Macroeconomic Determinants of International Tourism Arrivals in the Philippines
Authors
Joshua B. Magbago
Graduating Students, Bachelor of Arts in Economics, College of Arts and Sciences, Bukidnon State University (NO)
Melesa C. Cabusas
Graduating Students, Bachelor of Arts in Economics, College of Arts and Sciences, Bukidnon State University (PH)
Adriane John P. Luncido
Graduating Students, Bachelor of Arts in Economics, College of Arts and Sciences, Bukidnon State University (PH)
Article Information
DOI: 10.51583/IJLTEMAS.2026.150300045
Subject Category: Tourism
Volume/Issue: 15/3 | Page No: 550-568
Publication Timeline
Submitted: 2026-04-09
Published: 2026-04-09
Abstract
Tourism is a major driver of the Philippine economy, contributing significantly to employment, income generation, and regional development. Despite its importance, empirical modeling of international tourism demand in the Philippines remains limited. This study addresses this gap by estimating a tourism demand function using two econometric approaches—Ordinary Least Squares (OLS) and Seemingly Unrelated Regression (SUR)—to examine the macroeconomic determinants of international tourist arrivals. The analysis focuses on the top five source markets—South Korea, the United States, Japan, China, and Australia—using annual time-series data from 2007 to 2023. Data were sourced from the Department of Tourism, World Bank, Philippine Statistics Authority, EM-DAT, and the Bangko Sentral ng Pilipinas. Descriptive results reveal a steady increase in tourist arrivals from 2007 to 2019, followed by a sharp decline during the COVID-19 pandemic (2020–2021), and a gradual recovery beginning in 2022 with the easing of global travel restrictions. Econometric findings indicate that real per capita income and exchange rates positively and statistically significantly affect tourism demand, while relative prices and crime rates negatively affect arrivals. Notably, the frequency of natural disasters exhibits a moderate positive association with tourism demand, possibly reflecting post-disaster reconstruction efforts and intensified tourism promotion. Comparative results show that the SUR model yields more efficient and consistent estimates than OLS, due to the presence of contemporaneous correlation across country-specific equations. Overall, the findings underscore the interdependence of tourism demand across major source markets and provide policy-relevant insights for enhancing the competitiveness and resilience of the Philippine tourism sector.
Keywords
Contemporaneous correlation, demand, generalized least squares, seemingly unrelated regression (SUR), tourism arrivals
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