-data sampling (MIDAS) regressions with few predictors. The specification of these models requires several choices related to … forecasting quarterly German GDP, a key macroeconomic indicator for the largest country in the euro area, with a large set of …

smoother in a state-space model context. The monthly factors are used to estimate current quarter GDP, called the `nowcast …', using different versions of what we call factor-based mixed-data sampling (Factor-MIDAS) approaches. We compare all possible … combinations of factor estimation methods and Factor-MIDAS projections with respect to nowcast performance. Additionally, we …

technique in Monte-Carlo experiments. Finally, the MSMF-VAR model is applied to predict GDP growth and business cycle turning … switching mixed data sampling (MIDAS) models. The results suggest that MSMF-VAR models are particularly useful to estimate the …

paper, we compare their performance in a relevant case for policy making, i.e., nowcasting and forecasting quarterly GDP …This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model specification … in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on …

-VAR) models. We discuss their performances for nowcasting the quarterly growth rate of the Euro area GDP and its components, using … mixed-frequency and ragged-edge datasets: bridge equations, mixed-data sampling (MIDAS), and mixed-frequency VAR (MF … and factor models, in a pseudo real-time framework. MIDAS with an AR component performs quite well, and outperforms MF …

This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model specification … in the presence of mixed-frequency data, e.g. monthly and quarterly series. MIDAS leads to parsimonious models which are … suffer from the curse of dimensionality. However, if the restrictions imposed by MIDAS are too stringent, the MF-VAR can …