2019•Eurasian Journal of Forest ScienceOpen access

The forecasting of the exports and imports of paper and paper products of Turkey using Box-Jenkins method

Nadir Ersen, İlker Akyüz, Bahadır Çağrı Bayram

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Abstract

In this study, it is aimed to determine the most suitable time series models with Box-Jenkins method, which is the most widely used in prediction studies. Export and import values have been predicted by 2020 with the most suitable models. The data used in this study were obtained from the Turkey Statistical Institute. Data are monthly data covering from January 2003 to December 2014. Sum of Squared Errors (SSE) and Mean Squared Error (MSE) criteria were taken into consideration when selecting the best Box-Jenkins models. Also, in order to test the success of forecasting of the models, Root mean Error Square (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were used. As a result of the analyzes, it was determined that the most suitable models for export and import data were ARIMA (2,1,0) (0,0,1)12 and ARIMA(3,1,2)(1,0,1)12. It was predicted that the rate of exports meeting imports in paper and paper products of Turkey will be approximately 0.86 in 2020.

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What this paper is about

In this study, it is aimed to determine the most suitable time series models with Box-Jenkins method, which is the most widely used in prediction studies. Export and import values have been predicted by 2020 with the most suitable models. The data used in this study were obtained from the Turkey Statistical Institute. Data are monthly data covering from January 2003 to December 2014. Sum of Squared Errors (SSE) and Mean Squared Error (MSE) criteria were taken into consideration when selecting the best Box-Jenkins models. Also, in order to test the success of forecasting of the models, Root mean Error Square (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were used. As a result of the analyzes, it was determined that the most suitable models for export and import data were ARIMA (2,1,0) (0,0,1)12 and ARIMA(3,1,2)(1,0,1)12. It was predicted that the rate of exports meeting imports in paper and paper products of Turkey will be approximately 0.86 in 2020.

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Available abstract

In this study, it is aimed to determine the most suitable time series models with Box-Jenkins method, which is the most widely used in prediction studies. Export and import values have been predicted by 2020 with the most suitable models. The data used in this study were obtained from the Turkey Statistical Institute. Data are monthly data covering from January 2003 to December 2014. Sum of Squared Errors (SSE) and Mean Squared Error (MSE) criteria were taken into consideration when selecting the best Box-Jenkins models. Also, in order to test the success of forecasting of the models, Root mean Error Square (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were used. As a result of the analyzes, it was determined that the most suitable models for export and import data were ARIMA (2,1,0) (0,0,1)12 and ARIMA(3,1,2)(1,0,1)12. It was predicted that the rate of exports meeting imports in paper and paper products of Turkey will be approximately 0.86 in 2020.

Key concepts: Box–Jenkins, Autoregressive integrated moving average, Mean squared error, Mean absolute percentage error, Statistics, Mean absolute error, Econometrics, Mathematics

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