Fengmei Ma: Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 335400, China. ORCID
Heming Wang: Center for Collective Learning, CIAS, Corvinus University of Budapest, Közraktár u. 4-6, 1093, Budapest, Hungary. wanghm@mail.neu.edu.cn. ORCID
Asaf Tzachor: School of Sustainability, Reichman University (IDC Herzliya), Herzliya, 4610101, Israel. atzachor@runi.ac.il. ORCID
César A Hidalgo: Center for Collective Learning, CIAS, Corvinus University of Budapest, Közraktár u. 4-6, 1093, Budapest, Hungary.
Heinz Schandl: Commonwealth Scientific and Industrial Research Organisation (CSIRO), Canberra, ACT, 2601, Australia. ORCID
Yue Zhang: State Environmental Protection Key Laboratory of Eco-Industry, Northeastern University, Shenyang, 110819, China.
Jingling Zhang: LEREPS - Laboratoire d'Etude et de Recherche sur l'Economie, les Politiques et les Systèmes Sociaux; Institut d'Études Politiques [IEP], Toulouse, 31000, France.
Wei-Qiang Chen: Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 335400, China. wqchen@iue.ac.cn. ORCID
Yanzhi Zhao: Institute of Carbon Neutrality Technology and Policy, Shenyang University, Shenyang, 110044, China.
Yong-Guan Zhu: Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 335400, China. ORCID
Bojie Fu: State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China. ORCID
The Sustainable Development Goals (SDGs) provide a comprehensive framework for societal progress and planetary health. However, it remains unclear whether universal patterns exist in how nations pursue these goals and whether key development areas are being overlooked. Here, we apply the product space methodology, widely used in development economics, to construct an 'SDG space of nations'. The SDG space models the relative performance and specialization patterns of 166 countries across 96 SDG indicators from 2000 to 2022. Our SDG space reveals a polarized global landscape, characterized by distinct groups of nations, each specializing in specific development indicators. Furthermore, we find that as countries improve their overall SDG scores, they tend to modify their sustainable development trajectories, pursuing different development objectives. Additionally, we identify orphaned SDG indicators - areas where certain country groups remain under-specialized. These patterns, and the SDG space more broadly, provide a high-resolution tool to understand and evaluate the progress and disparities of countries towards achieving the SDGs.
References
Proc Natl Acad Sci U S A. 2015 May 19;112(20):6271-6
[PMID: 24003158]
Science. 2022 May 6;376(6593):597-603
[PMID: 35511968]
Environ Sci Technol. 2016 Oct 4;50(19):10512-10517
[PMID: 27587304]
