Application of Generalized Space-Time Autoregressive Model on GDP Data in West European Countries
Joint Authors
Pasaribu, Udjianna S.
Neswan, Oki
Nurhayati, Nunung
Source
Journal of Probability and Statistics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-05-08
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Nurhayati, Nunung& Pasaribu, Udjianna S.& Neswan, Oki. 2012. Application of Generalized Space-Time Autoregressive Model on GDP Data in West European Countries. Journal of Probability and Statistics،Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-504624
Modern Language Association (MLA)
Nurhayati, Nunung…[et al.]. Application of Generalized Space-Time Autoregressive Model on GDP Data in West European Countries. Journal of Probability and Statistics No. 2012 (2012), pp.1-16.
https://search.emarefa.net/detail/BIM-504624
American Medical Association (AMA)
Nurhayati, Nunung& Pasaribu, Udjianna S.& Neswan, Oki. Application of Generalized Space-Time Autoregressive Model on GDP Data in West European Countries. Journal of Probability and Statistics. 2012. Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-504624
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-504624