مجلة الدراسات القانونية والاقتصادية
Volume 8, Numéro 2, Pages 1380-1391
2025-12-20
Classifying Islamic Countries By Governance Indicators Through Pca And Model-based Clustering (mclust)
Authors : Bouatelli Mohamed .
Abstract
This study aims to classify 57 Islamic countries based on their governance performance for the year 2023. Relying on six key governance indicators from the World Bank namely Control of Corruption, Government Effectiveness, Political Stability and Absence of Violence/Terrorism, Regulatory Quality, Rule of Law, and Voice and Accountability, the study adopts a two-stage analytical approach. First, Principal Component Analysis (PCA) is used to reduce the dimensionality of the data while retaining most of its variance. Then, Model-Based Clustering is performed using the MCLUST algorithm in the R environment to uncover latent governance-based groupings. The results identify two distinct clusters: the first includes 48 countries characterized by heterogeneous and generally lower governance scores, while the second comprises 9 countries with relatively high and consistent institutional performance. These findings highlight the significant governance disparities across the Islamic world and underscore the urgent need for institutional reforms focused on transparency, regulatory quality, and administrative effectiveness.
Keywords
Governance ; Governance Indicators ; Islamic Countries ; Model-Based Clustering ; PCA ; MCLUST
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