Synergies, Trade-offs, and Structural Pathways: A Directed Network Approach to SDG Prioritisation

Abstract

To successfully implement the Sustainable Development Goals (SDGs), it is necessary to understand the process by which the achievement of one goal has a spillover effect in a development system. While existing research studies synergies and trade-offs among the SDGs, most empirical approaches operate at the goal level, treat interactions as undirected, or prioritise indicators without accounting for structural redundancy. In this paper, we propose a direction-sensitive and indicator-level network approach to detect high-impact and diversified entry points for policy intervention. By using statistically significant lagged correlations, we build a directed weighted network of SDG indicators and assign them into groups based on the balance of their positive and negative spillovers. Systemic effects are measured by weighted out-degree Opsahl centrality, and flow-based clustering is used to detect frequent paths of high positive spillovers. Applying the framework to the Indian context, it is found that the interlinkages in the SDGs are highly asymmetric and structured in specific structural subsystems. Although synergies slightly outweigh the total, trade-offs are still embedded in the sectors. Notably, the most influential indicators are focused on a single pathway of propagation, suggesting that influence-based prioritisation itself could result in redundant system-wide impacts. A cluster-based prioritisation approach leads to a more diversified set of interventions, triggering multiple structurally independent channels of beneficial spillovers. The proposed framework combines directionality, trade-off embedding, and structural propagation analysis in a single framework, providing a scalable solution for country-level SDG prioritisation under resource constraints.