JRC and the Environmental Performance Index
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1 JRC and the Environmental Performance Index Andrea Saltelli & Michaela Saisana, JRC-IPSC Interdepartmental Co-ordination Group "GDP and beyond, 4th meeting, 28 March 2012.
2 ESI & EPI: a long term cooperation with JRC
3 EPI EPI JRC testing for outliers, imputation, multivariate analysis, sensitivity analysis,... a conversation of the merits and demerits of aggregation
4 EPI Environmental Performance Index (EPI) Developed for 132 countries Based on 22 indicators grouped in Ten Policy Categories and Two Objectives
5 New: The Pilot Trend EPI, with information on the trends of nationsʼ sustainability levels over the last eleven years ( )
6 EPI 2012 Framework
7 EPI Coherence Objectives Weights 2008 Spearman EPI/Pillar Weights 2010 Spearman EPI/Pillar Weights 2012 Spearman EPI/Pillar Environment al Health Ecosystem Vitality Spearman between 2 Objectives
8 EPI report We made some notable changes to our past weighting and aggregation methodology for the 2012 EPI. [ ] With weights, the result is a much higher correlation between the overall EPI score and the Environmental Health objective score than for the Ecosystem Vitality objective score. In other words, countries that perform high in the Environmental Health objective are likely to perform better in the EPI overall, regardless of scores in the Ecosystem Vitality objective.
9 EPI REPORT To correct this statistical imbalance between the two objectives, the Environmental Health objective for the 2012 EPI comprises 30% of the overall score while Ecosystem Vitality objective makes up the other 70%. [ ]The change in weightings simply reflects a much-needed statistical correction to the aggregation method to produce EPI scores more balanced between the two objectives. 28 March
10 The analysis evolved as well: From Spearman rho to a new sensitivity measures = a measure of coherence between: Declared weights (declared importance) Effective weight: how important is a given variable or pillar?
11 The measure Si is the numerical translation of the shape of a scatterplot S i ~ 0.3 S i ~ 0.4 EPI 2012 Environmental Health (EH) Ecosystem Vitality (EV)
12 EPI index Si [linear/non linear] is the variance of the [linear/non linear] interpolation curve EPI variable
13 declared weight importance HDI 2010 more coherent than HDI 2009 See: Paruolo, P., Saisana, A., Saltelli, A., 2011, Ratings and rankings: Voodoo or Science? Revised for the Journal Royal Statistical Society A, December 2011, Available on arxiv submit/ [stat.ap]
14 EPI relatively balanced in the two objectives But Forestry and Marine are silent indicators
15 Conclusions Quality issue for composite indicators are our focus Linear aggregations are highly problematic. They are theoretically inconsistent (beware with synthetic ). A coherence analysis can limit the damage. Regrettable that social choice theory was and is neglected by most developers; which country would be the EPI 2012 Borda winner?... the Condorcet/Copeland winner? the Balinski winner?
16 Additional background material
17 Sensitivity index of the first order: same number as Pearson correlation ratio η 2
18 Pearson s correlation ratio Smoothed curve First order sensitivity index Unconditional variance
19 First order sensitivity index: Smoothed curve
20 2012 Ecosystem Vitality (score) An 100 issue in the 2012 EPI remains EPI rank EPI rank EPI rank Environmental Health (score)
21 Ongoing work at the JRC
22 Completed Being developed 2011 (2012) Small Business Act Principles (DG ENTR) 2011 Consumer empowerment (DG SANCO) 2011 Youth Civic Competencies Index (DG EaC) 2010 Regional Competitiveness Index (DG REGIO) 2010 (2012)Regional Innovation Index (DG ENTR, Maastricht University) 2012 Environmental Pressure Index (DG ENV) 2012 Resource Efficiency Index (DG ENV) 2012 Wellbeing sub-dimensions (DG REGIO) 2012 ERA, Research Excellence, Structural Change (RTD) 2012 Regional Learning Index (DG EaC)
23 Regional competitiveness versus HE research (EUMIDA) Innovation (RCI) Labour Market (RCI) Research in HE (Eumida, RTD)
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