This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed … frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon … the resulting non-linear MIDAS type mixed frequency VAR into a linear equation system that can be easily estimated. A …

This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed … frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon … the resulting non-linear MIDAS type mixed frequency VAR into a linear equation system that can be easily estimated. An out …

Building on a mixed data sampling (MIDAS) model we evaluate the predictive power of a variety of monthly macroeconomic … indicators for forecasting quarterly Chinese GDP growth. We iterate the evaluation over forecast horizons from 370 days to 1 day … 2009. Industrial production can be quite valuable for now- or even forecasting, but only if it is released shortly after …

In short-term forecasting, it is essential to take into account all available information on the current state of the … available data. In this respect, the Mixed-Data Sampling (MIDAS) model has proved to outperform existing tools by combining data … addresses this point by developing MIDAS based dimension reduction techniques and by introducing two novel approaches based on …

the so-called Mixed Data Sampling (MIDAS) approach that directly exploits the information content of monthly indicators to … smoothness priors in a distributed lag model, that weakens the restrictions the traditional MIDAS approach imposes on the data to …-nested specifications. It is found that the MIDAS approach is able to timely identify, from monthly information, important signals of the …

consumer spending is based on households’ expectations of their future income. However, in short-term forecasting, the … addition, consumer confidence seems to contain both a forecasting and independent explicative ability to predict consumption …

A forecasting model for unemployment is constructed that exploits the time-series properties of unemployment while … model clearly outperforms alternative forecasting procedures typically used to forecast unemployment. …

We evaluate the forecasting performance of six different models for short-term forecasting of Macedonian GDP: 1) ARIMA …

forecasts from an autoregressive model, an unconstrained VAR model, and a BVAR model with a Minnesota prior. Results indicate …