Housing price diffusions in mainland China: evidence from a spatially penalized graphical VAR model

Xiandeng Jiang, Le Chang () and Yanlin Shi
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Xiandeng Jiang: Southwestern University of Finance and Economics
Le Chang: Australian National University
Yanlin Shi: Macquarie University

Empirical Economics, 2023, vol. 64, issue 2, No 8, 765-795

Abstract: Abstract Although China has a large territory, few studies consider the factor of geographical distance when studying spatial interactions among city-level prices. We study housing price diffusions among seventy medium- and large-sized Chinese cities between July 2005 and August 2017 by using a spatially penalized graphical vector autoregression method that incorporates the intercity geographical distance. Our study reveals that the cities with the largest positive net centrality in each region are Nanchang (Central), Nanjing (Southeast), Changchun (Northeast), Beijing (North), Xiamen (South), Chongqing (Southwest) and Xining (Northwest). Furthermore, our results suggest that the four largest cities do not present the largest net centrality. Instead, many non-top-developed and non-major cities can play a significant role in affecting the regional housing markets. Our findings demonstrate that neglecting the influences of non-major cities may reduce the effectiveness and efficiency of relevant policies.

Keywords: Housing prices; Graphical models; Geographical distance; Centrality; Spatial spillovers (search for similar items in EconPapers)
JEL-codes: C31 C33 R21 R22 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s00181-022-02264-y

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