WALS Estimation and Forecasting in Factor-based Dynamic Models with an Application to Armenia

Authors : Karen POGHOSYAN, Jan R MAGNUS

Pages : 40-58

View : 14 | Download : 9

Publication Date : 2012-04-01

Article Type : Research Paper

Abstract :Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known Bayesian model averaging insert ignore into journalissuearticles values(BMA); and the recently developed weighted average least squares insert ignore into journalissuearticles values(WALS);. Both methods propose to combine frequentist estimators using Bayesian weights. We apply our framework to the Armenian economy using quarterly data from 20002010, and we estimate and forecast real GDP growth and inflation.
Keywords : Dynamic Models, Factor Analysis, Model Averaging, Monte Carlo, Armenia