




































American International Journal of Business and Management Studies  

Vol. 1, No. 1; 2019 

Published by American Center of Science and Education, USA 

 

38 

 

Asset Quality and Deposit Money Banks Performance in Nigeria 
 

 

 

Mbatabbey Joy Ogboru   

Department of Banking and Finance 

Faculty of Management Sciences 

Rivers State University, Port Harcourt 

Email: mbatabbeyjoy@gmail.com 

 

Abstract 

This study investigate the relationship between asset quality and deposit money banks performance in Nigeria over a 

period of 30 years ranging from 1986 to 2016, utilizing time series data collected from the Nigeria deposit insurance 

corporation annual reports and accounts, CBN financial stability report and CBN statistically bulletin for various 

years. The variables of study includes return on asset (ROA) proxy for Deposit Money Bank performance in 

Nigeria, ratio of non-performing loan to total loan (NPL), ratio of liquid assets to total assets (LAT) and ratio of 

liquid assets to short term liabilities (LAS) as measures of asset quality. The study utilizes both the descriptive and 

econometric techniques to analyze the time series data. The result shows that there is a short run relationship 

between asset quality and deposit money bank performance in Nigeria. Also, the co-integration result reveals the 

presence of a long run relationship between asset quality and deposit money bank performance in Nigeria while the 

granger causality result shows evidence of causality between asset quality and deposit money bank performance in 

Nigeria. Based on this we conclude by saying that maintaining sound assets quality position is critical to the long 

term performance, survival and sustainability of DMBs in Nigeria. 

. 

 Keywords: Asset Quality, Deposit Money Banks Return on Assets, Liquid Assets to Short Term Liabilities 

INTRODUCTION 

 

The issue of poor assets quality or in other words non-performing assets has gained increasing attention in the 

academia for some decades now. Deteriorating asset quality was a permanent characteristic of banking institutions 

in Nigeria. This was not unconnected with weak credit policies and practices, insider abuses and unstable 

macroeconomic environment. Non-performing assets (NPA) reached alarming levels in the late 90s sometimes in 

excess of fifty percent (50%) of gross credit. This led to the collapse of more than 30 banks in 1998, several 

community banks, primary mortgage institutions and finance companies. In 2009 the non performing assets ratio of 

10 banks including the intervened banks averaged 54.2 percents (Oni, 2012). Going by this, Nigeria as a nation has 

so far witnessed series of banking crises. These series of failure experienced in the nation’s banking sector over this 

periods can be captured by the number of failed financial banks, spate of poor assets, the debt and capitalization 

requirement, erosion of depositors and investors fund and the general effects on the economy (Iwedi, 2017). These 

crises (1936-1968, 1968-2000, 2000-2004, and 2004-2011) led to the closing down of over 58 deposit money banks 

(CBN, 1968, NDIC, 2002, Nzotta, 2004, Adeyemi, 2011 and Ohwofasa&Mayuku, 2012 and Iwedi, 2017). 

However, vast of studies on the effect of credit risk or non performing loan and performance of banking institutions 

in Nigeria have well been documented from both theoretical and empirical perspectives with the help of regression 

estimation techniques. But to the best knowledge of the researcher very fragmented studies of citable significance 

have dealt on the issue of asset quality and Deposit money banks (DMBs) performance in Nigeria. Among such 

works are the scholarly works of Abata, (2014), and Lucky &Nwosi, (2015) that studied assets quality and 

performance of fifteen selected commercial banks quoted on the Nigeria Stock Exchange. Based on this gap, this 

work is carried out to investigate the effects of asset quality on performance of twenty two (22) deposit money banks 

in Nigeria using the estimation of the ordinary least square (OLS) technique. Since the OLS technique have become 

very popular estimation techniques in investigating the link and the velocity of adjustment of variables under study. 

Therefore, it is important we used this estimation tool to bridge the knowledge gap and to find another perspective.  

 

 



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LITERATURE REVIEW 

Asset Quality 

Conceptually, in the banking industry, asset quality refers to the review or an evaluation, which assesses the credit 

risk associated with any particular assets that normally requires the payments of interest like investment and loans 

portfolios.  Ombaba (2013) defined asset quality as the general risk attached to various assets held by financial 

institution. It is commonly used by financial institution to determine how many of their assets are at financial risk 

and how much allowance for potential losses they must make. The most common assets of banks requiring a strict 

determination of asset quality are loans and advances. Increasing loan quality will increase the return of financial 

institution loans and reduce the costs of failure, but at the same time it will be attained at a cost that requires banks’ 

attention to manage (Khalid, 2012). The support of asset quality is an essential feature of bank (Gulia 2014). Asset 

quality of the bank is one of the main issues whenever research on banks is conducted (Chisti 2012). How efficient 

and effective is the bank management in monitoring and controlling credit risk can also have an effect on the kind of 

credit rating given.  

 

Conceptual Framework of Profitability 

Profitability connotes a situation where the income generated during a given period exceeds the expenses incurred 

over the same length of time for the sole purpose of generating income Banwo (1997), Sanni (2006). The 

fundamental requirements here are that the income and the expenses must occur during the same period of time 

(Matching Concept) and the income must be a direct consequence of the expenses. The period of time may be one 

week, three months, one year etc. Sabo (2007). It is not immaterial whether or not the income has been received in 

cash nor is it compulsory that the expenses must have been paid in cash.  The term profit can take either its 

economic meaning or accounting concept which shows the excess of income over expenditure viewed during a 

specified period of time.  

 

THEORETICAL LITERATURE  

Agency Theory  

The agency problem was developed by Coase (1960), Jensen and Meckling (1976) and Fama and Jensen (1983). 

The theory states the relationship between principals such as a shareholders, and agents such as a firm’s senior 

management. The principal delegates work to an agent. The theory attempts to deal with firstly, the agency problem 

where there is a conflict of interest between a company's management and the company's stockholders, and 

secondly, that the principal and agent settle for different risk tolerances. There are two main agency relationships in 

a firm that are normally in conflict; those between the company’s management and stockholders and between the 

stockholders and the debt holders. These agency conflicts have implications on corporate governance and business 

ethics. Such relationships have expensive agency costs that are incurred so as to sustain an effective agency 

relationship. Incentive fees paid to agents to encourage behavior consistent with the principal’s goals are common 

examples of agency costs Bowie and Edward (1992).  

Market Power Theory  
Market power theory emanated from Bain (1951). This theory stresses that an increase in market power results to a 

monopoly, profits (Athanasoglou, Brissimis& Delis, 2005). The theory is based on the premise that concentration of 

the market is a best measure for market power since more concentrated markets exhibit superior market 

imperfections facilitating various entities to set prices for their products and services at levels which is less 

favourable to their clients or customers (Punt and Rooij, 2001). The theory also affirms that companies with a large 

market share and sound differentiated products and services can easily earn monopolistic profits and succeed or win 

against their competitors (Nkegbe&Yazidu, 2015).  The market power theory assumes that extra profits results from 

a higher market concentration which allows commercial banks to collude and earn supernormal profits which arise 

due to the firms portfolio of differentiated products that also increases the market share and market power in 

determining prices for products (Mirzaei, 2012).  

Efficiency Theory 
The efficiency theory was formulated by Demsetz (1973) as an alternative to the market power theory. The 

efficiency theory presupposes that better management and scale efficiency results to higher concentration thus 

greater and higher profits. Accordingly, the theory posits that management efficiency not only increases profits, but 

also results to larger market share gains and improved market concentration (Athanasoglou, Brissimis& Delis, 

2005). The efficiency theory also states that a positive concentration profitability relation may be a sign of a positive 

connection relating to efficiency and size. The theory postulates that positive association between the concentration 



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40 

 

and profit arise from a lower cost which is mainly achieved through production efficient practices and increased 

managerial process (Birhanu, 2012).  

Empirical Literature 

Lucky and Nwosi (2015) examined the relationship between asset quality and the profitability of the fifteen (15) 

quoted commercial banks in Nigeria from 1980 – 2013. The objective was to investigate the relationship between 

CAMELS criteria for asset quality and the profitability performance of Nigerian commercial banks. Secondary data 

were sourced from annual reports of the quoted commercial banks. Return on Investment (ROI) was modeled as the 

function of percentage of non-performing loans to Total Loans (NPL/TL), percentage of Nonperforming 

Loans to Total Customers’ Deposit (NPL//TCD), percentage of Loan Loss Provision to Total Loans (LLP/TL) and 

percentage of Loan Loss Provision to Total Asset (LLP/TA). Multiple regressions with econometric view statistical 

package were used as data analysis method. The Ordinary Least Square properties of Augmented Dickey Fuller 

Test, Co-integration and Granger Causality test were employed to determine the short and long –run relationship 

between the dependent and the independent variables. Findings from the regression result proved that percentage of 

non-performing loans to Total Loans and percentage of nonperforming Loans to Total Customers’ Deposit have 

positive relationship with Return on Investment while percentage of Loan Loss Provision to Total Loans and 

percentage of Loan Loss Provision to Total Asset have negative relationship with Return on Investment of the 

commercial banks. The Unit Root test shows stationarity of the variables in order of 1(1), the co-integration reveal 

long run relationship between the variables while the granger causality reveals no causal relationship among the 

variables. The model summary proved that the independent variables can explain 65.5% variation on the dependent 

variables while the F-statistics of 12.508477 and the probability of 0.000008 proved that the model is significant. 

The study concludes that there is significant relationship between asset quality and the profitability of the 

commercial banks.  

 

Lis, et al. (2000) found that GDP growth and bank specific characteristic (bank size and Capital) had negative effect 

on bank assets quality while credit growth, collateral, net interest margin, debt-equity, market power and regulation 

regime had a positive impact on bank assets. Cantrell (1994) pin pointed that asset quality is one of the main 

concerns in the formula for evaluating the top one hundred U.S. banks stated in U.S. 

Abata (2014) examined assets quality and bank performance of six largest banks quoted in Nigeria stock exchange 

using secondary data sourced from the annual reports of the commercial banks for fifteen years (1999 – 2013). The 

study adopted the use of ratios as a measure of bank performance and asset quality since it is a verifiable means for 

gauging the firms level activities while the data were analyzed using the Pearson correlation and regression tool of 

the SPSS 17.0. The findings revealed that assets quality has a statistically relationship and influence on bank 

performance.   

 

Swamy (2015) revealed that private sector credit was found not to be significant in affecting the non-performing 

assets contrary to the general perception and similar in the case with rural branches implying that aversion to rural 

credit is falsely founded perception. Bad debts are dependent more on the performance of the industry than other 

sectors of the economy. Furthermore, Capital adequacy and investment activity significantly affect the profitability 

of commercial banks apart from other accepted determinants of profitability; assets size has no significant impact on 

profitability. 

Literature Gap 

So far we have reviewed the literature on the effect of asset quality and profitability of banking institution in 

different countries. Some of the studies reviewed were cross-country while others were country-specific. However, 

vast of studies on the effect of credit risk or non performing loan and performance of banking institutions in Nigeria 

have well been documented from both theoretical and empirical perspectives with the help of regression estimation 

techniques. But to the best knowledge of the researcher very fragmented studies of citable significance have dealt on 

the problem of asset quality and Deposit money banks (DMBs) performance in Nigeria.  Such as Abata, 2014 and 

Lucky &Nwosi, 2015 who only studied assets quality and performance of selected commercial banks quoted on the 

Nigeria Stock Exchange.  Therefore, the study is embarked on to examine the effect of asset quality on performance 

of deposit money banks in Nigeria using the estimation of the ordinary least square technique. Since the OLS 

technique have become very popular estimation techniques in investigating the nature of the link and the velocity of 

adjustment in each of the variables under study. Therefore, it is important we used this estimation tool to bridge the 

knowledge gap and to find another perspective.  

 



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RESEARCH METHODOLOGY 

The study adopted the quasi-experimental research design. Target population is the specific population from which 

information is required. The population of this study comprised of all the financial institutions operating in Nigeria.  

The data for this study are time series data ranging from 1986 – 2016. The data consist of yearly data of one 

dependent variables of return on assets and three independent variable of banking system assets quality indicators. 

Model Specification
 

Following the previous works of Abata, (2014) and Swamy, (2015) we model the relationship between asset quality 

and profitability of deposit money banks in Nigeria as follow: 

                     (3.1) 

To have the estimable version of above equation, equation (10) can be rewritten to have  

                    (3.2) 

Where 

ROA = Return on Assets 

NPL=Non-Performing Loans to Total Loans 

LAS =Liquid Assets (core) to Total Assets 

LSA =Liquid Assets (core) to Short term Liabilities 


00

= Constant  


1
 - 

3
= Coefficients of independent variables 


it

       = Error Term  

TECHNIQUES OF ANALYSIS 

 

ORDINARY LEAST SQUARE REGRESSION ANALYSIS 

 

Ordinary least squares (OLS)is a method for estimating the unknown parameters in a linear regression model. 

Hutcheson (2011) defined ordinary least  square (OLS) regression as a generalized linear modeling technique that 

may be used to model a single response variable which has been recorded on at least an interval scale. This method 

minimizes the sum of squared vertical distances between the observed responses in the dataset and the responses 

predicted by the linear approximation. 

UNIT ROOT TEST 

A unit root test is a statistical test for the proposition that in a autoregressive statistical model of a time series, the 

autoregressive parameter is one. (Econtermsy(t), where t a whole number, modeled by: 

y(t+1) = ay(t) + other terms 

Where a is an unknown constant, a unit root test would be a test of the hypothesis that a=1, usually against the 

alternative that |a| is less than 1.  

Mackinnon critical value. 

 
COINTEGRATION TEST 

Cointegration is a statistical property of time series variables. In a situation where two or more series are 

individually integrated (in the time series sense) but some linear combination of them has a lower order of 

integration, then the series are said to be cointegrated. According to (C T Eviews 2010) Cointegration refers to a 



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42 

 

scenario where linear combination of non stationary variables is stationary. For these non-stationary time series 

variables, there is a possibility of estimation by differencing in cases where the differences are stationary.  

 

GRANGER CAUSALITY TEST 

In conducting an econometric study, the direction of causal relationship among variables is determined according to 

the information obtained from the theory. In this study, Granger Causality test was used in order to test the 

hypotheses regarding the presence and the direction of the causality between assets quality and profitability of 

deposit money banks.  

 

DATA PRESENTATION, ANALYSIS AND DISCUSSION OF FINDINGS 

Table OLS Result Output between Assets Quality and Return on Assets 

Variable Coefficient Std. Error t-Statistic Prob.   

C 6.097605 3.563955 1.710909 0.0986 

NPL 0.015289 0.036380 0.420267 0.6776 

LAT -0.100918 0.045771 -2.204820 0.0362 

LAS 0.009531 0.083706 0.113865 0.9102 

R-squared 0.195479        Mean dependent var 2.116129 

Adjusted R-squared 0.106087     S.D. dependent var 3.204590 

S.E. of regression 3.029842     Akaike info criterion 5.174812 

Sum squared resid 247.8585     Schwarz criterion 5.359843 

Log likelihood -76.20959     F-statistic 12.18776 

Durbin-Watson stat 1.939832     Prob(F-statistic) 0.000693 

Source: E view 9.0 Output 

 

The objective of this study is to investigate the effects of asset quality on deposit money bank performance in 

Nigeria (measure by ROA). The regression model explains our hypothesis and coefficient of deformation (R
2
) of 

0.1955 and adjusted (R
2
) OF 0.106. This indicated that the regression has low explanatory power. However, the 

values of R
2 

and adjusted R
2 

show that 20 percent of the variations in the criterion variable (Return on Assets) is 

attributable to the predictor variable selected by the model and involve ratio of non-performing loan to total loan 

(NPL), ratio of liquid assets to total assets (LAT) and ratio of liquid assets to short term liabilities (LAS). Though 

the R
2 

and adjusted R
2 

is low but it is significant judging from the significant F. statistics, which is equally 

considerable the implication is that the regression model for this study is well specified and does not suffer any mis-

specification problem. Further, the result from the model can be relied upon in making useful inference with respect 

to return on assets (ROA). The Durbin Watson test is use for testing presence of auto-correlation which has a value 

of 1.94. The DW table shows the upper and lower value as 1.31 and 1.68 respectively. This shows that there is no 

presence of auto-correlation among the variable since the Durbin Watson computed does not fall within the DW 

tabulated. Under table 4.8 the results will reject the null hypothesis since it has a residue relationship on deposit 

money bank performance (ROA) in Nigeria. This mean that ratio of non-performing loan to total loan are significant 

in explaining the performance of deposit money banks. The result shows that the ratio of liquid assets to total asset 

of the bank is statistically significant in their influence on Return on Assets. LAT has negative relationship with 

return on assets (ROA). This indicates that return on assets (ROA) and ratio of liquid assets to total assets move in 

opposition direction. The coefficient shows that a percentage increase of ratio of liquid asset to total assets will lead 

to about o.10 decrease in return on asset (ROA). The output of this could be attributed to the unprofitable/volatile 

deposits and reserves which do not stay long in banks vault. Deposits in the bank vaults can be erratic and 

vulnerable that is subject to withdrawer without notification. This result is in line with finding of Ikpefan (2013), 

Abata (2014); Lucky & Nwosi, (2015) and Vighneswara (2015). Finally, the ratio of liquid assets to short term 

liabilities has insignificant effect on Return on Assets of 5% level of significance. The result shows that there is a 

positive relationship between ratios of liquid assets to short term liabilities though insignificant. 

Table 4.4 Stationarity Test for Assets Quality and Return on Asset 

Variables ADF stat @ 1
st
 

Difference 

Critical Value @ 1% Critical Value @ 

5% 

Order of 

Integration 

ROA -5.397653 -3.6852 -2.9705 I(1) 

NPL -5.573627 -3.6852 -2.9705 I(1) 

LAT -6.011578 -3.6852 -2.9705 I(1) 



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LAS -4.599397 -3.6852 -2.9705 I(1) 

Source: E-view 9.0 Output 

 

The study conducted stationarity test using the Augmented Dickey Fuller unit root test. The results are summarized 

on table 4.6 for each of the variables under study. Comparing the critical value at both 1% and 5% with the ADF 

statistics, the result indicates that all the variables are stationary at first differencing. Hence, the variables are all 

integrated serious of order 1(I). this implies that the absolute values of the ADF test statistics are all greater than the 

critical values at 5% level of significance. Having stationarized the series, the data can now be subjected to a test to 

ascertain whether these series are co-integrated or not by employing the Johansen Co-integration procedure to 

estimate the long run equilibrium relationship between the predictor and criterion variables. 

4.5 Econometric Analysis and Hypotheses Testing 

Table 4.7 Johansen Co-integration Test Output between Assets Quality and Return on Assets 

Eigenvalue Likelihood Ratio 5 Percent Critical 

Value 

1 Percent 

Critical Value 

Hypothesized No. of 

CE(s) 

 0.626201  48.37381  47.21  54.46       None * 

 0.369605  19.83675  29.68  35.65    At most 1 

 0.198525  6.455884  15.41  20.04    At most 2 

 0.001315  0.038146   3.76   6.65    At most 3 

Source: E-view 9.0 Output 

*(**) denotes rejection of the hypothesis at 5%(1%) significance level L.R. test indicates 1 cointegrating equation(s) 

at 5% significance level 

 

Since the data are of order 1(I), we now apply the Johansen co-integration techniques to ascertain the existence of 

long-run co-integrating relationship. The co-integration test is based on the likelihood ratio and the critical value. 

The result is presented in table 4.7 above and from table 4.7 it can be seen that the observed likelihood ratio of 

48.374 is greater than the critical value of 47.21 at 5% level of significance. Therefore from the table it is clear that 

the test indicate at most 1 co-integrating equation. This result means that there is a long run equilibrium relationship 

between return on assets (ROA) and bank asset quality indicators in Nigeria. The finding of this study is in line with 

the work of Lucky and Nwosi (2015) and Vighneswara (2015) and in contrary with this finding of Khalied (2012) 

and Li & Chiu (2004) who find no evidence of co-integration between bank performance asset qualities. 

 

Table 4.6 Granger Causality Test Output Assets Quality and Return on Assets 

  Null Hypothesis: Obs F-Statistic Probability 

  NPL does not Granger Cause ROA 29  1.77927  0.19031 

  ROA does not Granger Cause NPL  0.11710  0.89000 

 

  LAT does not Granger Cause ROA 

 

29 

 

 2.60432 

 

0.09471 

  ROA does not Granger Cause LAT  3.59150  0.04320 

 

  LAS does not Granger Cause ROA 

 

29 

 

1.04864 

 

0.36593 

  ROA does not Granger Cause LAS  3.35894  0.05174 

 

  LAT does not Granger Cause NPL 

 

29 

 

 0.92660 

 

0.40960 

  NPL does not Granger Cause LAT  0.62885  0.54176 

 

  LAS does not Granger Cause NPL 

 

29 

 

1.99824 

 

 0.15750 

  NPL does not Granger Cause LAS  1.25612  0.30281 

 

  LAS does not Granger Cause LAT 

 

29 

 

 0.02567 

 

 0.97468 

  LAT does not Granger Cause LAS  3.31366  0.05361 

Source: E view 9.0 Output 



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The result of the Pairwise granger causality test conducted with a maximum log of 2 is presented in table 4.9 below 

from result; the null hypothesis is rejected if the probability of F-statistics given in the test result is less than 0.05. 

From table 4.9 the result shows that at 5% level of significance. Ratio of non-performing loan to total loan (NPL) 

does not granger cause bank performance (ROA) just as ROA does not granger NPL. This implies that the level of 

NPL in the banking sector cannot influence return on assets of banking institutions in Nigeria vice versa. This is in 

line with the work of Lucky and Nwosi (2015). Also the result as shown in table 4.5 reveal that there is causality 

having from ether LAT to ROA or ROA to LAT at 2 years lagged periods. This evidence is confirmed by the 

probability value at both instances were less than 0.05 and 0.10 measured at 5% and 10% Significance level. This 

suggests that an increase in the ratio of liquid assets to total asset (LAT) will raise the performance of bank in 

Nigeria and vice versa. On the other hand, increase in ROA of Nigeria banks will in turn translate into a rise in 

liquid assets of Nigeria banks. Also, increased performance of banks can boost liquidity of Nigeria banks which in 

turn increase the credit creation ability of the Nigerian banks. Finally, the results reveal the case of a unidirectional 

causality flowing from ratio on assets (ROA) to liquids asset to short term liabilities of Nigeria. The implication of 

this is that an increase in ratio on assets (ROA) can boost banks liquidity to meet short term obligation as they come 

due. Our finding collaborate the findings (Kpefan 2013), the study cannot accept the null hypothesis of no causal 

affect between asset quality and DMB performance in Nigeria. By inference therefore, the results shows that asset 

quality granger cause and influence bank performance in Nigeria. 

 

Table 4.7 Serial Correlation Test for Asset Quality and Return on Asset 

Breusch-Godfrey Serial Correlation LM Test: 

F-statistic 0.649016     Probability 0.531141 

Obs*R-squared 1.530113     Probability 0.465308 

Source: E-view 9.0 Output 

The results of the Breusch-Godfrey Serial Correlation LM Test as presented in table 4.3 above indicate that there is 

problem of serial correlation among series. This evidence is confirmed by their respective F-statistic and observed* 

 statistic together with the probabilities values reported to be well above the conventional level of significance. 

Therefore the hypothesis of no serial correlation will have to be accepted. 

Table 4.8 Heteroskedasticity Test for Asset Quality and Return on Asset 

White Heteroskedasticity Test: 

F-statistic 0.971848            Probability 0.465188 

Obs*R-squared 6.059577            Probability 0.416549 

Source: E-view 9.0 Output 

The Heteroskedasticity Test results are presented in table 4.9, 4.10 and 4.11 above. From the tables above it shows 

that the presences of homoscedasticity among the variables are overcome. This is confirmed by their respective F-

statistic and observed*  statistics together with the probabilities values reported to be well above the conventional 

probabilities value. 

Table 4.9 Stability Test for Asset Quality and Return on Asset 

Ramsey RESET Test: 

F-statistic 0.121277              Probability 0.730458 

Log likelihood ratio 0.144263              Probability 0.704079 

Source: E-view 9.0 Output 

Similarly, the Ramsey RESET functional form test, reported on table 4.5 above revealed that model was properly 

specified and is in the appropriate form. The f-statistic and observed* R-squared statistics revealed probabilities of 

0.730 and 0.704 respectively and these are well above the conventional levels of acceptance. Thus we reject a null 

hypothesis of inappropriate functional form. We have no reason to worry about mis-specification problem.  

Discussion of Finding 

As earlier discussed, the study is an attempt to examine the effect of asset quality on deposit money bank 

performance. The result of the study discovered that in the long run there is a significant relationship between asset 

quality and deposit money bank performance in Nigeria. This explicitly rules out the acceptance of the null 

hypothesis of no evidence of co-integration between the variable of study. This submission is line with the 

submission of Lucky & Nwosi (2015). Following the consistency of the ordinary least square (OLS) result and 

notwithstanding the contentions of current theoretical thoughts, the results of regression technique is not sufficient to 

establish causality, this we cannot immediately conclude that asset quality or its variables (NPL, LAT and LAS) 



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45 

 

does significantly and positively influence deposit money bank performance in Nigeria measured by return of asset 

(ROA). It is in this regard that the third hypothesis was postulated. As identified in third hypothesis which was 

formulated in the null form of no causality between asset quality and Deposit Money Bank performance is rejected 

in place of the alternative. This is confirmed by the probability value of the result of the study finding is in line with 

the findings of Lucky & Nwosi (2015). But generally, the models were discovered to be statistically significant and 

asset quality of banks were discovered to account for variation in deposit money banks performance in Nigeria 

which goes in line with findings from scholars like Abata (2014); Vighneswara (2015) and Lucky & Nwosi (2015). 

 

CONCLUSION AND RECOMMENDATIONS 

 

Conclusion  

Conclusively, it can be deduced that there is a significant relationship existing between asset quality and DMBs 

performance in Nigeria. This agrees with the fact that good assets quality is relevant to the deposit money banks 

(DMBs) performance. Furthermore, maintaining sound assets quality position is critical to the long term 

performance, survival and sustainability of DMBs in Nigeria. 

Recommendations 

The following recommendations are made in this study: 

i Managers of banks should encourage activities that will promote DMBs liquidity which will be used to 

meet customers run on the banks and other short term obligation. 

ii Managers of banks should continue practice prudent credit risk management to safeguard assets and protect 

interests of the investors. 

iii Banks should from time to time review their credit pokey to further reduce the incidence of bad loans. 

 

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