Spatial clustering of environmental-economic nexus in Indonesia: A hierarchical agglomerative analysis of provincial disparities

Abstract

Background: Indonesia faces the paradox of development where economic growth is not followed by environmental quality improvement. Indonesia's environmental quality score (33.6) is well below the average of East Asian developing countries (40-45) despite gross domestic product (GDP) reaching USD 1,396.3 billion. Demographic pressure with a population of 286.7 million inhabitants exacerbates ecological degradation. Previous studies used a linear-aggregate approach that failed to capture the complexity of spatial interactions and heterogeneity between regions. Methods: this study used agglomerative hierarchical cluster analysis with Ward's method to classify 34 provinces based on Environmental Quality Index (EQI), gross regional domestic product (GRDP), and population density. Secondary data in 2023 from BPS and Bank Indonesia were analyzed using Euclidean distance and visualized through dendrograms to identify hierarchical structures with similar characteristics between provinces. Findings: The analysis identified two main clusters. Cluster 1 (30 provinces) has a high EQI (73.53), low GRDP (187,193.73), and low population density (205 peoples/km2). Cluster 2 (DKI Jakarta, West Java, Central Java, East Java) showed low EQI (59.49), high GRDP (1,666,813.67), and very high density (4,863 peoples/km2). The findings confirm the environmental Kuznets Curve hypothesis in Indonesia, with the island of Java hosting > 60% of the national population being the epicenter of ecological stress. Conclusion: spatial disparities in Environmental Quality are strongly influenced by the concentration of economic and demographic activities. Without structural economic transformation and technological modernization, provinces outside Java could potentially experience similar degradation as development accelerates. Novelty/Originality of this article: this study adopts an agglomerative hierarchical cluster approach that uncovers inter-provincial multiplier effects and spatial heterogeneity, providing an empirical basis for contextual and non-uniform sustainable development policies.