Conditional FAVAR and scenario analysis for a large data: Case of Tunisia

Arbeitspapier

The aim of this paper is to compute the conditional forecasts of a set of variables of interest on future paths of some variables in dynamic systems. We build a large dynamic factor models for a quarterly data set of 30 macroeconomic and financial indicators. Results of forecasting suggest that conditional FAVAR models which incorporate more economic information outperform the unconditional FAVAR in terms of the forecast errors.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Graduate Institute of International and Development Studies Working Paper ; No. HEIDWP15-2017

Klassifikation und Themen

• Klassifikation: Wirtschaft
• Thema: FAVAR ; Conditional FAVAR ; Conditional Forecast

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Romdhane, Hajer Ben ; Tanfous, Nahed Ben
• Ereignis: Veröffentlichung
• (wer): Graduate Institute of International and Development Studies
• (wo): Geneva
• (wann): 2017

Weitere Informationen

• Handle: http://hdl.handle.net/10419/184718
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ