Answers are grounded in this paper and cite their sources.
Panel data regression analysis reveals that UMP and HDI reduce poverty in Indonesia, suggesting targeted policies.
The purpose of this study is to evaluate the influence of UMP, HDI, and road length on poverty rates in several provinces in KTI from 2017 to 2023. This study uses secondary data. The analysis method is panel data regression, and the model is FEM. The results of the study show that the UMP and HDI variables have a negative and significant impact on the poverty rate. On the other hand, the length of the road does not show a significant effect on the poverty rate. These findings imply that poverty alleviation policies in the Eastern Region of Indonesia need to be focused on improving human quality and minimum wage protection, as well as encouraging more inclusive and sustainable infrastructure development.
No takes yet. Share an insight, caveat, or question.
Kurniawan et al. (2025) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: