Conditional FAVAR and scenario analysis for a large data: case of Tunisia
Ben Romdhane, Hager; Ben Tanfous, Nahed
2017

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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.

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Title Conditional FAVAR and scenario analysis for a large data: case of Tunisia
Author Ben Romdhane, Hager
Ben Tanfous, Nahed
Publisher Geneva, The Graduate Institute of International and Development Studies, International Economics Department
Date 2017
Pagination 23 p. : ill.
Series Graduate Institute of International and Development Studies Working Paper ; no. 15/2017
Content Type Papers and Reports
Record Created 2017-08-18
Record ID 295267
Record Appears in Academic Departments > International Economics Department
Papers and Reports
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