Using Box-Jenkins Methodology For Forecasting The Numbers Of Arrivals Through Syrian-Lebanese Border Crossings
Abstract
This research includes a study of ARIMA models for the forecasting of the numbers of arrivals through border crossings of Syrian- Lebanese according to a monthly time series during the period 2014-2017. Because the activity of border crossings positively affects the economy of countries, and the forecasting of this activity helps decision makers to take appropriate decisions to improve the performance of border crossings.
The BOX-Jenkins methodology was used to build a model of the time series. There are trend and seasonal components. Seasonal components were deleted, but the trend is included in the model.
Then we chose the best model to predict numbers for future arrivals through border crossings of Syrian- Lebanese for time series of one month in year 2018 (i.e. January) using statistical software EVIEWS. The best model for forecasting was ARIMA(0,0,1).
يهدف البحث إلى دراسة نماذج ARIMA للتنبؤ بأعداد القادمين عبر المعابر الحدودية السورية- اللبنانية حسب الأشهر وذلك وفق سلسلة زمنيّة شهرية خلال الفترة 2014- 2017، لأن نشاط المعابر الحدودية يؤثر إيجاباً على اقتصاديات الدول، كما أن التنبؤ بهذا النشاط يساعد متخذي القرارات على اتخاذ قرارات مناسبة لتحسين أداء المعابر الحدودية.
وتم استخدام منهجية بوكس- جنكينز في بناء نموذج للسلسلة الزمنية، ومن ثم اختيار أفضل نموذج للتنبؤ بالأعداد المستقبلية للقادمين عبر المعابر الحدودية السورية- اللبنانية، وقد وجدنا أن هناك مركبة اتجاه عام، ومركبات موسمية. تم حذف المركبات الموسمية وتضمين مركبة الاتجاه العام في النموذج.
وقد تم إجراء التنبؤ على السلسلة الزمنية الخاصة لشهر واحد في سنة 2018 (أي كانون الثاني) باستخدام البرنامج الإحصائي Eviews، وقد وجد أن أفضل نموذج للتنبؤ هو ARIMA(0,0,1).
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