Comparative Study of Conventional and Spatial Panel Models in Analyzing the Information and Communication Technology Development Index

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Authors: Toha Saifudin, Citrawani Marthabakti, Ezha Easyfa Wieldyanisa
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Abstract

Indonesia continues to face digital inequality, both in terms of inter-provincial disparities and in comparison, toother countries in Southeast Asia, where it lags behind Vietnam and is far below Singapore. These disparities highlight spatialheterogeneity, where regional characteristics influence by Information and Communication Technology (ICT) capacitydifferently, and spatial dependence, where development in one province can spill over to others. Given the strategicimportance of ICT in driving sustainable growth, overcoming such inequality is crucial. This challenge is also stronglylinked to SDG 9 and SDG 10, which emphasize inclusive digital development as a pathway to reducing gaps across regions.This research seeks to examine the determinants affecting Information and Communication Technology Development Index(ICT-DI) across Indonesian province by contrasting traditional panel data models with spatial panel modeling techniques.Secondary data from Central Bureau of Statistics (Indonesia) for 2020-2023 were used. Descriptive analysis and thematicmapping were conducted, followed by estimation using the panel model, as well as spatial panel models including SpatialAutoregressive Fixed Effect (SAR-FE) and Spatial Error Model Fixed Effect (SEM-FE). The results indicate significantspatial dependence across provinces, confirming the relevance of spatial analysis. The SAR-FE model was identified asthe best model, explaining 98.47% of the variation in ICT-DI with the lowest MAPE value (1.1023). Population densitywas identified as the only significant positive factor, indicating that more densely populated regions tend to have betterICT infrastructure and capacity. The findings emphasize the novelty of applying spatial panel models to ICT analysis inIndonesia and underline their policy relevance. Considering dependence and heterogeneity enables policymakers to designmore inclusive and sustainable strategies, tailored to the unique priorities of each province, to reduce digital inequality.

Fields of Study & Subjects

Spatial and Panel Data Analysis ICT Impact and Policies Regional Economic and Spatial Analysis

Publication details

Journal / source
Statistics Optimization & Information Computing
Volume
15
Issue
5
Pages
3539–3554
Publication date
27 January 2026