Spatiotemporal modelling of typhoon severity using backfitting cochrane-orcutt estimation

• Main Authors: Magtibay, Alexis Margaret Esperanza, Reyes, Aonee Jorvina, Santos, Mikaela Angela Cariaga
• Format: text
• Language: English
• Published: Animo Repository 2022
• Subjects: Typhoons > Philippines; Economics—Sociological aspects; Algorithms; Mathematics
• Online Access: https://animorepository.dlsu.edu.ph/etdb_math/9; https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1005&context=etdb_math
• Institution: De La Salle University

As one of the world’s most disaster-prone countries, Filipinos are heavily affected by the aftermath of natural disasters. Thus, this research aims to address the effects of socioeconomic and climatological factors on the severity of typhoons in the Philippines, as measured by the affected population, so as to improve disaster resilience in the country. A spatiotemporal model was fitted to the 2018 monthly data provided by NDRRMC, PSA, and PAGASA. Afterwards, a backfitting algorithm embedded with the Cochrane-Orcutt procedure was used to estimate the parameters. This model proved the significance of food expenditure and rainfall amount in measuring typhoon severity. Further, applying a spatiotemporal model using these significant variables is seen to be the best fit in the data. These results will be of great benefit to Filipinos and researchers alike as they would get a better understanding of the effects of typhoons in the Philippines.