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<p>This study employs Network Data Envelopment Analysis (NDEA), a Multiple Objective Programming (MOP) approach, to comprehensively assess the performance/efficiency of 103 countries over the period 2000–2024, at global, national, and group levels, in achieving their Sustainable Development Goals (SDGs). It extends the application of MOP to sustainability assessment, providing deeper insights into both overall SDG performance and stage-specific SDG performance, covering all 17 SDGs and explicitly accounting for their interdependencies. Specifically, we divide the 17 SDGs into two sequential stages: In Stage 1, countries use a virtual governance proxy as a fixed input to produce four economically oriented SDGs; in Stage 2, these economic SDGs are subsequently used to generate the remaining 12 socio-environmental SDGs. Our findings reveal an increasing trend in global SDG performance over time; however, substantial scope for improvement remains, particularly with respect to socio-environmental SDGs and among low- and upper-middle-income countries, where institutional quality-especially government effectiveness and political stability-plays a critical role. Importantly, the study also found a stronger performance in the first stage of economic SDGs than in the second stage of socio-environmental SDGs, supporting the “grow first, clean up later” argument in the Environmental Kuznets Curve (EKC) literature.</p>

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The global frontier of sustainable development goals: examination of multiple objective programming using network data envelopment analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月7日

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  • Sabri Boubaker,
  • Thanh Ngo,
  • Phuc V. Nguyen

摘要

This study employs Network Data Envelopment Analysis (NDEA), a Multiple Objective Programming (MOP) approach, to comprehensively assess the performance/efficiency of 103 countries over the period 2000–2024, at global, national, and group levels, in achieving their Sustainable Development Goals (SDGs). It extends the application of MOP to sustainability assessment, providing deeper insights into both overall SDG performance and stage-specific SDG performance, covering all 17 SDGs and explicitly accounting for their interdependencies. Specifically, we divide the 17 SDGs into two sequential stages: In Stage 1, countries use a virtual governance proxy as a fixed input to produce four economically oriented SDGs; in Stage 2, these economic SDGs are subsequently used to generate the remaining 12 socio-environmental SDGs. Our findings reveal an increasing trend in global SDG performance over time; however, substantial scope for improvement remains, particularly with respect to socio-environmental SDGs and among low- and upper-middle-income countries, where institutional quality-especially government effectiveness and political stability-plays a critical role. Importantly, the study also found a stronger performance in the first stage of economic SDGs than in the second stage of socio-environmental SDGs, supporting the “grow first, clean up later” argument in the Environmental Kuznets Curve (EKC) literature.