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

Author

Listed:
  • Md Muhtasim Munif Fahim
  • Md Jahid Hasan Imran
  • Luknath Debnath
  • Tonmoy Shill
  • Md. Naim Molla
  • Ehsanul Bashar Pranto
  • Md Shafin Sanyan Saad
  • Md Rezaul Karim

Abstract

The achievement of the 2030 Sustainable Development Goals (SDGs) is dependent upon strategic resource distribution. We propose a causal discovery framework using Panel Vector Autoregression, along with both country-specific fixed effects and PCMCI+ conditional independence testing on 168 countries (2000-2025) to develop the first complete causal architecture of SDG dependencies. Utilizing 8 strategically chosen SDGs, we identify a distributed causal network (i.e., no single 'hub' SDG), with 10 statistically significant Granger-causal relationships identified as 11 unique direct effects. Education to Inequality is identified as the most statistically significant direct relationship (r = -0.599; p

Suggested Citation

  • Md Muhtasim Munif Fahim & Md Jahid Hasan Imran & Luknath Debnath & Tonmoy Shill & Md. Naim Molla & Ehsanul Bashar Pranto & Md Shafin Sanyan Saad & Md Rezaul Karim, 2026. "Distributed Causality in the SDG Network: Evidence from Panel VAR and Conditional Independence Analysis," Papers 2601.20875, arXiv.org.
    • Handle: RePEc:arx:papers:2601.20875
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