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.

Object Details

• Language: Englisch

References and Relationships

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

Classification and Topics

• Classification: Wirtschaft
• Subject: FAVAR ; Conditional FAVAR ; Conditional Forecast

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Romdhane, Hajer Ben ; Tanfous, Nahed Ben
• Event: Veröffentlichung
• (who): Graduate Institute of International and Development Studies
• (where): Geneva
• (when): 2017

Further information

• Handle: http://hdl.handle.net/10419/184718
• Last update: 10.03.2025, 11:43 AM CET