The global frontier of sustainable development goals: examination of multiple objective programming using network data envelopment analysis
使用网络数据包络分析评估103个国家2000-2024年可持续发展目标绩效，发现全球绩效上升但社会经济目标改善空间大，且经济目标优于社会环境目标，支持“先增长后治理”假说。
Abstract 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.