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A network approach to rank countries chasing sustainable development.

Carla Sciarra1, Guido Chiarotti2, Luca Ridolfi2

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This study uses network science to analyze countries' progress on the 17 Sustainable Development Goals (SDGs). It reveals trade-offs between economic and environmental goals, highlighting the need for multi-variable analyses for sustainable development.

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Area of Science:

  • Network Science
  • Sustainable Development Studies
  • Complexity Economics

Background:

  • The United Nations' Agenda 2030 outlines 17 Sustainable Development Goals (SDGs) to address global challenges.
  • Assessing country performance across these diverse SDGs is complex and requires innovative analytical approaches.

Purpose of the Study:

  • To develop and apply a network-based methodology for evaluating countries' performance in achieving the SDGs.
  • To identify interdependencies and trade-offs between different SDGs at the country level.

Main Methods:

  • Representing countries and SDGs as a bipartite network.
  • Utilizing network centrality metrics, adapted from economic complexity, to derive country performance scores.
  • Analyzing the relationships between specific SDGs, such as Innovation and Climate Action.

Main Results:

  • Network centrality analysis provides a method to score countries' capacity to meet SDGs.
  • Distinct performance patterns emerge across SDGs, indicating that not all goals are equally challenging for every nation.
  • A significant trade-off is observed between achieving Innovation and Climate Action goals, reflecting economic versus environmental priorities.

Conclusions:

  • A single ranking indicator is insufficient to capture the complexity of sustainable development.
  • Multi-variable analyses of country-SDG networks offer deeper insights into sustainable development pathways.
  • Understanding these complex interrelationships is crucial for future sustainable development strategies.