This paper develops an estimable hybrid model that combines the micro-founded
DSGE model with the °exibility of the theoretical VAR model. The model is
estimated via the maximum likelihood technique based on quarterly data on real
Gross National Product (GNP), consumption, investment and hours worked, for
the South African economy, over the period of 1970:1 to 2000:4. Based on a re-
cursive estimation using the Kalman ¯lter algorithm, the out-of-sample forecasts
from the hybrid model are then compared with the forecasts generated from the
Classical and Bayesian variants of the VAR for the period 2001:1-2005:4. The
results indicate that, in general, the estimated hybrid DSGE model outperforms
the Classical VAR, but not the Bayesian VARs in terms of out-of-sample fore-
Gupta, Rangan(University of Pretoria, Department of Economics, 2007-02)
This paper develops a Bayesian Vector Error Correction Model (BVECM) for
forecasting inventory investment in South Africa. The model is estimated using
quarterly data on actual sales, production, unfilled orders, price ...
This paper develops a Bayesian Vector Error Correction Model (BVECM) for forecasting inventory investment. The model is estimated using South African quarterly data on actual sales, production, unfilled orders, price level ...
Poolman, Eugene Rene(University of Pretoria, 2015)
The development of the Severe Weather Impact Forecasting System (SWIFS) for flash flood
hazards in South Africa is described in this thesis. Impact forecasting addresses the need to
move from forecasting weather conditions ...