Forecasting Australia Gross Domestic Product (GDP) under Structural Change (SC) Using Break for Time Series Components (BFTSC)
Ajare Emmanuel Oloruntoba *
School of Quantitative Sciences, College of Art and Sciences, University Utara Malaysia, Malaysia and Department of Mathematical Sciences, Faculty of Sciences, Federal University Gusau, Gusau, Nigeria and Department of Mathematics and Statistics, Austin Peay State University, Clarksville, Tennessee, USA and Department of Statistics, University of Abuja (FCT), Nigeria.
Adefabi Adekunle
School of Quantitative Sciences, College of Art and Sciences, University Utara Malaysia, Malaysia and Department of Mathematics and Statistics, Austin Peay State University, Clarksville, Tennessee, USA.
Adeyemo Abiodun
Department of Statistics, University of Abuja (FCT), Nigeria.
*Author to whom correspondence should be addressed.
Abstract
The reason for this research is to enable us know the use BFTSC (break for time series components) in identification of the structural change and the time series components existing in Australia GDP. The data (Australia GDP) statistics spanned for period of fifty five years. The GDP of Australia is a higher information gotten from the StreamData of Universiti Utara Malaysia Library. The precincts of BFAST in terms of structural change was advanced to become BFTSC. BFTSC was created from basic research conducted on BFAST, results shows an innovative technique that captures the recurring (cyclicals) and non-recurring cyclical (irregular) components that was not included in the original BFAST technique and it was included in the methodology of this study. BFTSC was created to give a mutual image of all the required time series components. The subsequently forecasting technique was determined and forecast is made.
Keywords: Australia, break for time series components, seasonal data, gross domestic product, structural change, cyclical components, irregular components