IDEAS home Printed from https://ideas.repec.org/a/eee/chieco/v74y2022ics1043951x2200061x.html
   My bibliography  Save this article

A closer look at Chinese housing market: Measuring intra-city submarket connectedness in Shanghai and Guangzhou

Author

Listed:
  • Li, Qiang
  • Nong, Huifu

Abstract

In this paper, we study intra-city connections of housing submarkets, using data from two systemically important cities in China, Shanghai and Guangzhou. Chinese cities that underwent significant spatial and population growth in recent years provide an ideal testing ground for theories of urban spatial growth and the filtering models of housing market. By employing variance decompositions from vector autoregression models, we characterize three types of market connectedness. We find that price shocks mostly originate from the central areas and transmit to the suburban areas in both cities. Additionally, shocks usually run from new sale to resale markets, supporting the basic premise of filtering models. In both cities, trading volume shocks generally lead price shocks both within and across areas.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:chieco:v:74:y:2022:i:c:s1043951x2200061x
    DOI: 10.1016/j.chieco.2022.101803
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1043951X2200061X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chieco.2022.101803?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. Jozef Barunik & Mattia Bevilacqua & Radu Tunaru, 2022. "Asymmetric Network Connectedness of Fears," The Review of Economics and Statistics, MIT Press, vol. 104(6), pages 1304-1316, November.
    2. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    3. 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.
    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. 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.
    6. Stefan Klößner & Sven Wagner, 2014. "Exploring All Var Orderings For Calculating Spillovers? Yes, We Can!—A Note On Diebold And Yilmaz (2009)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 172-179, January.
    7. Deng, Xiangzheng & Huang, Jikun & Rozelle, Scott & Uchida, Emi, 2008. "Growth, population and industrialization, and urban land expansion of China," Journal of Urban Economics, Elsevier, vol. 63(1), pages 96-115, January.
    8. Agarwal, Sumit & Li, Keyang & Qin, Yu & Wu, Jing & Yan, Jubo, 2020. "Tax evasion, capital gains taxes, and the housing market," Journal of Public Economics, Elsevier, vol. 188(C).
    9. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    10. Lichtenberg, Erik & Ding, Chengri, 2009. "Local officials as land developers: Urban spatial expansion in China," Journal of Urban Economics, Elsevier, vol. 66(1), pages 57-64, July.
    11. Lee, Hahn Shik & Lee, Woo Suk, 2019. "Cross-regional connectedness in the Korean housing market," Journal of Housing Economics, Elsevier, vol. 46(C).
    12. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    13. Robert Novy‐Marx, 2009. "Hot and Cold Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 37(1), pages 1-22, March.
    14. Goodman, Allen C., 1978. "Hedonic prices, price indices and housing markets," Journal of Urban Economics, Elsevier, vol. 5(4), pages 471-484, October.
    15. David Genesove & Christopher Mayer, 2001. "Loss Aversion and Seller Behavior: Evidence from the Housing Market," The Quarterly Journal of Economics, Oxford University Press, vol. 116(4), pages 1233-1260.
    16. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    17. Capozza, Dennis R. & Helsley, Robert W., 1990. "The stochastic city," Journal of Urban Economics, Elsevier, vol. 28(2), pages 187-203, September.
    18. Sweeney, James L., 1974. "A commodity hierarchy model of the rental housing market," Journal of Urban Economics, Elsevier, vol. 1(3), pages 288-323, July.
    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. Richard K. Green & Stephen Malpezzi & Stephen K. Mayo, 2005. "Metropolitan-Specific Estimates of the Price Elasticity of Supply of Housing, and Their Sources," American Economic Review, American Economic Association, vol. 95(2), pages 334-339, May.
    21. Straszheim, Mahlon R, 1974. "Hedonic Estimation of Housing Market Prices: A Further Comment," The Review of Economics and Statistics, MIT Press, vol. 56(3), pages 404-406, August.
    22. Jan K. Brueckner & Stuart S. Rosenthal, 2009. "Gentrification and Neighborhood Housing Cycles: Will America's Future Downtowns Be Rich?," The Review of Economics and Statistics, MIT Press, vol. 91(4), pages 725-743, November.
    23. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    24. Anglin, Paul M. & Dale-Johnson, David & Gao, Yanmin & Zhu, Guozhong, 2014. "Patterns of growth in Chinese cities: Implications of the land lease," Journal of Urban Economics, Elsevier, vol. 83(C), pages 87-107.
    25. Liang Peng & Thomas Thibodeau, 2013. "Risk Segmentation of American Homes: Evidence from Denver," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 41(3), pages 569-599, September.
    26. Jon Faust, 1998. "The robustness of identified VAR conclusions about money," International Finance Discussion Papers 610, Board of Governors of the Federal Reserve System (U.S.).
    27. 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.
    28. Hsu, Nan-Jung & Hung, Hung-Lin & Chang, Ya-Mei, 2008. "Subset selection for vector autoregressive processes using Lasso," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3645-3657, March.
    29. Anas, Alex, 1978. "Dynamics of urban residential growth," Journal of Urban Economics, Elsevier, vol. 5(1), pages 66-87, January.
    30. Braid, Ralph M., 2001. "Spatial Growth and Redevelopment with Perfect Foresight and Durable Housing," Journal of Urban Economics, Elsevier, vol. 49(3), pages 425-452, May.
    31. Capozza, Dennis R. & Helsley, Robert W., 1989. "The fundamentals of land prices and urban growth," Journal of Urban Economics, Elsevier, vol. 26(3), pages 295-306, November.
    32. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    33. 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.
    34. 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.
    35. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
    36. Kock, Anders Bredahl & Callot, Laurent, 2015. "Oracle inequalities for high dimensional vector autoregressions," Journal of Econometrics, Elsevier, vol. 186(2), pages 325-344.
    37. Wheaton, William C, 1990. "Vacancy, Search, and Prices in a Housing Market Matching Model," Journal of Political Economy, University of Chicago Press, vol. 98(6), pages 1270-1292, December.
    38. Chien-Fu Chen & Shu-hen Chiang, 2020. "Time-varying spillovers among first-tier housing markets in China," Urban Studies, Urban Studies Journal Limited, vol. 57(4), pages 844-864, March.
    39. Mayer, Christopher J. & Somerville, C. Tsuriel, 2000. "Residential Construction: Using the Urban Growth Model to Estimate Housing Supply," Journal of Urban Economics, Elsevier, vol. 48(1), pages 85-109, July.
    40. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    41. Rosenthal, Stuart S., 2008. "Old homes, externalities, and poor neighborhoods. A model of urban decline and renewal," Journal of Urban Economics, Elsevier, vol. 63(3), pages 816-840, May.
    42. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    43. 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.
    44. Jeremy C. Stein, 1995. "Prices and Trading Volume in the Housing Market: A Model with Down-Payment Effects," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 379-406.
    45. Weicher, John C. & Thibodeau, Thomas G., 1988. "Filtering and housing markets: An empirical analysis," Journal of Urban Economics, Elsevier, vol. 23(1), pages 21-40, January.
    46. Wang, Xiaodan & Li, Keyang & Wu, Jing, 2020. "House price index based on online listing information: The case of China," Journal of Housing Economics, Elsevier, vol. 50(C).
    47. Stuart S. Rosenthal, 2014. "Are Private Markets and Filtering a Viable Source of Low-Income Housing? Estimates from a "Repeat Income" Model," American Economic Review, American Economic Association, vol. 104(2), pages 687-706, February.
    48. 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.
    49. Wheaton, William C., 1982. "Urban residential growth under perfect foresight," Journal of Urban Economics, Elsevier, vol. 12(1), pages 1-21, July.
    50. Arnott, Richard J & Lewis, Frank D, 1979. "The Transition of Land to Urban Use," Journal of Political Economy, University of Chicago Press, vol. 87(1), pages 161-169, February.
    51. Lok Ho & Yue Ma & Donald Haurin, 2008. "Domino Effects Within a Housing Market: The Transmission of House Price Changes Across Quality Tiers," The Journal of Real Estate Finance and Economics, Springer, vol. 37(4), pages 299-316, November.
    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. Nong, Huifu & Liu, Hongxiao, 2023. "Measuring the frequency and quantile connectedness between policy categories and global oil price," Resources Policy, Elsevier, vol. 83(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. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    2. Jalloul, Maya & Miescu, Mirela, 2023. "Equity market connectedness across regimes of geopolitical risks: Historical evidence and theory," Journal of International Money and Finance, Elsevier, vol. 137(C).
    3. Fengler, Matthias R. & Gisler, Katja I.M., 2015. "A variance spillover analysis without covariances: What do we miss?," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 174-195.
    4. Wu, Fei & Zhang, Dayong & Zhang, Zhiwei, 2019. "Connectedness and risk spillovers in China’s stock market: A sectoral analysis," Economic Systems, Elsevier, vol. 43(3).
    5. Wiesen, Thomas F.P. & Beaumont, Paul M. & Norrbin, Stefan C. & Srivastava, Anuj, 2018. "Are generalized spillover indices overstating connectedness?," Economics Letters, Elsevier, vol. 173(C), pages 131-134.
    6. Duranton, Gilles & Puga, Diego, 2015. "Urban Land Use," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 467-560, Elsevier.
    7. Shi Chen & Wolfgang Karl Hardle & Brenda L'opez Cabrera, 2020. "Regularization Approach for Network Modeling of German Power Derivative Market," Papers 2009.09739, arXiv.org.
    8. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    9. David Gabauer, 2020. "Volatility impulse response analysis for DCC‐GARCH models: The role of volatility transmission mechanisms," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 788-796, August.
    10. Chiang, Shu-hen & Chen, Chien-Fu, 2022. "From systematic to systemic risk among G7 members: Do the stock or real estate markets matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    11. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    12. Pagnottoni, Paolo & Spelta, Alessandro, 2023. "The motifs of risk transmission in multivariate time series: Application to commodity prices," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    13. Golitsis, Petros & Gkasis, Pavlos & Bellos, Sotirios K., 2022. "Dynamic spillovers and linkages between gold, crude oil, S&P 500, and other economic and financial variables. Evidence from the USA," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    14. Alexis Stenfors & Lilian Muchimba, 2023. "The Transmission Mechanism of Stress in the International Banking System," Working Papers in Economics & Finance 2023-03, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    15. Laura Liu & Christian Matthes & Katerina Petrova, 2022. "Monetary Policy Across Space and Time," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 37-64, Emerald Group Publishing Limited.
    16. David E. Allen & Michael McAleer & Robert Powell & Abhay K. Singh, 2017. "Volatility spillover and multivariate volatility impulse response analysis of GFC news events," Applied Economics, Taylor & Francis Journals, vol. 49(33), pages 3246-3262, July.
    17. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    18. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
    19. Thomas F. P. Wiesen & Todd Gabe & Lakshya Bharadwaj, 2023. "Econometric connectedness as a measure of urban influence: evidence from Maine," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-16, December.
    20. Yu Chen & Jie Hu & Weiping Zhang, 2020. "Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 78-100, November.

    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:chieco:v:74:y:2022:i:c:s1043951x2200061x. 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/chieco .

    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.