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Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations

Citation

Athanasopoulos, G and Poskitt, DS and Vahid, F and Yao, W, Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations, Journal of Applied Econometrics, 31, (6) pp. 1100-1119. ISSN 1099-1255 (2016) [Refereed Article]

Copyright Statement

Copyright 2015 John Wiley & Sons, Ltd.

DOI: doi:10.1002/jae.2484

Abstract

This article studies a simple, coherent approach for identifying and estimating error-correcting vector autoregressive moving average (EC-VARMA) models. Canonical correlation analysis is implemented for both determining the cointegrating rank, using a strongly consistent method, and identifying the short-run VARMA dynamics, using the scalar component methodology. Finite-sample performance is evaluated via Monte Carlo simulations and the approach is applied to modelling and forecasting US interest rates. The results reveal that EC-VARMA models generate significantly more accurate out-of-sample forecasts than vector error correction models (VECMs), especially for short horizons.

Item Details

Item Type:Refereed Article
Research Division:Economics
Research Group:Econometrics
Research Field:Time-Series Analysis
Objective Division:Economic Framework
Objective Group:Macroeconomics
Objective Field:Macroeconomics not elsewhere classified
Author:Yao, W (Dr Wenying Yao)
ID Code:103114
Year Published:2016 (online first 2015)
Deposited By:Tasmanian School of Business and Economics
Deposited On:2015-09-22
Last Modified:2016-11-01
Downloads:0

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