Abstract
As located within the Ring of Fire with more than half of the volcanoes are active making Indonesia as one of the most vulnerable countries to natural disasters. Moreover, Indonesia was ranked 12th of 35 countries with the highest risk from natural disasters by the World Bank in 2021. Such multiple disasters could hamper the Indonesian economy through disaster loss. This study is conducted to investigate the impact of several natural disasters, including hydrological, meteorological, climatological, and geophysical, on Indonesian economic growth of 34 provinces in Indonesia from 2018 to 2022 represented by annual per capita real output growth. While the disaster damages are measured by the number of affected people and the number of damaged infrastructures. The econometric approach of panel data analysis is employed and further extended to the additive mixed model with P-spline smooth function to capture the non-linear relationship. The human development index (HDI) and financial realization of the unexpected budget are also incorporated in the models. The results show that the best model, the P-spline model, could capture the nature of the non-linear relationship between natural disasters and economic growth. In addition, the estimation process is also carried out separately for each group based on the HDI and financial ability. The variation of impact behaviour from natural disasters is clearly revealed by modelling each group based on HDI and financial ability indicating that each provincial group has a different impact transmitted by the natural disasters.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Purwa, Taly taly@bps.go.id Wibowo, Wahyu UNSPECIFIED Abdul Bahri, Elya Nabila UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Multivariate analysis. Cluster analysis. Longitudinal method > Regression analysis. Correlation analysis. Spatial analysis (Statistics) |
Divisions: | Universiti Teknologi MARA, Perlis > Arau Campus |
Journal or Publication Title: | Journal of Computing Research and Innovation (JCRINN) |
UiTM Journal Collections: | UiTM Journal > Journal of Computing Research and Innovation (JCRINN) |
ISSN: | 2600-8793 |
Volume: | 9 |
Number: | 2 |
Page Range: | pp. 59-71 |
Keywords: | Catastrophic Disaster, Economic Growth, Spline Regression, Panel Data |
Date: | September 2024 |
URI: | https://ir.uitm.edu.my/id/eprint/102739 |