This paper compares the GDP forecasting performance of alternative factor models based on monthly time series for the French economy. These models are based on static and dynamic principal components obtained using time and frequency domain methods. We question whether it is more appropriate to...

We study the probability of rejecting the seasonal unit root tests developed by Hylleberg et al. when they are applied to fractionally integrated seasonal time series. We find that these tests have quite low power and that they lead to a risk of over-differencing. The forecasting performance of...

This paper deals with the k-factor extension of the long memory Gegenbauer process proposed by Gray et al. (1989). We give the analytic expression of the prediction function derived from this long memory process and provide the h-step-ahead prediction error when parameters are either known or...

This paper formalizes the process of forecasting unbalanced monthly datasets in order to obtain robust nowcasts and forecasts of quarterly gross domestic product (GDP) growth rate through a semi-parametric modeling. This innovative approach lies in the use of non-parametric methods, based on...