Transcript International developments in housing markets – lessons for Sweden

International developments in
housing markets – lessons for
Sweden
E Philip Davis
National Institute
of Economic and
Social Research
Introduction
• In this presentation we seek to give an overview
of recent developments in housing markets for 12
OECD countries, via data and relevant research
• We begin by noting key structural differences,
before looking at developments in the crisis
• We proceed to put these in a longer term context
• And finally look at key implications of house prices
for investment, consumption, public finance and
financial stability/financial regulation
Background – structural features
• Housing markets cannot be treated as
homogeneous
• Population density is correlated with dwelling
size and availability of land, although the latter is
also affected by planning restrictions
• Dwelling size and inhabitants per dwelling is
indicators of living standards in terms of housing
• Interest rate risk may affect both supply and
demand for housing, and demand may also be
affected by the prevalence of fixed rate loans
Structure of housing markets
Population
Housing
Dwelling size
density (2005) density (2001)
(2001)
long real interest rate volatility(a)
(persons per
(per 1000
average m2 per
sq km)
inhabitants)
capita
1980s
1990s 2000-2006
Australia
2.6
405
81.0
4.33
0.88
0.33
Canada
3.2
403
69.7
0.64
0.60
0.07
France
108.4
490
43.9
0.63
0.12
0.02
Germany
231.0
469
42.1
0.88
0.30
0.07
Italy
194.5
368(b)
35.0(b)
1.99
1.09
0.02
Netherlands
391.5
417
41.2
1.35
0.16
0.02
Spain
85.8
510
47.6
1.71
0.68
0.08
United Kingdom
246.3
431
36.4
1.08
0.55
0.09
United States
30.8
428
70.8
0.91
1.12
0.11
Floating rate debts as a proportion
of disposable incomes
0.8
0.6
Germany
0.4
0.2
0
1
Italy
Finland
UK
Sweden
US
1.2
1.6
Spain
Denmark
1.4
France
1
Neths
2
1.8
Ireland
Personal sector borrowing cost
vulnerability
Recent house price developments
• Boom-bust cycle in housing in a number of
countries…
• US housing credit linked to global crisis directly
via falling CDO prices (note principal agent
problem in US mortgage securitisation)
• Since crisis, house price falls less marked than
widely expected, recovery in some countries
• Evidence of further financial distress with high
level of arrears and repossessions in countries
such as the US
• Less so in those such as the UK as interest
rates low and house price falls modest – and
loans recourse based
20
01
-5
-10
-15
-20
Quarters
20
09
20
09
20
08
20
08
20
07
20
07
20
06
20
06
20
05
20
05
20
04
20
04
20
03
20
03
20
02
20
02
20
01
Q3
Q1
Q3
Q1
Q3
Q1
Q3
Q1
Q3
Q1
Q3
Q1
Q3
Q1
Q3
Q1
Q3
Q1
Annual percent change
Recent house price developments
House prices since 2001
25
20
15
10
AUphi
5
CNphi
FRphi
0
GEphi
IRphi
ITphi
20
01
Q
1
20
01
Q
3
20
02
Q
1
20
02
Q
3
20
03
Q
1
20
03
Q
3
20
04
Q
1
20
04
Q
3
20
05
Q
1
20
05
Q
3
20
06
Q
1
20
06
Q
3
20
07
Q
1
20
07
Q
3
20
08
Q
1
20
08
Q
3
20
09
Q
1
20
09
Q
3
20
10
Q
1
Annual percent change
Recent house price developments
House prices since 2001
30
25
20
15
JPphi
10
NLphi
SDphi
5
SPphi
UKphi
USphi
0
-5
-10
-15
Quarters
Latest “Economist” Data
Country
Year on year
Country
Year on year
change
change
Australia
18.4
Japan
-3.4
Canada
4.5
Netherlands
4.2
France
6.0
Sweden
8.9
Germany
4.8
Spain
-4.0
Ireland
-17.0
UK
3.0
Italy
-2.8
US
-4.9 (FHFA)
3.6 (CSNI)
A longer term perspective
• Boom in house prices following liberalisation in
the 1980s, often leading to banking crises…
• Long term rise in real house prices (higher
income, shortage of land) – implicit
intergenerational transfers (Weale 2007)
• Rise in debt-income ratios to households
correlated with rise in house prices (house
purchase but also equity extraction)
• But credit should not drive house prices in
liberalised financial system (conventional
determinants are income, interest rates, supply
conditions, demographics, see e.g. Muellbauer
and Murphy 1997))
House price inflation since 1980
House price inflation
50
40
AUhpinfl
20
CNhpinfl
FRhpinfl
GEhpinfl
IRhpinfl
10
IThpinfl
-10
-20
Years
20
08
20
06
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
0
19
80
Annual percentage change
30
House price inflation since 1980
House price inflation
50
40
JPhpinfl
20
NLhpinfl
SDhpinfl
SPhpinfl
UKhpinfl
10
UShpinfl
-10
-20
Years
20
08
20
06
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
0
19
80
Annual percent change
30
Real house prices
Real house prices (1980=100)
350
300
250
AUrph
CNrph
Index
200
FRrph
GErph
150
IRrph
ITrph
100
50
Years
20
08
20
06
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
0
Real house prices
Real house prices (1980=100)
400
350
300
250
JPrph
SDrph
200
SPrph
UKrph
150
USrph
100
50
Years
20
08
20
06
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
0
19
80
Index
NLrph
Debt-income ratios
Household debt/income ratios
250
200
AUdyr
150
Percent
CNdyr
FRdyr
GEdyr
IRdyr
100
ITdyr
50
Years
20
08
20
06
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
0
Debt-income ratios
Household debt-income ratios
300
250
200
JPdyr
SDdyr
150
SPdyr
UKdyr
USdyr
100
50
Years
20
08
20
06
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
0
19
80
Percent
NLdyr
Housing and investment
• Housing investment typically a small proportion
of the stock, given houses are long-lived assets
• Overall housing investment has tended to
decline as a proportion of GDP in a number of
countries, even before 2008/9 when sharp falls
especially Spain and Ireland
• Key determinant Q ratio (house prices/housing
investment deflator) (Jud and Winkler (2003),
Berg and Berger (2005))
• Correlation of house price change to
investment/GDP change in 2008/9 is 0.73
Housing investment/GDP
Housing investment/GDP ratios
16
14
12
10
AUiy
FRiy
8
GEiy
IRiy
6
ITiy
4
2
Years
20
08
20
06
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
0
19
80
Percent
CNiy
Housing investment/GDP
Housing investment/GDP ratios
12
10
8
JPiy
SDiy
6
SPiy
UKiy
USiy
4
2
Years
20
08
20
06
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
0
19
80
Percent
NLiy
1991-1995
1996-2000
2001-2006
US
UK
Spain
Netherlands
Germany
France
Canada
Australia
ave. annual percentage change
Q ratios for housing in upturn
10
8
6
4
2
0
-2
-4
-6
House prices and consumption
• Research on wealth effect shows strong link
from house prices/housing wealth to
consumption (e.g. Barrell and Davis (2007),
Case et al (2005)), although effect on nonhomeowners should partly offset
• Simple cross section regression shows house
prices discriminated the falls in consumption
between 2008/3 and 2009/4 better than equity
prices, although RPDI and lagged debt/income
also relevant
• Collateral effect likely intensified by credit
rationing, but banking crisis dummy not
significant
Change in consumption 2009/4 over
2008/3
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Dependent Variable: DC
Method: Least Squares
Date: 10/12/10 Time: 13:37
Sample: 1 12
Included observations: 11
Variable Coefficient
Std. Error
t-Statistic
Prob.
DPH
DRPDI
LDY
DEQP
0.092604
0.224692
0.005645
0.058024
2.796035
2.183794
-2.020971
-0.448169
0.0267
0.0653
0.0830
0.6676
0.258924
0.490681
-0.011408
-0.026005
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
0.752215
0.646022
1.674003
19.61600
-18.78980
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Durbin-Watson stat
-0.942513
2.813637
4.143600
4.288289
2.391862
Housing and fiscal position
• NIER (2010) decomposed deterioration in
fiscal position into cycle, policy changes,
bank support and residual
• Residual linked partly to revenue from
financial sector but also housing market
• Falling house prices affect tax revenues
directly (via stamp duties and profits of
construction/realtor sector) and indirectly
(via consumption taxes – to the extent
consumption fell more than in a normal
cycle)
House prices and deficits
6
House price growth 2009
4
2
Portugal
Finland
Germany
Sweden
0
Italy
Belgium
-2
Canada
Japan
Netherlands
Greece
US
-4
-6
France
Spain
-8
United Kingdom
-10
-12
Ireland
Denmark
-14
-9
-8
-7
-6
-5
-4
-3
-2
Residual category of the deficit (% of GDP)
-1
0
1
House prices and banking crises
• Barrell, Davis, Karim and Liadze (2010) in JBF and
subsequent work were first to find role for bank
capital and liquidity in OECD crisis models
• House price bubbles matter
• Sustained deficits matter
• Using logit model together with a banking sector
sub-model of NiGEM global macro model enabled
assessment of overall costs and benefits of
regulation in the UK – optimal level of tightening
(Barrell et al (2009) FSA OP)
• Recent work looks at the split between on balance
sheet and other revenues (OBS)
• Level of OBS does not matter as it varies across countries a lot
• Faster growth of OBS activity boosts crisis probabilities
Calibrating macroprudential surveillance
• In “Calibrating macroprudential surveillance” we
put in all ‘normal’ variables including lagged
house price rises and test down with 14 OECD
countries, 12 crisis and data for 1980 to 1997
(vastly shorter sample than earlier work)
• As in earlier work, found that “traditional”
variables such as credit growth, output growth
and M2/reserves less relevant to OECD –
artefact of dominance of global samples by
emerging markets
• A researcher undertaking this work in the late
1990s could have picked the same equation
Explaining OECD Financial Crises
• We explain crisis probabilities (logit) in OECD
1980-1997
Pr obYit  1  F X it  
e  'Xit
1  e  'Xit
Box 1: List of Variables (with variable key)
Variables used in
previous studies:
Demirguc-Kunt and
Detragiache (2005);
Davis and Karim (2008).
Variables introduced in
JoBF.
This paper
1. Real GDP Growth (%) (YG)
2. Real Interest Rate (%) (RIR)
3. Inflation (%) (INFL)
4. Fiscal Surplus/ GDP (%) (BB)
5. M2/ Foreign Exchange Reserves (%) (M2RES)
6. Real Domestic Credit Growth (%) (DCG)
7. Liquidity (%) (LIQ)
8. Leverage (%) (LEV)
9. Real Property Price Growth (%) (RHPG)
10 Current Balance as % GDP (CBR)
Nested testing of the crisis model, 19801997
Step
(1)
-0.339
(1.7)
(2)
-0.339
(1.8)
(3)
-0.348
(1.9)
(4)
-0.347
(1.9)
(5)
-0.417
(2.9)
(6)
-0.345
(2.7)
(7)
-0.384
(3.2)
NLIQ(-1)
-0.106
(1.8)
-0.106
(1.9)
-0.108
(2.0)
-0.113
(2.2)
-0.126
(2.7)
-0.104
(2.5)
-0.105
(2.6)
RHPG(-3)
0.091
(1.9)
0.091
(1.9)
0.089
(1.9)
0.095
(2.4)
0.09
(2.4)
0.086
(2.3)
0.081
(2.1)
CBR(-2)
-0.434
(2.3)
-0.434
(2.3)
-0.441
(2.4)
-0.438
(2.4)
-0.418
(2.3)
-0.3
(1.9)
-0.333
(2.2)
DCG(-1)
-0.101
(1.5)
-0.101
(1.6)
-0.1
(1.6)
-0.1
(1.5)
-0.108
(1.7)
-0.053
(1.0)
YG(-1))
0.277
(1.5)
0.277
(1.5)
0.274
(1.4)
0.279
(1.5)
0.29
(1.5)
RIR(-1)
-0.054
(0.3)
-0.055
(0.6)
-0.055
(0.6)
-0.06
(0.7)
BB(-1)
0.022
(0.2)
0.02
(0.2)
0.023
(0.2)
-1.51E-05
(0.2)
-1.52E-05
(0.2)
LEV(-1)
M2RES(-1)
INFL(-1)
-0.0012
(0.1)
Model character
• Up to four lags tried in house prices, credit
growth, current account and GDP growth
– Cyclical variables drop out
– Lending growth drops out
• Lending quality matters with house price growth
and current balances as indicators
Estimated Equation
Dep=0
Dep=1
Total
143
3
146
55
9
64
Total
198
12
210
Correct
143
9
152
% Correct
72
75
72
% Incorrect
28
25
28
P(Dep=1)<
0.057
P(Dep=1)>
0.057
9 out of 12 crises called
Almost half of false calls
precede crises
Using the model in macroprudential
surveillance setting
• Forecasts over 1998-2008, using actual
for RHS (bold exceeds sample mean)
BG
CN
DK
FN
FR
GE
IT
JP
NL
NW
SD
SP
UK
US
1998
0.005
0.032
0.015
0.004
0.025
0.026
0.001
0.071
0.020
0.011
0.019
0.005
0.049
0.025
1999
0.004
0.054
0.041
0.006
0.018
0.027
0.002
0.025
0.018
0.006
0.016
0.006
0.060
0.032
2000
0.003
0.056
0.060
0.011
0.012
0.029
0.002
0.009
0.050
0.039
0.034
0.010
0.088
0.044
2001
0.004
0.033
0.046
0.007
0.014
0.045
0.009
0.010
0.049
0.016
0.048
0.028
0.173
0.074
2002
0.009
0.018
0.048
0.000
0.040
0.058
0.017
0.007
0.157
0.001
0.039
0.043
0.203
0.081
2003
0.005
0.022
0.029
0.000
0.028
0.031
0.020
0.007
0.141
0.001
0.058
0.044
0.201
0.067
2004
0.007
0.026
0.043
0.000
0.032
0.016
0.026
0.003
0.079
0.006
0.017
0.047
0.115
0.103
2005
0.014
0.037
0.030
0.004
0.053
0.020
0.039
0.002
0.028
0.003
0.006
0.096
0.207
0.064
2006
0.025
0.030
0.042
0.002
0.100
0.007
0.034
0.001
0.017
0.002
0.009
0.266
0.282
0.075
2007
0.048
0.036
0.030
0.007
0.193
0.007
0.054
0.001
0.019
0.001
0.011
0.516
0.277
0.097
2008
0.070
0.042
0.113
0.008
0.218
0.007
0.019
0.002
0.007
0.001
0.008
0.580
0.254
0.125
Using the model in macroprudential
policy setting
• We can invert the probability model to calculate
the additional levels of liquidity and leverage
required for the probability of a crisis to be 0.01
in each country and year
– Re-estimate each year from 1997, predict one year
– Raise capital and liquidity to get probability 0.01
• Capital and liquidity form the defences, while
house prices and current balances are the
problems we need to provision against, not
cycles or credit.
• Separate result shows credit does not Granger
cause OECD house prices either (except
Belgium, Canada and Finland)
Country and aggregate targets
• Country max
reduces
probability to
0.01 in worst
year
• The average of
these could be
used as a
criterion
• Major cross
country
differences in
warranted
tightening
Column
Top Panel
Belgium
Canada
Denmark
Finland
France
Germany
Italy
Japan
Neths
Norway
Sweden
Spain
UK
US
Mean
(International
Benchmark)
SD
1
2
Additions to country
specific levels of
liquidity and
leverage to reduce
all prob. to 0.01 or
below*
lev+nliq lev alone
2.11
2.56
3.31
4.15
3.35
4.15
0.00
0.00
5.08
6.25
3.12
3.79
1.74
2.14
3.96
5.19
4.72
5.80
2.34
2.87
2.38
2.90
9.32
11.48
6.08
7.63
4.35
5.34
3.70
2.24
4.59
2.77
3
4
Under or overshoot
(column 1 3.7)
lev and nliq
-1.59
-0.39
-0.35
-3.70
1.38
-0.58
-1.96
0.26
1.02
-1.36
-1.32
5.62
2.38
0.65
(column 2 4.59)
lev
-2.03
-0.44
-0.44
-4.59
1.66
-0.80
-2.45
0.60
1.21
-1.72
-1.69
6.89
3.04
0.75
Countercyclical provisioning
• Has to be calibrated on house prices and
current account and not credit or output gap
– example of 5% higher house price growth
France
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Spain
UK
US
Regulatory
adjustment
Actual
RHPG (-3)
Regulatory
adjus tment
Actual
RHPG (-3)
Regulatory
adjustment
Actual
RHPG (-3)
Regulatory
adjustment
Ac tual
RHPG (-3)
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.7
2.2
3.7
4.0
-3.2
1.3
0.8
1.7
7.5
6.2
6.1
7.2
10.0
13.4
13.6
0.0
0.0
0.0
0.0
0.3
0.4
0.5
2.1
4.6
6.8
7.3
-0.1
-1.7
0.0
3.8
5.3
4.7
6.1
12.5
14.1
13.4
10.2
0.6
1.0
1.9
3.5
3.8
3.8
2.5
3.9
4.8
4.7
4.4
-2.5
0.2
6.2
8.9
9.5
13.7
6.1
14.3
13.9
10.1
3.0
0.0
0.0
0.4
1.5
1.7
1.2
2.2
1.1
1.5
2.1
2.7
0.8
1.5
1.8
4.2
3.1
4.0
5.4
4.9
4.3
6.7
8.4
Decomposing changes in crisis
probabilities
France
2004
2005
2006
2007
2008
Sum of changes
Contribution to change in probability
Probability
NLIQ
LEV
RHPG
CBR
DOFFTOON
0.006
0.046
0.131
0.106
0.895
na
na
0.007
0.011
0.016
-0.000
0.034
na
0.005
0.030
-0.008
0.013
0.040
na
0.004
0.023
0.024
0.001
0.051
na
0.006
0.006
0.027
0.001
0.039
na
0.036
0.044
-0.126
0.775
0.729
Spain
2004
2005
2006
2007
2008
Sum of changes
Adj for
Change in
Interaction probability
na
0.017
0.030
-0.043
-0.000
0.004
na
0.040
0.085
-0.025
0.789
0.889
Contribution to change in probability
Probability
NLIQ
LEV
RHPG
CBR
DOFFTOON
0.035
0.067
0.173
0.398
0.479
na
na
0.022
0.031
0.065
-0.021
0.097
na
-0.012
0.040
0.044
0.016
0.089
na
0.026
0.017
-0.013
-0.063
-0.033
na
0.004
0.055
0.120
0.098
0.277
na
-0.009
-0.007
0.045
0.050
0.079
Adj for Change in
Interaction probability
na
-0.001
0.030
0.037
-0.001
0.064
na
0.032
0.106
0.225
0.081
0.444
Decomposing changes in crisis
probabilities
UK
2004
2005
2006
2007
2008
Sum of changes
Contribution to change in probability
Probability
NLIQ
LEV
RHPG
CBR
DOFFTOON
0.116
0.241
0.442
0.292
0.253
na
na
0.002
0.009
-0.002
0.010
0.020
na
0.010
0.057
0.024
0.026
0.118
na
0.099
-0.008
-0.066
-0.119
-0.094
na
-0.007
0.031
0.026
0.036
0.087
na
0.035
0.127
-0.135
-0.007
0.020
US
2004
2005
2006
2007
2008
Sum of changes
Adj for Change in
Interaction probability
na
0.015
0.016
-0.003
-0.015
0.013
na
0.125
0.201
-0.151
-0.038
0.137
Contribution to change in probability
Probability
NLIQ
LEV
RHPG
CBR
DOFFTOON
0.074
0.045
0.043
0.064
0.087
na
na
-0.017
0.002
0.002
0.004
-0.008
na
-0.015
-0.000
-0.008
0.004
-0.019
na
-0.002
-0.002
0.011
0.010
0.017
na
0.004
0.006
0.008
0.002
0.019
na
0.003
-0.009
0.010
0.004
0.008
Adj for
Change in
Interaction probability
na
0.001
-0.001
0.002
0.002
0.004
na
-0.029
-0.002
0.021
0.023
0.013
Conclusion
• Caution needed in directly comparing housing
markets due to structural differences
• Housing finance clearly at core of recent financial
crisis – US housing loans packaged into CDOs and
recent defaults following price falls
• Falls in house prices can be related inter alia to
changes in consumption, housing investment and
fiscal deficits since the crisis
• And clear relation of lagged house price increases
to OECD banking crises – relevant to ongoing bank
regulation reform also
• Key lesson for Sweden is to avoid boom-bust
cycle in housing, given macroeconomic volatility
and systemic financial risk it generates – and
long term intergenerational implications
• Control could be via appropriate monetary and
macroprudential policies (including control of
LTVs) – possibly also planning regulations
• If using securitisation ensure system is
transparent and incentive compatible
• Ensure banks have sufficient capital as well as
countercyclical reserves based on trends in
house prices (not credit per se)