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‘Ripple’ Effects in South African House Prices

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  • Mehmet Balcilar
  • Abebe Beyene
  • Rangan Gupta
  • Monaheng Seleteng

Abstract

This paper analyses the ‘ripple’ effect of house prices in large-, medium- and small-sized houses of five major metropolitan areas of South Africa—namely, Cape Town, Durban Unicity, Greater Johannesburg, Port Elizabeth/Uitenhage and Pretoria—based on available quarterly data covering the period of 1966:Q1 to 2010:Q1. Following the extant literature, the issue is contextualised as a unit root problem, with one expecting the ratios of metropolitan house price to national house price to exhibit stationarity to an underlying trend value, if there is diffusion in house prices. Using Bayesian and non-linear unit root tests, besides the standard linear tests of stationarity with and without structural break, overwhelming support is found for the existence of robust ripple effects. Also factor analysis conducted suggested that ripple effects originate in Cape Town for the large housing segment and in Durban for the medium- and small-sized houses.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:urbstu:v:50:y:2013:i:5:p:876-894
    DOI: 10.1177/0042098012458551
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    2. 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.
    3. Steve Cook & Duncan Watson, 2016. "A new perspective on the ripple effect in the UK housing market: Comovement, cyclical subsamples and alternative indices," Urban Studies, Urban Studies Journal Limited, vol. 53(14), pages 3048-3062, November.
    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. Tsai, I-Chun, 2018. "House price convergence in euro zone and non-euro zone countries," Economic Systems, Elsevier, vol. 42(2), pages 269-281.
    6. Jin Hu & Xuelei Xiong & Yuanyuan Cai & Feng Yuan, 2020. "The Ripple Effect and Spatiotemporal Dynamics of Intra-Urban Housing Prices at the Submarket Level in Shanghai, China," Sustainability, MDPI, vol. 12(12), pages 1-17, June.
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    8. 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).
    9. 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.
    10. Shu-hen Chiang, 2014. "Housing Markets in China and Policy Implications: Comovement or Ripple Effect," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 22(6), pages 103-120, November.
    11. 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.
    12. Kurmaş Akdoğan, 2019. "Size and sign asymmetries in house price adjustments," Applied Economics, Taylor & Francis Journals, vol. 51(48), pages 5268-5281, October.
    13. 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.
    14. Williams, Joseph, 2018. "Housing markets with endogenous search: Theory and implications," Journal of Urban Economics, Elsevier, vol. 105(C), pages 107-120.
    15. 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.

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