WALS estimation and forecasting in factor-based dynamic models with an application to Armenia

Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known BMA and the recently developed 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 and inflation dynamics.

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Year of publication:	2011
Authors:	Magnus, Jan R. ; Poghosyan, K.
Institutions:	Tilburg University, Center for Economic Research
Subject:	Dynamic models \| Factor analysis \| Model averaging \| Monte Carlo \| Armenia

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Extent:	application/pdf
Series:	Discussion Paper.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series CentER Discussion Paper Number 2011-054
Classification:	C11 - Bayesian Analysis ; C13 - Estimation ; C52 - Model Evaluation and Testing ; C53 - Forecasting and Other Model Applications ; E52 - Monetary Policy (Targets, Instruments, and Effects) ; E58 - Central Banks and Their Policies
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011090802