Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/238800
Authors: 
Poghosyan, Karen
Magnus, Jan R.
Year of Publication: 
2012
Citation: 
[Journal:] International Econometric Review (IER) [ISSN:] 1308-8815 [Volume:] 4 [Year:] 2012 [Issue:] 1 [Pages:] 40-58
Publisher: 
Econometric Research Association (ERA), Ankara
Abstract: 
Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known Bayesian model averaging (BMA) and the recently developed weighted average least squares (WALS). Both methods propose to combine frequentist estimators using Bayesian weights. We apply our framework to the Armenian economy using quarterly data from 2000–2010, and we estimate and forecast real GDP growth and inflation.
Subjects: 
Dynamic Models
Factor Analysis
Model Averaging
Monte Carlo
Armenia
JEL: 
C11
C13
C52
C53
E52
E58
Creative Commons License: 
https://creativecommons.org/licenses/by-nc-nd/4.0/
Document Type: 
Article

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