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.

Publication Details

Journal
Graduate Institute Geneva Institutional Repository (Graduate Institute of International and Development Studies)
Published
2024-09-27
DOI
https://doi.org/10.71609/iheid-v0ge-zf06
Primary Topic
Monetary Policy and Economic Impact
Type
article
Field-Weighted Citation Impact
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article

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

Graduate Institute Geneva Institutional Repository (Graduate Institute of International and Development Studies)
Monetary Policy and Economic Impact
article

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

article en

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.

Graduate Institute Geneva Institutional Repository (Graduate Institute of International and Development Studies)
Decent work and economic growth
Openalex Percentile: Top 42%
Monetary Policy and Economic Impact
DOIOpen Access PDFOpenAlex
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Conditional FAVAR and scenario analysis for a large data: case of Tunisia · Graduate Institute Geneva Institutional Repository (Graduate Institute of International and Development Studies) (2024) | TGRS Research Map | TGRS