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

K. Poghosyan; J.R. Magnus

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

K. Poghosyan
, J.R. Magnus

Research output: Working paper › Discussion paper › Other research output

422 Downloads (Pure)

Abstract

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.

Original language	English
Place of Publication	Tilburg
Publisher	Econometrics
Volume	2011-054
Publication status	Published - 2011

Publication series

Name	CentER Discussion Paper
Volume	2011-054

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 17 Partnerships for the Goals

Keywords

Dynamic models
Factor analysis
Model averaging
Monte Carlo
Armenia

Access to Document

2011-054

Cite this

@techreport{419d588e78274cddb989447a0a76fe8d,

title = "WALS estimation and forecasting in factor-based dynamic models with an application to Armenia",

abstract = "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.",

keywords = "Dynamic models, Factor analysis, Model averaging, Monte Carlo, Armenia",

author = "K. Poghosyan and J.R. Magnus",

year = "2011",

language = "English",

volume = "2011-054",

series = "CentER Discussion Paper",

publisher = "Econometrics",

type = "WorkingPaper",

institution = "Econometrics",

}

TY - UNPB

T1 - WALS estimation and forecasting in factor-based dynamic models with an application to Armenia

AU - Poghosyan, K.

AU - Magnus, J.R.

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

KW - Dynamic models

KW - Factor analysis

KW - Model averaging

KW - Monte Carlo

KW - Armenia

M3 - Discussion paper

VL - 2011-054

T3 - CentER Discussion Paper

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

PB - Econometrics

CY - Tilburg

ER -

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

Abstract

Publication series

UN SDGs

Keywords

Access to Document

Fingerprint

Cite this