Forecasting Number of Births in the Philippines Using Seasonal Autoregressive Integrated Moving Average (SARIMA) Model

The phenomenon of birth decline is a significant demographic challenge impacting nations worldwide which poses potential issues such as labor force shortages and an aging population. Lessening the negative effects necessitates the accurate projection of the number of births. Such projections are important in anticipating demand and allocating sufficient resources, as they provide a more actionable basis for planning and decision-making in areas such as health, social services, and education. Related studies focus only on forecasting birth rates and not on the actual number of births, which presents a research gap in the field. This study aims to address this gap by formulating a Seasonal Autoregressive Moving Average (SARIMA) model to forecast the number of births in the Philippines. Using the Box-Jenkins methodology, the SARIMA (2,1,2) (0,1,1) 12 was identified as the most suitable model based on the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and corrected AIC (AICc) scores among the potential models. The chosen model also obtained a 5.5% Mean Absolute Percentage Error (MAPE), indicating a highly accurate forecast. The SARIMA model effectively captured the seasonality of births, characterized by a peak from September to October. The forecast predicts a continued decline in birth numbers over the next five years, with an estimated 10.96% decrease from 2024 to 2028.