Focusing on the MI(xed) DA(ta) S(ampling) regressions for handling different sampling frequencies and asynchronous releases of information, alternative techniques for the autoregressive augmentation of these regressions are presented and discussed. For forecasting quarterly euro area GDP growth...

Institutions which publish macroeconomic forecasts usually do not rely on a single econometric model to generate their forecasts. The combination of judgements with information from different models complicates the problem of characterizing the predictive density. This paper proposes a...

How should we forecast GDP? Should we forecast directly the overall GDP or aggregate the forecasts for each of its components using some level of disaggregation? The search for the answer continues to motivate several horse races between these two approaches. Nevertheless, independently of the...

We explore the use of nowcasts from the Philadelphia Survey of Professional Forecasters as a starting point for macroeconomic forecasting. Specifically, survey nowcasts are treated as anadditional observation of the time series of interest. This simple approach delivers enhanced model...

The estimation of dynamic factor models for large cross-sections poses a challenge in a real time environment. As macroeconomic data become available with different delays, unbalanced panel data sets with missing values at the end of the sample period (the so-called "jagged edge") have to be...

We compare theoretical and empirical forecasts computed by rational agents living in a model economy to those produced by professional forecasters. We focus on the variance of the prediction errors as a function of the forecast horizon and analyze the speed with which it converges to a constant...