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Chinas monetary policy: Quantity versus price rules q
Wenlang Zhang *
Research Department, Hong Kong Monetary Authority, 55th Floor, II International Finance Centre, 8 Finance Street, Central, Hong Kong
a r t i c l e i n f o
Article history:
Received 29 May 2007
Accepted 9 September 2008
Available online 23 September 2008
JEL classification:
E52
E58
Keywords:
Monetary policy rules
DSGE model
Taylor rule
a b s t r a c t
Two monetary policy rules, the money supply (quantity) rule and interest rate (price) rule,
are explored for China in a dynamic stochastic general equilibrium model. The empiricalresults seem to indicate that the price rule is likely to be more effective in managing the
macroeconomy than the quantity rule, favoring the governments intention of liberalizing
interest rates and making a more active use of the price instrument. Moreover, the econ-
omy would have experienced less fluctuations had interest rate responded more aggres-
sively to inflation.
2008 Elsevier Inc. All rights reserved.
1. Introduction
Compared with advanced economies, Chinas monetary policy appears to be more complicated, as can be seen at least in
the following two aspects. First, although the Law of Peoples Bank of China (PBoC) states that the objective of monetary pol-
icy is to maintain price stability so as to promote economic growth, in reality Chinas monetary policy seems to have been
assigned more goals than mandated by the law. According to a speech of the PBoC governor published in a recent issue of
Caijing Magazine (in Chinese, December 25, 2006), not only should monetary policy ensure price stability and promote eco-
nomic growth, it is also supposed to maximize employment and achieve balance of payments equilibrium. In addition, it is
expected to help promote financial liberalization and reforms. Second, unlike advanced economies which employ mainly one
policy instrument, short-term interest rate recently and money supply in the earlier period, Chinas monetary authority usu-
ally applies instruments of both quantity and price in nature in view of imperfect monetary policy transmission mechanism.
Take the recent episode as example, in order to rein in fast growth in investment, the PBoC has raised benchmark interest
rates, increased the reserve requirement ratio several times and issued a certain amount of one-year bills to selected bankswhose loans were considered to have grown too fast since April 2006.
The main reason that money supply gave way to interest rate as a policy instrument in numerous countries is that the
latter is usually difficult to control by monetary authority. The quantity rule is rooted in the Fisher quantity theory of money
and the assumption that velocity of money is relatively stable in the short run. But, as shown byMishkin (2003, chapter 21)),
the velocity of money has fluctuated too much to be seen as constant in the US from 1915 to 2002. Chinas velocity of money
(M2) also seems to be unstable and has increased remarkably since the early 1990s. Another assumption of the money-
supply rule is that there exists a close tie between inflation and nominal money growth. But this linkage has become looser
0164-0704/$ - see front matter 2008 Elsevier Inc. All rights reserved.doi:10.1016/j.jmacro.2008.09.003
q The views in this paper are solely those of the author and should not be interpreted as those of Hong Kong Monetary Authority.
* Tel.: +852 2878 1830; fax: +852 2878 1897.
E-mail address:[email protected]
Journal of Macroeconomics 31 ( 2009) 473484
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Journal of Macroeconomics
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because money demand may experience large volatility. Numerous papers have addressed this issue, see Wolters et al.
(1998) for example. In fact the tie between money and inflation in China has also become looser in the past few years, mainly
as a result of financial deepening. In addition, as shown inLaurens and Maino (2007), the gaps between actual and targeted
money growth have been relatively large between 1994 and 2004. Evidence in this line seems to indicate that money supply
should be assigned a less important role than interest rate. Indeed, as stated in the monetary policy implementation report of
2006 Q4, the PBoC is inclined to make a more active use of price-based policies and interest rate liberalization has become a
main task of monetary authority.Ha and Fan (2003), for example, find that Chinas investment was more sensitive to real
lending rate during 19942002 than during 19811993.
The research below aims at exploring two important monetary policy instruments in China, quantity and price, studying
their impacts and providing some advice for policy makers. Unlike most papers on Chinas policies in the literature, we will
employ a dynamic stochastic general equilibrium (DSGE) model. A few macro models have been set up for China, most of
which are macroeconometric models paying little attention to micro-foundations, see He et al. (2005) and Scheibe and Vines
(2005)for instance. One may argue that DSGE models might not capture Chinas economy well since it is not yet a perfect
market economy. As argued by Scheibe and Vines (2005) and Chow (2002), however, the Chinese economy has become
marketised to such a degree since 1978 that it is not inappropriate to model Chinas economy in a framework of the ad-
vanced economies. In addition, as mentioned by Chow (2002), a theoretical-quantitative approach is as important as a his-
torical-institutional one for China.
The remainder of the paper is organized as follows. The second section presents some empirical evidence on Chinas mon-
etary policy. Section3 presents the DSGE model and shows the consequential first order conditions engendered by house-
holds and firms optimization behaviors. The fourth section undertakes some numerical study of alternative monetary
policies, and section five concludes the paper.
2. Chinas monetary policy
Although money supply has been supposed to be a dominant policy instrument in China in the past decades, as the econ-
omy becomes more market-oriented over time, the quantity rule seems to be less operable as Chinas money velocity (the
ratio of nominal GDP to nominal M2) and multiplier (the ratio of M2 to reserve money) have increased significantly in the
past 15 years.1 This evidence has at least two implications: First, it is increasingly hard to determine money demand and as a
result, hard to determine money supply. Second, it challenges Chinas practice of controlling broad money by controlling base
money (reserve money). In addition, the tie between money growth and inflation has loosened in the past years, with the cor-
relation coefficient between CPI inflation and broad money growth decreasing from over 0.8 during 19921999 to about 0.16
during 20002006. In contrast, the tie between inflation and interest rate seems to have become closer, as the correlation coef-
ficient between CPI inflation and one-year benchmark lending rate changed from 0.16 during 19921999 to 0.676 during
20002006.
2.1. Quantity rule
Burdekin and Siklos (2005)claim that China seems to have followed the so-called McCallum rule.2 Assuming the annual
target nominal GDP growth to be 12% (target real growth of 8% plus target inflation of 4%), Liu and Zhang (2007)find that the
McCallum rule cannot capture Chinas money supply well during 19912006, especially before 1997. The differential between
the money supply simulated with the McCallum rule and the actual one was relatively large during 1991 and 1997, exceeding
40% points around 19931994. In fact, a main drawback of this monetary policy rule is that it does not take into account for-
ward-looking behaviors. In addition, it does not consider inflation pressure explicitly. In the literature of DSGE models, econo-
mists usually assume money growth to be a function of technology shock, see Walsh (2003, chapter 2)), for example. This
assumption is probably inappropriate for China as its money growth has been employed as an active instrument to manage
the economy and can not be determined by one exogenous variable such as technology shock. Defining mtas the deviation
of nominal money growth from its long-run value, we will employ the following quantity rule for China:
mt i1mt1 i2Etpt1 i3bYt vm;t 0 < i1 < 1; i2;3 >0 1wherevm;t is assumed to be an AR(1) process
vm;t kmvm;t1 t; 0 < km < 1
where t is white noise, ptdenotes inflation rate,3 bYtis output gap and E is expectation operator. Such a rule dates back to
Taylor (1979). Employing a dynamic macroeconomic model and taking money supply as policy instrument,Taylor (1979)finds
that the optimal money supply can be set as a function of inflation and output gap. In a recent paper, Taylor (2000)states that
1 While the former increased from about 3 to 6, the latter rose from 2.5 to 5 in the same period.2 This rule reads:.t g
t Dvelt 0:5g
t gt1;where.t denotes the growth rate of nominal money supply,g
t the target growth of nominal GDP,gtthe
actual growth of nominal GDP andDveltthe growth of velocity of money.3 One may assume it has a constant or zero target for simplicity.
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such a rule can still be relevant for emerging market economies. Here we consider expected inflation rate to highlight the PBoCs
increasing concerns over inflation expectations in recent issues of monetary policy implementation reports. The parameter i1reflects the smoothing effect in money supply as central banks usually feature some smoothing behavior to avoid drastic eco-
nomic fluctuations brought about by sudden changes in policies. Let Mtdenote nominal money supply with growth rate.t, weknow
Mt 1 .tMt1 ) mt 1 .t1 pt
mt1
where mtMt
Ptwith Ptdenoting price level.
FollowingLiu and Zhang (2007)we seti1 at 0.8,i2 1:0 andi3 0:5, suggesting that the monetary authority respondsactively to expected inflation, with a lower response to output. 4 Measuringmtby the deviation of actual money (M2) growthfrom its HP trend, we show the actualmtand that simulated with the above equation in Fig. 1. This figure shows that the sim-ulated series can capture the actual series relatively well except in 1994 when actual money growth was very high. Comparing
the simulated series inFig. 1and the McCallum rule inLiu and Zhang (2007), one may claim that the rule in Eq.(1) captures
Chinas money growth rule better. Measuring vm;twith the residuals in Eq.(1) we obtain the estimate ofkm 0:75.
2.2. Interest rate rule
Taylor (1993)proposes that short-term interest rate can be set as function of output gap and inflation. Liu and Zhang
(2007)find that the standard Taylor rule can not capture Chinas interest rate well during 1992 and 2006, especially before
1996. In particular, the differential between the actual one-year lending rate and the simulated interest rate can be as large
as 30% points in 1994. Below we will employ a modified Taylor rule for China: 5bRt k1bRt1 1 k1k2Etpt1 pt k3pt k4bYt vR;t; 1 > k1 >0; k2;3;4 > 0 2where bYtand bRtdenote output gap and the deviation of short-term rate from its steady state, respectively. The shock vR;tisassumed to follow an AR(1) stochastic process:
vR;t kRvR;t1 tt; 0 < kR
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seems to have captured Chinas interest rate rule better than the original Taylor rule without expectation and smoothing
shown inLiu and Zhang (2007). The differential between the actual and the simulated series is less than 2% points mostof the time. Measuring vR;twith the residuals from the above equation we obtain the estimate ofkR 0:51.
3. A dynamic stochastic general equilibrium model
3.1. Households
There exists a continuum of households, indexed by k,k 2 0; 1. Householdkmaximizes the following objective function
EtX1i0
biUk;ti
with
Uk;t 11 r
Ck;t hCt11r 1
1 cMk;tPt
1c 11 g
N1gk;t
s.t.
Mk;tPt
Bk;tPtRt
Ck;t Ik;tMk;t1
Pt
Bk;t1Pt
Wk;tPt
Nk;t rctKk;t Dk;t Tk;t 3
The household enters periodtwith capital stockKk;t, nominal money balanceMk;t1and coupon bondBk;t1.Rtand rct denote
gross return of bond and rental rate of capital, while Ck;t, Ik;tand Nk;t denote real consumption, investment and labor supply in
period t, respectively. The parameter h is referred to as habit parameter, so that hCt1denotes the external habit stock with Ctbeing aggregate consumption.rdenotes the coefficient of relative risk aversion of households,cthe inverse of the elasticityof money holdings with respect to interest rate. g denotes the inverse of the elasticity of work effort with respect to realwage.Wk;tis nominal wage. Each household is assumed to own an equal share of firms and receives an aliquot share of real
aggregate profits Dk;t
.Tk;t
denotes the real net transfer from government in period t. Assuming complete contingent claims
markets for labor income, and identical initial endowments of capital, bonds and money, all optimality conditions will be the
same across households, except for labor supply and wage. We can, therefore, drop the indexkfor all variables but labor and
wage.
The first-order conditions (FOCs) with respect to Ct andBt read
bEtCt1 hCt
rPtRt
Ct hCt1rPt1
1; 4
while the FOC with respect to Mt reads
MtPt
c
Rt 1
RtCt hCt1
r 5
Given the capital stock accumulation equation
Kt1 1 dKt It 6
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
94 95 96 97 98 99 00 01 02 03 04 05 06
ACTUAL
FITTED
Fig. 2. Actual and simulated interest rate rules.
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with d denoting depreciation rate, we have the following FOC with respect to investment and capital stock
1 bEtCt hCt1Ct1 hCt
r1 d rct1 7
In addition, the aggregate labor supply Ntis assumed to be a CES function of differentiated labor provided by household k
with the Dixit-Stiglitz elasticity of substitution among differentiated labor services being l(>1). The demand for differentiated
labor then reads
Nk;t Wk;tWt
lNt
In each period all households can adjust their wages, but only 1 nfraction ofhouseholds can adjust their wagesoptimally,
with the rest n fraction of households setting their wages according to the rule 7
Wk;t Vt1Wk;t1
whereVt PtPt1
1 pt. The household which can optimize the wage in period tthen chooses the optimal wage Wk;tto max-
imize the following objective function:8
Et
X1
i0
bni Uct i; t
PtiWk;tXtiNk;ti;t PtiCti;t UCti;t;Nk;ti;t
( );
where Uct i; t denotes the marginal utility of consumption at t i of workers that optimize at t, and Nk;ti;t the hours
worked at t iat the wage set at time t:
Nk;ti;tWk;tXti
Wti
lNti
with Xti 1, for i 0 and Xti VtVt1Vt2;. . .; Vti1, fori P 1.
The FOC with respect to Wk;tthen results in
Wk;t l
l 1
EtP1
i0bni Xti
Wti
l1gN1g
ti
Et
P1i0bn
i XtiWti
lXtiPti
Uct i; tNti
264375
1
1lg
: 8
The above equation shows that one can replaceW
k;twithW
t since all households have the same optimal wage. Based onthe above FOC and the following aggregate wage equation:
Wt 1 nWt
1l nVt1Wt11l
11l; 9
one can then obtain the following linearized real wage equation:
-tU
1 gln-t1 pt1 1 b1 glnpt 1 glnbEt-t1 pt1
1 bn1 n gbNt r1 h
bCt bCt1h iwith-t
WtPt
andU 11b1gln1bn1n.
3.2. Firms
3.2.1. Final goods
Final goodYt(subject to perfect competition) is assumed to be a CES function of the intermediate goodsYj;tproduced by a
continuum of firms indexed byj 2 0; 1, with the elasticity of substitution between varieties of intermediate goods being h.
LetPj;tdenote the price of intermediate goods j at time t, the demand for intermediate goods j then reads
Yj;t Pj;t
Pt
hYt
7 There are also economists assuming that this group of households set wage according to last-period wage inflation or a combination of last-period price and
wage inflation rate. Here we follow Sbordone (2006). assuming households that can not set wage optimally set their wages according to last-period price
inflation. This assumption seems to capture Chinas situation better than others because Chinas officially released wage growth data reflect only the wage
dynamics of a small part of employees. Migrant workers salaries, for example, are not well shown in the existing data.8 FollowingSbordone (2006), we assume the household maximizes the expected stream of discounted utility from the new wage.
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3.2.2. Intermediate goods
Intermediate goodsYj (subject to monopolistic competition) is assumed to be produced with the following production
function:
Yjt ZtNaj;tK
1aj;t ; 0 < a < 1;
where Nj;t and Kj;t denote labor and capital used for producing Yj;t. Ztdenotes technology shock subject to the following
path
lnZt j lnZ 1 j lnZt1 et; 0 < j < 1; 10
with Zbeing the mean ofZt andeta white noise. The FOCs with respect to Nj;tandKj;t are
-t autZtNj;tKj;t
a111
ut 1
Zt
-ta
a rct1 a
1a12
whereutdenotes the real marginal cost.
3.2.3. Price setting
Here we followChristiano et al. (2005) and Smets and Wouters (2002)assuming that in each period all firms can adjust
their prices, but only 1 xfraction of firms are allowed to adjust their prices optimally, and the remainingxfraction adjusttheir prices asPj;tVt1Pj;t1 . Firmj which can re-optimize its price at tchooses the optimal priceP
j;tto maximize the pres-
ent value of its real profits. The optimal price then reads
Pj;tPt
h
h 1
EtP1
i0xiKtiuti
PtiPt
hYtiX
hti
EtP1
i0xiKtiuti
PtiPt
h1YtiX
1hti
13
whereKtidenotes the stochastic discount factorbi
CtiCt
r. One can drop the indexjin Pj;tas the optimal price is the same for
each firmj .
From
Yj;t Pj;tPt
hYt 14
and assuming symmetric equilibrium with respect to intermediate goods, we know that the aggregate price at tis
Pt 1 xPt
1h xVt1Pt1
1h 11h: 15
From Eqs.(13) and (15)we can derive the following linearized Phillips curve:
pt x1 bx2
pt1 2 x bx bx2
1 bx2 Etpt1 1 x1 bx ut: 16
4. Policy analysis
4.1. Linearized equations
One can calculate the steady states of the variables of interest from the series of FOC conditions derived above. The steadystate ofRt, for example, isR
1baccording to Eq.(4). Assuming general equilibrium and employing the quantitative monetary
policy rule, one can then log-linearize relevant equations around the steady states of variables:
bCt h1 h
bCt1 11 h
EtbCt1 1 h1 hr
bRt Etpt1 17bCt hbCt1 EtbCt1 1 hr Etrct1 18bYt 1 ah 1
hbCt 1 ah 1
hbIt 19
bYtbZt abNt 1 abKt 20
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bKt1 1 dbKt dbIt 21pt
x1 bx2
pt1 2 x bx bx2
1 bx2 Etpt1 1 x1 bx ut 22
-tU
1 gln-t1 pt1 1 b1 glnpt 1 glnbEt-t1 pt1
1 bn1 n gbNt r1 h bCt hbCt1h i 23mt
r1 hc
bCt rh1 hc
bCt1 1cbRt 24mt mt1 pt mt 25
mt i1mt1 i2Etpt1 i3bYt vm;t 26bZt 1 jbZt1 et 27u a-t 1 arctbZt 28bNt rctbKt -t 29
In the case of interest rate rule, one then replaces Eqs. (24)(26)with Eq.(2).
4.2. Parameterization
As is known, it is quite challenging to parameterize a macro model for China because (a) Chinas data are relatively scarce
and (b) China has been shifting from a planning economy to a market one, suggesting possible structural changes in the past
decade. In view of this problem, economists have usually chosen to estimate single equations rather than a simultaneous
system for China. In the research below we will follow this line of literature, estimating some of the parameters with avail-
able data and assigning values to others according to related works in the literature. Equations will be estimated separately
for variable sample periods according to data availability.9
Following Walsh (2003), we set r 2. Estimating Eq.(18)with data of 19932005 by GMM we obtain h 0:61 (t-st.110.24).10 a and d are set at 0.4 and 0.04, respectively, following the estimates ofHe et al. (2007). Settinga 0:4 and esti-mating(19)with data of 19932007 one can figure out h 4:61.11 The average (annual) nominal interest rate is 0.08 from
1978 to 2005, which might justify a quarterly rate of 0.02 in the steady state and b 0:98 since R 1b. The GMM estimation
of Eq. (22)with data of 1995 to 2005 shows that x 0:84 (t-st. 24.10). Our estimation of the Phillips curve looks close tothat of Funke (2005)who estimates the new Keynesian Phillips curve for China with various methodologies. Following the
estimates of Liu (2007)we set g 6:16, n 0:6 and l 2. The estimation of Eq. (24) with data of 1992-2006 shows thatc is 3.13 (t-st. 1.92).12 Using total factor productivity (TFP) data from He and Zhang (2008) we obtain the estimate ofj 0:5.13
The main parameters are summarized inTable 1.
4.3. Simulations
Next, we will solve the above linear dynamic system by methods of undetermined coefficients with the algorithm devel-oped byUhlig (1999).Uhlig (1999)divides all variables into three categories: endogenous state variablesUt, jump variables
Wtand exogenous stochastic processesZt, withUt,WtandZtbeing vectors ofa1,a2anda3elements, respectively. Then thelinearized system can be arranged as follows:
9 Estimations are undertaken with quarterly data. When quarterly data are not available, we convert annual data into quarterly data with Eviews.10 Consumption in this equation is proxied with retail sales as consumption data from national account are annual. Consumption gap is measured with
percentage deviation of actual retail sales from its HP-filter trend. Return to capital is proxied by the marginal product of capital estimated byHe et al. (2007).11 Output gap, consumption and investment gaps are measured with the percentage deviations of the actual values of output, consumption (national account
data of total consumption) and investment (gross capital formation) from their HP-filter trends.12 Real money gap is measured by the percentage deviation of real broad money from its HP-filter trend.13 WhileHe et al. (2007)estimate TFP growth for China with the Cobb-Douglas production with national data, He and Zhang (2008)estimate TFP growth with
the Malmquist index using panel data. The latter seems to outperform the former since the production function approach assumes production is alwaysconducted on the frontier and may overestimate TFP growth.
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Table 1
Parameterization
h r a x b n g l h c j d
0.61 2.0 0.40 0.84 0.98 0.60 6.16 2.0 4.61 3.13 0.5 0.04
-1 0 1 2 3 4 5 6 7 8-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Years after Shock
PercentDeviatio
nfrom
SteadyState
Inflation
Output
-1 0 1 2 3 4 5 6 7 8-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
Years after Shock
PercentDeviationfrom
SteadyState
Inflation
Output
-1 0 1 2 3 4 5 6 7 8-0.35
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
Years after Shock
PercentDeviationfrom
SteadyState
Inflation
Output
Fig. 3. Impulse responses to shocks with quantity rule.
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0 AUt BUt1 CWt DZt; 30
0 EtFUt1 GUt HUt1 JWt1 KWt LZt1 MZt 31
Zt1 NZt z;t1; Etz;t1 0; 32
where Cis assumed to be of size a4 a2,a4 P a2 and of ranka2, Fis of size a1 a2 a4 a1.Nis assumed to have onlystable eigenvalues. Then one may express UtandWt as
-1 0 1 2 3 4 5 6 7 8-1.5
-1
-0.5
0
0.5
1
Years after Shock
PercentDeviationfrom
SteadyState
InflationOutput
-1 0 1 2 3 4 5 6 7 8-0.2
0
0.2
0.4
0.6
0.8
1
1.2
Years after Shock
PercentDeviationfrom
SteadyState
Inflation
Output
-1 0 1 2 3 4 5 6 7 8-0.35
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
Years after Shock
PercentDeviationfrom
SteadyState
Inflation
Output
Fig. 4. Impulse responses with interest rate rule.
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Ut S1Ut1 S2Zt 33
Wt S3Ut1 S4Zt: 34
We will explore how the two policy rules differ from each other from two perspectives: (a) which policy instrument is
more powerful assuming a shock to each of them separately, and (b) under which policy rule the economy experiences less
fluctuations assuming the economy faces shocks of other main economic variables than monetary policy since less fluctua-
tions in inflation and output imply a lower loss to the central bank.14
The impulse responses of inflation and output gap toshocks in money growth, technology bZtand real wage are presented in Fig. 3.
15
The upper panel shows that a positive shock from nominal money growth will lead to a half percentage point increase in
inflation in the first two quarters, together with a 0.6% point upturn in output, followed by a slide in GDP by about 0.3% point
in the second year. This suggests that although money can lead to a temporary expansion in GDP, it may result in an output
reduction in the medium term. The middle panel shows that output will increase by over 0.9% point in the first year follow-
ing a positive technology shock, while inflation may decline by 0.3% point in the meantime. Inflation declines because supply
increases due to productivity improvement. In the lower panel we show the reactions of inflation and output to a percentage
point deviation of real wage from its steady state. Clearly, while inflation increases by 0.1% point, output may decrease by
0.33% point.
The impulse responses of output and inflation to money growth, technology and real wage when interest rate rather than
money supply is employed as policy instrument are shown inFig. 4. Comparing Fig. 3with Fig. 4, one may have the following
findings: (a) the price instrument seems to be more powerful than the quantity instrument, and (b) facing similar shocks
from main variables in the economy, inflation and output may experience less fluctuations when the price rule rather thanthe quantity rule is in operation. Point (a) can be seen by comparing the upper panels of the two figures. While a shock in
interest rate may lead to decreases of inflation and output of between one and 1.5% points, a shock in money growth leads to
increases in inflation and output of about 0.50.6% point. This can also be partly reflected by the response coefficients of
inflation and output gap to monetary policy (relevant elements inS2 and S4). The response coefficients of inflation to shocks
in money growth and interest rate are 0.264 and 0.840, respectively (Table 2). Meanwhile, the response coefficients of out-
put gap to shocks in money growth and interest rate are 0.584 and 1.423, respectively (Table 3). In fact, observers of Chinas
economy have argued that impacts of interest rate on the economy have been underestimated as small-and-medium size
and private enterprizes are much less likely to get loans from banks than large-size and state-owned enterprizes (SOEs)
when monetary tightening occurs. In order to get the same amount of loans as SOEs the former may have to pay extra costs
other than interest.
Point (b) can be seen by comparing the middle and lower panels ofFigs. 3 and 4. Clearly, while a shock in technology may
lead to an increase in output of similar size in both figures, inflation experiences less fluctuations in Fig. 4. Moreover, both
inflation and output converge to their steady states much faster in Fig. 4. We get similar findings with respect to a shock inreal wage. While output decreases by about 0.33% point inFig. 3, it slides by less than 0.3% point inFig. 4. Likewise, inflation
experiences much less fluctuations inFig. 4. Moreover, both inflation and output converge to their steady states faster in
Fig. 4than inFig. 3. One can also see this point from the response coefficients of inflation and output to technology and real
wage under different policy rules. As shown inTables 2 and 3, the response coefficients of inflation and output to shocks in
technology and real wage are lower in magnitude under the price rule than under the quantity rule.
Some economists argue that China should have been more aggressive in interest rate policy. Take the recent episode of
monetary policy as example, although the PBoC has raised interest rate gradually, real interest rate still remains quite low
and even negative. The inactive policy stance of the authority has been argued by some commentators to be partly respon-
sible for upsurges (or bubbles) in stock prices since 2006. Moreover, inflation remains elevated. Artificially low costs of cap-
Table 2
Response coefficients of inflation to shocks
Monetary policy Technology Real wage
Quantity rule 0.264 0.192 0.019
Price rule 0.840 0.123 0.002
Table 3
Response coefficients of output to shocks
Monetary policy Technology Real wage
Quantity rule 0.584 0.963 0.328
Price rule 1.423 0.961 0.300
14 Woodford (2003) shows the links between quadratic loss functions of inflation and output and households objective functions.15
One may also see the reactions of inflation and output to shocks in other variables than real wage and technology. We have also simulated shocks for someother variables, inflation for example, and find that the main findings remain essentially unchanged.
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ital have not only led to wastes of resources but may have fueled volatility of economy. In fact, Taylor (1993)sets the coef-
ficient of inflation at above one and that of output gap at 0.5.Taylor (1999)further raises the coefficient of output gap to
unity. In the interest rate rule employed above, we have used the estimated coefficients of inflation and output gap. Next,
we will conduct an counterfactual experiment by assuming that interest rate reacts more aggressively to inflation and out-
put gap. Namely, we raise the coefficient of expected inflation k2 to 1.0 to see how inflation and output may have re-
sponded to various shocks in the economy. The simulation results are shown in Fig. 5.
ComparingFig. 4withFig. 5, one finds that the economy would have experienced less fluctuations if interest rate had
been more aggressive. For example, while output declines by about 0.3% point in the presence of a wage shock in Fig. 4,
it declines by less than 0.25% point inFig. 5. Inflation and output also fluctuate less in the wake of a technology shock in
Fig. 5than inFig. 4. Looking at the response coefficients of inflation and output to technology and real wage provides us
clearer evidence. For example, while the response coefficient of output gap to real wage is 0.300 inFig. 4, it is 0.242
inFig. 5.
5. Conclusions
Monetary policy with money supply as instrument seems to become more difficult to conduct in China than before, as
money multiplier and velocity have been increasing noticeably and the linkage between money supply and inflation be-
comes weaker over time. Experiments in a DSGE model based on data in the past decade indicate that effects of a price rule
on the economy seem to have become more significant than those of a quantity rule. Moreover, the economy may experience
less fluctuations in the presence of shocks from main macroeconomic variables when the price rule is employed to manage
the macroeconomy. The findings seem to favor the governments intention of liberalizing interest rates and making a moreactive use of the price instrument in recent years as the economy becomes more market-oriented.
-1 0 1 2 3 4 5 6 7 8-0.2
0
0.2
0.4
0.6
0.8
1
1.2
Years after Shock
PercentDeviationfrom
SteadyState
Inflation
Output
-1 0 1 2 3 4 5 6 7 8
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
Years after Shock
PercentDeviationfrom
SteadyState
Inflation
Output
Fig. 5. Impulse responses with more aggressive interest rate rule.
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We have also conducted a counterfactual study assuming that the monetary authority had reacted more aggressively to
inflation than estimated with data. The experiments seem to indicate that the economy would have experienced less fluc-
tuations had interest rate been more aggressive.
References
Burdekin, R.C.K., Siklos, P.L., 2005. What has driven Chinese monetary policy since 1990? Investigating the Peoples Banks policy rule. East-West CenterWorking Paper No. 85.
Chow, G., 2002. Chinas Economic Transmission. Blackwell Publishers Ltd., Oxford, 1990.Christiano, L.J., Eichernbaum, M., Evans, C.L., 2005. Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy
113 (1), 145.Clarida, R., Gali, J., Gertler, M., 1998. Monetary policy rules in practice: some international evidence. European Economic Review 42, 10331067.Funke, M., 2005. Inflation in mainland Chinamodelling a roller coaster ride. Hong Kong Institute for Monetary Research, Working Paper 15/2005.Ha J., Fan K., 2003. The monetary transmission mechanism in the mainland. Research memorandum 11/2003, Hong Kong Monetary Authority.He, D., Zhang, W., 2008. How dependent is Chinas economy on exports? Hong Kong Monetary Authority working paper.He, X., Wu, H., Cao, Y., Liu, R., 2005. China-QEM: A Quarterly Macroeconometric Model of China. Social Sciences Academic Press, Beijing.He, D., Zhang, W., Shek, J., 2007. How efficient has been Chinas investment? Empirical evidence from national and provincial data. Pacific Economic Review
12 (5), 597617.Laurens, B.J., Maino, R., 2007. China: Strengthening monetary policy implementation. IMF Working Paper, WP/07/14.Liu, B., 2007. Developing a DSGE model for China and its application in monetary policy. PBoC Research Bureau (in Chinese).Liu, L., Zhang, W., 2007. A model based appraoch to monetary policy analysis for China. Hong Kong Monetary Authority Working Paper 18/2007.Mishkin, F.S., 2003. The Economics of Money. Banking and Financial Markets. Addison Wesley.Sbordone, A.M., 2006. US wage and price dynamics: a limited-information approach. International Journal of Central Banking 2 (3), 155191.Scheibe, J., Vines, D., 2005. After the revaluation: Insights on Chinese macroeconomic strategy from an estimated macroeconomic model. Manuscript St
Antonys College and Department of Economics. University of Cambridge.
Smets, F., Wouters, R., 2002. An estimated dynamic stochastic general equilibrium model of the euro area. Journal of the European Economic Association 1(5), 11231175.Taylor, J.B., 1979. Estimation and control of a macroeconomic model with rational expectations. Econometrica 47 (5), 12671286.Taylor, J.B., 1993. Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy 39, 195214.Taylor, J.B., 1999. A historical analysis of monetary policy rules. In: Taylor, J.B. (Ed.), Monetary Policy Rules. University of Chicago Press, Chicago.Taylor, J.B., 2000. Using monetary policy in emerging market economies. Standford University, Unpublished.Uhlig H., 1999. A toolkit for analyzing nonlinear dynamic stochastic models easily. Department of Economics, Humboldt University.Walsh, C.E., 2003. Monetary Theory and Policy. The MIT Press, Cambridge, Massachusetts.Wolters, J., Tersvirta, T., Ltkepohl, D.H., 1998. Modelling the demand for M3 in the united Germany. The Review of Economics and Statistics 80 (3), 399
409.Xie, P., Luo, X., 2002. Taylor rule and its empirical tests in Chinas monetary policy. Economic Research Journal 3, 312 (in Chinese).
484 W. Zhang/ Journal of Macroeconomics 31 (2009) 473484