6067 Durbin-Watson stat 0.938699
Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.068956 Mean dependent var 0.116661
Sum squared resid 457.3923 Durbin-Watson stat 0.938699
Hypothesis 2: ROA vs LTDR
Dependent Variable: ROA
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.045827 0.008910 -5.143209 0.0000
LTDR -0.047893 0.005099 -9.392784 0.0000
SIZE 0.008082 0.000262 30.82366 0.0000
AGE -0.000395 0.001948 -0.202710 0.8394
Fixed Effects (Cross) Effects Specification Cross-section fixed (dummy variables) R-squared 0.033247 Mean dependent var 0.116878
Adjusted R-squared 0.031570 S.D. dependent var 0.126596
S.E. of regression 0.124582 Akaike info criterion -1.325948
Sum squared resid 474.0918 Schwarz criterion -1.311250
Log likelihood 20341.00 Hannan-Quinn criter. -1.321236
F-statistic 19.82070 Durbin-Watson stat 0.921497
Prob(F-statistic) 0.000000
Dependent Variable: ROA
Method: Pooled EGLS (Cross-section random effects)
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651
Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-Statistic Prob.
107
C -0.045827 0.008910 -5.143209 0.0000
LTDR -0.047893 0.005099 -9.392784 0.0000
SIZE 0.008082 0.000262 30.82366 0.0000
AGE -0.000395 0.001948 -0.202710 0.8394
Random Effects (Cross) Effects Specification
S.D. Rho Cross-section random 0.000000 0.0000
Idiosyncratic random 0.124582 1.0000 Weighted Statistics R-squared 0.033247 Mean dependent var 0.116878
Adjusted R-squared 0.033152 S.D. dependent var 0.126596
S.E. of regression 0.124480 Sum squared resid 474.0918
F-statistic 350.7390 Durbin-Watson stat 0.921497
Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.033247 Mean dependent var 0.116878
Sum squared resid 474.0918 Durbin-Watson stat 0.921497
Hypothesis 3: ROA vs STDR
Dependent Variable: ROA
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.049060 0.008660 -5.665276 0.0000
STDR -0.080427 0.002420 -33.22815 0.0000
SIZE 0.008725 0.000258 33.77416 0.0000
AGE 0.005466 0.001910 2.862244 0.0042
Fixed Effects (Cross) Effects Specification Cross-section fixed (dummy variables) R-squared 0.064697 Mean dependent var 0.116661
Adjusted R-squared 0.063077 S.D. dependent var 0.126603
S.E. of regression 0.122545 Akaike info criterion -1.358914
Sum squared resid 459.4849 Schwarz criterion -1.344238
Log likelihood 20880.04 Hannan-Quinn criter. -1.354210
F-statistic 39.93306 Durbin-Watson stat 0.940749
Prob(F-statistic) 0.000000
108
Dependent Variable: ROA
Method: Pooled EGLS (Cross-section random effects)
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651
Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-Statistic Prob. C -0.049060 0.008660 -5.665276 0.0000
STDR -0.080427 0.002420 -33.22815 0.0000
SIZE 0.008725 0.000258 33.77416 0.0000
AGE 0.005466 0.001910 2.862244 0.0042
Random Effects (Cross) Effects Specification
S.D. Rho Cross-section random 0.000000 0.0000
Idiosyncratic random 0.122545 1.0000 Weighted Statistics R-squared 0.064697 Mean dependent var 0.116661
Adjusted R-squared 0.064605 S.D. dependent var 0.126603
S.E. of regression 0.122445 Sum squared resid 459.4849
F-statistic 706.6369 Durbin-Watson stat 0.940749
Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.064697 Mean dependent var 0.116661
Sum squared resid 459.4849 Durbin-Watson stat 0.940749
Financial Structure vs ROE
Dependent Variable: ROE
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.212879 0.215871 -0.986139 0.3241
TDR 0.435471 0.054656 7.967514 0.0000
SIZE 0.041541 0.006408 6.483185 0.0000
AGE -0.133353 0.047377 -2.814726 0.0049 R-squared 0.003787 Mean dependent var 0.441041
Adjusted R-squared 0.003688 S.D. dependent var 3.018838
S.E. of regression 3.013266 Akaike info criterion 5.044059
Sum squared resid 272810.8 Schwarz criterion 5.045165
109
Log likelihood -75782.99 Hannan-Quinn criter. 5.044414
F-statistic 38.07609 Durbin-Watson stat 2.005692
Prob(F-statistic) 0.000000
Dependent Variable: ROE
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.212879 0.216047 -0.985335 0.3245
TDR 0.435471 0.054700 7.961015 0.0000
SIZE 0.041541 0.006413 6.477896 0.0000
AGE -0.133353 0.047416 -2.812429 0.0049
Fixed Effects (Cross) Effects Specification Cross-section fixed (dummy variables) R-squared 0.003787 Mean dependent var 0.441041
Adjusted R-squared 0.002060 S.D. dependent var 3.018838
S.E. of regression 3.015726 Akaike info criterion 5.047320
Sum squared resid 272810.8 Schwarz criterion 5.061978
Log likelihood -75782.99 Hannan-Quinn criter. 5.052023
F-statistic 2.193115 Durbin-Watson stat 2.005692
Prob(F-statistic) 0.000002
Dependent Variable: ROE
Method: Pooled EGLS (Cross-section random effects)
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651
Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-Statistic Prob. C -0.212879 0.216047 -0.985335 0.3245
TDR 0.435471 0.054700 7.961015 0.0000
SIZE 0.041541 0.006413 6.477896 0.0000
AGE -0.133353 0.047416 -2.812429 0.0049
Random Effects (Cross) Effects Specification
S.D. Rho Cross-section random 0.000000 0.0000
Idiosyncratic random 3.015726 1.0000 Weighted Statistics
110
R-squared 0.003787 Mean dependent var 0.441041
Adjusted R-squared 0.003688 S.D. dependent var 3.018838
S.E. of regression 3.013266 Sum squared resid 272810.8
F-statistic 38.07609 Durbin-Watson stat 2.005692
Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.003787 Mean dependent var 0.441041
Sum squared resid 272810.8 Durbin-Watson stat 2.005692
Dependent Variable: ROE
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.894926 0.212355 -4.214295 0.0000
LTDR 3.909283 0.121520 32.16983 0.0000
SIZE 0.045499 0.006249 7.281499 0.0000
AGE -0.047274 0.046435 -1.018050 0.3087 R-squared 0.034344 Mean dependent var 0.441817
Adjusted R-squared 0.034249 S.D. dependent var 3.021292
S.E. of regression 2.969103 Akaike info criterion 5.014527
Sum squared resid 269721.2 Schwarz criterion 5.015616
Log likelihood -76718.27 Hannan-Quinn criter. 5.014876
F-statistic 362.7172 Durbin-Watson stat 2.054255
Prob(F-statistic) 0.000000
Dependent Variable: ROE
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C -0.894926 0.212529 -4.210850 0.0000
LTDR 3.909283 0.121620 32.14354 0.0000
SIZE 0.045499 0.006254 7.275547 0.0000
AGE -0.047274 0.046473 -1.017218 0.3091
Fixed Effects (Cross) Effects Specification Cross-section fixed (dummy variables) R-squared 0.034344 Mean dependent var 0.441817
111
Adjusted R-squared 0.032668 S.D. dependent var 3.021292
S.E. of regression 2.971532 Akaike info criterion 5.017795
Sum squared resid 269721.2 Schwarz criterion 5.032493
Log likelihood -76718.27 Hannan-Quinn criter. 5.022507
F-statistic 20.49761 Durbin-Watson stat 2.054255
Prob(F-statistic) 0.000000
Dependent Variable: ROE
Method: Pooled EGLS (Cross-section random effects)
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651
Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-Statistic Prob. C -0.894926 0.212529 -4.210850 0.0000
LTDR 3.909283 0.121620 32.14354 0.0000
SIZE 0.045499 0.006254 7.275547 0.0000
AGE -0.047274 0.046473 -1.017218 0.3091
Random Effects (Cross) Effects Specification
S.D. Rho Cross-section random 0.000000 0.0000
Idiosyncratic random 2.971532 1.0000 Weighted Statistics R-squared 0.034344 Mean dependent var 0.441817
Adjusted R-squared 0.034249 S.D. dependent var 3.021292
S.E. of regression 2.969103 Sum squared resid 269721.2
F-statistic 362.7172 Durbin-Watson stat 2.054255
Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.034344 Mean dependent var 0.441817
Sum squared resid 269721.2 Durbin-Watson stat 2.054255
Dependent Variable: ROE
Method: Pooled Least Squares
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C 0.015307 0.213021 0.071854 0.9427
STDR -0.377063 0.059540 -6.332888 0.0000
112
SIZE 0.046488 0.006355 7.315785 0.0000
AGE -0.100061 0.046976 -2.130040 0.0332 R-squared 0.002987 Mean dependent var 0.441041
Adjusted R-squared 0.002890 S.D. dependent var 3.018837
S.E. of regression 3.014472 Akaike info criterion 5.044857
Sum squared resid 278490.5 Schwarz criterion 5.045944
Log likelihood -77310.95 Hannan-Quinn criter. 5.045205
F-statistic 30.60867 Durbin-Watson stat 1.956889
Prob(F-statistic) 0.000000
Dependent Variable: ROE
Method: Pooled Least Squares
Date: 12/03/14 Time: 16:02
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651 Variable Coefficient Std. Error t-Statistic Prob. C 0.015307 0.213195 0.071796 0.9428
STDR -0.377063 0.059589 -6.327719 0.0000
SIZE 0.046488 0.006360 7.309815 0.0000
AGE -0.100061 0.047015 -2.128301 0.0333
Fixed Effects (Cross) Effects Specification Cross-section fixed (dummy variables) R-squared 0.002987 Mean dependent var 0.441041
Adjusted R-squared 0.001260 S.D. dependent var 3.018837
S.E. of regression 3.016934 Akaike info criterion 5.048119
Sum squared resid 278490.5 Schwarz criterion 5.062796
Log likelihood -77310.95 Hannan-Quinn criter. 5.052824
F-statistic 1.729739 Durbin-Watson stat 1.956889
Prob(F-statistic) 0.000785
Dependent Variable: ROE
Method: Pooled EGLS (Cross-section random effects)
Sample: 2001 2012
Included observations: 601
Cross-sections included: 51
Total pool (balanced) observations: 30651
Swamy and Arora estimator of component variances Variable Coefficient Std. Error t-Statistic Prob. C 0.015307 0.213195 0.071796 0.9428
STDR -0.377063 0.059589 -6.327719 0.0000
SIZE 0.046488 0.006360 7.309815 0.0000
AGE -0.100061 0.047015 -2.128301 0.0333
113
Random Effects (Cross) Effects Specification
S.D. Rho Cross-section random 0.000000 0.0000
Idiosyncratic random 3.016934 1.0000 Weighted Statistics R-squared 0.002987 Mean dependent var 0.441041
Adjusted R-squared 0.002890 S.D. dependent var 3.018837
S.E. of regression 3.014472 Sum squared resid 278490.5
F-statistic 30.60867 Durbin-Watson stat 1.956889
Prob(F-statistic) 0.000000 Unweighted Statistics R-squared 0.002987 Mean dependent var 0.441041
Sum squared resid 278490.5 Durbin-Watson stat 1.956889
114
APPENDIX 3
List of Sample Firms
S/N
FIRMS SECTOR
1. OKOMU OIL PALM CO. PLC AGRICULTURE/AGRO-ALLIED
2. PRESCO PLC
AGRICULTURE/AGRO-ALLIED
3. RT BRISCO PLC.
AUTOMOBILE&TYRE
4. GUINNESS NIG. PLC.
BREWERIES
5. INTERNATIONAL BREWERIES PLC
BREWERIES
6. NIGERIAN BREWERIES. PLC
BREWERIES
7. CEMENT CO. OF NORTH NIG. PLC.
BUILDING MATERIALS
8. NIGERIAN ROPES PLC.
BUILDING MATERIALS
9. WA PORTLAND COMP. PLC.
BUILDING MATERIALS
10. BERGER PAINTS NIGERIA PLC.
CHEMICAL&PAINTS
11. CAP PLC.
CHEMICAL&PAINTS
12. DN MEYER PLC.
CHEMICAL&PAINTS
13. TRANS-NATIONWIDE EXP. PLC.
COMMERCIAL/SERVICES
14. NCR (NIGERIA) PLC.
COMPUTER AND OFFICE EQUIPMENT
15. TRIPPLE GEE&COMP. PLC.
COMPUTER AND OFFICE EQUIPMENT
16. A.G LEVENTIS NIG PLC.
CONGLOMERATES
17. CHELLARAMS PLC.
CONGLOMERATES
18. JOHN HOLT PLC.
CONGLOMERATES
19. PZ CUSSONS NIG. PLC.
CONGLOMERATES
20. SCOA NIG. PLC.
CONGLOMERATES
21. UAC PLC.
CONGLOMERATES
22. UNILEVER NIG. PLC.
CONGLOMERATES
23. JULIUS BERGER NIG. PLC.
CONSTRUCTION
115
24. JULI PLC
EMERGING MARKETS
25. SMART PRODUCTS NIG. PLC
EMERGING MARKETS
26. CUTIX PLC
ENGINEERING TECHNOLOGY
27. 7-UP BOTTLING CO. PLC.
FOOD/BEVERAGES&TOBACCO
28. CADBURY NIG. PLC.
FOOD/BEVERAGES&TOBACCO
29. FLOUR MILLS NIG. PLC.
FOOD/BEVERAGES&TOBACCO
30. NESTLE NIG PLC.
FOOD/BEVERAGES&TOBACCO
31. U T C NIG PLC.
FOOD/BEVERAGES&TOBACCO
32. EVANS MEDICAL PLC.
HEALTHCARE
33. GLAXO SMITHKLINE CONS.
HEALTHCARE
34. MAY&BAKER NIG. PLC.
HEALTHCARE
35. MORISON INDUST. PLC.
HEALTHCARE
36. NEIMETH INTER. PHARM
HEALTHCARE
37. PHARM-DEKO PLC.
HEALTHCARE
38. IKEJA HOTEL PLC.
HOTEL& TOURISM
39. ALUMINIUM EXTRUS. IND PLC.
INDUSTRIAL/DOMESTIC PRODUCT
40. FIRST ALUMIN. NIG. PLC.
INDUSTRIAL/DOMESTIC PRODUCT
41. VITAFOAM NIG. PLC.
INDUSTRIAL/DOMESTIC PRODUCT
42. VONO PRODUCTS PLC.
INDUSTRIAL/DOMESTIC PRODUCT
43. JAPAUL OIL&MARITIME SERV.
MARITIME
44. BETA GLASS CO. PLC.
PACKAGING
45. GREIF NIG. PLC.
PACKAGING
46. MOBIL OIL NIG. PLC.
PETROLEUM(MARKETING)
47. OANDO PLC.
PETROLEUM(MARKETING)
48. TOTAL NIG PLC
PETROLEUM(MARKETING)
49. ACADEMY PRESS
PRINTING&PUBLISHING
50. LONGMAN NIG. PLC.
PRINTING&PUBLISHING
51. UNIVERSITY PRESS PLC.
PRINTING&PUBLISHING
116
APPENDIX 4
Firm Performance and Financial Structure of the Sample Firms
ROA
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
AGRICULTURE/AGRO-ALLIED
OKOMU OIL PALM CO. PLC. 0.081 0.07 0.14 0.161 0.11 0.109 0.087 0.176 0.103 0.235
0.195 0.140
PRESCO PLC 0.133 0.109 0.162 0.232 0.167 0.093 0.086 0.228 0.059 0.203
0.123 0.150
AUTOMOBILE&TYRE
RT BRISCO PLC. 0.191 0.173 0.261 0.114 0.113 0.2 0.171 0.152 0.101 0.078
0.102 0.057
BREWERIES
GUINNESS NIG. PLC. 0.223 0.245 0.256 0.243 0.161 0.204 0.198 0.212 0.268 0.265
0.288 0.223
INTERNATIONAL BREWERIES -0.083 -0.114
-
0.254 -0.118 -0.375
-
0.232 0.0001 0.094
-
0.012 0.028
0.013 0.154
NIGERIAN BREWERIES. PLC 0.202 0.203 0.153 0.175 0.213 0.224 0.302 0.352 0.394 0.395
0.264 0.252
BUILDING MATERIALS
CEMENT CO. OF NORTH NIG.
PLC. -0.583 -0.076 0.08 0.157 0.06
-
0.001 0.061 0.252 0.477 0.193
0.262 0.116
NIGERIAN ROPES PLC. 0.174 0.102 0.108 0.084 0.0003 0.002 0.054 0.061 0.021 0.001
0.006 -0.272
WA PORTLAND COMP. PLC. 0.076 0.018
-
0.025 0.101 0.154 0.276 0.264 0.215 0.106 0.071
0.137 -0.048
CHEMICAL&PAINTS
BERGER PAINTS NIGERIA PLC. 0.193 0.144 0.132 0.142 0.04 0.095 0.116 0.12 0.138 0.197
0.085 0.067
CAP PLC. 0.522 0.195 0.187 0.202 0.222 0.295 0.286 0.449 0.286 0.481
0.416 0.529
DN MEYER PLC. 0.163 0.163 0.181 0.119 -0.093 0.143 0.099
-
0.052
-
0.104
-
0.006
0.006 0.010
COMMERCIAL/SERVICES
TRANS-NATIONWIDE EXP. PLC. 0.038 -0.014 -0.05 0.078 0.184 0.207 0.259 0.243 0.147 0.119
0.101 0.093
COMPUTER AND OFFICE
EQUIPMENT
NCR(NIGERIA)PLC. 0.072 0.167 0.094 0.173 0.077
-
0.395
-
0.0003 0.075 0.472 0.492
0.085 -0.221
TRIPPLE GEE&COMP. PLC. 0.1 0.081 0.081 0.057 0.039 0.02 0.044 0.104 0.115
-
0.004
0.009 0.024
CONGLOMERATES
A.G LEVENTIS NIG PLC. 0.032 0.052 0.041 0.075 0.107 0.237 0.09 0.083 0.112 0.076
0.090 0.119
CHELLARAMS PLC. 0.063 0.076 0.062 0.08 0.128 0.082 0.085 0.074 0.062 0.089
0.031 0.020
JOHN HOLT PLC. 0.167 0.137 0.067 0.099 -0.061
-
0.008 0.06 0.053 0.067 0.068
0.505 0.179
117
PZ CUSSONS NIG. PLC. 0.088 0.125 0.134 0.13 0.128 0.104 0.075 0.115 0.1 0.128
0.116 0.067
SCOA NIG. PLC. 0.254 0.11 0.125 0.071 0.026 0.38 0.437 0.157 0.237 0.091
0.054 0.077
UAC PLC. 0.106 0.077 0.196 0.139 0.116 0.125 0.15 0.165 0.135 0.109
0.369 0.105
UNILEVER NIG. PLC. 0.175 0.202 0.29 0.229 0.127
-
0.062 0.125 0.19 0.283 0.262
0.254 0.244
CONSTRUCTION
JULIUS BERGER NIG. PLC. 0.031 0.027 0.015 0.018 0.021 0.025 0.036 0.042 0.066 0.059
0.062 0.070
EMERGING MARKETS
JULI PLC 0.032 -0.017
-
0.074 0.033 -0.041
-
0.196 -0.037
-
0.087
-
0.085
-
0.128
SMART PRODUCTS NIG. PLC -0.062 -0.1 0.006 0.008 0.088 0.046 0.062 0.04 0.052 0.059
0.094 0.128
ENGINEERING TECHNOLOGY
CUTIX PLC 0.145 0.244 0.208 0.179 0.177 0.232 0.31 0.298 0.206 0.217
0.174 0.162
FOOD/BEVERAGES&TOBACCO
7-UP BOTTLING CO. PLC. 0.189 0.295 0.24 0.193 0.132 0.122 0.124 0.137 0.13 0.159
0.105 0.118
CADBURY NIG. PLC. 0.222 0.258 0.255 0.199 0.131
-
0.085 -0.081
-
0.057 0.002 0.062
0.109 0.086
FLOUR MILLS NIG. PLC. 0.124 0.141 0.079 0.104 0.091 0.125 0.142 0.108 0.126 0.267
0.135 0.084
NESTLE NIG PLC. 0.536 0.491 0.477 0.455 0.453 0.316 0.398 0.407 0.335 0.315
0.234 0.282
U T C NIG PLC. 0.105 0.115
-
0.046 0.05 -0.293 0.056 0.027 0.032 0.058 0.05
0.059
HEALTHCARE
EVANS MEDICAL PLC. 0.088 0.127 0.077 0.026 0.026 0.079 0.02 0.08 -0.03 0.119
0.061 0.073
GLAXO SMITHKLINE CONS. 0.669 0.15 0.222 0.223 0.18 0.169 0.116 0.177 0.216 0.228
0.195 0.191
MAY&BAKER NIG. PLC. 0.25 0.154 0.156 0.159 0.128 0.097 0.113 0.146 0.08 0.072
0.081 0.064
MORISON INDUST. PLC. 0.124 0.076 0.102 0.108 0.055 0.064 0.089 0.034
-
0.035 -0.06
0.026 0.058
NEIMETH INTER. PHARM 0.187 0.18 0.207 0.172 0.194 0.107 0.094 0.082
-
0.047 0.03
0.079
PHARM-DEKO PLC. 0.068 0.215 0.182 0.104 0.055
-
0.308 -0.04 0.002 -0.32 0.076
0.066 0.034
HOTEL& TOURISM
IKEJA HOTEL PLC. 0.206 0.259 0.057 0.046 0.067 0.061 0.084 0.097 0.127 0.126
0.128
INDUSTRIAL/DOMESTIC
PRODUCT
ALUMINIUM EXTRUS. IND PLC. 0.124 0.032 -0.01 0.045 0.063 0.106 0.161 0.172 0.223 0.143
0.093 0.065
FIRST ALUMIN. NIG. PLC. 0.051 0.066 0.16 0.131 0.138 0.07 0.003 0.032 0.058 0.037
0.008 -0.074
VITAFOAM NIG. PLC. 0.283 0.233 0.21 0.206 0.124 0.147 0.199 0.24 0.18 0.18
0.251 0.134
118
VONO PRODUCTS PLC. 0.078 0.116 0.141 0.232 -0.137 0.045 -0.416
-
0.026
-
0.059
-
0.108
-0.008 0.039
MARITIME
JAPAUL OIL&MARITIME SERV. -0.05 0.163 0.203 0.141 0.12 0.117 0.103 0.44 0.048 0.046
PACKAGING
BETA GLASS CO. PLC. 0.223 0.158 0.107 0.063 0.045 0.074 0.098 0.124 0.163 0.127
0.098 0.059
GREIF NIG. PLC. 0.049 -0.01
-
0.105 -0.118 0.013 0.023 -0.002 0.089 0.013 0.116
0.105 0.078
PETROLEUM(MARKETING)
MOBIL OIL NIG. PLC. 0.187 0.085 0.162 0.175 0.28 0.158 0.158 0.18 0.208 0.248
0.198 0.129
OANDO PLC. 0.107 0.076 0.131 0.063 0.05 0.066 0.044 0.057 0.022 0.013
0.066
TOTAL NIG PLC 0.204 0.186 0.222 0.182 0.169 0.13 0.138 0.162 0.134 0.114
0.112 0.113
PRINTING&PUBLISHING
ACADEMY PRESS 0.131 0.155 0.161 0.16 0.109 0.102 0.107 0.101 0.093 0.109
0.085 0.053
LONGMAN NIG. PLC. 0.169 0.111 0.108 0.157 0.198 0.249 0.26 0.202 0.212 0.063
UNIVERSITY PRESS PLC. 0.15 0.096 0.101 0.118 0.103 0.164 0.218 0.175 0.211 0.208
0.138
ROE
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
AGRICULTURE/AGRO-ALLIED
OKOMU OIL PALM CO. PLC. 0.1 0.1 0.198 0.212 0.141 0.154 0.193 0.32 0.188 0.347
0.240 0.171
PRESCO PLC 0.366 0.216 0.331 0.418 0.31 0.19 0.206 0.506 0.17 0.426
0.164 0.245
AUTOMOBILE&TYRE
RT BRISCO PLC. 0.628 0.46 0.935 0.177 0.195 0.401 0.447 0.457 0.236 0.214
0.280 0.235
BREWERIES
GUINNESS NIG. PLC. 0.447 0.491 0.663 0.704 0.442 0.584 0.45 0.429 0.628 0.608
0.659 0.567
INTERNATIONAL BREWERIES 0.251
-
0.628 1.705 0.149 0.181 0.181
-
0.0001 70.64 0.217
-
3.308
0.855 0.443
NIGERIAN BREWERIES. PLC 0.398 0.535 0.499 0.511 0.445 0.468 0.634 1.141 0.905 0.9
0.728 0.684
BUILDING MATERIALS
CEMENT CO. OF NORTH NIG.
PLC. -5.45 0.425 0.43 0.601 0.236 -0.007 0.178 0.558 0.549 0.426
0.470 0.216
NIGERIAN ROPES PLC. 1.185 0.793 0.224 0.171 0.001 0.005 0.111 0.159 0.092 0.004
0.021 -2.493
WA PORTLAND COMP. PLC. 0.191 0.07
-
0.182 1.501 0.422 0.527 0.404 0.328 0.211 0.175
0.291 -0.148
119
CHEMICAL&PAINTS
BERGER PAINTS NIGERIA PLC. 0.456 0.417 0.539 0.459 0.097 0.205 0.227 0.209 0.244 0.318
0.134 0.111
CAP PLC. 1.01 0.372 0.38 0.422 0.38 0.533 0.566 1.453 0.821 1.115
0.799 1.360
DN MEYER PLC. 0.274 0.414 0.492 0.412
-
0.878 0.96 0.314
-
0.118
-
0.338
-
0.027
0.026 0.039
COMMERCIAL/SERVICES
TRANS-NATIONWIDE EXP. PLC. 0.057
-
0.024
-
0.099 0.159 0.331 0.377 0.458 0.426 0.196 0.147
0.136 0.179
COMPUTER AND OFFICE
EQUIPMENT
NCR(NIGERIA)PLC. -0.414 -3.16 2.721 1.377 0.441 1.093 0.002
-
0.418 2.83 0.962
0.212 -8.345
TRIPPLE GEE&COMP. PLC. 0.244 0.211 0.22 0.126 0.083 0.042 0.093 0.198 0.227
-
0.009
0.020 0.065
CONGLOMERATES
A.G LEVENTIS NIG PLC. 0.074 0.105 0.073 0.109 0.159 0.188 0.119 0.115 0.156 0.12
0.146 0.192
CHELLARAMS PLC. 0.109 0.169 0.067 0.084 0.287 0.182 0.184 0.18 0.203 0.264
0.108 0.091
JOHN HOLT PLC. 7.111 1.503 1.333 1.281
-
1.617 -0.263 -10.22
-
6.823
-
0.385
-
0.438
0.404 0.437
PZ CUSSONS NIG. PLC. 0.132 0.184 0.213 0.189 0.201 0.154 0.107 0.169 0.153 0.206
0.195 0.105
SCOA NIG. PLC. 0.284 0.119 0.873 0.445 1.713 1.699 0.767 0.311 0.391 0.145
0.109 0.182
UAC PLC. 0.179 0.191 0.372 0.171 0.165 0.175 0.237 0.275 0.242 0.19
0.664 0.155
UNILEVER NIG. PLC. 0.387 0.519 0.836 0.591 0.557 -0.292 0.507 0.669 0.816 0.817
0.851 0.886
CONSTRUCTION
JULIUS BERGER NIG. PLC. 0.427 0.463 0.323 0.269 0.372 0.536 0.558 0.875 1.31 1.161
1.113 0.848
EMERGING MARKETS
JULI PLC 0.04 -0.02
-
0.079 0.036
-
0.043 -0.239 -0.049
-
0.118
-
0.103
-
0.171
SMART PRODUCTS NIG. PLC -0.078 -0.14 0.008 0.012 0.103 0.052 0.098 0.061 2.042 0.084
0.195 0.272
ENGINEERING TECHNOLOGY
CUTIX PLC 0.415 0.654 0.551 0.468 0.464 0.537 0.731 0.508 0.42 0.542
0.329 0.300
FOOD/BEVERAGES&TOBACCO
7-UP BOTTLING CO. PLC. 0.61 0.847 0.681 0.513 0.417 0.411 0.426 0.455 0.518 0.591
0.495 0.512
CADBURY NIG. PLC. 0.64 0.455 0.435 0.413 0.382 -0.889 -3.988 0.483 0.005 0.13
0.221 0.172
FLOUR MILLS NIG. PLC. 0.333 0.456 0.344 0.451 0.259 0.353 0.445 0.418 0.585 0.762
0.374 0.182
NESTLE NIG PLC. 2.435 2.904 3.554 3.518 4.36 1.26 1.357 1.313 1.501 1.28
0.784 0.733
U T C NIG PLC. 3.881 0.308
-
0.506 0.791
-
1.186 0.113 0.054 0.063 0.11 0.097
0.103
120
HEALTHCARE
EVANS MEDICAL PLC. 0.136 0.191 0.155 0.055 0.053 0.174 0.057 0.39
-
0.325 0.885
0.155 0.186
GLAXO SMITHKLINE CONS. 0.181 0.567 0.581 0.533 0.466 0.376 0.247 0.339 0.419 0.438
0.389 0.391
MAY&BAKER NIG. PLC. 0.356 0.198 0.312 0.297 0.306 0.147 0.192 0.303 0.183 0.17
0.181 0.165
MORISON INDUST. PLC. 0.19 0.114 0.162 0.179 0.097 0.119 0.164 0.043
-
0.047
-
0.084
0.034 0.078
NEIMETH INTER. PHARM 0.915 0.858 0.842 0.621 0.583 0.187 0.158 0.164
-
0.115 0.076
0.239
PHARM-DEKO PLC. 0.607 1.082 0.502 0.347 0.098 -2.945 0.9
-
0.011 0.328 0.132
-0.259 0.100
HOTEL& TOURISM
IKEJA HOTEL PLC. 0.212 0.267 0.373 0.292 0.446 0.221 0.27 0.271 0.334 0.285
0.537
INDUSTRIAL/DOMESTIC
PRODUCT
ALUMINIUM EXTRUS. IND PLC. 0.546 0.212 0.196 3.686 1.89 1.1 0.834 0.709 0.65 0.411
0.186 0.110
FIRST ALUMIN. NIG. PLC. 0.205 0.403 0.43 0.381 0.426 0.342 0.021 0.117 0.093 0.061
0.013 -0.144
VITAFOAM NIG. PLC. 0.878 0.755 0.774 0.557 0.306 0.369 0.487 0.585 0.451 0.441
0.845 0.433
VONO PRODUCTS PLC. 0.154 0.234 0.283 0.482
-
0.255 0.132 -1.758
-
0.171
-
0.119
-
0.382
-0.030 0.089
MARITIME
JAPAUL OIL&MARITIME SERV. -1.806 2.317 0.299 0.243 0.184 0.222 0.327 0.049 0.051 0.052
PACKAGING
BETA GLASS CO. PLC. 0.359 0.25 0.177 0.11 0.078 0.131 0.197 0.236 0.254 0.207
0.157 0.107
GREIF NIG. PLC. 0.066
-
0.015 0.19 -0.354 0.043 0.06 -0.006 0.202 0.032 0.23
0.199 0.142
PETROLEUM(MARKETING)
MOBIL OIL NIG. PLC. 3.117 1.645 3.813 2.471 1.227 0.968 1.302 1.264 1.099 0.996
1.367 0.659
OANDO PLC. 0.317 0.405 0.741 0.146 0.13 0.192 0.103 0.313 0.257 0.112
0.143
TOTAL NIG PLC 1.056 0.95 1.079 1.208 1.183 0.592 0.774 0.932 0.957 0.7
0.656 0.759
PRINTING&PUBLISHING
ACADEMY PRESS 0.52 0.457 0.458 0.459 0.312 0.384 0.349 0.311 0.273 0.381
0.291 0.205
LONGMAN NIG. PLC. 0.447 0.368 0.383 0.505 0.571 0.539 0.618 0.312 0.313 0.652
UNIVERSITY PRESS PLC. 0.233 0.153 0.149 0.178 0.149 0.243 0.353 0.256 0.336 0.334
0.187
121
TDR
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
AGRICULTURE/AGRO-ALLIED
OKOMU OIL PALM CO. PLC. 0.19 0.297 0.291 0.241 0.215 0.209 0.503 0.413 0.454 0.323
0.186 0.178
PRESCO PLC 0.638 0.493 0.512 0.445 0.461 0.564 0.58 0.55 0.654 0.523
0.250 0.390
AUTOMOBILE&TYRE
RT BRISCO PLC. 0.695 0.624 0.533 0.359 0.42 0.5 0.618 0.668 0.572 0.634
0.634 0.759
BREWERIES
GUINNESS NIG. PLC. 0.501 0.959 0.614 0.655 0.635 0.65 0.559 0.506 0.573 0.564
0.563 0.606
INTERNATIONAL BREWERIES 1.33 0.819 1.149 1.974 3.069 2.284 3.058 0.999 1.056 1.008
0.889 0.593
NIGERIAN BREWERIES. PLC 0.492 0.622 0.692 0.658 0.52 0.521 0.523 0.691 0.565 0.561
0.636 0.632
BUILDING MATERIALS
CEMENT CO. OF NORTH NIG.
PLC. 0.893 0.716 0.779 0.738 0.746 0.807 0.655 0.548 1.15 0.548
0.443 0.464
NIGERIAN ROPES PLC. 0.853 0.871 0.52 0.511 0.58 0.576 0.513 0.616 0.776 0.767
0.697 0.890
WA PORTLAND COMP. PLC. 0.6 0.746 0.865 0.933 0.636 0.476 0.352 0.345 0.499 0.592
0.528 0.675
CHEMICAL&PAINTS
BERGER PAINTS NIGERIA PLC. 0.577 0.654 0.721 0.691 0.59 0.538 0.486 0.426 0.433 0.376
0.368 0.391
CAP PLC. 0.483 0.476 0.509 0.522 0.415 0.445 0.494 0.691 0.651 0.569
0.479 0.611
DN MEYER PLC. 0.406 0.605 0.632 0.711 0.894 0.851 0.686 0.555 0.694 0.784
0.751 0.747
COMMERCIAL/SERVICES
TRANS-NATIONWIDE EXP. PLC. 0.33 0.417 0.496 0.513 0.446 0.449 0.435 0.651 0.37 0.312
0.256 0.480
COMPUTER AND OFFICE
EQUIPMENT
NCR(NIGERIA)PLC. 1.173 1.053 0.965 0.89 0.824 1.361 1.162 1.18 0.833 0.489
0.597 0.974
TRIPPLE GEE&COMP. PLC. 0.589 0.693 0.633 0.551 0.528 0.514 0.524 0.473 0.491 0.52
0.558 0.625
CONGLOMERATES
A.G LEVENTIS NIG PLC. 0.528 0.501 0.441 0.313 0.325 0.583 0.246 0.278 0.283 0.366
0.388 0.380
CHELLARAMS PLC. 0.42 0.553 0.067 0.051 0.555 0.547 0.544 0.588 0.743 0.73
0.708 0.776
JOHN HOLT PLC. 0.977 0.909 0.949 0.923 0.962 1.03 1.006 1.008 1.175 1.156
2.697 1.678
PZ CUSSONS NIG. PLC. 0.336 0.317 0.371 0.31 0.362 0.324 0.298 0.32 0.348 0.377
0.374 0.334
SCOA NIG. PLC. 0.998 0.984 0.856 0.84 0.985 0.776 0.43 0.495 0.395 0.368
0.505 0.578
UAC PLC. 0.409 0.595 0.475 0.267 0.299 0.287 0.384 0.414 0.443 0.424
0.444 0.325
122
UNILEVER NIG. PLC. 0.548 0.612 0.365 0.612 0.772 0.788 0.753 0.716 0.654 0.679
0.701 0.725
CONSTRUCTION
JULIUS BERGER NIG. PLC. 0.927 0.942 0.953 0.933 0.945 0.954 0.936 0.952 0.95 0.938
0.944 0.917
EMERGING MARKETS
JULI PLC 0.2 0.157 0.063 0.067 0.044 0.177 0.253 0.262 0.17 0.253
SMART PRODUCTS NIG. PLC 0.203 0.295 0.278 0.289 0.147 0.127 0.366 0.342 0.341 0.289
0.521 0.530
ENGINEERING TECHNOLOGY
CUTIX PLC 0.65 0.626 0.622 0.618 0.619 0.568 0.576 0.577 0.508 0.495
0.470 0.458
FOOD/BEVERAGES&TOBACCO
7-UP BOTTLING CO. PLC. 0.691 0.651 0.648 0.624 0.685 0.704 0.71 0.699 0.75 0.732
0.787 0.770
CADBURY NIG. PLC. 0.624 1.038 1.041 0.517 0.658 0.914 0.98 1.118 0.483 0.526
0.507 0.501
FLOUR MILLS NIG. PLC. 0.626 0.69 0.77 0.77 0.648 0.643 0.681 0.74 0.784 0.65
0.640 0.536
NESTLE NIG PLC. 0.78 0.831 0.867 0.871 0.896 0.495 0.707 0.69 0.777 0.754
0.591 0.062
U T C NIG PLC. 0.997 0.509 0.909 0.937 0.753 0.5 0.501 0.496 0.477 0.484
0.426
HEALTHCARE
EVANS MEDICAL PLC. 0.352 0.334 0.5 0.519 0.506 0.548 0.657 0.794 0.909 0.866
0.610 0.608
GLAXO SMITHKLINE CONS. 0.62 0.735 0.618 0.506 0.698 0.55 0.522 0.476 0.486 0.478
0.499 0.511
MAY&BAKER NIG. PLC. 0.667 0.588 0.499 0.465 0.58 0.34 0.413 0.519 0.56 0.577
0.552 0.611
MORISON INDUST. PLC. 0.351 0.338 0.371 0.398 0.427 0.464 0.457 0.211 0.264 0.277
0.250 0.796
NEIMETH INTER. PHARM 0.795 0.79 0.754 0.351 0.668 0.427 0.405 0.5 0.597 0.609
0.670
PHARM-DEKO PLC. 0.887 0.801 0.638 0.7 1.1 1.646 1.044 1.933 2.862 1.573
1.253 0.661
HOTEL& TOURISM
IKEJA HOTEL PLC. 0.029 0.03 0.847 0.844 0.85 0.723 0.69 0.643 0.621 0.559
0.762
INDUSTRIAL/DOMESTIC
PRODUCT
ALUMINIUM EXTRUS. IND PLC. 0.773 0.85 0.95 0.988 0.966 0.903 0.57 0.757 0.657 0.653
0.499 0.412
FIRST ALUMIN. NIG. PLC. 0.75 0.836 0.628 0.655 0.676 0.796 0.877 0.724 0.373 0.386
0.397 0.484
VITAFOAM NIG. PLC. 0.678 0.691 0.728 0.614 0.595 0.601 0.59 0.591 0.6 0.592
0.703 0.692
VONO PRODUCTS PLC. 0.492 0.492 0.503 0.518 0.462 0.655 0.763 0.847 0.505 0.717
0.724 0.563
MARITIME
JAPAUL OIL&MARITIME SERV. 0.972 0.93 0.322 0.423 0.349 0.475 0.686 0.105 0.058 0.113
PACKAGING
123
BETA GLASS CO. PLC. 0.379 0.367 0.397 0.432 0.421 0.431 0.502 0.476 0.356 0.385
0.371 0.445
GREIF NIG. PLC. 0.255 0.335 0.445 0.668 0.703 0.617 0.57 0.559 0.592 0.494
0.473 0.453
PETROLEUM(MARKETING)
MOBIL OIL NIG. PLC. 0.94 0.948 0.958 0.929 0.771 0.837 0.879 0.858 0.83 0.805
0.855 0.804
OANDO PLC. 0.733 0.812 0.823 0.569 0.613 0.654 0.574 0.818 0.913 0.887
0.536
TOTAL NIG PLC 0.786 0.805 0.794 0.849 0.857 0.781 0.821 0.826 0.86 0.836
0.829 0.851
PRINTING&PUBLISHING
ACADEMY PRESS 0.748 0.661 0.649 0.652 0.65 0.734 0.693 0.676 0.66 0.713
0.709 0.741
LONGMAN NIG. PLC. 0.622 0.698 0.719 0.689 0.654 0.538 0.58 0.363 0.324 0.348
UNIVERSITY PRESS PLC. 0.57 0.271 0.319 0.336 0.31 0.323 0.381 0.393 0.371 0.378
0.263
LTDR
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
AGRICULTURE/AGRO-ALLIED
OKOMU OIL PALM CO. PLC. 0 0 0 0 0 0 0.256 0.229 0.318 0.227
0.120 0.113
PRESCO PLC 0.289 0.199 0.343 0.277 0.326 0.361 0.308 0.22 0.393 0.451
0.146 0.290
AUTOMOBILE&TYRE
RT BRISCO PLC. 0 0 0 0.037 0.039 0.028 0.033 0.027 0.039 0.019
0.019 0.016
BREWERIES
GUINNESS NIG. PLC. 0.081 0.53 0.15 0.27 0.334 0.305 0.189 0.163 0.152 0.173
0.167 0.226
INTERNATIONAL BREWERIES 0 0 0 0 1.008 0.522 0.485 0.72 0.83 0.759
0.179 0.252
NIGERIAN BREWERIES. PLC 0.064 0.053 0.083 0.117 0.162 0.205 0.198 0.167 0.169 0.169
0.239 0.289
BUILDING MATERIALS
CEMENT CO. OF NORTH NIG. PLC. 0.164 0.077 0.052 0.085 0.061 0.044 0.043 0.299 0.26 0.14
0.120 0.098
NIGERIAN ROPES PLC. 0.24 0.197 0.095 0.118 0.112 0.124 0.181 0.185 0.213 0.194
0.273 0.306
WA PORTLAND COMP. PLC. 0.281 0.355 0.327 0.527 0.286 0.14 0.04 0.052 0.376 0.102
0.180 0.173
CHEMICAL&PAINTS
BERGER PAINTS NIGERIA PLC. 0.039 0.065 0.058 0.073 0.082 0.09 0.092 0.094 0.089 0.05
0.078 0.083
CAP PLC. 0.073 0.073 0.078 0.072 0.056 0.058 0.054 0.06 0.062 0.061
0.061 0.026
DN MEYER PLC. 0.072 0.081 0.079 0.065 0.071 0.181 0.052 0.06 0.129 0.163
0.436 0.438
COMMERCIAL/SERVICES
124
TRANS-NATIONWIDE EXP. PLC. 0 0 0 0 0 0 0.111 0.059 0.058
0.096 0.205
COMPUTER AND OFFICE
EQUIPMENT
NCR(NIGERIA)PLC. 0.086 0.103 0.095 0.118 0.035 0.428 0.245 0.301 0.178 0
0.040 0.000
TRIPPLE GEE&COMP. PLC. 0.274 0.307 0.28 0.422 0.391 0.378 0.364 0.298 0.25 0.294
0.290 0.419
CONGLOMERATES
A.G LEVENTIS NIG PLC. 0.039 0.049 0.044 0.047 0.066 0.152 0.094 0.087 0.088 0.102
0.166 0.136
CHELLARAMS PLC. 0.012 0.009 0.056 0.031 0.039 0.037 0.029 0.024 0.01 0.062
0.180 0.144
JOHN HOLT PLC. 0.002 0.006 0 0.03 0.039 0.037 0.028 0.032 0.082 0.078
0.214 0.104
PZ CUSSONS NIG. PLC. 0.085 0.088 0.083 0.097 0.088 0.083 0.049 0.057 0.06 0.064
0.052 0.069
SCOA NIG. PLC. 0.105 0.078 0.012 0.013 0.016 0.017 0.025 0.024 0.016 0.019
0.025 0.032
UAC PLC. 0.118 0.054 0.106 0.076 0.093 0.074 0.083 0.101 0.102 0.097
0.095 0.045
UNILEVER NIG. PLC. 0.108 0.114 0.152 0.134 0.12 0.137 0.127 0.131 0.13 0.124
0.115 0.113
CONSTRUCTION
JULIUS BERGER NIG. PLC. 0.005 0.03 0.023 0.082 0.07 0.047 0.055 0.039 0.07 0.058
0.579 0.538
EMERGING MARKETS
JULI PLC 0 0 0 0 0 0 0 0 0 0
SMART PRODUCTS NIG. PLC 0 0.042 0.032 0.019 0 0 0 0 0.209 0.163
0.183 0.208
ENGINEERING TECHNOLOGY
CUTIX PLC 0 0.019 0.024 0.075 0.011 0.006 0.104 0.099 0.109 0.072
0.085 0.079
FOOD/BEVERAGES&TOBACCO
7-UP BOTTLING CO. PLC. 0.058 0.113 0.124 0.18 0.199 0.205 0.848 0.417 0.385 0.351
0.366 0.192
CADBURY NIG. PLC. 0.227 0.644 0.669 0.056 0.23 0.107 0.175 0.158 0.137 0.105
0.095 0.080
FLOUR MILLS NIG. PLC. 0.048 0.044 0.148 0.178 0.153 0.178 0.245 0.208 0.261 0.25
0.381 0.252
NESTLE NIG PLC. 0.143 0.193 0.194 0.239 0.217 0.206 0.319 0.31 0.311 0.431
0.312 0.333
U T C NIG PLC. 0.259 0.203 0.135 0.077 0.121 0.082 0.107 0.075 0.088 0.111
0.217
HEALTHCARE
EVANS MEDICAL PLC. 0.005 0.005 0.009 0.033 0.048 0.042 0.07 0.082 0.075 0.455
0.333 0.277
GLAXO SMITHKLINE CONS. 0.187 0.112 0.105 0.088 0.079 0.083 0.091 0.092 0.077 0.089
0.077 0.074
MAY&BAKER NIG. PLC. 0.11 0.117 0.096 0.152 0.327 0.091 0.058 0.129 0.132 0.214
0.134 0.268
MORISON INDUST. PLC. 0.081 0.089 0.124 0.104 0.122 0.125 0.103 0.051 0.051 0.052
0.045 0.054
NEIMETH INTER. PHARM 0.028 0.037 0.037 0.035 0.288 0.164 0.121 0.233 0.181 0.192
0.094
125
PHARM-DEKO PLC. 0.173 0.171 0.152 0.118 0.128 0.517 0.24 0.31 0.386 0.504
0.361 0.085
HOTEL& TOURISM
IKEJA HOTEL PLC. 0.029 0.03 0.091 0.144 0.412 0.377 0.411 0.366 0.304 0.223
0.582
INDUSTRIAL/DOMESTIC
PRODUCT
ALUMINIUM EXTRUS. IND PLC. 0.144 0.178 0.531 0.574 0.544 0.328 0.285 0.139 0.103 0.122
0.093 0.125
FIRST ALUMIN. NIG. PLC. 0.152 0.066 0.03 0.1 0.074 0.098 0.242 0.035 0.03 0.048
0.069 0.108
VITAFOAM NIG. PLC. 0.138 0.151 0.136 0.164 0.171 0.095 0.088 0.136 0.099 0.084
0.097 0.077
VONO PRODUCTS PLC. 0.019 0.033 0.04 0.059 0.055 0.042 0.027 0.311 0.092 0.209
0.297 0.186
MARITIME
JAPAUL OIL&MARITIME SERV. 0 0 0 0 0.01 0.169 0.35 0.066 0.026 0.08
PACKAGING
BETA GLASS CO. PLC. 0.122 0.158 0.161 0.171 0.166 0.177 0.153 0.158 0.197 0.184
0.169 0.233
GREIF NIG. PLC. 0 0 0.008 0.017 0.02 0.024 0.002 0.0001 0.306 0.339
0.327 0.342
PETROLEUM(MARKETING)
MOBIL OIL NIG. PLC. 0.077 0.069 0.085 0.138 0.181 0.16 0.152 0.211 0.261 0.292
0.458 0.436
OANDO PLC. 0.002 0.231 0.175 0.05 0.043 0.034 0.095 0.144 0.001 0.101
0.438
TOTAL NIG PLC 0.038 0.057 0.09 0.091 0.092 0.101 0.08 0.069 0.069 0.04
0.045 0.037
PRINTING&PUBLISHING
ACADEMY PRESS 0 0 0 0.008 0.032 0.199 0.193 0.123 0.09 0.307
0.393 0.258
LONGMAN NIG. PLC. 0.054 0.037 0.052 0.041 0.059 0.053 0.062 0.033 0.016 0.005
UNIVERSITY PRESS PLC. 0.087 0.066 0.07 0.074 0.076 0.072 0.088 0.066 0.057 0.054
0.027
STDR
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
AGRICULTURE/AGRO-ALLIED
OKOMU OIL PALM CO. PLC. 0.19 0.297 0.291 0.241 0.215 0.209 0.247 0.184 0.137 0.096
0.066 0.065
PRESCO PLC 0.349 0.294 0.169 0.168 0.134 0.203 0.272 0.33 0.261 0.072
0.103 0.100
AUTOMOBILE&TYRE
RT BRISCO PLC. 0.695 0.624 0.533 0.322 0.381 0.472 0.585 0.641 0.533 0.615
0.615 0.743
BREWERIES
GUINNESS NIG. PLC. 0.499 0.429 0.465 0.385 0.301 0.345 0.37 0.343 0.422 0.391
0.396 0.380
INTERNATIONAL BREWERIES 1.33 0.819 1.149 1.974 2.06 1.763 2.573 0.279 0.226 0.249
0.711 0.341
126
NIGERIAN BREWERIES. PLC 0.428 0.568 0.609 0.54 0.359 0.316 0.325 0.525 0.396 0.392
0.397 0.342
BUILDING MATERIALS
CEMENT CO. OF NORTH NIG. PLC. 0.729 0.639 0.727 0.653 0.685 0.763 0.612 0.413 0.891 0.408
0.323 0.365
NIGERIAN ROPES PLC. 0.613 0.674 0.425 0.393 0.468 0.453 0.332 0.431 0.563 0.573
0.425 0.584
WA PORTLAND COMP. PLC. 0.319 0.391 0.538 0.407 0.35 0.336 0.311 0.293 0.123 0.49
0.348 0.501
CHEMICAL&PAINTS
BERGER PAINTS NIGERIA PLC. 0.538 0.589 0.663 0.618 0.507 0.449 0.394 0.332 0.344 0.326
0.290 0.307
CAP PLC. 0.411 0.403 0.431 0.45 0.359 0.387 0.441 0.631 0.589 0.508
0.417 0.585
DN MEYER PLC. 0.394 0.524 0.554 0.647 0.823 0.67 0.634 0.495 0.565 0.621
0.315 0.309
COMMERCIAL/SERVICES
TRANS-NATIONWIDE EXP. PLC. 0.33 0.417 0.496 0.513 0.446 0.449 0.435 0.54 0.311 0.254
0.256 0.275
COMPUTER AND OFFICE
EQUIPMENT
NCR(NIGERIA)PLC. 1.087 0.95 0.871 0.772 0.789 0.933 0.917 0.879 0.655 0.489
0.557 0.974
TRIPPLE GEE&COMP. PLC. 0.315 0.312 0.353 0.129 0.137 0.136 0.16 0.175 0.241 0.226
0.268 0.206
CONGLOMERATES
A.G LEVENTIS NIG PLC. 0.434 0.452 0.397 0.266 0.259 0.431 0.152 0.191 0.195 0.264
0.223 0.244
CHELLARAMS PLC. 0.409 0.044 0.012 0.02 0.516 0.51 0.515 0.564 0.733 0.668
0.528 0.633
JOHN HOLT PLC. 0.975 0.903 0.949 0.893 0.923 0.993 0.978 0.975 1.094 1.077
2.483 1.574
PZ CUSSONS NIG. PLC. 0.251 0.229 0.287 0.213 0.274 0.242 0.249 0.263 0.288 0.313
0.322 0.266
SCOA NIG. PLC. 0.883 0.907 0.845 0.827 0.969 0.76 0.405 0.471 0.379 0.35
0.479 0.546
UAC PLC. 0.291 0.541 0.369 0.191 0.206 0.212 0.302 0.313 0.341 0.328
0.283 0.144
UNILEVER NIG. PLC. 0.439 0.498 0.212 0.478 0.653 0.65 0.626 0.585 0.524 0.555
0.586 0.612
CONSTRUCTION
JULIUS BERGER NIG. PLC. 0.922 0.912 0.93 0.851 0.875 0.906 0.881 0.913 0.88 0.88
0.364 0.379
EMERGING MARKETS
JULI PLC 0.2 0.157 0.063 0.067 0.044 0.177 0.253 0.262 0.17 0.253
SMART PRODUCTS NIG. PLC 0.203 0.253 0.245 0.271 0.147 0.127 0.366 0.342 0.133 0.126
0.339 0.321
ENGINEERING TECHNOLOGY
CUTIX PLC 0.65 0.607 0.599 0.543 0.607 0.563 0.472 0.478 0.399 0.423
0.385 0.379
FOOD/BEVERAGES&TOBACCO
7-UP BOTTLING CO. PLC. 0.632 0.538 0.523 0.444 0.486 0.499 0.361 0.282 0.364 0.381
0.420 0.577
127
CADBURY NIG. PLC. 0.396 0.394 0.372 0.462 0.427 0.806 0.805 0.96 0.346 0.421
0.412 0.421
FLOUR MILLS NIG. PLC. 0.578 0.652 0.623 0.592 0.495 0.465 0.436 0.532 0.523 0.38
0.258 0.284
NESTLE NIG PLC. 0.637 0.638 0.672 0.632 0.679 0.289 0.388 0.38 0.466 0.322
0.279 0.283
U T C NIG PLC. 0.738 0.306 0.774 0.86 0.633 0.417 0.394 0.421 0.389 0.373
0.208
HEALTHCARE
EVANS MEDICAL PLC. 0.347 0.33 0.491 0.486 0.458 0.506 0.586 0.712 0.833 0.411
0.277 0.331
GLAXO SMITHKLINE CONS. 0.433 0.623 0.382 0.418 0.619 0.468 0.431 0.384 0.408 0.389
0.422 0.436
MAY&BAKER NIG. PLC. 0.557 0.471 0.403 0.313 0.253 0.249 0.355 0.39 0.429 0.363
0.418 0.343
MORISON INDUST. PLC. 0.27 0.248 0.247 0.294 0.305 0.339 0.354 0.16 0.213 0.225
0.205 0.204
NEIMETH INTER. PHARM 0.767 0.753 0.717 0.317 0.379 0.263 0.285 0.267 0.413 0.416
0.576
PHARM-DEKO PLC. 0.714 0.63 0.486 0.582 0.972 1.129 0.805 1.623 2.478 1.069
0.892 0.576
HOTEL& TOURISM
IKEJA HOTEL PLC. 0 0 0.756 0.7 0.438 0.346 0.279 0.277 0.317 0.335
0.180
INDUSTRIAL/DOMESTIC
PRODUCT
ALUMINIUM EXTRUS. IND PLC. 0.629 0.671 0.42 0.413 0.435 0.576 0.523 0.618 0.555 0.531
0.406 0.287
FIRST ALUMIN. NIG. PLC. 0.598 0.769 0.598 0.556 0.602 0.699 0.635 0.69 0.343 0.338
0.328 0.376
VITAFOAM NIG. PLC. 0.54 0.54 0.593 0.45 0.424 0.506 0.502 0.454 0.501 0.508
0.606 0.615
VONO PRODUCTS PLC. 0.474 0.459 0.463 0.459 0.407 0.613 0.736 0.536 0.413 0.507
0.427 0.377
MARITIME
JAPAUL OIL&MARITIME SERV. 0.972 0.93 0.322 0.423 0.34 0.307 0.336 0.039 0.032 0.033
PACKAGING
BETA GLASS CO. PLC. 0.256 0.291 0.236 0.261 0.255 0.253 0.349 0.318 0.159 0.201
0.203 0.212
GREIF NIG. PLC. 0.255 0.335 0.437 0.651 0.682 0.593 0.568 0.558 0.286 0.155
0.146 0.111
PETROLEUM(MARKETING)
MOBIL OIL NIG. PLC. 0.863 0.879 0.873 0.792 0.59 0.677 0.727 0.647 0.569 0.513
0.397 0.367
OANDO PLC. 0.731 0.58 0.648 0.519 0.57 0.62 0.478 0.674 0.912 0.786
0.098
TOTAL NIG PLC 0.748 0.747 0.704 0.758 0.766 0.68 0.741 0.757 0.792 0.796
0.784 0.814
PRINTING&PUBLISHING
ACADEMY PRESS 0.748 0.661 0.649 0.643 0.618 0.535 0.5 0.553 0.569 0.406
0.317 0.483
LONGMAN NIG. PLC. 0.567 0.661 0.667 0.649 0.595 0.485 0.518 0.33 0.308 0.342
UNIVERSITY PRESS PLC. 0.483 0.205 0.249 0.262 0.234 0.25 0.294 0.252 0.314 0.325
0.236
128