Silviase/jgov_v1.4_full_ann huggingface dataset:
real GNP growth, and vice versa. This result could indicate that the authorities were trying to adjust fluctuation of business cycle by controlling interest rate, but at the same time, the interest rate was being affected by the fluctuations in the business cycle.

Many interpretations could be considered on the mechanism of interest rate affecting real GNP growth. One possible route may be through the effect on equipment investment, while real GNP growth affects interest rate by the shift in money demand function. Even so, we can interpret that authorities were carefully trying to control real economic growth by influencing the interest rate, but at the same time considering the effect on interest rate from the real economic growth. In traditional terminology, we might be able to call this policy “stop-and-go policy” or “fine-tuning policy.”

We can only observe a limited effect of money supply on interest rate and innovation of money supply does not have any impact on the rest of the variables.

(2) Period II: From 1973 Q1 to 1990 Q1 (Flexible exchange rate period)

The percentage of the variance decomposition of the flexible exchange rate period is shown in Table 4-2. On the interest rate, 65% of forecasting error is attributed to the interest rate itself, and 26% is attributed to the inflation rate. On the money supply, contribution of its own variable is 82%, and this dominates the effect of other variables. Innovation of interest rate contributed 21% to the shock on inflation, but contribution of its own variable is 60%. Interest rate has 10%, and the rate of inflation has 15% contribution respectively on the shock on real GNP growth.

The outstanding characteristics of the second period were that the relationship between interest rate and real economic growth weakened and relationship between interest rate and inflation rate became stronger. One candidate for this explanation is the existence of Fisher Effect, due to growing inflationary expectations since the high inflation period in the mid-1970's.

Another view explaining the strong mutual relationship between inflation rate and the interest rate is the effect of exchange rate fluctuations in the second period. Since the exchange rate is closely related to the inflation rate, the interest rate is affected by the fluctuation of the exchange rate. To examine this hypothesis, we replaced the exchange rate by wholesale price index, and re-estimated the VAR Model. As a result, percentage of the variance decomposition of the forecasting error shows that 38% of shock on the interest rate is attributed to the fluctuations of the exchange rate. Also, we can see that the interest rate has a strong effect on the real GNP growth.

This result suggests that the interest rate was strongly affected by the fluctuation of the exchange rate in the flexible exchange rate period. Importance of the capital flows in the
Figure 4-3

[ ] Schwarz-Bayes Information Criterion
flexible exchange rate regime might be the background of this result. However, the effect of inflation on the real GNP growth disappeared in period II while the effect of interest rate on GNP growth retains its significance. This result suggests that the Fisher Effect is not robust, and still even in this period, the major tool of the monetary policy was controlling the interest rate.

## (3) Comparison between the two periods

In both periods, we were able to observe the strong effect of the interest rate on the real economic growth which indicates the significance of the monetary policy. $ ^{5} $

Another interesting result can be obtained by checking F-statistics of each VAR estimation. Comparing two periods, F-statistics on all variables improve in Period II. This result indicates that the mutual relations between variables are increasing. Also, if we compare Schwartz-Bayes Information Criterion for the two periods, the value is decreasing in Period II, which shows that the significance level of VAR estimation itself is improving. This means that the relationship between variables which indicate macroeconomic performance, and the variables which are the tools of the monetary policy, are growing closer in the second period.

### 4.3 Korea

We also divided the estimation period into two parts for Korea. In the first period, from third quarter of 1970 to fourth quarter of 1979, Korea adopted the fixed exchange rate system. In the second period, from second quarter of 1980 to first quarter of 1990, the exchange rate regime changed to a flexible rate system. However, the definition of this exchange rate system is not exactly the same as the flexible exchange rate system adopted in Japan. The exchange rate control system of Korea was so called “dirty float” system, where the exchange rate was not solely determined by the market, but actually determined by the monetary authorities.

## (1) Period I: 1970 Q1 to 1979 Q4

The percentage of variance decomposition of the forecasting error of the first period is shown in Table 4-4. A remarkable result of this period is, from the variance decomposition, we only deduced that the money supply had contributed 13% to the shock on real GNP.
growth. We obtained no other results from variance decomposition showing interrelation among variables.

The interest rate, which is the discount rate did not affect either on real economic growth or inflation, and these variables show strong exogenous feature. Also, concerning the shock on the interest rate, contribution to innovation of money supply is 3.3%, while the contribution of interest rate to money supply is 1.6%. These results can be interpreted from the well-known character of the financial policy that interest rate was used as a tool for rationing subsidized credits by the financial institutions, and was not used as a tool of macroeconomic adjustment.

Contributions of money supply to real GNP growth and inflation were 13% and 9% respectively. This result may indicate that the monetary authority was providing money supply with considerations for real economic growth. We might note that Shin (1978) applied Granger and Sim's causality test for the Korean Economy from 1962:Q2 to 1977:Q2. Though he failed to find an explicit result concerning causal relationship between money supply and nominal GNP, he found that money had unidirectional influence on real GNP and the GNP deflator. $ ^{6} $ Our result seems to be consistent with his claim.

One interesting feature of this period was the contribution of money supply to inflation. In this analysis, we can examine the causality between the variables, but it is difficult to determine the sign of the causality as we have explained at the beginning of this chapter. However, this result seems to be insinuating that the cause of the inflation was related to the supply of money.

## (2) 1980 Q1 to 1990 Q1

As we can see in Table 4-5, in this period, the relationship between variables shown by variance decomposition, is strong between interest rate (money market rate) and inflation. To the shock of interest rate, contribution of inflation is 12%, while interest rate contributes 11% to inflation.

The relationship between money supply and interest is weak. Contribution of interest rate to money supply is 5% while contribution of money supply to interest rate is 2%. Along with strong exogeneity of the interest rate, these results suggest that, even in 1980's, credit rationing had strong impact on the monetary policy.

We can interpret the relationship between interest rate and price in two different ways, as we have done in the case of Japan. First, we will focus on the possibility of the
existence of expectations of inflation, known as the Fisher Effect. Another explanation is to stress the effect of the exchange rate on interest rate, which could have been hidden in the rate of inflation.

To examine the relationship between interest rate and exchange rate, we replaced wholesale price index by nominal exchange rate and re-estimated the VAR Model. The results of the variance decomposition are shown in Table 4-6; they suggest that there is causality from interest rate to exchange rate, which indicates that the authorities started to determine the interest rate, not only focusing on the credit rationing, but also considering the effect of exchange rate.

When we consider the importance of credit rationing of the subsidized credits in Korea, the discount rate might have greater effect on macroeconomy than in the other countries. Therefore, we replaced money market rate by discount rate and re-estimated the VAR equation. We can see the strong influence of the discount rate from variance decomposition of forecasting error in Table 4-7. The discount rate contributes 13% to the forecasting error of the money supply, 28% to the inflation rate, and 13% to the real economic growth respectively. This result indicates that the impact of the interest rate on the macroeconomic variables became stronger in the 1980's.

Finally we will note results of VAR analysis by Kim and Oh (1991). They also estimated four variable VAR models for the Korean economy for the period from 1976:III to 1990:I. Their results differ considerably from ours. First, they used the interbank call rate, curb market rate, and the lending rate of the commercial banks as a short-term interest rate indicator. Although the variance decomposition result itself with these short-term interest rates was not apparently shown in the paper, they mentioned that only 2-7% of the variance of the growth rate of GNP can be attributed to shocks in short-term interest rates. However, they examined the corporate bond yield and the treasury bond yield as representative long-term interest rates as well. They found that for a period of 20 quarters, about 10-12% of the variance of the GNP growth rate can be attributed to the shock of long-term interest rates. More surprisingly, approximately 27% of the variance of the real GNP growth can be attributable to the shocks in the growth rate of M2. Our results using short-term interest rate indicate that innovation of the interest rate had much smaller impact. Moreover, the long-term interest rate seems to be significant in explaining the growth of real GNP. However, the effect of innovation of money supply with long-term interest rate is not comparable to ours. Although the sample period is rather different, further investigation of this difference is clearly in order. $ ^{7} $
(3) Results of Korean monetary policy

All the results mentioned above seem to be quite different from other countries. If we thoroughly investigate the monetary policy of Korea, we might have to consider the following other factors on top of the traditional study. First we can point out the importance of credit rationing, wherein interest rate and money supply were determined without the consideration of the macroeconomic conditions, but rather used as an integral part of the industrial policy. Second is the existence of large-scale unofficial financial markets, not controllable by the monetary authorities, which caused a leakage which cannot be ignored in controlling monetary aggregates. The third factor is the method of managing the target of the monetary aggregates. According to Korean authorities and a number of scholars, the target of the monetary policy of Korea was set at the growth rate of M2. However, the method of accomplishing this target was peculiar considering traditional monetary policy. When the growth of M2 exceeded the target, Korean monetary authorities influenced the banks to reduce M2 by shifting term deposits to saving deposits. As a result, by the shift of funds from M2 to M3, target of the growth rate of M2 was fulfilled. This must be clarified empirically, but suggests the peculiarity of the monetary policy in Korea.

Despite these results, the comparison of F-statistics of VAR estimation in Period I and Period II, reveals the importance of the monetary indicators in the Korean economy. Also, from Schwartz-Bayes Information Criterion, the significance of estimation of VAR analysis itself remained at the same level.

### 4.4 Indonesia

Despite the non-economical reason for division of the estimation period, a number of interesting issues can be pointed out by comparing the results of the two periods. The most significant feature of the economy of the first period was the heavy dependence on oil production, while in the second period, that dependence gradually declined. Also, deregulation of the financial market started in 1983 seemed to have an impact on the monetary policy and economic performance.

(1) Results of the period of 1977 Q1 to 1983 Q2

The percentage of variance decomposition of forecasting error is shown in Table 4-8. On the variance decomposition of interest rate, 95% of forecasting error is caused by the

potential effect of the long-term interest rate on those two main demand components.
innovation of own variable and shows strong exogeneity. Money supply has the dominant effect on the forecasting error of own variable, while the innovations of the other variables do not have significant impact on the money supply. The shock on inflation rate shows that 73% of the forecasting error is caused by the innovation itself, and 20% is by the innovation of the money supply, and other variables do not have significant effect. The variance decomposition of forecasting error of real GDP growth shows interesting results. The innovation of own variable contributes to 76% of the forecasting error of real GDP in the second period but this effect declines to 52% in the twentieth period. On the other hand, innovation of inflation rate contributes to the forecasting error of real GDP growth.

From the characteristics of the Indonesian economy in this period, we must consider that the oil price strongly influenced the general price level. Therefore, we replaced wholesale price index by oil price (\$US/BBL) and re-estimated the VAR Model. The results of the re-estimation in Table 4-9 show strong impact of oil price on real GDP growth rate and growth of money supply. When we look at the contributions of oil price on real GDP growth, 46% in the second period increases to 74% in the twentieth period, and dominates the effect on the shock of economic growth. We also can observe the shock on oil prices affecting the money supply. We can interpret the results in a straight-forward way that rise of oil price increases the export earnings dramatically, and this impact causes the increase of money supply. We confirmed that dominant factor of the Indonesian economy in the first period was oil and the impact of monetary policy was negligible.

(2) Results of the period 1984 Q3 to 1989 Q2

The percentage of variance decomposition of forecast error is shown in Table 4-10 and the relation of causality is shown in Chart 4-10. On the interest rate, the innovation of own variable contributes 89% and dominates the contribution of other variables. On money supply, we can see innovation of its own variable contributes 83% and inflation contributes 17%. On the inflation rate, innovation of money supply and real GDP growth have effects of 31% and 11% respectively, while 67% is due to its own shock. On real GDP growth rate, 50% of the shock is caused by the innovation of its own variable, while 26% is due to interest rate and 14% is due to money supply.

The most significant result of the second period is that the impact of inflation on real GDP weakened, which showed a 9% contribution on forecasting error. Also, both effects of money supply on real GDP growth and effect of interest rate on real GDP growth became apparent. Since the middle of 1980's, the role of oil in the Indonesian economy relatively declined, a result which was reflected in declining effect of inflation rate on real GDP growth. The interest rate started to have significant effect on real GDP growth, possibly suggesting
## • INDONESIA
that the effect of financial liberalization is beginning to reveal its impact on the macroeconomy in the late 1980's. $ ^{8} $ However, this interpretation is defective, since the relationship between money supply and interest rate is weak.

To confirm the effects of the oil price in the second period, we replaced wholesale price index by oil price (\$US/BBL), just as in the first period. The interesting result was that contribution of innovation of oil price was not strong as in the first period, and causality among other variables remains basically the same. This may indicate that in the case of Indonesia, impact of oil price declined and the effect of interest rate and money supply became stronger.

## (3) Comparison of two periods

As we have seen in the results mentioned above, in the first period, we saw clearly the dominant effect of oil on the economic performance of Indonesian economy. In the second period, we can see that the effect of oil declines and effect of the monetary variables increased. Even though we deduced that the impacts of monetary variables are increasing, it was difficult to point out the result of the financial liberalization by the VAR analysis. Most F-statistics on the VAR estimation increase in the second period which suggest the significance of the relationship between economic performance and monetary policy. However, significance of the VAR estimation itself measured by Schwartz-Bayes Information Criterion declines in the second period.

### 4.5 The Philippines

The period we applied the VAR analysis in the case of the Philippines is third quarter of 1982 to first quarter of 1990, corresponding to the estimation periods of the reaction function. The percentage of the variance decomposition of forecasting error is shown in Table 4-12. Contributions of growth of money supply to interest rate, inflation rate, and real GNP growth are 38%, 58%, 13% respectively, showing that money supply has strong impact on other variables. Inflation rate also contributes 20% to own variable and 30% to real GNP growth.

The results of the VAR analysis of the Philippines are difficult to interpret. One extraordinary characteristic is the extreme passivity of the interest rate, which is strongly influenced by money supply, but interest rate does not have significant influence on other variables. The strong effects of the money supply on the rate of inflation and interest rate can
• PHILIPPINES
be interpreted that the increase in money supply had a significant impact on inflation rate. Again, one candidate explanation is the Fisher Effect in the highly inflationary economy, when the expected inflation dominates the determination of nominal interest rate (Figure 4-12).

However, the result shows that interest rate does not have significant effect on real economic growth, which indicates the lack of effective tools for adjusting the real sector. On the other hand, the money supply has an impact on inflation and inflation has an impact on real economic growth. We also can observe that the money supply has a direct impact on the real economic growth. It seems that increase of money supply induces inflation and stimulates economic growth, but the inflation tends to have a negative impact on real economic growth. This result indicates that the supply of money has contradictory effects on performance of Philippine economy, that is, the coexistence of high inflation and low or negative real economic growth.

### 4.6 Interpretation of VAR analysis

We obtained interesting findings on the one hand, while we are disappointed on the other. In this final section, we will point out general findings of this analysis and will identify issues which might be interesting subjects for further study.

As we have explained earlier, many studies apply VAR, and most of them obtain different results from ours. The detailed comparison of these studies would be an interesting topic of the further study, but we will not attempt that comparison in this paper. $ ^{9} $ Currency in circulation, monetary base, M1, M2, and domestic credit were used to examine the role of money. The results are quite different from our study possibly due to the difference of data for Indonesia and the Philippines, and the different estimation periods for all countries. In particular, quarterly GDP data is estimated from annual GDP data in the case of Indonesia and the Philippines. The measuring periods are also different.

We can summarize the results of Hamann (1993) as follows. In the case of Indonesia, none of the variables representing money and output Granger-cause the price. At the same time, none of the variables representing money and price Granger-cause output, except for
the domestic credit. The relationships among money, price, and output by means of Granger-causality are apparently not found. The differences between our study are that, in our case, we can see strong relationship among variables in the case of Indonesia.

In the Korean case, currency, M2 and domestic credit Granger-cause the price, while monetary base, M1 and M2 Granger-cause the output. In only one case, where the estimation is made when M2 is adopted as the money variable, the price Granger-causes the output. Price also Granger-causes the money supply when domestic credit was chosen as a variable for money. Therefore money Granger-causes both price and output in almost cases. If the exchange rate is included in the model, it Granger-causes price in almost all cases on VAR model including interest rate. The results of our estimation show very weak relationship between variables, which is quite different from this analysis.

Results in the case of the Philippines are as follows. Currency, M2, and domestic credit Granger-cause the price, while price Granger-causes the output when M1 is adopted as the money supply in the model. Therefore the existence of Granger-causality from money to output is apparent. Furthermore, interest rates Granger-cause price in when currency or monetary base were chosen as a variable of money. We also were able to observe exchange rate Granger-causing the price. The results of this estimation are some what similarity with our results. We also obtained the causality of money supply to price, and causality of price to output. The significant difference was that in Hamann (1993) the causality was observed from interest rate to price, while we obtained a opposite direction of causality.

(1) Monetary policy and exchange rate regimes

In the cases of Japan, Korea, and Indonesia, we divided the estimation period into two parts. Japan's first period is a clearly fixed exchange rate regime and the second period is a flexible exchange rate regime. The first period of Korea was basically a fixed exchange rate regime, but the second period was not exactly a flexible exchange rate regime but can be considered to be a "dirty float" regime. Even the division of the estimation period of Indonesia is based on statistical reasons, the first period of Indonesia can be considered to be a fixed exchange rate system and the latter part of the second period is a "dirty float."

In orthodox or traditional economic theory, it is commonly understood that the monetary policy will become independent and effective in the flexible exchange rate system. Representative, well-known applications are the Mundell-Fleming type of analyses. Or at least there will be significant difference in the result of the monetary policy when there exists a difference in the exchange rate regime of restriction on capital mobility. However, the empirical findings from our four variable VAR estimations do not support this view. These results may suggest that we will obtain interesting results if we examine with different