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

Year: 2024

Type: article

Abstract: 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.

Source: Graduate Institute Geneva Institutional Repository (Graduate Institute of International and Development Studies)

DOI: 10.71609/iheid-v0ge-zf06

Authors: Ben Romdhane, Hager, Ben Tanfous, Nahed

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W6902575682

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