Using a dynamic factor model with time-varying stochastic volatility, we decompose a city’s real housing price growth into a global component, a cluster-based component, and an idiosyncratic component. We interpret this finding as suggestive of a rather segmented housing market for the global cities in our sample. Using a hierarchical clustering approach, we identify three clusters of cities with similar housing price cycles that are not solely determined by geographic proximity. We find that although there is evidence for bilateral positive phase synchronization, there is no evidence for an integrated global housing market for our sample of cities. In this paper we examine house price synchronization in 15 global cities using real house price data from 1995:Q1-2020:Q2.
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