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Empirical evidence of risk contagion across regional housing markets in China

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  • Hu, Genhua
  • Fan, Gang-Zhi

Abstract

This study constructed regular vine copula models to investigate risk contagion across China's regional housing markets, which has recently garnered substantial attention in academic and practical domains. We utilised the Chinese monthly price indices of new commercial housing sales from 2006 to 2019. We found that the housing markets within the three primary Chinese urban agglomerations have tail dependencies, thereby implying the tendency for these markets to experience extreme market situations together. Therefore, these housing markets share risk contagion. Furthermore, China's four first-tier cities—Shanghai, Beijing, Guangzhou, and Shenzhen—drive regional market risk contagion. Market risk alternately diffuses across the adjacent major housing markets and expands from these first-tier cities to their surrounding areas. These findings suggest that risk contagion should be carefully considered in developing regulation policies and making investment decisions associated with China's real estate markets.

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  • Hu, Genhua & Fan, Gang-Zhi, 2022. "Empirical evidence of risk contagion across regional housing markets in China," Economic Modelling, Elsevier, vol. 115(C).
    • Handle: RePEc:eee:ecmode:v:115:y:2022:i:c:s0264999322001912
    DOI: 10.1016/j.econmod.2022.105945
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    as
    1. Marco Helbich & Wolfgang Brunauer & Eric Vaz & Peter Nijkamp, 2014. "Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria," Urban Studies, Urban Studies Journal Limited, vol. 51(2), pages 390-411, February.
    2. Marcel Fratzscher, 2003. "On currency crises and contagion," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(2), pages 109-129.
    3. Jeffrey P. Cohen & Cletus C. Coughlin & David A. Lopez, 2012. "The boom and bust of U.S. housing prices from various geographic perspectives," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 341-368.
    4. Hanming Fang & Quanlin Gu & Wei Xiong & Li-An Zhou, 2016. "Demystifying the Chinese Housing Boom," NBER Macroeconomics Annual, University of Chicago Press, vol. 30(1), pages 105-166.
    5. Chang, Kuang-Liang & Chen, Nan-Kuang & Leung, Charles Ka Yui, 2012. "The dynamics of housing returns in Singapore: How important are the international transmission mechanisms?," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 516-530.
    6. Ji, Hao & Wang, Hao & Zhong, Rui & Li, Min, 2020. "China's liberalizing stock market, crude oil, and safe-haven assets: A linkage study based on a novel multivariate wavelet-vine copula approach," Economic Modelling, Elsevier, vol. 93(C), pages 187-204.
    7. Yao, Can-Zhong & Sun, Bo-Yi, 2018. "The study on the tail dependence structure between the economic policy uncertainty and several financial markets," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 245-265.
    8. Matthias Fischer & Christian Kock & Stephan Schluter & Florian Weigert, 2009. "An empirical analysis of multivariate copula models," Quantitative Finance, Taylor & Francis Journals, vol. 9(7), pages 839-854.
    9. Feng, Qu & Wu, Guiying Laura, 2015. "Bubble or riddle? An asset-pricing approach evaluation on China's housing market," Economic Modelling, Elsevier, vol. 46(C), pages 376-383.
    10. Ren, Yu & Xiong, Cong & Yuan, Yufei, 2012. "House price bubbles in China," China Economic Review, Elsevier, vol. 23(4), pages 786-800.
    11. Zietz, Joachim & Traian, Anca, 2014. "When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 271-281.
    12. Franklin Allen & Elena Carletti, 2010. "An Overview of the Crisis: Causes, Consequences, and Solutions-super-," International Review of Finance, International Review of Finance Ltd., vol. 10(s1), pages 1-26.
    13. Kjersti Aas & Daniel Berg, 2009. "Models for construction of multivariate dependence - a comparison study," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 639-659.
    14. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Dependence and extreme dependence of crude oil and natural gas prices with applications to risk management," Energy Economics, Elsevier, vol. 42(C), pages 332-342.
    15. Wei-Fong Pan, 2019. "Detecting bubbles in China’s regional housing markets," Empirical Economics, Springer, vol. 56(4), pages 1413-1432, April.
    16. Garriga, Carlos & Hedlund, Aaron & Tang, Yang & Wang, Ping, 2021. "Rural-urban migration and house prices in China," Regional Science and Urban Economics, Elsevier, vol. 91(C).
    17. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    18. Michael Young, 2008. "Revisiting Non-normal Real Estate Return Distributions by Property Type in the U.S," The Journal of Real Estate Finance and Economics, Springer, vol. 36(2), pages 233-248, February.
    19. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
    20. Bourassa, Steven C. & Hoesli, Martin & Peng, Vincent S., 2003. "Do housing submarkets really matter?," Journal of Housing Economics, Elsevier, vol. 12(1), pages 12-28, March.
    21. Ji, Qiang & Marfatia, Hardik & Gupta, Rangan, 2018. "Information spillover across international real estate investment trusts: Evidence from an entropy-based network analysis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 103-113.
    22. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    23. Hao Ji & Hao Wang & Jia Xu & Brunero Liseo, 2020. "Dependence Structure between China’s Stock Market and Other Major Stock Markets before and after the 2008 Financial Crisis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(11), pages 2608-2624, September.
    24. Gordon W. Crawford & Michael C. Fratantoni, 2003. "Assessing the Forecasting Performance of Regime‐Switching, ARIMA and GARCH Models of House Prices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(2), pages 223-243, June.
    25. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    26. Zhang, Dingsheng & Cheng, Wenli & Ng, Yew-Kwang, 2013. "Increasing returns, land use controls and housing prices in China," Economic Modelling, Elsevier, vol. 31(C), pages 789-795.
    27. Chia, Wai-Mun & Li, Mengling & Tang, Yang, 2017. "Public and private housing markets dynamics in Singapore: The role of fundamentals," Journal of Housing Economics, Elsevier, vol. 36(C), pages 44-61.
    28. Asimit, Alexandru V. & Gerrard, Russell & Hou, Yanxi & Peng, Liang, 2016. "Tail dependence measure for examining financial extreme co-movements," Journal of Econometrics, Elsevier, vol. 194(2), pages 330-348.
    29. Franklin Allen & Elena Carletti, 2010. "An Overview of the Crisis: Causes, Consequences, and Solutions," International Review of Finance, International Review of Finance Ltd., vol. 10(1), pages 1-26, March.
    30. Dayong Zhang & Gang-Zhi Fan, 2019. "Regional spillover and rising connectedness in China’s urban housing prices," Regional Studies, Taylor & Francis Journals, vol. 53(6), pages 861-873, June.
    31. Martin Hoesli & Kustrim Reka, 2013. "Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 47(1), pages 1-35, July.
    32. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    33. Tsai, I-Chun & Chiang, Shu-Hen, 2019. "Exuberance and spillovers in housing markets: Evidence from first- and second-tier cities in China," Regional Science and Urban Economics, Elsevier, vol. 77(C), pages 75-86.
    34. Fan, Ying & Yang, Zan & Yavas, Abdullah, 2019. "Understanding real estate price dynamics: The case of housing prices in five major cities of China✰," Journal of Housing Economics, Elsevier, vol. 43(C), pages 37-55.
    35. Aleksey Min & Claudia Czado, 2010. "Bayesian Inference for Multivariate Copulas Using Pair-Copula Constructions," Journal of Financial Econometrics, Oxford University Press, vol. 8(4), pages 511-546, Fall.
    36. Wang, Haiying & Yuan, Ying & Li, Yiou & Wang, Xunhong, 2021. "Financial contagion and contagion channels in the forex market: A new approach via the dynamic mixture copula-extreme value theory," Economic Modelling, Elsevier, vol. 94(C), pages 401-414.
    37. Cubillos-Rocha, Juan S. & Gomez-Gonzalez, Jose E. & Melo-Velandia, Luis F., 2019. "Detecting exchange rate contagion using copula functions," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 13-22.
    38. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 401-423, June.
    39. David M. Zimmer, 2012. "The Role of Copulas in the Housing Crisis," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 607-620, May.
    40. Paul Embrechts, 2009. "Copulas: A Personal View," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 639-650, September.
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    More about this item

    Keywords

    China housing Markets; Market risk; Risk contagion; Tail dependence; Urban agglomerations;
    All these keywords.

    JEL classification:

    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

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