Poisson simultaneous autoregressive analysis of poverty in the Philippines using national household targeting system for poverty reduction (NHTS-PR) data

• Main Authors: Go, Ellaine Krishel SD., Tse Wing, Paula Margarita J.
• Format: text
• Language: English
• Published: Animo Repository 2018
• Subjects: Physical Sciences and Mathematics
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/18583
• Institution: De La Salle University

Creating or finding the most efficient solution to diminish the prevalence of poverty in the Philippines remains as one of the country's major struggles. This paper formulates a spatial model that could aid in poverty reduction using the NHTS-PR 2015 data to identify which indicator variables have significant relationships with poverty count. Given the use of count data for modeling, the Simultaneous Autoregressive (SAR) models were modified to include the Poisson regression approach in the estimation of parameters. The Poisson-SAR models were generated using the backfitting algorithm and were compared with the Ordinary Least Squares (OLS) model for model accuracy. It was found that the Poisson-SARerr model with regional and class dummy variables has the lowest Mean Absolute Percentage Error (MAPE) and provides the most accurate poverty map.