Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/213123 
Year of Publication: 
2020
Series/Report no.: 
FORLand-Working Paper No. 19 (2020)
Publisher: 
Humboldt-Universität zu Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets - Efficiency and Regulation", Berlin
Abstract: 
Compared to other asset classes, information on transactions of residential real estate is scarce and available only with delay. Listing information from web-platforms is abundant and timely. Is listings data useful for research? We examine this question and find that distributions of ask and sale prices differ significantly, both because of characteristics composition and implicit pricing. Estimates of the average willingness to pay from ask data can be widely off when compared with estimates from sale data. Ask data is also not useful to predict prices of individual houses and suffer from large error variances. Quality-controlled ask and sale price indices show similar trends and we find that an ask price index can be used for nowcasting. Overall, our analysis shows that ask data has limited potential for research, and is no substitute for sale data.
Subjects: 
hedonic modelling
nowcasting
price prediction
stochastic dominance
JEL: 
C14
C81
R31
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Working Paper

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