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Canonical correlation analysis is implemented for both determining the cointegrating rank, using a strongly consistent method, and identifying the short\u2010run VARMA dynamics, using the scalar component methodology. Finite\u2010sample performance is evaluated via Monte Carlo simulations and the approach is applied to modelling and forecasting US interest rates. The results reveal that EC\u2010VARMA models generate significantly more accurate out\u2010of\u2010sample forecasts than vector error correction models (VECMs), especially for short horizons. 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