Research Data and Results of the Depositor Model
4.3 Analysis and Discussions of the Estimation Result
4.3.1 Empirical Result
130
131 indicated significant correlations between the growth of total deposits as seen in column 1a and 1b.
In general, the inflow of total deposits has positive correlations with the CAR, ROA, and NIM variables. The CAR influences the growth of total deposit positively and is significant at the p = 0.01. The influences are consistent both during the blanket guarantee and limited guarantee program, as can be seen in columns 1a and 1b respectively. However, the coefficient of correlation decreases from 0.508 during the blanket guarantee to 0.110 under the limited guarantee period. Similarly, the NIM ratio is used to provide an additional proxy to measure the bank ability to generate profit. The relationship between deposit growth and the NIM ratio is significant at the p value of 0.01, during both the blanket and the limited guarantee periods. Moreover, the ROA ratio, as a proxy for earning quality, indicates that over the period of 2001-2011, this variable is insignificant to determine the growth of total deposits. Interestingly, when the observation period is divided into two sub-periods, the regression results indicate that these relationships are significant. During the sub-period of full guarantee the relationship is positive, whereas under the limited guarantee period the relationship is negative.
In contrast, the NPL, OPEX and LDR variables indicate negative correlations with the growth of total deposits. The correlation between total deposit growth and the indicator for credit risk (NPL), is negative and significant at the p = 0.01 level (see column 1), as predicted by the model. However, column 1b indicates that there is a shift in this relationship from a negative into a positive relationship. The efficiency ratio (OPEX) as expected, had a negative relationship with the growth of total deposits and is significant at the p value of 0.05, during both the blanket and the limited guarantee periods. This coefficient increased from -0.0787 to -0.148 during the limited deposit scheme, reflecting depositors increasing concerned about the bank efficiency measure. Furthermore, the LDR variable as a proxy for liquidity risk has a significant positive relationship with total deposit growth in all periods. However, contrary to expectations, the sign indicates a parallel relationship between the LDR and total deposit growth.
132 Table 4.6 Regression Results: Total Deposit Variable
All Periods Blanket Gr. Limited Gr.
VARIABLES Lag
Expected Signs
TOT_DG (1)
TOT_DG (1a)
TOT_DG (1b)
TOT_DG L1 -0.165*** -0.193*** -0.216***
(0.00482) (0.00240) (0.00408)
CAR L1 (+) 0.159*** 0.508*** 0.110***
(0.0141) (0.0555) (0.0161)
NPL L1 (-) -0.0926*** -0.0411*** 0.547***
(0.00712) (0.00972) (0.0430)
ROA L1 (+) -0.416 0.452** -1.143***
(0.309) (0.226) (0.249)
OPEX L1 (-) -0.105*** -0.0787*** -0.148***
(0.0370) (0.0304) (0.0497)
LDR L1 (-) 0.425*** 0.276*** 0.486***
(0.0151) (0.0281) (0.0147)
NIM L1 (+) -0.0479 0.780*** 0.300**
(0.0757) (0.103) (0.137)
BANK_SIZE (+) 0.0819*** 0.113*** 0.118***
(0.00640) (0.00508) (0.00739)
DEP_IR (+) 0.0982** 0.567*** 0.184***
(0.0460) (0.104) (0.0526)
GDP_GR 0.578*** -0.110 2.602***
(0.0664) (0.101) (0.233)
INF_RT 0.661*** 0.119** 0.215
(0.0627) (0.0572) (0.132)
EXC_RT -0.0616*** 0.271*** -0.253***
(0.0168) (0.0327) (0.0209)
BLA_GR 0.0789***
(0.00570)
LIST_BANK -0.214*** -0.0334** -0.315***
(0.0259) (0.0154) (0.0235)
FORG_BANK -0.314*** -0.198*** -0.299***
(0.0179) (0.0204) (0.0124)
Constant -0.836*** -4.357*** 0.320
(0.196) (0.284) (0.206)
Observations 4,063 2,236 1,799
Number of banks 95 95 95
Wald Test Chi2 24958 108804 57395
0.000*** 0.000*** 0.000***
Sargan Test Chi2 80.97 80.97 89.56
1.000 1.000 1.000
Arellano–Bond test for AR(1) -2.620 -3.458 -1.907
0.0088 0.0005 0.0565
Arellano–Bond test for AR(2) -1.703 -2.380 -2.072
0.1886 0.1173 0.1382
Continued
133 Table 4.6 Continued
This table presents the results from the two-step GMM estimations. Coefficients and standard errors (in parentheses) are from the second step. The Sargan and Arellano–Bond tests are from the second. The estimation uses quarterly observations over the period 2001–2011. The dependent variable is TOT_DG (total deposit growth). The independent variables are: CAR, NPL, ROA, OPEX, NIM, LDR, BANK_SIZE (total asset of banks), and DEP_IR (deposit interest rate). Control variables for general macroeconomic conditions are:
GDP_GR (the growth rate in GDP); INF_RT (inflation rate); and EXC_RT (the annual average of exchange rate IDR/USD scaled in IDR 000). All variables are transformed using the natural logarithmic transformation. Three dummy variables are BLA_GR (1 = Quarter I of 2001 to Quarter of IV 2004 and 0 otherwise), LIST_BANK (1=listed bank and o otherwise and FORG_BANK (1 = foreign bank and 0 otherwise).
* Indicate statistical significance at the 10% level (2-tailed)
** Indicate statistical significance at the 5% level (2-tailed)
*** Indicate statistical significance at the 1% level (2-tailed)
Regression results for the model on time deposit growth and bank fundamentals are summarized in Table 4.7. Column 2 presents regression results over the period from Quarter I of 2001 to Quarter IV of 2011. Results for observation under the blanket guarantee over the period from Quarter I of 2001 to Quarter IV of 2005 are presented in column 2a, and the results for observation under the limited guarantee over the period from Quarter I of 2006 to Quarter IV of 2011, are presented in column 2b. In general, 5 out of the 6 CAMEL indicators (the CAR, NPL, OPEX, NIM, and LDR) used in this study suggest significant impact on the growth of time deposits. On the other hand, the ROA ratio has an insignificant impact on the inflow of time deposits.
Table 4.7 shows that the CAR and NIM ratios had positive impacts on the changes in the amount of time deposits at the 0.01 significance level. The sign of correlation for the CAR variable was consistent under both the blanket and the limited guarantee periods. However, the NIM variable indicates that during the blanket guarantee period, this variable impacted negatively on the changes in the amount of time deposits.
The NPL and OPEX indicators share a similar pattern on the regression results. During the full guarantee period, the relationship between these indicators and the growth of time deposit are negative and significant (p = 0.01), as shown in column 2a. In contrast, during the limited guarantee, time deposits have positive relationships with the NPL and OPEX indicators (see column 2b). Moreover, time deposit had a parallel correlation with the LDR ratio over the period of blanket and limited guarantee periods, as shown in columns 2a and 2b. This result is similar to the regression result on the growth of total deposits.
The ROA variable, however, is the only CAMEL indicator that presents insignificant regression results. These results suggest that under the period of blanket and limited guarantees, this earnings variable did not significantly influence the levels of time deposits.
134 Table 4.7 Regression Results: Time Deposit Variable
All Period Blanket Gr. Limited Gr.
Expected Signs Lag
Expected Signs
TIME_DG (2)
TIME_DG (2a)
TIME_DG (2b)
TIME_DG L1 -0.159*** -0.137*** -0.150***
(0.00251) (0.00297) (0.00237)
CAR L1 (+) 0.260*** 0.167*** 0.202***
(0.0310) (0.0244) (0.0158)
NPL L1 (-) -0.0107 -0.176*** 0.757***
(0.00883) (0.0122) (0.130)
ROA L1 (+) -0.530 0.145 -0.469
(0.374) (0.152) (0.367)
OPEX L1 (-) 0.0297 -0.147*** 0.0820*
(0.0468) (0.0233) (0.0480)
LDR L1 (-) 0.445*** 0.441*** 0.520***
(0.0231) (0.0200) (0.0209)
NIM L1 (+) 0.978*** -0.206*** 0.398**
(0.107) (0.0517) (0.177)
BANK_SIZE (+) 0.129*** 0.0738*** 0.191***
(0.00553) (0.00493) (0.00867)
DEP_IR (+) 0.132 0.363*** 0.146
(0.184) (0.0276) (0.220)
GDP_GR 0.693*** 0.358*** 7.272***
(0.129) (0.0398) (0.274)
INF_RT 0.723*** -0.127** -0.000552
(0.183) (0.0526) (0.110)
EXC_RT -0.117*** 0.247*** -0.404***
(0.0329) (0.0119) (0.0241)
BLA_GR 0.109***
(0.0146)
LIST_BANK -0.173*** -0.186*** -0.141***
(0.0160) (0.0138) (0.0337)
FORG_BANK -0.356*** -0.290*** -0.818***
(0.0332) (0.0166) (0.0406)
Constant -1.240*** -3.403*** 0.224
(0.267) (0.129) (0.223)
Observations 4,025 2,264 1,789
Number of bank 95 95 95
Wald Test 34119 6946 37395
Chi2 0.000*** 0.000*** 0.000***
Sargan Test 86.98 84.25 90.00
Chi2 1.000 1.000 1.000
Arellano–Bond test for AR(1) -4.420 -3.968 -4.320
0.0000 0.0001 0.0000
Arellano–Bond test for AR(2) -2.707 0.166 -1.796
0.1680 0.8683 0.725
Continued
135 Table 4.7 Continued
This table presents the results from the two-step GMM estimations. Coefficients and standard errors (in parentheses) are from the second step. The Sargan and Arellano–Bond tests are from the second. The estimation uses quarterly observations over the period 2001–2011. The dependent variable is TIME_DG (time deposit growth). The independent variables include: CAR, NPL, ROA, OPEX, NIM, LDR, BANK_SIZE (total asset of banks), and DEP_IR (deposit interest rate). Control variables for general macroeconomic conditions include:
GDP_GR(the growth rate in GDP); INF_RT (inflation rate); and EXC_RT (the annual average of exchange rate IDR/USD scaled in IDR000). All variables are transformed using the natural logarithmic transformation. Three dummy variables are BLA_GR (1 = Quarter I of 2001 to Quarter IV of 2004 and 0 otherwise), LIST_BANK (1=listed bank and o otherwise and FORG_BANK (1 = foreign bank and 0 otherwise).
* Indicate statistical significance at the 10% level (2-tailed)
** Indicate statistical significance at the 5% level (2-tailed)
*** Indicate statistical significance at the 1% level (2-tailed)
Table 4.8 shows the regression results of the model on uninsured deposits and bank fundamentals. Uninsured deposits were only measured during the period of the limited insurance scheme, from Quarter I of 2001 to Quarter IV of 2011, as presented in column 3.
As discussed in Chapter 3, within this period, the upper limit on deposit guarantee had changed twice. In order to minimize the impact of the changes in deposit insurance coverage on the growth of uninsured deposits, two sub-periods were included in the model, as shown in columns 3a and 3b. The regression results on uninsured deposits when the maximum guarantee was IDR 100 million for each depositor within a bank (over the period from Quarter II of 2007 to Quarter III of 2008) is presented in column 3a; and those for uninsured deposits when the maximum amount of deposit insured was IDR 2 billion (over the period from Quarter IV of 2008 to Quarter IV of 2011) is presented in column 3b.
In general, the regression results suggest that after the establishment of the Indonesian deposit insurance and the introduction of a limit on the deposit guarantee, the uninsured deposits were significantly influenced by the four CAMEL variables, CAR, ROA, LDR, and NIM ratios, as shown in column 3. The CAR ratios had a positive impact on uninsured deposits at the 0.01 significance level, whereas the NIM variable had a significantly negative impact. As shown in column 3b, whereas the government increased the deposit coverage to a maximum IDR 2 million in response to the evolving global finance crisis in 2008.
Similar to the results on time deposits, the relationship between uninsured deposits and the LDR variable is positive and significant at p value of 0.01. Furthermore, the relationship between uninsured deposit and the ROA is significant at p value of 0.01. However, the sign of relationships for these two variables is inconsistent with the expected direction.
136 Table 4.8 further indicates that, in general, the NPL and OPEX variables do not have a significant impact on uninsured deposits, except during the period of the maximum guarantee of IDR 100 million. As can be seen in column 3a, the NPL and OPEX indicators show a significant impact (at p-values of 0.10 and 0.05 respectively) only over the period from Quarter II of 2007 to Quarter III of 2008.
137 Table 4.8 Regression Results: Uninsured Deposit Variable
Q2'06 - Q4'11 Q2'07 - Q3'08 Q4'08 - Q4'11 VARIABLES Lag
Expected Signs
UIN_DG (3)
UIN_DG (3a)
UIN_DG (3b)
UIN_DG L1 -0.243*** -0.327*** -0.266***
(0.00534) (0.0128) (0.00551)
CAR L1 (+) 0.626*** 0.121 2.110***
(0.0642) (0.0843) (0.133)
NPL L1 (-) -0.342 -0.531* 0.794
(0.399) (0.274) (0.695)
ROA L1 (+) -2.492*** -1.955*** -0.698
(0.708) (0.710) (0.627)
OPEX L1 (-) -0.0237 -0.362** 0.0629
(0.0908) (0.154) (0.0762)
LDR L1 (-) 0.758*** 0.727*** 0.642***
(0.0498) (0.0887) (0.0506)
NIM L1 (+) -1.063** -0.782 -2.460***
(0.474) (0.566) (0.584)
BANK_SIZE (+) 0.177*** 0.457*** 0.655***
(0.0142) (0.0489) (0.0259)
DEP_IR (+) 0.0824 0.482 0.936***
(0.182) (0.522) (0.218)
GDP_GR 9.876*** 14.94*** 7.164***
(0.423) (1.215) (0.444)
INF_RT -5.356*** -4.141*** -3.495***
(0.111) (0.255) (0.152)
EXC_RT -2.436*** -5.159*** -1.736***
(0.0546) (0.360) (0.0686)
LIST_BANK 0.212*** 0.131 -0.151**
(0.0378) (0.115) (0.0690)
FORG_BANK -1.134*** -1.532*** -1.820***
(0.0685) (0.247) (0.164)
Constant 19.18*** 40.13*** 5.178***
(0.540) (3.259) (0.756)
Observations 1,815 561 1,081
Number of bank 95 95 95
Wald Test 20675 2590 38370
Chi2 0.000*** 0.000*** 0.000***
Sargan Test 90.06 65.15 85.87
Chi2 1.000 0.8502 1.000
Arellano–Bond test for AR(1) -5.109 -2.703 -4.336
0.0000 0.0069 0.0000
Arellano–Bond test for AR(2) -2.878 -0.556 -3.160
0.140 0.5782 0. 1600
Continued
138 Table 4.8 Continued
This table presents the results from the two-step Generalized Method of Moments System estimations.
Coefficients and standard errors (in parentheses) are from the second step. The Sargan and Arellano–Bond tests are from the second. The estimation uses quarterly observations over the period 2006–2011. The dependent variable is UIN_DG (uninsured deposit growth). The independent variables include: CAR, NPL, ROA, OPEX, NIM, LDR, BANK_SIZE (total asset of banks), and DEP_IR (deposit interest rate). Control variables for general macroeconomic conditions include: GDP_GR (the growth rate in GDP); INF_RT (inflation rate); and EXC_RT (the annual average of exchange rate IDR/USD scaled in IDR000). All variables are transformed using the natural logarithmic transformation. Two dummy variables are LIST_BANK (1=listed bank and o otherwise and FORG_BANK (1 = foreign bank and 0 otherwise).
* Indicate statistical significance at the 10% level (2-tailed)
** Indicate statistical significance at the 5% level (2-tailed)
*** Indicate statistical significance at the 1% level (2-tailed)
As shown in Table 4.6, Table 4.7 and Table 4.8, the variable of bank size (BANK_SIZE), as hypothesized, has a positive sign at the .01 significance level for all observation periods. The variable of deposit interest rate (DEP_IR) has a significant positive impact on total deposits with a p-value of 0.01. These results were consistent for the blanket and the limited guarantee periods. However, the significant impact of deposit interest rates on the growth of time deposits was found only over the period of full guarantee (Table 4.7 column 2a); whereas the significant impact of deposit interest rates on the growth of uninsured deposits was found during the limited guarantee period, particularly between Quarter IV of 2008 to Quarter IV of 2011, as seen in Table 4.8 column 3b.
The macroeconomic indicators, in general, present consistent results. The indicator of economic growth (GDP_RT) had a significantly positive impact on total deposits, time deposits, and uninsured deposits. The empirical evidence for the inflation rate variable (INF_RT) indicates mixed results. Overall, inflation rate had a significantly positive impact on total and time deposits, particularly during the blanket guarantee period. However, this relationship was found to be insignificant during the limited guarantee period. Interestingly, during the limited guarantee period, the inflation rate had a significantly negative impact on uninsured deposits. With respect to the exchange rate (EXC_RT), the regression results suggest a negative impact of exchange rates on all types of deposits.
The regression results on dummy variable BLA_GR, as shown in Table 4.6 and Table 4.7, suggest a positive impact of the provision of blanket guarantees on deposits. This is an encouraging result for the regulators because of the positive sign on the influence of guarantees on bank viability. Moreover, the regression results for the dummy variables, LIST_BANK and FORG_BANK, indicate a negative significant impact on deposits. These results suggest that both listed banks and foreign banks experienced a lower deposit growth than private and domestic banks.
139 4.3.2 Robustness Test
As a robustness check for the regression results, the present study ran regressions excluding independent variables that are strongly correlated. As can be seen from Table 4.5 correlation matrix, only OPEX and ROA exhibited strong correlations (77.73%). This study used a combination of equations excluding these variables in the model. In general, the results were consistent with the above findings (see Appendix A.3 to A.8 for more detail). As an alternative regression model, the price-based approach was adopted, including implicit deposit interest rates (DEP_IR) as a dependent variable. This is presented in Table 4.9.
According to Martinez-Peria and Schmukler (2001), the expected signs should be opposite to when deposit is used as a dependent variable. The present regression results indicate that for the full period of the study only NPL has an insignificant p value. Importantly, under the blanket guarantee, the results indicate that all CAMEL indicators have a significant influence on deposit interest rates, whereas for the limited guarantee period the results suggest that the impacts of CAR and OPEX were insignificant. From these results it can be concluded that ROA, LDR and NIM were the main drivers for deposit interest movements. The interest rate movements were also significantly influenced by macroeconomic variables, such as GDP, exchange rate, and inflation rate.
For comparative purposes, this study also analyzed the data employing the static panel data procedure, excluding lagged dependent variables as regressors in the model. The results in general are consistent with the dynamic panel data approach where most of the CAMEL variables have significant p-values. However, the R-squared values were relatively low, which might be because the nature of the data used in the dynamic panel data analysis was more appropriate.
140 Table 4.9 Regression Results Depositors Model – Price Effects
All Periods Blanket Gr. Limited Gr.
VARIABLES Lag
Expected
Signs DEP_IR DEP_IR DEP_IR
DEP_IR L1 0.445*** 0.420*** 0.263***
(0.00412) (0.00250) (0.00207)
CAR L1 (-) 0.00472*** 0.0329*** -6.46e-05
(0.00157) (0.00155) (0.000791)
NPL L1 (+) 0.00029 -0.00307*** 0.0647***
(0.00124) (0.000903) (0.00487)
ROA L1 (-) 0.0859*** 0.0442*** 0.0734***
(0.00698) (0.00643) (0.00523)
OPEX L1 (+) 0.0151*** 0.0190*** 0.00190
(0.00238) (0.00117) (0.00157)
LDR L1 (+) 0.0203*** -0.0115*** 0.0540***
(0.00186) (0.00108) (0.000944)
NIM L1 (-) -0.0836*** -0.0829*** -0.0543***
(0.00417) (0.00734) (0.00863)
BANK_SIZE 0.00497*** 0.00251*** 0.00353***
(0.000367) (0.000242) (0.000363)
TOT_DG 0.00346*** 0.00560*** 0.00123***
(0.000439) (0.000658) (0.000329)
GDP_GR 0.311*** 0.281*** 0.243***
(0.00644) (0.00448) (0.00712)
INF_RT 0.170*** 0.261*** 0.0193***
(0.00206) (0.00347) (0.00241)
EXC_RT -0.0156*** -0.0324*** 0.0140***
(0.000883) (0.00116) (0.00124)
BLA_GR 0.00271*** 0.00480***
(0.000301) (0.000329)
LIST_BANK 0.0123*** 0.0186*** 0.0155***
(0.00139) (0.00107) (0.00141)
FORG_BANK 0.0127*** 0.0259*** -0.0138***
(0.00409) (0.00111) (0.00214)
Constant 0.0541*** 0.241*** -0.177***
(0.00968) (0.00894) (0.0102)
Observations 4,069 2,267 1,802
Number of bank 95 95 95
Wald Test Chi2 236570 397748 43113
0.000*** 0.000*** 0.000***
Sargan Test Chi2 93.40 92.89 91.31
1.000 1.000 1.000
continued
141 Table 4.9 continued
Arellano–Bond test for
AR(1) -3.403 -2.308 -2.584
0.0007*** 0.021*** 0.0098***
Arellano–Bond test for
AR(2) 1.921 1.304 1.243
0.1548 0.1923 0.214
This table presents the results from the two-step Generalized Method of Moments System estimations.
Coefficients and standard errors (in parentheses) are from the second step. The Sargan and Arellano–Bond tests are from the second. The estimation uses quarterly observations over the period 2001–2011. The dependent variable is DEP_IR (deposit interest rate). The independent variables include: CAR, NPL, ROA, OPEX, NIM, LDR, BANK_SIZE (total asset of banks), and TOT_DG (total deposit growth). Control variables for general macroeconomic conditions include: GDP_GR (the growth rate in GDP); INF_RT (inflation rate); and EXC_RT (the annual average of exchange rate IDR/USD scaled in IDR000). All variables are transformed using the natural logarithmic transformation. Three dummy variables are BLA_GR (1 = Quarter I of 2001 to Quarter IV of 2004 and 0 otherwise), LIST_BANK (1=listed bank and o otherwise and FORG_BANK (1 = foreign bank and 0 otherwise).
* Indicate statistical significance at the 10% level (2-tailed)
** Indicate statistical significance at the 5% level (2-tailed)
*** Indicate statistical significance at the 1% level (2-tailed)