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 levels and interest rates,
for the period of 1978 to 2000. The out-of-sample-forecast accuracy obtained from the
BVECM, over the forecasting horizon of 2001:1 to 2003:4, is compared with those generated
from the Classical variant of the VAR and the VECM, the Bayesian VAR, and the ECM of
inventory investment developed by Smith et al. (2006) for the South African economy.
The BVECM with the most tight prior outperforms all the other models, except for a relatively
tight BVAR. This BVAR model also correctly predicts the direction of change of inventory
investment over the period of 2004:1 to 2006:3.
This paper uses a version of Hansen's (1985) Dynamic Stochastic General Equilibrium (DSGE) model to forecast the South African economy. The calibrated model, based on annual data over the period of 1970-2000, is used to ...
Cloud-to-ground lightning data from the Southern Africa Lightning Detection Network and numerical weather prediction model parameters from the Unified Model are used to develop a lightning threat index (LTI) for South ...
This paper analyses the out-of-sample forecasting performance of non-linear vs. linear models for the South African rand against the United States dollar and the British pound, in real terms. We compare the forecasting ...