Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations
Athanasopoulos, George, Poskitt, Donald S., Vahid, Farshid and Yao, Wenying 2015, 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, doi: 10.1002/jae.2484.
Attached Files
Name
Description
MIMEType
Size
Downloads
Title
Determination of long-run and short-run dynamics in EC-VARMA models via canonical correlations
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.
Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.