Eintrag weiter verarbeiten
Nowcasting with large Bayesian vector autoregressions
Gespeichert in:
| Personen und Körperschaften: | , , , , |
|---|---|
| Titel: | Nowcasting with large Bayesian vector autoregressions/ Jacopo Cimadomo, Domenico Giannone, Michele Lenza, Francesca Monti, Andrej Sokol |
| Format: | E-Book |
| Sprache: | Englisch |
| veröffentlicht: |
Frankfurt am Main, Germany
European Central Bank
[2020]
|
| Gesamtaufnahme: |
Europäische Zentralbank: Working paper series ; no 2453 (August 2020)
|
| Quelle: | Verbunddaten SWB Lizenzfreie Online-Ressourcen |
| Zusammenfassung: | Monitoring economic conditions in real time, or nowcasting, is among the key tasks routinely performed by economists. Nowcasting entails some key challenges, which also characterise modern Big Data analytics, often referred to as the three "Vs": the large number of time series continuously released (Volume), the complexity of the data covering various sectors of the economy, published in an asynchronous way and with different frequencies and precision (Variety), and the need to incorporate new information within minutes of their release (Velocity). In this paper, we explore alternative routes to bring Bayesian Vector Autoregressive (BVAR) models up to these challenges. We find that BVARs are able to effectively handle the three Vs and produce, in real time, accurate probabilistic predictions of US economic activity and, in addition, a meaningful narrative by means of scenario analysis. |
|---|---|
| Umfang: | 1 Online-Ressource (circa 30 Seiten); Illustrationen |
| ISBN: |
9789289943703
928994370X |
| DOI: | 10.2866/179524 |