Capital Structure and Financial Performance: A Sectorial Analysis
RITA I. SIKE, UMAR A. IBRAHIM,3FAIZA MAITALA
Department of Business Administration,
Nile University of Nigeria,
Cadastral Zone C-OO, Research & Institution Area, Airport Rd, Jabi 900001, Abuja,
NIGERIA
Abstract: - The prevailing market circumstances and the peculiarities of the industry impact their funding needs
and the availability of different forms of capital that could impact the ability of firms to have an optimal capital
structure that will lead to the maximization of firm value. This study examines the relationship between capital
structure and financial performance (FP), shedding new light on its effect across ten (10) sectors using Short-
term debts, Long-term debts and Total equity as proxies for capital structure and two Return on Assets and
Tobin’s Q as proxies for financial performance. The study was based on the positivism philosophy and adopted
the ex-post factor research methodology with data extracted from the audited financial firms of 129 listed non-
financial firms in Nigeria from 2010 to 2021. The Generalized Least Square (GLS) method was adopted for the
analysis of data. The study concludes that the listed non-financial firms are financed by a mix of short-term
debt, long-term debts and equity which have mixed effects on their financial performance across the various
sectors. The study, therefore, recommends that firms in Nigeria should have appropriate policies to guide their
capital structure decision that will ensure that they have the appropriate mix of debt and equity that will
optimize their performance.
Key-Words: - Capital structure, Financial Performance, GLS, Sector
Received: February 22, 2023. Revised: June 16, 2023. Accepted: June 25, 2023. Published: July 7, 2023.
1 Introduction
Businesses require funds to carry out their
operations and also exploit emerging investment
opportunities. [1] is of the view that the
liberalization of economic policies across the world
has expanded investment opportunities, widened
financing options and increased dependence on
capital markets. According to [2], the sources of
finance is a fundamental decisions to be made by
businesses because of the risk and reward associated
with such decisions. Furthermore, capital structure
decisions are fundamental and crucial as it enables
companies to determine the sources of finance and
the best mix of capital that will minimize the overall
cost of capital and maximize financial performance,
[3], [4], [5], [6], [7]. Capital structure also impacts
the ability of firms to deal with competition and the
dynamic nature of the business environment.
According to [8], capital structure decisions are
taken each time a firm decides to either start
operations, expand existing operations or have to
invest in a new project. The funds that firms utilize
in operations could be from debt in the form of
long-term loans and short-term loans sourced from
providers of capital or equity provided by the
owners of the business.
Capital structure decisions revolve around
choosing between debt and equity and the funding
sources could be either internal or external. Finance
managers must decide on the appropriate mix that
would enhance the financial performance of firms,
[8], notes that in countries where the financial sector
is underdeveloped, firms have to rely heavily on
banks to finance their operations. Thus, the
prevailing market circumstances, interest rates,
availability of different forms of capital, and costs
associated with each form of capital could limit the
ability of Finance Managers to choose the
appropriate mix of debt and equity. The difference
between these sources of capital raises a question on
the effect each form could have on the financial
performance of the firms across the industrial
sectors that are listed on the stock exchange in
Nigeria. This work aims to contribute to empirical
literature in the field of Corporate Finance by
exploring the effects.
This study is motivated by the fact that
businesses even within the same industry use
different forms of capital such as equity, long-term
debts, or short-term debts. The difference between
these sources of capital raises a question about the
effect that each form could have on the financial
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performance of the firms across the various sectors.
This work aims to contribute to empirical literature
in the field of Corporate Finance by exploring the
effects of capital structure on financial performance;
Specifically, the objectives are to assess the effect of
short-term debt, long-term debt and total equity on
Tobin's Q and firms return on assets of non-financial
firms that are listed in Nigeria's Exchange Group by
using a sectorial analysis. The rest of this paper is
structured as follows: in section 2 we provide the
literature review about the relationship between
capital structure and financial performance; section
3 provides the specification concerning the applied
methodology, section 4 explains the obtained results
and section 5 summarises and concluding remarks
are presented.
2 Literature Review
2.1 Theoretical and Conceptual Background
Several theories have been advanced to explain the
relationship between capital structure and firm
value, including the irrelevance theory of [9]–[15].
These theories play significant roles, in explaining
the relationship between capital structure and firm
value, but the trade-off theory that was first
introduced by Kraus and Litzenberger in 1973 and
modified by Myers, in 1984 and the pecking order
theory of [16], [17] are found most appealing to the
set of objectives of this study. The trade-off theory
provides for an optimal capital structure that firms
should maintain to maximise performance. The
theory places a limit which would be used to assess
the relationship between capital structure and firm
performance. The trade-off theory states that firms
will trade off the costs and benefits of debt to
maximise the value of the firm. It assesses the effect
of bankruptcy cost which is the risk associated with
debt, and the benefit of debt is the tax shield
associated with the decrease in income as a result of
interest paid on debt that is tax deductible.
[16] suggests that a firm operating under the
assumptions of trade-off theory sets a target capital
structure that is determined by balancing the dead
weight cost of bankruptcy with the tax deductions
on interest earnings. The trade-off theory is critical
to this study because it provides for an optimal
financing mix that maximises financial
performance. Another theory that was adopted for
the study is the pecking order theory which was
popularised by [16], [17] and states that firm
financing follows a hierarchy: retained earnings
first, followed by debt and equity. The theory
further states that more profitable firms have more
internal financing available. This implies that there
is a negative relationship between debt and
profitability. It is grounded in information
asymmetry between internal and external
stakeholders since managers know more about the
earning potentials of a business than external
investors.
The relationship between capital structure and
financial performance remains an open debate
among academics, managers and practitioners.
Capital Structure has been defined in several ways
in the empirical literature and no consensus exists
on any of the definitions. According to [15], [16],
capital structure is the mix of debt and equity
employed by a firm to finance its operations at any
time. In the view of [18], it is the combination of
the equity and debt capital that a firm uses for its
financing. Similarly, [19] defines it as an amalgam
of the sources through which a firm is financed.
According to [9], [10], [11], Financial Performance
is a measure of how effectively a firm uses its
resources and assets to maximize its profitability.
Financial performance can be described in various
ways and can be measured in several ways: For this
study, the return on assets (ROA) and Tobin's Q will
be used as proxies for financial performance.
2.2 Empirical Review
The empirical evidence on the subject provides
mixed and contradictory results and there is no
agreement among scholars, some report a positive
relationship, others report a negative relationship
while others report mixed outcomes long tenured
debts, or short-tenured debts.
[20] used a dynamic model to study the
relationship between financial leverage on the firm
value of selected firms quoted on the Nigerian Stock
Exchange with secondary data which covered five
years established that financial leverage has a
positive effect on the firm value both in the long and
short run. In Kenya, [21], [22] examined the effect
of capital structure on the financial performance of
non-financial firms that are listed at the Nairobi
Securities with data that covered eight years also
established that leverage had a significant positive
relationship on the financial performance of the
listed non-financial firms in the Nairobi Stock
Exchange.
Another study that established a positive
relationship was carried out by [23] that assessed the
influence of Financial Leverage on Firm's
Performance of listed non-financial firms in the
Karachi Stock Exchange (KSE) 100 index. The data
for the study covered ten years and the result of the
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panel data analysis shows that capital structure has a
positive impact on profitability.
A similar study was carried out in India by [24]
on the influence of capital structure on financial
performance with a sample of fifty manufacturing
companies. Secondary data was collected from the
financial statement of the selected companies. and
the result of the multiple regression analysis
established that there is a significant positive
relationship between capital structure and
profitability and the financial performance of the
selected companies.
In Kenya, [25] studied the capital structure and
financial performance using all the firms that are
listed on the Nairobi Stock Exchange between 2002
and 2011 which also had a positive outcome.
[18] also studied the relationship between
capital structure and the financial performance and
Shareholders’ wealth of firms in the textile industry
in Pakistan. The study covered a period of six years
from 2006 to 2011 using data from 155 companies
and found that there is a significant positive
relationship between capital structure and financial
performance. This study could have been extended
to cover a longer period. The findings of the study
might differ if extended to other sectors.
Some scholars also reported negative
relationships between capital structure. However,
[26] carried out a study on the effect of financial
leverage on firm value: evidence from selected
firms quoted on the Nigerian Stock Exchange.
Secondary data was obtained from the financial
statements of eighteen companies from 2014 to
2018. The result of the panel data analysis shows
that financial leverage has a significantly negative
effect on firm value. Similarly, [27] assessed the
relationship between capital structure and the
profitability of non-financial companies that are
listed on the Vietnam Stock Exchange. using data
from 488 listed companies and data that covered the
period from 2013 to 2018. The study also
established that the capital structure of Vietnamese
companies had a statistically negative effect on
performance. he equity component of the capital
structure.
Another study that found a negative relationship
was carried out by [27] in their assessment of the
impact of capital structure on the profitability of
firms in four Asian economies, Taiwan, Korea,
Singapore and Hong Kong using data from 2003 to
2016. The data used for the analysis was extracted
from 5,112 firms and includes 46,301 observations
over fourteen years. In Vietnam, [28] studied
Capital Structure and Firm Performance. The study
covered all listed non-financial firms and data was
collected over the period from 2007 to 2012. The
study established that all debt ratios have a
significant negative ratio with firm performance.
The result of this study brings to the fore certain
peculiarities of developing countries with
underdeveloped financial systems where the cost of
debt is higher than the distress from borrowing.
There is a need to replicate this study in Nigeria.
Similarly, [29] carried out an empirical
Investigation of Capital Structure and Firm Value
using accounting and stock market data of all the
non-financial firms that are listed on the Ho Minh
City Stock Exchange from 2007 to 2013. The
sample contained 1214 firm years and the result
indicates a negative relationship between leverage
and shareholder value that shows that debt financing
has a higher cost than benefit to firms in Vietnam.
Another study carried out in Nigeria that showed
positive outcomes of the relationship between
capital and performance was undertaken by [30].
The researchers assessed the empirical evidence of
the causal link between capital structure and
performance. The sample size was seventy -five
companies that are listed on the Nigerian Stock
Exchange for the period 2010 to 2014. Their
findings indicate a bi-directional relationship
between the short-term debt-to-equity ratio and
ROA as well as the proportion of equity to total
assets to ROA.
In Turkey, [31] studied the Impact of Capital
Structure on the Financial Performance of Firms
that are listed on the Istanbul Stock Exchange,
covering the period from 2005 to 2012 using
secondary data from the annual financial statements
of 136 companies and the results show that there is a
significant negative relationship between capital
structure and firm performance. Some scholars also
reported mixed outcomes from their studies. [28]
carried out a study to determine the effect of capital
structure on a Firm's performance in Nigeria using
data from 15 listed non-financial firms in Nigeria
covering the period from 1999 – 2018. The results
of the study show a significant negative relationship
between long-term debt to total assets, total debt to
total assets and the debt-to-equity ratio and ROE
which supports the pecking order theory while there
was a positive relationship between short-term debt
and ROE as well as ROA which supports the agency
theory. There was also a significant positive
relationship between long-term debt to total assets,
short-term debt to total assets, and the debt-to-equity
ratio and a negative relationship between Tobin's Q
and total debt.
In Kenya, [19] assessed the capital structure and
financial performance of eight companies listed
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under the manufacturing and allied sector in the
Nairobi Stock Exchange using data covering the
period from 2013 to 2018 and found that long-term
debts had a positive effect on financial performance
and most of the companies relied on and it was a
major source of financing of the firms that were
studied. Equity and retained earnings however had a
negative effect on financial performance. Similarly,
[32] carried out a study of the capital structure
decisions and financial viability of seven firms
quoted on the premium board segment of the
Nigeria Stock Exchange from 2010 to 2018. The
findings of the study show a mixed relationship
between capital structure decisions and the financial
viability of firms. the study.
In Pakistan, [33] studied the nexus between
capital structure, firm-specific factors,
macroeconomic factors and financial performance
in the textile sector on the Pakistan stock exchange
from 2008 to 2017 using data from 90 listed textile
companies. The findings of the study show a mixed
relationship between capital structure and financial
performance. [34] assessed the effect of capital
structure on the financial performance of all the
listed pharmaceutical companies in Vietnam's stock
market from 2015 to 2019. Using the ordinary least
square regression model, the findings of the study
show that financial leverage ratio, long-term asset
ratio and debt-to-asset ratio had a positive
relationship with performance while self-financing
had a negative effect on performance.
In Germany, [35] studied the relationship
between the financial performance of non-financial
firms and their capital structure and reversely used
data that covered a period of twenty-five years from
1993 to 2016. and the finding was that there is a
significant positive relationship between capital
structure and the financial performance of firms
while the stock price is negatively affected by
capital structure. A similar study was carried out by
[36], [37] on the impact of capital structure on the
profitability of ten publicly traded manufacturing
firms in Bangladesh from 2013 to 2017 The findings
are that debt ratio and equity ratio have a significant
positive on ROA but debt to equity ratio has a
significant negative impact on ROA. Equity ratio
has a significant positive impact while debt to equity
ratio has a negative impact on ROE. The debt and
equity ratio has a significant negative impact on
EPS. The sample size is considered small while the
period is considered too short and could affect the
credibility of its findings.
In Kenya, [38] reviewed the effect of Equity
financing options on the financial performance of
forty listed non-financial firms covering the period
from 2009 to 2015 Data was analyzed by using
panel regression econometric techniques. T The
study established that the common stock ratio has a
significant negative effect on ROA while retained
earnings ratio and total equity ratio have a
significant and positive effect on ROA. The ROE is
not significantly affected by the equity variables.
[39] studied Leverage and Firm Performance with a
focus on the role of firm size using panel data of
101 listed firms in Nigeria between 2003 and 2007.
The analysis of data was carried out by using the
threshold regression model and the results show that
leverage has a negative effect on the performance of
small firms and vanishes as the size exceeds its
estimated threshold level. Leverage has a positive
relationship with Tobin's Q and the strength of the
relationship depends on the size of the firm and is
mostly higher for small-sized firms indicating that
size also had a positive effect on Performance.
Another study with mixed outcomes was carried
out by [39] in their assessment of the impact of
capital structure on a firm's financial performance
using data from 739 very large and large companies
listed on the London Stock Exchange over the
period from 2006 to 2015. The finding of the study
is that there is a negative relationship between long-
term debt and ROE and ROA. Insignificant result
between short-term debt and ROE, and ROA.
Positive results between short-term and long-term
debt and Tobin's Q, while EPS had no relationship
with leverage. The study also established that size
and growth impact performance. The impact of
leverage on ROE and ROA is stronger than other
indicators.
Based on what has been thus far discussed, the
under-listed null hypotheses have been formulated
H01: Short-term debts do not affect the return
on assets of non-financial firms that are listed on the
Nigeria Stock Exchange (Nigerian Exchange
Group); H02: Short-term debts have no effect on the
Tobin's Q of non-financial firms that are listed on
the Nigeria Stock Exchange (Nigerian Exchange
Group); H03: Long-term debts have no effect on the
return on assets of non-financial firms that are listed
on the Nigeria Stock Exchange (Nigerian Exchange
Group); H04: Long- term debts have no effect on
the Tobin's Q of non-financial firms that are listed
on the Nigeria Stock Exchange (Nigerian Exchange
Group); H05: Total equity does not affect the return
on assets of non-financial firms that are listed on the
Nigeria Stock Exchange (Nigerian Exchange
Group); H06: Total Equity has no effect on the
Tobin's Q of non-financial firms that are listed on
the Nigeria Stock Exchange (Nigerian Exchange
Group). ceteris paribus.
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3 Methodology
Population: The population of the study comprised
all non-financial firms that are listed in 10 industry
sectors including Agriculture, Conglomerates,
Construction/Real Estate, Consumer Goods,
healthcare, ICT, Industrial goods, Natural
Resources, Oil and Gas and Services of the Nigerian
Stock Exchange. (Nigerian Exchange Group). The
study covered 129 non-financial firms that are listed
on the Nigerian Stock Exchange (Nigerian
Exchange Group) between 2010 and 2021.
Sample: The study used a census as it will cover all
the listed non-financial firms on the Nigeria Stock
Exchange (Nigerian Exchange Group).
Model Specification: Following the hypotheses that
were earlier formulated to assess the effect of capital
structure on financial performance the regression
models are designed in the light of studies carried
out by [2], [19], [35] with certain modifications. The
panel regression model that will be used for this
study will pool data from listed non-financial firms
over twelve (12) years.
Model Specification: We regress corporate financial
performance on the tailor-made CS measures on
three pillars of performance lagged by one year,
employing fixed effects regressions panel data as
suggested by the Hausman test. A fixed effects
model is typically used when the observed
quantities, in terms of explanatory variables, are
treated as non-random. The equations used are:
ROAi,t = β0 + β1STDRi,t–1 + β2LTDRi,t–1 +
β3TERi,t–1 + β4SIZi,t–1
+ ϵi,t
(1)
TQi,t = β0 + β1STDRi,t–1 + β2LTDRi,t–1 +
β3TERi,t–1 + β4SIZi,t–1 + ϵi,t
(2)
Accordingly, 𝒚𝒊𝒕 in eqn. (i) include return on Assets,
and Tobin’s Q respectively of the observed firm
units (ith), covering ten (10) sectors throughout t =
1...10 expressed above.
Where: Return on assets (ROA) is measured as
Earnings after interest and taxes divided by the book
value of total assets; Tobin's Q is measured as the
market value of equity plus total debt dived by total
assets; Short-term debt ratio (STDR) is measured as
the ratio of short-term debt to total assets; Long
term debt ratio (LDTR) is the measure of long-term
debt to total assets; Total Equity ratio (TER) is the
measure of total equity divided by total assets;
Industry (IND) and Firm size (SIZ) which is the
natural log of total sales is are the control variables.
Method of data analysis: The data were analyzed
with the use of panel multiple regression analysis to
assess the effect of capital structure on the financial
performance of the firms because the study will
combine both time series and cross-sectional data.
Panel data analysis is a statistical method that is
used to analyze multi-dimensional data that covers a
period of cross-sectional units that would enable the
study of the research variables and establish the
relationship between the independent and the
dependent variables.
4 Data Analysis and Interpretation
Descriptive Statistics: The descriptive statistics of
the selected variables of capital structure and
financial performance are presented in this section.
These statistics are used to describe the main
features of the data set, which include measures of
central tendency (mean); measures of variability
(standard deviation); the minimum and maximum
values of variables, providing the summary of
samples and observations which forms the basis for
the description of the data set. This is a precondition
for fitting the panel regression model.
The data in Table 1 (Appendix section) shows
the descriptive statistics of the variables. The
financial performance of firms proxied with return
on assets (ROA) has a mean of 0.03327 which
suggests that the average return on assets of the
firms at 3.3%, while the mean of Tobin's Q, the
market-based dependent variable was 0.9983 which
is approximately 1%, showing that the average
financial performance of Nigerian firms is low.
Also, the maximum and minimum Tobin's Q stood
at 12.508 and -0.018 and for ROA, it is 6.302
(approximately 6%) and -4.256 (approximately -
4%) This is an indication that whereas some of the
listed firms made a profit others made losses. For
Tobin's Q, the standard deviation was 1.221 which
is close to the mean and thus it is said to be well
dispersed. Similarly, for ROA, the standard
deviation was at the value of 0.404 which is an
indication that the variables are fairly
dispersed/spread without outliers. The results also
reflect that there is a significant disparity between
the accounting-based performance indicator and the
market-based performance indicators. The mean for
short-term debts is 0.554 as against the mean of
0.215 for long-term debts indicating that on average
the firms had more short-term debts than long-term
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debts. The maximum short-term debt is 34.24 while
the maximum long-term debt is 11.56. For the total
equity, the mean is 0.296 while the maximum equity
is 7.426 against the minimum which is a negative of
35.69. The standard deviation is N294 billion shows
the disparity between the minimum and maximum
equity held by the firms. This implies that the
average and standard deviation of the variables for
capital structure also shows a fair spread and are
devoid of outliers and thus meeting one of the panel
regression fundamental assumptions. Firm size has a
mean of 16.198 and a standard deviation of 2.024.
The industry had a mean of 6.23 and a standard
deviation of 2.833.
Pre-model Diagnostic Test- Normality Test,
Correlation and Unit Root Test
The pre-model diagnostic test was used to test for
the probabilities of the presence of conditions and
biases that may undermine the accuracy of
outcomes. The tests were carried out to ensure that
the data suits the basic assumptions of the panel
model as follows:
Normality Test: The result of the Doornik-Hansen
multivariate normality test for all the variables
returned a p-value less than 0.05 (5%) level of
significance. The result implies that the variables are
not normally distributed. As such, the variable
natural logarithm transformation or difference is
used to correct for the non-normality seen in the
series before modelling.
Table 2 (Appendix section) presents the
correlation coefficient for the variables on the effect
of the complete set of variables of Capital Structure
and the financial performance of listed non-financial
firms in Nigeria as considered in this study.
Correlation values ranged from -1 to +1; where
0.75-0.99 signifies a "very strong" relationship
between the intersecting variables, 0.5-0.74 implies
a "strong" relationship within the intersecting
variables and 0.35-0.49 implies a "weak"
relationship among variables. As observed, there
exists a significant negative relationship between
STDR and TER; there is a positive relationship
between ROA and Tobin's Q, ROA and STDR, and
ROA and LTDR, but a negative weak relationship is
observed between ROA and TER; also, a negative
relationship is observed between LTDR and TER,
LTDR and SIZ.
Table 3. Variance Inflation Factor for
Multicollinearity Test
Source: Researcher’s computation, Stata v 15 2022
From the test of multicollinearity shown in
Table 3 above, all the variable has a VIF value that
does not exceed the minimum condition (<10) for
no collinearity stated by the Variance Inflation
Factor (VIF). As such, we can apply Panel Data
Regression (generalized least square GLS) model
with the belief that another fundamental assumption
for modelling is met and hence the estimates will be
reliable and robust. Furthermore, fitting the GLS
model (fixed and random effect model) will further
suggest the most robust model for testing the
hypotheses of the study with the help of the
Hausman test and thus minimizing the effect of any
violation of the classical model assumptions.
The unit root test was carried out as a
precondition for the analysis of panel data variables
to ensure that the variables are stationary. The
outcome of our unit root tests using the Fisher-type
unit-root test for panel data shows that all variables
are stationary as seen in the unit root test table
above. Since all the variables have no effect of unit
root (stationary), the variables may not be required
to undergo any form of transformation to correct the
effect of any unit root before fitting the panel
regression for optimal results.
Table 4. Unit-Root Test
Fisher-type unit-root test
Based on augmented Dickey-Fuller tests
Ho: All panels contain unit roots
Ha: At least one panel is stationary
Variable
Test
p-value
ROA
Inverse chi-squared (224) P
0.000
TQ
Inverse chi-squared (224) P
0.000
STDR
Inverse chi-squared (224) P
0.000
LTDR
Inverse chi-squared (224) P
0.000
TER
Inverse chi-squared (224) P
0.000
SIZ
Inverse chi-squared (224) P
0.000
Source: Stata v 15 Output 2022
Table 4 shows the results of a Fisher-type unit-
root test conducted on six different variables: ROA,
TQ, STDR, LTDR, TER, and SIZ. The null
Mean VIF 3.76
SIZ 1.07 0.934178
LTDR 1.28 0.780254
STDR 6.16 0.162231
TER 6.52 0.153313
Variable VIF 1/VIF
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hypothesis (Ho) of the test is that all panels (or
groups) of the data contain unit roots, which means
that the data is non-stationary and has a trend or
momentum that persists over time. The alternative
hypothesis (Ha) is that at least one panel is
stationary, meaning that the data is stationary and
does not have a persistent trend over time.
The statistic column in the table shows the value
of the test statistic for each variable, while the p-
value column shows the corresponding probability
of obtaining a test statistic as extreme as the one
observed, assuming the null hypothesis is true. In
this case, all p-values are less than 0.05, which
suggests strong evidence against the null hypothesis
and in favour of the alternative hypothesis.
Therefore, the results of the unit-root test suggest
that at least one panel of the data is stationary,
meaning that there is no persistent trend over time
for at least one of the variables. This information is
important for time-series analysis and modelling, as
non-stationary data can lead to unreliable and biased
results.
Discussion of Findings
The results from sectorial static panel regression
analysis of the effect of capital structure on the
performance of listed non-financial firms in Nigeria
presented in table 5 are discussed below:
Sectorial Analysis for the effect of Capital Structure
on ROA: The results show that in the agriculture
sector, all the capital structure variables (short-term
debts, long-term debts and total equity) have a
positive effect on return on assets. However, only
the total equity had a significant positive effect on
the performance of the listed non-financial firms
while others were insignificant; In the
conglomerate's sector, short-term debts and long-
term debts have a negative and insignificant effect
on the performance of the firms. Total equity has a
positive but insignificant effect on the return on
assets. This implies that the capital structure
variables do not significantly affect the return on
assets of firms in the conglomerate's sector; In the
construction and real estate sector, all the proxies
for the capital structure (short-term debts, long-term
debts and total equity) have a positive effect on the
return on assets, however, they have no significance
since none of the variables parameter estimate have
a p-value less than 0.05 level of significance; For
the consumer goods sector, although all capital
structure measure shows a positive effect on the
return on asset, only the short-term debts and total
equity have a significant and positive effect on the
return on assets; For the healthcare sector, the short-
term debts and long-term debts have negative and
insignificant effect on return on assets, while total
equity has a positive and significant effect on return
on assets of the firms; The results also show that
short-term debts, long-term debts and total equity of
firms in the industrial goods sector had a positive
and significant effect on their return on assets;
Similarly, long-term debts and total equity had
positive and significant effect on the return on assets
of the firms in the ICT sector, while short-term
debts had positive but insignificant effect on the
return on assets; In the natural resources sectors,
short-term debts, long-term debts and total equity
had insignificant negative effect on the return on
assets since the p-values were greater than 0.05
(5%) level of significance; Also, in the oil and gas
sector, total equity had a positive and significant on
return on assets, while the short-term debts and
long-term debts returned a negative and
insignificant effect on return on assets; Similarly, in
the services sector, the total equity has a positive
and significant effect on the return on assets. Short-
term debts and long-term debts have a negative and
insignificant effect on the return on assets.
Sectorial Analysis for the effect of Capital
Structure on Tobin's Q: In the agricultural sector,
short-term debts and long-term debts did not affect
Tobin's Q, however, total equity has a positive and
significant effect on the firm's performance in the
sector; Also, in the conglomerate sector short-term
debts, long-term debts and total equity have no
significant effect on Tobin’s Q since all the
variables estimate returns coefficient p-values of
greater than the 0.05(5%) level of significance; In
the construction/real estate sector, short-term debts
has a positive and significant effect on Tobin’s Q,
while the long-term debts and total equity had a
positive but insignificant effect on the Tobin’s Q.
Also, in the consumer goods sector, short-term
debts, long-term debts and total equity have a
positive and insignificant effect on Tobin’s Q; In the
healthcare sector, the short-term debts and total
equity have a significant and positive effect on the
performance of the firms in the sector, while the
long-term debt was seen to have no significant
positive effect on the Tobin’s Q. For the industrial
goods sector short-term debts, long-term debts and
total equity had a negative and significant impact on
Tobin’s Q in explaining their effect on the firms'
performance within the sector. These findings
suggest that there is a significant negative and
generalizable effect of capital structure on the
performance of the firms.
Only the capital structure variable (short-term
debts and total equity) returns a positive and
significant relationship to the firm's performance in
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.132
Rita I. Sike, Umar A. Ibrahim, Faiza Maitala
E-ISSN: 2224-2899
1504
Volume 20, 2023
the ICT sector. While long-term debt is observed to
have a negative and not significant effect on the
firm's performance in the sector. As such, we can
conclusively say that capital structure has a
significant effect on the performance of the listed
firms in the ICT sector; However, short-term debts,
long-term debts and total equity had a positive and
insignificant effect on Tobin's Q of firms in the
natural resources sector, while short-term debts and
long-term debts had a negative and insignificant
effect on Tobin's Q of firms in the oil and gas sector
but the total equity had a positive and significant
effect on Tobin's Q; Similarly, in the services sector,
total equity also had a positive and significant effect
on the Tobin's Q, while; short-term debts had a
negative and significant effect on Tobin's Q and
long-term debts has a negative and insignificant
effect on Tobin’s Q.
5 Conclusion
The study established answers to the research
questions and thus concluded as follows:
There is a significant relationship between
capital structure and financial performance which is
largely dependent on the industry and the proxies of
the study variables that are considered. Overall,
short-term debts have a significant positive effect on
the return on assets of non-financial firms that are
listed on the Nigeria Stock Exchange (Nigerian
Exchange Group). The result supports the findings
of [30], [34],
Table 5. Sectorial Panel Regression Analysis of the Effect of Capital Structure on the Financial Performance of
Listed Non-Financial Firms in Nigeria
Dependent
Variable
Model selected
Coef. (p-value) of the independent variables (Capital Structure) and Control Firm Size
Number
of obs
Number
of
groups
Wald
chi2(4)
Prob.
STDR
LTDR
TER
SIZ
_cons
ROA
Fixed-effects
0.076(0.262)
0.097(0.31)
0.148(0.003)
-0.041(0.017)
0.575(0.045)
56
5
8.35
0.000
Random-effects
-0.249(0.064)
-0.003(0.983)
0.176(0.164)
0.035(0.123)
-0.607(0.159)
58
6
82.94
0.000
Random-effects
0.002(0.998)
0.091(0.269)
0.131(0.155)
0.013(0.459)
-0.284(0.353)
52
7
3.78
0.436
Fixed-effects
1.149(0.000)
0.018(0.766)
0.956(0.000)
-0.046(0.348)
-0.025(0.976)
238
27
14.93
0.000
Random-effects
-0.02(0.225)
-0.083(0.357)
0.085(0.000)
0.068(0.000)
-1.069(0)
83
9
73.46
0.000
Random-effects
0.516(0.000)
0.495(0.001)
0.956(0.000)
-0.002(0.842)
-0.619(0)
152
22
162.8
0.000
Random-effects
0.125(0.133)
0.254(0.030)
0.355(0.000)
0.008(0.474)
-0.38(0.081)
80
11
45.93
0.000
Random-effects
-0.036(0.897)
-0.098(0.723)
0.185(0.522)
-0.038(0.007)
0.501(0.08)
43
4
77.77
0.000
Random-effects
-0.024(0.791)
-0.24(0.401)
0.063(0.005)
0.01(0.353)
-0.136(0.515)
110
13
15.92
0.003
Fixed-effects
-0.013(0.569)
-0.066(0.262)
0.147(0.000)
-0.003(0.895)
-0.012(0.975)
249
25
9.23
0.000
TQ
Random-effects
0.838(0.264)
-3.232(0)
1.138(0.021)
-0.299(0)
5.514(0)
56
5
49.7
0.000
Random-effects
-0.682(0.572)
-1.389(0.308)
0.058(0.96)
-0.316(0.153)
6.646(0.115)
58
6
8.61
0.072
Random-effects
2.421(0.000)
1.171(0.112)
1.253(0.088)
-0.02(0.776)
-0.654(0.611)
52
7
17.18
0.002
Random-effects
0.151(0.618)
0.037(0.707)
0.196(0.488)
-0.224(0)
4.767(0)
238
27
16.03
0.003
Random-effects
1.038(0.000)
0.127(0.753)
0.447(0.000)
-0.231(0.018)
3.746(0.014)
83
9
649.04
0.000
Random-effects
-1.026(0.000)
-0.736(0.011)
-0.41(0.040)
-0.155(0)
3.991(0)
152
22
90.59
0.000
Random-effects
1.288(0.001)
-0.328(0.563)
0.677(0.078)
0.022(0.729)
-0.447(0.705)
80
11
15.31
0.004
Random-effects
1.893(0.326)
3.43(0.078)
3.203(0.113)
-0.532(0.000)
5.774(0.004)
43
4
57.59
0.000
Random-effects
-2.213(0.011)
-0.298(0.634)
0.263(0.647)
-0.712(0.000)
15.37(0)
110
13
39.16
0.000
Random-effects
-0.432(0.000)
-0.012(0.912)
0.396(0.000)
-0.292(0.000)
5.289(0)
249
25
191.83
0.000
Source: Researcher’s compilation, 2022
[36], [37]. The findings show that the higher the
leverage the higher the return on assets; Short-term
debts have a significant negative effect on Tobin's Q
of non-financial firms that are listed on the Nigeria
Stock Exchange (Nigerian Exchange Group). This
finding agrees with the findings of the studies done
by [9]–[12], [40], [30], [34], [36], [37]; Long-term
debts had a significant negative effect on the return
on assets of non-financial firms that are listed on the
Nigeria Stock Exchange (Nigerian Exchange
Group). This result is consistent with the studies
conducted by [15], [17], [25], [41], [42]; Long-term
debts had an insignificant negative effect on Tobin's
Q of non-financial firms that are listed on the
Nigeria Stock Exchange (Nigerian Exchange
Group). The finding is similar to the studies of [3],
[4], [5], [7], [8]; Total equity had an insignificant
negative effect on the return on assets of non-
financial firms that are listed on the Nigeria Stock
Exchange (Nigerian Exchange Group). The results
contradict the findings of [6] that established a
positive relationship between total equity and return
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.132
Rita I. Sike, Umar A. Ibrahim, Faiza Maitala
E-ISSN: 2224-2899
1505
Volume 20, 2023
on assets; Total equity had a significant positive
effect on Tobin’s Q of non-financial firms that are
listed on the Nigeria Stock Exchange (Nigerian
Exchange Group). The result supports the findings
of [39].
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DOI: 10.37394/23207.2023.20.132
Rita I. Sike, Umar A. Ibrahim, Faiza Maitala
E-ISSN: 2224-2899
1507
Volume 20, 2023
Appendix
Table 1. Summary of Descriptive Statistics
Source: Author’s computation, 2022
Table 2. Correlation Matrix Table
Source: Author's compilation from STATA v15 output, 2022
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed in the present
research, at all stages from the formulation of the
problem to the final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflict of interest to declare
that is relevant to the content of this article.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
_US
within 0 6.230701 6.230701 T-bar = 8.73643
between 2.710159 1 10 n = 129
IND overall 6.230701 2.833763 1 10 N = 1127
within .6022294 11.61185 21.11178 T-bar = 8.68992
between 2.018883 11.35776 21.62097 n = 129
SIZ overall 16.19834 2.024145 10.95583 22.06286 N = 1121
within .7896538 -20.07935 6.906365 T-bar = 8.68992
between 1.530163 -15.31926 2.475851 n = 129
TER overall .2955969 1.786602 -35.69421 7.427399 N = 1121
within .3582128 -.9155825 10.62591 T-bar = 8.68992
between .3207435 0 2.359295 n = 129
LTDR overall .215368 .4567991 0 11.55886 N = 1121
within .7744259 -5.445446 20.74817 T-bar = 8.68992
between 1.293576 0 14.04865 n = 129
STDR overall .5540765 1.589097 0 34.24274 N = 1121
within .8487063 -2.86942 9.211086 T-bar = 8.68992
between 1.002656 .0103072 7.224782 n = 129
TQ overall .9983918 1.221824 -.0180832 12.50878 N = 1121
within .3508127 -2.386116 5.319565 T-bar = 8.68992
between .4059104 -4.256455 1.150569 n = 129
ROA overall .0332738 .4047148 -4.256455 6.302756 N = 1121
Variable Mean Std. Dev. Min Max Observations
SIZ 0.0031 -0.0933 -0.2440 -0.0270 0.2014 1.0000
TER -0.2907 0.0427 -0.9126 -0.4578 1.0000
LTDR 0.0239 -0.0433 0.3832 1.0000
STDR 0.3330 0.0726 1.0000
TQ 0.1363 1.0000
ROA 1.0000
ROA TQ STDR LTDR TER SIZ
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.132
Rita I. Sike, Umar A. Ibrahim, Faiza Maitala
E-ISSN: 2224-2899
1508
Volume 20, 2023