Mapping China’s time-varying house price landscape

Michael Funke, Danilo Leiva-Leon () and Andrew Tsang

No 1930, Working Papers from Banco de España

Abstract: The recent increase in China’s house prices at the national level masks tremendous variation at the city level – a feature largely overlooked in the macroprudential literature. This paper measures the evolving heterogeneity in China’s house price dynamics across 70 major cities and assesses its relationship with housing market characteristics. We gauge the heterogeneity of house price dynamics using a novel regime-switching modelling approach to estimate the time-varying patterns of China’s city-level housing price synchronization. The estimates indicate an increasing synchronization leading up to 2015, and a decoupling pattern thereafter, which is associated to the heterogeneous strength of regional macroprudential policies. After sorting city-level housing prices into four clusters sharing similar cyclical features, we document high synchronization within clusters, but low synchronization among them. The empirical evidence suggests that differentials in the growth of population, income, and air quality are relevant explanatory factors of housing price synchronization among cities.

Keywords: house prices; Markov-Switching models; synchronization; China (search for similar items in EconPapers)
JEL-codes: C32 E31 E32 R11 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2019-09
New Economics Papers: this item is included in nep-cna, nep-mac, nep-tra and nep-ure
References: Add references at CitEc
Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Mapping China’s time-varying house price landscape (2019)
Working Paper: Mapping China's time-varying house price landscape (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:bde:wpaper:1930

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