Spatial autoregressive quantile regression modeling of gross regional domestic product data in Java Island


Sulvirah Rahmi, - and Nurtiti Sunusi, - and Nirwan Ilyas, - (2025) Spatial autoregressive quantile regression modeling of gross regional domestic product data in Java Island. MethodsX 15 (2025) 103621.

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Abstract (Abstrak)

This study analyzes the Gross Regional Domestic Product (GRDP) data of Java Island to understand the region’s economic conditions and the key factors influencing GRDP. Java Island contributes the largest share to the national GRDP; however, the data show the presence of spatial dependence, spatial heterogeneity, and outliers. To address these issues, this study employs the Spatial Autoregressive Quantile Regression (SARQR) model. The findings show that the number of workers significantly influences GRDP across all quantiles, whereas Local Own-Source Revenue (LOSR), Regency/City Minimum Wage (RCMW), and the Human Development Index (HDI) only impact specific quantiles. The SARQR model demonstrates the best performance at the 0.6

Item Type: Article
Subjects: Q Science > Q Science (General)
Divisions (Program Studi): Fakultas Matematika dan Ilmu Peng. Alam > Matematika
Depositing User: - Andi Anna
Date Deposited: 22 Oct 2025 07:25
Last Modified: 22 Oct 2025 07:25
URI: http://repository.unhas.ac.id:443/id/eprint/50165

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