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...

In this paper, we consider a threshold time series model in order to take into account certain stylized facts of the industrial business cycle, such as asymmetries in the phases of the cycle. Our aim is to point out some thresholds under (over) which a signal of turning point could be given....

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...

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...

The intricate issue of detecting and forecasting macroeconomic cycles turning points has been once more perfectly illustrated with the global downturn experienced by most countries around the world in 2000-2001. Governments and Central Banks are very sensitive to economic indicators showing...

In this paper, we consider a threshold time series model in order to take into account certain stylized facts of the business cycle, such as asymmetries in the phases of the cycle. Our aim is to point out some thresholds under (over) which a signal of turning point could be given in real-time....

Dimension reduction of large data sets has been recently the topic of interest of many research papers dealing with macroeconomic modelling. Especially dynamic factor models have been proved to be useful for GDP nowcasting or short-term forecasting. In this paper, we put forward an innovative...

Non-parametric methods have been empirically proved to be of great interest in the statistical literature in order to forecast stationary time series, but very few applications have been proposed in the econometrics literature. In this paper, our aim is to test whether non-parametric statistical...

Testing the fractionally integrated order of seasonal and non-seasonal unit roots is quite important for the economic and financial time series modelling. In this paper, Robinson test (1994) is applied to various well-known long memory models. Via Monte Carlo experiments, we study and compare...

Business surveys are an important element in the analysis of the short-term economic situation because of the timeliness and nature of the information they convey. Especially, surveys are often involved in econometric models in order to provide an early assessment of the current state of the...