Factor augmented vector autoregressions, panel VARs, and global VARs
This chapter provides a thorough introduction to panel, global, and factor augmented vector autoregressive models. These models are typically used to capture interactions across units (i.e., countries) and variable types. Since including a large number of countries and/or variables increases the dim...
Gespeichert in:
| Veröffentlicht in: | Macroeconomic forecasting in the era of big data |
|---|---|
| 1. Verfasser: | |
| Weitere Verfasser: | , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
2020
|
| Schlagworte: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Tag hinzufügen | Zusammenfassung: | This chapter provides a thorough introduction to panel, global, and factor augmented vector autoregressive models. These models are typically used to capture interactions across units (i.e., countries) and variable types. Since including a large number of countries and/or variables increases the dimension of the models, all three approaches aim to decrease the dimensionality of the parameter space. After introducing each model, we briefly discuss key specification issues. A running toy example serves to highlight this point and outlines key differences across the different models. To illustrate the merits of the competing approaches, we perform a forecasting exercise and show that it pays off to introduce cross-sectional information in terms of forecasting key macroeconomic quantities. |
|---|---|
| ISBN: | 9783030311490 303031149X |