Bayesian mapping of poverty prevalence in the city of Pasay, Philippines, 2005

• Main Authors: Ocampo, Shirlee R., Alfonso, John Jason, Carangian, Erlo Franco
• Format: text
• Published: Animo Repository 2009
• Subjects: Poverty—Philippines—Pasay City—Mathematical models; Demography, Population, and Ecology
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/9429
• Institution: De La Salle University

Mapping of poverty prevalence has been an essential tool which may identify high poverty incidence areas where intervention or programs from government or nongovernmental institutions are needed. To help the government achieve its goal of reducing poverty prevalence in the country, local government units should be able to implement programs to help areas of high poverty rates. This study generated poverty maps using poverty incidence that could aid in the planning of local community welfare development programs in the city of Pasay. This study also applied Bayesian hierarchical models in generating poverty prevalence using 2005 Community Based Monitoring System (CBMS) data in Pasay City. Poisson regression model was utilized to determine significant correlates and to predict poverty incidence using significant correlates.