Analisis Tingkat Kesenjangan Pendapatan antar Provinsi di Indonesia Menggunakan Regresi Data Panel Model Pengaruh Tetap

Authors

  • Thooriq Ghaith Department of Statistics, IPB
  • Hari Wijayanto Department of Statistics, IPB
  • Anang Kurnia Department of Statistics, IPB

DOI:

https://doi.org/10.29244/xplore.v7i3.125

Keywords:

Gini ratio, MAPE, panel data regression, provincial fixed effect model

Abstract

THOORIQ GHAITH. Analysis of Income Disparity Rates among Provinces in Indonesia Using Panel Data Regression. Supervised by HARI WIJAYANTO and ANANG KURNIA.

 

Income disparities in Indonesia generally and in each province particularly is a serious problem from year to year. It is necessary to find out the factors that affect the income disparity rates (Gini ratio) to be taken into consideration in determining the economic policy. By using data of 33 provinces from 2007 until 2016, panel data regression with provincial fixed effect model approach was used to determine factors that affect Gini ratios in Indonesia and to capture the differences of Gini ratio characteristics of each province in form of intercept. Modeling was done for whole Indonesia and for five regions as well to find out what factors that affect the Gini ratio of provinces in Indonesia generally and what factors affect Gini ratios of provinces in each region particularly. The percentage of poor people is a significant factor to Gini ratio in the model throughout Indonesia and in the model of each region, except in Sumatera. Beside the percentage of the poor people, other explanatory variables affecting Gini ratios are GDP growth rates in Kalimantan, open unemployment rates in Sulawesi, and provincial minimum wage in Nusa Tenggara, Maluku and Papua. All of the predicted models are good enough because they produce MAPE values below 10%.

Published

2019-01-02

How to Cite

Ghaith, T., Wijayanto, H., & Kurnia, A. (2019). Analisis Tingkat Kesenjangan Pendapatan antar Provinsi di Indonesia Menggunakan Regresi Data Panel Model Pengaruh Tetap. Xplore: Journal of Statistics, 7(3). https://doi.org/10.29244/xplore.v7i3.125

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