G2TT
来源类型Discussion paper
规范类型论文
来源IDDP16223
DP16223 Learning about Housing Cost: Survey Evidence from the German House Price Boom
Fabian Kindermann; Julia Le Blanc; Monika Piazzesi; Martin Schneider
发表日期2021-06-03
出版年2021
语种英语
摘要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.
主题Financial Economics ; Monetary Economics and Fluctuations
URLhttps://cepr.org/publications/dp16223
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/545192
推荐引用方式
GB/T 7714
Fabian Kindermann,Julia Le Blanc,Monika Piazzesi,et al. DP16223 Learning about Housing Cost: Survey Evidence from the German House Price Boom. 2021.
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