The Modeling of The Poverty Rate In Indonesia From 2018 to 2023 Using A Panel Data Regression Approach

Dhyana Venosia; Toha Saifudin; Nur Chamidah

doi:10.36456/jstat.vol18.no1.a10139

Authors

Dhyana Venosia Airlangga University
Toha Saifudin Airlangga University
Nur Chamidah Airlangga University

DOI:

https://doi.org/10.36456/jstat.vol18.no1.a10139

Keywords:

Poverty Rate, Panel Data Regression, Random Effects Model

Abstract

Indonesia was ranked sixth out of eleven Southeast Asian countries with the highest poverty rate, highlighting the need for effective strategies to address poverty issues. The governmental strategy was aligned with the Sustainable Development Goals (SDGs), with the primary objective of achieving zero poverty. In this study, the poverty rate in Indonesia from 2018-2023 exhibited fluctuating trends, marked by both increases and decreases over the years. This phenomenon reflects the dynamic nature of poverty levels in the country. Poverty rates are assumed to be related to education and the economy. Referring to the statement, this study involves the percentage of poverty as the dependent variable and access to clean water access, gini ratio, open unemployment rate, and literacy rate as independent variables. Based on the structure of the research data, the dynamics of the poverty rate from 2018-2023 involve both cross-sectional and time series data structures. In this case, the panel data regression method based on the Random Effects Model is appropriate and can accommodate the identification process to the conclusion. This study aims to identify the factors that influence the poverty rate. Furthermore, the findings indicate that all independent variables have simultaneous and partial effects on the poverty rate.

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