基于网络系统的结构分析和统计学方法构建中国可持续发展目标的关键目标和核心指标

Determination of Strategic Targets and Core Indicators for Sustainable Development Goals (SDGs) Integration in China Based on SDG Interlinkages Analysis and Statistical Method

2015年联合国通过了《2030年可持续发展议程》,确立了17项全球可持续发展总体目标和169项具体目标,同时制定了232项指标监测可持续发展进程。可持续发展目标(SDGs)之间以及指标之间相互关联,构成了一个不可分割的复杂系统。文章用51个指标和中国的时序列数据,对相应的108个目标构成的关联网络进行定量化评价。通过社会网络分析和主成分分析,识别出17个关键目标和17项核心指标。17个核心指标可以解释51项指标95%以上的信息量。用此方法构建的核心指标既可大幅减少统计工作量,又可以达到全面监测可持续发展进程的目的。建议在实施《中国落实2030年可持续发展议程国别方案》的初级阶段将17个关键目标列为优先领域,重点突破。同时,通过强化相关目标的正协同效应和防范规避负协同效应,全面提升该落实方案的实施效果。

The 2030 Agenda for Sustainable Development, adopted by the United Nations in 2015, set 17 global Sustainable Development Goals（SDGs） with 169 targets. 232 indicators were proposed as the global framework for monitoring the progress made in achieving SDGs. SDG targets and their corresponding indicators interact with each other forming an indivisible system. This study examined the interlinkages between SDG targets in China and used 51 indicators and relevant time-series data mapping with 108 SDG targets to quantify the network of interlinkages between SDG targets. Using Social Network Analysis and Principal Component Analysis, we identified 17 strategic targets and 17 core indicators. The core indicators can explain more than 95% of the variance of 51 indicators. Using core indicators can reduce statistical burden while satisfying the needs for SDG monitoring. Based on the dashboard indicating the synergies and trade-offs between 17 strategic targets and other targets, this paper recommended that China should set 17 strategic targets as priority areas and optimize the use of limited financial resources by maximizing the synergies and minimizing the trade-offs.