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Spatial Bayesian Methods Of Forecasting House Prices In Six Metropolitan Areas Of South Africa

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  • Rangan Gupta
  • Sonali Das

Abstract

This paper estimates Spatial Bayesian Vector Autoregressive (SBVAR) models, based on the First-Order Spatial Contiguity and the Random Walk Averaging priors, for six metropolitan areas of South Africa, using monthly data over the period of 1993:07 to 2005:06. We then forecast one- to six-months-ahead house prices over the forecast horizon of 2005:07 to 2007:06. When we compare forecasts generated from the SBVARs with those from an unrestricted Vector Autoregressive (VAR) and the Bayesian Vector Autoregressive (BVAR) models based on the Minnesota prior, we find that the spatial models tend to outperform the other models for large middle-segment houses; while the VAR and the BVAR models tend to produce lower average out-of-sample forecast errors for middle and small-middle segment houses, respectively. In addition, based on the priors used to estimate the Bayesian models, our results also suggest that prices tend to converge for both large- and middle-sized houses, but no such evidence could be obtained for the small-sized houses. Copyright (c) 2008 The Authors. Journal compilation (c) Economic Society of South Africa 2008.

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  • Rangan Gupta & Sonali Das, 2008. "Spatial Bayesian Methods Of Forecasting House Prices In Six Metropolitan Areas Of South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 76(2), pages 298-313, June.
  • Handle: RePEc:bla:sajeco:v:76:y:2008:i:2:p:298-313
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    Cited by:

    1. Charles Rahal, 2015. "House Price Forecasts with Factor Combinations," Discussion Papers 15-05, Department of Economics, University of Birmingham.
    2. repec:eee:jhouse:v:37:y:2017:i:c:p:22-28 is not listed on IDEAS
    3. Seung, Chang K. & Ahn, Sung K., 2010. "Forecasting Industry Employment for a Resource-Based Economy Using Bayesian Vector Autoregressive Models," The Review of Regional Studies, Southern Regional Science Association, vol. 40(2), pages 181-196.
    4. Sonali DAS , Rangan GUPTA & Patrick A. KAYA, 2010. "Convergence Of Metropolitan House Prices In South Africa: A Re-Examination Using Efficient Unit Root Tests," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 10(1).
    5. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    6. 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.
    7. Ali Azadeh & Mohammad Sheikhalishahi & Ali Boostani, 2014. "A Flexible Neuro-Fuzzy Approach for Improvement of Seasonal Housing Price Estimation in Uncertain and Non-Linear Environments," South African Journal of Economics, Economic Society of South Africa, vol. 82(4), pages 567-582, December.
    8. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Using Large Data Sets to Forecast Housing Prices: A Case Study of Twenty US States," Working Papers 200912, University of Pretoria, Department of Economics.
    9. Charles Rahal, 2015. "Housing Market Forecasting with Factor Combinations," Discussion Papers 15-05r, Department of Economics, University of Birmingham.
    10. Gupta, Rangan & Jurgilas, Marius & Kabundi, Alain, 2010. "The effect of monetary policy on real house price growth in South Africa: A factor-augmented vector autoregression (FAVAR) approach," Economic Modelling, Elsevier, vol. 27(1), pages 315-323, January.
    11. Cuestas, Juan Carlos, 2017. "House prices and capital inflows in Spain during the boom: Evidence from a cointegrated VAR and a structural Bayesian VAR," Journal of Housing Economics, Elsevier, vol. 37(C), pages 22-28.
    12. Rangan Gupta, 2012. "Forecasting House Prices for the Four Census Regions and the Aggregate US Economy: The Role of a Data-Rich Environment," Working Papers 201214, University of Pretoria, Department of Economics.
    13. 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.
    14. 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.
    15. 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.
    16. Rangan Gupta & Sonali Das, 2010. "Predicting Downturns in the US Housing Market: A Bayesian Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 41(3), pages 294-319, October.
    17. 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.
    18. Rangan Gupta & Alain Kabundi, 2010. "Forecasting macroeconomic variables in a small open economy: a comparison between small- and large-scale models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 168-185.

    More about this item

    JEL classification:

    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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