Title:
Sub-Annual Change Detection in Eritrea Gross Domestic Product (GDP) Using Innovative Breed Technique.

Authors:
Ajare Emmanuel Oloruntoba, Ahmadu Charles, Attah Hamid Onimisi, Alabi Olushola Mumini ,Adefabi Adekunleb, Akogun Haruna Isiaka, Ilara Sunday Olorunyomi,, Nigeria

Abstract:

The main objective of this study is to examine the phenomenon, Structural change in the gross domestic product of Eritrea,  forecast and recommend for future adjustment. Gross fixed capital formation (% of GDP). Eritrea Gross Domestic Product (GDP) data was obtained from the data stream of Universiti Utara Malaysia library.  In the methodology, BFAST (Break for additive, Season and trend) and BFTSC (Break for time series components) was used to examine the structural change,  time series components present in the data  (Eritrea  GDP) using R and Python software. BFTSC was created to capture the trend, seasonal, cyclical and irregular components as a combined image and to present them in a single plot.  The result obtained, model acquired from the components (pattern) extracted using BFTSC was subsequently process for forecasting purposes and recommendation follows.

DOI: http://dx.doi.org/10.51505/ijaemr.2025.1501