Economic Behavior of Sonali Bank
Introduction
The financial sector of Bangladesh is very dynamic in nature. Over the years, the interest rates on lending and deposit have changed frequently. The commercial banks, the largest segment of the financial sector, are now able to determine their lending and deposit rates on a competitive basis. As it is known now, a commercial bank is a profit maximizing institution. Hence, it should provide loans to those sectors in which its return is higher. But the nationalized commercial banks (NCBs) are conducting banking business with a different goal. Their prime objective is to maximize the welfare of the society. Our study on ‘Economic Behavior of Sonali Bank’ reveals such a different motto of the largest NCB. The basic objective of the study is to examine the sector-wise lending (Sanctioned, Disbursement, Outstanding, and Recovery & Classified) performance of Sonali Bank. It is hypothesized here that Sonali Bank is a profit maximizer. But our study does not provide sufficient evidence to conclude that Sonali Bank is a profit maximizing institution. While it is true that the whole picture of the overall lending performance of the bank may not available, it will certainly provide valuable insight into how other nationalized commercial banks (NCBs) in general may behave.
With this end in view, we have conducted both descriptive and univariate analysis in sector-wise lending. Besides, we developed two regression models showing Agriculture & General lending (Disbursement) and DIF as dependent variables; DUMMY and Interest rate as independent variables. We also showed sector-wise effective interest rate quarterly to show the real earnings of the bank overtime.
Executive Summary
The Study
The basic study was to analyze the ‘Economic Behavior of Sonali Bank. The hypothesis was that the bank is a profit maximizing institution. During the study, sector-wise lending (Sanctioned, Disbursement, Outstanding, and Recovery & Classified) was analyzed by statistical tool to test the validity of our hypothesis. We tried to make a comprehensive study on the deposit and lending of Sonali Bank by taking quarterly data of the last five years (From 97-01). It was found in our study that Sonali Bank, the largest NCB, not only provides loan to the profitable sectors but also provides advances to the socio-economic sectors, which may not be profitable. Being an NCB, sometimes it has to sanction loans under the guidance of the Ministry. While preparing this paper we have a representative picture of the nationalized commercial banks of Bangladesh. The most crucial problem faced by us in preparing the paper was that the Executives declined to give monthly figures of deposit and advances, as they have not the information in standard form. In addition, sector-wise interest ceiling created a problem for us.
Purpose Of The Study
The purpose of the study was to gain practical knowledge about the banking business. It is not always that a bank provides advances only to the profitable sectors, especially when we are dealing with an NCB. Further it is not the rate of interest only to determine the amount of advances. To clarify all these ideas, the study was conducted.
Methodology
To prepare this paper, we collected the quarterly deposit and lending amount including sector-wise interest rates. Besides, we collected the Annual Reports of Sonali Bank for the years 1996-1999.For statistical analysis; we used MS Excel and SPSS 10.0.
Findings
The findings of this paper do not provide any conclusive remarks that a bank is a profit maximizing institution. Rather, it can be said that a nationalized commercial bank extends its credit to some sectors where interest earning is much lower. But still it cannot be said that Sonali Bank is not making profit. We may conclude that in a semi-liberalized regime, Sonali Bank not only considers profit in extending advances but also considers the socio-economic perspective.
Part – 1: Descriptive Statistics
For this study we have used quarterly data of disbursement, outstanding, and interest rate.
The data were of 20 quarters, from year 1997to year 2001. Now we are individually discuss average disbursements of four sectors export, industrial, general & agricultural. Only in export sector we have collected monthly data. First of all we are showing the average disbursements and trend of export sectors.
Export Loan:
From our data we have seen that in 1997 disbursement in export sector is tk.252.37crore, in1998 it is tk.267.51crore, in 1999 it is tk.293.07crore, in 2000 it is increase to tk.329.03crore and in the 2001 year it is tk.337.76crore. The average disbursement is tk.297.75crore with a standard deviation of tk.58.86crore.The average maximum and minimum disbursements are of tk.443.73crore and tk.147.13crore. From where Sonali bank has received average 87% of its loan disbursement. The lending interest rate is 10% through these five years.
Industrial Loan:
In industrial lending sector Sonali bank lends its money in project loan sector and in working capital sector. In project loan the disbursement is higher than the working capital loan. The average disbursement in this two sub sectors are tk.1387.03crore and tk.227.82crore, with a standard deviation of tk.245.823crore in project loan and tk.99.531crore in working capital. The average maximum and minimum amounts of disbursement are consecutively tk.1815.25crore and tk.1061.44crore in project loan and tk.465.01 crore & tk.80.25 crore in working capital loan. From this figure it is seen that disbursement in project lending is gradually increasing. Where there is a fluctuation remains in working capital lending sector through the last five years. About 47.34% is recovered in industrial sector.
General Loan:
In general lending sector average disbursement amount is tk.389.80crore with a standard deviation of tk.74.7422 crore. The maximum amount of disbursement is tk.503.25crore and minimum amount is tk.269.50 crore. The average amount of classified loan is tk.295.69crore. Average received is 44.74% and outstanding is tk.4306.65 crore. The maximum and minimum amount of loan disbursement is tk.389.80 crore and tk.391.90 crore.
Agriculture:
In agricultural sector the average amount of loan disbursement is tk. 5860.30 crore with a standard deviation of tk. 867.3267 crore. The average maximum and minimum amount is tk.7117.16 crore and tk.4456.42 crore. Average loan received is41.08%.
Interest Rates:
| Periods | General | Agriculture | Project Loan | Working Capital | Export | |||||
| Min | Max | Min | Max | Min | Max | Min | Max | Min | Max | |
| 1997 | 13.63 | 13.63 | 13.87 | 13.87 | 14.08 | 14.08 | 15.50 | 15.50 | 10.00 | 10.00 |
| 1998 | 13.63 | 13.63 | 13.87 | 13.87 | 14.08 | 14.08 | 15.50 | 15.50 | 10.00 | 10.00 |
| 1999 | 12.75 | 13.63 | 12.75 | 12.75 | 13.83 | 14.17 | 14.50 | 14.50 | 10.00 | 10.00 |
| 2000 | 12.75 | 12.75 | 12.75 | 12.75 | 14.17 | 14.17 | 14.00 | 14.00 | 10.00 | 10.00 |
| 2001 | 12.00 | 12.75 | 12.00 | 12.00 | 13.38 | 14.17 | 14.00 | 14.00 | 9.00 | 10.00 |
Descriptive Statistics:
General loans |
|||||
| Variable | Mean | Median | SD | Maximum | Minimum |
| Overdue | 4306.65 | 4384.80 | 451.0999 | 5096.43 | 3665.75 |
| Disbursement | 389.80 | 391.90 | 74.7422 | 503.25 | 269.50 |
| Lending rate | 0.1562 | 0.1567 | 0.0022 | 0.1567 | 0.1467 |
| Effective interest rate | 0.1456 | 0.1460 | 0.0031 | 0.1512 | 0.1371 |
Agriculture loans |
|||||
| Variable | Mean | Median | SD | Maximum | Minimum |
| Overdue | 5762.61 | 5747.34 | 591.5518 | 6692.32 | 4651.83 |
| Disbursement | 5860.30 | 6017.42 | 867.3267 | 7117.14 | 4456.42 |
| Lending rate | 0.1320 | 0.1363 | 0.0052 | 0.1363 | 0.1200 |
| Effective interest rate | 0.0728 | 0.0641 | 0.0157 | 0.1018 | 0.0547 |
Project loans |
|||||
| Variable | Mean | Median | SD | Maximum | Minimum |
| Overdue | 1864.21 | 1857.88 | 264.6571 | 2237.29 | 1455.00 |
| Disbursement | 1387.03 | 1292.43 | 245.8230 | 1815.25 | 1061.44 |
| Lending rate | 0.1407 | 0.1408 | 0.0018 | 0.1417 | 0.1338 |
| Effective interest rate | 0.0985 | 0.1007 | 0.0058 | 0.10.58 | 0.0841 |
Working Capital |
|||||
| Variable | Mean | Median | SD | Maximum | Minimum |
| Overdue | 420.90 | 376.50 | 137.0546 | 625.00 | 217.17 |
| Disbursement | 227.82 | 208.48 | 99.5314 | 465.01 | 80.25 |
| Lending rate | 0.1470 | 0.1450 | 0.0070 | 0.1550 | 0.1400 |
| Effective interest rate | 0.0994 | 0.1031 | 0.0142 | 0.1174 | 0.0629 |
Export Loan |
|||||
| Variable | Mean | Median | SD | Maximum | Minimum |
| Overdue | 2048.18 | 2058.43 | 172.0636 | 2414.41 | 1689.65 |
| Disbursement | 893.25 | 888.62 | 120.3506 | 1104.96 | 605.61 |
| Lending rate | 0.0995 | 0.1000 | 0.0022 | 0.1000 | 0.0900 |
| Effective interest rate | 0.0891 | 0.0889 | 0.0028 | 0.0948 | 0.0846 |
Progress at a Glance:
Progress at a Glance |
||||||||
| Year | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 |
| Total Income | 691.75 | 696.4 | 726.26 | 760.52 | 851.75 | 983.65 | 1109.44 | 1242.96 |
| Total Expenditure | 687.1 | 694.44 | 664.98 | 688.95 | 826.95 | 970.44 | 1099.25 | 1230.34 |
| Net Profit | 4.47 | 1.96 | 61.28 | 71.57 | 24.8 | 13.21 | 10.19 | 12.62 |
| Capital | 242.69 | 327.22 | 327.22 | 327.22 | 327.22 | 327.22 | 327.22 | 327.22 |
| Reserve Fund | 38.42 | 40.32 | 89.32 | 150.32 | 174.32 | 186.63 | 193.88 | 203.6 |
| Deposits | 7667.84 | 8468.46 | 10141.08 | 11083.25 | 12383.45 | 13606.17 | 15170.65 | 16937.27 |
| Advances | 4869.33 | 5363.05 | 5389.29 | 6582.99 | 7611.62 | 8545.14 | 9444.13 | 10056.19 |
| Total Foreign | ||||||||
Exchange Business4012.524066.136599.458265.097559.928928.9210089.18N/ANo. of Employee26243262182567725636247622612526518N/ANo. of Branches13131310130713031300131313111306
Regression Model:
Our hypothesis is that bank is a profit maximizer. As a profit maximizer the regression model of this bank should be
It implies that bank will disburse more loans where the rate of return or interest rate will be higher. According to our model
This regression model is completely opposite to the profit maximizing condition. So from this model it is obvious that Sonali Bank is not a profit maximizer. Like other national banks it works for the social welfare of our country. Its loan disbursement does not depend on rate of return rather its investment sectors are those from where society as a whole will get maximum benefit. For example, Sonali bank is extending a huge loan in agriculture loan all though the rate of return from this sector is very low. The only reason is social welfare that is dedicated to a great number of people who are leading below standard life.
Let us take the null hypothesis that Sonali bank does not discriminate in providing advance to General Loan and Agriculture Loan sector with respect to interest rate.
The relationship between loan and dummy is significant. It is also found that the relationship between loan and interest rate is negative and significant. So the null hypothesis is rejected. The coefficient of determination (R2) is .975, which indicates that this model explains as much as 97% variations in dependent variables. In a word, it is evident that it is a significant model and the coefficients of independent variables are also significant.
The relationship between DIF and Dummy is negative but insignificant. On the other hand, the relationship between interest rate and DIF is positive but insignificant. The null hypothesis is accepted. The coefficient of determination (R2) is 0.104, which indicates that this model explains 10% variation in dependent variables. The coefficient of correlation is .323, which indicates lower positive relationship.
Although the 1st regression model is significant the 2nd model provides insignificant relationship. This contrasting result is due to the problem of Autocorrelation.
T Test
Let us the null hypothesis that there is no significant mean difference between agriculture loan and general loan. But the calculated t value is more than table value. So the null hypothesis must be rejected. So the samples of agriculture and general loan do not truly represent the population. Coz, lack of sufficient data.
Regression1: Export and Project loan
Let us take the null hypothesis that Sonali bank does not discriminate in providing advance to export and project loan sector with respect to interest rate.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | ||||
| .801 | .642 | .623 | 193.2952 |
a Predictors: (Constant), DUMMY, EXINTRAT
ANOVA
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | ||||||
| Regression | 2479125.629 | 2 | 1239562.814 | 33.176 | .000 | |
| Residual | 1382432.387 | 37 | 37363.037 | |||
| Total | 3861558.015 | 39 |
a Predictors: (Constant), DUMMY, EXINTRAT
b Dependent Variable: EXPORT
Coefficients
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||
| Model | ||||||
| B | Std. Error | Beta | ||||
| 1 | ||||||
| (Constant) | 3662.134 | 2174.430 | 1.684 | .101 | ||
| EXINTRAT | -161.716 | 154.530 | -1.077 | -1.047 | .302 | |
| DUMMY | -1159.810 | 639.359 | -1.866 | -1.814 | .078 |
a Dependent Variable: EXPORT
The sign of the coefficients of b1 and b2 are negative. Thereby we can say that it is not a profit-maximizing bank Here table value is less than two. So null hypothesis is accepted.
Regression2: Export and working capital
Let us take the null hypothesis that Sonali bank does not discriminate in providing advance to export and working capital loan sector with respect to interest rate.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | ||||
| .952 | .905 | .900 | 111.8182 |
a Predictors: (Constant), DUMMY, EXINTRAT
Coefficients
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||
| Model | ||||||
| B | Std. Error | Beta | ||||
| 1 | ||||||
| (Constant) | 97.124 | 516.543 | .188 | .852 | ||
| EXINTRAT | 8.891 | 35.098 | .062 | .253 | .801 | |
| DUMMY | 707.660 | 170.423 | 1.012 | 4.152 | .000 |
a Dependent Variable: EXPORT
The coefficient of dummy is positive and significant. So we can say that in this sector bank considers interest rates in providing loans.
Regression 3: Export and general loan sector
Let us take the hypothesis that Sonali bank does not discriminate in providing advance to export and general loan sector with respect to interest rate. So it is our null hypothesis.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | ||||
| .935 | .874 | .867 | 99.5431 |
a Predictors: (Constant), DUMMY, EXINTRAT
ANOVA
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | ||||||
| Regression | 2549360.174 | 2 | 1274680.087 | 128.641 | .000 | |
| Residual | 366626.944 | 37 | 9908.836 | |||
| Total | 2915987.118 | 39 |
a Predictors: (Constant), DUMMY, EXINTRAT
b Dependent Variable: EXPORT
Coefficients
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||
| Model | ||||||
| B | Std. Error | Beta | ||||
| (Constant) | 1764.468 | 1128.236 | 1.564 | .126 | ||
| EXINTRAT | -88.007 | 72.216 | -.927 | -1.219 | .231 | |
| DUMMY | 4.452 | 410.674 | .008 | .011 | .991 |
a Dependent Variable: EXPORT
Since the table value is less than 2, so null hypothesis is rejected. Thus we can say that Sonali bank has discrimination is extending credit to export and general loan with respect to interest rate.
Regression4:
Export and agricultural loan sector
Let us take the hypothesis that Sonali bank does not discriminate in providing advance to export and agricultural loan sector with respect to interest rate. So it is our null hypothesis.
Variables Entered/Removed
| Model | Variables Entered | Variables Removed | Method |
| 1 | |||
| DUMMY, |
EXINTRAT.Enter
a All requested variables entered.
b Dependent Variable: EXPORT
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | ||||
| .985 | .970 | .969 | 457.3613 |
a Predictors: (Constant), DUMMY, EXINTRAT
ANOVA
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | ||||||
| Regression | 253544228.829 | 2 | 126772114.415 | 606.045 | .000 | |
| Residual | 7739637.554 | 37 | 209179.393 | |||
| Total | 261283866.383 | 39 |
a Predictors: (Constant), DUMMY, EXINTRAT
b Dependent Variable: EXPORT
Coefficients
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||
| Model | ||||||
| B | Std. Error | Beta | ||||
| 1 | ||||||
| (Constant) | 19887.438 | 2457.225 | 8.093 | .000 | ||
| EXINTRAT | -1062.944 | 186.041 | -.694 | -5.713 | .000 | |
| DUMMY | -8417.897 | 621.059 | -1.647 | -13.554 | .000 |
a Dependent Variable: EXPORT
Since the table value is greater than 2, so null hypothesis is rejected. Thus we can say that Sonali bank has discrimination in extending credit to export and agricultural loan with respect to interest rate.
Regression5:
Project loan and working capital
Let us take the hypothesis that Sonali bank does not discriminate in providing advance to project loan and working capital loan sector with respect to interest rate. So it is our null hypothesis.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | ||||
| .954 | .910 | .905 | 190.0306 |
a Predictors: (Constant), DUMMY, PROINTRA
ANOVA
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | ||||||
| Regression | 13437898.053 | 2 | 6718949.026 | 186.061 | .000 | |
| Residual | 1336130.406 | 37 | 36111.633 | |||
| Total | 14774028.458 | 39 |
a Predictors: (Constant), DUMMY, PROINTRA
b Dependent Variable: PROJECTL
Coefficients
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||
| Model | ||||||
| B | Std. Error | Beta | ||||
| 1 | ||||||
| (Constant) | 154.678 | 892.680 | .173 | .863 | ||
| PROINTRA | 4.976 | 60.658 | .005 | .082 | .935 | |
| DUMMY | 1162.351 | 71.263 | .956 | 16.311 | .000 |
a Dependent Variable: PROJECTL
Since the table value of dummy is greater than 2, so null hypothesis is rejected. Thus we can say that Sonali bank has discrimination in extending credit to project loan and working capital loan with respect to interest rate. But coefficient of
Regression6:
Project loan and general loan sector
Let us take the hypothesis that Sonali bank does not discriminate in providing advance to project loan and general loan sector with respect to interest rate. So it is our null hypothesis.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | ||||
| .944 | .890 | .885 | 182.0659 |
a Predictors: (Constant), DUMMY, PROINTRA
ANOVA
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | ||||||
| Regression | 9972583.019 | 2 | 4986291.510 | 150.425 | .000 | |
| Residual | 1226475.192 | 37 | 33147.978 | |||
| Total | 11199058.211 | 39 |
a Predictors: (Constant), DUMMY, PROINTRA
b Dependent Variable: PROJECTL
Coefficients
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||
| Model | ||||||
| B | Std. Error | Beta | ||||
| 1 | ||||||
| (Constant) | 2472.481 | 2273.892 | 1.087 | .284 | ||
| PROINTRA | -133.334 | 145.552 | -.202 | -.916 | .366 | |
| DUMMY | 790.366 | 233.048 | .747 | 3.391 | .002 |
a Dependent Variable: PROJECTL
The t value of prointrat provides the null hypothesis is accepted. But the t value of dummy tends to reject the null hypothesis is rejected. So there is no conclusive decision to be made. There may exist autocorrelation and insufficiency of data.
Regression7:
Project loan and agricultural loan sector
Let us take the hypothesis that Sonali bank does not discriminate in providing advance to project loan and agricultural loan sector with respect to interest rate. So it is our null hypothesis.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | ||||
| .981 | .962 | .960 | 468.4055 |
a Predictors: (Constant), DUMMY, PROINTRA
ANOVA
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | ||||||
| Regression | 207424293.193 | 2 | 103712146.596 | 472.700 | .000 | |
| Residual | 8117935.912 | 37 | 219403.673 | |||
| Total | 215542229.105 | 39 |
a Predictors: (Constant), DUMMY, PROINTRA
b Dependent Variable: PROJECTL
Regression8:
Working capital and general loan sector
Let us take the hypothesis that Sonali bank does not discriminate in providing advance to working capital and general loan sector with respect to interest rate. So it is our null hypothesis.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | ||||
| .689 | .474 | .446 | 88.9243 |
a Predictors: (Constant), DUMMY, WORINTRA
ANOVA
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | ||||||
| Regression | 264143.708 | 2 | 132071.854 | 16.702 | .000 | |
| Residual | 292578.621 | 37 | 7907.530 | |||
| Total | 556722.329 | 39 |
a Predictors: (Constant), DUMMY, WORINTRA
b Dependent Variable: WORKCAPI
Coefficients
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||
| Model | B | Std. Error | Beta | |||
| 1 | (Constant) | 182.579 | 436.435 | .418 | .678 | |
| WORINTRA | 13.266 | 27.912 | .077 | .475 | .637 | |
| DUMMY | -149.770 | 38.081 | -.635 | -3.933 | .000 |
a Dependent Variable: WORKCAPI
Table value of interest rate is less than 2 so null hypothesis is rejected. But table value of dummy is grater than 2. So null hypothesis is accepted. There is possibility of having autocorrelation.
Regression9: Working capital and agricultural loan sector
Let us take the hypothesis that Sonali bank does not discriminate in providing advance to working capital and agricultural loan sector with respect to interest rate. So it is our null hypothesis.
Model Summary
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | ||||
| .982 | .964 | .962 | 566.1354 |
a Predictors: (Constant), DUMMY, WORINTRA
ANOVA
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | ||||||
| Regression | 319870151.362 | 2 | 159935075.681 | 499.003 | .000 | |
| Residual | 11858844.918 | 37 | 320509.322 | |||
| Total | 331728996.280 | 39 |
a Predictors: (Constant), DUMMY, WORINTRA
b Dependent Variable: WORKCAPI
Coefficients
| Unstandardized Coefficients | Standardized Coefficients | t | Sig. | |||
| Model | ||||||
| B | Std. Error | Beta | ||||
| 1 | ||||||
| (Constant) | 11512.570 | 1980.144 | 5.814 | .000 | ||
| WORINTRA | -428.316 | 149.744 | -.143 | -2.860 | .007 | |
| DUMMY | -4988.503 | 287.644 | -.866 | -17.343 | .000 |
a Dependent Variable: WORKCAPI
Table value of interest rate and dummy is grater than 2 so null hypotheses is rejected
Part – 3: Effective Lending Rate
| Export Loan | Project Loan | Working Capital | Agriculture Loan | General Loan |
| 0.0872 | 0.1035 | 0.1069 | 0.0872 | 0.1481 |
| 0.0889 | 0.1045 | 0.1111 | 0.0889 | 0.1512 |
| 0.0874 | 0.1047 | 0.1144 | 0.0874 | 0.1485 |
| 0.0897 | 0.1058 | 0.1174 | 0.0897 | 0.1501 |
| 0.0906 | 0.1057 | 0.1122 | 0.0906 | 0.1441 |
| 0.0885 | 0.1032 | 0.1002 | 0.0885 | 0.1472 |
| 0.086 | 0.1019 | 0.1106 | 0.086 | 0.1451 |
| 0.0847 | 0.1009 | 0.1074 | 0.0847 | 0.1482 |
| 0.0898 | 0.1016 | 0.0629 | 0.0898 | 0.144 |
| 0.0874 | 0.1011 | 0.0866 | 0.0874 | 0.1466 |
| 0.0882 | 0.0955 | 0.074 | 0.0882 | 0.1439 |
| 0.0889 | 0.0941 | 0.1078 | 0.0889 | 0.1465 |
| 0.0891 | 0.0947 | 0.0995 | 0.0891 | 0.1429 |
| 0.0897 | 0.0964 | 0.0935 | 0.0897 | 0.1462 |
| 0.0889 | 0.0841 | 0.0949 | 0.0889 | 0.1435 |
| 0.0896 | 0.0949 | 0.0915 | 0.0896 | 0.1464 |
| 0.0946 | 0.0921 | 0.0829 | 0.0946 | 0.1427 |
| 0.0948 | 0.0919 | 0.101 | 0.0948 | 0.1458 |
| 0.0943 | 0.0932 | 0.1079 | 0.0943 | 0.1439 |
| 0.0846 | 0.1004 | 0.1053 | 0.0846 | 0.1371 |
Part – 4: Deposit Interest Rate
| 1997 | 1998 | 1999 | 2000 | 2001 | |
| 1.Savings Deposit | 7.75% | 7.75% | 7.75% | 7.00% | 6.00% |
| 2.Short term Deposit | 6.00% | 6.00% | 6.00% | 5.00% | 4.00% |
| 3.Fixed Deposit: | |||||
| 3 months & more but less than 6 months | 8.25% | 8.75% | 8.75% | 8.25% | 7.50% |
| 6 months & more but less than 1year | 8.50% | 9.00% | 9.00% | 8.50% | 8.00% |
| 1year & more but less than 2 years | 8.75% | 9.25% | 9.25% | 8.75% | 8.25% |
| 2years & more but less than 3 years | 9.25% | 9.50% | 9.50% | 9.25% | 8.50% |
| 3years & more but at best 5 years | 9.75% | 10.00% | 10.00% | 9.50% | 9.00% |
| 4. Deposit Pension Scheme | 15.00% | 15.00% | 15.00% | 15.00% | 15.00% |
| 5.Special Deposit Pension Scheme | |||||
| For 5 years | 10.00% | 10.00% | 10.00% | 10.00% | 10.00% |
| For 10 years | 12.00% | 12.00% | 12.00% | 12.00% | 12.00% |
Part – 5: Regression
Disbursement with sector wise effective return
Descriptive Statistics
| Mean | Std. Deviation | N | |
| TOTDISBU | |||
| 8758.1995 | 1192.3190 | 20 | |
| EXPORT | |||
| 79.7576 | 12.0456 | 20 | |
| PROJECT | |||
| 135.8044 | 20.4071 | 20 | |
| WORKING | |||
| 22.9020 | 10.8420 | 20 | |
| AGRICUL | |||
| 523.4502 | 86.6860 | 20 | |
| GENERAL | |||
| 56.7510 | 10.9766 | 20 |
Variables Entered/Removed
| Model | Variables Entered | Variables Removed | Method |
| 1 | |||
| GENERAL, |
PROJECT,
WORKING,
AGRICUL,
EXPORT.Enter
a All requested variables entered.
b Dependent Variable: TOTDISBU
Model Summary
| R | R Square | Adjusted R Square | Std. Error of the Estimate | Change Statistics | |||||
| Model | |||||||||
| R Square Change | F Change | df1 | df2 | Sig. F Change | |||||
| 1 | |||||||||
| .989 | .978 | .970 | 205.3790 | .978 | 125.273 | 5 | 14 | .000 |
a Predictors: (Constant), GENERAL, PROJECT, WORKING, AGRICUL, EXPORT
ANOVA
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | ||||||
| Regression | 26420339.899 | 5 | 5284067.980 | 125.273 | .000 | |
| Residual | 590527.263 | 14 | 42180.519 | |||
| Total | 27010867.162 | 19 |
a Predictors: (Constant), GENERAL, PROJECT, WORKING, AGRICUL, EXPORT
b Dependent Variable: TOTDISBU
Coefficients
| Unstandardized Coefficients | |||
Standardized CoefficientstSig.95% Confidence Interval for B
Model BStd. ErrorBeta Lower BoundUpper Bound1(Constant)133.152387.319 .344.736-697.565963.869 EXPORT7.6839.302.078.826.423-12.26927.634 PROJECT7.4863.461.1282.163.048.06414.909 WORKING15.4115.532.1402.786.0153.54627.275 AGRICUL11.3671.113.82610.217.0008.98113.754 GENERAL12.2025.264.1122.318.036.91123.493
a Dependent Variable: TOTDISBU
Bibliography
- SONALI BANK: ANNUAL REPORT 1996 – 1999.
- SONALI BANK: TABLES OF RATES.
- SONALI BANK: EXPORT LOAN QUARTERLY DATA.
- SONALI BANK: INDUSTRIAL LOAN QUARTERLY DATA.
- SONALI BANK: DEPOSIT QUARTERLY DATA.
- SONALI BANK: AGRICULTURE LOAN QUARTERLY DATA.
- SONALI BANK: GENERAL LOAN QUARTERLY DATA.
- STATISTICS FOR BUSINESS AND ECONOMICS – JAMES T. MCCLAVE, BENSON.
- BASIC ECONOMATRICS – DAMODAR N. GUJARATI.
- BUSINESS STATISTICS – S. P. GUPTA & M. P. GUPTA.
| Year | Agriculture Loan | Effective Interest Rate | Industrial Project Loan | Effective Interest Rate | Industrial Working Capital | Effective Interest Rate | Export Loan | Effective Interest Rate | General Loan | Effective Interest Rate |
| 1997 | 13.63 | 8.72 | 14.08 | 10.35 | 15.50 | 10.69 | 10.00 | 8.72 | 15.67 | 14.81 |
| 13.63 | 8.89 | 14.08 | 10.45 | 15.50 | 11.11 | 10.00 | 8.89 | 15.67 | 15.12 | |
| 13.63 | 8.74 | 14.08 | 10.47 | 15.50 | 11.44 | 10.00 | 8.74 | 15.67 | 14.85 | |
| 13.63 | 8.97 | 14.08 | 10.58 | 15.50 | 11.74 | 10.00 | 8.97 | 15.67 | 15.01 | |
| 1998 | 13.63 | 9.06 | 14.08 | 10.57 | 15.50 | 11.22 | 10.00 | 9.06 | 15.67 | 14.41 |
| 13.63 | 8.85 | 14.08 | 10.32 | 15.50 | 10.02 | 10.00 | 8.85 | 15.67 | 14.72 | |
| 13.63 | 8.60 | 14.08 | 10.19 | 15.50 | 11.06 | 10.00 | 8.60 | 15.67 | 14.51 | |
| 13.63 | 8.47 | 14.08 | 10.09 | 15.50 | 10.74 | 10.00 | 8.47 | 15.67 | 14.82 | |
| 1999 | 13.63 | 8.98 | 14.08 | 10.16 | 14.50 | 6.29 | 10.00 | 8.98 | 15.67 | 14.40 |
| 13.63 | 8.74 | 14.08 | 10.11 | 14.50 | 8.66 | 10.00 | 8.74 | 15.67 | 14.66 | |
| 13.63 | 8.82 | 13.83 | 9.55 | 14.50 | 7.40 | 10.00 | 8.82 | 15.67 | 14.39 | |
| 12.75 | 8.89 | 14.17 | 9.41 | 14.50 | 10.78 | 10.00 | 8.89 | 15.67 | 14.65 | |
| 2000 | 12.75 | 8.91 | 14.17 | 9.47 | 14.00 | 9.95 | 10.00 | 8.91 | 15.67 | 14.29 |
| 12.75 | 8.97 | 14.17 | 9.64 | 14.00 | 9.35 | 10.00 | 8.97 | 15.67 | 14.62 | |
| 12.75 | 8.89 | 14.17 | 8.41 | 14.00 | 9.49 | 10.00 | 8.89 | 15.67 | 14.35 | |
| 12.75 | 8.96 | 14.17 | 9.49 | 14.00 | 9.15 | 10.00 | 8.96 | 15.67 | 14.64 | |
| 2001 | 12.75 | 9.46 | 14.17 | 9.21 | 14.00 | 8.29 | 10.00 | 9.46 | 15.67 | 14.27 |
| 12.75 | 9.48 | 14.17 | 9.19 | 14.00 | 10.10 | 10.00 | 9.48 | 15.67 | 14.58 | |
| 12.75 | 9.43 | 14.17 | 9.32 | 14.00 | 10.79 | 10.00 | 9.43 | 15.67 | 14.39 | |
| 12.00 | 8.46 | 13.38 | 10.04 | 14.00 | 10.53 | 9.00 | 8.46 | 14.67 | 13.71 |