HOUSING AND THE MACROECONOMY: THE ITALIAN CASE Guido Bulligan*

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HOUSING AND THE MACROECONOMY: THE ITALIAN CASE Guido Bulligan* “The Macroeconomics of housing markets” Session 1A: Housing and the business cycle - Domestic features HOUSING AND THE MACROECONOMY: THE ITALIAN CASE Guido Bulligan* Paris, 3-4 December 2009 * Bank of Italy, Department of Economic Outlook and Monetary Policy Studies 1

Motivations Rising housing prices, indebtedness and imbalances (graphs) Real house prices in Italy have increased by 40% since last cyclical trough Households debt (as % of GDP) has doubled in the last 10 years Local nature of housing markets, cross-country heterogeneity (graphs) High home-ownership rate (72%) Low (but increasing) level of indebtedness of Italian households Incomplete housing finance markets (products variety, transaction costs) Empirical evidence Existing empirical evidence mainly focused on Anglo-saxon countries Previsione= NIPE di dicembre 2

Aim of the paper Searching for stylized facts of the Italian housing market Over the cycle: growth cycle approach In reaction to a monetary policy shock: SVAR analysis Previsione= NIPE di dicembre 3

The Housing market Cycle: descriptive statistics Previsione= NIPE di dicembre 4

The Housing market Cycle: GC approach Focus on cycles as deviationd from trend: Cycle defined as fluctions with period between 3 and 10 years as shortest cycle is 26 quarters and longest is 46 quarters Use of band pass filter (Baxter and King) Previsione= NIPE di dicembre 5

The Housing market Cycle: Synchronization I Lead/lag relationships analyzed through cross-correlations Residential investment leads real house price by 3 quarters GDP and demand components (C and I not shown) lead house price by 7 quarters Inflation and policy rate lead house price by 1 and 3 quarters Previsione= NIPE di dicembre 6

The Housing market Cycle: Synchronization I Lead/lag relationships analyzed through cross-correlations GDP and demand components (C and I not shown) lead res. inv. by 2 quarters Inflation and policy rate lag house res. inv. By 1 and 4 quarters Previsione= NIPE di dicembre 7

The Housing market Cycle: Synchronization II Lead/lag relationships analyzed through cross- concordance Residential investment lead real house price by 5 quarters GDP and demand components (C and I not shown) lead house price by 7 quarters Inflation and policy rate lead house price by 5 and 1 quarters Previsione= NIPE di dicembre 8

The Housing market: SVAR analysis I VARIABLES: Endogenous: CPI, GDP, Nominal House price index (PH)*, real residential investment (INV), Policy rate (P.rate)** Exogenous: dummy variables, World commodity price index DATA Quarterly data 1990-2008 All variables (except policy rate) in log-levels IDENTIFICATION Recursive (Cholesky) Sign restrictions on impulse-reponses Notes: * In the following graphs, the response of real house price is obtained by construction ** P. rate is the bank of Italy repo rate until 1999 and rate on main refinancing operation of ECB from 1999 Previsione= NIPE di dicembre 9

The Housing market: SVAR analysis I Previsione= NIPE di dicembre 10

The Housing market: SVAR analysis I Previsione= NIPE di dicembre 11

The Housing market: SVAR analysis II Previsione= NIPE di dicembre 12

The Housing market: SVAR analysis At business cycle horizons, monetary policy shocks account between 10 and 15% of variance of residential investment and around 10% of variance of nomina house price but less then 10% of variance of real house prices Previsione= NIPE di dicembre 13

Conclusions To summarize: Housing cycles are longer than cycles in macro variables Housing cycles are asymmetric in terms of duration, intensity and price adjustment GDP and components lead housing cycle Inflation and interest rates are more coincident Monetary policy shocks have modest but significant and long-lasting effects on housing variables (maximum impact between 0.2% and 1% for res. investment and between 0.1% and 0.5% for real house price) Monetary policy shocks explains around 10-20 percent of variability of housing variables at the 2-5 years horizons their role is insignificant at shorter horizons Previsione= NIPE di dicembre 14

House price and residential investment (back) Previsione= NIPE di dicembre 15

Cross-country heterogeneity (back) Previsione= NIPE di dicembre 16