Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/217594
Authors: 
Poghosyan, Karen
Year of Publication: 
2016
Citation: 
[Journal:] Journal of Central Banking Theory and Practice [ISSN:] 2336-9205 [Volume:] 5 [Year:] 2016 [Issue:] 2 [Pages:] 81-99
Abstract: 
We evaluate the forecasting performance of four competing models for short-term macroeconomic forecasting: the traditional VAR, small scale Bayesian VAR, Factor Augmented VAR and Bayesian Factor Augmented VAR models. Using Armenian quarterly actual macroeconomic time series from 1996Q1 – 2014Q4, we estimate parameters of four competing models. Based on the out-of-sample recursive forecast evaluations and using root mean squared error (RMSE) criterion we conclude that small scale Bayesian VAR and Bayesian Factor Augmented VAR models are more suitable for short-term forecasting than traditional unrestricted VAR model.
Subjects: 
vector autoregression
Bayesian estimation
principal components
recursive regression
forecast evaluation
macroeconomic indicators
Armenia.
JEL: 
C11
C13
C52
C53
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-nc-nd/3.0/
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.