1. House Price Cycles and the Real Economy
Deniz Igan
IMF – Research
LIME Workshop
Brussels - December 8, 2012
Disclaimer: Views expressed in the presentation and during the talk are those of the presenter and should not be ascribed to the IMF.

2. Background Work
The Changing Housing Cycle and the Implications for Monetary Policy – Chapter 3 in WEO April 2008
Housing, Credit, and Real Activity Cycles: Characteristics and Comovement – JHE 2011 (revision of Three Cycles: Housing, Credit, and Real Activity, IMF WP 09/231)
Global Housing Cycles – IMF WP forthcoming
Early Warning Exercise – conducted twice a year

3. Outline Research questions Relevant literature (briefly)
Preview of results
Methodology and data (briefly)
Results
Conclusions and policy implications

4. Research Questions
How similar are the cycles: in duration, amplitude, etc.?
How do the cycles relate to the interest rate changes?
Are the cycles synchronized, or does one lead the others?
How important are global versus local factors?
What are the policy implications?
Individual country cycles vary not only in the sense that their characteristics are different but also supported by the fact that, over the minor cycle, lead-lag relationships vary across countries.

5. Literature—Domestic Context
Bank credit, house prices and aggregate demand tend to move in tandem
Financial accelerator effects through external finance premium and collateral prices result in procyclicality of bank credit
Bernanke and Gertler, 1989; Kiyotaki and Moore, 1997
Liquidity and leverage of banks also contribute
Adrian and Shin (2008), Berger and Bouwman (2008)
Liquidity of housing wealth and availability of housing financing can also alter the relationship through consumption and investment

6. Literature—International Context
The degree of synchronization in real and financial cycles increased
Kose, Prasad and Terrones, 2003; Imbs, 2004; Otrok and Terrones, 2005
International comovement in house prices may reflect comovement of interest rates
Especially with debt-financed ownership and adjustable-rate mortgages
Global liquidity may have also contributed
Belke and Orth, 2008

7. Literature—Monetary Policy
Transmission through the credit channel and the housing market
Monetary policy, credit and asset prices
Benign neglect: Monetary policy is not an effective tool for targeting asset prices, so better not to prick the bubble but mop up afterwards (Bernanke, Gertler, and Gilchrist, 1999)
Leaning against the wind: Monetary policy needs to play a more proactive role to prevent financial bubbles (Borio and Lowe, 2002, and Borio, 2006)

8. Contribution of This Paper
Multidirectional links
Goodhart and Hofman (2008)
Focus on output, bank credit, house prices (as well as residential investment) and interest rates
Descriptive approach
GDFM as opposed to VAR
Data properties
Unit root tests
Filtering as opposed to differencing
Different horizons
Short to medium term (6 to 16 quarters)
Long term (16 to 32 quarters)
Individual country cycles vary not only in the sense that their characteristics are different but also supported by the fact that, over the minor cycle, lead-lag relationships vary across countries.

9. Preview of Results
House price cycles lead credit and business cycles over the long run
Interest rates tend to lag other cycles at all horizons
Country cycles are largely driven by global factors
the role of which has increased over time, especially for credit and business cycles
U.S. cycles tend to lead other countries’ respective cycles
Individual country cycles vary not only in the sense that their characteristics are different but also supported by the fact that, over the minor cycle, lead-lag relationships vary across countries.

10. Generalized Dynamic Factor Model
Identifies a common component using a large number of series
Builds on the traditional factor models
Sargent and Sims (1977) and Geweke (1977)
By allowing for serial correlation and weakly cross-sectional correlation of idiosyncratic components
Chamberlain (1983) and Chamberlain and Rothschild (1983)
Recent examples
Giannone, Reichlin, and Sala (2002)
Forni and others (2005)
Eickmeier (2007)

11. (Approximate) GDFM
where Yt is a (N x T) vector stochastic stationary process with zero mean and
unit variance and Xt and Ξt are (N x T) vectors of common and idiosyncratic
components, respectively.
Xt can be written as:
where Ft is a (r x T) vector of common factors and C is a (N x r) matrix of factor
loadings.
The model has N>>T and r<<N.
The common factors assumed to follow an AR(1) process:
with B and (r x r) matrix and ut a (r x T) vector of residuals.

12. Measures of Comovement
The dynamic correlation varies between -1 and 1. Formally,
where the numerator is the cospectrum between y1 and y2 processes at frequency
λ and S (y1) and S (y2) are the spectral density functions of the processes at
frequency λ defined over –π and π.
Coherence is intrinsically related to dynamic correlation given by:
Coherence is symmetric and a real number between 0 and 1.

13. Lead-Lag Relationship
The phase angle between processes helps identify the lead-lag relationship
where q (y1 y2) is the quadrature spectrum. Only when K (y1y2) ≠0, the phase angle converges in distribution to a normal random variable.

14. Panel Data 18 industrial countries 1981 Q1 to 2006 Q4 1,283 series
Real activity indicators
Consumption
Investment, including residential
International trade
Confidence indicators
Portfolio and FDI flows
Financial variables
Credit to the private sector and other monetary aggregates
Short-term and long-term interest rates
House prices and stock prices
Balance sheet data
Household savings and assets (in particular, housing stock)
Capital stock of business sector

15. Unit Root Tests ERS (Elliott, Rothenberg and Stock, 1996)
Generalized least squares
More powerful than standard Dickey-Fuller test
KPSS (Kwiatowski, Phillips, Schmidt and Shin, 1992)
Cross check
Stationarity as H0 instead of unit root
Constant and deterministic trend
Lags chosen based on the Schwarz information criterion

16. Results of Unit Root Tests
House prices are sometimes I(2)
France, Ireland, the Netherlands, New Zealand, Sweden and the United States
Credit series are also I(2) in some cases
Japan and Spain
Over-differencing versus under-differencing

17. Unit Root Tests (Details)
17 cases of I(2) out of 60 (20 countries x 3 cycles)

18. Band-Pass Filter Corbae and Ouliaris (2006) ideal band-pass filter
Passes through the components of time series with periodic fluctuations between 6 and 32 quarters (in line with widely used minor-major cycle lengths)
Consistent
No finite sampling error
Not subject to end-point problems

19. Advantages of Filtering over Differencing

20. Wrong data transformation may introduce a downward bias in the degree of economic integration and an upward bias in the efficiency of uncoordinated macroeconomic policies.

21. Characteristics of Cycles
Credit and house price cycles tend to be slightly more protracted on average than business cycles...
but peaks and troughs generally are not too far.
Credit and house price cycles have larger swings than real activity cycles).
In some countries, there are significant differences across these characteristics…
Countries that allow MEW and refinancing tend to have larger amplitude and longer duration in house price cycles relative to the business cycle if the share of variable rate mortgages is large (e.g., New Zealand versus Germany).
Not necessarily Leamer (“Housing is the business cycle”) but housing does matter.

22. Characteristics of Cycles

23. Procyclicality
Financial accelerator model is not empirically supported in all countries—correlations vary in significance and sign.
Collateral is a driver of procyclicality more than lending is—stronger correlation between output and house prices than between output and bank credit.

24. Procyclicality

25. Common Components
A large share of common components drive the three cycles.
The share of the common component in GDP and in credit has increased over time.
The importance of common shocks and/or the speed of transmission of shocks has increased over time.

26. Common Components
GDP

27. Common Components
Credit

28. Common Components
House prices

29. Evolution of Common Components

30. Leads and Lags
During the minor cycle, house prices lead output and credit only in a few cases.
In the long run, there is some support for financial accelerator mechanism, but which channel?
balance sheet improvements -> credit -> house prices or
house prices -> creditworthiness -> credit
Short-term interest rates never lead house prices.
House prices lead output, which in turn leads credit.
U.S. cycles lead the corresponding cycles in the long run in most cases, and U.S. credit cycles lead only in the short run.

31. Leads and Lags (Details - 1)

32. Leads and Lags (Details – 2)

33. Conclusions House price cycles lead other cycles in the long run
Interest rates tend to lag other cycles at all horizons
Global factors are important for all cycles, especially for credit and real activity in the latter part of the sample period
U.S. leads other countries in all cycles
Individual country cycles vary not only in the sense that their characteristics are different but also supported by the fact that, over the minor cycle, lead-lag relationships vary across countries.

34. Similar conclusions from other research
A six-variable VAR: real GDP, private consumption, residential investment, CPI inflation, the nominal (short term) interest rate and real house prices. 20 countries, sample from
House price shocks are identified with a Cholesky decomposition. In practice they look like “housing demand shocks” because they lead to a strong comovement between real house prices and residential investment. Alternative identification through sign restrictions.
VAR delivers average responses, but there could be asymmetries between house price booms and busts.

35. Impact on Real GDP of a 10% decline in real house prices

36. Mortgage market characteristics matter

37. Policy Implications
Can a uniform policy prescription of taking into account asset prices in monetary policy making be made? It seems not, statistical properties of house prices vary across countries. In addition, some shocks to house price inflation are persistent.
The U.S. business, house price, and interest rate cycles tend to lead the respective cycles in other countries over all horizons and more so recently. Questions domestically-focused economic policies.
MP targeting HP may contradict with price stabilization objective, opening credibility questions.