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Distributed Causality in the SDG Network: Evidence from Panel VAR and Conditional Independence Analysis

M. M. Fahim, M. J. H. Imaran, Md. Naim Molla, M. R. Karim

Abstract

Understanding the causal interconnectedness among the United Nations Sustainable Development Goals (SDGs) is essential for prioritizing policy interventions and preventing unintended trade-offs. This study introduces an empirical framework combining Panel Vector Autoregression (Panel VAR) with conditional independence analysis to evaluate distributed causality and directional relationships across multi-country SDG indicators.

Key Highlights

  • Panel VAR Modeling: Modeled dynamic endogenous feedback loops across multiple SDG dimensions while controlling for country-level heterogeneity.
  • Conditional Independence Analysis: Applied statistical conditional independence tests to untangle direct versus mediated causal relationships across the development network.
  • Policy Trade-off & Synergy Insights: Identified key systemic leverage points where targeted investments produce distributed synergies across interconnected sustainability targets.