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An in-sample and out-of-sample empirical investigation of the nonlinearity in house prices of South Africa

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  • Balcilar, Mehmet
  • Gupta, Rangan
  • Shah, Zahra B.

Abstract

This paper tests whether housing prices in the five segments of the South African housing market, namely large-middle, medium-middle, small-middle, luxury and affordable, exhibit non-linearity based on smooth transition autoregressive (STAR) models estimated using quarterly data from 1970:Q2 to 2009:Q3. Findings point to an overwhelming evidence of non-linearity in these five segments based on in-sample evaluation of the linear and non-linear models. We next 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, for the out-of-sample horizon 2001:Q1 to 2009:Q3, using the in-sample period 1970:Q2 to 2000:Q4. Our results indicate that barring the one-, two and four-step(s)-ahead forecasts of the small segment, the non-linear model always outperforms the linear models. In addition, given the existence of strong causal relationship amongst the house prices of the five segments, the multivariate versions of the linear (classical and Bayesian) and STAR (MSTAR) models were also estimated. The MSTAR always outperformed the best performing univariate and multivariate linear models. Thus, our results highlight the importance of accounting for non-linearity, as well as the possible interrelationship amongst the variables under consideration, especially for forecasting.

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  • Balcilar, Mehmet & Gupta, Rangan & Shah, Zahra B., 2011. "An in-sample and out-of-sample empirical investigation of the nonlinearity in house prices of South Africa," Economic Modelling, Elsevier, vol. 28(3), pages 891-899, May.
  • Handle: RePEc:eee:ecmode:v:28:y:2011:i:3:p:891-899
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    Cited by:

    1. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working Papers 1209, University of Nevada, Las Vegas , Department of Economics.
    2. 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.
    3. repec:ipg:wpaper:2014-585 is not listed on IDEAS
    4. 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), Eastern Macedonia and Thrace Institute of Technology (EMATTECH), Kavala, Greece, vol. 7(1), pages 113-127, April.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. repec:eee:joecas:v:16:y:2017:i:c:p:42-52 is not listed on IDEAS
    10. 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.
    11. 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.

    More about this item

    Keywords

    Bayesian autoregressive models Housing market Smooth transition autoregressive models Forecast accuracy;

    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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