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Forecasting Algeria’s unemployment rates using SARIMA model in python programming : during 2001-2021
Joint Authors
Ibn Ayyad, Wafa
Hulaymi, Wahiba
Source
Forum for Economic Studies and Research Journal
Issue
Vol. 6, Issue 1 (30 Jun. 2022), pp.586-600, 15 p.
Publisher
Publication Date
2022-06-30
Country of Publication
Algeria
No. of Pages
15
Main Subjects
Topics
Abstract EN
Unemployment is one of the major economic, social and political problems that all the countries of the world are seeking to reduce its severity and to guard against his negatives effects on economy.
On that basis, this study aimed to model and to forecast monthly unemployment rates in Algeria using Seasonal Auto Regressive Integrated Moving Average Model (SARIMA), which is one of the crucial and most widely used forecasting models for univariate time series data forecasting that takes into account seasonal elements.
Depending on modern python programming, the expected results indicated that among the suggested models, SARIMA Model (5.
1.
3) (1.
0.
0) has got good performance, and it has been statistically accepted.
The forecasting findings during the 12 months of 2021, indicate that a steady enormous increase of the unemployment rates.
American Psychological Association (APA)
Ibn Ayyad, Wafa& Hulaymi, Wahiba. 2022. Forecasting Algeria’s unemployment rates using SARIMA model in python programming : during 2001-2021. Forum for Economic Studies and Research Journal،Vol. 6, no. 1, pp.586-600.
https://search.emarefa.net/detail/BIM-1403784
Modern Language Association (MLA)
Ibn Ayyad, Wafa& Hulaymi, Wahiba. Forecasting Algeria’s unemployment rates using SARIMA model in python programming : during 2001-2021. Forum for Economic Studies and Research Journal Vol. 6, no. 1 (Jun. 2022), pp.586-600.
https://search.emarefa.net/detail/BIM-1403784
American Medical Association (AMA)
Ibn Ayyad, Wafa& Hulaymi, Wahiba. Forecasting Algeria’s unemployment rates using SARIMA model in python programming : during 2001-2021. Forum for Economic Studies and Research Journal. 2022. Vol. 6, no. 1, pp.586-600.
https://search.emarefa.net/detail/BIM-1403784
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 599-600
Record ID
BIM-1403784