Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/184718 
Year of Publication: 
2017
Series/Report no.: 
Graduate Institute of International and Development Studies Working Paper No. HEIDWP15-2017
Publisher: 
Graduate Institute of International and Development Studies, Geneva
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.
Subjects: 
FAVAR
Conditional FAVAR
Conditional Forecast
Document Type: 
Working Paper

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