Transcript Slide 1

Macro-Prudential Tools and Regulation –
The International Perspective
Franklin Allen
Riksbank Workshop on Housing Markets,
Monetary Policy and Financial Stability
November 12, 2010
Real Estate Markets and Financial Stability
• Reinhart and Rogoff (2009) document that many
financial crises are the result of a sharp drop in
property prices
• In the current crisis Ireland, Spain and some regions
of the U.S. had sharp run ups and then collapses in
property prices that have had a severe effect on these
countries’ banking systems and economies
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Figure 1
Housing Prices in Ireland, Spain and the U.S.
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What are the causes of these real estate
bubbles?
• It is widely argued there are two important ones
1. Loose monetary policy – low interest rates
2. Global imbalances – easy availability of credit
•
The debate needs to go beyond Taylor’s (2008)
assertion that low interest rates cause property
bubbles if preventive policies are to be designed
•
We need to model how property bubbles arise
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Theories of bubbles
1. Infinite horizon (Tirole 1985, Caballero and
Krishnamurthy 2006, and Farhi and Tirole 2010)
2. Asymmetric information (Allen, Morris and
Postlewaite 1993, Conlon 2004, and Dobles-Madrid
2010)
3. Agency problems (Allen and Gorton 1993, Allen
and Gale 2000, 2003, Barlevy 2009)
4. Behavioral (De Long et al. 1990, Herring and
Wachter 1999, Abreu and Brunnermeier 2003, and
Scheinkman and Xiong 2003)
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What should a theory of bubbles explain?
• In “normal times” there are not property bubbles (e.g.
Germany for last 20 years)
• In “bubble times” there is a sharp run up in property
prices and then a collapse
• This distinction suggests there is a threshold where
speculators enter and start a bubble as developed in
Allen and Carletti (2010), which is based on an
agency approach
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Normal times
Willingness to pay
for housing services
P1’ = H(S1’)
P1’’ = H(S1’’)
S1’
Pr. π
S1’’
Pr. 1- π
Supply of housing
services
Risk neutral consumers determine prices
N
0
P
P1  (1  )P1
 H0 
1  C
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Bubble times
• Risk neutral speculators use their own wealth W and
loan with loan-to-value ratio λ to buy x units at price Pt
so Pt x  W  Pt x
• We focus on the case where there is no default when
the price is high but there is when it is low so
speculators enter if
N


 H0 (1  S )  P1  (1  r0 )P0 x  W(1  S ).


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• In this case speculators enter and the price is bid up
so this condition is satisfied with equality and there is
a bubble if
H 0 (1  S )  P1  W(1  S ) /(x)
P 
 P0N
(1  r0 )
B
0
• In the special case λ = 1, W = 0 and ρS = ρC = r0 = r
P1
P1  (1  )P1
N
P  H0 
 P0  H0 
(1  r)
1 r
B
0
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Policy considerations
• Objective of policy should be to prevent bubbles
occurring in the first place and restoring normal times
if speculators have entered
• Speculators’ entry condition more likely to be
satisfied with low interest rates and easily available
credit
• Monetary policy and credit availability can have a
role to play in controlling bubbles in small
homogeneous countries like Sweden but in large
heterogeneous economies like China, the Eurozone
and the U.S. macro-prudential policies need to be
relied upon
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Macro-Prudential policies
• Should eliminate speculators’ incentive to enter the
real estate market and create a bubble
1. Mandatory reductions in loan-to-value ratios
2. Increases in taxes on real estate transfers
3. Increases in annual real estate taxes
4. Direct restrictions on real estate lending
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Implementation of macro-prudential
• Borio and Lowe (2002) and other papers from the
BIS suggest difficult but not impossible to identify
property bubbles
• Christensson et al. (2010) look at Financial Stability
Reports of the Netherlands, Norway, Spain, Sweden,
and the U.K. over the period preceding and during the
crisis
• FSRs were successful in identifying risks and
unsustainable trends but many were regarded as low
probability events not worthy of action
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Chinese experience
• The Chinese have tried a number of these measures
– Lower loan-to-value ratios for second, third, and more
houses
– Taxes on resales of certain types of housing
– Restrictions on foreigners buying
– Loan restrictions on commercial property
• They have not worked very well in the major cities
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Beijing Housing Price vs Disposable Annual Income
Normalized, base year=2002
adjusted by CPI, 2002=100
400
350
300
250
200
150
100
50
housing price, RMB/sqm
Apr-10
Dec-09
Aug-09
Apr-09
Dec-08
Aug-08
Apr-08
Dec-07
Aug-07
Apr-07
Dec-06
Aug-06
Apr-06
Dec-05
Aug-05
Apr-05
Dec-04
Aug-04
Apr-04
Dec-03
Aug-03
Apr-03
Dec-02
income
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Apr-10
Dec-09
Aug-09
Apr-09
Dec-08
Aug-08
Apr-08
Dec-07
Aug-07
Apr-07
Dec-06
Aug-06
Apr-06
Dec-05
Aug-05
Apr-05
Dec-04
Aug-04
Apr-04
350
300
250
200
150
100
50
Dec-03
Aug-03
Apr-03
Dec-02
Shanghai Housing Price vs Disposable Annual Income
adjusted by CPI, 2002=100
housing price, RMB/sqm
income
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Shenzhen Housing Price vs Disposable Annual Income
Normalized, base year=2002
adjusted by CPI, 2002=100
400
350
300
250
200
150
100
50
housing price, RMB/sqm
Apr-10
Dec-09
Aug-09
Apr-09
Dec-08
Aug-08
Apr-08
Dec-07
Aug-07
Apr-07
Dec-06
Aug-06
Apr-06
Dec-05
Aug-05
Apr-05
Dec-04
Aug-04
Apr-04
Dec-03
Aug-03
Apr-03
Dec-02
income
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Concluding remarks
• Objective of policy should be to prevent the property
market becoming speculative
• Monetary policy and credit availability can have an
important role in some economies like Sweden
• It is not clear that macro-prudential policies will
prevent or eliminate bubbles but they may help
• Inefficiency of property markets is also important, i.e.
positive serial correlation of returns (e.g. Englund,
Quigley and Redfearn 1998), and needs to be
incorporated in the analysis
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