IDEAS home Printed from https://ideas.repec.org/a/cup/nierev/v223y2013ipr39-r48_13.html

Real-Time Warning Signs of Emerging and Collapsing Chinese House Price Bubbles

Author

Listed:
  • Chen, Xi
  • Funke, Michael

Abstract

The recent increase in Chinese house prices has led to concerns that China is vulnerable to asset price shocks. In this paper, we apply recently developed recursive unit root tests to spot the beginning and the end of potential speculative bubbles in Chinese house price cycles. Overall, we find that except for 2009–10 actual house prices are not significantly disconnected from fundamentals. Thus, the evidence for speculative house price bubbles in China is in general weak.

Suggested Citation

  • Chen, Xi & Funke, Michael, 2013. "Real-Time Warning Signs of Emerging and Collapsing Chinese House Price Bubbles," National Institute Economic Review, National Institute of Economic and Social Research, vol. 223, pages 39-48, February.
    • Handle: RePEc:cup:nierev:v:223:y:2013:i::p:r39-r48_13
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S0027950100000818/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Renhe Liu & Eddie Chi-man Hui & Jiaqi Lv & Yi Chen, 2017. "What Drives Housing Markets: Fundamentals or Bubbles?," The Journal of Real Estate Finance and Economics, Springer, vol. 55(4), pages 395-415, November.
    2. Tie-Ying Liu & Hsu-Ling Chang & Chi-Wei Su & Xu-Zhao Jiang, 2016. "China's housing bubble burst?," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 24(2), pages 361-389, April.
    3. Francisco Blasques & Siem Jan Koopman & Gabriele Mingoli, 2023. "Observation-Driven filters for Time- Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics," Tinbergen Institute Discussion Papers 23-065/III, Tinbergen Institute, revised 01 Mar 2024.
    4. Peter C.B. Phillips & Shu-Ping Shi, 2014. "Financial Bubble Implosion," Cowles Foundation Discussion Papers 1967, Cowles Foundation for Research in Economics, Yale University.
    5. Blasques, Francisco & Koopman, Siem Jan & Nientker, Marc, 2022. "A time-varying parameter model for local explosions," Journal of Econometrics, Elsevier, vol. 227(1), pages 65-84.
    6. Kennedy, Gerard & O'Brien, Eoin & Woods, Maria, 2016. "Assessing the sustainability of Irish residential property prices: 1980Q1-2016Q2," Economic Letters 11/EL/16, Central Bank of Ireland.
    7. Yang Hu & Les Oxley, 2018. "Bubbles in US regional house prices: evidence from house price–income ratios at the State level," Applied Economics, Taylor & Francis Journals, vol. 50(29), pages 3196-3229, June.
    8. Wen-Yi Chen & Yia-Wun Liang & Yu-Hui Lin, 2016. "Is the United States in the middle of a healthcare bubble?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(1), pages 99-111, January.
    9. Gabriele Mingoli, 2024. "Modeling Common Bubbles: A Mixed Causal Non-Causal Dynamic Factor Model," Tinbergen Institute Discussion Papers 24-072/III, Tinbergen Institute.
    10. ZEREN, Feyyaz & ERGÜZEL, Oylum Şehvez, 2015. "Testing For Bubbles In The Housing Market: Further Evidence From Turkey," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(1), pages 40-52.
    11. Marcelo M. de Oliveira & Alexandre C. L. Almeida, 2014. "Testing for rational speculative bubbles in the Brazilian residential real-estate market," Papers 1401.7615, arXiv.org.
    12. Iris Claus & Les Oxley & Jie Chen & Xuehui Han, 2014. "The Evolution Of The Housing Market And Its Socioeconomic Impacts In The Post-Reform People'S Republic Of China: A Survey Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 28(4), pages 652-670, September.

    More about this item

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

    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:cup:nierev:v:223:y:2013:i::p:r39-r48_13. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Kirk Stebbing (email available below). General contact details of provider: https://edirc.repec.org/data/niesruk.html .

    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.