arXiv subjects

Gaurav Kottari

Publications and source records attributed to Gaurav Kottari.

4 recordsLinked to original sources

arXiv2026

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

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.

math.DS↗

arXiv2026

A Network-Based Framework to Identify Synergies and Trade offs among SDG Indicators

Achieving the United Nations Sustainable Development Goals (SDGs) requires an understanding of the complex interlinkages that exist among their underlying indicators. While most existing research examines these interconnections at the goal level, policy interventions are typically designed and implemented at the indicator level, where synergies and trade-offs most directly emerge. This study addresses this gap by proposing a network-theoretic framework to assess indicator-level interactions in a systematic and data-driven manner. We introduce two complementary measures, the positive strength and negative strength of an indicator, which jointly capture the balance between synergistic and conflicting interactions within a national SDG indicator network. Based on these measures, indicators are classified as synergy- and trade-off-dominated according to their net systemic interaction structure. To move beyond classification, we further examine the structural drivers of synergy dominance using an explanatory regression framework, focusing on the roles of direct positive interactions and indirect network embeddedness. This analysis shows that indicators classified as synergy-dominated are typically characterized by a high concentration of direct synergies and additional support from indirect pathways through the network, allowing positive effects to extend beyond immediate neighbors. The framework is applied to two national case studies, India and Italy, to illustrate how the classification of indicators varies across development contexts. Overall, the proposed methodology provides a transparent and scalable tool for identifying the structural conditions under which indicator-level synergies emerge, thereby supporting a more nuanced understanding of how development actions can generate reinforcing effects across the SDG system.

math.DS↗

arXiv2025

A generic network theoretic based model to classify SDG indicators

To achieve the United Nations Sustainable Development Goals, coordinated action across their interlinked indicators is required. Although most of the research on the interlinkages of the SDGs is done at the goal level, policies are usually made and implemented at the level of indicators (or targets). Our study examines the existing literature on SDG interlinkages and indicator (or target) prioritization, highlighting important drawbacks of current methodologies. To address these limitations, we propose a generic network-based model that can quantify the importance of the SDG indicators and help policymakers in identifying indicators for maximum synergistic impact. Our model applies to any country, offering a tool for national policymakers. We illustrate the application of this model using data from India, identifying important indicators that are crucial for accelerating progress in the SDGs. While our main contribution lies in developing this network-theoretic methodology, we also provide supporting empirical evidence from existing literature for selected key observations.

stat.AP↗

arXiv2025

Structural Characterisations of (n-1,n)-Trees

We study higher-dimensional analogues of graph-theoretic trees within the class of pure n-simplicial complexes. Focusing on the case m = n-1 in Dewdney's (m, n)-tree framework, we introduce refined notions of path and circuit sequences that overcome the structural limitations of existing definitions. Using these refinements, we establish higher-dimensional analogues of the classical characterisations of trees in graphs, including equivalences based on connectivity, acyclicity, path uniqueness, and enumerative constraints. We further disprove two conjectures posed by Dewdney by constructing explicit counterexamples, and we formulate corrected versions that hold under additional necessary conditions in the case m = n-1. These results provide a structural characterisation of (n-1, n)-trees, parallel to the classical theory of graph-theoretic trees.

math.CO↗