Gender Inequality Index Modeling in Indonesia Using Geographically Weighted Panel Regression Method

DOI

10.2991/978-94-6463-228-6_34How to use a DOI?

Keywords

Panel Data Regression; GWPR; Gender Inequality Index; Adaptive Kernel Bisquare

Abstract

The Gender Inequality Index (GII) is an index that describes the failure of human development achievement due to the inequality of gender that is measured by several aspects such as health, empowerment, and labor market access. The Geographically Weighted Panel Regression (GWPR) is a developed model which amalgamates the GWR model with panel data regression. The GWPR is used to address spatial heterogeneity problems in panel data. This study aims to determine the results of the GII modeling in Indonesia using the GWPR and their several influenced factors. The results of the GII modeling using the GWPR with adaptive kernel bisquare weighted functions produce different model equations at each location. The GWPR model produced an R² of 73.97% with factors that significantly affect the GII including the percentage of people aged over 10 years who have no school (X₂), the percentage of non-health facilities of childbirth (X₃), the percentage of women sitting in parliament (X₄), DI (X₅), GDI (X₆), OUR (X₇) and LFPR (X₈). Moreover, given an example, by the assumption of other variables are ignored the GII of Central Sulawesi Province in the t-th year will decrease by 0.0296. Moreover, the increase of 1% of women sitting in parliament (X₄) in the t-th year by the assumption of ignoring other variables, will then decrease the GII by 0.0524. In addition, the increase of 1 unit of HDI (X₅) in the t-year by assuming other variables are ignored, will decrease the GII by 1.7063.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Khaira Umi
AU  - Junaidi
AU  - Fadjryani
PY  - 2023
DA  - 2023/08/22
TI  - Gender Inequality Index Modeling in Indonesia Using Geographically Weighted Panel Regression Method
BT  - Proceedings of the 4th International Seminar on Science and Technology (ISST 2022)
PB  - Atlantis Press
SP  - 303
EP  - 311
SN  - 2352-541X
UR  - https://doi.org/10.2991/978-94-6463-228-6_34
DO  - 10.2991/978-94-6463-228-6_34
ID  - Umi2023
ER  -