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.