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Variations in sustainable development goal interactions: Population, regional, and income disaggregation

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  • Anne Warchold
  • Prajal Pradhan
  • Jürgen P. Kropp

Abstract

To fulfill the 2030 Agenda, the complexity of sustainable development goal (SDG) interactions needs to be disentangled. However, this understanding is currently limited. We conduct a cross‐sectional correlational analysis for 2016 to understand SDG interactions under the entire development spectrum. We apply several correlation methods to classify the interaction as synergy or trade‐off and characterize them according to their monotony and linearity. Simultaneously, we analyze SDG interactions considering population, location, income, and regional groups. Our findings highlight that synergies always outweigh trade‐offs and linear outweigh non‐linear interactions. SDG 1, 5, and 6 are associated with linear synergies, SDG 3, and 7 with non‐linear synergies. SDG interactions vary according to a country's income and region along with the gender, age, and location of its population. In summary, to achieve the 2030 Agenda the detected interactions and inequalities across countries need be tracked and leveraged to “leave no one behind.”

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  • Anne Warchold & Prajal Pradhan & Jürgen P. Kropp, 2021. "Variations in sustainable development goal interactions: Population, regional, and income disaggregation," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(2), pages 285-299, March.
    • Handle: RePEc:wly:sustdv:v:29:y:2021:i:2:p:285-299
    DOI: 10.1002/sd.2145
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    4. Harman Preet Singh & Ajay Singh & Fakhre Alam & Vikas Agrawal, 2022. "Impact of Sustainable Development Goals on Economic Growth in Saudi Arabia: Role of Education and Training," Sustainability, MDPI, vol. 14(21), pages 1-25, October.
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    6. Anne Warchold & Prajal Pradhan & Pratibha Thapa & Muhammad Panji Islam Fajar Putra & Jürgen P. Kropp, 2022. "Building a unified sustainable development goal database: Why does sustainable development goal data selection matter?," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 1278-1293, October.
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    11. Ghimire, Sujan & Deo, Ravinesh C. & Casillas-Pérez, David & Salcedo-Sanz, Sancho, 2022. "Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Deep Residual model for short-term multi-step solar radiation prediction," Renewable Energy, Elsevier, vol. 190(C), pages 408-424.
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