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

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.

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Year of publication:	2017
Authors:	Romdhane, Hajer Ben ; Tanfous, Nahed Ben
Publisher:	Geneva : Graduate Institute of International and Development Studies
Subject:	FAVAR \| Conditional FAVAR \| Conditional Forecast

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Series:	Graduate Institute of International and Development Studies Working Paper ; HEIDWP15-2017
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	897206401 [GVK] hdl:10419/184718 [Handle] RePEc:gii:giihei:HEIDWP15-2017 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10011926764