Download – BUBBLES AND CRISES THE ROLE OF CREDIT AND HOUSE PRICES

BUBBLES AND CRISES –
THE ROLE OF CREDIT
AND HOUSE PRICES
NORGES BANK WP BY ANUNDSEN,
GERDRUP, HANSEN, AND KRAGH-SØRENSEN
PRESENTED BY KARSTEN GERDRUP AT
RBNZ WORKSHOP, 22 OCT 2014
Background
 Financial crises are costly
 Banks had too little capital and liquidity prior to the great financial crisis
 Potentially many new macro-pru tools in the EU regulation following Basel III
– Norway is associated to EU through European Economic Agreement (EEA)
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Motivation for paper
 Norges Bank responsible for giving advice on the countercyclical capital
buffer (CCB) to the Ministry of Finance
 CCB should be increased when financial imbalances build up
 Needs an analytical framework for assessing the time dimension of systemic
risk
– Focus on early warning systems for the build-up phase
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House prices continue to rise
Index. Q1 2005 = 100. Q1 1995 – Q1 2014
180
Belgium
Sweden
160
140
Switzerland
Norway
120
180 180
160 160
140 140
120 120
Denmark
US
Netherlands
Spain
180
160
140
120
80
100 100
80
80
60
60
60
60
40
40
40
40
20
20
20
20
Source: BIS
100
2013
2011
2009
2007
2005
2003
2001
1999
1997
80
1995
2013
2011
2009
2007
2005
2003
2001
1999
1997
1995
100
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Main findings in paper
 Merit in monitoring credit to households and non-financial corporations
separately
 Global housing imbalances have predictive power for financial crises
 Real-time measures of exuberance in the housing and credit market enter as
significant explanatory variables
– Probability of a crisis increases markedly when exuberant behavior coincides with
high leverage
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Outline
 Data
 Logit model
 Econometric results
 Out-of-sample properties and stability
 Concluding remarks
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Data
 Panel of 16 industrialized countries over the period 1970Q1 – 2013Q2
 Australia, Belgium, Canada, Finland, France, Germany, Italy, Japan, Korea,
Netherlands, Norway, Spain, Sweden, Switzerland, UK and USA
 27 identified crises (40 % related to the great financial crisis)
 Explanatory variables






HH credit, NFE credit, and total private credit to GDP
Growth in total private credit
House prices to disposable income
Measures of global credit and house prices (based on country data)
Measures of exuberance in credit and house prices (based on country data)
Other variables: GDP growth, non-core funding ratio, bank leverage, country-fixed
effects
 Variables enters as growth rates or gaps (one-sided HP filter on data
extended with recursive forecasts, λ=400000)
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Behaviour of variables around crises
 Is the average development in pre- and post-crisis periods significantly
different compared to «normal/tranquil times»?
 Inspired by Gourinchas and Obstfeld (2012), we consider a the following
specification:
𝑦𝑖,𝑡 = 𝛼𝑖 + 𝛽′𝑠 𝛿𝑖,𝑠 + 𝜀𝑖𝑡
 𝑦𝑖,𝑡 is the explanatory variable
 𝛿𝑖,𝑠 takes the value 1 when country i is s quarters away from the start of a crisis,
and 0 otherwise
 𝛽𝑠 is the conditional effect on 𝑦𝑖,𝑡 of being s quarters away from the start of a crisis
episode relative to «normal times»
 The event window is set (ad hoc) to 𝑠 = (+/−) 1,….,16
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Total
credit
House
prices
Noncore
funding
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Decomposing credit
HH
credit
NFE
credit
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Outline
 Data
 Logit model
 Econometric results
 Out-of-sample properties and stability
 Concluding remarks
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Logit model
 Independent variable: 𝑌𝑖,𝑡 =
1 𝑖𝑓𝐹𝐶𝑖,𝑡+𝑘 = 1 for k ∈ [5,12]
0 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒
 The probability of being in a pre-crisis state is given by:
𝑃𝑟𝑜𝑏 𝑌𝑖,𝑡 = 1 =
exp α𝑖 + 𝛽′𝒙𝑖,𝑡
1 + exp α𝑖 + 𝛽′𝒙𝑖,𝑡
,
where 𝒙𝑖 is a vector of explanatory variables and α𝑖 country fixed effects
 In some specifications we include an indicator variable for exuberance:
𝐼 𝐸𝑥𝑢𝑏𝑒𝑟𝑎𝑛𝑐𝑒 =
1 𝑖𝑓 𝐸𝑥𝑢𝑏𝑒𝑟𝑎𝑛𝑐𝑒(𝑥𝑖,𝑡 ) ≥ 0
0 𝑖𝑓 𝐸𝑥𝑢𝑏𝑒𝑟𝑎𝑛𝑐𝑒 𝑥𝑖,𝑡 < 0
 Measures for global credit-to-GDP and house prices-to-income are based on
trade-weights
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More on the exuberance indicators
 Present value of an asset (house price) should be equal to the expected
discounted stream of pay-offs (imputed rent)
 The price of a house at time t can be written as:
∞
𝑃𝐻𝑡 = 𝐸𝑡
𝑖=1
1
1+𝑟
𝑖
𝑅𝑡+1 + 𝐵𝑡
 In the absence of explosive behaviour, house prices (𝑃𝐻𝑡 ) and rents (𝑅𝑡+1 )
follows the same stochastic process (are cointegrated) and the «bubble»
component 𝐵𝑡 = 0
 We follow a framework suggested by e.g. Pavalidis et al. (2014) to test
(recursively) whether 𝐵𝑡 > 0
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Exuberance in selected countries
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Outline
 Data
 Logit model
 Econometric results
 Out-of-sample properties and stability
 Concluding remarks
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Regression
results –
global
variables
16
Regression
results –
measures of
exuberance
17
Driving forces behind vulnerabilities
Decomposition of change in crisis probabilities
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Outline
 Data
 Logit model
 Econometric results
 Out-of-sample properties and stability
 Concluding remarks
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Out-of-sample properties
1. Use data up to 2000 to estimate the parameters of our models and then
make forecasts for the period 2000-2012


Able to forecast (reasonably) the great financial crisis
Reasonable AUROC that is comparable to the credit-to-GDP gap
2. Estimate the probability of a crisis for each country (over the whole sample
period) using data for all other countries


A lot of information in a country’s own history, but
still reasonable AUROC that is comparable to the credit-to-GDP gap
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Temporal stability
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Global house prices – now and then
Behaviour of global house prices-to-income gap around crises
Great financial crisis
Earlier episodes
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Concluding remarks
 We confirm that policy-makers should pay attention to early warning
indicators such as credit-to-GDP gap, non-core funding gap, and house
price-to-income gap
 Merit in monitoring credit to households and non-financial companies
separately
 Found a role for global house prices in predicting financial crises, in particular
the great financial crisis (policy implications?)
 Econometric measures of exuberance were tested. The effect of domestic
housing market exuberance particularly important.
 The road ahead: Crisis probability as a measure of financial imbalances to be
used both in monetary policy considerations and macro-pru
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BUBBLES AND CRISES –
THE ROLE OF CREDIT
AND HOUSE PRICES
NORGES BANK WP BY ANUNDSEN,
GERDRUP, HANSEN, AND KRAGH-SØRENSEN
PRESENTED BY KARSTEN GERDRUP AT
RBNZ WORKSHOP, 22 OCT 2014