Housing Prices and Demography at City Level: The Case of Germany
||Hiller, Norbert; Oliver Lerbs
||Housing Prices and Demography at City Level: The Case of Germany
||21st Annual European Real Estate Society Conference in Bucharest, Romania
||Macroeconomists have long been interested in the role of money and credit growth for residential real estate price developments. For example, Goodhart and Hofmann (2008) analyze money effects on house prices across industrialized nations. Using panel vector autoregression (Holtz-Eakin et al. 1988), the authors find significant evidence for a strong link between monetary policy and housing price booms or even bubbles. Housing prices may be affected through different monetary transmission channels, like the volume of credit or interest rates. Although housing is produced and consumed locally, the focus of this research has been relying heavily upon national-level data. However, if economists want to examine house price effects of monetary variables, the viability of cross-country comparisons may be offset by a lack of comparability with regard to different institutions. Usually, researchers conclude that the impact of monetary and financial variables differs substantially between countries characterized by different institutional settings. Subnational economies, such as regions or local housing markets, can represent useful quasi-laboratories for examining monetary policy effects under fixed institutional or financial frameworks, because they share the same legal, political and social systems (Carlino and DeFina 2008).Since the financial crisis in 2008-09, residential real estate prices are significantly increasing in many major German cities. This may arguably be a result of the low interest rate policy, which has been applied to stabilize the European Monetary Union. To analyze the dynamic relationships between changes in interest rates, changes in the local demand for housing, and local housing price developments, we apply panel vector autoregression to city-level data from Germany. Our panel dataset contains 90 German cities and spans a time period of 16 years. By using Arellano-Bond (Arellano and Bond 1991) estimators we calculate orthogonalized impulse-response functions. Hence we are able to separate fundamental factors (demography, income) from monetary factors (interest rates) that influence city-level housing prices. We find that monetary shocks, like lower interest rates, affect local house prices differently across different city groups. Housing markets with low elasticity of supply are very sensitive to interest rate changes. Therefore a continued low interest rate policy may accelerate local residential real estate booms in parts of Germany.
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||D : Housing Markets & Economics
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