The Impact of Human Development Index on Poverty Rates in Indonesia - Panel Data Analysis of 34 Provinces, 2015-2023

Q: What variables does the study examine to explain poverty rates in Indonesia?

The study analyzes the impact of Human Development Index (HDI), GRDP per capita, and the open unemployment rate (OUR) on poverty rates across 34 provinces from 2015-2023.

Q: Which econometric method is used, and why is it selected?

A fixed effects model is used for balanced panel data, with the model choice supported by Chow, Hausman, and Lagrange Multiplier tests.

Q: What are the key findings regarding HDI, GRDP per capita, and unemployment?

HDI has a significant negative effect on poverty, while GRDP per capita shows an even stronger negative relationship. The open unemployment rate is positive but only marginally significant.

Sep 20, 2026

Uploaded by Kyle

Poverty remains a persistent development challenge in Indonesia despite sustained macroeconomic growth. This study investigates the effect of the Human Development Index (HDI) on poverty rates across 34 provinces during 2015-2023 using balanced panel data regression with a fixed effects model selected via Chow, Hausman, and Lagrange Multiplier tests. HDI shows a significant negative relationship with poverty, while GRDP per capita has a stronger poverty-reducing effect. Open unemployment is positive but only marginally significant, with errors clustered at the provincial level. The model explains 74.2% of poverty variation and supports policies strengthening education quality, health coverage, inclusive growth, and productive employment.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Abstract / Article Info

Introduction

Research Objectives and Contributions

Poverty Data and Regional Determinants

Jurnal Ilmu Perbankan dan Keuangan Syariah Vol. 7, No. 2 (2025), page 372-388 p-ISSN: 2963-3524 e-ISSN: 2686-6625 Journal homepage: [http://jurnaljipsya.org/index.php/jipsya](http://jurnaljipsya.org/index.php/jipsya) The Impact of Human Development Index on Poverty Rates in Indonesia: Panel Data Analysis of 34 Provinces, 2015-2023 DedeArseyani Pratamasyari 1, Irham pakawaru 2, Nuriatullah 3, Noor Riefma Hidayah 4, Rizki Amalia5 1,2,3,4,5 Faculty of Economics and Islamic Business, Datokarama State Islamic University, Palu [Corresponding email:](Corresponding email: dede_arseyani@iainpalu.ac.id)[ dede_arseyani@iainpalu.ac.id](Corresponding email: dede_arseyani@iainpalu.ac.id) Leave it blank | Received: October 2025 | Revised: December 2025 | Published: December 2025 | | --- | --- | --- | | ABSTRACT | ARTICLE INFO | | --- | --- | | Poverty remains a critical development challenge in Indonesia despite significant economic growth over the past decades. This study examines the impact of Human Development Index (HDI) on poverty rates across 34 Indonesian provinces during 2015-2023. Using balanced panel data regression with fixed effects model (selected through Chow, Hausman, and Lagrange Multiplier tests), we analyze how HDI, GRDP per capita, and open unemployment rate affect poverty levels. The sample comprises 306 observations (34 provinces × 9 years) sourced from Statistics Indonesia (BPS) . Results indicate that HDI has a significant negative effect on poverty (coefficient: -0.0487, p<0.01), suggesting that a 10-point increase in HDI reduces poverty by approximately 0.49 percentage points. GRDP per capita shows a stronger elasticity (coefficient: -0.5623, p<0.01), with 1% increase in GRDP per capita reducing poverty by 0.562 percentage points. Standard errors are clustered at the provincial level to account for serial correlation and heteroskedasticity. The open unemployment rate exhibits a positive but marginally significant relationship with poverty (coefficient: 0.0876, p<0.10) . The fixed effects model explains 74. 2% of poverty variation (R² = 0. 742), indicating that human capital development through HDI improvements is crucial for sustainable poverty reduction. Policy recommendations include enhancing education quality, expanding health services coverage, promoting inclusive economic growth, and creating productive employment opportunities. This study contributes to the literature by providing comprehensive evidence from the postpandemic period and quantified elasticities useful for poverty reduction policy simulation. | Keywords:
Human Development Index; poverty; panel data; fixed effects model;
regional development; Indonesia | | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. | | Introduction Poverty remains a persistent challenge in Indonesia despite consistent macroeconomic growth over the past decade. Data from Statistics Indonesia (BPS) reveals that while the national poverty rate has declined, significant disparities exist across provinces ranging from single-digit rates in Java and Bali to over 20% in regions like Papua and Nusa Tenggara. This uneven distribution suggests that aggregate economic growth alone (trickle-down effect) has been insufficient to eradicate poverty uniformly, necessitating a deeper examination of regional determinants such as human capital quality and labor market dynamics. Theoretically, poverty reduction is driven by both income and non-income factors. Economic growth, represented by GRDP per capita, provides the necessary resources for poverty alleviation (Dollar & Kraay, 2002) . However, structuralists argue that growth without human capability improvement measured by the Human Development Index (HDI) is unsustainable (Sen, 1999) . Furthermore, labor market rigidities, manifested in the Open Unemployment Rate (OUR), directly sever households from income sources, exacerbating vulnerability. Understandin

FAQs

What variables does the study examine to explain poverty rates in Indonesia?

The study analyzes the impact of Human Development Index (HDI), GRDP per capita, and the open unemployment rate (OUR) on poverty rates across 34 provinces from 2015-2023.

Which econometric method is used, and why is it selected?

A fixed effects model is used for balanced panel data, with the model choice supported by Chow, Hausman, and Lagrange Multiplier tests.

What are the key findings regarding HDI, GRDP per capita, and unemployment?

HDI has a significant negative effect on poverty, while GRDP per capita shows an even stronger negative relationship. The open unemployment rate is positive but only marginally significant.

Sep 20, 2026

Uploaded by Kyle