Modeling the Spatial Durbin Error Model on Open Unemployment Rate Data in Indonesia 2023

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Published: Sep 29, 2025
Keywords:
Spatial Durbin Error Model Maximum Likelihood Estimator The Lagrange Multiplier test Open Unemployment Rate Queen Contiguity Customized Contiguity

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Arbain
Statistics Study program, Department of Mathematics, Faculty of Mathematics Natural Sciences, Mulawarman University, East Kalimantan 75123, Indonesia
Memi Nor Hayati
Statistics Study program, Department of Mathematics, Faculty of Mathematics Natural Sciences, Mulawarman University, East Kalimantan 75123, Indonesia
Siti Mamuda
Statistics Study program, Department of Mathematics, Faculty of Mathematics Natural Sciences, Mulawarman University, East Kalimantan 75123, Indonesia

Abstract

This study applies the Spatial Durbin Error Model (SDEM) to analyze the factors in fluencing the Open Unemployment Rate (OUR) across 34 provinces in Indonesia in 2023. The model incorporates both direct effects and spatial spillover effects of the independent variables. The Maximum Likelihood Estimation (MLE) method was used for parameter estimation. The spatial weight matrix was constructed using a customized contiguity approach. The results show that the Labor Force Participation Rate (LFPR) and Gender Development Index (GDI) have significant direct effects on OUR, while Population Growth Rate (PGR) and GDI also exhibit significant spatial lag effects. The spatial autoregressive coefficient λ is 0.371, indicating significant spatial dependence in the error term. The model’s AIC value 104.750 is lower than the MLR model, confirming better model fit.

Article Details

How to Cite
Arbain, Nor Hayati, M. ., & Mamuda, S. (2025). Modeling the Spatial Durbin Error Model on Open Unemployment Rate Data in Indonesia 2023. Science & Technology Asia, 30(3), 189–198. retrieved from https://ph02.tci-thaijo.org/index.php/SciTechAsia/article/view/258009
Issue
Vol.30 No.3 (July-September 2025)
Section
Engineering
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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