Modeling Internal Migration Dynamics Through Markov Chains: Empirical Findings of Long-Term Population Redistribution in Antipolo City

Internal migration shapes population distribution, urban growth, and local development in rapidly urbanizing areas. Anchored on Lee's Push–Pull Theory of Migration, this study modeled internal migration dynamics among the sixteen barangays of Antipolo City, Rizal, Philippines, using Markov Chain analysis to examine migration transitions and long-term population redistribution. It determined transition probabilities, steady-state probabilities, and expected population distribution; identified Economic and Non-Economic Push and Pull factors influencing migration decisions; and assessed significant differences among these factors. An applied quantitative, non-experimental, descriptive-analytical design was used. Data were gathered from 384 qualified internal migrants selected through proportionate stratified random sampling. Frequency and percentage distribution, weighted mean, Kruskal-Wallis test, Dunn's post hoc test with Bonferroni correction, and Markov Chain modeling were applied. Findings showed that migration decisions were influenced more strongly by destination-side attractions than by origin-based pressures. Better livelihood or business opportunities, better employment and income opportunities, and better and more affordable housing options emerged as leading pull factors, while high cost of living and low income or financial difficulty were the main economic push factors. The Kruskal–Wallis results showed significant differences among all factor groups. Markov Chain results indicated convergence toward San Roque, San Isidro, and Cupang. The findings emphasize integrating migration analytics into local planning for infrastructure, housing, livelihood, service delivery, and governance interventions.