Since the seminal article of Bates and Granger (1969), a large number of theoretical and empirical studies have shown that pooling different forecasts of the same event tends to outperform individual forecasts in terms of forecast accuracy. However, the results remain heterogenous regarding the...

In diesem Beitrag wird die Verwendung von VAR-Modellen für die Prognose des realen Bruttoinlandsprodukts in den Vereinigten Staaten analysiert. Den Ausgangspunkt bildet ein Basismodell, das neben dem realen BIP den Verbraucherpreisindex sowie einen kurzfristigen Geldmarktsatz enthält. Das...

Given the relatively low computational effort involved, vector autoregressive (VAR) models are frequently used for macroeconomic forecasting purposes. However, the usually limited number of observations obliges the researcher to focus on a relatively small set of key variables, possibly...

The use of log-transformed data has become standard in macroeconomic forecasting with VAR models. However, its appropriateness in the context of out-of-sample forecasts has not yet been exposed to a thorough empirical investigation. With the aim of filling this void, a broad sample of VAR models...

Since the seminal article of Bates and Granger (1969), a large number of theoretical and empirical studies have shown that pooling different forecasts of the same event tends to outperform individual forecasts in terms of forecast accuracy. However, the results remain heterogenous regarding the...

Since the seminal article of Bates and Granger (1969), a large number of theoretical and empirical studies have shown that pooling different forecasts of the same event tends to outperform individual forecasts in terms of forecast accuracy. However, the results remain heterogenous regarding the...

This paper analyzes the mechanics of VAR forecast pooling and quantifies the forecast performance under varying conditions. To fill the gap between empirical and purely theoretical research we run a Monte Carlo study and simulate the data from different New Keynesian DSGE models. We find that...