Download Positivist Study on Chinese Monetary Policy Transmission Mechanism

Positivist Study on Chinese Monetary Policy Transmission
Mechanism
GUO Yaxiong
School of accounting Jiangxi University of Finance and Economic, P.R.China, 330013
[email protected]
，
Abstract: This paper, based on monthly data from Jan.2000 to Jun.2007, introducing interest rate,
investment and consumption concepts and adopting modern computing/econometric techniques, has
herein reviewed the coordinating relationships between GDP, money supply M2, M1, M0 and interest
rate. Review findings indicate that between GDP, money supply M2, M1& M0 and interest rate, there
exist long-term stable relationship, and M2, M1 & M0 and interest rate are of significantly positive
correlation with GDP. Positivist analysis indicates that Chinese monetary policy has obvious impact on
the operation of macro-economy, the reason is that money supply, as the intermediate objective of
transmitting monetary policy, bears sensitive impact on final objective variables.
Key Words: Monetary Policy; GDP;M2;Interest Rate; Granger
1 Introduction
At present, there contain two sequential components in theoretic study of monetary policy functions: the
first is whether monetary policy can affect economic operation; the second is how monetary policy
affects economic variables in economic operational objects, i.e. how monetary policy will transmit.
Friedman and Schwartz are the earliest (1963) to conduct this type of statistic relationship. Sims (1972)
adopted a testing method judging Granger effect relationship which enjoys widespread influence
afterward (Granger 1969). In addition, Freeman (1992), through differentiation between internal
currency and external currency, found correlativity between currency and actual output, and regarded
that this kind of correlation be realized through the relationship between output disturbance and
currency multipliers.
As for the relationship between money supply change and output change, Friedman, Schwartz
(1963) and Tobin (1970) figured that in the short term the money supply change actually had some effct
upon output fluctuation. Stock, Watson (1989) and Cover (1992) had also arrived the same research
results. However, Kormendi, Meguire 1984 ,Boschen, Mill 1995 ,McCandless and Weber 1995 ,
through positive analysis, held that change of money supply would not have long-term impact on output
change. Besides, Sims (1980), through positive study, deemed that, upon adding nominal variables of
interest rate and price, the impact of money supply on actual output will be decreased. What’s more,
King and Plosser (1984) found upon further positive study that the currency in narrow sense had weaker
impact upon actual output even than the currency of wide sense. It can be seen that the academia has
two points of view on the relationship between money supply and output as follows: in the long run,
money supply does not have impact on output, i.e. in the long time, currency is newtral and the
long-term output change is determined by actual elements except currency section; while in the short
run, money supply will surely have impact upon output.
Recently, many scholars, on basis of chronologically sequential data, have adopted VAR and
coordinating method to estimate the impact of monetary policy to output. Hafer and Kutan (1994) used
error correction models to test the coordinating relationship between currency demand and actual
national income and expectant inflation rate between 1952 and 1988. With VAR models, Blinder (1988)
derived the conclusion that the three officially defined money supply indexes announced by the U.S.
Federal Reserve had no long-term stable statistic relationship with the nominal GDP. Analysis of Rich
(1997) and Otmar (1997) about the Swiss and German data indicates that their regulating
macro-economy with money supply as intermediate objective of monetary policy is relatively successful
among western countries. Christiano etc (1998), based on Sims’s double-variable model, concluded that
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logarithmic value of the U.S. money supply M1 and that of industrial output level are of significantly
Granger causal-relationship. Firedman and Kuttner (1992) analyzed the U.S. 1960-1990 data and found
that the relationships between currency variables and income and price are stable. Although findings of
scholars’’ positive studies on monetary policy’s functioning efficiency are not highly consistent,
generally speaking, for countries with stronger market economy basis and sounder financial system, the
monetary policies are relatively effective.
This Article, based on monthly data from Jan.2000 to Jun. 2007, introduced interest rate,
investment and consumption and adopted modern computing technology to examine the coordinating
relationships between GDP, money supply M2, M1, M0 and interest rate of China.
2 Stability Testing of Economic Variables
In order to study the transmission mechanism of monetary policy, we adopt herein monthly data
sequence of GDP, M2, M1, M0, year-period savings interest rate (Rate), fixed assets investment (Inv)
and total social consumables retail amount (Cons). Except interest rate, all these variables, upon
seasonable adjustment by X-11 method, are subject to natural logarithm, of which variable form are
LnGDP LnM2 LnM1 LnM0 LnInv LnCons LnRate respectively.
Shown in Figure 1 is the result of testing by ADF root of unit. Testing result indicates that the
logarithmic sequence of variables is not stable, but the first order difference sequence of their
logarithmic values is stable.
、
、
、
、
、
、
、 、 、
（
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Figure 1 Unit Root Testing Results of GDP M0 M1 M2, Investment and Consumption Monthly Data
Variable
lngdp
lngdp
LnM0
lnM0
LnM1
lnM1
LnM2
lnM2
Lninv
lninv
Lncons
lncons
Lnrate
Lnrate
△
△
△
△
△
△
△
Testing Form
C T P
C,T,5
C,N,9
C,T,11
C,N,6
C,T,1
C,N,0
C,T,8
C,N,0
C,T,11
C,N,11
C,T,1
C,N,2
C,T,0
N,N,0
（
（
（
（
（
（
（
（
（
（
（
（
（
（
（
，，）
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ADF Testing
Value
-3.252663
-6.140835
-1.647176
-4.582326
-1.450988
-12.33803
-3.244229
-10.58400
-2.751129
-4.685056
-3.360186
-8.223338
0.145427
-9.327379
Critical Value
Result
-3.464198**
-3.515536***
-3.161067*
-3.512290***
-3.157121*
-3.506484***
-3.466248**
-3.506484***
-3.161067*
-3.517847***
-3.461686**
-3.508326***
-3.156776*
-2.591505***
Unstable
Stable
Unstable
Stable
Unstable
Stable
Unstable
Stable
Unstable
Stable
Unstable
Stable
Unstable
Stable
Remarks: ADF testing results in this Figure is derived by Eviews 5.0 software. Testing forms (C, T, P)
stand for constant item, timing tendency and lagging period of unit root testing equation, N means not
containing C or T, adding the lagging items is intended to make the residual error item as white noise,
means difference operator. * ** *** represent the level of significance of 10% 5% 1%.
△
、 、
、 、
3 Monetary Policy’s Effect on Economic Growth upon Introducing Interest Rate
Variables
3.1. Coordinating Testing
Through establishing VAR model and based on the AIC principle and the SC principle, the results
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derived by JJ coordination are shown in Figure 2. Results of coordinating testing indicate that, under the
level of significance of 1%, there exists a coordinating relationship between GDP, M2 and interest rate.
By the same method, it is found that, under the level of significance of 1%, there also exist respectively
a coordinating relationship between GDP, M1 and interest rate; and between GDP, M0 and interest rate.
Figure 2Johansen Coordinating Testing Results of GDP and Interest Rate, M2,M1 & M0
Variable
Eigenvalue Likelihood 5% Critical 1% Critical
Ratio
Value
Value
Originally Optional
Supposed Supposed
H0
H1
LnGDP
0.284200
38.15593
29.68
35.65
r=0**
r=1
1
LnRate
0.080707 8.732784
15.41
20.04
r≤1
r=2
3.76
6.65
r≤2
r=3
LnM2
0.014973 1.327584
LnGDP
0.265596
34.58059
29.68
35.65
r=0*
r=1
1
LnRate
0.080813 7.415388
15.41
20.04
r≤1
r=2
LnM1
7.00E-09
6.16E-07
3.76
6.65
r≤2
r=3
LnGDP
0.238108
32.51763
29.68
35.65
r=0*
r=1
2
LnRate
0.095821 8.857922
15.41
20.04
r≤1
r=2
LnM0
0.001087 0.094622
3.76
6.65
r≤2
r=3
Notes r stands for the number of coordinating vectors *, ** stands respectively for the level of
significance of 5% 1%.
：
Lagging
Period
，
、
：
The coordinating equations of GDP and interest rate, M2,M1 & M0 are respectively as follows
EC LnGDP 0.77LnM2 0.26LnRate 0.29
EC LnGDP 0.83LnM1 0.33LnRate 0.22
EC LnGDP 1.30LnM0 0.24LnRate 3.57
It can be seen from Equations 1 , 2 and 3 , interest rate, M2, M1 and M0 can notably boost
the growth of GDP standard errors of various coefficients and t statistic values are available from the
author . From Equations 1 , 2 and 3 , we can see that with respective 1% increase of M2, M1
and M0 GDP will respectively rise by 0.77% 0.83% and 1.3%.
2. Error correction Models
1 Error correction Models of GDP, M2 and Interest Rate
Short-term dynamic equations given by Appendix Table 1, Table 2 and Table 3 can be derived by
normalization of vectors (see Formulas 4 , 5 , 6 ) .Lagging orders in above formulas is
determined by repetitive estimation and calculation by integrating multi-variable model causality and
meanwhile based on AIC principle and SC principle, among which the smallest is selected (detailed
estimation and calculation is available on request). Therefore, the error correction models of GDP,M2,
M1, M0 and interest rate can be derived as follows:
＝
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－
－
－
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＋ （1）
－
＋ （2）
－
＋ （3）
（ ）（ ） （ ）
（ ）（ ） （ ）
、
（ ）（ ）（ ）
dLnGDP = −0.004 + 0.04dLnGDPt −1 + 1.14dLnM 2 t −1 + 0.35dLnRatet −1 − 0.55EC t −1
（4）
dLnM 2 = 0.015 − 0.01dLnGDPt −1 − 0.14dLnM 2 t −1 − 0.01dLnRatet −1 + 0.01ECt −1
（5）
dLnRate = −0.017 − 0.03dLnGDPt −1 + 1.62dLnM 2 t −1 − 0.03dLnRatet −1 + 0.07 EC t −1
（6）
（）
，
In Formula 4 , the adjustment coefficient of error correction item EC is 55% complying with the
negative feedback process of error correction and thus indicating that long-term equation enjoys
strong binding force to short-term dynamic behaviors and boasts strong adjusting speed in the process
of approaching long-term balanced relationship; while in Formulas 5 and 6 the coefficient of
error correction item EC does not comply with the negative feedback process of error correction,
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according to this representation of the short-term equation, we think that the short-term modification
process mainly takes the first form, i.e. long-term balanced relationship is mainly caused by the
impact of money supply M2 in the wide sense and the interest rate to economic operation.
3.2 Error correction Models of GDP, M1and Interest Rate
Based on the VAR model, the AIC and SC principles the error correction models of GDP, M1 and
interest rate are as follows:
，
dLnGDP = 0.016 + 0.04dLnGDPt −1 − 0.47 dLnM 1t −1 + 0.23dLnRatet −1 − 0.55EC t −1
（7）
dLnM 1 = 0.016 + 0.01dLnGDPt −1 − 0.29dLnM 1t −1 + 0.02dLnRatet −1 − 0.01EC t −1
（8）
dLnRate = −0.001 − 0.02dLnGDPt −1 + 0.43dLnM 1t −1 − 0.03dLnRatet −1 + 0.06 ECt −1
（9）
（）
The correction coefficient of EC in the short-term equation 7 indicates that in the short-term
coordinating process the adjusting speed is relatively fast at 55%; compared with that of M2, we
reckon that from the results of long-term equation and short-term equation, the effect of M2 to GDP is
basically same as that of M1 to GDP. Likewise, from EC in Formula 9 , we can see that the symbol is
inconsistent with the negative feedback significance of error correction, indicating that the effect of
M1 and interest rate upon GDP is acted mainly through short-term equation (7), i.e. long-term
balanced relationship is mainly formed through the effect of LnM1 to LnGDP.
（）
3.3 Error correction Models of GDP, M0 and Interest Rate
According to VAR model, AIC and SC principles, the error correction models of GDP, M0 and
interest rate are as follows:
dLnGDP = 0.019 + 0.08dLnGDPt −1 + 0.10dLnGDPt −2 − 0.35dLnM 0 t −1
− 0.58dLnM 0 t − 2 + 0.25dLnRatet −1 − 1.03dLnRatet − 2 − 0.61ECt −1
dLnM 0 = 0.019 − 0.09dLnGDPt −1 + 0.02dLnGDPt − 2 − 0.72dLnM 0 t −1
− 0.35dLnM 0 t − 2 + 0.01dLnRatet −1 − 0.12dLnRatet − 2 + 0.03ECt −1
dLnRate = −0.002 + 0.02dLnGDPt −1 + 0.04dLnGDPt − 2 + 0.38dLnM 0 t −1
+ 0.08dLnM 0 t − 2 + 0.05dLnRatet −1 + 0.15dLnRatet −2 − 0.01EC t −1
（ ）
（10）
（11）
（12）
The adjustment coefficient of EC in the short-term equation
10 indicates that the short-term
coordinating process enjoys higher adjusting speed of -61% and comply with the negative feedback
process of error correction. Compared with that of M2 and M1, we think that if only examine from the
estimation of the long-term and short-term equations, the impact of M0 to GDP is evidently greater that
that of M2 and M1 to GDP. Likewise,it is known that from the EC of Formula 11 , its symbol is
inconsistent with the negative feedback significance of error correction, indicating that the impact of M0
and interest rate to GDPis mainly realized through the short-term formula 10
i.e. long-term balanced
relationship is mainly formed by the impact of LnM1to LnGDP, which also shows that cash M0 in
circulation enjoys stronger long-term binding force, while fast short-term adjusting speed.
（ ），
（ ）
4 Conclusion
This paper, based on monthly data from Jan.2000 to Jun.2007, introducing interest rate, investment
and consumption concepts and adopting modern computing techniques, has herein reviewed the
coordinating relationships between GDP, money supply M2, M1, M0 and interest rate. Review findings
indicate that between GDP, money supply M2, M1& M0 and interest rate, there exist long-term stable
659
relationship, and M2, M1 & M0 and interest rate are of significantly positive correlation with GDP. In
the long run, the GDP elastic coefficients of M2, M1, M0 are respectively 0.77, 0.83 and 1.30; GDP
elastic coefficients of the interest rate are between 0.24 and 0.33. In the short term, based on estimated
error correction models, the error correction items of GDP short-term fluctuation comply with reverse
modification mechanism, and the error correction coefficients of M2, M1 and M0 are 0.55, 0.55 and
0.61 respectively.
References
1. Fang Xianming, Sun Xuan, Xiong Peng and Zhang Yino: Positivist Study of Effectiveness of
Interest-Rate Transmitting Mechanism in Chinese Monetary Policy, Journal of Modern Economic
Sciences Issue 4, 2005(in Chinese)
2. Feng Cunping, Mobility of the Effect of Money Supply to Output and Price, Journal of Financial
Research, Issue 7, 2002(in Chinese)
3.Guo Mingxing, Liu Jinquan, Liu Zhigang Testing of Interaction between Chinese Money Supply
Growth Rate and Internal Output Growth Rate---New Proofs from MS-VECM Model, Journal of
Computing Economy and Technological Economy Research, Issue 5, 2005(in Chinese)
4. Jiang Yingkun, Liu Yanwu, Zhao Zhenquan: Positivist Analysis of EffectivenessofTransmitting
Mechanism of the Monetary Channel and Credit Channel, Journal of Financial Research, Issue 5, 2005
(in Chinese)
5. Yu Ze:Regional Effect Analysis of Chinese Monetary Policies, Journal of Management World, Issue 5,
2006(in Chinese)
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