IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2601.20875.html

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
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2601.20875
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2601.20875. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.