Gupta, RDas, Sonali2008-11-042008-11-042008-06Gupta, R and Das, S. 2008. Spatial Bayesian methods of forecasting house prices in six metropolitan areas of South Africa. South African Journal of Economics, Vol. 76(2), pp 298-3130038-2280http://hdl.handle.net/10204/2505Copyright: 2008 Blackwell Publishing LtdThis paper estimates Spatial Bayesian Vector Autoregressive models (SBVAR), 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. The authors then forecast one- to six-months-ahead house prices over the forecast horizon of 2005:07 to 2007:06. They then compare forecasts generated from the SBVAR's with those from an unrestricted Vector Autoregressive (VAR) and the Bayesian Vector Autoregressive (BVAR) models based on the Minnesota prior, they found 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, the results suggested that prices tend to converge for both large- and middle-sized houses, but no such evidence could be obtained for the small-sized housesenBVARBayesian vector autoregressive modelBayesian vector autoregressive forecastsForecast accuracySBVASpatial bayesian vector autoregressive modelVARVector autoregressive modelArticleGupta, R., & Das, S. (2008). Spatial Bayesian methods of forecasting house prices in six metropolitan areas of South Africa. http://hdl.handle.net/10204/2505Gupta, R, and Sonali Das "Spatial Bayesian methods of forecasting house prices in six metropolitan areas of South Africa." (2008) http://hdl.handle.net/10204/2505Gupta R, Das S. Spatial Bayesian methods of forecasting house prices in six metropolitan areas of South Africa. 2008; http://hdl.handle.net/10204/2505.TY - Article AU - Gupta, R AU - Das, Sonali AB - This paper estimates Spatial Bayesian Vector Autoregressive models (SBVAR), 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. The authors then forecast one- to six-months-ahead house prices over the forecast horizon of 2005:07 to 2007:06. They then compare forecasts generated from the SBVAR's with those from an unrestricted Vector Autoregressive (VAR) and the Bayesian Vector Autoregressive (BVAR) models based on the Minnesota prior, they found 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, the results suggested that prices tend to converge for both large- and middle-sized houses, but no such evidence could be obtained for the small-sized houses DA - 2008-06 DB - ResearchSpace DP - CSIR KW - BVAR KW - Bayesian vector autoregressive model KW - Bayesian vector autoregressive forecasts KW - Forecast accuracy KW - SBVA KW - Spatial bayesian vector autoregressive model KW - VAR KW - Vector autoregressive model LK - https://researchspace.csir.co.za PY - 2008 SM - 0038-2280 T1 - Spatial Bayesian methods of forecasting house prices in six metropolitan areas of South Africa TI - Spatial Bayesian methods of forecasting house prices in six metropolitan areas of South Africa UR - http://hdl.handle.net/10204/2505 ER -