Effect of Prudential Regulation on the Financial Performance of Quoted
Deposit Money Banks in Nigeria
1ISAIAH ADEMOLA ADELEKE, 2UMAR ABBAS IBRAHIM
Department of Business Administration, Faculty of Management Science
Nile University of Nigeria
Cadastral Zone C-OO, Research & Institution Area, Airport Rd, Jabi, Abuja
NIGERIA
Abstract: - International and national financial authorities are constantly issuing new prudential policies, rules,
and guidelines to ensure a safe and sound financial system. How well the deposit money banks (DMBs) have
kept to these prudential thresholds is expected to reflect on their financial performance. However, there has
been no consensus by previous studies on the effect of prudential regulation on financial performance of
deposit money banks. As such, this study seeks to assess the effect of prudential regulation on the financial
performance of deposit money banks in Nigeria from 2011 to 2020. The prudential regulation is proxied by -
capital adequacy, liquidity, leverage, and asset quality as the independent variables while the financial
performance is proxied by earnings per share (EPS) as dependent variable. The data was sourced from the
annual reports of the thirteen (13) quoted deposit money banks and analysed using descriptive statistics and
Panel Data Regression to determine the relationships between the variables. As a form of diagnostics test,
Jarque-Bera test was engaged for checking for normality, Pearson Correlation was employed to evaluate the
degree of relationship among variables and extent of linearity, Unit root test was used to test for stationarity and
the Hausman test to determine whether to use fixed or random effect panel least square regression of which
fixed effect model was favoured. Data were estimated with STATA 15. The significance level was set at 0.05.
Findings from the study reflect that capital adequacy has a positive coefficient of 0.7166 and a non-significance
level of 0.5250 on financial performance using the EPS. Liquidity has a positive coefficient of 0.1804 and non-
significance level of 0.8720 on the EPS. Asset quality has a co-efficient of -0.2843 and non-significance level
0.8850 on the EPS. Leverage has a coefficient of -1.5006 and a non-statistical significance level of 0.3800 on
the EPS. The study concludes that an increase in capital does not necessarily translate to higher EPS, higher
liquidity lessens banks’ liquidity risk, asset quality in form of non-performing loans reduces the bank’s capacity
to create further loans, hence less earnings for the bank and leverage negatively influences financial
performance. It is also discovered that control variables - age and size of banks - are positive determining
factors for financial performance of banks. The study recommends that the CBN as the Regulator needs to
strengthen capital adequacy by moving it to thresholds that will be impactful enough on the financial
performance, get the banks to improve on asset quality by bringing non-performing loans to the regulatory
limit, be discretional in the use of regulatory forbearance and interventions to bail out the banks to prevent
reckless lending conduct. Lastly, banks are required to pay attention to the capital mix (leverage) to reap its
benefits and manage the associated risk.
Key-Words: - Earnings Per Share, Regulatory Capital, Liquidity, Risk Asset Quality & Leverage
Received: September 8, 2021. Revised: May 13, 2022. Accepted: June 5, 2022. Published: July 22, 2022.
1 Introduction
The global financial system was hit by an
unprecedented crisis in the 1930s which led to a
reduction by 40%, in the number of commercial
banks in the United States of America within three
(3) years [1]–[3]. This was after the Showa financial
crisis of 1927 in Japan that resulted in poor financial
performance and mass failure of banks across the
Empire of Japan [4], [5]. History would not also
forget the waves of similar systemic failures such as
the Norwegian, Swedish, Finnish, Peruvian,
Venezuelan and Asian banking crises in the 1990s
[2], [6]–[8].
The 2008/2009 global financial crisis caused by
excessive risk- taking by the banks and the United
States’ housing bubble burst which caused a
nosedive in the values of derivatives and other
securities tied to the United States’ real estate [9],
[10] and pockets of related incidents across the
globe have taken a place in banking history [11],
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[12]. Nations around the world have experienced
well over 151 systemic banking crises from 1970 to
2017 [11]–[14]. This has put the banks in the centre
of intense scrutiny, as they were held responsible for
creating or fueling the financial crisis [7], [15]. It
also necessitated the search for causes of the
systemic failure and more effective ways to ensure a
sound and stable banking system that could avert
future banking crises [16]. [17], [18] opined that one
of the major causes of the global financial crisis in
2008/2009 was utmost disregard for prudential
regulation and as such, called for the strengthening
of prudential regulation across the globe. A school
of thought advocated that the global financial
system must adopt a systemic perspective to
prevention and early identification of weaknesses in
the financial system often heralded by negative
financial performance persistent decline in return
on assets (ROA), earnings per share (EPS), and
other performance measurements - by using a
strengthened and comprehensive prudential
regulation [19]. The Nigerian financial system that
was already fragile due to poor risk management,
the burden of non-performing loans, and poor
corporate governance slid into crisis due to the
global financial meltdown of 2008 [20]. The
Nigerian banking system had witnessed the bailout
extended to eight (8) deposit money banks (DMBs),
sacking of the chief executives and boards of those
banks and nationalisation of three (3) banks, into
bridge banks by the Central Bank of Nigeria (CBN)
and Nigerian Deposit Insurance Corporation
(NDIC) in 2009 due to financial distress the banks
suffered as a result of huge non-performing loans
[20], [21]. It became pertinent to tighten its financial
regulation for a safe and sound financial system and
to protect depositors’ funds. However, this needs to
be done without discouraging competition,
openness, and innovation [19]. As a response to this,
effective July 1, 2010, the CBN released prudential
regulation through the Prudential Guidelines (PG)
for Deposit Money Banks {Central Bank of Nigeria
[22]. As of December 31, 2021, Nigeria had thirty-
one (31) deposit money banks of which thirteen (13)
were quoted on the Nigerian Exchange Group
(NGX) [22]. Ten years’ post-implementation of the
new prudential guidelines, some banks have been
meeting the prudential thresholds while some are
still falling short in meeting capital adequacy, non-
performing loan (NPL), and other ratios which are
all integral parts of the prudential regulation for
Nigerian banks [23]. The result of these vagaries is
often mirrored in the financial performance of the
banks through the impact it has on profitability [1],
[24].
2 Problem Formulation
The study is geared towards how the application of
prudential regulatory rules can trigger a safe and
sound banking system that will be reflective in the
financial performance of the quoted deposit money
banks.
The main objective of the study is to find out the
effect of prudential regulations (guidelines) on
financial performance of quoted deposit money
banks in the Nigerian financial sector. Thus, the
specific objective is to examine the influence of
capital adequacy; liquidity; asset quality; risk asset
quality; leverage; on earning per share in Nigerian
quoted deposit money banks.
2.1 Literature Review
2.1.1 Operational Conceptual Framework
The selected variables are conceptualised in figure 1
as shown below:
Fig. 1: Operational Conceptual Framework
Source: Researcher 2022 adaption [1], [3], [4],
[24], [25]
2.1.2 Empirical Review
The global financial crisis of 2008/2009 gave a
renewed awakening to the importance of strict
prudential regulations on banking practice across the
globe. As a remedial and proactive measure, the
Bank of International Settlements (BIS) released
more robust, risk-based and forward-looking
prudential guidelines for the global banking practice
in 2009, which was adopted and domesticated by
each country to control risks, hold adequate capital,
protect depositors’ funds and ensure stability of the
financial system [26]. However, there were still
cases of negative financial performances that
ultimately led to bank failure. For instance, in 2019,
the USA witnessed failure of four 4 (banks) - the
Enloe state bank, Louisa community bank, Resolute
bank and City national bank of New Jersey, and in
2020, 4 (four) other banks - Ericson state bank, the
First state bank, first city bank of Florida and
Almena state bank went under [27]. In November
13, 2018, court order was issued for final liquidation
of VBS mutual bank of South Africa; a bank that
Figure 2.1 Operational Conceptual Framework
Control Variable
Age
Bank Size
Independent Variables
Prudential Regulation
Regulatory Capital
Liquidity
Asset Quality
Leverage
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failed due to severe liquidity problem [28]. In
Nigeria, the annual reports of Unity bank plc
showed that the bank made losses in 4 years (2013,
2016, 2017, 2018) out of 10 years post introduction
of revised prudential regulation. Can this be an
indication that prudential regulation aimed at
strengthening the stability and soundness of the
banking sector has not been effective?
There are several empirical studies conducted
internationally on: the USA, China, Canada, Spain,
Vietnam, Iran, Saudi, Nepal, Barbados, Jamaica,
Trinidad and Tobago, Jordan, India, Indonesia,
Pakistan, Oman, Ethiopia, Bangladesh, Rwanda,
Kenya, Morocco, Kenya and South Africa and
locally (Nigeria) in relation to prudential regulation
and its effect on banks’ financial performance.
Some of the studies which examined the individual
components of prudential regulation and financial
performance are [1], [14]–[17], [29], [30], [30]–
[42], [42] and found significant effect of the
prudential regulations on the various banks’
performance.
However, some other studies looked at combination
of components and presented diverse results. Such
as the work of [38] established a significant
relationship between liquidity and banks’ financial
performance on the ground that availability of
liquidity is a risk-taking incentive which if well
managed, results to better bank performance and if
poorly managed, poor bank performance. studies by
[18] who found out that banks that hold higher
fraction of liquid assets in cash and government
securities tend to have a lower net interest margin
than banks with less liquid assets in his works to
examine the impact of the liquidity management on
profitability in the Jordanian commercial banks.
[32] who also found that there is an existence of
causality and long-run relationship between
liquidity management measures and bank
performances in Nigeria was established. Similarly,
[42] drew the same conclusion of positive
relationship between liquidity and profitability in
the study on banks in Pakistan. Still on banks
operating in Pakistan, [41] extended the study
testing liquidity impact on EPS, ROA, ROI, ROE
and net profit margin averred that ROA and ROE
have positive relationship with liquidity but EPS
and ROI have adverse relationship with liquidity.
Lastly, [18] investigated the relationship between
bank’s loan creation as a measure of liquidity and
financial performance for two banks in Jordan and
the result of the study indicated that there was a
positive and non-significant impact of LDR on
ROA.
In addition, a number of studies have been carried
out on the effect of prudential regulations on
performance of banks across the globe with respect
to China (Jiang, 2014), South America (Williams,
2015), United States of America (Saunders and
Cornett, 2011), European Union (Marin et al.,
2019), Middle East and North Africa (MENA)
countries [1], [3], [4], [6], [13], [14], [24], [25],
[43]–[47]. However, the regulatory and financial
performance indicators adopted as independent and
dependent variables were grossly under-explored.
Indicators such as capital adequacy, liquidity, asset
quality and leverage have witnessed some coverage
on stand-alone basis in previous studies but no much
studies have been done to assess the combined
effect of prudential indicators (capital adequacy,
liquidity, risk asset quality and leverage) on the
banks’ performance using both accounting-based
and market based measurements, factoring in
control variables and having full coverage of 10
year period of introducing revised prudential
regulations in Nigeria to aid investment decisions in
the Nigerian banking sector.
Furthermore, most previous studies in the research
area have produced limited evidences, mixed and
inconclusive results. For instance, while [18], [44],
[45], [48] agreed to some form of causal
relationships between prudential regulation and
bank’s performance, Researchers like [49]–[51]
disagreed. This necessitates further research into the
direction of causality. Therefore, this study sought
to reduce the above-mentioned gaps by investigating
the individual and collective effects of a set of four
(4) prudential indicators on the financial
performance of quoted deposit money banks in
Nigeria in the last 10 years that the new prudential
regulation was introduced so as to eliminate the
incidence of limited evidences, mixed and
inconclusive result and ascertain a clear direction of
causality.
2.1.3 Theoretical Framework
The public interest theory is found to be most
suitable in anchoring this study. It offers the suitable
foundation and framework that best support the
assessment of prudential regulation on financial
performance of DMBs in Nigeria. Public Interest
theory assumes that the markets in an economy are
very fragile and prone to inefficiency that will
benefit individuals instead of the society at large and
that governments can correct these market failures
through regulation (Shleifer, 2005). Banking
business is characterized by high risk by virtue of
using depositors’ funds for business, limitless
yearning for profits, fierce competition, and insiders
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abuses in some cases. All of these are around the
depositors’ funds [21]. The safety of depositors’
funds should not be compromised. As such, there
has to be a regulatory body that will set rules and
moderate the activities of the banks in the public
interest; in this case, to protect the depositors and
ensure the financial system is safe and sound for
economy to thrive.
2.1.4 Methodology
The study was a panel (longitudinal and time series)
survey of quoted banks on the Nigerian Exchange
Group (NGX Group) and the descriptive research
methodology was employed. The variables
examined consisted of Earnings Per Share (EPS) as
proxies for bank’s financial performance which is
the dependent variable and Capital adequacy,
Liquidity, Risk Asset Quality and Leverage which
represent the independent variables. Emphasis was
on prudential guidelines that have taken place in
Nigeria.
The target population of the study comprised of all
the thirteen (13) licensed deposit money banks that
are listed on the Nigeria Exchange Group (NGX).
All the quoted banks are up to 10 years on the
Nigerian Exchange Group (NXG).
For this study, the panel cross-sectional and time-
series secondary data collected were analyzed using
the Static Panel Regression estimation procedure
suggested by [29], [36], [39], [52]. The study’s
model specification is adopted from the study [39],
who also investigated the effect of prudential
regulations (guidelines) on financial performance.
Therefore, the model specification for the test of the
posited hypotheses is stated thus:
For this study, the model is specified as:
𝐸𝑃𝑆𝑖𝑡 = 𝑋0+ 𝑋1𝑅𝐶𝐴𝑖𝑡 + 𝑋2𝐿𝑄𝐷𝑖𝑡 + 𝑋3𝐴𝑄𝑌
𝑖𝑡 +
𝑋4𝐿𝐸𝑉
𝑖𝑡 + 𝑋5𝐴𝐺𝐸𝑖𝑡 + 𝑋6𝐵𝑆𝑍𝑖𝑡 + 𝜇𝑖𝑡 … (3.1)
Where:
EPSit = Earnings per Share (as proxy for financial
performance) for bank (i) and at time (t)
X0 = Constant; X1, X2, X3, X4, X5 and X6 =
Coefficients; RCA=Regulatory Capital; LQD =
Liquidity; AQY = Risk Asset Quality & LEV =
Leverage; μ = Error term.
3 Problem Solution
3.1 Descriptive Statistics
This sub-section presents the descriptive statistics of
the bank specific prudential indicators that
determine the financial performance of deposit
money banks in Nigeria. It shows their respective
mean, median, maximum/minimum value, standard
deviation and the Jarque-Bera normality test which
is a goodness-of-fit test to ascertain if the sample
data have the skewness and kurtosis that show
normal distribution. This is a precondition for fitting
the panel regression model. Table 4.1 below shows
the descriptive statistics of all the variables in the
study.
Table 1. Summary Statistics
EPS
RCA
LIQ
AQY
LEV
AGE
BSZ
Mean
144.432
12.542
40.324
10.389
10.853
47.192
2089.785
Median
133.312
18.255
37.22
5.545
13.13
30
1311
Maximum
458.9
30
87.32
98
64.93
116
8680
Minimum
-425.231
-213.6
17.06
1.2
-200.7
5
135
Jarque-Bera
267.415
6596.92
91.638
2035.718
7631.615
20.833
70.439
Probability
0.000
0.000
0.000
0.000
0.000
0.000
0.000
Observations
130
130
130
130
130
130
130
Source: Author's Computation, 2021
Table 4.1 examines the descriptive statistics of
the profile of variables. It is noted that the financial
performance of banks proxied with earnings per
share (EPS) was at the mean of 144k and the
maximum and minimum EPS stood at 458.9k and -
425.2k. This is an indication that some of the
considered banks made a profit while some made
losses. For EPS, the standard deviation was at the
value of 104.721 and the Jarque-Bera result was at
the significant value of 267.415 (P-value of 0.000)
which is less than 5% critical value. This shows that
EPS is significant in predicting financial
performance. As indicated in the Table, the average
capital adequacy ratio of deposit money banks in
Nigeria was 12.54%. The figure is above the 10%
statutory requirement in the CBN Prudential
Regulation Guideline for the DMBs of July 1, 2010
(CBN, 2010). However, currently, the minimum
requirement of 10% is set for banks with National
and Regional licence while 15% is set for banks
with International banking licence and 16% for
banks with an international banking licence who
also qualify as systemically important banks (SIBs).
The “mean” in the table is the average of 10 years
period (2011 to 2020). This implies that the
Nigerian DMBs hold more capital than required. It
is worthwhile to mention that as much as adequate
capital helps in having an appetite for more risk-
taking and loss absorption, it does not automatically
translate to high financial performance because
some banks may prefer less risky investments,
which result in a lower profit or conversely, have
huge non-performing loans portfolio and can result
to high loan loss provisions; hence, lower profit.
Liquidity stood at an average of 40.32% as against
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the CBN’s set minimum limit of 30%; a clear
indication that the Nigerian DMBs are liquid on the
average. The average non-performing loan which
reflects the asset quality of the DMBs in the stated
period stood at 10.39%. This is above the statutory
maximum limit of 5% (CBN, 2010). It is a clear
reflection of high exposure to credit risk and the
relationship of the high non-performing loan
portfolio is expected to be negative with profit.
Leverage stood at 10.85%; an average that falls
within the regulatory maximum allowable limit of
25%. This reflects a good capital mix among
Nigerian DMBs. More importantly, regarding the
test for normality, as observed in table 4.1, the test
for all the variables returned a p-value less than 0.05
(5%) level of significance, thus, implying that the
variables are normally distributed. As such, the
variable natural logarithm transformation is used to
correct for the non-normality seen in the series
before modelling in sub-section 3.4.
3.2 Unit Root Test
This a test for stationarity in a time series data.
Stationarity is present in a time series if a shift in
time does not cause a change in the shape of the
distribution and on the other hand, there is no
stationarity if a shift in time causes a change in
shape of the distribution. Unit root is a cause for
non-stationarity. The test result and interpretation
are contained in Unit-Root Table 2.
Table 2. Unit-Root
Ho: Panels contain unit roots
Number of panels
13
Ha: Panels are stationary
Number of periods
10
Xtunitroot
Statistic
Statistic
p-value
Decision
EPS
Unadjusted t
-3.5718
0.946
Not Stationary
Adjusted t*
1.6058
RCA
Unadjusted t
-11.1612
0.000
Stationary
Adjusted t*
-9.7083
LIQ
Unadjusted t
-8.2131
0.000
Stationary
Adjusted t*
-3.6871
AQY
Unadjusted t
-8.9427
0.000
Stationary
Adjusted t*
-3.7669
LEV
Unadjusted t
-7.8342
0.000
Stationary
Adjusted t*
-6.1301
*Not Stationary, i.e (p-value < 0.05)
Variable Key:
EPS: Earnings per share
LQD: Liquidity
REC: Regulatory Capital
AQY: Risk Asset Quality
LQD: Liquidity
LEV: Leverage
Source: Stata 15 Output
As a precondition for the analysis of panel data
variables, the need to ensure that the variables are
stationary requires unit root tests of each of the
variables in the model. The outcome of our unit root
tests using the Levin-Lin-Chu unit-root test for
panel data shows that only EPS is not stationary; all
other variables are stationary as seen in the unit root
test table above. As a result of most variables
having no effect of unit root (stationary), the
variables not stationary are therefore transformed
(differenced) by taking their natural logarithm
before fitting the static panel regression panel for
optimal result.
Table 3. Test of Multicollinearity Table
Model
Coefficientsa
Collinearity Statistics
Tolerance
VIF
1
CAPITAL ADEQUACY
(Equal to or greater than
10%)
.097
10.360
LIQUIDITY (Equal to or
greater than 30%)
.761
1.315
ASSET QUALITY i.e Non
Performing Loan Ratio
(Equal to or less than 5%)
.184
5.445
LEVERAGE
.217
4.618
AGE
.866
1.155
BANK SIZE i.e Total
Assets
.769
1.301
a. Dependent Variable: EPS
From the test multicollinearity shown in table 4.3
above, it was noticed that only the variable “Capital
Adequacy” returns a high VIF value but does not
exceed the minimum condition (<13) for no
collinearity stated by the Variance Inflation Factor
(VIF). As such, it is seen that the variable “Capital
Adequacy” greatly exhibits the collinearity
tendency, hence we cannot apply Panel Data
Regression (generalised least square GLS) model
without a natural log transformation of the variable
“Capital Adequacy to correct for the effect of
almost multicollinearity observed. Furthermore,
fitting the GLS model (fixed and random effect
model) will further minimize the effect of
multicollinearity which is a classical model
assumption violation.
3.3 Diagnostic Tests - Determination of Best
Panel Regression Model
Before delving proper into the hypothesis analysis
of the prudential regulation on financial
performance of quoted banks in Nigeria, the
researcher decide on the most appropriate panel
regression model technique for the estimation.
Hence, as earlier highlighted, this study used the
Lagrange multiplier test (LM) to first determine
whether Random Effect model is better than
Common Effect (Pooled Least Square - PLS) model,
if the Random effect model is selected, the
Hausman test is used to select between the Fixed
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Effect or Random Effect model for the study
hypotheses testing and interpretation.
The results of the estimation of Lagrange
multiplier test (LM) and Hausman test are reported
in tables 4.5 and 4.6 respectively, as shown below:
Table 4. Lagrange Multiplier Test (LM)
Source: Researcher’s computation
Since the LM test p-value of 0.000 which is less
than the 0.05 (5%) level of significance, the model
thus suggests the presence of random effect and
such the pooled OLS model is not the best for the
test hypothesis. However, the Hausman test will be
required to select the best model between fixed and
random effect model since the pooled OLS is
removed by LM test.
Table 5. Hausman test for the models
As observed from the Hausman test p-value (0.000)
which is less than the 0.05 (5%) level of
significance, which in turns implies that the fixed
effect model is the most appropriate and thus better
than both the Pooled OLS and the Random Effect
model. Therefore, this study will base its test of
hypotheses on the parameter estimates of the fixed
effect model as in [53]and [40].
Table 6. Panel Model Estimate
EPS
Fixed Effect Model
Coef.
T
P>|t|
CAR
0.7166
0.6400
0.5250
LIQ
0.1804
0.1600
0.8720
AQY
-0.2843
-0.1500
0.8850
LEV
-1.5006
-0.8800
0.3800
AGE
25.6899
3.7200
0.0000
BSZ
0.0097
0.5500
0.5800
_cons
-1031.8720
-3.3100
0.0010
Number of groups
13.0000
Number of obs
130.0000
F(6, 123)
6.3500
Prob > F
0.0000
R-squared
0.4000
Adj R-squared
NA
3.4 Test of Hypotheses
Assessment of the plausibility of the hypotheses was
carried out on the available data, using the panel
model regression with the aim to ascertain the effect
of prudential regulation on financial performance of
quoted banks in Nigeria. The independent variables
are capital adequacy, liquidity, asset quality and
leverage which are the proxies for prudential
regulation while the dependent variable is Earnings
per share (EPS), a proxy for financial performance.
Age and bank size are the control variables. The
fixed effect model was favoured due to its
consistencies in meeting the assumption of
applicability using the earnings per share (EPS) as a
measure of financial performance, to explain the
effect of the four (4) prudential indicators - capital
adequacy, liquidity asset quality and leverage in
Nigeria deposit money banks. The level of
significance adopted in the regression analysis is
5%. Below is the table showing summary of finding
and detailed discussion:
Ho1: There is no significant effect of capital
adequacy on earnings per share of Nigerian quoted
deposit money banks: The variable “capital
adequacy (CAR)” has a panel regression coefficient
of 0.7166 against banks’ earnings per share (EPS).
This implies that the capital adequacy (CAR) has a
positive relationship with banks’ earnings per share
(EPS) as a measure of financial performance;
suggesting that, with a percentage increase in the
capital adequacy requirement (CAR), the banks will
see about 0.7166 percent increase in financial
performance as explained by their earnings per
share. Furthermore, the capital adequacy
requirement (CAR) has a p-value of 0.5250 which is
greater than 0.05 (5%) level of significance. This
implies that the coefficient is not statistically
significant. Hence, the null hypothesis cannot be
rejected. We, therefore, conclude that the
relationship observed between the capital adequacy
requirement (CAR) and the earnings per share is not
generalisable. This is in concurrence with the
findings from the studies conducted by [44], [6],
[15], [41] who established a positive relationship
and the fact that prudential regulation
around capital adequacy plays a role in
increasing the financial fortunes of deposit money
banks.
Prob > chibar2 = 0.0000
chibar2(01) = 15.71
Test: Var(u) = 0
u 9382.903 96.86539
e 20742.49 144.0225
EPS 49830.02 223.2264
Var sd = sqrt(Var)
Estimated results:
EPS[BANK,t] = Xb + u[BANK] + e[BANK,t]
Breusch and Pagan Lagrangian multiplier test for random effects
= -3587.84 chi2<0 ==> model fitted on these
chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B)
Test: Ho: difference in coefficients not systematic
B = inconsistent under Ha, efficient under Ho; obtained from xtreg
b = consistent under Ho and Ha; obtained from xtreg
BSZ .0096802 .0603389 -.0506587 .0130884
AGE 25.68991 -1.960868 27.65077 6.837596
LEV -1.500608 -.0526713 -1.447937 .2917951
AQY -.2843234 -1.574728 1.290404 .
LIQ .1804147 .925852 -.7454373 .
CAR .7165684 -.7864881 1.503056 .1184137
fixed random Difference S.E.
(b) (B) (b-B) sqrt(diag(V_b-V_B))
Coefficients
. hausman fixed random
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This could be attributed to non-buffering of
capital large enough to the point of generating
significant profit or sub-optimal use of capital
leading to sub-optimal financial performance.
Another possible reason is that, in some instances,
having a sizeable capital could lead banks to trading
over-cautiously as to avoid sanctions from the CBN,
as such, such banks advanced low quantum of loans
when compared the capital size and this delivers
profitability that is not significant. However, [29]
are of contrary view and opinion. They claimed that
the capital adequacy does not influence improved
financial performance. Rather, banks do raise capital
for other objectives such as, providing adequate
cushions for risks, and not for profit motive [29].
Ho2: There is no significant effect of liquidity on
earnings per share of Nigerian quoted deposit
money banks: The variable liquidity (LIQ) has a
panel regression coefficient of 0.1804 for EPS,
which implies that the liquidity (LIQ) has a positive
effect on the banks’ earnings per share (EPS) as
measure of performance. Thus, suggesting that with
a percentage increase in the liquidity (LIQ), the
banks will see about 1.8 percent increase in its
performance as explained its earnings per share.
However, the p-value of 0.8720 of the parameter is
observed to be greater than 5% level of significance
adopted for the study under EPS, therefore, the
relationship is not statistically significant for EPS.
Hence, the null hypothesis is not rejected. Thus, we
conclude that liquidity has a positive but not
significant effect on the banks’ earnings per share.
This result is consistent with the studies conducted
by [40], [32] and [42], [44], [46] and [40] who
agreed with the finding to the extent that there was a
positive but a non-significant relationship between
liquidity and profitability and advised the regulators
to improve the management of liquidity risk in the
banks.
The positive association can be attributed to
adequate mobilisation of deposits, effective treasury
management and the effective utilisation of liquidity
via lending to SMEs, Retail, Mortgage and
Consumer products. High liquidity means more
available funds to meet depositors’ expectations,
more working capital to finance transactions that
will generate more profit. In total disagreement to
the results of the findings, [52] and [16] shared a
contrary opinion and submitted that there was a
negative relationship between liquidity management
and financial performance.
Ho3: There is no significant effect of asset
quality on earnings per share of Nigerian quoted
deposit money banks: Also, from the estimator, the
effect of asset quality (AQY) proxy by non-
performing loans on financial performance in
Nigerian quoted deposit money banks. The variable
AQY, has a panel regression coefficient of -0.2843
which implies that the asset quality (AQY), proxied
with non-performing loan ratio has a negative effect
on the banks’ earnings per share (EPS) as a measure
of financial performance, implying that the higher
non-performing loan ratio, the lower the
profitability. It is further observed that the p-value
of 0.8850 is greater than the 5% level of
significance. Hence, the null hypothesis is not
rejected; meaning that the asset quality has no
significant effect on the banks’ return on assets.
This finding is consistent with [54] and [53] whose
findings were that regulatory variable “asset
quality” proxied by non-performing loans had
negative impact on bank’s financial performance.
An increase in non-performing loan ratio reduces
the bank’s capacity to create further loans, hence
less earnings for the bank, leads to high loan loss
provisions which will put further pressure on the
earnings of the ban thereby, reducing shareholders’
value. This position is a worrisome trend in the
banking industry because increased non-performing
loan portfolio above the regulatory threshold
threatens banks stability. It is a pointer to the
changing dynamics of lending practice where banks
are forced to take up more risk or poor lending
culture in Nigerian bank. On the contrary, [5] and
[34] averred that the banks with huge portfolio of
non-performing loans still do enjoy high
profitability.
Ho4: There is no significant effect of leverage on
earnings per share of Nigerian quoted deposit
money banks: The variable leverage (LEV) has a
panel regression coefficient -1.5006 which implies
that the leverage (LEV) has a negative impact on the
banks’ earnings per share (EPS) as measure of
performance. Thus, suggesting that with a unit
increase in the leverage (LEV), the banks will see
about 1.5006 decrease in EPS. The p-value of
0.3800 is greater than 0.05 level of significance and
is not statistically significant at 5% level of
significance. Hence, the null hypothesis is not
rejected. This is in concurrence with the study
outcomes by [46], [13], [34] who empirically
examined the impacts of capital structure (leverage)
on the financial performance and came up with the
inverse relationship, thereby calling for a review of
leverage as a critical strategy to maximise
shareholders’ returns but in sharp disagreement with
[55], [29] and [32] who ascertained that there is
positive relationship and statistical significance
between leverage and financial performance.
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Control Variables - Age and Bank Size: At co-
efficient of 25.6899 and p-value of 0.000, it shows
that bank age has a positive and significant
relationship with bank’s financial performance
proxied by EPS. This is in concurrence with the
finding of [17]. Furthermore, the findings showed a
negative and insignificant relationship between bank
size and EPS with coefficient of 0.0097 and p-value
of 0.5800. This indicates that the size of banks has
nothing to do with the financial performance. The
result is consistent with previous study in Ghana on
bank profitability determinants and other similar
studies in other jurisdictions [34].
4 Conclusion
The study considered a panel data analysis to
determine the effect the CBN’s prudential
regulations on financial performance of quoted
DMBs in Nigeria using the fixed effect model of
static panel regression model. It can be concluded
that capital adequacy has a negative and non-
significant linear relationship with bank’s EPS. This
implies that increase in capital does not necessarily
translate to higher EPS. When the capital as the
primary funding source is not optimally managed to
generate profit or its large proportion is subject to
absorbing losses due to poor credit management.
This will negatively affect the returns to
shareholders. The variable - liquidity (LIQ) has a
positive effect on the bank’s earnings per share
(EPS) as a measure of performance. Thus,
suggesting that higher liquidity lessens banks’
liquidity risk and prevents financial crisis and the
bank has sufficient liquidity to meet all the cash
obligations within a short time and meet the
required relevant regulatory requirements Risk
Asset quality proxied by the non-performing loan
negatively and but insignificantly impacts the
financial performance of quoted DMBs. An increase
in non-performing loan ratio reduces the bank’s
capacity to create further loans, hence less earnings
for the bank, leads to high loan loss provisions
which will put further pressure on the earnings of
the ban thereby, reducing shareholders’ value. It can
also be concluded that effect of leverage on the
financial performance of the quoted banks under
consideration is negative. Impliedly, there is
deficiency in the capital mix of deposit banks to the
extent that it does not add value to profitability.
Leverage is to ensure that financing risk is kept
under control, as such, the banks need an optimal
capital-mix to prevent the financing risk from being
pushed beyond acceptable limit, so as to prevent a
drop in returns to shareholders. It is also discovered
that control variable - age and size of banks - are
positive determining factors though not significant,
that boosts the financial performance of banks
because, they can help them in positive customer
perception and to achieve economies of scale.
Overall, following the results of various analyses
and findings, the combined effect of the prudential
regulation capital adequacy, liquidity, asset
quality, leverage - has strengthened some aspects of
banking in Nigeria. However, it behooves on the
Regulator to provide more holistic and integrated
regulations that will enable capital adequacy achieve
the intended objective, ensure sustainability of the
positive influence of liquidity and leverage for
sustained financial performance and reduce non-
performing loan which is currently well above the
industry average as a way of boosting risk asset
quality.
The study therefore recommends the following:
The inverse relationship between capital and
financial performance (EPS) which is contrary to
the apriori requires that the CBN must do a
thorough check on the quality of capital held by the
banks. Situations whereby owners of banks are able
to finance their equity holdings by borrowing from
their own bank is an indication of poor quality of
capital. In such cases the capital requirement is met
but the it would neither reduce incentives for risk
taking nor provide a buffer against losses,
consequently, it will not have any positive impact
on profitability.
Assess the effect of liquidity on earning per share
in Nigerian quoted deposit money banks.
• To sustain the positive relationship and statistically
significant effect of liquidity on the financial
performance (EPS), the banks should continue to
drive deposit liability at low cost and ensure
efficient liquidity management
The banks need to work down the NPL that
currently has the industry average that well above
the statutory limit of 5% through aggressive loan
recovery and sound credit management such as
application of principles of prudence to problem
loans, strict adherence to credit policies of the
banks, enhanced due diligence on loan customers,
knowledge of business being financed, and adequate
collaterisation that meets legality and marketability
requirement and sound loan monitoring.
The use of leverage is encouraged in financing the
banking business. However, to achieve the positive
relationship and remain competitive with financial
performance, the optimal debt- equity mix should be
adopted by banks. Furthermore, the mix should be
closely monitored because, leverage is two-edged
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word, so the banks have to ensure that financing risk
is not increased beyond the acceptable thresholds,
which is capable of leading to lower returns to
shareholders.
Regulator needs to pay attention to the perfect
balance (mix) between the benefits that leverage
confers to industry and the potential systemic risk
posed by high levels of leverage to ensure that
existing market mechanisms adequately guides on
the use of leverage to avoid it resulting to high
levels of systemic risk.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
Isaiah Ademola Adeleke: Conceptualization,
Methodology, Formal analysis, Software, Writing -
original draft.
Umar Abbas Ibrahim: Conceptualization,
Methodology and Supervision.
Authors’ Declarations
The Authors have no conflict of interests to declare.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
This research received no specific grant from any
funding agency in the public, commercial, or non-
for-profit sectors.
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
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