Simulating poverty reduction strategy with the use of regression modeling and spatial analysis

• Main Author: Tan, Kent Robinson
• Format: text
• Language: English
• Published: Animo Repository 2010
• Subjects: Poverty > Simulation methods; Regression analysis; Spatial analysis (Statistics); Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/3998; https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10836/viewcontent/CDTG004878_P.pdf
• Institution: De La Salle University

This research is about developing a system using regression modelling to create poverty models and combine with spatial analysis that can simulate poverty reduction strategies. Statistical Package for the Social Sciences (SPSS) was used to generate the poverty models applying regression modeling on Community-Based Monitoring System (CBMS) data with 14 poverty indicators. Simulations were done using the data from Pasay Metro Manila in order to see the effects of variables to poverty models. Results were presented in numerical and graphical form using maps. The results were able to show meaningful results that can assist the officials in setting priorities and identifying beneficiaries when planning their programs.