Silviase/jgov_v1.4_full_ann huggingface dataset:
## (iv) The Philippines

For the discount rate, all measures of the inflation rates were significant at the 1% level in the individual regressions. Furthermore, foreign reserve and exchange rate were significant at 1% level as well. However, in the second-stage regression, where GNP deflator, inflation rate, exchange rate, and foreign reserve were jointly estimated, only inflation rates were significant at the 1% level, with foreign reserve and inflation rates being significant at 5% level. However, using M2 as monetary instruments, only real GNP was significant at 10% level.

### 2.5 Discussion of the Results

Let us evaluate the estimated results for each country. The estimated results were conveniently summarized in Tables 2.13 to 2.16. In those tables, in taking account of the multicollinearity problem, any variables which revealed individual significance in the first-stage regressions were listed as such.

## (i)Japan

For the fixed exchange rate period, the well-known “stop-and-go” aspects of the Japanese monetary policy during this period can be clearly discerned from the results. That is, as current account deficit prevailed, tight monetary policy was undertaken and only current account surplus initiated an introduction of expansionary monetary policy, which was shown by the results in Table 2.13, using both discount rate and money supply for the first period. Also since economic booms were usually associated with the current account deficits during these years, the responses of monetary instruments to the changes of real GNP and industrial production indexes were comprehensive as well. These results also accord with the empirical results of Kama (1987).

The results for the flexible exchange rate period are more cumbersome. First, using discount rate as a tool for monetary policy, it was found that the inflation rate as well as the movements of the exchange rates became primarily concerns of the monetary policy. This result supports the anti-inflationary view of the monetary policy, often claimed by the Bank of Japan officials during these years. It also highlights the ever-increasing significance of the exchange rate consideration in the conduct of the Japanese monetary policy.

Using M2 measure of the money supply, none of the macroeconomic variables turned out to be significant in the response function. This result seems quite puzzling and does not coincide that of Kama (1987). He found that, using M2 component of money supply, inflationary consideration remained as significant factor influencing the monetary
TABLE 2.13: JAPANESE REACTION FUNCTION

PERIOD	DEPENDENT VARIABLE	GNP	IP	PW	PC	DEF	BP	R	E
1962:III - 1973:I	DR	***	****	***
1962:III - 1973:I	M2	***	***	****	*
1973:IV - 1990:I	DR	*	**	***	****
1973:IV - 1990:I	M2

$ ^{*} $ : Significance at the 20% level.

** : Significance at the 10% level.

*** : Significance at the 5% level.

**** : Significance at the 1% level.

TABLE 2.14: KOREAN REACTION FUNCTION

PERIOD	DEPENDENT VARIABLE	GNP	IP	PW	PC	DEF	BP	R	E
1970:III - 1979:IV	DR	**
1970:III - 1979:IV	M2	**	***	***
1980:III - 1990:I	DR	*	*
1980:III - 1990:I	M2

$ ^{*} $ : Significance at the 20% level.

** : Significance at the 10% level.

*** : Significance at the 5% level.
policy; nevertheless, there are two distinctions between our study and his. The first is simply that the sample periods are different: his sample period for the flexible exchange rate years was the period from 1973:IV to 1986:III; ours is from 1973:II to 1990:I. The second is the difference of the data sets: different methods were used for seasonality problem. He kept original data series, however, the growth rate of the variables, which were measured as the log difference between current value and one-year lagged value, were used as the empirical counterparts of the macroeconomic variables. On the other hand, we used seasonally adjusted variables for the flow variables and employed the growth rate, calculated by the log difference against one-quarter lagged value, in the relevant empirical estimations. Since both factors can, in principle, affect empirical results, our conclusions remain unsettled.

However, one crucial point for these discrepancies may be our longer sample period; sample years may be long enough to contain several regimes of monetary policy. Based on this idea, as a tentative approach, the second period was further divided into two periods: from 1973:II to 1981:IV and from 1982:I to 1990:IV. The preliminary results for the money supply regressions show that the inflation rates measured by the change of the wholesale price became significant at the 10% level from 1973:IV to 1981:IV. However, none of the macroeconomic variables became important objectives for the latter period. The basic conclusions remain unaltered for the discount rate regressions.

### (ii) Korea (Table 2.14)

One notable feature of the empirical results for Korea is that the empirical results, using money supply, clearly signify the “stop-and-go” character of the Korean monetary policy during fixed exchange rate years. Furthermore, our result suggests that Korean monetary authority paid at least some attention to the movements of the inflation rates, measured by either the rate of change of GNP deflator or that of wholesale price index. In Jae-Yoon Park (1982), he examined monetary reaction function for the fixed exchange rate years. He regressed natural logarithm of M2 on natural logarithm of lagged value of real GNP, inflation rate, and lagged value of the level of net foreign assets. $ ^{8} $ He claims that the most important goal of Korea’s monetary policy was economic growth and the role of anti-inflationary monetary policy was unnoticeable. Furthermore, he asserts that monetary authorities disregarded the problem of the balance of payments. This conclusion remarkably contrasts with ours in many aspects. Though his method thoughtfully incorporates important aspects of Korean monetary policy that we rather dismissed, his empirical equation seems to be subject to serious methodological dispute.
The result for the discount rate reveals the significance of real GNP only at 10% level. It could be the case that the discount rate might have been mainly used for the purpose, other than the short-run stabilization for Korea; it was sometimes claimed that more than half of the domestic credit had been allocated by the government to heavy and chemical industries as well as the large business firms in Korea. Hence the central role of the discount rate might be in line with this preferential credit allocation policy of the Korean government.

In any event, this strongly contrasts with the Japanese experience, which case this type of discrepancy was not observed. Furthermore, for the second period, discount rate only minimally responds to the change of real economic activities. In Japan the discount rate was extremely sensitive to the change of the macroeconomic indicators, such as inflation rates and exchange rates. These apparent differences in the macroeconomic role of the discount rate surely deserve further serious investigation.

The empirical result using M2 money supply for the second period was quite confusing because it was often claimed that since 1979 Korea has used the growth rate of M2 money stock as an intermediate target of monetary policy.

However, the fact that there was a kind of “crisis” for the Korean economy might be relevant for this aspect. As the preliminary attempts, we adopted different estimation periods, such as starting the periods from 1982 or 1983. Nonetheless, this problem was not resolved by this attempt.

Several other lines of explanation might also be relevant; actual implementation of monetary policy was very rigid. Once target value was decided, allocation of domestic credits was planned and it was strictly enforced, regardless of the macroeconomic condition thereafter. This might, if it is true, obviously leave little room for the discretionary monetary policy. $ ^{9} $

Another issue surrounding conduct of the monetary policy in Korea was the problem of the unregulated curb money markets; even in 1985, the share of the curb market remained at one-quarter of the banking claims on the private sector. Besides the discouraging effects on the development of the open money market, this has two critical implications for the monetary policy. First, this curb market with growing non-banking financial sector would probably complicate the macroeconomic information role of the traditional financial data, such as banking loans and loan rates. Second, it is easy to understand that the effectiveness of the monetary policy can be seriously affected by such leakage out of the traditional
banking system.

Finally we have to admit some of the empirical results here are statistically poor. Especially, explanatory power of the response functions for the money supply for the second period is extremely low. This problem of our empirical methodology, however, not only for Korea, would be re-examined further in the final section.

### (iii) Indonesia (Table 2.15)

Though it is often argued that one of the primary objectives of macroeconomic policy in Indonesia was the maintenance of external balance, this aspect is not directly reflected in our empirical results. Nevertheless, for the second period, M2 money supply negatively responded to the increase of the wholesale price inflation rate. Higher inflation rates, however, can result in the depreciation of exchange rate which raises a serious barrier for the Indonesian economy. This result may simply reflect these considerations.

It is worth noting that, for the first period, inflation rates measured as the changes of the wholesale prices, consumer prices, GNP deflator, were significant at the 10% level, 5% level, 5% level, respectively. Above all, none of them satisfied sign conditions.

Finally, we here also note the poor statistical performance of these monetary response functions for both periods.

### (iv) The Philippines (Table 2.16)

It is well-known that, in contrast to many other developing countries, a “stabilization program” was rapidly achieved in the Philippines when needed. For example, after high growth in money supply in 1983 and resulting high inflation rates, the Philippines was highly successful in reducing inflation rates. The domestic inflation rate dropped as quickly as it had risen; tight monetary policy was imposed in 1984 and maintained through 1985 and consumer prices actually fell during 1986. The growth rate of nominal money, as M1 or M3, was low by historical standards. It should also be noted that this particular adjustment program was carried out by continuous face-to-face discussion with IMF and its external creditors. The result that the discount rate was extremely sensitive to the inflation rate, foreign reserve, and exchange rate should be understood in this context.

Nonetheless, the result with M2 money supply component revealed only real economic activity as a significant factor for the conduct of the monetary policy. This is quite opposite case to the first period results of Korea; here the discount rate policy reveals strong short-run stabilization aspects, whereas money supply can not be characterized as such.

Finally, as in the case of Indonesia, for the money supply, the inflation rates measured as the changes of the wholesale prices, and consumer price were significant at the
### TABLE 2.15: INDONESIAN REACTION FUNCTION

PERIOD	DEPENDENT VARIABLE	GNP	IP	PW	PC	DEF	BP	R	E
1976:III - 1983:IV	M2
1983:III - 1990:I	M2	**

$ ^{*} $ : Significance at the 20% level.

** : Significance at the 10% level.

TABLE 2.16: PHILIPPINE REACTION FUNCTION

PERIOD	DEPENDENT VARIABLE	GNP	IP	PW	PC	DEF	BP	R	E
1981:III - 1990:I	DR	****	****	****	*	****	****
1981:III - 1990:I	M2	**

$ ^{*} $ : Significance at the 20% level.

** : Significance at the 10% level.

*** : Significance at the 5% level.

**** : Significance at the 1% level.
1% level. GNP deflator inflation rate was significant at the 5% level, but with the wrong sign. Moreover, the exchange rate was also significant at the 1% level with unexpected sign.

Before closing the discussion of the results, it seems worthwhile to discuss several puzzling aspects and the serious caveats of the analyses. First we may pay serious attention to some of the estimated results of the response function for the money supply; more specifically, second period results for Japan and Korea. Moreover, apparent discrepancy of the results between the discount rates and money supply for the Philippine economy may also be relevant in this respect. In most of the cases, quite unexpectedly almost none of the macroeconomic variables affected the money growth rates. Besides the specification error issues, a potentially critically factor for those results might be the drastic financial innovation which occurred in these countries.

Significant financial reform in Japan started in the late 1970's, and in Indonesia in the early 1980's. Although Korea has taken some steps toward financial reform in recent years, the restrictive controls on the financial transactions still remain effective. Thus, although the motivations, degree, and the timing of the reform vary across countries, all these countries experienced vital changes of the financial structures.

It is obvious that these financial reforms had significant impact on the conduct of the monetary policy. With a spectrum of new financial instruments and drastic changes of the financial structure, it might become tough to get a proper grip on the relevant monetary aggregates.

Second point to be focused here is the poor statistical performance of our estimated response functions. This may be due to the omission of some of the more important macroeconomic variables, potentially important for the developing countries. Possibilities may include such factors as the degree of the central bank's accommodation of the credit requirements of the government or the effect of the foreign debt outstanding and other country-specific macroeconomic variables. Though extension of our study in this direction only remains to be seen, we focus on the following observation: The presence of the several macroeconomic variables which were extremely significant but with unexpected signs is related with the first perspective. Though this is probably due to the specification error problem mentioned above, these phenomena may reflect the information lag problem. That is, in some of the countries, relevant macroeconomic data were not as readily available as in Japan, or for that matter other industrialized countries, so that there may exist much longer time-lag relationship between the macroeconomic changes and the corresponding changes of the monetary instruments than those presumed in our theoretical model. This issue will be examined in the next section.
### 2.6 The Lagged Values of Macroeconomic Variables

As mentioned in the introduction of the study, this study is motivated by the emergence of the quarterly macroeconomic variables in recent years. Though financial figures have been readily accessible in these countries, quarterly macroeconomic data has been published quite recently. It is true that the many surrogate variables reflecting the real economic activities exist in any economy, besides the standard macroeconomic variables. However, the extremely poor statistical performance of our results motivates us to include lagged values of the macroeconomic variables in the response function.

Formally if we assume that desirable money growth rate in equation $ (2.10) $ is determined by the lagged growth rates of the macroeconomic variables, it is obvious that final equation to be estimated such as $ (2.3) $ includes lagged values of macroeconomic variables.

To focus on the time lag problem of the macroeconomic policy formulation, we suppose that relevant macroeconomic variables include lagged values up to two periods in the past. In other words, we include two lagged values of the macroeconomic variables in the estimation of the policy response function. In the following, we compare the results of this specification with the former results for each country.

## (i) Japan

The estimated results for the response function with new specification are shown in Tables 2.17 - 2.20 and summarized in 2.29. Compared with Table 2.13, several observations are in order. Putting the poor statistical performance of these equations aside, for the first period, discount rate to some extent responds with lagged values of growth rates of GNP, wholesale price indexes and foreign reserves. However, according to Table 2.13, discount rate moves along with the contemporaneous change of those variables as well, except foreign reserves. Regarding the money supply, it changes quite strongly according to contemporaneous movements, the exception being the wholesale price indexes. It is possible to view that the monetary policy in the first period responded to the contemporaneous information.

For the second period, though discount rate changes with the current as well as the past changes of the wholesale prices, it responds quite strongly with the contemporaneous changes of the exchange rates. This accords with our observations on the prompt reply of the monetary authorities regarding exchange rate movements in recent years. It is curious to find that the money supply equation indicates the significance of the second lagged value of the industrial production indexes. Summarizing these, we may purport that the contemporaneous information was rather influential in the formation of the monetary policy.
### TABLE 2.17: JAPANESE REACTION FUNCTION DISCOUNT RATE, 1962: IV - 1973: I

CONSTANT	GNP(-1)	GNP(-2)	PW(-1)	PW(-2)	BP(-1)	BP(-2)	PC(-1)	PC(-2)	DEF(-1)	DEF(-2)	R(-1)	R(-2)	IP(-1)	IP(-2)	DR(-1)	ρ	R²	DW
-0.051	.794	1.172	.326	-.354	.386	2.09
(-2.519)	(1.312)	(1.659)	(1.541)	(-1.586)
-0.021	1.279	1.549	.138	.169	1.979
(-2.460)	(1.214)	(1.297)	(.894)
.002	-.0004	-.026	.062	.159	1.845
(.281)	(-.032)	(-2.206)	(.400)
-.002	-.414	-.165	.204	-.021	1.945
(-.117)	(-.466)	(-.187)	(1.265)
-.031	.714	.853	.196	.017	2.011
(-1.742)	(.855)	(1.034)	(1.259)
-.006	-.00002	.00002	.167	.089	1.833
(-.652)	(-2.121)	(1.961)	(1.080)
-.0367	.721	1.251	-.184	.379	1.933
(-3.794)	(1.601)	(2.652)	(-1.247)

See Table 2.1

### TABLE 2.18: JAPANESE REACTION FUNCTION MONEY SUPPLY, 1962: IV - 1973: I

CONSTANT	GNP(-1)	GNP(-2)	PW(-1)	PW(-2)	BP(-1)	BP(-2)	PC(-1)	PC(-2)	DEF(-1)	DEF(-2)	R(-1)	R(-2)	IP(-1)	IP(-2)	M(-1)	ρ	R²	DW
.025	-.191	-.105	.554	.448	2.181
(3.476)	(-1.875)	(-.983)	(4.463)
.010	.040	-.433	.797	-.473	.721	1.871
(2.237)	(.237)	(-2.444)	(8.287)	(-2.72)
.018	.003	.002	.493	-.338	.697	1.858
(2.849)	(1.782)	(.962)	(2.896)	(-1.395)
.014	.104	-.025	.628	.393	2.156
(2.715)	(.706)	(-.174)	(4.979)
.009	-.140	-.018	.641	.399	2.122
(2.827)	(-1.014)	(-.131)	(5.342)
.010	-.000007	.000001	.715	-.327	.628	1.751
(1.854)	(-.627)	(-.627)	(4.954)	(-1.467)
.026	-.147	-.063	.533	.510	2.247
(3.915)	(-1.687)	(-.639)	(4.159)

See Table 2.1
### TABLE 2.19: JAPANESE REACTION FUNCTION DISCOUNT RATE, 1974: I - 1990: I

CONSTANT	GNP(-1)	GNP(-2)	PW(-1)	PW(-2)	BP(-1)	BP(-2)	PC(-1)	PC(-2)	DEF(-1)	DEF(-2)	R(-1)	R(-2)	IP(-1)	IP(-2)	E(-1)	E(-2)	DR(-1)	ρ	R²	DW
-0.032	1.505	1.505	.687	-.321	.446	2.04
(-1.598)	(.9679)	(.979)	(5.684)	(-2.158)
-0.008	.291	.131	.391	.164	1.963
(-.626)	(.359)	(.180)	(2.972)
-.005	-.010	.011	.645	-.319	.271	2.102
(-.392)	(-2.209)	(2.402)	(5.324)	(-2.205)
.006	-.622	-.284	.453	.171	2.103
(.3850	(-.507)	(-.240)	(3.951)
.005	.671	-.911	.745	-.427	.409	2.155
(.283)	(.152)	(-.257)	(4.173)	(-2.105)
-.046	-.00005	.00006	.304	.250	2.121
(-2.261)	(-1.298)	(1.606)	(2.450)
-.012	.544	.334	.403	.178	2.041
(-.904)	(.734)	(.438)	(3.560)
.002	.298	.320	.290	.159	2.189
(.995)	(1.083)	(1.619)
(.140)

### TABLE 2.20: JAPANESE REACTION FUNCTION

CONSTANT	GNP(-1)	GNP(-2)	PW(-1)	PW(-2)	BP(-1)	BP(-2)	PC(-1)	PC(-2)	DEF(-1)	DEF(-2)	R(-1)	R(-2)	IP(-1)	IP(-2)	E(-1)	E(-2)	M(-1)	ρ	R²	DW
.002	.109	-.075	.774	-.644	.576	2.207
(2.218)	(1.078)	(-.734)	(8.669)	(-6.193)
.002	-.035	.008	.788	-.637	.595	2.258
(2.238)	(-.774)	(.206)	(8.749)	(-6.095)
.005	.001	-.00008	.781	-.628	.565	2.222
(2.139)	(.425)	(-.2810)	(8.451)	(-5.902)
.005	.032	-.013	.756	-.621	.559	2.177
(2.715)	(.361)	(-.154)	(7.841)	(-5.703)
.006	.217	.029	.690	-.649	.365	2.139
(1.627)	(.737)	(.129)	(4.325)	(-4.333)
.005	.00000007	-.00000004	.769	-.630	.564	2.219
(2.206)	(.363)	(-.281)	(8.512)	(-5.944)
.006	.067	-.120	.763	-.656	.629	2.318
(3.002)	(1.556)	(-2.818)	(9.116)	(-6.403)
.005	-.004	-.01	.770	-.636	.572	2.224

(2.451)	(-.335)	(-.672)	(8.575)	(-6.041)

See Table 2.1
#### (ii) Korea (Table 2.21 - Table 2.24)

For the first period, in the discount rate equations, lagged values of the balance of payments and the GNP deflator were significant. For the money supply equations, lagged value of the consumer price indexes were significant. However, according to Table 2.14, it responds with the current changes of the wholesale price indexes, GNP deflators, and the balance of payments.

For the second period, the lagged values did not change the fundamental conclusion obtained in the former results. Although there might be slight possibilities of the time lag problem for this country, the order was apparently not so serious.

#### (iii) Indonesia (Table 2.25 - Table 2.26)

Unlike Japan and Korea, the inclusion of the lagged values of the macroeconomic variables yielded new insights in this country.

For the first period, lagged value of the foreign reserve was insignificant at the 10% level. Moreover, lagged values of the balance of payments and exchange rate were significant at the 5% level. Compared with the results in Table 2.15, the time lag problem might be much more serious than for Japan and Korea.

#### (iv) The Philippines (Table 2.27 - Table 2.28)

Comparing Tables 2.16 and 2.32, it seems fair to say that the monetary policy in this country was responsive to contemporaneous information. Thus the time lag problem was not so critical.

As an overall conclusion, the acclaimed time lag problem in the formation of the monetary policy was only critically relevant for Indonesia. Hence the issue of the poor statistical performance of our response functions remains unresolved.

However, the study of Asako and Kanoh (1989) sheds some light on this problem. In this analysis, we used the data from entire period to estimate the policy response function. Though this is the standard practice on this topic, Asako and Kanoh (1989) employed sophisticated Bayesian method to estimate the response functions of monetary and fiscal policy for the Japanese economy. Their recursive estimation of the policy function produced several important findings. Following them, we would adapt the recursive estimation method in the next section.
### TABLE 2.21: KOREAN REACTION FUNCTION DISCOUNT RATE, 1970: IV - 1979: IV

CONSTANT	GNP(-1)	GNP(-2)	PW(-1)	PW(-2)	BP(-1)	BP(-2)	PC(-1)	PC(-2)	DEF(-1)	DEF(-2)	R(-1)	R(-2)	IP(-1)	IP(-2)	DR(-1)	ρ	R²	DW
-.016	.228	.094	-.024	-.082	1.94
(-.009)	(.492)	(.189)	(-.139)
-.008	-.163	.318	.530	-.547	-.062	2.007
(-.601)	(-.448)	(.841)	(3.025)	(-3.153)
-.006	.00006	-.00008	.552	-.575	.318	2.143
(-.641)	(1.389)	(-1.730)	(3.407)	(-3.471)
-.035	.464	.309	-.049	-.043	1.946
(-1.449)	(.760)	(.506)	(-.284)
-.049	.182	.707	-.034	.040	1.925
(-1.845)	(.538)	(2.12)	(-.202)
-.032	-.00002	-.000005	-.526	.493	.231	2.098
(-.866)	(-.314)	(-.061)	(1.080)	(2.584)
-.032	.184	.464	.427	-.513	.260	2.092
(-1.383)	(.415)	(.854)	(2.048)	(-2.499)

See Table 2.1

### TABLE 2.22: KOREAN REACTION FUNCTION MONEY SUPPLY, 1970: IV - 1979: IV

CONSTANT	GNP(-1)	GNP(-2)	PW(-1)	PW(-2)	BP(-1)	BP(-2)	PC(-1)	PC(-2)	DEF(-1)	DEF(-2)	R(-1)	R(-2)	IP(-1)	IP(-2)	M(-1)	ρ	R²	DW
.033	-.104	-.070	.543	-.438	.208	2.176
(2.407)	(-.698)	(-.494)	(2.449)	(-2.043)
.071	-.125	.006	.011	-.044	1.906
(4.931)	(-.981)	(.051)	(.063)
.076	.00001	.00001	-.043	.026	1.873
(5.602)	(.618)	(.827)	(-.244)
.075	-.357	.054	.037	.061	1.895
(5.120)	(-2.151)	(.317)	(.219)
.054	.059	.071	.103	-.063	1.917
(3.433)	(.559)	(.709)	(.572)
.065	.00003	-.00003	-.021	-.001	1.919
(5.410)	(1.615)	(-1.516)	(-.202)
.059	.221	-.019	-.007	.002	1.855
(4.972)	(1.689)	(-.143)	(-.039)

See Table 2.1