IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v115y2022ics0264999322001912.html
   My bibliography  Save this article

Empirical evidence of risk contagion across regional housing markets in China

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999322001912
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econmod.2022.105945?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Feng, Yun & Hou, Weijie & Song, Yuping, 2023. "Asymmetric contagion of jump risk in the Chinese financial sector: Monetary policy transmission matters," Economic Modelling, Elsevier, vol. 119(C).
    2. Xu, Xiaoyue & Mi, Anran & Li, Xiuting & Li, Xuerong & Dong, Jichang, 2024. "Bad news travels fast: Network analysis of the Chinese housing market connectivity," China Economic Review, Elsevier, vol. 84(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    2. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    3. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    4. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
    5. Grundke, Peter & Polle, Simone, 2012. "Crisis and risk dependencies," European Journal of Operational Research, Elsevier, vol. 223(2), pages 518-528.
    6. Zhang, Ran & Czado, Claudia & Min, Aleksey, 2011. "Efficient maximum likelihood estimation of copula based meta t-distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1196-1214, March.
    7. So, Mike K.P. & Yeung, Cherry Y.T., 2014. "Vine-copula GARCH model with dynamic conditional dependence," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 655-671.
    8. Dong Hwan Oh & Andrew J. Patton, 2017. "Modeling Dependence in High Dimensions With Factor Copulas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 139-154, January.
    9. Gregor Weiß, 2013. "Copula-GARCH versus dynamic conditional correlation: an empirical study on VaR and ES forecasting accuracy," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 179-202, August.
    10. Prayer M. Rikhotso & Beatrice D. Simo-Kengne, 2022. "Dependence Structures between Sovereign Credit Default Swaps and Global Risk Factors in BRICS Countries," JRFM, MDPI, vol. 15(3), pages 1-22, February.
    11. Krupskii, Pavel & Joe, Harry, 2013. "Factor copula models for multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 85-101.
    12. BenSaïda, Ahmed, 2018. "The contagion effect in European sovereign debt markets: A regime-switching vine copula approach," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 153-165.
    13. Thijs Markwat, 2014. "The rise of global stock market crash probabilities," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 557-571, April.
    14. Li, Qiang & Nong, Huifu, 2022. "A closer look at Chinese housing market: Measuring intra-city submarket connectedness in Shanghai and Guangzhou," China Economic Review, Elsevier, vol. 74(C).
    15. Çekin, Semih Emre & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "Measuring co-dependencies of economic policy uncertainty in Latin American countries using vine copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 207-217.
    16. Dißmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    17. Wang, Hao & Dong, Yizhe & Sun, Mingli & Shi, Baofeng & Ji, Hao, 2024. "Dynamic dependence of futures basis between the Chinese and international grains markets," Economic Modelling, Elsevier, vol. 130(C).
    18. EnDer Su, 2017. "Measuring and Testing Tail Dependence and Contagion Risk Between Major Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 325-351, August.
    19. Eling, Martin & Jung, Kwangmin, 2020. "Risk aggregation in non-life insurance: Standard models vs. internal models," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 183-198.
    20. Simon Fritzsch & Maike Timphus & Gregor Weiss, 2021. "Marginals Versus Copulas: Which Account For More Model Risk In Multivariate Risk Forecasting?," Papers 2109.10946, arXiv.org.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecmode:v:115:y:2022:i:c:s0264999322001912. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.