Table 4.1: Unit Root Test at Levels
Variable
|
LLC
|
Fisher-ADF
|
ROA
|
0.52987
(0.7019)
|
24.4629
(0.4354)
|
CADR
|
-2.99061
(0.0014)
|
19.6568
(0.7161)
|
NPLR
|
-6.66849
(0.0000)
|
40.9602
(0.0168)
|
LLPR
|
-2.24308
(0.0124)
|
21.3509
(0.6179)
|
LTDR
|
-7.74768
(0.0000)
|
51.9388
(0.0008)
|
SIZE
|
-8.90141
(0.0000)
|
49.2246
(0.0018)
|
Source: Author’s Compilation 2022. Note: parenthesis are p –values
Next, the result of the unit root test on these variables in first differences is reported in table 4.2 below. From the result, it is seen that the LLC and Fisher-ADF test statistic for each of the variable is P-values that are significant at the 1 percent levels. With these result, these variables are adjudged to be stationary after their first differences. Thus, we would accept the hypothesis that the variables possess unit roots. Indeed, the variables are integrated of order one (i.e. I[1]).
Table 4.2: Unit Root Test (at First Differences)
Variable
|
LLC
|
Fisher-ADF
|
ROA
|
-3.80425
(0.0001)
|
50.0208
(0.0014)
|
CADR
|
-4.69350
(0.0000)
|
33.8848
(0.0867)
|
NPLR
|
-9.10387
(0.0000)
|
37.5635
(0.0384)
|
LLPR
|
-24.1086
(0.0000)
|
49.8891
(0.0015)
|
LTDR
|
-10.5866
(0.0000)
|
45.5156
(0.0051)
|
SIZER
|
-7.62787
(0.0000)
|
42.6239
(0.0110)
|
Source: Author’s Compilation 2022. Note: The numbers in parenthesis are p –values
4.3 Correlation Analysis
The result of the correlation tests is presented in table 4.3 below. In the result, Deposit Money Banks’ Performance has a weak negative correlation values of -0.1626990, -0.226717, -0.218155 and -0.256743 with capital adequacy ratio (CADR), non-performing loan ratio (NPLR), loan loss provisions (LLPR) and bank size (SIZE), as well as a weak positive correlation value of 0.160343 with loan to deposit ratio (LTDR). Also, capital adequacy ratio (CADR) and loan loss provisions (LLPR) are strongly correlated with value of 0.547914. On the other hand, non-performing loan ratio (NPLR) has a strong positive correlation value of 0.761478 with loan loss provisions (LLPR). In a nut shell the above results indicate is no strong indication of the problem of multicollinearity amongst the independent variables used in the model.
Table 4.3: The Pairwise Correlation Matrix
|
ROA
|
CADR
|
NPLR
|
LLPR
|
LTDR
|
SIZE
|
ROA
|
1
|
|
|
|
|
|
CADR
|
-0.1626990
|
1
|
|
|
|
|
NPLR
|
-0.226717
|
0.354636
|
1
|
|
|
|
LLPR
|
-0.218155
|
0.547914
|
0.761478
|
1
|
|
|
LTDR
|
0.160343
|
-0.131557
|
-0.022633
|
-0.097905
|
1
|
-
|
SIZE
|
-0.256743
|
0.011420
|
-0.160690
|
-4.487309
|
-0.137061
|
1
|
Source: Author’s compilations 2022 from Eview 9.0
4.4 The Panel Fully Modified Least Squares (FMOLS) Analysis
The result of the Fully Modified Least Squares (FMOLS) method are presented in Table 4.4. The goodness of fit is moderate, with the R squared value of 0.46, indicating that over 46 percent of the systematic variations in banks’ performance is captured in the model. Even the adjusted R squared values of 0.42 percent is moderate, suggesting that the models possessed good predictive abilities.
Table 4.5: Credit Risk Management and Deposit Money Banks Performance in Nigeria (FMOLS) Dependent Variable = ROA
Variables
|
Coeff.
|
T-Ratio
|
Prob.
|
CADR
|
-0.003632
|
-2.487960
|
0.0154*
|
NPLR
|
-0.186634
|
-0.936495
|
0.3524
|
LLPR
|
0.141732
|
0.288485
|
0.7739
|
LTDR
|
-0.003227
|
-0.600766
|
0.5501
|
SIZE
|
-0.061242
|
-3.297829
|
0.0016**
|
ROA(-1)
|
-0.264238
|
-2.231736
|
0.0290
|
R2 = 0.46
|
Ṝ2 = 0.42
|
|
|
Source: Author’s computations 2021: Note: * sig at 1%; * sig at 5% level.
Given the analysis of the individual result, the coefficient of capital adequacy ratio (CADR) is negative and passed the 1 percent level of significance, suggesting that it plays important role in the determination of deposit money banks’ performance in Nigeria. The implication of this result as it relates to the negative sign is that as the risk associated with ratio of banks’ capital adequacy rises, banks’ overall performance reduces by -0.003632 percent.
The coefficient of non-performing loans ratio (NPLR) has a weak inverse relationship with deposit money banks’ performance, it failed the 5 percent significance level, and it suggests that this variable does not play any significant role in the determination of deposit money banks’ performance in Nigeria. Also, the coefficient of loan loss provisions ratio (LLPR) and Loan to deposit ratio (LTDR) failed the 5 percent significance level, as they do not have any significant impact on deposit money banks’ performance. The coefficient of bank size (SIZE) has significant negative impact on deposit money banks’ performance, which indicates that total banks’ assets very potent to actualizing banks’ performance in Nigeria. However, the negative sign suggests as banks’ size increases, overall performance reduces by -0.264238% approximately. Even the lagged value of return on assets (ROA) is significant at the 5 percent level, meaning that previous values of ROA have more impact on deposit money banks’ performance than the current values. Based on the foregoing analysis, we conclude that credit risk management is a significant determinant of banks’ overall performance in Nigeria.
CHAPTER FIVE
SUMMARY OF FINDINGS, CONCLUSION AND RECOMMENDATIONS
5.1 Summary of Findings
On the basis of the findings from this study from chapter four (4) above, the following specific findings are presented:
(a) That capital adequacy ratio plays significant role in deposit money banks’ performance in Nigeria; as it was found to have significant negative impact on performance in the period under investigation.
(b) That non-performing loans is negatively signed and does not have any significant impact on deposit money banks’ performance in Nigeria.
(c) That loans loss provision though positively signed but does not significantly affect the performance of deposit money banks’ performance in Nigeria.
(d) That loan-to-deposit-ratio has a weak negative impact on the performance of deposit money banks in Nigeria.
(e) That bank size plays significant role in deposit money banks’ performance in Nigeria, as it consistently have negative influence on banks’ performance.
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