What Beyond Massification? Forecasting The Future Of Enrollment In Algerian Higher Education Using Arima Approach

Résumé: The demand for higher education in Algeria is expanding rapidly, and accurate forecasting methods are necessary for planning its future. This paper aims to investigate whether data on the student population in higher education can be adjusted to Auto Regressive Integrated Model (ARIMA) for forecasting the future trend until 2030. The author compares three ARIMA models in terms of their fit indices and analysis of residuals. The process of estimation and model selection is conducted using the 'auto.arima' function from the ‘fpp2’ package in the statistical software, 'R'. The data consists of the annual recorded population of students from 1963 to 2022, obtained from relevant national and international bodies. The results show a continuous upward demand for higher education in the upcoming years, slightly exceeding two million in 2030. This finding has direct implications on planning the resources to be deployed for the higher education sector on a national level.

Publié dans la revue: مجلة أبحاث ودراسات التنمية - Revue Recherches et Etudes en Développement -