Application of Threshold Autoregressive Model: Modeling and Forecasting Using U.S. Export Crude Oil Data
Document Type : Original Article
Authors
1 Laboratory MSTD, Faculty of Mathematics, USTHB Algiers, Algeria
2 Department of Mathematics and Informatics, University of Mila, Algeria
Abstract
This work focuses on the specification of the threshold autoregressive model and forecasting. We
consider U.S. Export is the amount of oil exported from January 1991 to December 2004. We
present threshold models that are special cases of the procedure for non-linear models on average
above TAR (threshold autoregressive). This means that we start with a simple model and we use
a more complicated model if the diagnostic tests indicate that the model obtained is not
satisfactory. We will use this procedure to compare an approach of ARMA models and approach
the nonlinear threshold for the series. Between the two methods, the prediction threshold
autoregressive model is better in the mean square error.
consider U.S. Export is the amount of oil exported from January 1991 to December 2004. We
present threshold models that are special cases of the procedure for non-linear models on average
above TAR (threshold autoregressive). This means that we start with a simple model and we use
a more complicated model if the diagnostic tests indicate that the model obtained is not
satisfactory. We will use this procedure to compare an approach of ARMA models and approach
the nonlinear threshold for the series. Between the two methods, the prediction threshold
autoregressive model is better in the mean square error.
Keywords
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