Title: Vector autoregressive order selection and forecasting via the modified divergence information criterion
Authors: Panagiotis Mantalos, Kyriacos Mattheou, Alex Karagrigoriou
Addresses: Department of Statistics, University of Lund, Box 743, 22007 Lund, Sweden. ' Department of Mathematics and Statistics, University of Cyprus, P.O. Box 20537, CY-1678 Nicosia, Cyprus. ' Department of Mathematics and Statistics, University of Cyprus, P.O. Box 20537, CY-1678 Nicosia, Cyprus
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.
Keywords: average squared forecasting errors; order selection; modified divergence information criterion; MDIC; vector autoregressive; VAR process.
International Journal of Computational Economics and Econometrics, 2010 Vol.1 No.3/4, pp.254 - 277
Published online: 05 Jan 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article