To forecast at several, say h, periods into the future, a modeller faces a choice between iterating one-step ahead forecasts (the IMS technique) or directly modeling the relation between observations separated by an h-period interval and using it for forecasting (DMS forecasting). It is known that structural breaks, unit-root non-stationarity and residual autocorrelation may benefi?t DMS accuracy in ?finite samples, all of which occuring when modelling the South African GDP over 1965-2000. This paper analyses the forecasting properties of 779 multivariate and univariate models that combine di?fferent techniques of robust forecasting. We fi?nd strong evidence supporting the use of DMS and intercept correction (IC) and attribute it to their improved peformance in the presence of breaks.
CHEVILLON, G. (2009). Multi-Step Forecasting in Emerging Economies: An Investigation of the South African GDP. International Journal of Forecasting, 25(3), pp. 602-628.