Forecasting Regional Trends of Land-Based Overseas Filipino Workers in the Philippines through ARIMA Modeling

Abstract

This study employs K-means clustering and AutoRegressive Integrated Moving Average (ARIMA) modeling to analyze and forecast regional trends in the employment of land-based Overseas Filipino Workers (OFWs) in the Philippines. The Department of Migrant Workers (DMW) provided official data from 2022 to 2025, which was used to group regions with similar deployment patterns and make a five-year prediction for 2029. The clustering process revealed three distinct clusters: Cluster 1 (High Deployment) comprises Region III (Central Luzon), Region IV-A (CALABARZON), and Others (NEC); Cluster 2 (Lower/Variable Deployment) is composed of Regions IV-B (MIMAROPA), V, VIII, IX, X, XI, XII, XIII (Caraga), BARMM, and CAR ; and Cluster 3 (Moderate/Growing Deployment) includes the NCR, Region I, Region II, Region VI, and Region VII. The ARIMA time-series forecasts indicated divergent regional trends: deployment in regions like BARMM is predicted to see a substantial increase, while areas like Region IV-A and Region VII are forecasted to decline significantly. These results support data-driven labor planning and suggest the need for targeted policy actions in regions with varying growth rates.