The geographic profiling of poverty and accessibility: The case of two provinces in the Philippines

• Main Authors: Fillone, Alexis M., Roxas, Nicanor, Dakila, Cristela Goce-
• Format: text
• Published: Animo Repository 2011
• Subjects: Poverty > Philippines > Siquijor Island; Poverty > Philippines > Samar Island; Social indicators > Philippines > Siquijor Island; Social indicators > Philippines > Samar Island; Economics; Growth and Development
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2122; https://animorepository.dlsu.edu.ph/context/faculty_research/article/3121/type/native/viewcontent
• Institution: De La Salle University

This study attempts to relate the poverty problem in the Philippines using spatial accessibility measures. Spatial accessibility is the ease with which one could avail of the social services and economic opportunities laid in geographic space to the individual. Using the provinces of Eastern Samar and Siquijor Island as case studies, a Social Composite Index (SCI) value for the household was derived from the 13+1 CBMS core indicators of poverty, which represents the unmet needs of the household and which was then aggregated at the barangay level. The spatial accessibility values were estimated by measuring how each barangay, specifically households, would avail themselves of the social services (such as schools and hospitals) and economic opportunities in the town center or major economic centers. The ease or difficulty of availing these social services and economic opportunities was estimated using the time variable in order to relate accessibility to the poverty indicators in the barangay. Multiple regression models were developed to relate poverty indicators to spatial accessibility measures and then tested to determine their impact on poverty. The tests showed that expected improvements in accessibility of more elementary schools in Siquijor would redound to a higher SCI or lower poverty levels. The planned merger of hospitals in Eastern Samar, revealed a lower SCI or an increase in poverty levels. Clearly, therefore, the link between poverty and accessibility could be established using CBMS data, and more importantly, could be used to predict the impact of planned social infrastructures on poverty levels. © 2011 De La Salle University, Philippines.