Learning about Housing Cost: Survey Evidence from the German House Price Boom
This paper uses new household survey data to study expectation formation during the recent housing boom in Germany. The cross section of forecasts depends on only two household characteristics: location and tenure. The average household in a region responds to local conditions but underpredicts local price growth. Renters make on average higher and hence more accurate forecasts than owners, although their forecasts are more dispersed and their mean squared forecast errors are higher. A quantitative model of learning about housing cost can match these facts. It emphasizes the unique information structure of housing among asset markets: renters who do not own the asset are relatively well informed about its cash flow, since they pay for housing services that owners simply consume. Renters then make more accurate forecasts in a boom driven by an increase in rents and recovery from a financial crisis.
We thank Rudi Bachmann, Theresa Kuchler, Ulrike Malmendier, Charles Nathanson, Tom Sargent, Johannes Stroebel, Stijn van Nieuwerburgh, Michael Weber, and seminar participants at Bonn, Chicago, Deutsche Bundesbank, ECB, Federal Reserve Bank at Cleveland, Harvard, HULM, Leuven, Manchester, Munich, "Micro and Macro Implications of Household Finance", NBER Summer Institute, NYU, Queens, UBC, and UC Santa Cruz for helpful comments. A large part of this paper was written while Julia Le Blanc was a senior research economist at the Deutsche Bundesbank in Frankfurt. We thank the Deutsche Bundesbank for kindly providing us with all their available data on house prices and expectations as well as with an excellent research infrastructure. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.