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Spatial and Temporal House Price Diffusion in the Netherlands: A Bayesian Network Approach

Author

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  • Alfred Larm Teye
  • Daniel Felix Ahelegbey

Abstract

Following the 2007-08 Global Financial Crisis, there has been a growing research interest on the spatial interrelationships between house prices in many countries. This paper examines the spatio-temporal relationship between house prices in the twelve provinces of the Netherlands using a recently proposed econometric modelling technique called the Bayesian Graphical Vector Autoregression (BG-VAR). This network approach is suitable for analysing the complex spatial interactions between house prices. It enables a data-driven identification of the most dominant provinces where temporal house price shocks may largely diffuse through the housing market. Using temporal house price volatilities for owner-occupied dwellings from 1995Q1 to 2016Q1, the results show evidence of temporal dependence and house price diffusion patterns in distinct sub-periods from different provincial housing sub-markets in the Netherlands. In particular, the results indicate that Noord-Holland was most predominant from 1995Q1 to 2005Q2, while Drenthe became most central in the period 2005Q3–2016Q1

Suggested Citation

  • 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).
  • Handle: RePEc:arz:wpaper:eres2017_337
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    References listed on IDEAS

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    1. 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.
    2. Mark J. Holmes & Arthur Grimes, 2008. "Is There Long-run Convergence among Regional House Prices in the UK?," Urban Studies, Urban Studies Journal Limited, vol. 45(8), pages 1531-1544, July.
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    5. 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.
    6. 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.
    7. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2010. "Unit Roots and Structural Change: An Application to US House-Price Indices," Working papers 2010-04, University of Connecticut, Department of Economics, revised Dec 2010.
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    Citations

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    Cited by:

    1. 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).
    2. Enwei Zhu & Jing Wu & Hongyu Liu & Xindian Li, 2022. "Within‐City Spatial Distribution, Heterogeneity and Diffusion of House Price: Evidence from a Spatiotemporal Index for Beijing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(3), pages 621-655, September.
    3. Robert J. Hill & Alicia N. Rambaldi, 2022. "Hedonic Models and House Price Index Numbers," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 413-444, Springer.
    4. Xiandeng Jiang & Le Chang & Yanlin Shi, 2023. "Housing price diffusions in mainland China: evidence from a spatially penalized graphical VAR model," Empirical Economics, Springer, vol. 64(2), pages 765-795, February.
    5. Weida Kuang & Qilin Wang, 2018. "Cultural similarities and housing market linkage: evidence from OECD countries," Frontiers of Business Research in China, Springer, vol. 12(1), pages 1-25, December.
    6. Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2021. "Linking U.S. State-level housing market returns, and the consumption-(Dis)Aggregate wealth ratio," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 779-810.
    7. 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.
    8. Dayong Zhang & Qiang Ji & Wan-Li Zhao & Nicholas J Horsewood, 2021. "Regional housing price dependency in the UK: A dynamic network approach," Urban Studies, Urban Studies Journal Limited, vol. 58(5), pages 1014-1031, April.
    9. Jeffrey P. Cohen & Cletus C. Coughlin & Daniel Soques, 2019. "House Price Growth Interdependencies and Comovement," Working Papers 2019-028, Federal Reserve Bank of St. Louis, revised 11 Jan 2021.
    10. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2023. "Time-varying impacts of monetary policy uncertainty on China's housing market," Economic Modelling, Elsevier, vol. 118(C).
    11. Bahar Öztürk & Dorinth van Dijk & Frank van Hoenselaar & Sander Burgers, 2018. "The relation between supply constraints and house price dynamics in the Netherlands," DNB Working Papers 601, Netherlands Central Bank, Research Department.

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    More about this item

    Keywords

    Graphical models; House price diffusion; Spatial dependence; Spillover effect; The Netherlands;
    All these keywords.

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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