2009 Zhang

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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

Contents lists available at ScienceDirect

Journal of Macroeconomics

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c at e / j m a c r o
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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.

474 W. Zhang/ Journal of Macroeconomics 31 (2009) 473484
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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.

W. Zhang / Journal of Macroeconomics 31 (2009) 473484 477

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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


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


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


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


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


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


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).


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