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FORECASTING THE SOUTH AFRICAN ECONOMY WITH GIBBS SAMPLED BVECMs
Author(s) -
Gupta Rangan
Publication year - 2007
Publication title -
south african journal of economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.502
H-Index - 31
eISSN - 1813-6982
pISSN - 0038-2280
DOI - 10.1111/j.1813-6982.2007.00141.x
Subject(s) - homoscedasticity , heteroscedasticity , gibbs sampling , econometrics , economics , sample (material) , bayesian probability , pooling , statistics , mathematics , computer science , chemistry , artificial intelligence , chromatography
The paper uses the Gibbs sampling technique to estimate a heteroscedastic Bayesian Vector Error Correction Model (BVECM) of the South African economy for the period 1970:1‐2000:4, and then forecasts GDP, consumption, investment, short and long term interest rates, and the CPI over the period of 2001:1 to 2005:4. We find that a tight prior produces relatively more accurate forecasts than a loose one. The out‐of‐sample‐forecast accuracy resulting from the Gibbs sampled BVECM is compared with those generated from a Classical VECM and a homoscedastic BVECM. The homoscedastic BVECM is found to produce the most accurate out of sample forecasts.