IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i6p890-d1418157.html
   My bibliography  Save this article

Research on the Risk Spillover among the Real Economy, Real Estate Market, and Financial System: Evidence from China

Author

Listed:
  • Yubin Huangfu

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    National Land Science Center, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Haibo Yu

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    National Land Science Center, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Zuoji Dong

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    National Land Science Center, University of Chinese Academy of Sciences, Beijing 100190, China)

  • Yingman Wang

    (School of Finance, Zhongnan University of Economics and Law, Wuhan 430073, China)

Abstract

Amidst escalating global policy uncertainties and the painful transformation phase of the Chinese economy, studying the time-varying characteristics of risk spillover among the real economy, real estate market, and financial system holds substantial practical relevance for preventing and resolving significant systemic risks. This paper employs the TVP-VAR-DY model, selects indices from the real sectors to construct a risk spillover index for the real economy, and incorporates indices from the real estate and financial sectors to develop a trivariate SV-TVP-VAR model for empirically analyzing the time-varying nature of risk spillover relationships among these variables. This study reveals that risk spillover among different sectors of the real economy exhibits asymmetry and volatility, with the industrial sector experiencing the highest degree of risk spillover. The prosperity of the real estate market consistently aligns with that of the financial system; however, shocks during periods of risk accumulation in the real estate market significantly amplify risks in the real economy. The financial system serves the real economy, which suffers lesser impacts. Nonetheless, post-2008, the financial system’s support for the real estate market has gradually diminished. Crises exacerbate the extent of risk spillover, but the causative factors and socio-economic context create heterogeneity in fluctuations. Based on these findings, in response to the current real estate shock, the Chinese government should discuss the real economy, the real estate industry, and the financial system within the same research framework. Policies should primarily focus on fiscal measures to promote the recovery of the real economy more rapidly. Additionally, by allowing local governments to implement tailored policies based on local conditions, potential homebuying demand has been effectively stimulated.

Suggested Citation

  • Yubin Huangfu & Haibo Yu & Zuoji Dong & Yingman Wang, 2024. "Research on the Risk Spillover among the Real Economy, Real Estate Market, and Financial System: Evidence from China," Land, MDPI, vol. 13(6), pages 1-26, June.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:6:p:890-:d:1418157
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/6/890/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/13/6/890/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    3. Thomas Chaney & David Sraer & David Thesmar, 2012. "The Collateral Channel: How Real Estate Shocks Affect Corporate Investment," American Economic Review, American Economic Association, vol. 102(6), pages 2381-2409, October.
    4. Athari, Seyed Alireza & Kondoz, Mehmet & Kirikkaleli, Dervis, 2021. "Dependency between sovereign credit ratings and economic risk: Insight from Balkan countries," Journal of Economics and Business, Elsevier, vol. 116(C).
    5. Yi Huang & Marco Pagano & Ugo Panizza, 2020. "Local Crowding‐Out in China," Journal of Finance, American Finance Association, vol. 75(6), pages 2855-2898, December.
    6. Jacob Kleinow & Tobias Nell, 2015. "Determinants of systemically important banks: the case of Europe," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 7(4), pages 446-476, November.
    7. Korobilis, D & Yilmaz, K, 2018. "Measuring Dynamic Connectedness with Large Bayesian VAR Models," Essex Finance Centre Working Papers 20937, University of Essex, Essex Business School.
    8. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    9. Asgharian, Hossein & Nossman, Marcus, 2011. "Risk contagion among international stock markets," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 22-38, February.
    10. Glawe, Linda & Wagner, Helmut, 2020. "China in the middle-income trap?," China Economic Review, Elsevier, vol. 60(C).
    11. Kondoz, Mehmet & Kirikkaleli, Dervis & Athari, Seyed Alireza, 2021. "Time-frequency dependencies of financial and economic risks in South American countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 170-181.
    12. Vicente Cuñat & Dragana Cvijanović & Kathy Yuan, 2018. "Within-Bank Spillovers of Real Estate Shocks," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 7(2), pages 157-193.
    13. Peter Midmore & Max Munday & Annette Roberts, 2006. "Assessing industry linkages using regional input-output tables," Regional Studies, Taylor & Francis Journals, vol. 40(3), pages 329-343.
    14. repec:hal:spmain:info:hdl:2441/75koqefued8i7pihbrl9u84p4u is not listed on IDEAS
    15. Nelson Marconi & Igor L. Rocha & Guilherme R. Magacho, 2016. "Sectoral capabilities and productive structure: An input-output analysis of the key sectors of the Brazilian economy," Brazilian Journal of Political Economy, Center of Political Economy, vol. 36(3), pages 470-492.
    16. Chiu, Wan-Chien & Peña, Juan Ignacio & Wang, Chih-Wei, 2015. "Industry characteristics and financial risk contagion," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 411-427.
    17. Wenlang Zhang & Gaofeng Han & Steven Chan, 2014. "How Strong are the Linkages between Real Estate and Other Sectors in China?," Working Papers 112014, Hong Kong Institute for Monetary Research.
    18. Gkillas, Konstantinos & Tsagkanos, Athanasios & Vortelinos, Dimitrios I., 2019. "Integration and risk contagion in financial crises: Evidence from international stock markets," Journal of Business Research, Elsevier, vol. 104(C), pages 350-365.
    19. Silva, Thiago Christiano & da Silva, Michel Alexandre & Tabak, Benjamin Miranda, 2017. "Systemic risk in financial systems: A feedback approach," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 97-120.
    20. Mirko Titze & Matthias Brachert & Alexander Kubis, 2011. "The Identification of Regional Industrial Clusters Using Qualitative Input-Output Analysis (QIOA)," Regional Studies, Taylor & Francis Journals, vol. 45(1), pages 89-102.
    21. Kenneth Rogoff & Yuanchen Yang, 2021. "Has China's Housing Production Peaked?," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(1), pages 1-31, January.
    22. Sun, Tao, 2010. "Identifying Vulnerabilities in Systemically Important Financial Institutions in a Macro-Financial Linkages Framework," The Journal of Economic Asymmetries, Elsevier, vol. 7(2), pages 77-103.
    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. Yousaf, Imran & Jareño, Francisco & Tolentino, Marta, 2023. "Connectedness between Defi assets and equity markets during COVID-19: A sector analysis," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    2. Feng, Huiqun & Zhang, Jun & Guo, Na, 2023. "Time-varying linkages between energy and stock markets: Dynamic spillovers and driving factors," International Review of Financial Analysis, Elsevier, vol. 89(C).
    3. Chatziantoniou, Ioannis & Gabauer, David & Stenfors, Alexis, 2020. "From CIP-deviations to a market for risk premia: A dynamic investigation of cross-currency basis swaps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 69(C).
    4. David Gabauer & Sowmya Subramaniam & Rangan Gupta, 2022. "On the transmission mechanism of Asia‐Pacific yield curve characteristics," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 473-488, January.
    5. Gabauer, David & Gupta, Rangan, 2020. "Spillovers across macroeconomic, financial and real estate uncertainties: A time-varying approach," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 167-173.
    6. Mahdi Ghaemi Asl & Oluwasegun B. Adekoya & Muhammad Mahdi Rashidi, 2023. "Quantiles dependence and dynamic connectedness between distributed ledger technology and sectoral stocks: enhancing the supply chain and investment decisions with digital platforms," Annals of Operations Research, Springer, vol. 327(1), pages 435-464, August.
    7. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan, 2019. "International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression," International Review of Financial Analysis, Elsevier, vol. 65(C).
    8. Papież, Monika & Rubaszek, Michał & Szafranek, Karol & Śmiech, Sławomir, 2022. "Are European natural gas markets connected? A time-varying spillovers analysis," Resources Policy, Elsevier, vol. 79(C).
    9. Jia, Yanjing & Dong, Zhiliang, 2024. "Characteristics and influencing factors of risk spillover effects across clean energy stock prices: A comparative analysis during four periods of the COVID-19 pandemic," Energy Economics, Elsevier, vol. 135(C).
    10. Alexakis, Christos & Kenourgios, Dimitris & Pappas, Vasileios & Petropoulou, Athina, 2021. "From dotcom to Covid-19: A convergence analysis of Islamic investments," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    11. John Cotter & Mark Hallam & Kamil Yilmaz, 2017. "Mixed-Frequency Macro-Financial Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1704, Koc University-TUSIAD Economic Research Forum.
    12. Umar, Zaghum & Manel, Youssef & Riaz, Yasir & Gubareva, Mariya, 2021. "Return and volatility transmission between emerging markets and US debt throughout the pandemic crisis," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    13. Yousaf, Imran & Yarovaya, Larisa, 2022. "Static and dynamic connectedness between NFTs, Defi and other assets: Portfolio implication," Global Finance Journal, Elsevier, vol. 53(C).
    14. Jiasha Fu & Hui Qiao, 2022. "The Time-Varying Connectedness Between China’s Crude Oil Futures and International Oil Markets: A Return and Volatility Spillover Analysis," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 341-376, December.
    15. Chatziantoniou, Ioannis & Gabauer, David, 2021. "EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 1-14.
    16. Boeckelmann Lukas & Stalla-Bourdillon Arthur, 2021. "Structural Estimation of Time-Varying Spillovers: An Application to International Credit Risk Transmission," Working papers 798, Banque de France.
    17. Chen, Zhenlong & Zheng, Changmei & Hao, Xiaozhen, 2022. "Volatility spillover effect between internet finance and banks," Journal of Business Research, Elsevier, vol. 141(C), pages 512-519.
    18. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    19. Shang, Jin & Hamori, Shigeyuki, 2024. "Quantile time-frequency connectedness analysis between crude oil, gold, financial markets, and macroeconomic indicators: Evidence from the US and EU," Energy Economics, Elsevier, vol. 132(C).
    20. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).

    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:gam:jlands:v:13:y:2024:i:6:p:890-:d:1418157. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.