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 …

-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 …

This paper introduces a new regression model - Markov-switching mixed data sampling (MS-MIDAS) - that incorporates … regime changes in the parameters of the mixed data sampling (MIDAS) models and allows for the use of mixed-frequency data in … Markov-switching models. After a discussion of estimation and inference for MS-MIDAS, and a small sample simulation based …

nowcasting Euro area and US GDP using monthly indicators. …Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by … to employ distributed lag functions. In this paper, we discuss the pros and cons of unrestricted lag polynomials in MIDAS …