Work

Forecasting school enrollments in the Australian Capital Territory

Year: 2024

Type: article

Abstract: School enrollment forecasts are vital for effective planning. This study introduces a probabilistic multiregional population projection model, which accounts for different components, including preschool entries, migration, grade progression, and graduations. Using different distributions with a cohort component projection and Monte Carlo simulation, this paper forecasts student enrollments for each school and academic year level in the Australian Capital Territory based on the annual record-level administrative data. In the in-sample validation tests, the model’s overall performance is robust, and the probabilistic design offers reliable prediction intervals reflecting the variation in observed values. The paper ends with a discussion on the importance of prediction intervals for informing school planning.

Source: Journal of the Royal Statistical Society Series A (Statistics in Society)

DOI: 10.1093/jrsssa/qnae094

Authors: Tianyu Shen, James Raymer, Caroline Hendy

Institution: Australian National University

Language: English

Topic: Insurance, Mortality, Demography, Risk Management

Subfield: Demography

Field: Social Sciences

Domain: Social Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $3,518