Real estate listings and their usefulness for hedonic regressions

Jens Kolbe, Rainer Schulz, Martin Wersing, Axel Werwatz* (Corresponding Author)

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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 differ 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.
Original languageEnglish
Pages (from-to)1-31
Number of pages31
JournalEmpirical Economics
Early online date13 Jan 2021
DOIs
Publication statusE-pub ahead of print - 13 Jan 2021

Keywords

  • hedonic modelling
  • nowcasting
  • price prediction
  • Stochastic dominance
  • Hedonic modelling
  • Price prediction
  • Nowcasting

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