Nowcasting real GDP growth: Comparison between old and new EU countries

Arbeitspapier

We analyze the performance of a broad range of nowcasting and short-term forecasting models for a representative set of twelve old and six new member countries of the European Union (EU) that are characterized by substantial differences in aggregate output variability. In our analysis, we generate ex-post out-of-sample nowcasts and forecasts based on hard and soft indicators that come from a comparable set of identical data. We show that nowcasting works well for the new EU countries because, although that variability in their GDP growth data is larger than that of the old EU economies, the economic significance of nowcasting is on average somewhat larger.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: IES Working Paper ; No. 05/2020

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Multiple or Simultaneous Equation Models: Panel Data Models; Spatio-temporal Models ; Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models ; Model Evaluation, Validation, and Selection ; Forecasting Models; Simulation Methods ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications ; Monetary Policy
• Thema: Bayesian VAR ; dynamic and static principal components ; European OECD countries ; factor augmented VAR ; nowcasting ; real GDP growth ; short-term forecasting

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Koécenda, Evézen ; Poghosyan, Karen
• Ereignis: Veröffentlichung
• (wer): Charles University in Prague, Institute of Economic Studies (IES)
• (wo): Prague
• (wann): 2020

Weitere Informationen

• Handle: http://hdl.handle.net/10419/228086
• Letzte Aktualisierung: 10.03.2025, 11:45 MEZ