Bank Indonesia applied interest rate base in 2005 using the SBI (Certificate of Bank Indonesia) rate as an instrument policy. The research will begin to review the effect of SBI rate on interest rate in the financial market. Furthermore, it will investigate the relationship between market interest rate and consumption, also the relationship between lending rate and investment by constructing a long-term and short-term model.
The model must provide a strong explanation of the effect of the interest rate on the real sector (consumption and investment). Hopefully, it can provide a recommendation to Bank Indonesia according to using interest rate as an instrument policy in the inflation targeting framework. However, it only focuses on the effect of the interest rate on consumption and investment when constructing the long-run and short-run model.
The sample period is fifteen years to obtain the long-term effect of the interest rate on consumption and investment. The SBI rate as the central bank rate directs the interest rate in the financial market, such as the commercial bank rate and the lending rate. The difference between the nominal interest rate and expected inflation can be defined as the real interest rate.
The first interest rate model shows the effect of the SBI rate on the commercial bank rate, and the second model indicates the effect of the SBI rate on the lending rate.
EMPIRICAL RESULT AND ANALYSIS
The Effect of SBI Rate to Interest Rate at Financial System
To investigate the relationship between SBI rate and commercial bank rate and lending rate, we develop simple ordinary least square (OLS) regression model. The result of the two interest rate models is presented in table IV.3 and IV.4. The probability t of the ISBI variable (SBI rate) is 0.00 which means that we can accept the alternative hypothesis that the ISBI variable is significantly related to the commercial bank rate.
Meanwhile, the R-squared is 0.75, which means that the ISBI variable can explain 75% of the interest rate variable, and its coefficient is 1.228, which means that an increase of 1% in ISBI can increase the interest rate of a commercial bank in the financial market by 1.228%. It proves that the interest rate of SBI as a market guideline greatly affects the interest rate of the commercial bank. Similarly, we found that the t-probability of the ISBI variable (SBI interest rate) is 0.00, which means that we accept the alternative hypothesis that the ISBI variable is related to the nominal lending rate.
On the other hand, we found that the ISBI coefficient is 0.359 smaller compared to the first interest rate model. This means that a 1% increase in ISBI can raise the lending rate in the financial market by only 0.359%. This situation can be explained by data on banking sector credits, which are still low, as banks are still reluctant to place funds in real sectors.
Banks prefer to invest on the low risk instrument, for example buying SBI from Bank Indonesia. To examine the causality between SBI interest and both the commercial bank's interest and lending interest, we do Granger Causality tests with the result shown in Table IV.5. Since the t-probability is below 1%, we can reject both the null hypotheses that the commercial bank rate does not cause the SBI rate and the SBI rate does not cause the commercial rate.
Meanwhile, we cannot reject the null hypotheses that lending rate does not Granger cause SBI rate because t-probability above 1%. On the other hand, we can reject the null hypothesis that the SBI rate does not Granger cause the lending rate. This means that the Granger causality runs one way from SBI rate to lending rate, not the other way around.
The Effect of Interest Rate to both Consumption and Investment
- Model of Consumption
- Model of Investment
We perform unit root test on each variable using three lags because we want to know which lag has no serial correlation with residual in the variable. Based on economic theory, the real disposable income has a positive relationship with the real consumption with coefficient is about one in the long run. Furthermore, we estimate the short-term dynamic model obtained by ECM in the long-term comparison by Johansen's technique.
We find that ∆3∆ln(DI) is significant (t-prob is 0.0005 under 1%), implying that lags in disposable income have the same effect in the long run. The theory says that real consumption will fall in the short run when the real interest rate rises. The two-month lag ECM (ecmt-2) has a t-probability of 0.00, which is highly significant, implying that the ECM is still persistent in the system for the past three quarters and influences other variables.
However, we still want to find out whether the model has structural change in the linkage between the dependent variable DLCS and other explanatory variables. However, we can use recursive procedure in the PCGIVE software to examine the stability of the model estimates. Moreover, the prediction of Chow test (figure IV.14) which shows the line is below the limit line (blue line).
To examine the effect of real borrowing rate on long-run real investment, we cointegrate the logarithm of investment, logarithm of real borrowing rate, and logarithm of real income as endogenous variable with three lags of each variable. The result of vector co-integration into the long-term investment model is shown in Table IV.12. It can be interpreted that ECM is still present in the system during the past month and is affecting other variables.
The use of the Chow test is intended to investigate the structural change in the relationship between the dependent variable (DLCS) and other explanatory variables. Using a recursive procedure in the PCGIVE software, we investigate the stability of the model estimates. Meanwhile, in Figure IV.17, we achieve that the line for is above the limit in several periods (blue line).
However, the Chow breakpoint test (Figure IV.18) shows that a structural break did not occur in any period. In addition, the Chow test prediction (Figure IV.19) shows a line below the limit (blue line).
The Effect of both Consumption and Investment to GDP Growth
We can conclude that the dynamic model does not have a structural break in the sample of the period June 1990 √ December 2002. The t-probability of the variable logarithm of consumption is 0.00, which means that it accepts the alternative hypothesis that the ISBI variable is related to the nominal interest rate. The consumption coefficient is 0.70, which means that a 1% increase in real consumption can increase output by 0.70%.
The t-probability of variable real investment is 0.00, which means that the alternative hypothesis that variable investment is related to real GDP can be accepted. The coefficient of investment is 0.244, which means that a 1% increase in investment can increase output by 0.244%. The intercept term in this model cannot be interpreted because it has no particular physical meaning.
Although the model indicates the strong correlation between both consumption and investment and output, we still need to find the causality among them by Granger Causality test. Due to the t-probability below 5%, we can reject the null hypotheses, output does not Granger cause consumption and consumption does not cause production. Meanwhile, we cannot reject the null hypothesis that investment does not cause output because t-probability above 5%.
On the other hand, we can reject the null hypothesis that Granger production does not cause investment. This means that Granger causality runs in one direction from output to investment, but not in the other direction.
SUMMARY AND CONCLUSION 1 Summary
Conclusion
As mentioned earlier, the SBI rate can be a guide for the financial market to determine the interest rate. Bank Indonesia's policy of raising SBI rates will be followed by markets to raise their interest rates, such as commercial bank rates and lending rates. Although their effect is not comparable, they still follow the trend of the SBI rate as that of the central bank.
The interest rate can affect the real sector, where an increase in the interest rate can lower both consumption and investment. Currently, they can affect real GDP, meaning that increasing either of them can increase real GDP. We can conclude that an increased SBI rate can shrink real GDP through the financial market.
Therefore, the central bank may be cautious in using the interest rate as a policy instrument in the context of inflation targeting. They need to consider the effect of changes in the SBI rate on economic growth, even if it is only a small effect. This research does not indicate at what level SBI would achieve both high economic growth and low inflation.
It can be developed by simultaneous models to get optimal SBI rate to be used. However, it can explain the effect of SBI rate to GDP growth gradually through the financial system. Bank Indonesia, ≈The Short-term Forecast Model of Indonesian Economy (SOFIE)∆, Directorate of Economic Research and Monetary Policy, 2001.
Iljas, Achjar, ≈Peran Bank Indonesia dalam Pengendalian Inflasi∆, Bank Indonesia, 1999 Iljas, Achjar, ≈Inflation Targeting and Central Bank Accountability∆, Bank Indonesia, 2001 Johansen, S. Walsh, Carl E., ≈Is New Zealand »s Reserve Bank Act of 1989 Kontrak optimal dengan bank sentral?∆, Jurnal Uang, Kredit dan Perbankan. Warjiyo, Perry, ∆Menuju Penargetan Inflasi: Kasus Indonesia∆, Bank Indonesia, 2001 Warjiyo, Perry dan Agung, Juda, ≈Mekanisme Transmisi Kebijakan Moneter di Indonesia∆,.
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