Identifying local housing markets through revealed preference

Michael Beenstock, Dan Feldman, Daniel Felsenstein*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

A new empirical approach to identify local housing markets (LHM’s) is proposed, which focuses on the spatial correlation between local house price indices constructed from repeat sales data. It extends the work of Pryce who claimed that if housing in different locations are perfect substitutes, their house price indices should be perfectly correlated over time. Pryce’s work represents a paradigmatic change in identifying local housing markets using revealed preferences rather than hedonic pricing. It requires spatial panel data for house prices which we construct using repeated sales data to generate house price indices for Tel Aviv (1998–2014) for over 100 census tracts. These price indices are used to define LHMs.  The number of LHMs varies inversely with the degree to which house prices in locations belonging to the same LHM, are expected to be correlated. It also varies directly with the order of contiguity of these locations. Results point to considerable spatial heterogeneity in house price movement. This belies the popular impression that the Tel Aviv housing market is relatively homogeneous, characterised by expensive housing and uniform house price movements.

Original languageAmerican English
Pages (from-to)118-146
Number of pages29
JournalJournal of Property Research
Volume37
Issue number2
DOIs
StatePublished - 2 Apr 2020

Bibliographical note

Publisher Copyright:
© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Hedonic method
  • correlation
  • real estate
  • repeat sales index
  • revealed preference

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