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The international transmission of house price shocks Are there contagion effects? Olivier de Bandt (BdF) Karim Barhoumi (BdF) Catherine Bruneau (Paris.

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Presentation on theme: "The international transmission of house price shocks Are there contagion effects? Olivier de Bandt (BdF) Karim Barhoumi (BdF) Catherine Bruneau (Paris."— Presentation transcript:

1 The international transmission of house price shocks Are there contagion effects? Olivier de Bandt (BdF) Karim Barhoumi (BdF) Catherine Bruneau (Paris X and BdF)

2 Transmission/contagion Transmission: reaction of house prices to fundamentals in « normal times », including all available information –Fundamentals are correlated –Arbitrage behaviour across markets smooth out idiosyncracies Contagion: 2 definitions: –Amplitude of reaction differs in « crisis periods », with possible non linearities –Pandemic model: « from local to global and global to local »

3 Data House prices from OECD and national sources OECD quarterly national accounts : GDP, inflation, short and long term interest rates, housing investment 15 countries: AUS, CAN, CHE, FIN, FRA, DEU, IRE, ITA, JPN, NLD, NOR, NZL, ESP, UK, US

4 Methods Single linear equations to estimate the link between ‘local’ and ‘global’ levels, including house prices Linear Favar models and causality tests – to take into account endogeneity –But need to accomodate the high persistence of variables Crisis dummies and STAR models to assess possible non linearities

5 Main Findings Contagion from US house prices, which appear to be exogenous Spreading to the rest of the world, according to the « pandemic view » of contagion : common house prices « Granger cause » domestic house prices in Favar models

6 Plan I – A closer look at the data II- Empirical results III- Conclusion

7 l- A closer look at the data (1/4) Common SW’s house prices in OECD countries

8 I- A closer look at the data (2/4) Using a larger database : fac1 correlated with interest rates

9 I- A closer look at the data (3/4) Using a larger database : fac2 correlated with GDP growth)

10 I- A closer look at the data (4/4) Using a larger database : fac3 corr. with OGAP

11 II- Empirical results 1- single one period ahead equation with global house price factor 2- single one period ahead equation with crisis dummy 3-single one period ahead equation with other global factors 4- single non linear (LSTAR) with all global factors 5- causality tests in Favar models

12 1- Single one period ahead linear equations => international housing factor is significant in many countries: AUS, ESP, UK

13 2- robustness to Financial Crisis periods (Reinhart & Rogoff, 2008)

14 Tab2: Robustness to crisis periods

15 3- Tab3: Sensitiveness to global factors in single one period ahead equation

16 4-LSTAR models: contemporaneous impact of the threshold variable in the two regimes

17 5-Causality in favar models of reduced order: US house prices are exogeneous and affect Common house prices

18 Causality in favar models of reduced order: Other domestic house prices are affected by Common house prices

19 Causality from systems : Other domestic house prices are affected by Common house prices

20 III-Conclusion Evidence in favour of international transmission Evidence in favour of « pandemic model » with contagion from USA to rest of countries


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