Journal of Probability and Statistics
Volume 2012 (2012), Article ID 867056, 16 pages
http://dx.doi.org/10.1155/2012/867056
Research Article

Application of Generalized Space-Time Autoregressive Model on GDP Data in West European Countries

Nunung Nurhayati,1 Udjianna S. Pasaribu,2 and Oki Neswan2

1Faculty of Science and Engineering, Jenderal Soedirman University, Purwokerto 53122, Indonesia
2Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, Bandung 40132, Indonesia

Received 28 September 2011; Revised 1 February 2012; Accepted 14 February 2012

Academic Editor: Shein-chung Chow

Copyright © 2012 Nunung Nurhayati et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper provides an application of generalized space-time autoregressive (GSTAR) model on GDP data in West European countries. Preliminary model is identified by space-time ACF and space-time PACF of the sample, and model parameters are estimated using the least square method. The forecast performance is evaluated using the mean of squared forecast errors (MSFEs) based on the last ten actual data. It is found that the preliminary model is GSTAR(2;1,1). As a comparison, the estimation and the forecast performance are also applied to the GSTAR(1;1) model which has fewer parameter. The results showed that the ASFE of GSTAR(2;1,1) is smaller than that of the order (1;1). However, the t-test value shows that the performance is significantly indifferent. Thus, due to the parsimony principle, the GSTAR(1;1) model might be considered as a forecasting model.