Becker William, Saisana Michaela, Paruolo Paolo, Vandecasteele Ine
European Commission, Joint Research Centre, Via Enrico Fermi, 2749, 21027 Ispra VA, Italy.
Ecol Indic. 2017 Sep;80:12-22. doi: 10.1016/j.ecolind.2017.03.056.
Composite indicators are very popular tools for assessing and ranking countries and institutions in terms of environmental performance, sustainability, and other complex concepts that are not directly measurable. Because of the stakes that come with the media attention of these tools, a word of caution is warranted. One common misconception relates to the effect of the weights assigned to indicators during the aggregation process. This work presents a novel series of tools that allow developers and users of composite indicators to explore effects of these weights. First, the importance of each indicator to the composite is measured by the nonlinear Pearson correlation ratio, estimated by Bayesian Gaussian processes. Second, the effect of each indicator is isolated from that of other indicators using regression analysis, and examined in detail. Finally, an optimisation procedure is proposed which allows weights to be fitted to agree with pre-specified values of importance. These three tools together give developers considerable insight into the effects of weights and suggest possibilities for refining and simplifying the aggregation. The added value of these tools are shown on three case studies: the Resource Governance Index, the Good Country Index, and the Water Retention Index.
综合指标是评估国家和机构在环境绩效、可持续性以及其他不可直接衡量的复杂概念方面的排名的非常流行的工具。由于这些工具受到媒体关注所带来的利害关系，因此需要谨慎对待。一个常见的误解与汇总过程中分配给指标的权重的影响有关。这项工作提出了一系列新颖的工具，使综合指标的开发者和使用者能够探索这些权重的影响。首先，每个指标对综合指标的重要性通过非线性皮尔逊相关比来衡量，该相关比由贝叶斯高斯过程估计。其次，使用回归分析将每个指标的影响与其他指标的影响隔离开来，并进行详细检查。最后，提出了一种优化程序，该程序允许权重拟合以符合预先指定的重要性值。这三种工具共同为开发者提供了对权重影响的深入了解，并为细化和简化汇总提供了可能性。这些工具的附加值在三个案例研究中得到了展示：资源治理指数、美好国家指数和保水指数。
