The quantile connectedness of the international housing market

Xichen Wang

Journal of International Money and Finance, 2025, vol. 152, issue C

Abstract: This paper investigates the interconnectedness of the international housing market using quantile connectedness models. It finds that: (1) House price shocks spread more strongly in tails than in the median. (2) Large positive shocks spread as strongly as large adverse shocks. (3) The US housing market is the leading transmitter of systematic shocks. The machine learning algorithms further reveal that the US interest rate is the most influential global factor in predicting spillover intensities. These findings suggest that policymakers should monitor global contagions, paying attention to booms/busts in US house prices and fluctuations in its monetary policy.

Keywords: International housing market; Quantile connectedness; Machine learning; Global financial cycle (search for similar items in EconPapers)
JEL-codes: E44 F36 G15 R31 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jimfin:v:152:y:2025:i:c:s0261560625000014

DOI: 10.1016/j.jimonfin.2025.103266

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