IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v63y2022i1d10.1007_s00181-021-02143-y.html
   My bibliography  Save this article

The connectedness between Hong Kong and China real estate markets: spillover effect and information transmission

Author

Listed:
  • I-Chun Tsai

    (National University of Kaohsiung)

Abstract

Frequently migration between Hong Kong (HK) and China can cause the real estate price standards of HK’s and China’s first-tier cities to resemble one another. This study adopts the real estate prices of HK and four major cities in China, namely Beijing, Shanghai, Shenzhen, and Guangzhou, from January 2001 to April 2019. The results reveal that for both long- and short-term returns, the HK real estate market is influenced by the Shanghai real estate market. The HK real estate market and the Shenzhen real estate market exhibit the most connectedness. This may be because of their geographic closeness; people are more likely to migrate between these two cities. The real estate market in Beijing exhibits the greatest informativeness. In the four cities, only the informativeness of Guangzhou City substantially lags behind that of HK. This study also discovers that in the relationship between those regional real estate markets, exchange rate and stock market returns are key factors. The connection between the housing markets of Beijing and Hong Kong is attributable to the foreign exchange market, whereas the connection between the housing markets of Hong Kong and other first-tier cities is attributable to the stock market. The change in exchange rate influences the volatility of Beijing’s real estate market. After this volatility is transmitted to HK, it influences the correlation between HK and Shanghai real estate markets as well as between HK and Shenzhen real estate markets.

Suggested Citation

  • I-Chun Tsai, 2022. "The connectedness between Hong Kong and China real estate markets: spillover effect and information transmission," Empirical Economics, Springer, vol. 63(1), pages 287-311, July.
  • Handle: RePEc:spr:empeco:v:63:y:2022:i:1:d:10.1007_s00181-021-02143-y
    DOI: 10.1007/s00181-021-02143-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-021-02143-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00181-021-02143-y?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. Eddie Chi-man Hui & Ivan Ng, 2009. "Price discovery of property markets in Shenzhen and Hong Kong," Construction Management and Economics, Taylor & Francis Journals, vol. 27(12), pages 1175-1196.
    2. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    3. Bodart, Vincent & Reding, Paul, 1999. "Exchange rate regime, volatility and international correlations on bond and stock markets," Journal of International Money and Finance, Elsevier, vol. 18(1), pages 133-151, January.
    4. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    5. LEUNG, K. Y. Charles & TANG, C. H. Edward, 2011. "Comparing two financial crises: the case of Hong Kong real estate markets," MPRA Paper 31562, University Library of Munich, Germany.
    6. Caporale, Guglielmo Maria & Hunter, John & Menla Ali, Faek, 2014. "On the linkages between stock prices and exchange rates: Evidence from the banking crisis of 2007–2010," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 87-103.
    7. Qin Xiao & Yunhua Liu, 2010. "The residential market of Hong Kong: rational or irrational?," Applied Economics, Taylor & Francis Journals, vol. 42(7), pages 923-933.
    8. Gong, Yunlong & Hu, Jinxing & Boelhouwer, Peter J., 2016. "Spatial interrelations of Chinese housing markets: Spatial causality, convergence and diffusion," Regional Science and Urban Economics, Elsevier, vol. 59(C), pages 103-117.
    9. Peter C. B. Phillips & Jun Yu, 2011. "Dating the timeline of financial bubbles during the subprime crisis," Quantitative Economics, Econometric Society, vol. 2(3), pages 455-491, November.
    10. Bekiros, Stelios, 2014. "Nonlinear causality testing with stepwise multivariate filtering: Evidence from stock and currency markets," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 336-348.
    11. Yongheng Deng & Eric Girardin & Roselyne Joyeux & Shuping Shi, 2017. "Did bubbles migrate from the stock to the housing market in China between 2005 and 2010?," Pacific Economic Review, Wiley Blackwell, vol. 22(3), pages 276-292, August.
    12. Francis X. Diebold & Kamil Yilmaz, 2013. "Measuring the Dynamics of Global Business Cycle Connectedness," PIER Working Paper Archive 13-070, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    13. Huo, Rui & Ahmed, Abdullahi D., 2017. "Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect," Economic Modelling, Elsevier, vol. 61(C), pages 260-272.
    14. Hong Miao & Sanjay Ramchander & Marc W. Simpson, 2011. "Return and Volatility Transmission in U.S. Housing Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 39(4), pages 701-741, December.
    15. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    16. Baklaci, Hasan Fehmi & Aydoğan, Berna & Yelkenci, Tezer, 2020. "Impact of stock market trading on currency market volatility spillovers," Research in International Business and Finance, Elsevier, vol. 52(C).
    17. Deng, Yongheng & Girardin, Eric & Joyeux, Roselyne, 2018. "Fundamentals and the volatility of real estate prices in China: A sequential modelling strategy," China Economic Review, Elsevier, vol. 48(C), pages 205-222.
    18. Gerlach-Kristen, Petra, 2009. "Business cycle and inflation synchronisation in Mainland China and Hong Kong," International Review of Economics & Finance, Elsevier, vol. 18(3), pages 404-418, June.
    19. 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.
    20. Yiu, Matthew S. & Yu, Jun & Jin, Lu, 2013. "Detecting bubbles in Hong Kong residential property market," Journal of Asian Economics, Elsevier, vol. 28(C), pages 115-124.
    21. Suk-Joong Kim & Fari Moshirian & Eliza Wu, 2018. "Evolution of International Stock and Bond Market Integration: Influence of the European Monetary Union," World Scientific Book Chapters, in: Information Spillovers and Market Integration in International Finance Empirical Analyses, chapter 12, pages 391-428, World Scientific Publishing Co. Pte. Ltd..
    22. Fan, Qingliang & Wang, Ting, 2017. "The impact of Shanghai–Hong Kong Stock Connect policy on A-H share price premium," Finance Research Letters, Elsevier, vol. 21(C), pages 222-227.
    23. Nikolaos Antonakakis & Ioannis Chatziantoniou & Christos Floros & David Gabauer, 2018. "The dynamic connectedness of UK regional property returns," Urban Studies, Urban Studies Journal Limited, vol. 55(14), pages 3110-3134, November.
    24. Rangan Gupta & Stephen Miller, 2012. "The Time-Series Properties of House Prices: A Case Study of the Southern California Market," The Journal of Real Estate Finance and Economics, Springer, vol. 44(3), pages 339-361, April.
    25. Liow, Kim Hiang & Huang, Yuting & Song, Jeonseop, 2019. "Relationship between the United States housing and stock markets: Some evidence from wavelet analysis," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    26. Qing He & Zongxin Qian & Zhe Fei & Terence Tai-Leung Chong, 2019. "Do speculative bubbles migrate in the Chinese stock market?," Empirical Economics, Springer, vol. 56(2), pages 735-754, February.
    27. Juan Huang & Geoffrey Qiping Shen, 2017. "Residential housing bubbles in Hong Kong: identification and explanation based on GSADF test and dynamic probit model," Journal of Property Research, Taylor & Francis Journals, vol. 34(2), pages 108-128, April.
    28. Xintong Yang & Yu Zhang & Qi Li, 2021. "The role of price spillovers: what is different in China," Empirical Economics, Springer, vol. 60(1), pages 459-485, January.
    29. Paul De Grauwe & Zhaoyong Zhang & Kin-Yip Ho & Yanlin Shi & Zhaoyong Zhang, 2016. "It takes two to tango: A regime-switching analysis of the correlation dynamics between the mainland Chinese and Hong Kong stock markets," Scottish Journal of Political Economy, Scottish Economic Society, vol. 63(1), pages 41-65, February.
    30. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    Full references (including those not matched with items on IDEAS)

    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. Nguyen, Thi Thu Ha & Naeem, Muhammad Abubakr & Balli, Faruk & Balli, Hatice Ozer & Syed, Iqbal, 2021. "Information transmission between oil and housing markets," Energy Economics, Elsevier, vol. 95(C).
    2. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2021. "A regional decomposition of US housing prices and volume: market dynamics and Portfolio diversification," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 66(2), pages 279-307, April.
    3. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.
    4. Gabauer, David & Gupta, Rangan & Marfatia, Hardik A. & Miller, Stephen M., 2024. "Estimating U.S. housing price network connectedness: Evidence from dynamic Elastic Net, Lasso, and ridge vector autoregressive models," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 349-362.
    5. He, Xie & Hamori, Shigeyuki, 2021. "Is volatility spillover enough for investor decisions? A new viewpoint from higher moments," Journal of International Money and Finance, Elsevier, vol. 116(C).
    6. So Jung Hwang & Hyunduk Suh, 2021. "Analyzing Dynamic Connectedness in Korean Housing Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(2), pages 591-609, January.
    7. Zhang, Yulian & Hamori, Shigeyuki, 2022. "A connectedness analysis among BRICS’s geopolitical risks and the US macroeconomy," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 182-203.
    8. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2019. "A Regional Decomposition of US Housing Prices and Volume: Market Dynamics and Economic Diversification Opportunities," Working Papers in Economics & Finance 2019-06, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    9. Tsai, I-Chun, 2022. "Changes in social behavior and impacts of the COVID-19 pandemic on regional housing markets: Independence and risk," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    10. Mustafa Çakır, 2023. "Regional inflation spillovers in Turkey," Economic Change and Restructuring, Springer, vol. 56(2), pages 959-980, April.
    11. Mishra, Aswini Kumar & Ghate, Kshitish, 2022. "Dynamic connectedness in non-ferrous commodity markets: Evidence from India using TVP-VAR and DCC-GARCH approaches," Resources Policy, Elsevier, vol. 76(C).
    12. Uluceviz, Erhan & Yilmaz, Kamil, 2021. "Measuring real–financial connectedness in the U.S. economy," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    13. Erdenebat Bataa & Denise R.Osborn & Marianne Sensier, 2016. "China's Increasing Global Influence: Changes in International Growth Spillovers," Centre for Growth and Business Cycle Research Discussion Paper Series 221, Economics, The University of Manchester.
    14. Billah, Mabruk & Amar, Amine Ben & Balli, Faruk, 2023. "The extreme return connectedness between Sukuk and green bonds and their determinants and consequences for investors," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    15. James E. Payne & Xiaojin Sun, 2023. "Time‐varying connectedness of metropolitan housing markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(2), pages 470-502, March.
    16. Tihana ŠKRINJARIĆ & Lidija DEDI & Boško ŠEGO, 2021. "Return and Volatility Spillover between Stock Prices and Exchange Rates in Croatia: A Spillover Methodology Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 93-108, December.
    17. I-Chun Tsai & Che-Chun Lin, 2019. "Variations and Influences of Connectedness among US Housing Markets," International Real Estate Review, Global Social Science Institute, vol. 22(1), pages 27-58.
    18. repec:ire:issued:v:22:n:01:2019:p:27-59 is not listed on IDEAS
    19. Yang, Jian & Yu, Ziliang & Deng, Yongheng, 2018. "Housing price spillovers in China: A high-dimensional generalized VAR approach," Regional Science and Urban Economics, Elsevier, vol. 68(C), pages 98-114.
    20. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    21. Juncal Cunado & David Gabauer & Rangan Gupta, 2024. "Realized volatility spillovers between energy and metal markets: a time-varying connectedness approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-17, December.

    More about this item

    Keywords

    The HK real estate market; The China real estate market; Connectedness; Spillover effect; Information transmission;
    All these keywords.

    JEL classification:

    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

    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:spr:empeco:v:63:y:2022:i:1:d:10.1007_s00181-021-02143-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.