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

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1 Citation (Scopus)

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. 
Original languageEnglish
Pages (from-to)1100-1119
Number of pages20
JournalJournal of Applied Econometrics
Volume31
Issue number6
DOIs
Publication statusPublished - 1 Sep 2016

Cite this

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title = "Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations",
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. ",
author = "George Athanasopoulos and Poskitt, {Donald S.} and Farshid Vahid and Wenying Yao",
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language = "English",
volume = "31",
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journal = "Journal of Applied Econometrics",
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Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations. / Athanasopoulos, George; Poskitt, Donald S.; Vahid, Farshid; Yao, Wenying.

In: Journal of Applied Econometrics, Vol. 31, No. 6, 01.09.2016, p. 1100-1119.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations

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AU - Vahid, Farshid

AU - Yao, Wenying

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AB - 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. 

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