Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/286798 
Year of Publication: 
2021
Citation: 
[Journal:] Empirical Economics [ISSN:] 1435-8921 [Volume:] 61 [Issue:] 6 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2021 [Pages:] 3239-3269
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
Real estate platforms provide a new source of data which has already been used as a substitute for transaction data in hedonic regression applications. This paper asks whether it is valid to do so in the established research areas of (1) willingness to pay estimation, (2) automated valuations, and (3) price index construction. It therefore compares listings and transaction data and regression results derived from them. We find that ask prices stochastically dominate sale prices, mainly because the composition of characteristics differs between the two data sets. But estimates of implicit prices also differ. As a result, willingness to pay estimates from listings data can be widely off when compared with estimates from transaction data. Listings data are not very useful to predict market values of individual houses either, as these predictions suffer from upward bias and large error variance. We find, however, that an ask price index complements a sale price index, as it is useful for nowcasting.
Subjects: 
Hedonic modelling
Nowcasting
Price prediction
Stochastic dominance
JEL: 
C14
C81
R31
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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