China's Monetary Policy

China’s monetary policy An empirical analysis using the Taylor rule.

15/05/2015

Abstract

This paper empirically examines China’s monetary policy, using the

Taylor rule from 1993 and from 2001 over the period 2000:1-­2015:1.

We compare the lending rate, set by the People’s Bank of China (PBC), to the Taylor rule implied interest rates. Specifically, we tried to estimate PBC’s reaction function that models the PBC’s interest rate determination process.

Furthermore, we show that the Taylor rule can be used as a benchmark to understand China’s monetary policy. The NLS estimates show that benchmark interest rate, responds passively to the CPI gap and output-­ gap. Furthermore, we point out that the literature fails to mention heteroskedasticity caused by the period 2008:3-­2009:1, which is likely to be caused by stimulative measures taken by the Chinese government.

Keywords: Taylor rule, China, monetary policy, financial crisis

Catello Alvino Sybren Dijkstra Vasile Nagacevschi

s2450763 s2409267 s2507102

c.alvino@student.rug.nl s.j.dijkstra.3@student.rug.nl v.nagacevschi@student.rug.nl

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1. Introduction

One of the main issues scholars debate over is whether monetary policy should be conducted in accordance with a uniform rule, or whether the policy should be conducted in a discretionarily fashion by central banks. Two types of monetary policy rules can be found in the literature. One is the purely theoretical derivation of the optimal monetary policy rule, which can be obtained by analysing the optimal behaviour of central banks in subject to the loss function and macroeconomic restraints. The second type of policy comprises setting the monetary policy rule exogenously. One of the more known examples of this exogenous rule setting is the Taylor rule. The Taylor rule was introduced by Stanford economist John Taylor in order to stipulate by how much the central bank should adjust nominal interest rates in response to changes in the inflation rate, the real Gross Domestic Product (GDP), and other economic variables depending on which Taylor rule one uses. To a large degree, the estimated Taylor rule can be considered as a benchmark or starting point for the central banks when investigating possible monetary policies.

Many central banks’ conduct of monetary policy, including the Federal Reserve, the Bank of England, the Bank of Japan, the Bundesbank, and the European Central Bank, has been examined according to the Taylor rule (McCallum 1993, Judd, Rudebusch 1998, Gerlach, Schnabel 2000, McCallum 2000, Nelson Edward E 2000). Although the research about the monetary policy conduct in major industrial countries has proliferated, little English written literature can be found on the transition and emerging market economies’ monetary policy analysis, using the Taylor rule. This is the case of China, on which only Chinese written literature, and a considerably limited English written literature, is available.

The lack of studies regarding this rule application to the interest rate in China, in the English written literature, could reflect the obstacles we came across in conducting our research. In the first place, the monetary policy in a transition and emerging market economy tend to lack consistency. This may be due to the fact that the economy in these countries is likely to be under reconstruction or major reform. Indeed, China is currently undergoing substantial market-­oriented reforms. Moreover, data availability for non-­Mandarin speakers is still far from satisfactory. These practical obstacles could prevent scholars from doing research in these areas. However, in this paper we try to overcome these boundaries, hence this paper’s main purpose is to estimate how well the Taylor rule estimates China’s monetary policies, during the period 2000:1 – 2015:1.

The remaining consists of five sections. Section 2 will provide a brief overview of the literature. Section 3 will describe the data used. Section 4 will provide the econometric model used. Section 5 will cover the results obtained. Section 6 will conclude this empirical paper with a summary.

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2. Literature Overview

As mentioned in the introduction a substantial amount of research has been focussed on monetary policy in macroeconomic and monetary economics. In terms of Chinese monetary policy rule, there has been little English literature on the application of the Taylor rule to China. On the other hand, the Chinese literature regarding monetary policy effectiveness and monetary policy rule is increasing after 2000. (Ping, Xiong 2002) is the first Chinese paper we could find to conduct the empirical study of the Taylor rule with Chinese data, and their viewpoint is that the Taylor rule is a good measure of the Chinese monetary policy. Regarding the little English written literature there is, the overall consensus is that the Taylor rule can accurately describe the People’s Bank of China (PBC) monetary policy (Fan, Yu & Zhang 2011). However, no recent published English literature can be found, which is slightly odd considering that China wants to grow into a more consumer driven, rather than an investment driven, economy, which has to be achieved via political and monetary policies.

An important piece of information from the literature is that the PBC claims that its main monetary policy tool is the money supply, while other instruments, such as the benchmark interest rates or the open market operations, are used as complimentary tools to protect the money supply target (Fan, Yu & Zhang 2011).

3. Data Description

The data used in our analysis are quarterly, which span from 2000:1 to 2015:1. The PBC has used, and is still using, multiple policy instruments that include benchmark interest rates, required reserve ratios and refinancing banks. In China, interest rates decisions are taken by The Peoples Bank of China Monetary Policy Committee. The PBC oversees two nominal benchmark interest rates: one-­year lending and one-­year deposit rate. In this paper we focus on the lending rate for three reasons: first, data about the latter rate is more available, second, the two rates are highly correlated, and third, because of the fact that it has been continuously used as an instrument since 1986 (Xiong 2012).

3.1 Real GDP, potential real GDP and the output gap

We obtained the real GDP data from the National Bureau of Statics of China (NBS), which is the accumulated GDP per quarter in 100 million current Yuan. This data was converted into quarterly GDP by subtracting the accumulated GDP in quarter 2 from the GDP in quarter 1 etc. We estimated the potential real GDP by using the linear trend estimate, as used by (Ping, Xiong 2002). Since the output figures have demonstrated potential quarter-­ related varied characteristics, we implemented three dummy variables.

3

 đ??ˇ! = Â

1  đ??šđ?‘–đ?‘&#x;đ?‘ đ?‘Ą  đ?‘žđ?‘˘đ?‘Žđ?‘&#x;đ?‘Ąđ?‘’đ?‘&#x; 1  đ?‘†đ?‘’đ?‘?đ?‘œđ?‘›đ?‘‘  đ?‘žđ?‘˘đ?‘Žđ?‘&#x;đ?‘Ąđ?‘’đ?‘&#x; 1  đ?‘‡â„Žđ?‘–đ?‘&#x;đ?‘‘  đ?‘žđ?‘˘đ?‘Žđ?‘&#x;đ?‘Ąđ?‘’đ?‘&#x;   đ??ˇ! =   đ??ˇ! =    0                  đ?‘œđ?‘Ąâ„Žđ?‘’đ?‘&#x; 0                      đ?‘œđ?‘Ąâ„Žđ?‘’đ?‘&#x; 0                   đ?‘œđ?‘Ąâ„Žđ?‘’đ?‘&#x;

 The  potential  output  can  be  based  on  the  following  equation  đ??żđ?‘ đ?‘…đ??şđ??ˇđ?‘ƒ = 10.21 + 0.04 ∗ đ?‘‡đ?‘&#x;đ?‘’đ?‘›đ?‘‘  − 0.31 ∗ đ??ˇ! − 0.24 ∗ đ??ˇ! − 0.22đ??ˇ!  (t)                      (547)***     (89.2)***        (-­16.0)***     (-­12.0)***      (-­11.0)*** Â

(1) Â

Â

                 Sample  Period   2001:1-­2015:1 Â

Observations   61 Â

R2 Â 0.99 Â

Â

F-­statistic  2082.84 Â

Note:  ***  denotes  the  1%  significance  level   In  accordance  with  equation  (1),  the  potential  GDP  can  be  estimated  using   đ?‘ƒđ?‘œđ?‘Ąđ?‘’đ?‘›đ?‘Ąđ??şđ??ˇđ?‘ƒ = đ??¸đ?‘‹đ?‘ƒ 10.21 + 0.04 ∗ đ?‘‡đ?‘&#x;đ?‘’đ?‘›đ?‘‘ − 0.31 ∗ đ??ˇ! − 0.24 ∗ đ??ˇ! − 0.22 ∗ đ??ˇ!   (2)   Using  this  information  we  can  estimate  the  output  gap  with  the  following  expression:   đ?‘Ś! = 100 ∗

!"#!!"#$%#&'! !"#$%#&'!

Â

(3) Â

 3.3  Inflation  rate  and  inflation  target     The  inflation  rate  adopted  is  measured  by  using  the  Consumer  Price  Index  (CPI).  This  CPI  data  can  be  found  consulting  the  database  of  the  Federal  Reserve  Bank  of  St.  Louis.   Information  regarding  the  inflation  rate  target  was  collected  by  reading  “The  Report  on  Plan  Implementation  for  National  Economic  and  Social  Development  of  the  year  and  the  Draft  plan  for  National  Economic  and  Social  Development  of  the  following  yearâ€?.  This  report   is  published  annually  by  the  State  Development  and  Reform  Commission  of  China.  However,  in  this  paper  quarterly  data  is  used,  while  the  inflation  targets  are  annual,  therefore,  we  set  the  quarterly  target  equal  to  the  annual  target  (see  table  1  in  the  appendix  for  more  details).   3.4  Interest  rate  and  long  run  real  interest  rate  Â

  The  official  interest  rate  used  is  the  average  of  the  one-­year  lending  rate.  It  is  set  by  the  PBC  and  can  be  found  on  their  website.  The  long  run  equilibrium  real  interest  rate  posed  a  dilemma;Íž  the  literature  does  not  provide  a  clear  cut  answer  to  which  rate  should  be  used.  In  4  Â

the  literature  both  the  median  and  the  average  real  interest  rates  are  used  as  the  long  run  equilibrium  real  interest  rate  (Ping,  Xiong  2002).  We  chose  to  go  with  4.7%,  since  this  is  the  most  recent  data  we  could  find  in  the  literature  concerning  the  equilibrium  long  real  run  interest  rate  (He,  Wang  2012).   3.5  Stationarity  Tests     The  Augmented  Dickey-­Fuller  (ADF)  test  was  employed  to  test  the  variables  used  in  the  Non-­Linear  Least  Squares  (NLS)  regression.  The  outcomes  of  these  tests  can  be  found  in  table  2,  in  the  appendix.   We  reject  the  null  of  non-­stationarity  of  the  output  gap  (đ?‘Ś! )  at  the  5%  level,  when  the  test  with  the  assumption  that  the  output  gap  is  mean  reverting  around  zero  without  any  trend.  The  assumption  that  the  output  gap  is  mean  reverting  was  derived  from  the  literature  (Gerlach  2011).  Furthermore,  the  null  of  non-­stationarity  was  rejected  for  the  CPI  gap  for  all  assumptions  at  the  1%  level.  What’s  more,  the  null  of  unit  root  for  the  interest  rate  is  rejected  at  the  10%  level  for  the  assumption  which  includes  an  intercept.  We  chose  this  assumption,  because  the  interest  rate  cannot  go  below  zero;Íž  however,  we  do  feel  that  that  the  interest  rate  is  mean  reverting.  In  summary,  all  the  used  variables  in  our  regression  are  stationary,  thus  we  feel  confident  that  our  regression  is  non-­spurious.   4.  Establishment  of  the  model   The  original  Taylor  rule  (Taylor  1993)  states  that  the  interest  rate  determined  by  the  central  bank  can  be  described  by:  đ?‘–!∗ = đ?‘Ž!∗ ∗ đ??żđ?‘…đ?‘…đ??ź +  đ?‘Ž!∗ đ??¸ đ?œ‹!!! đ??ź! − đ?œ‹ ∗ +  đ?›ź! đ?‘Ś!   (4)    Where  đ?‘–!∗  is  the  interest  rate  set  by  the  central  bank,  LRRI  is  the  long  run  equilibrium  real  interest  rate,   đ?œ‹!   is  the  realized  inflation  as  measured  by  the  Consumer  Price  Index  (CPI)  on  a  quarterly  basis,   đ??ź!  is  the  information  available  to  the  central  bank  at  time  t,   đ?œ‹ ∗  is  the  inflation  target  set  by  the  State  Development  and  Reform  Commission  of  China,   đ?œ‹! − đ?œ‹ ∗  can  be  described,  and  will  be  referred  to  in  this  paper,  as  the  CPI  gap,   đ?‘Ś!  is  the  output  gap.  We  expect  the  parameters  đ?‘Ž!∗ > 0  and  đ?›ź! > 0,  since  this  is  in  line  with  the  rule  (Taylor  1993).  What’s  more,   đ?‘Ž!∗ > 1  would  represent  an  active  interest  rate  policy  towards  the  CPI  gap,  whereas  đ?‘Ž!∗ ≤ 1  would  indicate  a  more  passive  policy.  Furthermore,  a  higher  value  for  đ?›ź!  would  indicate  a  more  responsive  interest  policy  towards  the  output  gap.  The  inflation  rate  is  highly  persistent,  therefore  đ??¸ đ?œ‹!!! đ??ź! = đ?œ‹!  can  be  applied  (Fan,  Yu  &  Zhang  2011).      However,  in  reality  central  banks  apply  a  degree  of  smoothness  to  the  rate.  In  the  literature  a  weighted  average  method  is  used,  which  comprises  of  the  target  interest  rate,  đ?‘–!∗ ,  the  existing  interest  rate  đ?‘–!!! ,  and  an  error  term,  đ?œ€! .  This  can  be  summarized  in  the  following  expression:   đ?‘–! = 1 − đ?œŒ đ?‘–!∗ + đ?œŒđ?‘–!!! + đ?œ€!  (5)  5  Â

 Â

 The  đ?&#x153;&#x152; = 0  conforms  the  original  Taylor  rule,  furthermore,  0 â&#x2030;¤ đ?&#x153;&#x152; < 1.  When  (4)  and  (5)  are  combined  we  obtain  the  following  definition  for  the  Taylor  rule  for  the  benchmark  interest  rate,  đ?&#x2018;&#x2013;! :   đ?&#x2018;&#x2013;! = 1 â&#x2C6;&#x2019; đ?&#x153;&#x152; â&#x2C6;&#x2014; đ?&#x2018;&#x17D;!â&#x2C6;&#x2014; đ??żđ?&#x2018;&#x2026;đ?&#x2018;&#x2026;đ??ź + đ?&#x2018;&#x17D;!â&#x2C6;&#x2014; đ?&#x153;&#x2039;! â&#x2C6;&#x2019; đ?&#x153;&#x2039; â&#x2C6;&#x2014; + đ?&#x2018;&#x17D;! đ?&#x2018;Ś! + đ?&#x153;&#x152;đ?&#x2018;&#x2013;!!! + đ?&#x153;&#x20AC;!  (6)  5.  Results        This  section  presents  our  findings  based  on  the  Taylor  rule  (6)  from  section  4.  We  faced  substantial  heteroskedasticity  in  the  error  term.  Interestingly,  after  looking  at  the  residual  graph  of  our  regression  (see  figure  1)  this  seemed  to  be  due  to  the  observations  from  2008:3  to  2009:1.  This  period  is  especially  interesting,  since  on  9  November  2008  the  State  Council  of  the  Peopleâ&#x20AC;&#x2122;s  Republic  of  China  announced  a  $586  billion  (current  dollars)  stimulus  package,  before  this  period  the  PBC  already  cut  the  interest  rate  three  times  in  an  effort  to  bolster  economic  growth1.  Furthermore,  the  PBC  cut  interest  rates  for  the  fourth  time  that  year  by  108  basis  point,  the  biggest  drop  in  11  years,  on  26  November  20082.  In  the  literature  we  could  not  find  similar  mentions  of  the  heteroskedasticity  issue,  which  causes  incorrect  test  statistics  and  overstated  precision.    1.6

Figure  1:  Residual  graph Â

1.2

0.8

0.4 0.0

-0.4

-0.8 00

01

02

03

04

05

06

07

08

09

10

11

12

13

14 15

Time (quarters ) Res iduals

 Â

Â

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                                                             1 2

 Retrieved  from:  http://www.economist.com/node/12585407   Retrieved  from:  http://www.theguardian.com/business/2008/nov/26/global-­recession-­china-­banking Â

6 Â Â

 At  first,  we  tried  to  get  rid  of  the  heteroskedasticity  by  applying  White  heteroskedasticity-­corrected  standard  errors.  However,  this  did  not  solve  the  heteroskedasticity  issue.  Besides,  we  found  that  when  these  observations  are  removed  the  đ?&#x2018;&#x2026;!  increases  from  0.81  to  0.92,  the  output  gap  (đ?&#x2018;Ś! )  becomes  more  significant,  and  the  long  run  equilibrium  real  interest  rate  and  the  CPI  gap  become  less  significant  (see  (7)  and  (8)  below  and  tables  3  and  6  in  the  appendix).                 đ?&#x2018;&#x2013;! = 1 â&#x2C6;&#x2019; 0.89 1.39đ??żđ?&#x2018;&#x2026;đ?&#x2018;&#x2026;đ??ź + 0.42 đ?&#x153;&#x2039;! â&#x2C6;&#x2019; đ?&#x153;&#x2039; â&#x2C6;&#x2014; + 0.10đ?&#x2018;Ś! + 0.89đ?&#x2018;&#x2013;!!! + đ?&#x153;&#x20AC;! Â

Â

   Â

(7) Â

 (t)                         (2.21)**          (3.57)***               (2.11)**      (18.03)***  Â

Sample  Period    2001:1-­2008:2  2009:2-­2015:1 Â

 Â

Â

Observations  57 Â

R2  F-­statistic  0.92  19291.19 Â

 đ?&#x2018;&#x2013;! = 1 â&#x2C6;&#x2019; 0.72 1.29đ??żđ?&#x2018;&#x2026;đ?&#x2018;&#x2026;đ??ź + 0.26 đ?&#x153;&#x2039;  ! â&#x2C6;&#x2019; đ?&#x153;&#x2039; â&#x2C6;&#x2014; + 0.04đ?&#x2018;Ś! + 0.72đ?&#x2018;&#x2013;!!! + đ?&#x153;&#x20AC;!    (t)                       (4.06)***         (4.01)***                (1.49)        (10.34)*** Â

(8) Â

Â

Sample  Period   2001:1-­2015:1 Â

Â

Observations  R2   60  0.81 Â

F-­statistic  13227.03 Â

               Note:  *,  **,  ***  denote  significance  levels  of  10%,  5%  and  1%,  respectively  (see  table  6                  for  more  detailed  results).  The  F-­statistic  refers  to  a  Wald  test  run  on  the  null  hypothesis  đ?&#x2018;&#x17D;!â&#x2C6;&#x2014; =  đ?&#x2018;&#x17D;!â&#x2C6;&#x2014; =  đ?&#x2018;&#x17D;! = 0   đ?&#x2018;&#x17D;!  table  7  in  the  appendix  for  more  detailed  After  running  a  Breusch-­Godfrey  test  (see  results),  no  sign  of  serial  correlation  was  detected.  If  it  were  detected,  it  would  have  meant   that  our  error  terms  would  have  followed  a  pattern,  which  would  have  invalidated  our  regression.  For  the  full  sample  test,  with  a  t-­value  of  0.91  and  a  p-­value  of  0.34,  it  fails  to  reject  the  null  of  no  serial  correlation.  For  the  adjusted  sample  test,  with  a  t-­value  of  1.44  and  a  p-­value  of  0.24,  it  still  fails  to  reject  the  null  of  serial  correlation.  During  the  sample  period  the  benchmark  interest  rate  responds  passively  to  the  CPI  gap  < 1).  Whatâ&#x20AC;&#x2122;s  more,  the  set  interest  rate  reacts  positively  to  changes  in  the  output  gap  (đ?&#x2018;Ś! ).   Furthermore,  we  find  that  the  coefficients  for  the  output  gap  and  the  CPI  gap  are  significantly  bigger  than  zero  (see  table  4  and  5  in  the  appendix).  (đ?&#x2018;&#x17D;!â&#x2C6;&#x2014;

Â

6.  Conclusion     In  this  empirical  paper  we  analysed  how  well  the  Taylor  rule  can  describe  the  PBCâ&#x20AC;&#x2122;s  monetary  policy  during  the  period  2000:1  to  2015:1.  The  recent  developments  in  Chinaâ&#x20AC;&#x2122;s  monetary  policies,  the  lack  of  literature  regarding  our  topic,  and  the  fluctuations  in  macro-­ economic  variables  provided  a  challenging  opportunity  to  see  whether  the  benchmark  interest  rate  set  by  the  PBC  is  accurately  described  by  the  Taylor  rule.  We  found  that  the  interest  rate  reacts  positively,  but  passively  to  the  CPI  gap.  Whatâ&#x20AC;&#x2122;s  more,  the  interest  rate  also  reacts  7  Â

positively to the output gap. Furthermore, all our variables were statistically significant.

Additionally, we pointed out that the literature fails to mention a heteroskedasticity issue caused by the observations of the period ranging from 2008:3 to 2009:1. This heteroskedesticity in the error term is likely to be caused by the stimulus package initiated by the Chinese government around that period. Although the PBC explicitly states that money supply is its primary monetary tool, the Taylor rule does fairly accurately describe the PBC monetary policy.

8

References

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9

Appendix    Table  1:  inflation  target  2000-­2015;Íž  Source:  the  State  Development  and  Reform  Commission  of  China  Year  Inflation  target  2000  4%  2001  1.5%*  2002  1.5%*  2003  1.0%  2004  3%  2005  4%  2006  3%  2007  3%  2008  4.8%  2009  4%  2010  3%  2011  4%  2012  4%  2013  3.5%  2014  3.5%  2015  3%  *  In  2001  and  2002  the  inflation  target  was  1-­2%,  we  chose  to  go  for  1.5%   Table  2:  Augmented  Dickey-­Fuller  Test  Results  Variable  đ?&#x2019;&#x161;đ?&#x2019;&#x2022;  Ď&#x20AC; t  â&#x20AC;&#x201C;  Ď&#x20AC; *   đ?&#x2019;&#x160;đ?&#x2019;&#x2022;  đ?&#x161;Ťđ?&#x2019;&#x160;đ?&#x2019;&#x2022; Â

ADFn             -­2.22**             -­2.60**             -­0.30             -­6.04*** Â

ADFc               -­2.13               -­5.91***               -­2.70*               -­5.99*** Â

ADFT              -­0.91              -­5.85***               -­2.76               -­5.94*** Â

 Note:  ADFn,  ADFc,  and  ADFT  denote  the  augmented  Dickey-­Fuller  unit  root  test  statistics  for  when  nothing  is  included,  when  an  intercept  is  included  and  when  both  trend  and  intercept  are  included,  respectively.  We  selected  a  maximum  of  10  lags.   *,  **,***  denote  rejections  of  the  null  hypothesis  of  the  unit  root  at  the  10%,  5%   and  1%  significance  levels,  respectively.   Table  3:  Heteroskedasticity  White  Test,  with  White  cross  terms,  results  2008:3  to  2009:1  included  F-­value  28.90  Prob.  (F)  0.00 Â

2008:3  to  2009:1  excluded  F-­value  Prob.  (F) Â

1.19 Â 0.32 Â 10 Â

Â

Table  4:  t-­test,  đ?&#x2018;&#x17D;! â&#x2030;¤ 0  null  hypothesis   Output  gap  â&#x20AC;&#x201C;  Sample  period  T-­value  df  Critical  t-­value  Null  of   â&#x2030;¤ đ?&#x;&#x17D;  rejected  2001:1-­2015:1  1.49  55  1.673  No  2001:1-­2008:2  2009:2-­2015:1  2.11  53  1.67  Yes   Table  5:  t-­test,  đ?&#x2018;&#x17D;!â&#x2C6;&#x2014; â&#x2030;¤ 0  null  hypothesis   CPI  gap  â&#x20AC;&#x201C;  Sample  period  2001:1-­2015:1  2001:1-­2008:2  2009:2-­2015:1  Â

T-­value  df  Critical  t-­value  4.01  55  1.673  3.57  53  1.67 Â

Null  of  â&#x2030;¤ đ?&#x;&#x17D;  rejected  Yes  Yes Â

Table  6:  coefficients  significance  with  and  without  heteroskedasticity  Coefficient  related  variable  đ?&#x2019;&#x161;đ?&#x2019;&#x2022;  Ď&#x20AC;t  â&#x20AC;&#x201C;  Ď&#x20AC;*  đ?&#x2019;&#x160;đ?&#x2019;&#x2022;!đ?&#x;?  đ?&#x2018;łđ?&#x2018;šđ?&#x2018;šđ?&#x2018;° Â

P-­value  full  sample  P-­value  adjusted  sample  0.1414  0.0393  0.0002  0.0008  0.0000  0.0000  0.0002  0.0313    Table  7:  Breusch-­Godfrey  Serial  Correlation  LM  test,  1  lag  included Â

Serial  correlation  -­  Sample  period  2000:1-­2015:1  2000:1-­2008:2  2009:2-­2015:1  Â

T-­value  0.91  1.44 Â

P-­value  0.3447  0.2355 Â

   Â

11 Â Â