Robust hedonic price indexes

Steven C. Bourassa (Corresponding Author), Eva Cantoni, Martin Hoesli

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


– The purpose of this paper is to demonstrate the application of robust techniques to the estimation of hedonic house price indexes.

– The authors use simulation analysis to compare an index estimated using ordinary least squares (OLS) with several indexes estimated using robust techniques. The analysis uses sales transactions data from a US city. The authors then explore how robust methods can correct for omitted variables under some circumstances and how they affect the revision problem that occurs when longitudinal hedonic indexes are updated.

– Robust methods can resolve missing variable problems in some circumstances and also can substantially reduce the revision problem in longitudinal hedonic indexes.

Practical implications
– Robust techniques may be preferable to OLS when constructing longitudinal hedonic indexes.

– This is the first paper to undertake a systematic analysis of the applicability of robust techniques in constructing hedonic house price indexes.
Original languageEnglish
Pages (from-to)47-65
Number of pages19
JournalInternational Journal of Housing Markets and Analysis
Issue number1
Publication statusPublished - 2016


  • housing market analysis
  • data problems
  • distressed sales
  • Hedonic models
  • house price indexes
  • robust methods


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