Monetary Policy, Asset Prices and M i C di iMacroeconomic Conditions:

A Panel VAR Study

Katrin Assenmacher-WescheS i N ti l B kSwiss National Bank

Stefan GerlachIMFS and CEPRIMFS and CEPR

University of Frankfurt

Using Panel VARs (PVAR) to look at issues concerning monetary policy and asset prices:concerning monetary policy and asset prices:

A-W & G (2008a): importance of financial structure?( ) p

A-W & G (2008b): role of credit & international transmission of shocks?

A-W & G (in progress): non-linearities?

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MotivationMotivation

• Asset prices provide a link through which macro economic shocks can cause financial instability.• AP collapses have played a key role in many episodes

of financial instability.• AP booms raise the risk of a “correction,” triggering

defaults among borrowers and banks.AP b bbl b tt d b l ki t dit• AP bubbles can be spotted, e.g. by looking at credit.

P li i ti• Policy prescription:• Use monetary policy to lean against AP bubbles!

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Raises many questions:Raises many questions:

1. Does monetary policy impact predictably on AP?1. Does monetary policy impact predictably on AP?a) Do APs react “quickly” to monetary policy?b) Do different APs react at the same rate?

2. Are the interest changes necessary to stabilize AP so large as to raise output and inflation volatility?g p y

3. Do credit shocks have large implications for APs and macroeconomic conditions?macroeconomic conditions?

4. How do AP shocks impact on the economy?p y

5. How are US shocks transmitted internationally?

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ObjectivesObjectives

1 S d CPI GDP di 3 i1. Study CPI, GDP, credit, 3-m interest rate, property & equity prices.• E ti ate a PVAR fo 17 ou t ie• Estimate a PVAR for 17 countries:

• Australia, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Italy, Japan, the Netherlands, Norway, S i S d S i l d UK d USSpain, Sweden, Switzerland, UK and US.

• Quarterly data for 1986-2006.• Tool to summarise the data.

2. Evidence on transmission of US shocks.

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Some Related LiteratureSome Related Literature

Goodhart and Hofmann (2007):Cross-country studies of the role of AP.

Goodhart and Hofmann (2008):Panel VARs; same 17 countries.All variables endogenous and correlations high.Need to understand structure.

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Some differences:Variables:

Equity prices instead of money.

Treatment of data:Treatment of data:Levels; property prices I(2).

EEstimation:Slope heterogeneity and serially correlated regressors give rise to bias in the case of the standard fixed-effect estimator.Mean group estimator of Pesaran and Smith (1995).

Parameters differ randomly across countries; seek to estimate mean.

Ordering.

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ShortcomingsShortcomings

Assume a single regime.Non-linearities and asymmetric responses?G&H (2008) use “boom dummies.”Kaufmann and Valderrama (2007) allow for MS.

Lucas critique:Behaviour of economy may (or may not) change if a leaning-against-the-wind policy is adopted.

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I PVAR AnalysisI. PVAR Analysis

• Six variable system:• CPI, real GDP, credit, 3-month interest rate, property

prices & equity prices.• Property prices appear to be I(2).• More work needed on order of integration.

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• Standard recursive identification scheme: • Interest rate ordered after CPI, GDP and credit but ,

before residential property and equity prices.• Contemporaneous correlations:

P, Y, CR → R → HP, SP

• Results insensitive to identification scheme.• Highest correlation 0.39 (between CPI, HP).• G&H (2008) do NOT interpret results as structural.

• Do NOT seek to identify AS & AD shocks.

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Monetary Policy Shocks (± 2 SE)Monetary Policy Shocks (± 2 SE)

CPI

-0 002

-0.001

0.000

0.001

0.002Interest rate

0.25

0.50

0.75

1.00

0 5 10 15 20-0.004

-0.003

-0.002

Real GDP

0 5 10 15 20-0.25

0.00

Nominal property prices

-0.004

-0.002

0.000

-0.025

-0.015

-0.005

0.005

0 5 10 15 20-0.006

Nominal credit

0.000

0.004

0 5 10 15 20-0.035

Nominal equity prices

0 00

0.01

0.02

0 5 10 15 20-0.012

-0.008

-0.004

0 5 10 15 20-0.04

-0.03

-0.02

-0.01

0.00

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Credit Shocks (± 2 SE)Credit Shocks (± 2 SE)

CPI Interest rate

0.0000

0.0010

0.0020

0.0030

-0.2

-0.1

0.0

0.1

0.2

0.3

0 5 10 15 20-0.0010

Real GDP

0.003

0.004

0 5 10 15 20-0.3

Nominal property prices

0.01

0.02

0 5 10 15 20-0.002

-0.001

0.000

0.001

0.002

0 5 10 15 20-0.03

-0.02

-0.01

0.00

Nominal credit

0.015

0.025

Nominal equity prices

0.02

0.04

0 5 10 15 20-0.005

0.005

0 5 10 15 20-0.02

0.00

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Property Price Shocks (± 2 SE)Property Price Shocks (± 2 SE)

CPI I t t tCPI

-0.00025

0.00025

0.00075

0.00125

Interest rate

0 1

0.0

0.1

0.2

0.3

0.4

0 5 10 15 20-0.00075

0.00025

Real GDP

0.003

0.004

0 5 10 15 20-0.2

-0.1

Nominal property prices

0.030

0 5 10 15 20-0.002

-0.001

0.000

0.001

0.002

0 5 10 15 200.000

0.010

0.020

0 5 10 15 20

Nominal credit

0.0025

0.0050

0.0075

0 5 10 15 20

Nominal equity prices

0 005

0.015

0.025

0 5 10 15 20-0.0025

0.0000

0 5 10 15 20-0.015

-0.005

0.005

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Equity Price Shocks (± 2 SE)Equity Price Shocks (± 2 SE)CPI Interest rate

0.20

-0.0015

-0.0005

0.0005

0.0015

-0.10

-0.05

0.00

0.05

0.10

0.15

0 5 10 15 20

Real GDP

0.0025

0.0035

0 5 10 15 20

Nominal property prices

0 000

0.010

0.020

0 5 10 15 20-0.0005

0.0005

0.0015

Nominal credit

0 5 10 15 20-0.020

-0.010

0.000

Nominal equity prices0 10

0 001

0.001

0.003

0.005

0.007

0 02

0.00

0.02

0.04

0.06

0.08

0.10

0 5 10 15 20-0.001

0 5 10 15 20-0.02

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Some ConclusionsSome Conclusions

Monetary policy has “large” effects on Y, relative y p y g ,to those on AP.Credit shocks impact on P & Y but not on HPCredit shocks impact on P & Y but not on HP.AP shocks impact on P, Y & CR.

Implications for MP?L t t l f l i i t th i d?Large output losses from leaning-against-the-wind?CBs reacting to P & Y will respond to CR & AP shocksshocks.Does CR contains marginal information for HP?

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II Multi Country VARII. Multi-Country VAR

How do US shocks spread internationally?Highly preliminary!Highly preliminary!

Use a multi-country VAR.Use a multi country VAR.Traditional VAR overparametrized.Canova and Ciccarelli (2006)Canova and Ciccarelli (2006).

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Let Ynt include all variables for all countries.

tntnnntn YLAy ,1,, )( εμ ++= −

nt

),,,( ,,2,1, tNtttn yyyY ′′′= K

),,,,,( ,,,,,,, tntntntntntntn sphpicrypy Δ=

VAR with 17 countries and 6 variables ⇒ 7140 coefficients.N i bl i h i iNot estimable without restrictions.

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C&C’s idea is to summarize the information in the data using linear combinations of the data.

Intuitively, imposes restrictions on VAR parameters.VAR parameters, δ, can be factored:

∑ +Ξ=F

ff uθδ

We let θ have a common, country-specific, variable-

∑=f

ff1

y pspecific and lag-specific parts.Estimate θ using a linear transformation of the data, XΞ.

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US Monetary Policy Shocks (± 1 SE)US Monetary Policy Shocks (± 1 SE)

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US Credit Shocks (± 1 SE)US Credit Shocks (± 1 SE)

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US Property Price Shocks (± 1 SE)US Property Price Shocks (± 1 SE)

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US Equity Price Shocks (± 1 SE)US Equity Price Shocks (± 1 SE)

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Limited transmission (?).Potential explanations:

Correlation between US and other countries may be ydue to AS and AD shocks in the US.

Need to identify these.

These effects could depend on the state of economy.Allow for non-linearities.

May have become more important over timeMay have become more important over time.

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ConclusionsConclusions

PVAR system:Reproduce the standard findings regarding MTM.Credit matters … but not for property prices.AP matter:

Raise GDP and interest rates after 3 – 4 quarters.Raise prices after 8 quarter.

R di P Y b h (?)Responding to P, Y may be enough (?).

M lti t VARMulti-country VAR:Some transmission but less than expected (?).

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