Agboluaje, Ayodele Abraham and Ismail, Suzilah and Chee Yin, Yip (2016) Modelling the Error Term of Australia Gross Domestic Product. Journal of Mathematics and Statistics, 12 (4). pp. 248-254. ISSN 1549-3644

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Abstract

The main aim of this study is to model the Gross Domestic Product (GDP) with the new Combine White Noise (CWN) Model and compare the results with the Vector Autoregressive (VAR) Model and Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) Model which are the existing models. The CWN model estimation yields best results with least information criteria and high log likelihood values. While the EGARCH model estimated yields better results with least information criteria and high log likelihood values when compared with VAR model. CWN has the least forecast errors which are indications of best results when compare with the EGARCH and VAR models, dynamic evaluation forecast errors. The minimum forecast error values indicate forecast accuracy. The determinant of the residual of the covariance matrix value indicates that CWN is efficient, while the determinant of the residual of the covariance matrix value indicates that VAR is not efficient. The total results testify that CWN is the most right model. To model the data that exhibit conditional heteroscedasticity with leverage effect in Australia and other societies in the world efficiently, CWN is recommended

Item Type:	Article
Uncontrolled Keywords:	Combine White Noise, Determinant of the Residual of Covariance, Efficient, Forecast Accuracy, Log Likelihood
Subjects:	Q Science > QA Mathematics
Divisions:	School of Quantitative Sciences
Depositing User:	Mdm. Sarkina Mat Saad @ Shaari
Date Deposited:	04 Jul 2024 03:26
Last Modified:	04 Jul 2024 03:26
URI:	https://repo.uum.edu.my/id/eprint/30984

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