The Effect of Economic Growth on The Human Development Index in Indonesia

This study aims to test and analyze the effect of economic growth on the Human Development Index in 34 provinces in Indonesia. This research uses quantitative data methods. The independent variable used in this study is economic growth with control variables, namely poverty and population. The dependent variable used is the Human Development Index. The data type used is panel data, a combination of time series and cross-section. Time series data was obtained from 2015-2020, and cross-section data was obtained from 34 provinces in Indonesia. The data used is secondary data sourced from the Central Statistics Agency (BPS) report, especially from 2015 to 2020. Hypothesis testing in this study uses multiple linear regression with the Chow test, Hausman test, t-test, f-test, and coefficient of determination test. The results show that economic growth had no significant effect on the Human Development Index in Indonesia in 2015-2020, Ceteris Paribus. The control variables of poverty and population influence the Human Development Index. The poverty control variable has a significant negative effect, and the population control variable has a significant positive impact. This study contributes new empirical evidence to fill gaps and address inconsistencies in the existing literature on the relationship between economic growth and human development.

Authors

Institutions

Publication Details

Journal
Journal of Economics Research and Social Sciences
Published
2024-08-20
DOI
https://doi.org/10.18196/jerss.v8i2.22627
Citations
4
Primary Topic
Economic Growth and Fiscal Policies
Type
article
Field-Weighted Citation Impact
4.52
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Effect of Economic Growth on The Human Development Index in Indonesia

Gea Dwi Asmara, Rahmat Saleh, Galuh Jati Asmara
4 citations
Journal of Economics Research and Social Sciences
Economic Growth and Fiscal Policies
4.52
article

The Effect of Economic Growth on The Human Development Index in Indonesia

Gea Dwi Asmara, Rahmat Saleh, Galuh Jati Asmara
article en
4 citations

Abstract

This study aims to test and analyze the effect of economic growth on the Human Development Index in 34 provinces in Indonesia. This research uses quantitative data methods. The independent variable used in this study is economic growth with control variables, namely poverty and population. The dependent variable used is the Human Development Index. The data type used is panel data, a combination of time series and cross-section. Time series data was obtained from 2015-2020, and cross-section data was obtained from 34 provinces in Indonesia. The data used is secondary data sourced from the Central Statistics Agency (BPS) report, especially from 2015 to 2020. Hypothesis testing in this study uses multiple linear regression with the Chow test, Hausman test, t-test, f-test, and coefficient of determination test. The results show that economic growth had no significant effect on the Human Development Index in Indonesia in 2015-2020, Ceteris Paribus. The control variables of poverty and population influence the Human Development Index. The poverty control variable has a significant negative effect, and the population control variable has a significant positive impact. This study contributes new empirical evidence to fill gaps and address inconsistencies in the existing literature on the relationship between economic growth and human development.

Journal of Economics Research and Social SciencesVol. 8(2)
Universitas Gadjah Mada (ID), Universitas Ahmad Dahlan (ID)
Openalex Percentile: Top 5%
Economic Growth and Fiscal Policies
4.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.