Statistical Analysis and Forecasting of the Number of Students, Teachers and Graduates in Romania’s Pre-University Education System

This study examines the evolution and main trends in the number of students, teaching staff and graduates in Romania’s pre-university education system over the period 1990–2024 (and 1990–2023 for graduates), employing ARIMA models to generate forecasts up to the year 2027. The research is grounded in the premise of profound structural transformations within the Romanian educational system, driven by demographic decline, external migration, recurrent reforms, and shifts in resource allocation. The descriptive analysis highlights a pronounced downward trend for all three variables (students, teaching staff and graduates), reflecting the continuous reduction in the school-age population and the restructuring of the educational network. The statistical tests employed, such as Shapiro–Wilk, Augmented Dickey–Fuller, Durbin–Watson, Breusch–Godfrey and ARCH, validate the selected optimal ARIMA models: ARIMA(1,1,1) for teaching staff, ARIMA(4,1,3) for students, and ARIMA(3,1,5) for graduates. The forecasting results indicate that this declining trend is expected to persist through 2027: the number of teaching staff is estimated to decrease to approximately 178,700 individuals, the number of students is estimated to decrease to around 2.78 million, and the number of graduates is projected to fall until 2026, followed by a potential slight stabilization in 2027. The Spearman correlation analysis indicates strong associations among all variables, suggesting that their dynamics are predominantly shaped by demographic and migratory factors. Granger causality analysis shows that changes in birth rates lead to rapid adjustments in teaching staff within 2–3 years. No significant short-term causality is found for the number of students or graduates, though demographic effects appear after 5–6 years for students, indicating long-term impacts on the school population. This study underscores the importance of econometric methods in informing educational policy, particularly in the context of the marked contraction of the school-age population. It also highlights the need for strategic planning regarding human resources in education, per-student funding, the reorganization of the school network, and curriculum adaptation.