IDEAS home Printed from https://ideas.repec.org/a/wly/mgtdec/v42y2021i4p898-919.html
   My bibliography  Save this article

Urban agglomeration, housing price, and space–time spillover effect—Empirical evidences based on data from hundreds of cities in China

Author

Listed:
  • Feng Lan
  • Chengcai Jiao
  • Guoying Deng
  • Huili Da

Abstract

Taking 100 cities in China, this paper adopts gravity model, time–space model, and generalized impulse response function to probe into the spillover effect of housing price against the backdrop of spatial agglomeration. This study found that the degree of spillover effect between cities is correlated to economic foundations and grade of cities in general. When economic foundations and grade of a city are basically the same, the spillover effect presents a law of weakening with the increase of distance. In urban agglomerations with higher degree of networked structure, the features are the all‐around spillover effect of central city.

Suggested Citation

  • Feng Lan & Chengcai Jiao & Guoying Deng & Huili Da, 2021. "Urban agglomeration, housing price, and space–time spillover effect—Empirical evidences based on data from hundreds of cities in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(4), pages 898-919, June.
  • Handle: RePEc:wly:mgtdec:v:42:y:2021:i:4:p:898-919
    DOI: 10.1002/mde.3281
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/mde.3281
    Download Restriction: no

    File URL: https://libkey.io/10.1002/mde.3281?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
    ---><---

    References listed on IDEAS

    as
    1. Lennart Berg, 2002. "Prices on the second-hand market for Swedish family houses: correlation, causation and determinants," European Journal of Housing Policy, Taylor and Francis Journals, vol. 2(1), pages 1-24.
    2. Carol Alexander & Michael Barrow, 1994. "Seasonality and Cointegration of Regional House Prices in the UK," Urban Studies, Urban Studies Journal Limited, vol. 31(10), pages 1667-1689, December.
    3. Holly, Sean & Pesaran, M. Hashem & Yamagata, Takashi, 2010. "A spatio-temporal model of house prices in the USA," Journal of Econometrics, Elsevier, vol. 158(1), pages 160-173, September.
    4. Wu, Jing & Gyourko, Joseph & Deng, Yongheng, 2016. "Evaluating the risk of Chinese housing markets: What we know and what we need to know," China Economic Review, Elsevier, vol. 39(C), pages 91-114.
    5. Le Ma & Chunlu Liu, 2013. "A panel error correction approach to explore spatial correlation patterns of the dominant housing market in Australian capital cities," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 6(4), pages 405-421, September.
    6. Muellbauer, John & Murphy, Anthony, 1997. "Booms and Busts in the UK Housing Market," Economic Journal, Royal Economic Society, vol. 107(445), pages 1701-1727, November.
    7. Song Shi & Martin Young & Bob Hargreaves, 2009. "The ripple effect of local house price movements in New Zealand," Journal of Property Research, Taylor & Francis Journals, vol. 26(1), pages 1-24, April.
    8. 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.
    9. Todd Kuethe & Valerien Pede, 2011. "Regional Housing Price Cycles: A Spatio-temporal Analysis Using US State-level Data," Regional Studies, Taylor & Francis Journals, vol. 45(5), pages 563-574.
    10. Sing, Tien-Foo & Tsai, I-Chun & Chen, Ming-Chi, 2006. "Price dynamics in public and private housing markets in Singapore," Journal of Housing Economics, Elsevier, vol. 15(4), pages 305-320, December.
    11. Cohen, Jeffrey P. & Ioannides, Yannis M. & (Wirathip) Thanapisitikul, Win, 2016. "Spatial effects and house price dynamics in the USA," Journal of Housing Economics, Elsevier, vol. 31(C), pages 1-13.
    12. 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.
    13. Mehmet Balcilar & Abebe Beyene & Rangan Gupta & Monaheng Seleteng, 2013. "‘Ripple’ Effects in South African House Prices," Urban Studies, Urban Studies Journal Limited, vol. 50(5), pages 876-894, April.
    14. Tsai, I-Chun, 2014. "Ripple effect in house prices and trading volume in the UK housing market: New viewpoint and evidence," Economic Modelling, Elsevier, vol. 40(C), pages 68-75.
    15. Roehner, Bertrand M., 1999. "Spatial analysis of real estate price bubbles: Paris, 1984-1993," Regional Science and Urban Economics, Elsevier, vol. 29(1), pages 73-88, January.
    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. Qiguang An & Lin Zheng & Mu Yang, 2024. "Spatiotemporal Heterogeneities in the Impact of Chinese Digital Economy Development on Carbon Emissions," Sustainability, MDPI, vol. 16(7), pages 1-19, March.
    2. Zhou, Yulin & Lan, Feng & Zhou, Tao, 2021. "An experience-based mining approach to supporting urban renewal mode decisions under a multi-stakeholder environment in China," Land Use Policy, Elsevier, vol. 106(C).
    3. Leeyoung Kim & Wonseok Seo, 2021. "Micro-Analysis of Price Spillover Effect among Regional Housing Submarkets in Korea: Evidence from the Seoul Metropolitan Area," Land, MDPI, vol. 10(8), pages 1-21, August.
    4. Huang, Daohan & Li, Guijun & Chang, Yuan & Sun, Chengshuang, 2023. "Water, energy, and food nexus efficiency in China: A provincial assessment using a three-stage data envelopment analysis model," Energy, Elsevier, vol. 263(PE).
    5. Chen, Ming & Chen, Chen, 2023. "Financial constraints alleviation: Why does state-owned share reduction in China promote firm performance?," Finance Research Letters, Elsevier, vol. 55(PA).

    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. Huayi Yu, 2015. "The spillovers and heterogeneous responses of housing prices: a GVAR analysis of China's 35 major cities," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 20(4), pages 535-558, October.
    2. Cheng-Wen Lee & Shu-Hen Chiang & Zhong-Qin Wen, 2023. "Pursuing the Sustainability of Real Estate Market: The Case of Chinese Land Resources Diversification," Sustainability, MDPI, vol. 15(7), pages 1-19, March.
    3. 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.
    4. 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.
    5. Cynthia Fan Yang, 2021. "Common factors and spatial dependence: an application to US house prices," Econometric Reviews, Taylor & Francis Journals, vol. 40(1), pages 14-50, January.
    6. Teye, Alfred Larm & Ahelegbey, Daniel Felix, 2017. "Detecting spatial and temporal house price diffusion in the Netherlands: A Bayesian network approach," Regional Science and Urban Economics, Elsevier, vol. 65(C), pages 56-64.
    7. Leeyoung Kim & Wonseok Seo, 2021. "Micro-Analysis of Price Spillover Effect among Regional Housing Submarkets in Korea: Evidence from the Seoul Metropolitan Area," Land, MDPI, vol. 10(8), pages 1-21, August.
    8. Chunping Liu & Zhirong Ou, 2022. "Revisiting the determinants of house prices in China’s megacities: Cross‐sectional heterogeneity, interdependencies and spillovers," Manchester School, University of Manchester, vol. 90(3), pages 255-277, June.
    9. I-Chun Tsai, 2015. "Spillover Effect between the Regional and the National Housing Markets in the UK," Regional Studies, Taylor & Francis Journals, vol. 49(12), pages 1957-1976, December.
    10. 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.
    11. Cipollini, Andrea & Parla, Fabio, 2020. "Housing market shocks in italy: A GVAR approach," Journal of Housing Economics, Elsevier, vol. 50(C).
    12. 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.
    13. 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.
    14. Alfred Larm Teye & Daniel Felix Ahelegbey, 2017. "Spatial and Temporal House Price Diffusion in the Netherlands: A Bayesian Network Approach," ERES eres2017_337, European Real Estate Society (ERES).
    15. Giorgio Canarella & Stephen Miller & Stephen Pollard, 2012. "Unit Roots and Structural Change," Urban Studies, Urban Studies Journal Limited, vol. 49(4), pages 757-776, March.
    16. 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.
    17. Williams, Joseph, 2018. "Housing markets with endogenous search: Theory and implications," Journal of Urban Economics, Elsevier, vol. 105(C), pages 107-120.
    18. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2021. "Time-varying inter-urban housing price spillovers in China: Causes and consequences," Journal of Asian Economics, Elsevier, vol. 77(C).
    19. Lu Liu & Linda Qiu & Yuanyuan Yang, 2022. "Urban housing prices within a core urban agglomeration in China," SN Business & Economics, Springer, vol. 2(11), pages 1-38, November.
    20. 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.

    More about this item

    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:wly:mgtdec:v:42:y:2021:i:4:p:898-919. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/7976 .

    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.