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

George Athanasopoulos; Donald S. Poskitt; Farshid Vahid; Wenying Yao

doi:10.1002/jae.2484

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

George Athanasopoulos, Donald S. Poskitt, Farshid Vahid, Wenying Yao

Econometrics & Business Statistics

Research output: Contribution to journal › Article › Research › peer-review

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 language	English
Pages (from-to)	1100-1119
Number of pages	20
Journal	Journal of Applied Econometrics
Volume	31
Issue number	6
DOIs	https://doi.org/10.1002/jae.2484
Publication status	Published - 1 Sep 2016

Cite this

Athanasopoulos, G., Poskitt, D. S., Vahid, F., & Yao, W. (2016). Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations. Journal of Applied Econometrics, 31(6), 1100-1119. https://doi.org/10.1002/jae.2484

Athanasopoulos, George ; Poskitt, Donald S. ; Vahid, Farshid ; Yao, Wenying. / Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations. In: Journal of Applied Econometrics. 2016 ; Vol. 31, No. 6. pp. 1100-1119.

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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. ",

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Athanasopoulos, G , Poskitt, DS , Vahid, F & Yao, W 2016, 'Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations', Journal of Applied Econometrics, vol. 31, no. 6, pp. 1100-1119. https://doi.org/10.1002/jae.2484

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 journal › Article › Research › peer-review

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