House price information flows among some major Chinese cities: linear and nonlinear causality in time and frequency domains

Xiaojie Xu and Yun Zhang

International Journal of Housing Markets and Analysis, 2022, vol. 16, issue 6, 1168-1192

Abstract: Purpose - With the rapid-growing house market in the past decade, the purpose of this paper is to study the important issue of house price information flows among 12 major cities in China, including Shanghai, Beijing, Xiamen, Shenzhen, Guangzhou, Hangzhou, Ningbo, Nanjing, Zhuhai, Fuzhou, Suzhou and Dongguan, during the period of June 2010 to May 2019. Design/methodology/approach - The authors approach this issue in both time and frequency domains, latter of which is facilitated through wavelet analysis and by exploring both linear and nonlinear causality under the vector autoregressive framework. Findings - The main findings are threefold. First, in the long run of the time domain and for timescales beyond 16 months of the frequency domain, house prices of all cities significantly affect each other. For timescales up to 16 months, linear causality is weaker and is most often identified for the scale of four to eight months. Second, while nonlinear causality is seldom determined in the time domain and is never found for timescales up to four months, it is identified for scales beyond four months and particularly for those beyond 32 months. Third, nonlinear causality found in the frequency domain is partly explained by the volatility spillover effect. Originality/value - Results here should be of use to policymakers in certain policy analysis.

Keywords: House price; Information flow; Causality; VECM/VAR; Wavelet; Nonlinear causality; Linear causality (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijhmap:ijhma-07-2022-0098

DOI: 10.1108/IJHMA-07-2022-0098

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