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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions The Effectiveness of Monetary Policy in China: Evidence from a Qual VAR Hongyi Chen 1 Kenneth Chow 1 Peter Tillmann 2 1 Hong Kong Institute for Monetary


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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

The Effectiveness of Monetary Policy in China: Evidence from a Qual VAR

Hongyi Chen1 Kenneth Chow1 Peter Tillmann2

1Hong Kong Institute for Monetary Research 2University of Giessen, Germany

HKIMR October 2015

Chen, Chow, Tillmann Monetary Policy in China HKIMR 1 / 30

September 2016

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

Motivation

  • Understanding Chinese monetary policy becomes increasingly more

important.

  • At the same time, the policy framework is not straightforward to

model using conventional models.

  • The PBoC uses more than one instrument to implement policy:
  • Makes standard VARs not suitable.
  • Difficult to quantify the effect of the overall policy stance.
  • Here we propose a Qual VAR to model Chinese monetary policy:
  • A latent variable filtered out of the data summarized the policy stance.
  • The model retains the usefulness of standard monetary policy VARs.

Chen, Chow, Tillmann Monetary Policy in China HKIMR 2 / 30

summarizes

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

  • We use Dueker’s (2005) Qual VAR: Include binary information on

policy announcements in an otherwise standard VAR.

  • The binary policy announcements are interpreted as realizations of a

latent, unobservable pressure for policy tightening or easing, respectively.

  • Advantages:

1

Handles the multitude of different instruments: RRR, lending rates, deposit rates, ...

2

Acknowledges the endogenous nature of policy steps by allowing for a feedback of the business cycle on policy.

3

Identifies the shock component of policy using sign restrictions.

Chen, Chow, Tillmann Monetary Policy in China HKIMR 3 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

Literature

  • Two recent papers are particularly related to what we do.

1

He and Pauwels (2008):

◮ Code tightening/easing actions implemented by different instruments

as a -1/ 0/ +1 series.

◮ Estimate a discrete choice model. ◮ Show that the reaction function of the PBoC is a function of the

inflation and money gap, but not the output gap.

2

Fernald, Spiegel and Swanson (2014):

◮ Estimate a Factor-augmented VAR model robustify results despite

concerns about data quality.

◮ A shock to RRR or policy-determined interest rates is transmitted in a

way that similar to advanced economies.

Chen, Chow, Tillmann Monetary Policy in China HKIMR 4 / 30

is similar to advanced economies. Estimate a Factor-augmented VAR model in order to handle concerns about data quality and structural change.

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

The Qual VAR

  • Suppose we observe a binary dependent variable, yt ∈ {0,1}, driven by

a continuous latent variable y∗ yt = 1 if y∗

t ≤ 0

if y∗

t > 0

(1)

  • A Qual VAR puts an equation that relates the latent variable to
  • bservables into a VAR system.
  • A Qual VAR with k variables and p lags can be written as

Φ(L)Yt = µ + εt (2) where Yt = Xt y∗

t

  • (3)

consists of macroeconomic data, Xt, and the latent variable, y∗

t .

  • The latent variable is estimated using MCMC techniques.

Chen, Chow, Tillmann Monetary Policy in China HKIMR 5 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

  • Dueker (2005) shows that Gibbs sampling enables the joint estimation
  • f the VAR coefficients, Φ, the covariance matrix of the VAR

residuals, Σ, and the latent variable, y∗

t .

  • Distributional assumptions:

1

The VAR coefficients, Φ, are normally distributed with the mean and the variance given by the OLS estimates.

2

For the covariance matrix, Σ, an inverted Wishart distribution is assumed.

3

The latent variable, y∗, that is required to be positive whenever yt is equal to one, is said to follow a truncated normal distribution.

  • We do 10,000 draws, from which the first 2,000 are discarded.

Chen, Chow, Tillmann Monetary Policy in China HKIMR 6 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

Data

  • We estimate the Qual VAR on monthly data from 1999:01 to 2015:07.
  • The following y-o-y growth rates are included in Xt:

1

industrial production.

2

CPI.

3

real consumption

4

stock prices.

  • Alternatively, we include the y-o-y growth of

1

loans to non-financials.

2

house prices.

  • Most growth rates exhibit a low-frequency trend. We believe this

reflects structural developments and detrend the variables with a three-year moving average.

Chen, Chow, Tillmann Monetary Policy in China HKIMR 7 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

  • We model tightening and easing steps in separate models, a tightening

model and an easing model. yt,i = 1 if y∗

t,i ≤ 0

if y∗

t,i > 0

for i ∈ {tight, ease}

  • The two alternative variables should be interpreted as reflecting

tightening and easing pressure relative to a neutral stance.

  • Separate tightening and easing estimates shed light on asymmetry of

policy transmission.

Chen, Chow, Tillmann Monetary Policy in China HKIMR 8 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions date RRR Lending Rate

  • Dep. Rate

date RRR Lending Rate

  • Dep. Rate

2003/09 +1.00 2008/01 +0.50 2004/04 +0.50 2008/03 +0.50 2004/10 +0.37 +0.27 2008/04 +0.50 2006/04 +0.27 2008/05 +0.50 2006/07 +0.50 2008/06 +1.00 2006/08 +0.50 +0.27 +0.27 2010/01 +0.50 2006/11 +0.50 2010/02 +0.50 2007/01 +0.50 2010/05 +0.50 2007/02 +0.50 2010/10 +0.25 +0.25 2007/03 +0.27 +0.27 2010/11 +1.00 2007/04 +0.50 2010/12 +0.50 +0.25 +0.25 2007/05 +0.50 +0.18 +0.27 2011/01 +0.50 2007/06 +0.50 2011/02 +0.50 +0.25 +0.25 2007/07 +0.27 +0.27 2011/03 +0.50 2007/08 +0.50 +0.18 +0.27 2011/04 +0.50 +0.25 +0.25 2007/09 +0.50 +0.27 +0.27 2011/05 +0.50 2007/10 +0.50 2011/06 +0.50 2007/11 +0.50 2011/07 +0.25 +0.25 2007/12 +1.00 +0.18 +0.27

Tightening steps of the PBoC

Chen, Chow, Tillmann Monetary Policy in China HKIMR 9 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions date RRR Lending Rate

  • Dep. Rate

date RRR Lending Rate

  • Dep. Rate

1999/06

  • 0.54
  • 1.53

2012/05

  • 0.50

1999/11

  • 2.00

2012/06

  • 0.25
  • 0.25

2002/02

  • 0.54
  • 0.27

2012/07

  • 0.31
  • 0.25

2008/09

  • 0.25
  • 0.27

2014/11

  • 0.40
  • 0.25

2008/10

  • 0.50
  • 0.54
  • 0.54

2015/02

  • 0.50

2008/11

  • 1.08
  • 1.08

2015/03

  • 0.25
  • 0.25

2008/12

  • 1.75
  • 0.27
  • 0.27

2015/04

  • 1.00

2011/12

  • 0.50

2015/05

  • 0.25
  • 0.25

2012/02

  • 0.50

2015/06

  • 0.25
  • 0.25

Easing steps of the PBoC

Chen, Chow, Tillmann Monetary Policy in China HKIMR 10 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

Identification

  • To identify a monetary policy shock, we impose sign restrictions

following Uhlig (2005). model latent variables ∆IP ∆CPI ∆Cons ∆StockP tightening +

  • unrestricted

easing + + + unrestricted

  • The restrictions are imposed for t = 1,...4.
  • We also report Fry-Pagan median-target responses.

Chen, Chow, Tillmann Monetary Policy in China HKIMR 11 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

Results

✁ ✁
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✆ ✂ ✝ ✆ ✁ ✟ ✁ ✝ ✠ ✟ ✞ ✝ ✞ ✟ ✁ ✝
✞ ✁ ✟ ✁

Latent tightening (left) and easing (right) pressure for the baseline model

Chen, Chow, Tillmann Monetary Policy in China HKIMR 12 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

✡ ☛ ☞ ✌ ✍ ☞ ✎ ✏ ✑ ✒ ✌ ✍ ✓ ✔ ☞ ✕ ✖ ✗ ✘ ✖ ✘ ✗ ✙ ✖ ✙ ✗ ✚ ✖ ✛ ✙ ✗ ✖ ✛ ✖ ✖ ✖ ✛ ✙ ✗ ✖ ✛ ✗ ✖ ✖ ✛ ✜ ✗ ✘ ✛ ✖ ✖ ✢ ✍ ✣ ✤ ✓ ☞ ✏ ✔ ☛ ✥ ✎ ✏ ✑ ✣ ✤ ✦ ☞ ✔ ✑ ✍ ✖ ✗ ✘ ✖ ✘ ✗ ✙ ✖ ✙ ✗ ✚ ✖ ✛ ✧ ✖ ✚ ✖ ✛ ★ ✖ ✚ ✖ ✛ ✙ ✖ ✖ ✛ ✖ ✖ ✖ ✛ ✙ ✖ ✩ ✑ ✍ ✓ ✤ ✪ ✌ ✏ ✎ ✏ ✔ ✦ ✌ ✓ ✖ ✗ ✘ ✖ ✘ ✗ ✙ ✖ ✙ ✗ ✚ ✖ ✛ ✙ ✖ ✚ ✖ ✛ ✘ ✖ ✖ ✛ ✖ ✖ ✖ ✛ ✘ ✖ ✖ ✛ ✙ ✖ ✩ ✑ ✍ ✓ ✤ ✪ ✒ ☞ ✔ ✑ ✍ ✖ ✗ ✘ ✖ ✘ ✗ ✙ ✖ ✙ ✗ ✚ ✖ ✛ ✜ ✗ ✚ ✖ ✛ ✗ ✖ ✚ ✖ ✛ ✙ ✗ ✖ ✛ ✖ ✖ ✖ ✛ ✙ ✗ ✫ ☞ ✑ ✦ ✬ ✎ ✏ ✔ ✦ ✌ ✓ ✖ ✗ ✘ ✖ ✘ ✗ ✙ ✖ ✙ ✗ ✚ ✗ ✛ ✖ ✖ ✖ ✛ ✖ ✖ ✗ ✛ ✖ ✖ ✘ ✖ ✛ ✖ ✖ ✘ ✗ ✛ ✖ ✖

Response to PBoC tightening in the baseline model

Chen, Chow, Tillmann Monetary Policy in China HKIMR 13 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

✭ ✮ ✯ ✰ ✱ ✯ ✲ ✳ ✴ ✵ ✰ ✱ ✶ ✷ ✯ ✸ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✺ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✺ ✹ ✾ ✺ ✹ ✹ ✾ ✿ ✺ ✻ ✾ ✹ ✹ ❀ ✱ ❁ ❂ ✶ ✯ ✳ ✷ ✮ ❃ ✲ ✳ ✴ ❁ ❂ ❄ ✯ ✷ ✴ ✱ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ❅ ✹ ✽ ✹ ✾ ✼ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✹ ✹ ✾ ❅ ✹ ❆ ✴ ✱ ✶ ❂ ❇ ✰ ✳ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✹ ✹ ✾ ❅ ✹ ❆ ✴ ✱ ✶ ❂ ❇ ✵ ✯ ✷ ✴ ✱ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✺ ✹ ✽ ✹ ✾ ✼ ✺ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✺ ✹ ✾ ✺ ✹ ❈ ✯ ✴ ❄ ❉ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✺ ✾ ✹ ✹ ✹ ✾ ✹ ✹ ✺ ✾ ✹ ✹ ✻ ✹ ✾ ✹ ✹ ✻ ✺ ✾ ✹ ✹

Response to PBoC easing in the baseline model

Chen, Chow, Tillmann Monetary Policy in China HKIMR 14 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

✁ ✁
✁ ✂
✁ ✄
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✆ ✁ ✝ ☎ ✝ ✄ ✝ ✂ ✝
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✁ ☎
✆ ✁
✆ ✂ ✝
✝ ✆ ✞ ✝ ✆ ✁ ✝ ✞ ✁ ✞

Latent tightening (left) and easing (right) pressure for the model with loans

Chen, Chow, Tillmann Monetary Policy in China HKIMR 15 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

✭ ✮ ✯ ✰ ✱ ✯ ✲ ✳ ✴ ✵ ✰ ✱ ✶ ✷ ✯ ✸ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✺ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✺ ✹ ✾ ✺ ✹ ✹ ✾ ✿ ✺ ✻ ✾ ✹ ✹ ❀ ✱ ❁ ❂ ✶ ✯ ✳ ✷ ✮ ❃ ✲ ✳ ✴ ❁ ❂ ❄ ✯ ✷ ✴ ✱ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ❅ ✹ ✽ ✹ ✾ ✼ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✹ ❆ ✴ ✱ ✶ ❂ ❇ ✰ ✳ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✹ ✽ ✹ ✾ ✻ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✻ ✹ ✹ ✾ ✼ ✹ ✭ ✴ ✮ ✱ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✺ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✺ ✹ ✻ ✾ ✹ ✹ ✻ ✾ ✺ ✹ ❈ ✯ ✴ ❄ ❉ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✺ ✾ ✹ ✹ ✹ ✾ ✹ ✹ ✺ ✾ ✹ ✹ ✻ ✹ ✾ ✹ ✹

Response to PBoC tightening in the model with loans and stock prices

Chen, Chow, Tillmann Monetary Policy in China HKIMR 16 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

✭ ✮ ✯ ✰ ✱ ✯ ✲ ✳ ✴ ✵ ✰ ✱ ✶ ✷ ✯ ✸ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✺ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✺ ✹ ✾ ✺ ✹ ✹ ✾ ✿ ✺ ✻ ✾ ✹ ✹ ❀ ✱ ❁ ❂ ✶ ✯ ✳ ✷ ✮ ❃ ✲ ✳ ✴ ❁ ❂ ❄ ✯ ✷ ✴ ✱ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ❅ ✹ ✽ ✹ ✾ ✼ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✹ ✹ ✾ ❅ ✹ ✹ ✾ ❊ ✹ ❆ ✴ ✱ ✶ ❂ ❇ ✰ ✳ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✹ ✹ ✾ ❅ ✹ ✭ ✴ ✮ ✱ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✻ ✾ ✺ ✹ ✽ ✻ ✾ ✹ ✹ ✽ ✹ ✾ ✺ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✺ ✹ ❈ ✯ ✴ ❄ ❉ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✺ ✾ ✹ ✹ ✹ ✾ ✹ ✹ ✺ ✾ ✹ ✹ ✻ ✹ ✾ ✹ ✹ ✻ ✺ ✾ ✹ ✹ ✼ ✹ ✾ ✹ ✹

Response to PBoC easing in the model with loans and stock prices

Chen, Chow, Tillmann Monetary Policy in China HKIMR 17 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

✭ ✮ ✯ ✰ ✱ ✯ ✲ ✳ ✴ ✵ ✰ ✱ ✶ ✷ ✯ ✸ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✺ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✺ ✹ ✾ ✺ ✹ ✹ ✾ ✿ ✺ ✻ ✾ ✹ ✹ ❀ ✱ ❁ ❂ ✶ ✯ ✳ ✷ ✮ ❃ ✲ ✳ ✴ ❁ ❂ ❄ ✯ ✷ ✴ ✱ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ❋ ✹ ✽ ✹ ✾ ✼ ✹ ✽ ✹ ✾ ✻ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✻ ✹ ✹ ✾ ✼ ✹ ❆ ✴ ✱ ✶ ❂ ❇ ✰ ✳ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✹ ✽ ✹ ✾ ✻ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✻ ✹ ✭ ✴ ✮ ✱ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✺ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✺ ✹ ✻ ✾ ✹ ✹ ✻ ✾ ✺ ✹
❂ ✶ ✰ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✼ ✾ ✹ ✹ ✽ ✻ ✾ ✺ ✹ ✽ ✻ ✾ ✹ ✹ ✽ ✹ ✾ ✺ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✺ ✹

Response to PBoC tightening in the model with loans and house prices

Chen, Chow, Tillmann Monetary Policy in China HKIMR 18 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

✭ ✮ ✯ ✰ ✱ ✯ ✲ ✳ ✴ ✵ ✰ ✱ ✶ ✷ ✯ ✸ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✺ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✺ ✹ ✻ ✾ ✹ ✹ ❀ ✱ ❁ ❂ ✶ ✯ ✳ ✷ ✮ ❃ ✲ ✳ ✴ ❁ ❂ ❄ ✯ ✷ ✴ ✱ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ❅ ✹ ✽ ✹ ✾ ✼ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✹ ✹ ✾ ❅ ✹ ❆ ✴ ✱ ✶ ❂ ❇ ✰ ✳ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✹ ✹ ✾ ❅ ✹ ✭ ✴ ✮ ✱ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✻ ✾ ✺ ✹ ✽ ✻ ✾ ✹ ✹ ✽ ✹ ✾ ✺ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✺ ✹
❂ ✶ ✰ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✼ ✾ ✹ ✹ ✽ ✻ ✾ ✺ ✹ ✽ ✻ ✾ ✹ ✹ ✽ ✹ ✾ ✺ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✺ ✹

Response to PBoC easing in the model with loans and house prices

Chen, Chow, Tillmann Monetary Policy in China HKIMR 19 / 30

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Motivation Literature The Qual VAR Data Results Conventional VAR Robustness Conclusions

A Conventional VAR

  • How large is a one-standard deviation shock in the latent variable?
  • For comparative purposes, we transform the Qual VAR into a VAR

with RRR as the policy instrument.

  • All other aspects (restrictions, variables, sample, ...) remain

unchanged.

  • When scaled by the response of ∆IP we find that a latent easing shock

is equivalent to a 0.20pp cut in RRR.

Chen, Chow, Tillmann Monetary Policy in China HKIMR 20 / 30

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❍ ✰ ■ ❂ ✷ ✳ ✰ ❁ ❍ ✰ ✶ ✰ ✳ ❏ ✰ ❍ ✮ ✯ ✷ ✴ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ❋ ✹ ✽ ✹ ✾ ✼ ✹ ✽ ✹ ✾ ✻ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✻ ✹ ❀ ✱ ❁ ❂ ✶ ✯ ✳ ✷ ✮ ❃ ✲ ✳ ✴ ❁ ❂ ❄ ✯ ✷ ✴ ✱ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✺ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✺ ✹ ✾ ✺ ✹ ✹ ✾ ✿ ✺ ❆ ✴ ✱ ✶ ❂ ❇ ✰ ✳ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✹ ✹ ✾ ❅ ✹ ❆ ✴ ✱ ✶ ❂ ❇ ✵ ✯ ✷ ✴ ✱ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✺ ✹ ✽ ✹ ✾ ✼ ✺ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✺ ✹ ✾ ✺ ✹ ✹ ✾ ✿ ✺ ❈ ✯ ✴ ❄ ❉ ✲ ✳ ✷ ✶ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✻ ✹ ✾ ✹ ✹ ✽ ✺ ✾ ✹ ✹ ✹ ✾ ✹ ✹ ✺ ✾ ✹ ✹ ✻ ✹ ✾ ✹ ✹ ✻ ✺ ✾ ✹ ✹

Shock to Required Reserve Ratio in conventional VAR

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Robustness

  • Concerns about the quality of Chinese macro data.
  • Famously, Li Keqiang, then party secretary in the Liaoning province,

suggested measuring real activity using electricity consumption, new bank loans and cargo freight volume.

  • We construct a pseudo Li-Keqiang-index from electricity and freight

volume (normalized series, average of electricity and freight, in y-o-y growth rates).

  • The baseline results remain unchanged. Again, we find a strong effect
  • n real activity.

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❑ ▲ ▲ ▲ ▼ ◆ ◆ ❑ ▼ ◆ ◆ ❖ ▼ ◆ ◆ P ▼ ◆ ◆ ◗ ▼ ◆ ◆ ▲ ▼ ◆ ❑ ❑ ▼ ◆ ❑ ❖ ▼ ◆ ❑ P P ❘ ◆ ◗ ❘ P ❑ ◆ ❘ ◆ ❑ ▼ ❘ P ❑ P ❘ ◆ ❑ ◗ ❘ P ▼ ◆ ❘ ◆ ❙ ◆ ❘ ❖ ❙ ◆ ❘ ▼ ❙ ◆ ❘ ❑ ◆ ❘ ◆ ◆ ❘ ❑ ◆ ❘ ▼ ◆ ❘ ❖ ◆ ❘ ❚ ❯ ❱ ❲ ❳ ❨ ❩ ❬ ❭ ❪ ❫ ❴ ❬ ❵ ❲ ❳ ❛ ❩ ❭ ❵ ❱ ❜ ❫ ❝ ❞ ❩ ❨ ❛ ❪ ❫ ❝ ❡ ❢ ❭ ❣ ❝ ❤ ❭ ❪ ❱ ✐ ❭ ❱ ❲ ❝ ❥

Growth of industrial production and pseudo Li-Kequiang-index

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✭ ✮ ✯ ✰ ✱ ✯ ✲ ✳ ✴ ✵ ✰ ✱ ✶ ✷ ✯ ✸ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✺ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✺ ✹ ✻ ✾ ✹ ✹ ✭ ✷ ❦ ✰ ■ ✷ ✮ ✱ ❧ ❀ ✱ ❁ ✰ ♠ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✹ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✹ ✻ ✹ ✾ ✹ ✻ ✹ ✾ ✹ ✻ ❆ ✴ ✱ ✶ ❂ ❇ ✰ ✳ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✹ ✽ ✹ ✾ ✻ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✻ ✹ ✹ ✾ ✼ ✹ ✹ ✾ ❋ ✹ ❆ ✴ ✱ ✶ ❂ ❇ ✵ ✯ ✷ ✴ ✱ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✹ ✾ ✼ ✺ ✹ ✾ ✹ ✹ ✹ ✾ ✼ ✺ ✹ ✾ ✺ ✹ ✹ ✾ ✿ ✺ ✻ ✾ ✹ ✹ ❈ ✯ ✴ ❄ ❉ ✲ ✳ ✷ ❄ ✰ ✶ ✹ ✺ ✻ ✹ ✻ ✺ ✼ ✹ ✼ ✺ ✽ ✻ ✹ ✾ ✹ ✹ ✽ ✺ ✾ ✹ ✹ ✹ ✾ ✹ ✹ ✺ ✾ ✹ ✹ ✻ ✹ ✾ ✹ ✹

Response to PBoC easing in the model with Li Keqiang index of economic activity

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  • An experiment: Is the monetary transmission different between

state-owned and shareholder-owned firms?

  • We substitute industrial production by the change in value added by

these two firm types.

  • The transmission of policy shocks is indeed highly different: after a

tightening state-owned firms suffer less, after an easing they benefit more.

  • Certainly an interesting topic for a separate paper.

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♥ ♦ ♣ q r s t t r t ✉ ✈ ✇ ♦ ✇ r ① ② ③ ④ r t ⑤ ⑥ ⑦ ⑧ ⑥ ⑧ ⑦ ⑨ ⑥ ⑨ ⑦ ⑩ ⑧ ❶ ⑦ ⑥ ⑩ ⑧ ❶ ⑥ ⑥ ⑩ ⑥ ❶ ⑦ ⑥ ⑥ ❶ ⑥ ⑥ ⑥ ❶ ⑦ ⑥ ♥ ♦ ♣ q r s t t r t ✉ ✈ ❷ ♦ ❸ r ❷ ② ♣ t ❹ ④ ❺ r ④ ✇ r ❸ ❻ ❸ ❹ ✈ r ⑤ ⑥ ⑦ ⑧ ⑥ ⑧ ⑦ ⑨ ⑥ ⑨ ⑦ ⑩ ⑧ ❶ ⑦ ⑥ ⑩ ⑧ ❶ ⑥ ⑥ ⑩ ⑥ ❶ ⑦ ⑥ ⑥ ❶ ⑥ ⑥ ⑥ ❶ ⑦ ⑥ ♥ ♦ ♣ q r s t t r t ✉ ✈ ✇ ♦ ✇ r ① ② ③ ④ r t ⑤ ⑥ ⑦ ⑧ ⑥ ⑧ ⑦ ⑨ ⑥ ⑨ ⑦ ⑩ ⑥ ❶ ⑦ ⑥ ⑥ ❶ ⑥ ⑥ ⑥ ❶ ⑦ ⑥ ⑧ ❶ ⑥ ⑥ ♥ ♦ ♣ q r s t t r t ✉ ✈ ❷ ♦ ❸ r ❷ ② ♣ t ❹ ④ ❺ r ④ ✇ r ❸ ❻ ❸ ❹ ✈ r ⑤ ⑥ ⑦ ⑧ ⑥ ⑧ ⑦ ⑨ ⑥ ⑨ ⑦ ⑩ ⑥ ❶ ⑦ ⑥ ⑥ ❶ ⑥ ⑥ ⑥ ❶ ⑦ ⑥ ⑧ ❶ ⑥ ⑥

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Conclusions

  • We proposed a Qual VAR to model Chinese monetary policy:
  • Summarizes the policy stance by a latent variable.
  • Allows policy to be analyzed in a VAR framework - with all the

advantages of a VAR over alternative models, e.g. focuses on unexpected shocks, facilitates a comparison with advanced countries’ policy framework, ...

  • Sheds light on the asymmetry of the transmission process.
  • Main findings:

1

The monetary transmission to output and inflation is similar to Western economies - despite less developed financial system and weak institutions.

2

A monetary tightening lacks grip on asset prices - which raises financial stability concerns.

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Additional slides

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❀ ✱ ❁ ❂ ✶ ✯ ✳ ✷ ✮ ❃ ✲ ✳ ✴ ❁ ❂ ❄ ✯ ✷ ✴ ✱ ❼ ✷ ✱ ❽ ✵ ❾ ✮ ❾ ❿ ✻ ➀ ➀ ➀ ✼ ✹ ✹ ✻ ✼ ✹ ✹ ❋ ✼ ✹ ✹ ✺ ✼ ✹ ✹ ✿ ✼ ✹ ✹ ➀ ✼ ✹ ✻ ✻ ✼ ✹ ✻ ❋ ✼ ✹ ✻ ✺ ✺ ✾ ✹ ✹ ✻ ✹ ✾ ✹ ✹ ✻ ✺ ✾ ✹ ✹ ✼ ✹ ✾ ✹ ✹ ❆ ✴ ✱ ✶ ❂ ❇ ✰ ✳ ✲ ✳ ✷ ❄ ✰ ✶ ❼ ✷ ✱ ❽ ✵ ❾ ✮ ❾ ❿ ✹ ✼ ✺ ✺ ✹ ✿ ✺ ✻ ✹ ✹ ✻ ✼ ✺ ✻ ✺ ✹ ✻ ✿ ✺ ✽ ✼ ✾ ✺ ✹ ✹ ✾ ✹ ✹ ✼ ✾ ✺ ✹ ✺ ✾ ✹ ✹ ✿ ✾ ✺ ✹ ✻ ✹ ✾ ✹ ✹ ✭ ✴ ✮ ✱ ✶ ❼ ✷ ✱ ❽ ✵ ❾ ✮ ❾ ❿ ✹ ✼ ✺ ✺ ✹ ✿ ✺ ✻ ✹ ✹ ✻ ✼ ✺ ✻ ✺ ✹ ✻ ✿ ✺ ✹ ✾ ✹ ✹ ✻ ✹ ✾ ✹ ✹ ✼ ✹ ✾ ✹ ✹ ❋ ✹ ✾ ✹ ✹ ❅ ✹ ✾ ✹ ✹ ❍ ✰ ✮ ❃ ❆ ✴ ✱ ✶ ❂ ❇ ✵ ✯ ✷ ✴ ✱ ❼ ✷ ✱ ❽ ✵ ❾ ✮ ❾ ❿ ✻ ➀ ➀ ➀ ✼ ✹ ✹ ✻ ✼ ✹ ✹ ❋ ✼ ✹ ✹ ✺ ✼ ✹ ✹ ✿ ✼ ✹ ✹ ➀ ✼ ✹ ✻ ✻ ✼ ✹ ✻ ❋ ✼ ✹ ✻ ✺ ✺ ✾ ✹ ✹ ✻ ✹ ✾ ✹ ✹ ✻ ✺ ✾ ✹ ✹ ✼ ✹ ✾ ✹ ✹ ✼ ✺ ✾ ✹ ✹ ❈ ✯ ✴ ❄ ❉ ✲ ✳ ✷ ❄ ✰ ✶ ❼ ✷ ✱ ❽ ✵ ❾ ✮ ❾ ❿ ✻ ➀ ➀ ➀ ✼ ✹ ✹ ✻ ✼ ✹ ✹ ❋ ✼ ✹ ✹ ✺ ✼ ✹ ✹ ✿ ✼ ✹ ✹ ➀ ✼ ✹ ✻ ✻ ✼ ✹ ✻ ❋ ✼ ✹ ✻ ✺ ✽ ✻ ✹ ✹ ✾ ✹ ✹ ✹ ✾ ✹ ✹ ✻ ✹ ✹ ✾ ✹ ✹ ✼ ✹ ✹ ✾ ✹ ✹ ❋ ✹ ✹ ✾ ✹ ✹
❂ ✶ ✰ ✲ ✳ ✷ ❄ ✰ ✶ ❼ ✷ ✱ ❽ ✵ ❾ ✮ ❾ ❿ ✻ ➀ ➀ ➀ ✼ ✹ ✹ ✻ ✼ ✹ ✹ ❋ ✼ ✹ ✹ ✺ ✼ ✹ ✹ ✿ ✼ ✹ ✹ ➀ ✼ ✹ ✻ ✻ ✼ ✹ ✻ ❋ ✼ ✹ ✻ ✺ ✽ ✼ ✹ ✾ ✹ ✹ ✽ ✻ ✹ ✾ ✹ ✹ ✹ ✾ ✹ ✹ ✻ ✹ ✾ ✹ ✹ ✼ ✹ ✾ ✹ ✹ ❋ ✹ ✾ ✹ ✹

Growth rates (red) and three-year moving average (dotted)

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Financial Times, September 29 2015

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