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An In-Sample and Out-of-Sample Empirical Investigation of the Nonlinearity in House Prices of South Africa

Author

Listed:
  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Famagusta, North Cyprus,via Mersin 10, Turkey)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Zahra Shah

    (Department of Economics, University of Pretoria)

Abstract

This paper first tests if housing prices in the five segments of the South African housing market, namely, large-middle, medium-middle, small-middle, luxury and affordable, exhibits non-linearity based on smooth transition autoregressive (STAR) models estimated using quarterly data covering the period of 1970:Q2 to 2009:Q3. We find overwhelming evidence of non-linearity in these five segments based on in-sample evaluation of the linear and non-linear models. We then provide further support for non-linearity by comparing one- to four-quarters-ahead out-of-sample forecasts of the non-linear time series model with those of the classical and Bayesian versions of the linear autoregressive (AR) models for each of these segments, over an out-of-sample horizon of 2001:Q1 to 2009:Q3, using an in-sample period from 1970:Q2 to 2000:Q4. Our results indicate that barring the one-, two and four-step(s)-ahead forecasts of the small-middle-segment, the non-linear model always outperforms the linear models.

Suggested Citation

  • Mehmet Balcilar & Rangan Gupta & Zahra Shah, 2010. "An In-Sample and Out-of-Sample Empirical Investigation of the Nonlinearity in House Prices of South Africa," Working Papers 201008, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201008
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    Cited by:

    1. Sibel Cengiz & Afsin Sahin, 2014. "Modelling nonlinear behavior of labor force participation rate by STAR: An application for Turkey," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(1), pages 113-127, April.
    2. Mirriam Chitalu Chama-Chiliba & Rangan Gupta & Nonophile Nkambule & Naomi Tlotlego, 2011. "Forecasting Key Macroeconomic Variables of the South African Economy Using Bayesian Variable Selection," Working Papers 201132, University of Pretoria, Department of Economics.
    3. Kyriazakou, Eleni & Panagiotidis, Theodore, 2017. "Causality analysis of the Canadian city house price indices: A cross-sample validation approach," The Journal of Economic Asymmetries, Elsevier, vol. 16(C), pages 42-52.
    4. repec:ipg:wpaper:2014-585 is not listed on IDEAS
    5. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2015. "The out-of-sample forecasting performance of nonlinear models of regional housing prices in the US," Applied Economics, Taylor & Francis Journals, vol. 47(22), pages 2259-2277, May.
    6. Fuzuli Aliyev, 2019. "Testing Market Efficiency with Nonlinear Methods: Evidence from Borsa Istanbul," IJFS, MDPI, vol. 7(2), pages 1-11, June.
    7. Tsangyao Chang & Wen-Chi Liu & Goodness C. Aye & Rangan Gupta, 2016. "Are there housing bubbles in South Africa? Evidence from SPSM-based panel KSS test with a Fourier function," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 18(5), pages 517-532.
    8. 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.
    9. 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.
    10. Novella Maugeri, 2010. "Money Illusion and Rational Expectations: New Evidence from Well Known Survey Data," Department of Economics University of Siena 606, Department of Economics, University of Siena.
    11. 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.
    12. Behr,Daniela Monika & Chen,Lixue & Goel,Ankita & Haider,Khondoker Tanveer & Sandeep Singh & Zaman,Asad, 2023. "Estimating House Prices in Emerging Markets and Developing Economies : A Big Data Approach," Policy Research Working Paper Series 10301, The World Bank.
    13. Novella Maugeri, 2014. "Some Pitfalls in Smooth Transition Models Estimation: A Monte Carlo Study," Computational Economics, Springer;Society for Computational Economics, vol. 44(3), pages 339-378, October.
    14. Tsai, I-Chun, 2019. "Relationships among regional housing markets: Evidence on adjustments of housing burden," Economic Modelling, Elsevier, vol. 78(C), pages 309-318.
    15. 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.

    More about this item

    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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