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Convergence of Metropolitan House Prices in South Africa: A Re-Examination Using Efficient Unit Root Tests

Author

Listed:
  • Sonali Das

    (LQM, CSIR, Pretoria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Patrick Agu Kaya

    (Department of Economics, University of Pretoria)

Abstract

This paper analyzes whether the Law of One Price (LOOP) holds in the housing market of five metropolitan areas of South Africa, namely Cape Town, Durban, Greater Johannesburg, Port Elizabeth/Uitenhage and Pretoria. We test the existence of LOOP using the efficient unit root tests proposed by Elliott et al. (1996) [DF-GLS] and Elliott (1999) [DF-GLSu] based on monthly data on residential property prices covering the period of 1967:01 to 2009:03 for the large-, medium and small-middle segments of the housing market. Based on the DF-GLSu test, we find overwhelming evidence of the existence of LOOP in twelve of the fifteen possible cases, especially as the sample period becomes more recent. More importantly, our results are in sharp contrast with those obtained by Burger and Van Rensburg (2008) using quarterly data based on the Im, Pesharan and Shin (IPS, 2003) test, which are, in turn, shown to be highly sensitive to frequency of the data and temporal aggregation. With the rejection or the non-rejection of the null hypothesis of unit roots, based on panel data tests, not providing sufficient evidence to conclude that all the series in the panels have a unit root or that they are all stationary, more reliability should be placed on our results obtained from the efficient unit root tests.

Suggested Citation

  • Sonali Das & Rangan Gupta & Patrick Agu Kaya, 2009. "Convergence of Metropolitan House Prices in South Africa: A Re-Examination Using Efficient Unit Root Tests," Working Papers 200922, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:200922
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    2. Roula Inglesi-Lotz & Rangan Gupta, 2011. "Relationship between House Prices and Inflation in South Africa: An ARDL Approach," Working Papers 201130, University of Pretoria, Department of Economics.
    3. Goodness C. Aye & Samrat Goswami & Rangan Gupta, 2012. "Metropolitan House Prices In India: Do They Converge?," Working Papers 201220, University of Pretoria, Department of Economics.
    4. Tsangyao Chang & Tsung-Pao Wu & Rangan Gupta, 2015. "Are house prices in South Africa really nonstationary? Evidence from SPSM-based panel KSS test with a Fourier function," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 32-53, January.
    5. Luis A. Gil-Alana & Goodness C. Aye & Rangan Gupta, 2012. "Testing for Persistence with Breaks and Outliers in South African House Prices," Working Papers 201233, University of Pretoria, Department of Economics.
    6. Borozan, Djula, 2017. "Testing for convergence in electricity consumption across Croatian regions at the consumer's sectoral level," Energy Policy, Elsevier, vol. 102(C), pages 145-153.
    7. Beatrice Simo-Kengne & Manoel Bittencourt & Rangan Gupta, 2012. "House Prices and Economic Growth in South Africa: Evidence From Provincial-Level Data," Journal of Real Estate Literature, Taylor & Francis Journals, vol. 20(1), pages 97-117, January.
    8. 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.
    9. Aye, G.C. & Goswami, S. & Gupta, R., 2013. "Metropolitan House Prices In Regions of India: Do They Converge?," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 13(1), pages 135-144.
    10. Nicholas Apergis & Beatrice D. Simo-Kengne & Rangan Gupta, 2015. "Convergence In Provincial-Level South African House Prices: Evidence From The Club Convergence And Clustering Procedure," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 27(1), pages 2-17, March.

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    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General
    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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