Vector autoregressive order selection and forecasting via the modified divergence information criterion
by Panagiotis Mantalos, Kyriacos Mattheou, Alex Karagrigoriou
International Journal of Computational Economics and Econometrics (IJCEE), Vol. 1, No. 3/4, 2010

Abstract: This paper examines the problem of order selection in connection to the forecasting performance for vector autoregressive (VAR) processes. For this purpose we present a generalisation of the modified divergence information criterion (MDIC) for VAR models and compare it with traditional information criteria by Monte Carlo methods for different data generating processes for small, medium, and large sample sizes. The VAR modified divergence information criterion (VAR/MDIC) shows remarkable good results by choosing the correct model more frequently than the known traditional information criteria with the smallest mean squared forecast error.

Online publication date: Wed, 05-Jan-2011

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