Developing alternative visions for assessing progress to sustainable development ‘Beyond GDP’ : constructing new measurement indicator sets.
Date: 2023-02-27
Institutions: Directorate-General for Research and Innovation
Subjects: EU Member State, carbon neutrality, economic development, economic indicator, environmental indicator, environmental protection, governance, gross domestic product, quality of life, report, social indicator, statistical method, sustainable development

Developing Alternative Visions 
for Assessing Progress to 
Sustainable Development 
‘Beyond GDP’  

CONSTRUCTING NEW MEASUREMENT 
INDICATOR SETS 

 
 
 
 
 
 
 
 
 
 
Developing  Alternative  Visions  for  Assessing  Progress  to  Sustainable  Development 
‘Beyond GDP’  
European Commission 
Directorate-General for Research and Innovation 
Directorate E — Prosperity 
Unit E.5 — Economic & Social Transitions 
Contact   Sabine Prevost 
Email  

Sabine.PREVOST@ec.europa.eu 
RTD-PUBLICATIONS@ec.europa.eu 

European Commission 
B-1049 Brussels 

Manuscript completed in January 2023  
This  document has been prepared  for the European Commission,  however it reflects the  views only of the 
authors, and the European Commission shall not be liable for any consequence stemming from the reuse. 

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ISBN 978-92-76-98844-1 

doi:10.2777/888071  KI-03-23-036-EN-N 

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EUROPEAN COMMISSION 

Developing Alternative Visions 
for Assessing Progress to 
Sustainable Development 
‘Beyond GDP’  

CONSTRUCTING NEW MEASUREMENT 
INDICATOR SETS 

2023 

Directorate-General for Research and Innovation 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
The  fallout  from  the  continuing  Russian  invasion  in  Ukraine  has  put  Europe’s 
sustainable economic development leadership through one of its most difficult tests 
so  far.  Bridging  the  policy  ambition  gap  between  the  development  and  the 
implementation  of  EU-wide  sustainable  transition  strategy  could  be  aided  by  the 
introduction  of  new  evidence-based  policy  instruments  to  monitor  the  countries’ 
progress, options and possible actions. This report develops two alternative visions 
for  a  ‘Beyond  GDP’  monitoring  set  of  indicators  to  continuously  assess  the 
global  progress  to  achieving  the  Sustainable  Development  Goals  (SDGs).  The 
Indices  are  based  on  the  information  and  data  from  a  multitude  of  existing 
dashboards  and  different 
socio-economic  development, 
environmental protection, and good governance. The  two proposals for alternative 
analytical  frameworks  include  an  ambitious  scenario  with  5  statistically  tested 
indicators  (including  GDP),  and  a  transition  scenario  with  12  indicators  that  is 
more  encompassing  of  the  different  existing  approaches  for  the  monitoring  of 
sustainable development. The two versions of the Index were piloted for the EU-27 
Member  States  with  the  results  showing  a  moderate  improvement  of  sustainable 
development indicators across Europe. 

indicators  on 

Authors: 
Martin Vladimirov, Director, Energy and Climate Program, Center for the Study of 
Democracy  
Dr. Alexander Gerganov,  Director, Sociological Program, Center for the Study of 
Democracy 
Dr.  Vanya  Petrova,  Senior  Analyst,  Economic  Program,  Center  for  the  Study  of 
Democracy 
Marius  Koeppen,  Analyst,  Energy  and  Climate  Program,  Center  for  the  Study  of 
Democracy 

Contributors and peer reviewers: 
Dr.  Alexander  Stoyanov,  Senior  Fellow,  Center  for  the  Study  of  Democracy,  Dr. 
Mariya  Trifonova,  Research  Fellow,  Economic  Program,  Center  for  the  Study  of 
Democracy, Kostantsa Rangelova, Senior Analyst, Energy and Climate Program, 
Center  for  the  Study  of  Democracy,  German  Rueda,  Analyst  and  Remina 
Alexieva, Analyst, Center for the Study of Democracy 

Acknowledgements: 
CSD would like to thank the participants in the survey and the in-depth interviews. 
In  particular,  we  would  like  to  express  our  special  gratitude  to  Dr.  Rutger 
Hoeckstra from the University of Leiden for his guidance and insightful comments 
on  the  main  challenges  of  developing  a  ‘Beyond  GDP’  monitoring  and  analytical 
framework. 

Editorial Board:  
Ruslan Stefanov  
Dr. Ognian Shentov  
Dr. Todor Galev 

The information and views set out in this report are those of the authors and do not 
necessarily  reflect  the  official  opinion  of  the  Commission.  The  Commission  does 
not  guarantee  the  accuracy  of  the  data  included  in  this  study.  Neither  the 
Commission  nor  any  person  acting  on  the  Commission’s  behalf  may  be  held 
responsible for the use which may be made of the information contained therein. 

2 

 
 
Table of contents 

LIST OF TABLES, FIGURES AND BOXES ........................................ 4 

LIST OF ABBREVIATIONS ................................................................ 5 

EXECUTIVE SUMMARY ..................................................................... 6 

RÉSUMÉ EXÉCUTIF ........................................................................... 10 

1. 

2. 

3. 

INTRODUCTION ..................................................................... 15 

CHALLENGES OF GOING ‘BEYOND GDP’ .......................... 17 

MAPPING EXISTING INDICATORS ...................................... 19 

4. 
CONSTRUCTING  ALTERNATIVE  VISIONS  OF  THE 
TRANSITIONS  PERFORMANCE  INDEX:  METHODOLOGICAL 
APPROACH ........................................................................................ 29 

5. 

TWO ALTERNATIVE INDICES .............................................. 31 

5.1  Ambitious scenario .............................................................................. 36 

5.2 Transition scenario ............................................................................... 43 

6. 

WHAT’S NEXT? ..................................................................... 49 

ANNEX 1 – LIST OF TESTED INDICATORS ..................................... 52 

ANNEX 2 – SUMMARY OF IN-DEPTH INTERVIEWS ........................ 107 

ANNEX 3 – ONLINE EXPERT SURVEY ............................................. 111 

3 

 
 
 
 
LIST OF TABLES, FIGURES AND BOXES 

Figure  1  Two  alternative  visions  for  a  ‘beyond  GDP’  sustainable  development 

monitoring framework ........................................................................................................36 

Figure  2  The  performance  of  the  short  version  of  the  ‘Beyond  GDP’  Sustainable 

Development Index for the top 5 EU Member States ........................................................39 

Figure  3  The  performance  of  the  ambitious  version  of  the  ‘beyond  GDP’  Sustainable 

Development Index for the bottom 5 EU member states ...................................................40 

Figure  4  The  performance  of  the  ambitious  version  of  the  ‘beyond  GDP’  Sustainable 

Development Index (without GDP) for the top 5 EU member states ..................................43 

Figure 5  Beyond GDP - three scenarios, EU-27 scores. ........................................................47 

Table  1  Selected  indices,  scoreboards  and  dashboards  relevant  for  the  ‘Beyond  GDP’ 
approach to sustainable development ........................................................................... 24 

Table  2  ‘Beyond  GDP’  ambitious  scenario  with  GDP  included.  Higher  scores  mean  better 
performance. ................................................................................................................. 37 

Table 3 ‘Beyond GDP’ ambitious scenario with GDP dropped and material footprint included. 
Higher scores mean better performance. ...................................................................... 41 

Table 4 ‘Beyond GDP’ - 12 indicators scenario. Higher scores mean better performance. ..... 44 

Table 5 Comparative ranking of EU-27 member states for 2020 in the two main scenarios and 
the sensitivity version of the ambitious scenario with GDP dropped .............................. 47 

Box 1 TPI methodology overview ............................................................................................ 20 

4 

 
 
 
 
 
 
 
LIST OF ABBREVIATIONS 

BGDP-A 

BGDP-12 

‘Beyond GDP’ Sustainable Development Index: Short 

‘Beyond GDP’ Sustainable Development Index: Long 

CEE 

DESI 

EAP 

EU  

GDP 

GHG 

RCI 

SDGs 

TPI 

Central and Eastern Europe 

Digital Economy and Society Index 

Environmental Action Program 

European Union 

Gross Domestic Product 

Greenhouse Gases 

Regional Competitiveness Index 

Sustainable Development Goals 

Transitions Performance Index 

5 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
EXECUTIVE SUMMARY  

Bridging  the  policy  ambition  gap  between  the  development  and  the  implementation  of 
EU-wide  sustainable  transition  strategy  could  be  aided  by  the  introduction  of  new 
evidence-based  policy  instruments  to  monitor  the  countries’  progress,  options  and 
possible actions.  

DG Research and Innovation of the European Commission contracted Vitosha Research 
EOOD (CSD Group) to study and suggest a  draft integrated approach for assessing 
the  well-being  of  European  countries  combining  the  information  and  data  from  the 
multitude  of  dashboards  and  indices  and  the  different  indicators  on  socio-economic 
development, environmental protection, and good governance, which currently exist. The 
aim was to further try to improve the existing methodologies for tracking  the progress to 
sustainable transition.  

The  methodological  approach  used  for  the  assessment  of  the  identified  indicators 
involved: 

●  Deconstruction  of  multiple  composite  indicators  and  instruments  to  their 

building blocks, i.e. their lowest level indicators (a total of 624 metrics).  

● 

●  Assessment  of  the  indicators  based  on  multiple  qualitative  and  quantitative 
dimensions  to  test  their  suitability  for  inclusion  in  an  alternative  ‘Beyond  GDP’ 
analytical  framework  based  on  technical  criteria  such  as  geographical  scope,  data 
availability,  data  sources,  relevance  to  the  SDGs,  comparability  over  time  and 
space,  relation  to  GDP,  predictable  power,  etc.  Data  was  collected  for  all  202 
metrics and for all EU-27 Member States with a 2011-2020 time coverage.  
Statistical  testing  performed  on  143  indicators  and  indexes  for  which  there  had 
been enough data points to further narrow down the list to the 32 most suitable for 
inclusion  in  alternative  beyond  GDP  metrics.  The  indicators  were  tested  through  a 
series  of  statistical  analyses  including  Correlation  Analysis,  Regression  Analysis 
and  Principal  Component  Analysis.  The  quantitative  score  was  based  on  the 
uniqueness of the indicator (whether it represented a different principal component 
or belonged in a group with many other indicators), on its strength in terms of good 
representation  of  its  respective  dimension  (based  on  factor  loading  score),  on  its 
usefulness (i.e. whether it represented a strong dimension that could be interpreted 
qualitatively or not) and on its EU-27 data availability on the scale from 0 to 270.  

● 

●  Online  survey,  in  which  eighteen  international  experts  assessed  the  pre-selected 
32 indicators on 8 dimensions: General Relevance, Effectiveness, Policy relevance, 
Early  warning  strength,  Short-term  changes  sensitivity,  Foresight  assessment 
sensitivity, Robustness to data manipulation, and Robustness to subjective bias. An 
average  score  was  computed  for  all  32  indicators,  ranking  them  in  descending 
order.  
In-depth  interviews  with  five  of  the  experts  who  took  part  in  the  survey.  The  in-
depth  interviews  aimed  at  drilling  further  down  into  the  experts’  qualitative 
knowledge  and  opinion  on  various  aspects  of  the  current  exercise  including  the 
challenges in  developing  a  “Beyond-GDP”  monitoring  set,  a  conceptual  framework 
for  sustainable  development  assessment  as  well  as 
the  difficulties  when 
communicating the results to different stakeholders. 
Index  construction.  Based  on  additional  statistical  testing  the  short-listed  32 
indicators  were  further  narrowed  down  to  two  alternative  scenarios  for  a  ‘Beyond 
GDP’ Sustainable Development Index.  
Piloting  the  Indices  for  the  EU-27  Member  States  after  a  process  of  min-max 
normalisation. Normalised scales are from 0 to 100 and the final index computed for 
the  two  scenarios  shares  the  same  scale  -  from  0  to  100  where  0  is  the  lowest 
performance score and 100 is the highest. 

● 

● 

6 

 
The  two  scenarios  for  alternative  analytical  frameworks  for  monitoring  ‘beyond  GDP’ 
progress on sustainable development included: 

● 
● 

An ambitious scenario with 5 statistically tested indicators (including GDP), and 
A transition scenario with 12 indicators that is more encompassing of the different 
existing approaches for the monitoring of the sustainable development progress. 

A third sensitivity version of the ambitious scenario was also developed whereas GDP 
was  dropped  completely  from  the  five  indicators  so  as  to  test  a  pure  Beyond  GDP 
scenario.  Instead,  focus  was  put  on  the  use  of  resources,  which  is  a  key  ingredient  to 
achieving long-term sustainable development. Hence, the Material footprint indicator was 
included  to  reflect  better  sustainability.  It  should  be  noted  that  Material  footprint  is  not 
necessarily related to economic growth, so in this sensitivity version less focus is put on 
economic development as a whole.  

The  ambitious  ‘Beyond  GDP’  scenario (BGDP-A)  includes  5  indicators,  one  of  which 
remains  GDP,  representative  of  five  broader  categories.  Choosing  primary-level 
indicators  rather  than  composite  indices  was  also  considered  a  soft  constraint  for  this 
scenario. The list of indicators is:  

● 
Economic Development: Real Gross domestic product (GDP) per capita,  
●  Climate Neutrality: Gross greenhouse gas emissions (tonnes per capita),  
●  Health: Air quality  
●  Human Capital: In-work-at-risk-of-poverty rate (% population),  
●  Governance that Delivers: Life satisfaction.  

The  less  ambitious  transition  ‘Beyond  GDP’  scenario  (BGDP-12)  includes  12 
indicators, one of which remains GDP, representing the same five categories. Here again 
mostly  primary-level  indicators  were  chosen,  but  the  Human  Development  Index  was 
also 
for  socio-economic  sustainable 
development. The list of indicators is:  

included  as  a  statistically  robust  measure 

● 

Economic  Development:  Real  Gross  domestic  product  (GDP)  per  capita;  Gini 
coefficient  of  disposable income,  after taxes  and  transfers;  Unemployment  rate  (% 
of labour force 15-74) 

●  Climate Neutrality: Gross greenhouse gas emissions (tonnes per capita); Material 

footprint (tonnes per capita); Energy Consumption per Capita 

●  Governance that Delivers: Life satisfaction; Human Development Index;  

7 

 
 
●  Human Capital: In-work-at-risk-of-poverty rate (% population); Gender employment 

gap 

●  Health: Air quality; Healthy life expectancy at birth (years) 

The chosen indicators are powerful proxies for measuring the success of environmental, 
social,  and  economic  policies  in  achieving  sustainable  development  goals.  The  goal  on 
the  economic  side  is  to  ensure  that  the  chosen  metrics  are  giving  more  attention  to 
inequality  issues.  This  reflects  a  common  observation  by  many  experts  working  on 
alternative  visions  for  measuring  well-being  that  indices  should  measure  not  economic 
inputs  (such  as  production,  value-added,  assets  accumulation,  etc.)  but  quality  of  life 
based  on  outcomes,  among  others,  related  to  healthy  well-being,  satisfaction  with  life, 
clean  air,  environmental  sustainability 
to  climate  change  adaptation  and 
biodiversity preservation.  

linked 

To select the optimal proxies for good governance, we used the following criteria: 

Data availability: The World Justice Project Rule of Law Index had lower data availability 
than  the  rest  with  whole  years  completely  missing  (e.g.  2017)  and  several  EU-27 
countries not having a score even in recent years. All in all, from 280 possible data points 
(for  the  period  2011-2020)  the  WJP  Rule  of  Law  index  had  only  120  data  points.  The 
other  three  composite  indexes  had  better  data  availability  and  longer  history  which 
makes them more reliable as a data source for the future as well. 

Source of information: where possible we considered hard (objective) data to be more 
reliable and more readily available than experts’ assessments and therefore the HDI was 
deemed slightly better than the other three in terms of data sources.  

Statistical  analyses:  HDI  was  considered  as  the  top  candidate  to  represent  this 
particular principal component because it had the highest factor loading.  

Concerns  for  redundancy  and  double  counting.  As  composite  indicators  have 
complex structure and their final value is not a simple sum of their parts, there are always 
concerns  regarding  redundancy  with  other  primary  indicators  included  in  the  mix.  For 
example,  HDI  is  partly  based  on  both  GDP-related  indicators  and  life-expectancy 
indicators  which  raises  the  concern  about  double  counting.  To  test  such  hypothesis 
statistically,  a  simple  bivariate  correlation  analysis  was  performed  on  the  4  composite 
indicators  considered  as  proxies  for  good  governance  and  the  rest  of  the  short-listed 
indicators. Correlation results  demonstrated that despite the way HDI is constructed, its 
correlation with both GDP and Healthy life expectancy was one of the lowest from the 4 
composite  governance-related  indicators  (r  =  0.44  and  r  =  0.47  respectively)1. 
Considering  all  the  analyses  and  arguments  above,  HDI  was  chosen  as  a  proxy  for 
governance  in  the  transition  scenario.  We  believe  it  is  still  problematic  that  individual 
components  of  this  composite  indicator  are  closely  related  to  other  primary  indicators 
included in the scenario. This caveat should be considered in future works and we would 
recommend that composite indicators are excluded as a whole from a final Beyond GDP 
index even if this leads to the weakening of the important governance dimension.  

In  the  sensitivity  version  of  the  ambitious  ‘Beyond  GDP’  scenario  where  GDP  is 
dropped as a whole from the 5 indicators, EU Member States are showing moderate to 
strong  improvement  in  sustainability  since  2011.  The  results  also  might  reflect  the 
gradual decoupling between GDP and material footprint as national economies become 

1 The WJP Rule of law index in particular had very high correlation with GDP (r = 0.85) as well as with life 
satisfaction (r= 0.882) – another primary indicator critical for both BGDP scenarios. These results revealed 
potential risk of redundancy in case WJP Rule of law index was selected. 

8 

 
 
 
less  material  intensive,  with  higher  shares  of  recycled  intermediary  goods  and 
transitioning to service sector-based growth fundamentals.  

The  results  from  the  piloting  of  the  transition  ‘Beyond  GDP’  scenario  in  the  EU-27 
countries  also  reveals  a  10%  increase  in  the  Index  score  on  average  for  the  EU-27 
across the assessed areas since 2011. Central and Eastern European (CEE)2 countries 
lead  the  way  in  this  improvement.  Some  CEE  EU  member-states  have  raised  their 
sustainability scores by a fifth in comparison to 2011 and are already catching up with the 
most economically developed European countries.   

A comparison of the EU-27 scores for the two scenarios (+ the sensitivity version of the 
ambitious one) indicates there is not much difference in the trajectories. However, in the 
ambitious  scenario  with  GDP,  there is  a  strong  downward  trajectory  between  2018  and 
2020,  which  could  be  attributed  to  the  larger  influence  of  GDP  in  this  index  and  the 
economic recession as a result of the COVID-19 pandemics.  

The inherent volatility of short-term indicators such as GDP could significantly skew the 
results of an Index that measures progress on a long-term agenda for sustainability. This 
gives stronger credence to the concept of an ambitious scenario without GDP providing a 
more realistic picture of the  overall improvement of societal well-being. The inclusion of 
the  raw  material  footprint  is  crucial  for  considering  the  planetary  constraints  linked  to 
economic  growth.  This  indicator  could  be  seen  as  a  cornerstone  for  understanding  the 
intertwined logic between decarbonization and socio-economic transformation.  

As  a  follow  up  to  the  work  performed  in  this  study,  there  is  a  need  for  further 
enhancement  of  the  methodological  approach  to  the  statistical  testing  and  expert 
assessment  of  the  different  indicators  included.  To  maximise  the  policy  impact  of  the 
Index,  the  main  results  could  be  summarised  in  interactive  online  national  score  cards 
and a comparative report launched annually and simultaneously in Brussels and different 
national  capitals  in  the  EU  and  across  the  world.  The  data  variables,  indicators,  Index 
metrics and country analyses could be included in an online Beyond GDP Sustainable 
Development Database. 

2 Czech Republic, Slovakia, Poland, Hungary, Slovenia, Croatia, Romania, Bulgaria, Estonia, Latvia and 
Lithuania 

9 

 
 
 
 
RÉSUMÉ EXÉCUTIF 

L'introduction  de  nouveaux  instruments  de  politiques  publiques  pourrait  permettre  de 
réduire  l'écart  entre  l'élaboration  d'une  stratégie  de  transition  durable  à  l'échelle 
européenne et sa mise en œuvre. Ces instruments doivent être basés sur des données 
fiables  pour  permettre  de  suivre  les  progrès  des  États  membres  vers  des  objectifs 
communs,  ainsi  que  d’identifier  les  voies  d’actions  possibles  pour  parvenir  à  ces 
objectifs. 

La  Direction Générale de la Recherche et l'Innovation de la Commission européenne a 
confié  à  Vitosha  Research  EOOD  (CSD  Group)  la  réalisation  d'une  recherche  avec 
l’objectif  de  proposer  une  approche  intégrée  et  systématique  pour  évaluer  le  bien-être 
des  pays  européens,  qui  intégrera  des  données  provenant  d’une  multitude  de  tableaux 
de  bord,  d’indices  et  d’indicateurs  sur  le  développement  durable,  la  protection  de 
l'environnement  et  la  bonne  gouvernance,  qui  existent  actuellement.  L'objectif  était 
d'essayer  d'améliorer  les  méthodologies  actuelles  qui  servent  à  suivre  les  progrès  de 
l'UE et de ses États membres vers la transition durable.  

L’approche méthodologique qui a été adoptée pour l’analyse des indicateurs identifiés 
dans le cadre du présent projet de recherche comprend les éléments suivants :  

●  Désagrégation  de  plusieurs 

instruments 
présélectionnés  jusqu’à  leurs  éléments  constitutifs  de  base  –  leurs  indicateurs 
primaires (624 indicateurs au total). 

indicateurs  composites  et 

●  Analyse quantitative et qualitative multidimensionnelle des indicateurs primaires pour 
identifier  ceux  qui  sont  les  plus  pertinents  à  être  intégrés  dans  un  cadre  analytique 
alternatif  „Au-delà  du  PIB”.  Cette  analyse  a  été  basée  sur  plusieurs  critères 
techniques tels que la portée géographique, la disponibilité des données, les sources 
de  données,  la  pertinence  par  rapport  aux  Objectifs  de  Développement  (ODD)  ,  la 
comparabilité  dans  le  temps  et  dans  l'espace,  le  rapport  au  PIB,  la  puissance 
prévisible, etc. Ceci a permis de réduire le nombre des indicateurs de 624  à 202, ce 
qui a été suivi par la collecte de données pour ces 202 indicateurs pour tous les États 
membres de l'UE pour la période 2011-2020. 

●  Tests  statistiques  réalisés  sur  143  indicateurs  et  indices  –  ceux  pour  lesquels  il  y 
avait  suffisamment  de  données  pour  réaliser  les  tests.  Ces  tests  ont  permis  de 
réduire  le  nombre  d’indicateurs  à  32  –  les  plus  pertinents  à  être  intégrés  dans  un 
cadre analytique alternatif „Au-delà du PIB”. Plus précisément, les indicateurs ont été 
testés  par  le  biais  d'une  série  d'analyses  statistiques,  notamment  l'analyse  de 
corrélation,  l'analyse  de  régression  et  l'analyse  des  composantes  principales.  Le 
score quantitatif final, sur une échelle de 0 à 270, était basé sur le caractère unique 
l'indicateur  (s'il  représentait  une  composante  principale  différente  ou  s'il 
de 
appartenait à un groupe comprenant de nombreux autres indicateurs), sur sa force en 
termes de bonne représentation de sa dimension respective (sur la base du score de 
charge  factorielle),  sur  son  utilité  (c'est-à-dire  s'il  représentait  une  dimension  forte 
pouvant  être  interprétée  qualitativement  ou  non)  et  sur  la  disponibilité  des  données 
pour tous les  États membres de l'UE. 

●  Enquête  en  ligne,  dans  laquelle  dix-huit  experts  internationaux  ont  évalué  les  32 
indicateurs  présélectionnés  sur  8  dimensions  :  Pertinence  générale,  Efficacité, 
Pertinence  politique,  Force  d'alerte  précoce,  Sensibilité  aux  changements  à  court 
terme,  Sensibilité  à  l'évaluation  prospective,  Robustesse  à  la  manipulation  des 

10 

 
données et Robustesse aux biais subjectifs. Une note  moyenne a été calculée pour 
l'ensemble  des  32  indicateurs,  ce  qui  a  permis  de  classer  les  indicateurs  par  ordre 
décroissant. 

●  Des  entretiens  approfondis  avec  cinq  des  experts  ayant  participé  à  l'enquête  en 
ligne.  Les  entretiens  approfondis  visaient  à  approfondir  l’analyse,  en  mobilisant  les 
connaissances qualitatives et l'opinion personnelle des experts sur plusieurs aspects 
clés  du  projet  de  recherche,  notamment  sur  les  défis  liés  à  l'élaboration  d’un  cadre 
conceptuel pour l'évaluation du développement durable et d'un cadre analytique " au-
delà du PIB " ainsi que sur les difficultés liées à la communication des résultats des      
analyses aux différentes parties prenantes. 

●  Construction  de  l'indice.  Des  tests  statistiques  supplémentaires  ont  permis  de 
réduire  encore  le  nombre  d’indicateurs  des  32  présélectionnés  en  créant  deux 
scénarios alternatifs pour l’indice de développement durable " Au-delà du PIB ". 

●  Pilotage  des  indices  pour  les  27  États  membres  de  l'UE  après  un  processus  de 
normalisation  min-max.  Les  échelles  normalisées  vont  de  0  à  100  et  l'indice  final 
calculé  pour  les  deux  scénarios  partage  la  même  échelle  -  de  0  à  100  où  0  est  le 
score de performance le plus bas et 100 le plus élevé. 

Les  deux  scénarios  alternatifs  pour  le  cadre  analytique  „Au-delà  du  PIB”  développés 
dans le cadre de ce projet sont les suivants : 

●  Scénario ambitieux incluant 5 indicateurs (dont le PIB) 
●  Scénario de la transition incluant 12 indicateurs qui englobent mieux les approches 

différentes de suivi du progrès vers le développement durable.  

Une  troisième  version  de  sensibilité  du  scénario  ambitieux  a  également  été 
développée,  dans  laquelle  le  PIB  a  été  retiré  des  cinq  indicateurs  afin  de  tester  un 
scénario purement "Au-delà du PIB". Au lieu du PIB, l'accent a été mis sur l’exploitation 
des  ressources,  qui  est  un  élément  clé  pour  atteindre  les  objectifs  du  développement 
durable à long terme. L'indicateur Empreinte matérielle a été inclus pour  mieux refléter 
les  aspects  de  la  durabilité.  Il  convient  de  noter  que  l'empreinte  matérielle  n'est  pas 
nécessairement  liée  à  la  croissance  économique,  et  que  dans  cette  version  de 
sensibilité, le développement purement économique n’est pas autant mis en évidence.  

11 

 
 
Le scénario ambitieux "Au-delà du PIB" (BGDP-A) comprend 5 indicateurs, incluant le 
PIB , qui représentent cinq catégories générales. Pour la sélection des cinq indicateurs 
dans  ce  scénario,  la  préférence  pour  les  indicateurs  primaires  au  lieu  des  indicateurs 
composites était une contrainte molle. La liste des indicateurs choisis est la suivante : 

●  Développement économique : Le produit intérieur brut (PIB) réel par habitant,  
●  Neutralité  climatique  :  Émissions  brutes  de  gaz  à  effet  de  serre  (tonnes  par 

habitant),  

●  Santé: Qualité de l'air.  
●  Capital  humain  :  Taux  de  travailleurs  exposés  au  risque  de  pauvreté  (%  de  la 

population) 

●  La gouvernance qui tient ses promesses : La satisfaction de la vie. 

Le  scénario  de  la  transition  (BGDP-12)  moins  ambitieux  comprend  12  indicateurs, 
incluant le PIB, qui représentent toujours les mêmes cinq catégories générales. Dans ce 
scénario, la préférence pour les indicateurs primaires au lieu des indicateurs composites 
a  été  aussi  respectée  en  tant  que  contrainte  molle  mais  l’Indice  de  développement 
humain (IDH) a été inclut dans la liste des 12 en tant qu’un estimateur du développement 
socio-économique  avec  une  grande  robustesse  statistique.  La  liste  des  indicateurs 
choisis est la suivante: 

●  Développement  économique  :  Produit  intérieur  brut  (PIB)  réel  par  habitant  ; 
coefficient de Gini du revenu disponible (après impôts et transferts); taux de chômage 
(% de la population active de 15 à 74 ans). 

●  Neutralité  climatique  :  Émissions  brutes  de  gaz  à  effet  de  serre  (tonnes  par 
habitant)  ;  Empreinte  matérielle  (tonnes  par habitant) ;  Consommation  d'énergie  par 
habitant. 

●  Santé : Qualité de l'air ; espérance vie en bonne santé à la naissance (années). 
●  Capital humain : Taux de risque de pauvreté au travail (% de la population) ; Écart 

de taux d'activité entre les sexes. 

●  La gouvernance qui tient  ses promesses : La satisfaction dans la vie ; l'indice de 

développement humain (IDH). 

Les  indicateurs choisis  sont des  indicateurs indirects  puissants  pour évaluer la  réussite 
des  politiques  publiques  environnementales,  sociales  et  économiques  à  atteindre  les 
objectifs  de  développement  durable.  L’objectif  principal  des  indicateurs  économiques 
était de mettre en évidence les enjeux d'inégalités. Cette décision prend en considération 
l’observation unanime de nombreux experts travaillant sur le développement de modèles 
alternatives  d’évaluation  du  bien-être  que  les  indices  devraient  mesurer  non  pas  les 
intrants  économiques  (tels  que  la  production,  la  valeur  ajoutée,  l'accumulation  d'actifs, 
etc.), mais la qualité de vie évaluée sur la base de certains aboutissements, entre autres, 
le  bien-être,  la  santé,  la  satisfaction  de  la  vie,  la  qualité  de  l’air,  la  durabilité 
environnementale,  l’adaptation  au  changement  climatique  et  la  préservation  de  la 
biodiversité. 

Pour  sélectionner  les  indicateurs  indirects  optimaux  pour  l’évaluation  de  la  bonne 
gouvernance, nous nous sommes appuyés sur les critères suivants :  

Disponibilité des données : L’Indice sur l'Etat de droit du World Justice Project (WJP) 
avait plus de problèmes de disponibilité et fiabilité des données que les autres, avec des 
années  entières  complètement  manquantes  (par  exemple  2017)  et  plusieurs  pays  de 

12 

 
l'UE-27 n'ayant pas de score même pour les années récentes. Au total, sur 280 points de 
données  possibles  (pour  la  période  2011-2020),  l'indice  sur  l'état  de  droit  du  WJP  ne 
disposait  que  de  120  points  de  données.  Les  trois  autres  indices  composites  ont  une 
meilleure disponibilité des données et un historique plus long, ce qui les rend plus fiables 
en tant que source de données pour l'avenir également. 

Source  des  données  :  dans  la  mesure  du  possible,  nous  avons  considéré  que  les 
données concrètes (objectives) étaient plus fiables et plus facilement disponibles que les 
évaluations  d'experts  et,  par  conséquent,  l'IDH  a  été  jugé  légèrement  meilleur  que  les 
trois autres en termes de sources de données.  

Analyses  statistiques  :  L'IDH  a  été  considéré  comme  le  meilleur  candidat  pour 
représenter cette composante principale particulière car il présentait la charge factorielle 
la plus élevée. 

Inquiétudes  liées  à  la  redondance  et  au  double  comptage.  Comme  les  indicateurs 
composites  ont  une  structure  complexe  et  que  leur  valeur  finale  n'est  pas  une  simple 
somme  de  leurs  parties,  il  y  a  toujours  des  préoccupations  concernant  la  redondance 
avec d'autres indicateurs primaires inclus dans le même groupe. Par exemple, l'IDH est 
partiellement basé sur des indicateurs liés au PIB et des indicateurs d'espérance de vie, 
ce  qui  soulève  la  question  du  double  comptage.  Pour  tester  statistiquement  cette 
hypothèse,  une  simple  analyse  de  corrélation  bivariée  a  été  effectuée  sur  les  4 
indicateurs composites considérés comme des approximations de la bonne gouvernance 
et  le  reste  des  indicateurs  de  la  liste  restreinte.  Les  résultats  de  la  corrélation  ont 
démontré  que  malgré  la  manière  dont  l'IDH  est  construit,  sa  corrélation  avec  le  PIB  et 
l'espérance  de  vie  en  bonne  santé  était  l'une  des  plus  faibles  parmi  les  4  indicateurs 
composites liés à la gouvernance (r = 0,44 et r = 0,47 respectivement). Compte tenu de 
l'ensemble des analyses et arguments ci-dessus, l'IDH a été choisi comme indicateur de 
la  gouvernance  dans  le  scénario  BGDP-12.  Quand  même,  nous  considérons  toujours 
que les liens étroits entre les composants individuels de cet indicateur composite et les 
autres  indicateurs  primaires  inclus  dans  le  même  scénario  reste  problématique.  Cette 
considération  devrait  être  prise  en  compte  dans  les  travaux  futurs  sur  ce  sujet  et  nous 
recommandons que les indicateurs composites soient exclus entièrement de l'indice final 
"Au-delà du PIB" même si cela conduit à l'affaiblissement de sa dimension importante lié 
à la bonne gouvernance. 

La  version  de  sensibilité  du  scénario  ambitieux  où  le  PIB  est  omis  de  la  liste  de  5 
indicateurs,  les  États  membres  de  l'UE  montrent  une  amélioration  de  modérée  à  forte 
depuis  2011  en  termes  de  durabilité.  Les  résultats  peuvent  être  indicateurs  du 
découplage  progressif  entre  le  PIB  et  l’empreinte  matérielle  suite  à  la  diminution  de 
l’intensité matérielle des économies nationales grâce au plus grand taux de recyclage de 
produits  intermédiaires  et  à  la  transition  vers  la  croissance  économique  dont  le moteur 
principal et le secteur des services.  

Les résultats du pilotage du  scénario de la transition montrent aussi une amélioration 
du  score  de  l’indice  de  10%  en  moyenne  pour  les  27  États  membres  de  l'UE  depuis 
2011. Les pays de l’Europe Centrale et Orientale3 montrent la plus grande amélioration. 

3  République  Tchèque,  Slovaquie,  Pologne,  Hongrie,  Slovénie,  Croatie,  Roumanie,  Bulgarie,  Estonie, 
Lettonie et Lituanie 

13 

 
 
Certains États membres de cette région ont vu leurs scores s’améliorer de 20% depuis 
2011  et  sont  déjà  en  train  de  rattraper  les  États  membres  les  plus  développés 
économiquement.  

Une  comparaison  des  scores  de  l'UE-27  pour  les  deux  scénarios  (+  la  version  de 
sensibilité du scénario ambitieux) indique qu'il n'y a pas une grande divergence entre les 
trajectoires. Cependant, dans le scénario ambitieux incluant le PIB, on observe une forte 
trajectoire  à  la  baisse  entre  2018  et  2020,  qui  pourrait  être  attribuée  à  la  plus  grande 
influence  du  PIB  dans  cet  indice  et  à  la  récession  économique  suite  à  la  pandémie  du 
COVID-19. 

La  volatilité  inhérente  aux  indicateurs  à  court  terme  tels  que  le  PIB  pourrait  fausser 
considérablement  les  résultats  d'un  indice  qui  mesure  le  progrès  réalisé  dans  le  cadre 
d'une stratégie de durabilité à long terme. Cela donne plus de crédibilité au concept d'un 
scénario ambitieux sans PIB fournissant une image plus réaliste de l'amélioration globale 
du bien-être sociétal. Le remplacement du PIB par l'empreinte matérielle est crucial pour 
prendre  en  compte  les  contraintes  planétaires  liées  à  la  croissance  économique.  Cet 
indicateur  pourrait  être  considéré  comme  une  pierre  angulaire  pour  comprendre  la 
logique imbriquée entre la décarbonation et la transformation socio-économique.  

Dans le cadre d’un éventuel prolongement du travail effectué par ce projet de recherche, 
il  serait  nécessaire  d'améliorer  encore l'approche  méthodologique  des  tests  statistiques 
et  de  l'évaluation  par  des  experts  des  différents  indicateurs.  Pour  maximiser  l'impact 
politique  de  l'indice,  les  principaux  résultats  pourraient  être résumés  dans  des  tableaux 
de bord nationaux interactifs en ligne et dans un rapport comparatif lancé annuellement 
et simultanément à Bruxelles et dans les capitales nationales de l'UE et du monde. Les 
différents  variables,  indicateurs  et  paramètres  de  l'indice  et  les  analyses  des  résultats 
pour  chaque  pays  pourraient  être  inclus  dans  une  base  de  données  en  ligne 
"Développement durable au-delà du PIB". 

14 

 
 
 
 
 
 
1.  INTRODUCTION  

today  requires  a  comprehensive  strategy 

Tackling the wide spectrum of geopolitical, socio-economic, energy and climate security 
risks  engulfing  Europe 
for  a  deep 
transformation  of  the  European  economy,  with  a  full  harmonisation  between  the  low-
carbon  transition,  the  sustainable  development  goals  and  the  need  for  continued 
improvement of living standards and human well-being. Bridging the policy ambition gap 
between  the  development  and  the  implementation  of  EU-wide  sustainable  transition 
strategy should be aided by the introduction of new evidence-based policy instruments to 
monitor  member-states’  progress,  options  and  possible  actions.  Based  on  an  objective, 
comparative  assessment,  the  EU  would  be  able  to  further  and  deepen  coordination  of 
national  policies  across  sectors  and  policy  areas  on  the  back  of  a  long-term  political, 
financial and social commitment. 

There  is  a  need  to  design  an  integrated  approach  to  assessing  well-being  resting  on  a 
multitude  of  dashboards  and  indices  combining  different  indicators  on  socio-economic 
development,  environmental  protection  and  good  governance.  However,  these  metrics 
are not sufficiently linked to the monitoring of the implementation of the SDG goals, lack 
coherence with existing long-term strategy documents, and are not well-communicated to 
the broader European society.  

The  European  Parliament  Resolution  on  the  Implementation  and  Delivery  of  the 
Sustainable  Development  Goals4  recognizes  that  no  country,  including  any  European 
country,  is  on  track  to  achieving  all    the  SDGs.  Europe  as  a  whole  is  on  track  to  meet 
only 26 of the 169 targets. The Resolution notes the lack of accountability, transparency 
and  good  governance  that  have  negatively  impacted  the  implementation  of  the  2030 
Agenda. It further stresses the need to promote anti-corruption and integrity to accelerate 
the implementation of the SDGs. 

Building  upon  the  European  Parliament  Resolution,  the  8th  Environmental  Action 
Programme  (EAP)5  monitoring  framework  envisions  a  two-step  consultation  process, 
which  starts  with  first  agreeing  on  principles  that  will  guide  the  selection  of  headline 
indicators.  Based  on  these  agreed  principles,  the  second  stage  of  the  consultation  will 
consist  of  discussing  the  choice  of  headline  indicators.  They  are  distributed  among  six 
priority objectives: 

●  Achieving the 2030 greenhouse gas emission reduction targets 
●  Enhancing  adaptive  capacity,  strengthening  resilience,  and  reducing  vulnerability  to 

climate change; 

●  Advancing  towards  a  regenerative  growth  model,  decoupling  economic  growth  from 
resource  use  and  environmental  degradation,  and  accelerating  the  transition  to  a 
circular economy; 

●  Pursuing a zero-pollution ambition, including for air, water and soil; 
●  Protecting, preserving, and restoring biodiversity and enhancing natural capital; and 
●  Reducing  environmental  and  climate  pressures 

to  production  and 

related 

consumption. 

The  EAP  framework  notes  that  the  monitoring  indicators  will  be  chosen  from  existing 
ones  that  are  current  and  policy  relevant  but  this  approach  should  accommodate  also 
more long-term needs to develop and integrate new indicators and indications/contextual 
information, as these become available. There is also the need to develop indicators that 
link environment, employment and social policy in line with the European Pillar of Social 

4 Texts adopted - Implementation and delivery of the Sustainable Development Goals - Thursday, 23 June 
2022 (europa.eu) 
5 EUR-Lex - 32022D0591 - EN - EUR-Lex (europa.eu) 

15 

 
 
Rights.  In  addition,  the  EAP  framework  lists  a  number of  guiding  principles  for the  right 
choice of indicators: 

●  Representativeness: of the overall policy objectives and scope of the 8th EAP; 
●  Balance  the  type  of  indicators,  in  line  with  overall  purpose:  with  respect  to  the 

types of indicators included (state, pressures, actions/output, results/impact); 

●  Quality  assurance:  A  wide  range  of  data  should  be  considered,  including  citizen 

science and Copernicus, research and modelling; 

●  Granularity  in  combination  with  time  series:  screen  indicators  in  view  of  their 

capacity to show trends over time at various levels of governance; 

●  Measuring progress towards European Green Deal targets; 
●  SDG-relevance:  so-called  “systemic  indicators”,  could  be  prioritised,  also  taking 
account of spill-over effects, synergies and trade-offs. The (a) indivisibility and the (b) 
universality  of  the  SDG  agenda,  as  well  as  the  (c)  do  no  harm  principle  or  (d)  the 
leaving no one behind principle could also be considered; 

●  Balancing  robustness  and  flexibility:  the  monitoring  framework  should  be  robust, 
yet  flexible  enough  to  allow  for  the  more  long-term  need  to  improve  or  complement 
existing indicators, as relevant following statistical and political developments. 

A  discussion  paper  by  DG  Economic  and  Financial  Affairs  from  June  2021  on  the 
Economic  Policy  Making  Beyond  GDP6,  conducts  a  more  detailed  review  of  the 
indicators and areas, which would need to feature in a  more comprehensive monitoring 
methodology.  The  Paper  defines  five  horizontal  enablers  for  the  sustainable  transition, 
including: 

●  Education, science, technology, research and innovation: 

ICT skills and the uptake of AI technologies; 

o 
o  R&D target for EU Member States in terms of share of GDP. 

●  Finance, pricing, taxation and competition: 

o  Around  EUR  180  billion  of  additional  investments  to  achieve  the  EU’s  2030 

o 

emissions reduction targets agreed in Paris; 
Investments in renewable energy, energy efficiency, research, development and 
innovation, as well as social infrastructure such as affordable housing; 

o  Effective pricing of externalities; 
o  Reduction  of  labour  taxes  and  increase  of  environmental  taxes  (polluter  pays 

principle). 

●  Responsible  business  conduct,  corporate  social  responsibility  and  new 

business models: 

o  Corporate Social Responsibility; 
o  Responsible metals and minerals imports. 

●  Open and rules-based trade: 

o  Sustainable development as a key aspect of trade agreements. 

●  Governance and ensuring policy coherence at all levels 

o  Respect for the rule of law, democracy and fundamental rights; 
o 

Impact  of  EU’s  internal  policies  on  the  development  of  countries  outside  the 
Union. 

Despite  these  detailed  policy  guidelines  for the  development  of  a  monitoring  framework 
for a ‘beyond GDP’ assessment of sustainable development, there is still a lack of clear, 
measurable  and  time-bound  EU-wide  targets  to  report  on  for  all  SDGs,  which  is  why 
there is a need for a revised set of concrete measurable, EU-wide, time-bound targets to 
bolster  the  EU’s  ambition  and  to  achieve  the  EU  Agenda  2030.  The  expanded  set  of 
indicators  needs  to  add  an  assessment  of  the  quality  and  effectiveness  of  the  EU 
external action, the European security of supply of goods and of value chains. In addition, 

6 Economic Policy-Making Beyond GDP: An Introduction (europa.eu) 

16 

 
 
 
the  EP  Resolution  stresses  that  a  minimum  level  of  data  and  statistical  disaggregation 
should  be  established,  covering,  where  appropriate,  geographic  differences,  gender 
aspects,  sexual  orientation,  income,  educational  level,  age,  race,  ethnicity,  migratory 
status, impairment and other characteristics. 

In  the  improvement  of  the  existing  methodologies  for  tracking  the  EU  progress  to 
sustainable  transition,  Vitosha  Research  (CSD  Group)  set  out  to  design  an  integrated 
approach  to  assessing  the  well-being  of  European  countries  resting  on  a  multitude  of 
dashboards  and  indices  combining  different  indicators on  socio-economic  development, 
environmental protection and good governance. The approach included a comprehensive 
review of the existing set of SDG indicators and ensured they cover not only the internal 
priorities of the EU but also the state of diplomacy and international action to restore and 
protect  the  global  commons  and  address  international  spill  over  effects  of  EU  internal 
policies, as well as the positive and negative aspects of EU action. In addition, the study 
developed a comprehensive desktop assessment of the different indicators testing them 
both quantitatively and qualitatively. In this way,  the review process narrowed down  the 
624 indicators, first identified to a limited set of 32 metrics that then were evaluated via a 
DELPHI method of expert assessment7. As a result of this in-depth review, two concrete 
proposals  (case  studies)  for  a  “beyond  GDP”  monitoring  set  were  developed:  an 
ambitious  scenario  with  five  indicators  (including  GDP)  and  a  transition  one  with  12 
existing and new indicators. The two alternative monitoring frameworks were then piloted 
on  EU-27  level  contributing  to  the  development  of  a  beta  version  of  a  ‘Beyond  GDP’ 
Sustainable Development Index. 

2.  CHALLENGES OF GOING ‘BEYOND GDP’ 

Both  economists  and  other  social  scientists  have  criticised  GDP  as  a  good  measure  of 
societal  success.  There  is  an  urgent  need  for  a  transition  from  a  development  model 
driven  by  growth  to  one  predicated  on  sustainability  in  order  to  cope  with  the  global 
challenges  of  the  21st  century.  Hundreds  of  ‘beyond  GDP’  alternatives  have  been 
proposed,  and  some  are  already  among  the  Nobel  laureates:  Nordhaus  and  Tobin 
(Measure  of  Economic  Welfare),  Sen  (Human  Development 
Index),  Tinbergen 
(Sustainable  National  Income),  Kahneman  (U-index),  Stiglitz  Report’s  (Dashboard  of 
indicators based on the capital approach). In addition, the European Commission, OECD 
(Better  Life  Index),  UN  (Sustainable  Development  Goals);  UNDP  (Human  Development 
Index);  UNEP  (Inclusive  Wealth  Index),  the  World  Bank  (Comprehensive  Wealth),  and 
Eurostat,  among  others,  have  also  developed  indicators  to  measure  well-being  and 
prosperity at individual, community and national level more effectively.  

truly  successful. 

initiative  has  not  been 

Despite the intense debate and efforts from institutions, researchers, and politicians, the 
‘beyond  GDP’ 
faces  numerous 
methodological and empirical challenges, but the ultimate problem is the lack of a 
coherent  ‘beyond  GDP’  scientific  community8.  The  various  schools  of  thought  have 
no  common  language  to  bind  them,  but  advocate  their  own  methodologies,  indicators, 
and 
terminology.  Heterogeneous  definitions  of  welfare,  sustainability,  progress, 
development, happiness, etc. can be overcome by developing shared vocabulary, data, 
and methods. Adopting a holistic definition of sustainability that ensures the well-being of 
both  humans  and  the  planet,  while  taking  spill  over  effects  into  account,  is  the  main 
challenge  of  going  ‘beyond  GDP.’  As  composite  indicators  are  used  to  compare 
economic development between different countries and regions—either in time series or 

It 

7 Involves multiple rounds of expert assessments by means of a survey and in-depth interviews, with each 
round  considering  the  previous  assessments  to  eventually  reach  a  consensus  among  experts  about  a 
specific scenario or choice of indicators. 
8  Hoekstra,  R.  (2019).  Why  Is  Beyond-GDP  Not  Successful?  In  Replacing  GDP  by  2030:  Towards  a 
Common  Language  for  the  Well-being  and  Sustainability  Community  (pp.  79-102).  Cambridge: 
Cambridge University Press. 

17 

 
 
in a certain point of time—it is crucial that concepts, data sources, and methods support 
the construction of internationally comparable indicators. 

One  of  the  key  dilemmas  in  the  ‘Beyond  GDP’  analytical  framework  is  the  choice 
between  a  composite  index  and  a  scoreboard9.  While  dashboards  and  scoreboards 
paint  a  detailed  picture  of  a  phenomenon  through  the  prism  of  selected  individual 
indicators,  they  sometimes  deliver  contradictory  information.  Composite  indices  try  to 
extract a synthesised message but, due to the assumptions and decisions that must be 
made  in  the  process  of  their  construction,  they  often  turn  out  to  be  too  subjective. 
Composite  indicators  are  easier  to  interpret  and  suitable  to  shape  the  policy  agenda. 
They  facilitate  communication  with  the  general  public  and  promote  accountability.  
However,  composite  indicators  may  send  misleading  signals  if  poorly  constructed  and 
may  invite  simplistic conclusions.  If  the construction  process  is  not  transparent  enough, 
such indicators may also conceal flaws in some dimensions and make it harder to identify 
the  best  course  of  policy  action.  Thus,  the  ‘Beyond  GDP’  monitoring  set  should  utilise 
composite indicators and dashboards/scoreboards only as complementary tools.  

The  OECD-JRC  Handbook  provides  thorough  technical  guidelines  on  constructing 
composite  indicators  for  policy-makers,  researchers,  the  media  and  other  interested 
parties.  The  Handbook  contributes  to  a  better  understanding  of  the  complexity  of  these 
indicators and to an improvement in the techniques currently used to build them.10 

The  choice  of  weighting  and  aggregation  methods  is  also  an  open  question. 
Weights  could  be  the  decisive  factor  determining  the  final  result  of  the  Index  and  the 
country  rankings  making  the  outcome  subjective  as  well11.  Although  equal  weighting  is 
often  preferred,  in  this  case,  there  is  also  a  risk  of  double  counting  when  applying  it  to 
series,  some  of  which  might  be  highly  correlated  with  each  other.  Weights  may  be 
assigned  to  reflect  the  economic  significance  (coverage,  reliability,  policy  relevance), 
statistical  correlation,  cyclical  conformity  and  timeliness.  Weighting  indicators  and/or 
dimensions is problematic because specific issues could be particularly relevant to some 
communities,  so  questions  of  how  significant  an  indicator/dimension  is,  should  be 
addressed  locally.  Overall,  a  composite  ‘Beyond  GDP’  monitoring  system  may  be 
compiled in one step, in which the individual indicators are weighted and aggregated, or 
in two steps: (1) from individual indicators to dimensions, and then, (2) from dimensions 
to  the  composite  index.  A  related  challenge  is  to  decide  how  many  and  which 
indicators and dimensions to be included12. There is a potential trade-off between the 
number of indicators and the usefulness and relevance of the composite Index to policy 
makers13. Having different dimensions is an artificial distinction since  they often overlap: 
the  social  dimension  leads  to  the  economic  one,  and  environmental  leads  to  social. 
“Building and naming dimensions is a political decision, as well as having an aggregate 
number.  If  an  index  cannot  be  decomposed,  it  might  be  appealing,  but  it  will  not  aid  in 
political decision-making and accountability.”14   

The following criteria are essential when producing indicators: 

9 Parris, T. M., and Kates, R. W. (2003). Characterizing and Measuring Sustainable Development. Annual 
Review of Environmental Resources 28, 559–586. 
10  Nardo  M,  Saisana  M,  Saltelli  A,  Tarantola  S,  Hoffmann  A,  Giovannini  E.(2008)  Handbook  on 
Constructing  Composite  Indicators:  Methodology  and  User  Guide.  Paris  (France):  OECD  publishing. 
https://publications.jrc.ec.europa.eu/repository/handle/JRC47008 
11  Mazzi,  G.L.  (2015).  Complementing  scoreboards  with  composite  indicators:  the  new  business  cycle 
clock. EURONA Eurostat Review on National Accounts and Macroeconomic Indicators. 
12 Economic Commission for Europe. (2019). Guidelines on Producing Leading, Composite and Sentiment 
Indicators. Conference on European Statistics. 
13  Organisation  for  Economic  Co-operation  and  Development.  (2008).  Handbook  on  Constructing 
Composite Indicators. Methodology and User Guide. 
14 CSD’s in-depth interview with a ‘Beyond GDP’ expert, December 2022. 

18 

 
 
  
 
Institutional environment, Statistical processes 
•  Professional independence 
Impartiality and objectivity 
• 
•  Methodological soundness 

Statistical output 
•  Relevance 
•  Accuracy and reliability 
•  Coherence and comparability 
•  Accessibility and clarity 
•  Timeliness and punctuality 

The selection of indicators depends on four key technical criteria: (1) geographical scope 
(EU and non-EU); (2) degree of aggregation (regional, national); (3) frequency of the data 
(annual, biannual); and (4) overall data availability. 

The  process  of  developing  indicators  should  take  into  consideration  the  metrics’:  (1) 
comparability; (2) aggregation; (3) decontextualisation; (4) goal displacement; (5) misuse; 
and  (6)  easy  maintenance.  Two  complications  frequently  associated  with  the  use  of 
indicators  are decontextualisation  and  goal  displacement.    Decontextualisation  occurs 
when  an  indicator  is  taken  out  of  context  and  misinterpreted,  while  at  the  same  time, 
other  relevant  information  might  be  ignored.  To  prevent  decontextualisation,  the 
accompanying  analysis  should  make  it  obvious  what  the  indicator  is  meant  to  evaluate 
and how it should be used and understood. Goal displacement occurs when a measure 
becomes  a  target  and  stakeholders,  striving  to  achieve  it,  lose  sight  of  the  actual  goal 
behind  it.  A  possible  solution  is  using  indicators  that  account  for  outcomes  rather  than 
inputs (e.g., years of schooling instead of government expenditures for education). 

Another challenge is to determine whether GDP should be included or excluded from the 
‘Beyond  GDP’  monitoring  set.  It  is  vital  to  recognize  that  GDP  is  not  an  inherently  bad 
metric  but  rather,  is  misused  as  an indicator of  something  it  does  not  measure. Metrics 
that  look  beyond  GDP  should  do  more  than  merely  monitor  and  measure:  they  should 
inform  policy  development,  improve  communication  and  promote  target  setting.  There 
are  several  scenarios  here:  include  GDP  as  an  integral  part  of  the  ‘Beyond  GDP’ 
indicator; do not include it but use both as complementary tools; use an adjusted version 
of GDP (e.g., adjusted to the rate of depletion of natural resources). 

The ultimate challenge to developing a ‘Beyond GDP’ monitoring system is, however, not 
the lack of alternative indicators and measuring systems, but instead, the lack of political 
will  to  acknowledge  and  use  them  as  equally  important  drivers  of  policy  decisions  as 
GDP.  This  is  why  a  ‘Beyond  GDP’  measuring  system  should  be  developed  through  a 
public process of collaboration and debate in different countries. To ensure accountability 
of the process, there is also the need for active civil society engagement (NGOs, media, 
researchers, etc.) that would be able to reflect the different critiques of the GDP approach 
and could propose viable and policy-relevant alternatives. 

3.  MAPPING EXISTING INDICATORS  

To  fill  the  policy  research  gap  in  the  assessment  of  the  progress  towards  sustainable 
development, DG Research and Innovation has developed the Transitions Performance 
Index  (TPI)15,  a  composite  index  aiming  to  measure  the  EU’s  progress  towards 
sustainable  and  just  development.  In  developing  its  approach,  DG  Research  and 

15 Transitions Performance Index (TPI) (europa.eu) 

19 

 
  
 
 
Innovation  has  consulted  a  number  of  other  dashboards  and  scoreboards  that  have 
influenced  the  Commission’s  thinking.  To  ensure  the  comprehensiveness  and  policy 
relevance of the future single ‘Beyond GDP’ index, the current study steps on a detailed 
mapping of most available methodologies and selected more than 600 indicators that can 
be considered representative of sustainable development (See annex for a table with the 
complete  list).  Over  the  course  of  the  assessment  of  these  indicators,  they  were 
evaluated  using  both  quantitative  and  qualitative  methods  to  determine  whether  they 
comply with some key criteria including: 

●  A  holistic  view  on  people  and  planet  wellbeing  with  attention  to  spill  over  effects 

from EU internal policies; 

●  Brevity and policy relevance at the same time; 
●  Wide geographical scope and long, time series data availability; 
●  Usefulness  in  terms  of  ranking  countries  as  a  policy  instrument  for  influencing 

national decisions; 

●  Ensuring media and citizen buy-in that would increase awareness of the necessary 
transformational  changes  to  achieving  the  SDGs  and  making  the  ‘Beyond  GDP’ 
approach the standard reference for assessing sustainable development. 

The following section presents a review of the most crucial dashboards, scorecards and 
indices that the TPI builds upon, as well as of the TPI itself. They formed the basis for the 
analytical team’s process of narrowing relevant indicators and of constructing a coherent 
new  Index  that  captures  the  main  elements  of  sustainable  development  emerging  as 
robust metrics across the different SDG areas and the different evaluation approaches. 

Box 1 TPI methodology overview 

The  TPI  was  developed  by  the  European  Commission  as  a  tool  to  monitor  and  rank 
countries’  transition  towards  fair  and  prosperous  sustainability  which  is  measured  on  4 
dimensions, namely economic, social, environmental and governance.  

28  internationally  comparable  indicators  were  chosen  in  line  with  the  6  priorities  of  the 
European  Commission  and  the  17  Sustainable  Development  Goals.  The  scores  for  the 
four dimensions, or pillars, are weighted arithmetic averages of 4 sub-pillar scores each, 
while those are computed as weighted arithmetic averages of indicators. The attribution 
of different weights to indicators, sub-pillars and pillars is based on expert opinions and 
was subsequently adjusted in some cases to boost robustness. All scores for elementary 
indicators are results of a goalpost normalisation procedure that defines upper and lower 
bounds for each indicator and then translates the initial values into a 0-100 scale.  

The index provides data for all EU Member States plus 45 additional countries between 
2011 and 2020 and is updated annually.  

20 

 
 
Source: European Commission, Directorate-General for Research and Innovation, Transitions performance index 2021: 
key findings and rankings, Publications Office of the European Union, 2022. 

Eurostat’s report on SDGs (Sustainable Development Goals)16 

Eurostat conducts an annual assessment of the EU Member States’ movement towards 
or  away  from  the  UN’s  SDGs.  Eurostat  uses  statistical  data  going  back  5  to  15  years, 
which  means  that  there  is  good  geographical  and  time  coverage  for  the  different 
indicators  and  only  a  small  number  of  missing  values.  The  report’s  indicators  are  well-
aligned with the UN SDG indicators and several of them are used to monitor more than 
one goal, reflecting the interconnectedness of the SDGs. When assessing the countries’ 
progress,  the  report  differentiates  between  four  possible  trends:  Significant  progress, 
moderate progress, insufficient progress and movement away from the respective SDG. 
Hence, it allows for a detailed assessment of each country’s trajectory towards individual 
SDGs,  whereas  it  is  not  possible  to  draw  any  conclusions  about  the  countries’  overall 
progress towards the SDGs since the report does not include a composite score. 

16  Sustainable  development  in  the  European  Union  –  2022  edition  -  Products  Flagship  publications  - 
Eurostat (europa.eu) 

21 

 
 
 
 
 
 
Social scoreboard17 

The  Social  Scoreboard  provides  several  headline  and  secondary-level  indicators  taken 
from  Eurostat  that  measure  the  progress  of  EU  member-states  towards  a  more  social 
and  fairer  Europe.  The  scoreboard  is  meant  to  serve  as  a  compass  for  the  EU’s  path 
towards  socio-economic  convergence.  The  overarching  topic  of  employment  and  social 
policies  is  split  into  three  main  dimensions  for  closer  evaluation,  namely  equal 
opportunities,  fair  working  conditions,  and  social  protection  and  inclusion.  All  31 
indicators can be found on Eurostat and exhibit decent availability across countries and 
between  2011  and  2021,  with  few  missing  values.  There  is  no  aggregated  Index 
incorporating the 3 dimensions; instead, trends and current values are displayed for each 
indicator separately. 

Circular economy monitoring framework18 

The  European  Commission’s  Circular  Economy  Action  Plan  is  one  of  the  main  building 
blocks of the European Green Deal, introducing measures to bolster sustainability along 
the entire life cycle of products. To assess the effectiveness of the countries’ measures 
and  progress  towards  achieving  a  circular  economy,  Eurostat  introduced  a  circular 
economy  monitoring  framework  with  a  total  of  10  indicators.  Some  of  them  are  broken 
down  into  sub-indicators  and  into  four  thematic  areas:  Production  and  consumption, 
waste  management,  secondary  raw  materials,  and  competitiveness  and  innovation. 
There  are  no  aggregated  scores  for  the  four  thematic  areas  and  no  composite  index 
score, thus progress can only be monitored separately for each indicator. Most indicators 
are  updated  annually  and  are  available  for  the  past  20  years  although  some  of  the 
metrics  are  only  available  for  the  most  recent  period  and  are  only  updated  every  two 
years.  Some  indicators  such  as  food  waste  and  green  public  procurement  are  not  yet 
available at all. 

Recovery dashboard19 

The  European  Statistical  Recovery  Dashboard  was  initiated  by  the  German  Federal 
Statistical  Office  and  developed  together  with  Eurostat  and  EU  Member  States.  It 
provides  23  monthly  and  quarterly  indicators  both  for  the  whole  EU  and  individual 
Member States that are based on Eurostat’s database. Currently the scoreboard is being 
updated  on  a  monthly  basis,  thus  current  trends  in  indicators  can  be  compared  very 
easily,  however,  the  time  range  varies  widely  between  indicators  (time  series  start  in 
2000 for some, in 2020 for others) which impedes retrospective comparisons over longer 
periods. The focus of the recovery dashboard clearly lies on macroeconomic indicators, 
and it solely presents those raw indicators without calculating composite values. 

Single market scoreboard20 

The Single Market Scoreboard monitors EU Member States’ performance regarding the 
implementation  of  the  single  market’s  four  freedoms  of  movement  (goods,  capital, 
services, and labour/people). There is no aggregated score that allows an overall ranking 
of  how  well  Member  States  are  integrated  in  the  single  market,  but  the  scoreboard 
provides detailed information for each country, for governance tools, per policy area, and 
on integration and market openness. Policy areas are divided into 8 areas that are either 
measured by macroeconomic indicators (e.g. in the case of “greening of the industry”) or 
by the extent to which tools for facilitating cross-border business and job applications are 
used.  Currently,  the  time  span  for  the  scoreboard’s  data  varies  widely  and,  in  most 

17 Social scoreboard indicators - European Pillar of Social Rights - Eurostat (europa.eu) 
18 Monitoring framework - Circular economy - Eurostat (europa.eu) 
19 Recovery Dashboard 
20 The Single Market Scoreboard | Single Market Scoreboard (europa.eu) 

22 

 
 
cases,  only  the  most  recent  data  are  presented,  hence  past  data  cannot  be  extracted 
directly from the online database. 

Justice scoreboard21 

The  EU  Justice  Scoreboard  serves  as  an  objective,  data-based  assessment  of  the 
effectiveness  of  Member  States’  justice  systems.  Its  findings  provide  crucial information 
on the current state of the rule of law and on how EU law is implemented in the Member 
States,  which  is,  amongst  others,  used  for  the  annual  Rule  of  Law  Report  and  the 
assessments within the European Semester. As is usually the case for scoreboards, no 
aggregated  scores  are  calculated,  but  still  each  one  of  the  more  than  50  indicators 
included  in  the  scoreboard  is  assigned  to  one  of  the  three  key  parameters  of  effective 
justice  systems,  namely  efficiency,  quality,  and  independence.  The  justice  scoreboard 
has been updated annually since 2013 and data availability is generally good, however, it 
should  be  noted  that  for  most  efficiency  indicators’  data  is  missing  for  at  least  one 
country. 

Regional competitiveness index22 

The Regional Competitiveness Index employs 70 indicators to measure at NUTS-2 level 
the  quality  of  the  business  environment  and  the  level  of  regional  cohesiveness.  The 
overall  RCI  score  is  composed  of  11  pillars  that  are  divided  into  the  3  groups  Basic, 
Efficiency,  and  Innovation,  whose  relevance  changes  as  regions  become  more 
advanced.  This  is  reflected  in  the  weight  of  the  innovation  sub-index  increasing  with 
higher stages of economic development, while the weight of the Basic sub-index declines 
(meanwhile, the Efficiency sub-index’s weight remains constant at 50%). The index does 
not provide annual data as it is only updated every three years and uses averages of the 
past three years to compute scores for the respective year of publication. 

European innovation scoreboard23 

The  European  Innovation  Scoreboard  (EIS)  assesses  innovation  performance  in  EU 
Member States and associated countries, providing annual data starting in 2014. The EIS 
distinguishes between four main types of activities – Framework conditions, Investments, 
Innovation  activities,  and  Impacts  –  each  of  which  is  divided  further  into  three 
dimensions, capturing 32 indicators in total. Data availability is 100% for all EU countries 
except Ireland (97%) and generally slightly lower for non-EU countries, although for most 
of them it is still above 90%, with the exceptions of Israel, Ukraine, Albania, and Bosnia 
and Herzegovina. Most of the data is readily available on Eurostat. 

DESI24 

The  Digital  Economy  and  Society  Index  has  been  providing  annual  updates  on  EU 
countries’  progress  towards  digitalisation  since  2014.  The  index  has  a  three-level 
structure  consisting  of  4  dimensions,  10  sub-dimensions,  and  32  indicators.  Its  four 
dimensions:  human  capital,  connectivity,  integration  of  digital  technology,  and  digital 
public  services  are  identical  with  the  four  principal  policy  areas  of  the  2030  Digital 
Compass and are equally weighted for the index score. Most of the indicators used in the 
DESI are objective data primarily taken from Eurostat but also from other sources, while 
a small number of indicators come from survey data. 

21 EU Justice Scoreboard (europa.eu) 
22 Regional Competitiveness Index 2019 | Data | European Structural and Investment Funds (europa.eu) 
23 European innovation scoreboard (europa.eu) 
24 The Digital Economy and Society Index (DESI) | Shaping Europe’s digital future (europa.eu) 

23 

 
 
Social progress index25 

The Social Progress Index focuses exclusively, comprehensively, and systematically on 
the  non-economic  dimensions  of  social  progress.  Social  progress  is  defined  as  “the 
capacity of a society to meet the basic human needs of its citizens, establish the building 
blocks  that  allow  citizens  and  communities  to  enhance  and  sustain  the  quality  of  their 
lives, and create the conditions for all individuals to reach their full potential”26. The index 
consists of 3 dimensions, 12 components and 60 indicators, covering 169 countries fully 
and another 27 partially. Each of the indicators chosen for the index is linked to at  least 
one  of  the  UN’s  Social  Development  Goals  and  each  objective  is  characterised  by  the 
monitoring of at least one indicator.  The final index score is the arithmetic average of the 
3 dimensions: basic human needs, foundations of well-being and opportunity. 

While all of the aforementioned indices and scoreboards make a valuable contribution to 
improving  the  methodology  for  measuring  sustainable  development  beyond  GDP,  none 
of them have been able to establish themselves as widely-accepted alternatives to GDP, 
thus there is a need for further research. A summary of these existing approaches can be 
found in the table below. The full list of 600+ indicators reviewed and statistically tested 
can be found in the Annex below. 

Table  1  Selected  indices,  scoreboards  and  dashboards  relevant  for  the  ‘Beyond 
GDP’ approach to sustainable development 

Name 

Transitions 
Performance 
Index (TPI)  

Geograph
ical 
coverage 

Time 
coverage 

General 
overview 
and goal 

2011 to 
2020 

All EU 
countries 
and 45 
other 
countries 

Monitoring 
and ranking 
countries 
based on 
their 4 
transitions 
(economic, 
social, 
environmenta
l, 
governance) 
to fair and 
prosperous 
sustainability 

Data availability 

Two criteria for 
inclusion of 
additional 
countries: A 
maximum of three 
missing data 
points out of 28 
(10.7%); and a 
maximum of one 
missing data point 
per pillar. 

Main 
indicators 
used/ 
exemplary 
indicators27 

Some of the 
indicators with 
the highest 
weight: 

●  Gross 

greenhouse 
gas 
emissions 
(tonnes per 
capita) 
●  Energy 

productivity 
(PPP$ per 
koe) 
●  Homicide 
rate (per 

25 Social Progress Imperative | Social Progress Imperative 
26 Stern, S., Harmacek, J., Krylova, P. & Htitich, M.: 2022 Social Progress Index Methodology Summary. 
Social Progress Imperative. Washington, DC. Available at: www.socialprogress.org/global/methodology 
27 The presented indicators were primarily chosen to provide readers with a general idea of the contents of 
the respective index, scoreboard or dashboard. ‘Main indicators’ refers to the ones that are given the most 
weight in the indices, whereas ‘exemplary indicators’ refers to dashboard indicators for which there is no 
intuitive order of importance. 

24 

 
 
 
 
Eurostat’s report 
on SDGs 

EU 

All data: 
2010-2021 

Social 
Scoreboard 

2011-2021 

EU + 
Iceland, 
Switzerland
, Norway 

Circular Economy 
monitoring 
framework 

EU + 
Iceland, 
Switzerland
, Norway 

Varies from 
2012 the 
earliest until 
2021 

Provides an 
assessment 
of indicator 
trends over 
time against 
SDG-related 
EU objectives 
and targets 

The 
European 
Pillar of 
Social Rights 
has been put 
forward to 
serve as a 
compass for 
a process 
leading to 
renewed 
socio-
economic 
convergence.  

Main 
dimensions: 
Equal 
opportunities, 
fair working 
conditions, 
social 
protection 
and inclusion 

Monitoring 
allows the 
European 
Commission 
and other 
policy makers 
to keep track 
of the 
progress 
made and 
assess the 
effectiveness 
of their 
actions. It 
also provides 
a clear signal 
to economic 
actors such 
as business 
and 
household 

25 

Not all 17 SDGs 
are shown for 
each country. 

●  Progress score 
calculations are 
based on shorter 
or longer periods 
for some countries 

Most data are 
available for all 
countries, except 
“Individuals who 
have basic or 
above basic 
overall digital 
skills” 

4/23 indicators are 
not available on 
the country-level, 
only for EU 

100,000 
inhabitants) 

●  Gini 

coefficient 

●  Years of life 

lost due to 
PM2.5 
exposure 
Tertiary 
educational 
attainment 

● 

●  Share of 

renewable 
energy in 
gross final 
energy 
consumption 
Income 
inequality 
●  Employment 

● 

rate 
●  At-risk-of-
poverty or 
social 
exclusion 
rate 

●  EU self-

sufficiency 
for raw 
materials, 
aluminium  
●  Recycling 
rates 
●  Circular 

material use 
rate 
●  Private 

investment, 
jobs and 
gross value 
added 
related to 
circular 
economy 
sectors 

 
Recovery and 
Resilience 
Scoreboard 

EU 

2021- 

Recovery 
Dashboard 

EU + 
Iceland, 
Switzerland
, Norway 

Single Market 
Scoreboard 

EU + 
Iceland, 
Switzerland
, Norway 

Some of the 
indicators 
from 2007-
2021 others 
only from 
2020 
onwards 

Depends on 
the 
indicator, 
earliest 
1997, latest 
2020 

Justice 
Scoreboard 

EU 

2013-2021 

consumers 
on ongoing 
trends. 

The Recovery 
and 
Resilience 
Scoreboard 
gives an 
overview of 
how the 
implementatio
n of the 
Recovery and 
Resilience 
Facility (RRF) 
and the 
national 
recovery and 
resilience 
plans is 
progressing. 

Providing 
data on the 
impact of the 
Covid crisis in 
the economic, 
financial and 
social 
spheres 

As part of the 
Single Market 
strategy, the 
Single Market 
Scoreboard 
monitors the 
countries’ 
performance 
when 
implementing 
the four 
freedoms 
(goods, 
capital, 
services, and 
labour/people
). 

Presenting an 
annual 
overview of 
indicators on 
the efficiency, 
quality and 
independenc
e of national 
justice 
systems, the 
EU Justice 
Scoreboard 

26 

● 

Fulfilled 
milestones 
and targets 
of the NRRP 

Available for all 
EU countries 

●  Excess 

mortality 
●  Bankruptcy 
declarations 

●  Air quality 

Overall good data 
availability across 
countries 

Data available for 
all countries 

●  Evolution of 
transposition 
deficit 
●  Evolution of 

conformity 
deficit 
●  Evolution of 
infringement 
cases 

For many 
indicators data are 
not available for at 
least two countries 

● 

Length of 
proceedings 

●  Availability 
of legal aid 
●  Perceived 
judicial 
independenc
e 

 
Regional 
Competitiveness 
Index 

EU 

2010,2013,
2016,2019 

European 
Innovation 
Scoreboard 

EU + 11 
non-EU 
countries 

2014-2021 

Digital Economy 
and Society 
Index (DESI) 

EU 

Depends on 
the 
indicator, 
generally 
early 2000s 
until 
2020/2021 

traces 
developments 
in the rule of 
law in EU 
Member 
States. 

The Index 
measures 
with more 
than 70 
comparable 
indicators the 
ability of a 
region to offer 
an attractive 
and 
sustainable 
environment 
for firms and 
residents to 
live and work. 

The EIS 
assesses the 
relative 
strengths and 
weaknesses 
of national 
innovation 
systems and 
helps 
countries 
identify areas 
they need to 
address. 

Monitoring 
digital 
progress and 
supporting 
Member 
States in 
identifying 
areas 
requiring 
priority action 
as well as 
thematic 
chapters 
offering a 
European-
level analysis 
across key 
digital areas, 
essential for 
underpinning 
policy 
decisions. 

Good data 
availability for all 
regions 

●  Population 
accessible 
by railway 

●  Heart 

disease 
death rate 

●  Early school 
leavers 
●  Household 

access to 
internet 

● 

International 
scientific co-
publications  

Good data 
availability for all 
countries 

●  Broadband 
penetration 

●  R&D 

expenditures 
in the 
business 
sector 

●  SMEs selling 
online 

●  E-

Government 
users 
●  Enterprises 

● 

analysing 
big data 
from any 
data source 
Individuals 
with ‘basic’ 
or ‘above 
basic’ digital 
skills 

Good data 
availability for all 
countries 

Social Progress 

Almost all 
countries in 

2011-2021  Meeting the 

pressing 

27 

●  Deaths from 
infectious 

Good data 
availability for all 

 
Index 

the world 

countries 

diseases 
●  Access to 
improved 
sanitation 
●  Women with 
no schooling 

●  Outdoor air 
pollution 
attributable 
deaths 
●  Equality of 
political 
power by 
social group 

needs of 
communities 
and 
equipping 
them with the 
right 
information to 
tackle urgent 
global 
challenges 
like Covid-19 
and climate 
change. 
Develop data-
driven tools 
that measure 
whether 
people have 
what they 
need to 
prosper, 

28 

 
 
 
 
 
4.  CONSTRUCTING  ALTERNATIVE  VISIONS  OF  THE  TRANSITIONS 

PERFORMANCE INDEX: METHODOLOGICAL APPROACH  

The  methodological  approach  used  for  the  assessment  of  the  identified  indicators 
involves the deconstruction of multiple composite indicators and instruments to their 
building blocks, i.e. their lowest level indicators and then assessing both the primary 
indicators  and  the  composite  indices  along  multiple  qualitative  and  quantitative 
dimensions.  

The  process  of  indicators  assessment  began  by  listing  and  reviewing  all  EU 
dashboards  and  indicators  used  for  monitoring  EU  policies  as  well  as  other 
internationally-recognized 
the  previous  section.  These 
composite indexes and dashboards were deconstructed to their building blocks, i.e. 
their  lowest  level  indicators,  which  resulted  in  a  database  with  624  primary  and 
secondary  indicators,  as  well  as  a  limited  number  of  composite  indices.  Technical 
information was collected for all 600+ indicators from the database including: 

indices  mentioned 

in 

Indicator description and structure (in the case of composite indicators), 

● 
●  Measurement  units  and  data  type:  objective  data  vs  expert  assessments  vs 

polls vs other; 

●  Data sources: national statistics / Eurostat; other sources; ad hoc surveys, etc.;  
●  Data availability: geographical coverage, time coverage, update regularity, etc.; 

how many composite indexes rely on this raw indicator and others.  

All 624 metrics were then rated by at least 2 in-house experts for:  

1.  Comparability  over  time  and  space,  whether  the  indicator  is  interpreted 

consistently in different composite indexes;  

2.  How self-explanatory is the raw indicator;  
3.  Conceptual connection to GDP;  
4.  Predicting power of the indicator about different social/economic phenomena; 
5. 
Link to the SDGs (and if so, how many SDGs is it related to);  
6.  Uniqueness of the indicators in terms of dimension coverage.  

In the case of discrepancies between the experts’ assessment scores, more experts 
provided  their  assessments  in  a  Delphi-style  discussion.  A  combined  qualitative 
score was computed based, on the one hand, on the expert assessment scores and, 
on  the  other,  on  the  update  frequency,  number  of  SDGs  the  indicator  is  related  to 
and number of composite indexes the indicator is included in.  

Following  this  initial  process,  202  primary  indicators  and  composite  indexes  were 
selected  based  on  the  highest  qualitative  score  as  well  as  on  covering  all  the 
important  thematic  dimensions  linked  to  sustainable  development.  Data  was 
collected for all 202 metrics and for all EU-27 Member States with a 2011-2020 time 
coverage.  This  also  led  to  a  more  precise  estimate  of  the  data  availability  for  the 
indicators – on a scale from 0 to 270, where 270 meant data were available for all 27 
Member States and an EU-27 aggregate for all years between 2011 and 2020.  

The  next  step  included  various  statistical  tests  performed  on  143  indicators  and 
indexes  for  which  there  had  been  enough  data  points.  The  indicators  were  tested 
through  a  series  of  statistical  analyses  including  Correlation  Analysis,  Regression 

29 

 
Analysis  and  Principal  Component  Analysis.  Missing  data  points  for  the  remaining 
143 indicators were replaced through a multiple imputations procedure where all 143 
indicators were included as predictors. Imputed data points were less than 10% for 
each indicator. Principal Component Analysis and Factor Analysis included principal 
components method of extraction as well as principal axis factoring extraction, then 
different  types  of  rotation  were  attempted:  Varimax,  Promax  and  Direct  Oblimin. 
Analyses  with  extraction  based  on  eigenvalues  (with  an  eigenvalue  above  1 
criterion)  were  performed  as  well  as  extraction  based  on  a  fixed  number  of  factors 
(either 5  or 12) were  both  attempted.  The  performance  of  difference  indicators  and 
indexes in the various analyses was studied carefully and considered when selecting 
the final short list of 32 indicators.    

The  tests  described  above  led  to  a  quantitative  assessment  of  each  of  the  143 
indicators.  The  quantitative  score  was  based  on  the  uniqueness  of  the  indicator 
(whether it represented a different principal component or belonged in a group with 
many  other  indicators),  on  its  strength  in  terms  of  good  representation  of  its 
respective  dimension  (based  on  factor  loading  score),  on  its  usefulness  (i.e. 
whether  it  represented  a  strong  dimension  that  could  be  interpreted  qualitatively  or 
not) and on its EU-27 data availability on the scale from 0 to 270.  

The  statistical  assessment  yielded  21  possible  groups  of  indicators.  Several 
indicators  were  selected  from  each  group  based  on  the  quantitative  scores  of  the 
indicators,  on  the  importance  of  the  group  (in  terms  of  variance  explained)  and  on 
qualitative expert assessment of the salience of the indicators and different groups. 
This eventually led to 32 indicators and composite indexes that were short-listed for 
further assessment and testing.  

The  next  step  in  the  assessment  process  included  an  online  survey,  where  18 
international experts in the field assessed all 32 indicators on 8 dimensions: General 
Relevance, Effectiveness, Policy relevance, Early warning strength, Short-term 
changes  sensitivity,  Foresight  assessment  sensitivity,  Robustness  to  Data 
Manipulation,  and  Robustness  to  Subjective  Bias.  An  average  score  was 
computed  for  all  32  indicators,  ranking  them  from  number  1  with  the  highest  score 
(“Gross  greenhouse  gas  emissions  (tonnes  per  capita)”)  to  number  32  (“Freedom 
House's Freedom in the World Index”).  

More  detailed  in-depth  interviews  were  then  organized  with  five  of  the  experts  who 
took  part  in  the  survey.  The  in-depth  interviews  aimed  at  tapping  into  the  experts’ 
knowledge  and  opinion  on  various  aspects  of  the  current  exercise  including  the 
challenges in developing a ‘Beyond GDP’ monitoring set, a conceptual framework for 
sustainable development assessment as well as the difficulties when communicating 
the results to different stakeholders. More concrete questions were asked regarding 
the  nature  of  the  different  indicators  from  the  list  and  the  experts’  rationale  behind 
preferring  a  certain  indicator  over  the  rest.  General  findings  from  the  in-depth 
interviews were considered when building the final two ‘Beyond GDP’ indexes.  

Finally,  additional  statistical  tests  were  performed  on  the  short-listed  32  indicators. 
These  led  to  outlining  9  possible  groups  of  indicators,  of  which  12  final  indicators 
were selected based on the statistical analyses, on the expert survey ranking of the 
indicators,  and  on  the  in-depth  interviews  information.  These  12  indicators  were 
grouped in 5 different dimensions, finally narrowing down the selection to the best 5 
indicators  representing  these  5  dimensions  in  an  ambitious  scenario.  All  indicators 

30 

 
were  normalised  using  min-max  normalisation,  and  where,  needed  scales  were 
inverted  so  that  for  every  indicator  larger  values  meant  better  performance. 
Normalised  scales  are  from  0  to  100  and  the  final  index  computed  for  the  two 
scenarios shares the same scale - from 0 to 100 where 0 is the lowest performance 
score and 100 is the highest28.  

5.  TWO ALTERNATIVE INDICES  

On the basis of the thorough statistical and expert assessment of the most relevant 
indicators,  we  have  developed  two  separate  proposals  for  alternative  analytical 
frameworks for monitoring ‘Beyond GDP’ progress to sustainable development: 

●  An ambitious scenario with 5 statistically tested indicators (including GDP), 

and 

●  A transition scenario with 12 indicators that is more encompassing of the 
different existing approaches for the monitoring of sustainable development 
progress. 

A third sensitivity version of the ambitious scenario was also developed, whereas 
GDP  is  dropped  from  the  list  of  five  indicators  and  instead  the  Material  Footprint 
metric is added as to test the process of decoupling of economic growth from the use 
of  resources,  which  is  a  key  ingredient  to  achieving  long-term  sustainable 
development. 

The  assessment  of  the  two  versions  reflects  on  their  statistical  robustness  and 
inherent  biases  and  should  not  be  seen  as  the  one  and  only  possible  approach  to 
measuring  the  performance  of  sustainable  development  policies.  However,  the 
selected  indicators  are  the  result  of  a  robust,  data-driven  and  encompassing 
approach to studying the pathway to sustainable development focused on the overall 
well-being  of  individuals  and  societies  stepping  on  the  existing  metrics  in  place  for 
monitoring of the progress to achieving the SDGs.  

To  go  the  extra  mile,  the  study  pilots  the  two  alternative  methodologies  using  the 
collected data from the selected indicators for the EU-27 countries. This was crucial 
to  ensure  the  chosen  levers  are  robust  and  to  avoid  inherent  biases  or 
interdependencies  that  may  skew  the  evaluation  of  the  sustainable  development 
progress. 

Below  are  short  descriptions  of  the  chosen  indicators  and  a  brief  overview  of  the 
piloting results: 

Real  GDP  per  Capita  is  a  measurement  of  the  total  economic  output  of  a  country 
divided  by  the  number  of  people  and  adjusted  for inflation.  This  is  a  very  suitable 

28 Z-score normalisation was discussed internally as an alternative to min-max normalisation, but in 
the end min-max was chosen as a simple and transparent way of normalising the data that produces 
the exact same scale for all indicators. While this approach was selected as the most convenient one 
for  the  purposes  of  pilot  testing  and  demonstrating  the  two  BGDP  index  scenarios,  there  are 
important shortcomings to  the  min-max  approach,  namely  its  poor  handling  of  outliers  and  its very 
strong  dependency  on  the  maximum  and  minimum  values  in  a  current  dataset.  A  careful 
consideration  of  the  different  normalisation techniques  as  well  as more  rigorous testing  of  the final 
index would be recommended if any of the suggested scenarios is to be adopted. 

31 

 
 
indicator to compare the standard of living between countries and over time. Many of 
the experts who participated in the in-depth interviews pointed out that an adjusted-
form of GDP should be included in the monitoring set.  

Gini Coefficient of Disposable Income, after Taxes and Transfers is a measure 
of the extent to which the distribution of income or consumption among individuals or 
households  within  an  economy  deviates  from  a  perfectly  equal  distribution.  This  is 
one of the most well-known and utilized measures of economic inequality. Its role for 
measuring  income/wealth  inequality  can  be  related  both  to  the  human  capital 
dimension of a ‘Beyond GDP’ index and to the economic development dimension. Its 
calculation  does  not  depend  on  the  size  of  the  economy  or  population.  The 
advantage of the Gini index is that inequality of the entire income distribution can be 
summarized by using a single, relatively easy to interpret, statistic, which allows for 
comparison among countries with different population sizes. 

Unemployment Rate (% of labour force 15-74) is the share of people in the labour 
force, who do not currently have a job but are actively looking for work. It is one of 
the most significant economic indicators to measure the health of an economy. It is 
among  the  metrics  most  commonly  watched  by  policy  makers,  investors,  and  the 
general public. Since it tends to fluctuate with the business cycle, central banks and 
policy  makers  consider  unemployment  rate  to  gauge  a  recession’s  impact  and  to 
decide how to tailor fiscal and monetary policies to mitigate its adverse effects on the 
economy.  The  indicator  represents  the  fourth  principal  component  from  the  PCA, 
where  it  has  the  highest  factor  loading  (0.89).  Moreover,  it  received  quite  high 
assessment scores by the experts, ranked 12th overall.  

Gross Greenhouse Gas Emissions (tonnes per capita) is a paramount measure 
of  the  progress  towards  climate  neutrality.  The  indicator  received  the  highest 
assessment scores on average from all 32 indicators included in the expert survey. 
can  be  relatively  easily  evaluated  across  different  sectors.  The  indicator  is  also 
standardized per capita as to neutralize the impact of the size of the population.  

Raw  Material  Consumption  (tonnes  per  capita)  or  Material  Footprint  is  a 
consumption-based indicator of resource use, which refers to the total amount of raw 
materials  extracted  to  meet  final  consumption  demands.  Thus,  it  is  an  appropriate 
signal of the pressures placed on the environment to support economic growth and 
to satisfy peoples’ material needs and wants. While Domestic Material Consumption 
(DMC)  considers  the  tonnage  of  materials  extracted  domestically  (to  which  imports 
are added and exports subtracted), it is insufficient to consider the full range of raw 
materials  actually  being  mobilized  to  sustain  domestic  demand  for  goods  and 
services  from  resident  economic  agents.  The  reason  for  this  is  that  DMC  does  not 
include indirect flows of raw materials. To the contrary, Raw Material Consumption, 
also known as Material Footprint, is the total amount of natural resources demanded. 
It provides the much-needed perspective on global material supply chains and on the 
shared responsibility for the extraction, processing, and consumption of resources.29 
Besides the indicator is adjusted for population. This is a viable measure to indicate 

29 Wiedmann T, Schandl H, Lenzen M, Moran D, Suh S, West J, Kanemoto K (2013) The material 

footprint of nations. Proc Natl Acad Sci USA 112(setembro). 

32 

 
 
 
 
 
and  track  the  progress  of  SDG  12  (Responsible  production  and  consumption).  It  is 
imperative  to  include  this  aspect  in  the  monitoring  set  because  the  global  material 
footprint  has  been  increasing  at  a  faster  rate  than  both  population  and  economic 
output.  In  addition,  the  material  footprint  of  high-income  economies  has  been 
exceeding their domestic material consumption (indicating their reliance on materials 
through international supply chains).  Raw material consumption (tonnes per capita) 
reflects the 7th principal component of the PCA. It was ranked as the 6th most useful 
indicator  by  the  experts  and  it  provides  an  important  view  on  sustainability  by 
focusing on the planetary constraints rather than on pure economic growth. 

Energy Consumption per Capita is the indicator that measures the key input in all 
phases  of  production  and  consumption  in  a  society.  Energy  is  the  essential 
ingredient in economic growth and in any strategy for improving the quality of human 
life. Despite increasing energy production, energy poverty is still a global concern. It 
is  well  known  that  the  energy  demand  of  countries  is  increasing,  but  the  resources 
used  to  generate  energy  are  limited  in  both  amount  and  range.  There  is  uneven 
distribution  of  energy  resources  and  a  significant  imbalance  in  consumption  levels 
between  countries  and  regions.  Therefore,  Energy  Consumption  per  Capita  is  an 
indispensable  component  of  SDG  7  (Affordable  and  clean  energy)  and  must  be 
incorporated  in  any  ‘Beyond  GDP’  monitoring  set.  The  indicator  was  ranked  very 
high by the experts (rank 4 from all indicators included in the expert survey). Energy 
Consumption  per  Capita  ultimately  replaced  another  strong  candidate  for  the  final 
12:  Terrestrial  key  biodiversity  areas  (KBAs)  protected  (%),  ranked  5th  and 
representing the 9th principal component.30 

Life  Satisfaction  is  a  crucial  indicator  for  societal  welfare  as  it  effectively 
complements  other  measures  of  people’s  well-being,  such  as  their  income, 
education,  health,  family  circumstances,  social  conditions,  etc.  Therefore,  life 
satisfaction is a good proxy for overall well-being. For this reason, surveys such as 
the Gallup World Poll and the World Happiness Data Base are becoming an integral 
part of the ‘Beyond GDP’ discussion. The indicator considers people's evaluation of 
their life as a whole. It is a weighted-sum of different response categories based on 
people's  rates  of  their  current  life  relative  to  the  best  and  worst  possible  lives  for 
them  on  a  scale  from  0  to  10,  using  the  Cantril  Ladder  (known  also  as  the  "Self-
Anchoring  Striving  Scale").  Although  measuring  feelings  can  be  criticized  as  being 
rather subjective, it is nonetheless a useful complement to more objective data when 
evaluating quality of life and sustainable development. The fact that the Gallup World 
Poll uses the same questionnaire in all countries, ensures maximum comparability of 
results.  Another  potential  thorny  issue  is  to  what  extend  the  English  language 
concept of “life satisfaction” is translatable into different languages. Yet, compared to 

30 In terms of statistical analyses, Terrestrial key biodiversity areas (KBAs) protected (%) represented 
the weakest 9th principal component that explained only 3.4% of the overall variance for the 30 
indicators  included  in  the  analysis.  While  we  acknowledge  that  biodiversity  is  really  important 
and should definitely be considered as a sub-dimension in a future ‘Beyond GDP’ index, none 
of  the  short-listed  indicators  related  to  biodiversity  managed  to  reflect  well  enough  this 
dimension. "Grassland loss" is another indicator grouped in the same principal component and 
was also considered, but in the end "Energy Consumption per Capita" was selected instead as 
a  critical  indicator  of  climate  neutrality.  In  addition,  according  to  the  European  Environmental 
Agency,  ‘protected areas are the backbone of nature conservation, but this type of ‘protection 
regime’ is not sufficient to address the significant pressures on European biodiversity’. Indeed, 
despite the increase of protected areas in Europe the last 10 years, Europe continues to lose 
biodiversity (source: SOER 2019, EEA) 

33 

 
 
happiness-style  questions,  the  problem  is  less  pronounced.  Despite  the  fact  that 
there  are  known  limitations  and  inconsistencies  with  using  Life  Satisfaction  as  a 
proxy  for  overall  well-being  (i.e.,  cultural  differences;  varying  perceptions  of  reality; 
personal differences etc.), it has been demonstrated to correlate well with objective 
assessments  of  well-being31  and  is  measured  at  regular  intervals  (for  most  UN 
countries).  The  indicator  was  correlated  with  multiple  Principal  components,  one  of 
which  was  the  important  first  “governance”  dimension.  In  addition,  life  satisfaction 
has very high correlation with The World Justice Project Rule of Law Index (r = 0.88) 
as well as with the Gender Equality Index (r = 0.76) effectively serving as a proxy for 
both composite indicators. The relative simplicity of this indicator, combined with the 
reliability,  availability  and  wide  geographic  coverage  of  the  Gallup  World  Poll  made 
this  indicator  not  only  a  must  among  the  12  short-listed  indicators,  but  also  the 
preferred  indicator  for  a  ‘governance  that  delivers’  category  in  the  ambitious 
scenario.    

Human  Development  Index  is  a  composite  measure  of  average  progress  in  key 
dimensions  of  human  development:  health,  education  and  the  standard  of  living. 
While  representing  the  governance  dimension  in  the  ambitious  scenario  with  Life 
satisfaction  only,  the  study  wanted  to  include  a  well-known  governance-related 
indicator in the transition scenario. Despite their low average assessment scores on 
the expert survey, composite indexes like Rule of law from the Worldbank Worldwide 
Governance Indicators, The World Justice Project Rule of Law Index, Freedom in the 
World Total, and Human Development Index (HDI) remain instantly recognizable and 
easily associated with good governance. As we used Principal Component Analysis 
to test the structure of the suggested indicator, we tried to select the best indicators, 
representing  their  corresponding  principal  component.  The  PCA  was  performed  on 
30 of the 32 short-listed indicators. It grouped together Human Development Index, 
Rule of law from the Worldbank Worldwide Governance Indicators, and Freedom in 
the  World  Total  (together  with  other  indicators)  in  one  large  principal  component 
explaining 28% of the overall variance. HDI and the Rule of Law from WGI had by far 
the  highest  factor  loadings  for  this  principal  component  with  0.9  and  0.815 
respectively.  The  World  Justice  Project  Rule  of  Law  Index  was  not  included  in  the 
PCA  at  all,  since  there  were  not  enough  data  points.  Since  HDI  has  the  highest 
factor loading and is based on objective data as well as better known than the  Rule 
of  Law  from  WGI,  HDI  was  considered  as  the  top  candidate  to  represent  this 
particular principal component. 

In-work-at-risk-of-poverty  rate  (%  population)  is  the  indicator  with  the  third 
principal component together with Gini coefficient. In-work-at-risk-of-poverty rate was 
ranked  11th  in  the  expert  survey  and  its  factor  loading  was  0.87.  The  indicator  is 
based on objective data and represents well the human capital dimension as it is a 
good  proxy  of  whether  societies  can  provide  the  economic  means  for  humans  to 
overcome poverty factors when their labour is utilized. The higher the share the less 
efficient  is  human  labour  utilized  for  providing  the  necessary  means  for  ensuring  a 
high living standard. 

31  Oswald,  A.  J.,  & Wu,  S. (2010). Objective  confirmation  of  subjective  measures  of  human  well-
U.S.A. Science, 327(5965), 576–

Evidence 

the 

being: 
579. https://doi.org/10.1126/science.1180606 

from 

34 

 
 
Gender Employment Gap is an indicator that measures the difference between the 
employment  rates  of  men  and  women,  and  is  part  of  the  EU  SDG  indicator  set  to 
monitor progress towards SDG  5 (Achieve gender equality and empower all women 
and  girls),  which  is  embedded  in  the  European  Commission’s  Priorities  under 'An 
economy  that  works  for  people'  and  'A  new  push  for  European  democracy'. 
Increasing female labour market participation and the equal economic independence 
is  one  of  the  priorities  of  the EU  Gender  Equality  Strategy,  which  commits  to 
achieving a Union of Equality. The Gender Employment Gap forms the fifth principal 
component of the PCA together with Employment-to-population ratio gender gap 25+ 
(%).  Both  indicators  had  very  high  factor  loadings  (above  0.9),  however  Gender 
Employment  Gap  was  slightly  higher,  and  in  addition,  it  was  ranked  higher  in  the 
expert  survey  (rank  15)  compared  to  the  Employment-to-population  Ratio  Gender 
Gap (rank 24). Therefore, the Gender Employment Gap was the one selected as an 
indicator representing gender inequality in particular and related to the human capital 
dimension in general. 

Air Quality is an indicator that measures the level of air pollution, which is one of the 
primary causes of health ailments and premature deaths in the world, is an outcome 
of  the  complex  interaction  of  multiple  factors  involving  meteorological  parameters, 
chemical  reactions,  and  emissions  from  natural  and  anthropogenic  sources.  A 
pressing  sustainability  concern,  air  pollution  is  directly  mentioned  in  two  SDG 
targets: SDG  3.9 
from  hazardous 
substances) and SDG 11.6 (reduction of adverse impacts of cities on people). Thus, 
Air  Quality  deserves  a  place  in  the  ‘Beyond  GDP’  scenario  not  only  as  a  health 
indicator,  but  also  as  a  proxy  for  good  governance.  Air  Quality  reflects  the  second 
Principal component of the PCA (explaining 14% of the variance). Air Quality had the 
highest factor loading (0.75), and at the same time, it is the second highest ranked 
indicator in the expert survey. Representing the health dimension, Air Quality’s role 
in both the transition and the ambitious scenario is undeniable.   

(substantial  reduction  of  health 

impacts 

Healthy  Life  Expectancy  at  Birth  (years)  is  an  indicator  of  the  quality  of  health 
governance,  including  the  impacts  of  mortality  and  morbidity,  which  offers  a 
summary  of  the  overall  health  conditions  for  a  population,  which  are  in  turn  an 
integral  part  of  sustainable  development.  It  reflects  many  social,  economic,  and 
environmental  influences  and  impacts.  Besides,  the  indicator  is  closely  related  to 
other  demographic  variables  but  it  provides  a  more  complete  picture  than  life 
expectancy  alone.  Healthy  Life  Expectancy  is  a  vital  measure  of  the  health  of  the 
population  because  it  indicates  whether  any  gains  in  life  expectancy  are  lived  in 
good  health:  a  greater  number  of  healthy  life  years  translates  into  healthier 
workforce,  fewer  early  retirements,  reduced  long-term  care  needs  and  higher  life 
satisfaction. Healthy life expectancy increases are the result of, among other things, 
improvements  in  health,  nutrition,  economic  and  social  conditions.  It  is  correlated 
with  the  strongest  two  Principal  components  (0.46  and  0.48  respectively)  thus 
playing  the  double  role  of  a  proxy  for  good  governance  and  important  part  of  the 
health  dimension.  It  was  ranked  13  in  the  expert  survey,  confirming  once  again  its 
importance as an indispensable part of the transition scenario. 

35 

 
 
 
 
 
Figure 1 Two alternative visions for a ‘Beyond GDP’ sustainable development 
monitoring framework 

Source: CSD 

5.1 Ambitious scenario 

The ambitious ‘Beyond GDP’ scenario (BGDP-A) includes 5 indicators, one of which 
remains  GDP,  allocated  in  five  representative  categories.  Simpler  primary-level 
indicators  were  chosen  rather  than  composite  indices,  also  considered  a  soft 
constraint for this scenario. The list of indicators are:  

●  Economic Development: Real Gross domestic product (GDP) per capita,  
●  Climate Neutrality: Gross greenhouse gas emissions (tonnes per capita),  
●  Health: Air quality  
●  Human Capital: In-work-at-risk-of-poverty rate (% population),  
●  Governance that Delivers: Life satisfaction.  

The  five  chosen  indicators  are  powerful  proxies  for  measuring  the  success  of 
environmental,  social,  and  economic  policies.  The  goal  on  the  economic  side  is  to 
ensure  that  the  chosen  metrics  are  giving  more  attention  to  inequality  issues.  This 
reflects  a  common  observation  by  many  experts  working  on  alternative  visions  for 
measuring  well-being  that  indices  should  measure  not  economic  inputs  (such  as 
production,  value-added,  assets  accumulation,  etc.)  but  quality  of  life  based  on 
outcomes,  among  others,  related  to  healthy  well-being,  satisfaction  with  the  life 
experience,  clean  air,  environmental  sustainability  linked 
to  climate  change 
adaptation and biodiversity preservation.  

The five metrics are representative of broader development objectives including the 
standard  macroeconomic  understanding  of  economic  growth  (increasing  annual 
GDP per capita), the cornerstone of the European Green Deal and the global climate 
agreements  (Gross  Greenhouse  Gas  Emissions),  an  indirect  measurement  of 
poverty reduction and inequality policies linked to the realisation of human potential 

36 

 
 
(In-work-at-risk-of-poverty rate), a proxy indicator that provides a crucial link between 
health  and  sustainability  (air  quality),  and  finally,  a  comprehensive  indicator  that 
captures  the  perception  of  individuals  of  the  overall  quality  of  governance  and  its 
impact on people’s self-actualization (Life satisfaction). These five indicators, due to 
their  strong  statistical  robustness  and  wide  geographical  and  time  availability,  are 
strong  predictors  of  the  success  of  sectoral  policies  for  ensuring  inclusion, 
sustainability and well-being.  

The  results  from  the  piloting  of  the  ambitious  scenario  of  the  Index  in  the  EU-27 
countries  reveals  an  only  marginal  improvement  of  sustainability  across  the 
assessed  areas  (See  Table  2).  The  stagnation  of  economic  growth  in  many  of  the 
the  COVID-19  pandemics  have 
largest  European  countries  combined  with 
undermined  the  fundamentals  of  European  prosperity  and  well-being.  The  gains 
achieved  in  the  decarbonisation  of  the  European  economy,  represented  by  the 
decline  in  gross  greenhouse  gas  emissions,  have  been  offset  by  worsening  air 
quality, lower life satisfaction and stagnant rates of poverty and inequality.  

Table  2  ‘Beyond  GDP’  ambitious  scenario  with  GDP  included.  Higher  scores 
mean better performance. 

2011 

2012 

2013 

2014 

2015 

2016 

2017 

2018 

2019 

2020 

67.4 

65.9 

66.2 

68.6 

69.1 

69.9 

69.0 

68.5 

71.2 

68.0 

67.8 

67.5 

67.6 

69.2 

69.7 

69.5 

69.1 

69.4 

71.0 

68.1 

29.8 

40.2 

44.9 

42.1 

45.4 

44.0 

43.5 

48.5 

48.5 

45.3 

56.3 

54.3 

53.3 

56.2 

54.4 

56.6 

57.5 

62.4 

61.6 

61.0 

49.8 

50.0 

52.3 

54.7 

54.8 

58.0 

57.7 

60.2 

61.1 

56.0 

Austria 

Belgium 

Bulgaria 

Croatia 

Cyprus 

Czechia 

57.9 

57.6 

58.8 

60.8 

61.6 

62.7 

59.2 

62.1 

65.9 

63.0 

Denmark 

72.0 

76.5 

76.5 

77.1 

77.9 

79.1 

80.4 

77.4 

79.5 

77.9 

Estonia 

EU-27 

Finland 

50.6 

51.5 

51.1 

46.7 

53.5 

54.3 

53.8 

56.2 

59.1 

49.8 

56.6 

58.2 

58.9 

59.3 

59.1 

59.9 

60.3 

61.2 

63.5 

58.1 

74.7 

75.7 

76.2 

77.1 

80.0 

80.7 

82.0 

81.0 

82.4 

77.5 

37 

 
 
France 

64.8 

64.2 

64.1 

66.8 

67.7 

67.9 

69.2 

70.1 

70.6 

66.2 

Germany 

63.2 

64.6 

63.6 

61.7 

64.0 

64.8 

65.4 

67.1 

69.4 

63.9 

Greece 

Hungary 

Ireland 

Italy 

Latvia 

44.0 

39.6 

51.7 

41.0 

46.0 

47.7 

52.3 

54.0 

54.8 

51.0 

48.5 

52.4 

55.4 

54.8 

53.9 

52.6 

52.7 

57.0 

58.7 

56.2 

63.8 

65.4 

68.5 

70.7 

74.3 

72.9 

75.9 

75.8 

77.9 

73.3 

50.6 

52.8 

54.0 

56.3 

54.4 

57.4 

56.7 

58.8 

59.9 

57.5 

47.8 

55.8 

56.6 

57.0 

57.3 

58.2 

59.0 

59.6 

60.4 

56.9 

Lithuania 

49.2 

55.4 

57.0 

58.8 

59.5 

62.2 

61.3 

63.8 

61.9 

57.8 

Luxembourg 

62.2 

62.5 

59.8 

65.1 

65.9 

67.3 

68.6 

63.7 

68.0 

63.9 

Malta 

60.3 

61.8 

63.3 

63.7 

66.7 

68.7 

68.0 

63.6 

66.3 

63.2 

Netherlands 

69.0 

71.4 

71.2 

72.1 

72.4 

72.7 

72.3 

73.0 

74.8 

71.3 

Poland 

Portugal 

42.1 

43.5 

45.4 

46.4 

47.2 

47.3 

48.4 

48.2 

51.7 

49.4 

55.1 

56.2 

57.4 

56.7 

57.3 

58.7 

58.2 

59.0 

59.9 

54.8 

Romania 

37.4 

41.0 

44.5 

44.8 

44.8 

45.2 

45.0 

46.0 

49.6 

48.2 

Slovakia 

Slovenia 

Spain 

Sweden 

52.5 

56.3 

58.6 

59.3 

60.4 

61.4 

60.1 

62.3 

65.4 

62.0 

54.4 

54.6 

54.6 

58.8 

57.4 

58.2 

61.1 

61.8 

65.6 

64.2 

58.6 

59.8 

61.9 

58.9 

56.8 

59.5 

58.8 

59.7 

60.3 

55.4 

77.8 

78.3 

78.9 

78.3 

78.7 

81.0 

81.3 

80.5 

80.4 

75.9 

Source: CSD 

38 

 
The  five  countries  with  highest  ambitious  scenario  scores  for 2019  are all  Northern 
European  economies32  (see  Figure  2)  with  traditionally  high  living  standards,  low 
poverty levels, ambitious low-carbon transition objectives and declining inequalities. 
All countries have experienced a slight deterioration in 2020, which can be attributed 
to  the  COVID-19  pandemic  and  the  subsequent  increase  in  unemployment  and 
poverty  rates,  the  sharp decline in  GDP  growth rates  and  the  lower life satisfaction 
linked  to  reduced  social  interaction  and  a  rise  of  mental-health  issues.  Ireland 
emerges as a star performer among the best ranked EU countries as its Index score 
has  improved  by  more  than 20% from  2011  to  2019  associated  with  fast  economic 
growth, steep reduction of poverty levels and a successful energy transition process. 

Figure  2  The  performance  of  the  short  version  of  the  ‘Beyond  GDP’ 
Sustainable Development Index for the top 5 EU Member States 

Source: CSD  

All  bottom  five  performers  in  the  Index  include  Central  and  Eastern  European 
countries  (Hungary,  Greece,  Poland,  Romania  and  Bulgaria).  Despite  the  wide  gap 
between  the  highly-developed  countries  in  Europe,  discussed  above,  and  the  CEE 
Member States, there has been a similarly strong improvement of the development 
indicators for all countries, whereas their performance has strengthened by between 
15 and 20% over the last decade (see Figure 3). Again, the COVID crisis has taken 
a  toll  on  the  development  trajectory  in  2020  but  the  enormous  expansion  of  the 
national  economies  (some  of  them  growing  more  than  three-fold  over  the  last 
decade) and  the  reduction  of  emissions  on  the  back  of economic  restructuring  and 
green energy growth have improved the region’s overall development prospects. 

32 Denmark, Finland, Ireland, Netherlands, Sweden 

39 

 
 
 
 
Figure  3  The  performance  of  the  ambitious  version  of  the  ‘Beyond  GDP’ 
Sustainable Development Index for the bottom 5 EU member states 

Source: CSD 

Zooming  in  on  the  role  that  economic  growth plays  for setting  development  trends, 
the  ambitious  index  remains  relatively  highly  correlated  with  GDP  (r  =  0.68),  which 
reflects  comments  from  the  in-depth  interviews,  where  experts  have  proposed  that 
GDP  could  be  entirely  excluded  from  a  ‘Beyond  GDP’  index.  To  test  such  an 
alternative approach, a sensitivity version of the ambitious index was computed with 
“Material footprint (tonnes per capita) (see Table 3). The results reveal that the new 
version  of  the  Index  is  completely  decoupled  from  GDP  (the  correlation  with  GDP 
drops to r=0.13)33. 

33 It should be noted that in small countries like Luxembourg normalisations per capita could lead to 
more extreme values and results in such cases should be interpreted carefully.   

40 

 
 
 
 
 
 
 
 
 
Table  3  ‘Beyond  GDP’  ambitious  scenario  with  GDP  dropped  and  material 
footprint included. Higher scores mean better performance. 

2011 

2012 

2013 

2014 

2015 

2016 

2017 

2018 

2019 

202
0 

Austria 

Belgium 

Bulgaria 

Croatia 

Cyprus 

67.2 

66.1 

66.9 

69.2 

70.2 

70.4 

69.5 

69.2 

71.8 

78.1 

74.5 

74.7 

75.9 

76.9 

77.1 

77.4 

77.2 

77.4 

79.1 

78.7 

42.8 

53.8 

58.7 

54.7 

56.1 

56.2 

54.2 

57.9 

57.8 

60.0 

73.8 

72.5 

67.6 

71.0 

68.9 

70.8 

71.2 

75.6 

74.4 

78.6 

51.5 

56.5 

62.2 

64.1 

64.4 

66.3 

63.5 

66.2 

65.6 

66.7 

Czechia 

68.4 

69.3 

71.3 

71.4 

71.3 

72.9 

71.2 

71.7 

75.3 

78.9 

Denmark 

72.5 

76.7 

77.5 

77.7 

77.8 

78.5 

79.1 

76.2 

77.6 

86.0 

Estonia 

EU-27 

Finland 

France 

57.4 

57.7 

57.3 

53.9 

60.5 

61.5 

58.3 

59.4 

63.6 

62.5 

67.7 

70.2 

71.2 

71.4 

71.0 

71.7 

71.7 

72.3 

74.4 

74.1 

69.2 

70.9 

68.8 

73.2 

77.2 

78.4 

79.0 

77.1 

80.3 

90.4 

72.9 

72.7 

72.5 

75.2 

76.6 

76.8 

77.1 

78.0 

78.5 

77.6 

Germany 

69.2 

71.2 

70.2 

68.1 

70.7 

71.2 

71.3 

73.1 

75.9 

72.9 

Greece 

Hungary 

Ireland 

Italy 

54.3 

50.9 

63.6 

55.7 

58.1 

60.3 

64.6 

66.9 

67.8 

63.5 

64.2 

68.7 

71.2 

68.6 

71.1 

70.1 

65.6 

69.0 

69.9 

71.9 

73.3 

73.6 

74.5 

76.2 

76.8 

74.2 

76.1 

73.9 

73.2 

73.7 

59.3 

63.2 

65.3 

67.7 

65.7 

68.6 

67.7 

69.4 

70.8 

72.7 

41 

 
   
Latvia 

64.7 

69.6 

69.4 

70.0 

69.6 

71.2 

70.7 

70.4 

71.1 

72.9 

Lithuania 

65.0 

71.9 

68.4 

70.1 

71.0 

73.0 

70.6 

72.9 

70.6 

73.4 

Luxembour
g 

45.8 

49.5 

46.2 

51.7 

50.6 

53.4 

53.6 

47.1 

55.4 

47.9 

Malta 

75.0 

78.3 

80.4 

84.5 

82.2 

85.9 

83.4 

74.4 

76.9 

78.0 

Netherlands  78.0 

81.1 

81.2 

82.1 

82.1 

82.2 

81.9 

82.4 

84.0 

80.4 

Poland 

Portugal 

52.6 

55.5 

58.0 

58.9 

59.2 

58.7 

58.8 

58.4 

62.1 

62.7 

64.5 

67.0 

69.3 

67.7 

68.1 

69.9 

68.2 

68.9 

69.5 

68.1 

Romania 

48.8 

53.2 

56.7 

56.3 

54.1 

54.1 

54.6 

56.4 

55.3 

62.7 

Slovakia 

Slovenia 

Spain 

Sweden 

64.4 

69.0 

74.1 

71.6 

73.2 

74.1 

72.2 

73.8 

77.5 

78.4 

63.8 

65.2 

65.0 

69.2 

68.1 

69.3 

71.4 

71.3 

75.7 

79.6 

70.0 

72.8 

75.2 

72.2 

69.7 

72.3 

71.2 

71.5 

72.3 

66.8 

78.5 

79.4 

79.1 

79.3 

79.0 

80.8 

81.6 

80.1 

79.5 

85.4 

Source: CSD 

The  five  countries  with  highest  ranking  for  the  sensitivity  version  of  the  ambitious 
scenario  (without  GDP  among  the  5  indicators)  are  similarly  Northern  European 
countries with the notable exception of Slovenia from CEE, all exhibiting moderate to 
strong improvement in sustainability indicators since 2011 (see Figure 4 below). The 
results  also  reflect  the  gradual  decoupling  between  GDP  and  material  footprint  as 
national  economies  become  less  material  intensive,  with  higher  shares  of  recycled 
intermediary  goods  and  transitioning  to  service  sector-based  growth  fundamentals. 
The decline of traditional resource-based heavy industries in Western34 and Northern 
Europe  and  their  replacement  with  high-added  value  sectors  such  as  ICT, 
electronics,  financial  services  and  generally  the  knowledge  economy  are  slashing 
the imports or domestic production of fossil fuels, metals and minerals.  

34Western  and  North  European  member  states  would  include:  Ireland,    France,  Belgium, 
Netherlands, Luxembourg, Germany, Switzerland, Austria 

42 

 
 
Diminished raw material footprint is also indicative of the process of outsourcing the 
lower-added  value  segments  of  the  supply  chain  to  non-EU  parts  of  the  world.  It 
should be noted that with very few exceptions (most notably Spain), all EU Member 
States are improving their sustainable development performance as the phaseout of 
the heavy industry is even stronger in Central and Eastern Europe in the past three 
decades.  The  outcome  is  not  only  lower  demand  for  metals,  minerals  and  fossil 
fuels, among other resources, but a slump in GHG emissions. In most of the region 
(making up the bottom half of the Index’ performance), the political decision to close 
down coal-fired power plants and not to significantly expand natural  gas use would 
achieve  most  of  the  climate  transition  objectives  over  the  next  two  decades 
narrowing the gap with other EU Member States in Northern and Western Europe.  

Figure  4  The  performance  of  the  ambitious  version  of  the  ‘Beyond  GDP’ 
Sustainable Development Index (without GDP) for the top 5 EU member states 

95

85

75

65

55

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Netherlands

Finland

Sweden

Denmark

Slovenia

Source: CSD 

5.2 Transition scenario 

The  less  ambitious  transition  ‘Beyond  GDP’  scenario  (BGDP-12)  includes  12 
indicators,  one  of  which  remains  GDP,  allocated  in  the  same  five  representative 
categories.  Here  again  mostly  primary-level  indicators  were  chosen  but  also  the 
human  development  index  as  a  statistically  robust  measure  for  socio-economic 
sustainable development. The list of indicators are:  

● 

Economic Development: Real Gross domestic product (GDP) per capita; Gini 
coefficient of disposable income, after taxes and transfers; Unemployment rate 
(% of labour force 15-74) 

●  Climate  Neutrality:  Gross  greenhouse  gas  emissions  (tonnes  per  capita); 

Material footprint (tonnes per capita); Energy Consumption per Capita 
●  Governance that Delivers: Life satisfaction; Human Development Index;  
●  Human  Capital: 

In-work-at-risk-of-poverty 

(%  population);  Gender 

rate 

employment gap 

●  Health: Air quality; Healthy life expectancy at birth (years) 

43 

 
 
The  12  indicators  provide  for  a  much  more  complete  picture  of  the  countries’ 
progress towards improving living standards, health, equality and overall satisfaction 
with  societal  development.  Standard  macroeconomic  indicators  such  as  GDP  and 
unemployment are still important predictors of economic development but the weight 
in  this  alternative  vision  for  measuring  sustainability  falls  on  equality,  energy 
transition and good governance. The indicators are proxies for quality of life and the 
quality of policy measures fighting the biggest long-term challenge to the plane and 
humanity’s well-being, namely climate change. Metrics are again linked to outcomes 
of  policies  and  to  demand-side  pathways  such  as  consumption  trends,  the  fair  and 
efficient  utilisation  of  human  capital  and  critical  systems  of  governance  linked  to 
health,  education  and  inclusion.    It  should  be  noted  that  for  some  of  the  indicators 
included in this scenario, min-max normalisation would probably be insufficient. For 
example, Energy Consumption per Capita is dependent on external factors, such as 
average  temperatures  during  the  winter  season,  which  should  be  considered  in  a 
final version of this index.  

The results from the piloting of the long version of the Index in the EU-27 countries 
reveals a quite different result to the one from piloting the short version. There has 
been  a  10%  increase  in  the  Index  score  on  average  for  the  EU-27  across  the 
assessed  areas  (See  Table 4) with  Central  and  Eastern European  (CEE)  countries 
leading  the  way.  Some  post-Communist  EU  member-states  have  improved  their 
sustainability  scores  by  a  fifth  in  comparison  to  2011  and  are  already  catching  up 
with  the  most  economically  developed  European  countries.    The  stagnation  of 
economic  growth  in  many  of  the  largest  European  countries  combined  with  the 
COVID-19  pandemics  is  in  stark  contrast  with  the  strong  and  consistent  economic 
growth  in  CEE,  which  has  been  combined  with  the  acceleration  of  decarbonization 
trends,  the  preservation  of  traditionally  low  inequality  levels  and  the  increase  in 
health  and  overall  living  standards.  The  much  stronger  results  in  the  transition 
scenario of the Index can be explained by the inclusion of more basic quality of life 
and energy transition indicators, which are revealing the improvement of efficiencies, 
the betterment of health and education systems, and a robust GDP growth that has 
also led to sharp drops in the unemployment rates experienced in the 1990s.  

Table  4  ‘Beyond  GDP’  -  12  indicators  scenario.  Higher  scores  mean  better 
performance. 

2011 

2012 

2013 

2014 

2015 

2016 

2017 

2018 

2019  2020 

Austria 

67.6 

67.2 

67.8 

69.2 

69.8 

70.3 

69.9 

70.7 

71.8 

73.4 

Belgium 

68.3 

68.8 

69.4 

70.9 

71.4 

71.6 

72.2 

73.6 

75.1 

73.7 

Bulgaria 

40.4 

45.8 

47.6 

46.4 

47.1 

47.4 

45.7 

47.9 

47.8 

46.1 

44 

 
 
 
 
Croatia 

58.4 

57.8 

57.3 

59.2 

59.1 

61.6 

62.8 

66.2 

66.9 

66.4 

Cyprus 

57.6 

58.3 

59.8 

60.6 

61.9 

63.9 

64.3 

66.8 

66.4 

67.6 

Czechia 

63.3 

64.1 

65.3 

65.8 

66.6 

68.1 

68.0 

69.3 

71.3 

71.2 

Denmark 

72.3 

74.8 

75.6 

75.6 

76.4 

77.5 

78.2 

77.1 

78.4 

81.2 

Estonia 

52.8 

54.5 

54.4 

52.7 

57.3 

58.0 

58.4 

59.9 

63.5 

62.4 

EU-27 

62.2 

63.2 

63.6 

64.2 

64.6 

65.5 

66.2 

67.0 

68.5 

67.9 

Finland 

64.6 

66.1 

66.1 

67.9 

70.3 

70.7 

71.2 

70.7 

72.8 

74.0 

France 

68.9 

69.0 

69.8 

71.9 

72.8 

73.1 

73.9 

74.9 

75.4 

75.0 

Germany 

65.9 

67.2 

66.7 

66.1 

67.7 

68.9 

69.8 

70.2 

72.6 

70.3 

Greece 

50.2 

46.9 

52.0 

49.1 

51.5 

52.5 

55.4 

57.7 

59.8 

57.1 

Hungary 

55.7 

58.1 

59.3 

58.9 

59.6 

60.2 

59.5 

61.3 

62.5 

60.8 

Ireland 

62.4 

62.5 

64.5 

65.7 

68.0 

67.7 

69.4 

70.2 

71.0 

70.7 

Italy 

59.5 

61.0 

62.0 

63.7 

63.5 

64.9 

65.1 

66.1 

67.7 

68.4 

Latvia 

53.1 

56.1 

57.4 

58.1 

58.8 

60.6 

60.5 

60.6 

62.0 

60.0 

Lithuania 

52.4 

56.2 

55.7 

57.2 

57.2 

59.5 

59.5 

61.3 

61.7 

59.8 

45 

 
Luxembour
g 

57.8 

60.2 

58.6 

62.9 

62.5 

64.3 

65.2 

62.8 

64.6 

64.3 

Malta 

59.6 

62.2 

64.6 

67.3 

67.4 

69.6 

69.8 

67.5 

69.3 

68.5 

Netherland
s 

69.8 

71.6 

72.1 

72.6 

73.1 

73.5 

74.5 

75.7 

77.5 

74.3 

Poland 

54.6 

56.1 

57.4 

58.6 

59.7 

60.4 

61.2 

62.2 

64.0 

65.0 

Portugal 

57.5 

58.5 

60.4 

60.6 

61.9 

63.5 

63.8 

65.8 

66.6 

66.0 

Romania 

45.5 

47.4 

49.3 

49.4 

47.8 

49.6 

51.4 

51.1 

51.7 

53.0 

Slovakia 

54.1 

56.2 

58.1 

58.5 

61.0 

62.3 

63.3 

65.8 

67.5 

66.1 

Slovenia 

62.1 

62.8 

62.2 

64.3 

64.4 

66.1 

67.9 

68.9 

71.3 

71.6 

Spain 

60.8 

61.1 

62.8 

61.8 

61.5 

63.9 

64.5 

66.0 

67.4 

64.3 

Sweden 

73.4 

74.0 

75.2 

75.4 

76.3 

76.9 

77.4 

77.5 

77.3 

78.5 

Source: CSD 

A comparison of the EU-27 scores (See Table 5 below for EU-27 ranking) for the two 
scenarios  presented  above  (+  the  sensitivity  version  of  the  ambitious  one  without 
GDP)  shows  similar  trajectories  with  the  exception  of  the  2018-2020  period  for  the 
GDP-based ambitious scenario (See Figure 5 below). This could be attributed to the 
larger influence of GDP in this index and the economic recession in response to the 
COVID-19  pandemics.  The  inherent  volatility  of  short-term  indicators  such  as  GDP 
could  significantly  skew  the  results  of  an  Index  that  measures  progress  on  a  long-
term pathway to sustainability.  

This  gives  stronger  credence  to  the  concept  of  an  ambitious  scenario  without  GDP 
providing  a  more  realistic  picture  of  the  overall  improvement  of  societal  well-being. 
The inclusion of the material footprint indicator is crucial for considering the planetary 
constraints linked to economic growth. This indicator could be seen as a cornerstone 
for understanding the intertwined logic between decarbonization and socio-economic 
transformation.  Once  the  Index  is  piloted  on  a  global  scale,  however,  it  would  be 

46 

 
crucial  to  also  assess  economic  interdependencies  between  nations  that  may 
explain  regional  variance  in  the  progress  toward  sustainable  development  and  to 
better understand spill-over effects. 

Figure 5  ‘Beyond GDP’ - three scenarios, EU-27 scores. 

Source: CSD 

Table 5 Comparative ranking of EU-27 member states for 2020 in the two main 
scenarios  and  the  sensitivity  version  of  the  ambitious  scenario  with  GDP 
dropped 

Ambitious 5 

2020 

Ambitious 5 with 
Raw Material 
Footprint 

2020 

12 
Indicators 

2020 

Denmark 

77,9 

Finland 

90,4 

Denmark 

81.2 

Finland 

77,5 

Denmark 

86,0 

Sweden 

78,5 

Sweden 

75,9 

Sweden 

85,4 

France 

75,0 

Ireland 

73,3 

Netherlands 

80,4 

Netherlands 

74,3 

Netherlands 

71,3 

Slovenia 

79,6 

Finland 

74,0 

Belgium 

68,1 

Czechia 

78,9 

Belgium 

73.7 

47 

 
 
Austria 

68,0 

Belgium 

78,7 

Austria 

73.4 

France 

66,2 

Croatia 

78,6 

Slovenia 

71.6 

Slovenia 

64,2 

Slovakia 

78,4 

Czechia 

71.2 

Germany 

63,9 

Austria 

78,1 

Ireland 

70.7 

Luxembourg 

63,9 

Malta 

78,0 

Germany 

70.3 

Malta 

63,2 

France 

77,6 

Malta 

68.5 

Czechia 

63,0 

EU-27 

74,1 

Italy 

68.4 

Slovakia 

62,0 

Ireland 

73,7 

EU-27 

67.9 

Croatia 

61,0 

Lithuania 

73,4 

Cyprus 

67.6 

EU-27 

58,1 

Germany 

72,9 

Croatia 

66.4 

Lithuania 

57,8 

Latvia 

72,9 

Slovakia 

66.1 

Italy 

57,5 

Italy 

72,7 

Portugal 

66.0 

Latvia 

56,9 

Hungary 

71,9 

Poland 

65.0 

Hungary 

56,2 

Portugal 

68,1 

Spain 

64.3 

Cyprus 

56,0 

Spain 

66,8 

Luxembour
g 

64.3 

Spain 

55,4 

Cyprus 

66,7 

Estonia 

62.4 

Portugal 

54,8 

Greece 

63,5 

Hungary 

60.8 

Greece 

51,0 

Poland 

62,7 

Latvia 

60.0 

Estonia 

49,8 

Romania 

62,7 

Lithuania 

59.8 

Poland 

49,4 

Estonia 

62,5 

Greece 

57.1 

48 

 
Romania 

48,2 

Bulgaria 

60,0 

Romania 

53,0 

Bulgaria 

45,3 

Luxembourg 

47,9 

Bulgaria 

46.1 

Source: CSD 

6.  WHAT’S NEXT?  

The final section provides an overview of a proposed approach for further testing and 
piloting  of  the  ‘Beyond  GDP’  Indices.  The  remaining  big  question  is  how  to 
implement  in  practice  the  alternative  Indices  as  a  benchmark  for  sustainable 
development on EU and global level. The section also provides a non-exclusive list 
of proposals for an update of the existing definitions for sustainable economic growth 
and  development  with  a 
transparency, 
accountability,  as  well  as  ensure  the  policy  vision  on  transition  takes  into 
consideration  the  changing  geopolitical  landscape  and  the  potential  democratic 
deficits  in  EU  and  national  decision-making  on  these  key  long-term  development 
pathways. 

improving  governance, 

focus  on 

Improving the methodology for measurement 

There is a possibility for further enhancement of the methodological approach to the 
statistical  testing  and  expert  assessment  of  the  different  indicators  included.  The 
interdependencies  of  the  different  metrics  and  their  link  to  external  indicators  and 
processes  could  be  studied  in  more  depth  through  more  complex  and  laborious 
regression  and  path  analyses.  On  the  expert  side,  the  Delphi  method  should  be 
expanded to include a much wider pool of experts in all areas of the SDGs assessed 
by  the  different  indicators  on  top  of  the  researchers  specialising  in  identifying 
alternative ‘Beyond GDP’ methodologies.  

Apart  from  extending  the  scope  of  the  survey,  the  latter  should  be  followed  by  a 
series of methodological workshops in different European capitals to gather leading 
European and U.S. think tanks and independent experts to discuss how to improve 
the  current  methodology  with  a  particular  focus  on  the  measurement  of  well-being, 
inclusion, equality and quality of governance. The workshops will also be a platform 
to improve the final selection and weights of the indicators and to develop a strategy 
for  data  gathering  and  analysis.  To  maximise  the  utility  and  impact  of  the  Index, 
experts should develop forward-looking policy scenarios to help guide the EU’s long-
term strategy for achieving the SDGs.  

The  DELPHI-based  method  for  expert  assessment  can  also  be  combined  with 
participatory  foresight  exercises  with  citizens  across Europe  and  beyond in  attempt 
to  first  raise  awareness  about  sustainable  development  measurement  approaches, 
receive  citizen  feedback  on  the  most  important  indicators  measuring  quality  of  life, 
inequality,  good  governance  and  life  satisfaction,  and  finally,  to  draw  out  forward-
looking scenarios for the sustainable development indicators’ pathways to 2050. The 
ultimate  objective  would  be  to  align  the  macro-level  SDGs  with  the  citizens’ 
expectations for the pace of socio-economic transition.  

49 

 
 
Globalising the index 

The  second  phase  of  developing  the  Index  will  expand  its  coverage  to  as  many 
countries  as  data  availability  permits,  contributing  to  the  creation  of  a  truly  global 
policy  instrument  that  aims  to  bring  closer  together  the  sustainable  development 
policies of both the developed and developing world. Once the Index is piloted on a 
to  also  assess  economic 
global  scale,  however, 
interdependencies  between  nations  that  may  explain  regional  variance  in  the 
progress toward sustainable development and to better understand spill over effects.  
In addition, the globalisation of the Index will: 

it  would  be  crucial 

● 

Improve  the  understanding  and  transparency  of  the  most  important  social-
economic and climate vulnerabilities faced by humanity. 

●  Enable data-driven policy action that allows for the consistent setting of long-term 

objectives in multiple fields contributing to similar goals; 

●  Help  align  developed  and  developing  countries’  policy  priorities,  accelerate  the 
decarbonization  of  economies,  strengthen  the  global  resilience  to  future  energy 
and climate security risks, and improve health standards and the global response 
to health challenges 

●  Contribute to the building of data-driven expert and policy capacity for monitoring 

sustainable development pathways. 

●  To  develop  a  community  of  academic  experts  and  policy-makers  that  have  a 
unified vision of sustainable development and a new approach to measuring well-
being. 

The Index can be included in the UN toolbox, which would foster policy transparency 
through  the  creation  of  a single  data  and  policy  analysis  repository  that  focuses  on 
sustainable  development.  All  the  data  variables,  indicators,  Index  metrics  and 
country  analyses  could  be  included  in  an  online  ‘Beyond  GDP’  Sustainable 
Development  Database.  The  database  should  be  digitalised  via  an  interactive, 
user-friendly online interface providing access not only to the main results but to the 
whole methodology and the full statistical datasets.  

Translating the index results into actionable policy recommendations 

in  an 

To maximise the policy and media impact on national level, the main results from the 
interactive  online  National  Sustainable 
Index  could  be  summarised 
Development Score Cards that would track changes in the variables making up the 
monitored indicators and would assess the impact of sustainable development policy 
changes  on  national  level.  The  Score Cards  could  be  accompanied  by  short policy 
papers that would be widely disseminated via national and international media where 
key  policy  recommendations  will  be  flagged.  The  European  Commission  can  work 
with  local  think  tanks  to  develop  the  detailed  country  assessments  providing  policy 
context and amplifying the impact nationally. 

An  annual,  comparative  Global  ‘Beyond  GDP’  Sustainable  Development  report 
could be launched as a summary of the main findings from the Index and the policy 
implications  from  the  general  trends.  The  assessment  will  track  the  countries’ 
progress  in  improving  social  and  economic  equality,  accelerating  decarbonisation, 
improving the quality of governance and overall quality of life. The indicators chosen 

50 

 
in the Index have the widest possible global coverage, which would allow for global 
comparability of the countries’ progress. 

To  maximise  the  media  impact  of  the  Index,  there  could  also  be  an  annual 
Sustainable Development Policy Forum for the presentation of the Index results in 
Brussels  and  other  EU  capitals.    The  local  think  tanks  in  each  country,  developing 
the assessments, could also present the key national findings at a policy roundtable 
in each capital.  

51 

 
 
 
 
 
 
 
 
ANNEX 1 – LIST OF TESTED INDICATORS 

Table  6  Full  List  of  Statistically  Tested  Indicators  during  the  Pre-selection 
Phase 

Indicator 

Time 
coverage 

Geographical 
coverage 

Source 

Relation to 
‘Beyond GDP’ 
and SDGs 

Employment rate % of 
population 20-64 

2009-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Eurostat 

Relates to SDGs 8 
and 10 

GDP 

1960-2021  Worldwide 

GDP (nominal) per 
capita 

1960-2021  Worldwide 

GDP (PPP) per capita 

1960-2021  Worldwide 

Government 
expenditure in 
education per student 
(% of GDP per capita) 

1970-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

UNESCO 

Relates to SDG 8 

Relates to SDG 8 

Relates to SDG 8 

Relates to SDG 4 

Proportion of people 
with ICT skills 
(composite) 

2013-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

The ITU 
ICT SDG 
indicators 

Relates to SDGs 4, 
5, 9, and 17 

Gross domestic 
product (GDP) per 
capita 

1980-2027 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

IMF 
DATAMMA
PER  

Relates to SDG 8 

Output per worker 
(2011 constant GDP 
PPP$) 

1991-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Relates to SDG 8 

ILOSTAT 
on Labour 
Productivity 

Gross expenditure on 
R&D (% of GDP) 

1980-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 9 

Gross value added of 
manufacturing (% of 
GDP) 

1975-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 9 

Patent families filed in 
two offices (per billion 
PPP$ GDP) 

1980-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

WIPO IP 
Statistics 
Data Center  

Relates to SDG 9 

Healthy life expectancy 
at birth (years) 

2000/2010/
2015/2019 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

WHO 
Indicators 

Relates to SDG 3 

52 

 
  
  
  
others 

Employment-to-
population ratio gender 
gap 25+ (%) 

1983-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Relates to SDGs 5 
and 8 

ILOSTAT 
on 
Employmen
t 

Gross enrolment ratio, 
pre-primary, both 
sexes (%) 

2010-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

UNESCO 

Relates to SDG 4 

Free or non-remunerated time 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Free or non-
remunerated time: 
Labour force 20-64 

1946-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

ILOSTAT 
Labour 
Force 

Free or non-
remunerated time: 
Average annual hours 
worked per worker 

1950-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

OECD Stat 

Free or non-
remunerated time: 
Mean weekly hours 
usually worked per 
employed person by 
sex 

Gini coefficient of 
disposable income, 
after taxes and 
transfers 

1950-2021  Worldwide 

2010-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

ILOSTAT 
Labour 
Force 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 10 

Income share held by 
the poorest quintile (%) 

Limited 
coverage 

EU-27 + Iceland, Norway, 
UK, Switzerland 

WB - WDI 

Relates to SDG 11 

Gross greenhouse gas 
emissions (tonnes per 
capita) 

1990-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

EEA 

Relates to SDG 13 

Terrestrial key 
biodiversity areas 
(KBAs) protected (%) 

2000-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

UNECE 
UN-SDGs 

Relates to SDG 15 

Freshwater KBAs 
protected (%) 

2000-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

UNECE 
UN-SDGs 

Relates to SDG 15 

53 

 
 
  
 
 
 
Pesticides use per 
area of cropland 
(kg/ha) 

1990-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

Resource productivity 
(PPP$ per kg) 

2000-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Relates to SDG 15 

Relates to SDGs 8 
and 12 

FAO STAT 

Statistics | 
Eurostat 
(europa.eu) 

Material footprint 
(tonnes per capita) 

1990-2016 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

UNEP UN-
SDGs 

Relates to SDGs 8 
and 12 

Energy productivity 
(PPP$ per koe) 

2000-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

IEA 
Database 

Relates to SDG 7 

Voice and 
accountability index 

1996-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Rule of law index 

1996-2021 

140 countries 

WGI 

World 
Justice 
Project 

Relates to SDG 16 

Rule of Law Index: 
Factor 1 Constraints on 
Government Powers |  

Rule of Law Index: 
Factor 1 Constraints on 
Government Powers | 
1.1. Government 
powers are effectively 
limited by the 
legislature 

Rule of Law Index: 
Factor 1 Constraints on 
Government Powers | 
1.2 Government 
powers are effectively 
limited by the judiciary  

Rule of Law Index: 
Factor 2:  Absence of 
Corruption  

Rule of Law Index: 
Factor 3: Open 
Government 

1996-2021 

140 countries 

1996-2021 

140 countries 

1996-2021 

140 countries 

1996-2021 

140 countries 

1996-2021 

140 countries 

54 

 
 
  
 
  
 
  
 
  
 
  
 
Rule of Law Index: 
Factor 4: Fundamental 
Rights 

Rule of Law Index: 
Factor 5: Order and 
Security 

Rule of Law Index: 
Factor 6: Regulatory 
Enforcement 

1996-2021 

140 countries 

1996-2021 

140 countries 

1996-2021 

140 countries 

Rule of Law Index: 
Factor 7: Civil Justice 

1996-2021 

140 countries 

Rule of Law Index: 
Factor 8: Criminal 
Justice 

Rule of Law Index: 
Factor 9: Informal 
Justice 

1996-2021 

140 countries 

1996-2021 

140 countries 

Homicide rate (per 
100000 inhabitants) 

1990-2021 

Corruption Perceptions 
Index 

2012-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

dataUNOD
C 

Transparen
cy 
Internationa
l 

Relates to SDG 16 

Relates to SDG 16 

Basel Anti-Money 
Laundering Index 

2012-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

Domain 1: Quality of 
AML/CFT Framework 
(65%) 

2012-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

Domain 2: Corruption 
and Bribery Risk (10%) 

2012-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

Domain 3: Financial 
Transparency and 
Standards (10%) 

2012-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

Domain 4: Public 
Transparency and 
Accountability (5%) 

2012-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

55 

 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
Domain 5: Political and 
Legal Risk (10%) 

2012-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

General government 
gross debt (% of GDP) 

1980-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
Others 

IMF 
DATAMMA
PER  

Relates to SDG 17 

Early leavers from 
education and training 
% of population 18-24 

Individuals who have 
basic or above basic 
overall digital skills % 
of population 16-74 

Young people neither 
in employment nor in 
education and training 
(NEET)  % of 
population 15-29 

2000-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Relates to SDG 4 

2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Eurostat 

Eurostat 

Relates to SDG 5 

2000-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Relates to SDGs 8 
and 10 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 5 

Relates to SDG 10 

Relates to SDG 4 

Relates to SDG 4 

Relates to SDG 5 

Relates to SDG 5 

Relates to SDG 8 

Gender employment 
gap 

2005-2021 

EU-27 + Iceland, Norway, 
Switzerland 

Income inequality - 
quintile share ratio 
(S80/S20) Ratio 

Adult participation in 
learning % of 
population 25-64 

Tertiary education 
attainment % of 
population 30-34 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2000-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Gender gap in part-
time employment 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Gender pay gap in 
unadjusted form % of 
average gross hourly 
earnings of men 

2002-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Employment rate % of 
population 20-64 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

56 

 
  
 
Unemployment rate  % 
of labour force 15-74 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Long term 
unemployment rate % 
of labour force 15-74 

Real gross disposable 
income of households 
Per capita increase 
(Index = 2008) 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Activity rate % of 
population 15-64 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Youth unemployment 
rate % of labour force 
15-24 

Employment in current 
job by duration % of 
employed 20-64 from 
0-11 months 

Transition rates from 
temporary to 
permanent contracts % 
(3 year average) 

In-work-at-risk-of-
poverty rate % 
population 

At-risk-of-poverty or 
social exclusion rate 
(AROPE) % of 
population 

At-risk-of-poverty-rate 
(AROP) % of 
population 

Severe material and 
social deprivation rate 
(SMSD) % of 
population 

Persons living in a 
household with a very 
low work intensity % of 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2008-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2015-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2015-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2015-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 

57 

Relates to SDG 8 

Relates to SDG 8 

Relates to SDG 8 

Relates to SDG 1 

Relates to SDG 1 

Relates to SDG 1 

Relates to SDG 1 

Relates to SDG 1 

 
 
 
 
 
population <65 

At-risk-of-poverty rate 
or exclusion of children 
% of population 0-17 

At-risk-of-poverty-rate 
(AROP) for children % 
of population 0-17 

Severe material and 
social deprivation rate 
(SMSD) for children % 
of population 0-17 

Children living in a 
household with a very 
low work intensity % of 
population 0-17 

Impact of social 
transfers (other than 
pensions) on poverty 
reduction % reduction 
of AROP 

2015-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2015-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2015-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Disability employment 
gap 

2014-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2010-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

2005-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Relates to SDG 1 

Relates to SDG 1 

Relates to SDG 1 

Relates to SDG 1 

Relates to SDG 1 

Relates to SDGs 1, 
3, 5, 10 and 11 

Relates to SDG 11 

(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

2008-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Relates to SDGs 1 
and 3 

Eurostat 

2011-2018 

EU  

Statistics | 
Eurostat 
(europa.eu) 

The UN SDGs 
framework does not 
include an explicit 
goal on raw materials 

Green public 
procurement 

No 
coverage 

No coverage 

Relates to SDG 12 

Eurostat 

58 

Housing cost 
overburden % of 
population 

Children aged less 
than 3 years in formal 
childcare  % of under 
3-years-olds 

Self-reported unmet 
need for medical care 
% of population 16+ 

EU self-sufficiency for 
raw materials, 
aluminium 
(percentage) 

 
 
2000-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Relates to SDG 11 

Statistics | 
Eurostat 
(europa.eu) 

Generation of 
municipal waste per 
capita (Kg per capita) 

Generation of waste 
excluding major 
mineral wastes per 
GDP unit (Kg per 
thousand euro, chain 
linked volumes (2010)) 

Generation of waste 
excluding major 
mineral wastes per 
domestic material 
consumption 
(percentage) 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

UNEP UN-
SDGs 

Relates to SDG 12 

Food waste 

2005-2021 

54 countries 

Recycling rate of 
municipal waste 
(percentage) 

2000-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 11 

Recycling rate of all 
waste excluding major 
mineral waste 
(percentage) 

2010-2018 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 12 

Recycling rate of 
overall packaging 
(percentage) 

Recycling rate of 
plastic packaging 
(percentage) 

2000-2019 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 12 

2000-2019 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 12 

Recycling rate of 
wooden packaging 
(percentage) 

2000-2019 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 12 

Recycling rate of e-
waste (percentage) 

2008-2018 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 12 

Recycling of biowaste 
(kg per capita) 

2000-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 12 

Recovery rate of 
construction and 
demolition waste 

2010-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

Relates to SDG 12 

Statistics | 
Eurostat 

59 

 
 
 
(percentage) 

others 

(europa.eu) 

End-of-life recycling 
input rates (EOL-RIR), 
aluminium 
(percentage) 

2013/2016/
2'19 

EU 

Relates to SDG 12 

Statistics | 
Eurostat 
(europa.eu) 

Circular material use 
rate (percentage) 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 12 

Trade in recyclable raw 
materials (tonne) 

2004-2021 

EU-27 

Imports from non-EU 
countries 

2004-2021 

EU-27 

Exports to non-EU 
countries 

2004-2021 

EU-27 

Intra EU trade 

2004-2021 

EU-27 

Relates to SDG 12 

Relates to SDG 12 

Relates to SDG 12 

Relates to SDG 12 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Gross investment in 
tangible goods 
(percentage of gross 
domestic product 
(GDP) at current 
prices) - Circular 
Economy 

Persons employed 
(percentage of total 
employment) - Circular 
Economy 

Value added at factor 
cost (percentage of 
gross domestic product 
(GDP) at current 
prices) - Circular 
Economy 

Number of patents 
related to recycling and 
secondary raw 
materials 

2008-2019 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Relates to SDGs 6, 
8, 11, 12 ,13, 14 and 
15 

2008-2019 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDGs 6, 
8, 11, 12 ,13, 14 and 
16 

2008-2019 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Relates to SDGs 6, 
8, 11, 12 ,13, 14 and 
17 

2000-2019 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDGs 6, 
8, 11, 12 ,13, 14 and 
18 

60 

 
  
Excess mortality 

2020-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

- 

GDP 

2007-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 8 

Unemployment rate 

1983-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 8 

Greenhouse gas 
emissions t/capita 

2010-2022 

EU-27 

Relates to SDG 13 

Statistics | 
Eurostat 
(europa.eu) 

Inflation 

1997-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 8 

Industrial production 

1980-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Economic sentiment 
indicator 

1980-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Business registrations 

2015-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Bankruptcy 
declarations 

2015-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Air quality 

2018-2022 

Number of flights 

2010-2022 

Electricity consumption 

2008-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Government surplus / 
deficit 

1980-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

61 

 
 
 
 
 
 
 
 
 
Production in services 

1994-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Production in 
construction 

1990-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Retail trade 

1991-2022 

Labour market slack  

2006-2022 

Tourism nights 

2020-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Exports 

1999-2022 

EU-27  

Imports 

1999-2022 

EU-27  

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Openness to trade 

1991-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

From unemployment to 
employment 

2003-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

From unemployment to 
inactivity 

2003-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

From employment to 
inactivity 

2003-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Evolution of 
transposition deficit 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Overdue directives 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Average delay 

1997-2020 

EU-27 

SMS EC 

SMS EC 

- 

- 

- 

62 

 
 
 
 
 
 
 
 
 
 
 
 
Evolution of conformity 
deficit 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Evolution of 
infringement cases 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Single Market-related 
pending cases 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Problematic sectors 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Average case duration 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Compliance with Court 
rulings 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Requests accepted 
within one week (%) 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Requests answered by 
the deadline agreed in 
IMI (%) 

Satisfaction with 
timeliness of replies - 
as rated by 
counterparts (%) 

Satisfaction with efforts 
made - as rated by 
counterparts (%) 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

SMS EC 

SMS EC 

Speed in answering 
requests (days) 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Trade in goods and 
services 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Foreign Direct 
Investment 

1997-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

SMS EC 

Number of incoming 
civil, commercial, 
administrative and 
other cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 

Number of incoming 
civil and commercial 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

CEPEJ 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

- 

63 

 
 
 
litigious cases 

others 

Number of incoming 
administrative cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 

Estimated time needed 
to resolve civil, 
commercial, 
administrative and 
other cases 

Estimated time needed 
to resolve litigious civil 
and commercial cases 
at first instance 

Estimated time needed 
to resolve litigious civil 
and commercial cases 
at all court instances 

Estimated time needed 
to resolve 
administrative cases at 
first instance 

Estimated time needed 
to resolve 
administrative cases at 
all court instances 

Rate of resolving civil, 
commercial, 
administrative and 
other cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 

CEPEJ 

CEPEJ 

CEPEJ 

CEPEJ 

CEPEJ 

Rate of resolving 
litigious civil and 
commercial cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 

Rate of resolving 
administrative cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 

Number of pending 
civil, commercial and 
administrative and 
other cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Number of pending 
litigious civil and 

2010/12/14/

EU-27 + Iceland, Norway, 
UK, Switzerland and 

CEPEJ 

CEPEJ 

64 

 
 
 
 
 
 
 
 
 
 
 
 
commercial cases 

16/18/2020 

others 

Number of pending 
administrative cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 

Competition: average 
length of judicial review 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

ECN 

Competition: average 
length of proceedings 
before the national 
competition authorities 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Electronic 
communications: 
average length of 
judicial review 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Electronic 
communications: 
average length of 
proceedings before the 
National Regulatory 
Authority 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

EU trademark: average 
length of EU trademark 
infringement cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Consumer protection: 
average length of 
judicial review 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Consumer protection: 
average length of 
administrative 
decisions by consumer 
protection authorities 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

ECN 

European 
Commissio
n with the 
Communica
tions 
Committee 

European 
Commissio
n with the 
Communica
tions 
Committee 

EUIPO 

Consumer 
Protection 
Cooperatio
n Network 

Consumer 
Protection 
Cooperatio
n Network 

Money laundering: 
average length of court 
cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

MONEYVA
L 

Income threshold for 
legal aid in a specific 
consumer case 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CCBE 

65 

 
 
 
 
 
 
 
 
 
 
 
Court fee to start 
judicial proceedings in 
a specific consumer 
case 

Court fee to start 
judicial proceedings in 
a specific commercial 
case 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CCBE 

CCBE 

Recoverability of legal 
fees in a commercial 
trial 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CCBE 

Promotion of and 
incentives for using 
ADR methods 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

Specific arrangements 
for access to justice of 
persons with 
disabilities 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

Specific arrangements 
for child-friendly 
proceedings 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

Specific arrangements 
for child-friendly 
proceedings with 
children involved as 
victims or suspects or 
as accused persons 

General government 
total expenditure on 
law courts in EUR per 
inhabitant 

General government 
total expenditure on 
law courts as a 
percentage of GDP 

Number of judges 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2000-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

1995-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Proportion of female 
professional Supreme 
Court judges 

2003-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

CEPEJ 

European 
Institute for 
Gender 
Equality, 
Gender 

66 

Relates to SDG 16 

Relates to SDG 5 

 
 
 
 
 
 
 
 
 
 
Statistics 
Database: 

Number of lawyers 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 

Availability of training 
in communication for 
judges 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

Availability of online 
information about the 
judicial system for the 
general public 

Procedural rules 
allowing digital 
technology in courts in 
civil/commercial, 
administrative and 
criminal cases 

Use of digital 
technology by courts 
and prosecution 
services 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

CEPEJ 
Qualitative 
data 

CEPEJ 
Qualitative 
data 

Courts: electronic 
communication tools 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

Prosecution service: 
electronic 
communication tools 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

Digital solutions to 
initiate and follow 
proceedings in 
civil/commercial and 
administrative cases 

Digital solutions to 
conduct and follow 
court proceedings in 
criminal cases 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

CEPEJ 
Qualitative 
data 

Online access to 
published judgments 
by the general public 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CEPEJ 
Qualitative 
data 

67 

 
 
 
 
 
 
 
 
 
 
 
CEPEJ 
Qualitative 
data 

EUROBAR
OMETER 

EUROBAR
OMETER 

EUROBAR
OMETER 

EUROBAR
OMETER 

EUROBAR
OMETER 

EUROBAR
OMETER 

Arrangements for 
producing machine-
readable judicial 
decisions 

How the general public 
perceives the 
independence of courts 
and judges 

Main reasons among 
the general public for 
the perceived lack of 
independence 

How companies 
perceive the 
independence of courts 
and judges 

Main reasons among 
companies for the 
perceived lack of 
independence 

How companies 
perceive the 
effectiveness of 
investment protection 
by the law and courts 

Main reasons among 
companies for their 
perceived lack of 
effectiveness of 
investment protection 

National security 
checks on judges: 
authorities involved 
and timing 

Possibility of 
higher/Supreme Courts 
to take decisions on 
the consistency of 
case-law of lower 
courts on their own 
initiative 

Safeguards relating to 
temporary employment 
of judges/prosecutors 
as politicians/ministers/ 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

68 

 
 
 
 
 
 
 
 
  
 
  
 
  
 
government 
officials/cabinet 
members/in other 
political offices 

others 

Authority reviewing a 
prosecutor’s decision 
not to prosecute  

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

MONEYVA
L 

Bodies with power to 
conduct criminal 
investigation 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

MONEYVA
L 

Independence of Bars 
and lawyers 

2010/12/14/
16/18/2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

CCBE 

Corruption from the 
quality of Government 
Index by the Quality of 
Government Institute 

2010/12/14/
16/18/2020 

Quality and 
accountability from the 
Quality of Government 
Index by the Quality of 
Government Institute 

2010/12/14/
16/18/2020 

Impartiality from the 
Quality of Government 
Index by the Quality of 
Government Institute 

2010/12/14/
16/18/2020 

NUTS0: IE, LT 
NUTS1: BE, DE, EL, SE, 
UK 
NUTS2 all the other 
countries (2013 rev) 

NUTS0: IE, LT 
NUTS1: BE, DE, EL, SE, 
UK 
NUTS2 all the other 
countries (2013 rev) 

NUTS0: IE, LT 
NUTS1: BE, DE, EL, SE, 
UK 
NUTS2 all the other 
countries (2013 rev) 

2010/12/14/
16/18/2020 

EU28 

2010/12/14/
16/18/2020 

EU28 

There is corruption in 
the national public 
institutions in (OUR 
COUNTRY) from the 
Special Eurobarometer 
470 

There is corruption in 
the local or regional 
public institutions in 
(OUR COUNTRY) from 
the Special 
Eurobarometer 470 

QoG Data 

QoG Data 

QoG Data 

EUROBAR
OMETER 

EUROBAR
OMETER 

Political stability from 
the Worldbank 
Worldwide Governance 

1996-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

WGI 

69 

 
 
 
 
 
 
 
 
 
 
Indicators 

Government 
effectiveness from the 
Worldbank Worldwide 
Governance Indicators 

Regulatory quality from 
the Worldbank 
Worldwide Governance 
Indicators 

1996-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

1996-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Rule of law from the 
Worldbank Worldwide 
Governance Indicators 

1996-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Control of corruption 
from the Worldbank 
Worldwide Governance 
Indicators 

1996-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

WGI 

WGI 

WGI 

WGI 

Ease of doing business 
from Worldbank - 
Doing Business 

Discontinue
d 

Discontinued 

WB 
DATABANK 

Doing Business has 
been discontinued as 
of 9/16/2021 

Property rights from 
World Economic 
Forum - Global 
Competitiveness Index 

Intellectual property 
protection from World 
Economic Forum - 
Global 
Competitiveness Index 

Efficiency of legal 
framework in settling 
disputes from World 
Economic Forum - 
Global 
Competitiveness Index 

Efficiency of legal 
framework in 
challenging regulations 
from World Economic 
Forum - Global 
Competitiveness Index 

Transparency of 
government 
policymaking from 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

GPI 

GPI 

GPI 

GPI 

70 

 
 
 
 
 
 
 
 
 
  
 
World Economic 
Forum - Global 
Competitiveness Index 

Business costs of 
crime and violence 
from World Economic 
Forum - Global 
Competitiveness Index 

Organised crime from 
World Economic 
Forum - Global 
Competitiveness Index 

Reliability of police 
services from World 
Economic Forum - 
Global 
Competitiveness Index 

others 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

GPI 

GPI 

National savings 
(Household saving 
rate) 

2010-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Government bond 
yields 

2021/10-
2022/09 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Net international 
investment position 
NIIP 

1995-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Population accessible 
by road 

2019 

NUTS2 

Population accessible 
by railway 

2019 

NUTS2 

Number of passenger 
flights (accessible 
within 90' drive) from 
Eurostat 

1993-2020 

NUTS2 

Road fatalities from 
Eurostat 

1990-2020 

NUTS2 

Relates to SDG 11 

Relates to SDG 11 

Relates to SDG 3 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Infant mortality from 

1960-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

Statistics | 
Eurostat 

Relates to SDG 3 

71 

 
 
  
 
 
 
 
 
 
Eurostat 

others 

Cancer disease death 
rate from Eurostat 

2013-2017 

NUTS2 

Heart disease death 
rate from Eurostat 

2013-2017 

NUTS2 

Suicide death rate from 
Eurostat 

2013-2017 

NUTS2 

(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 3 

Relates to SDG 3 

Relates to SDG 3 

Employer-sponsored 
training from Eurostat 

2007/2011/
2016 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Access to learning 
information from 
Eurostat 

2007/2011/
2016 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

No foreign language 
from Eurostat 

2007/2011/
2016 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 4 

Higher education 
attainment from 
Eurostat 

2010-2021 

NUTS2 

Lifelong learning from 
Eurostat 

1999-2021 

NUTS2 

Early school leavers 
from Eurostat 

2000-2021 

NUTS2 

Lower-secondary 
completion only from 
Eurostat 

Employment rate 
(excluding agriculture) 
from Eurostat 

Gender balance 
unemployment from 
Eurostat 

Gender balance 
employment from 

2000-2021 

NUTS2 

2008-2021 

NUTS2 

1999-2021 

NUTS2 

1999-2021 

NUTS2 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 

72 

 
 
 
 
 
 
 
 
 
 
Eurostat 

Female unemployment 
from Eurostat 

2012-2021 

NUTS2 

Involuntary parttime / 
temporary employment 

2012-2021 

NUTS2 

Disposable income per 
capita 

1995-2020 

NUTS2 

Potential market size 
expressed in GDP 

1995-2020 

NUTS2 

Potential market size 
expressed in 
population 

1995-2020 

NUTS2 

Households with 
access to broadband 

2006-2021 

NUTS2 

Individuals buying over 
internet 

2006-2021 

NUTS2 

Household access to 
internet 

2006-2021 

NUTS2 

Availability of latest 
technologies from 
World Economic 
Forum - Global 
Competitiveness Index 

Firm-level technology 
absorption from World 
Economic Forum - 
Global 
Competitiveness Index 

FDI and technology 
transfer from World 
Economic Forum - 
Global 
Competitiveness Index 

2007-2017 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2007-2017 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2007-2017 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Enterprises having 
purchased online (at 

2007-2017 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

73 

(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

World 
Economic 
Forum GCI 

World 
Economic 
Forum GCI 

World 
Economic 
Forum GCI 

Relates to SDG 9 

Relates to SDG 9 

Relates to SDG 9 

 
 
  
 
 
  
 
  
 
 
 
 
  
 
least 1%)  

others 

Enterprises having 
received orders online 
(at least 1%) 

2010-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Enterprises with fixed 
broadband access 

2010-2017 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Employment (K-N 
sectors) 

2014-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

GVA (K-N sectors) 

2014-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Innovative SMEs 
collaborating with 
others 

2014-2022 

NUTS2 and EU-27 + 
Iceland, Norway, UK, 
Switzerland and others 

Marketing or 
organisational 
innovators 

2014-2022 

NUTS2 and EU-27 + 
Iceland, Norway, UK, 
Switzerland and others 

EIS RIS 

EIS RIS 

Core Creativity Class 
employment 

2015-2017 

NUTS2 

Knowledge workers 

2015-2017 

NUTS2 

Scientific publications 

2015-2017 

NUTS2 

Total intramural R&D 
expenditure 

1981-2020 

NUTS2 

Human Resources in 
Science and 
Technology (HRST) 

Employment in 
technology and 
knowledge-intensive 

Exports in medium-
high/high-tech 
manufacturing 

1999-2021 

NUTS2 

2008-2021 

NUTS2 

2014-2022 

NUTS2 

CWTS 
UNIV 
LEIDEN 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

74 

 
 
 
 
 
 
 
  
 
  
 
 
 
 
 
 
Sales of new-to-market 
and new-to-firms 
innovation 

New doctorate 
graduates in science, 
technology, 
engineering, and 
mathematics (STEM) 
per 1000 population 
aged 25-34 

Percentage population 
aged 25-64 
participating in lifelong 
learning 

2014-2022 

NUTS2 

2013-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2004-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

International scientific 
co-publications per 
million population 

Limited 
coverage 

Limited coverage 

Scientific publications 
among the top-10% 
most cited publications 
worldwide as 
percentage of total 
scientific publications 
of the country 

Foreign doctorate 
students as a 
percentage of all 
doctorate students 

Limited 
coverage 

Limited coverage 

2012-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Broadband penetration 

2014-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Venture capital 
expenditures 
(percentage of GDP) 

Limited 
coverage 

Limited coverage 

Invest 
Europe 

2000-2019 

32 countries 

Direct government 
funding and 
government tax 
support for business 
R&D (percentage of 
GDP) 

OECD  

R&D expenditure in the 
business sector 
(percentage of GDP) 

1980-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

75 

 
 
 
 
  
 
  
 
 
 
 
 
 
Non-R&D innovation 
expenditures 
(percentage of 
turnover) 

Limited 
coverage 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Innovation 
expenditures per 
person employed 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Enterprises providing 
training to develop or 
upgrade ICT skills of 
their personnel 

2012-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

ICT specialists (as a 
percentage of total 
employment) 

2004-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

2004-2020 

EU27  

2004-2020 

EU27 

2004-2020 

EU27 

SMEs introducing 
product innovations 
(percentage of SMEs) 

SMEs introducing 
business process 
innovations 
(percentage of SMEs) 

Innovative SMEs 
collaborating with 
others (percentage of 
SMEs) 

Public-private co-
publications per million 
population 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Job-to-job mobility of 
Human Resources in 
Science & Technology 

1996-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

PCT patent 
applications per billion 
GDP (in PPS) 

1999-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

OECD Stat 

Trademark applications 
per billion GDP (in 
PPS) 

1999-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

EUIPO 

Design applications per 
billion GDP (in PPS) 

1999-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

EUIPO 

76 

 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
Employment in 
knowledge-intensive 
activities (percentage 
of total employment) 

2008-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Employment in 
innovative enterprises 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Exports of medium and 
high technology 
products as a share of 
total product exports 

Knowledge-intensive 
services exports as 
percentage of total 
services exports 

Sales of new-to-market 
and new-to-enterprise 
innovations as 
percentage of turnover 

2007-2021 

EU27 

2010-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

2004-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Statistics | 
Eurostat 
(europa.eu) 

Resource productivity 

2000-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Air emissions by fine 
particulate matter 
(PM2.5) in Industry 

1995-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Development of 
environment-related 
technologies, 
percentage of all 
technologies 

1976-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

OECD Stat 

Above basic digital 
skills 

2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

At least basic digital 
content creation skills 

2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Female ICT specialists 

2004-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

ICT graduates 

2012-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

Statistics | 
Eurostat 

77 

 
 
 
 
 
 
 
 
 
 
 
 
 
others 

(europa.eu) 

Overall fixed 
broadband take-up 

2010-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

At least 100 Mbps fixed 
broadband take-up 

2013-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

At least 1 Gbps take-
up 

2019-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Fast broadband (NGA) 
coverage 

2013-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Fixed Very High 
Capacity Network 
(VHCN) coverage 

2019-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

5G spectrum 

2020-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

5G coverage 

2020-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Mobile broadband 
take-up 

2010-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Broadband price index 

2017-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

SMEs with at least a 
basic level of digital 
intensity 

2009-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Electronic information 
sharing 

2012-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Social media 

2014-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Big data 

2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

Statistics | 
Eurostat 

78 

 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
Cloud 

2014-2021 

AI 

2021 

others 

(europa.eu) 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

ICT for environmental 
sustainability 

2020 

EU-27 + Iceland, Norway, 
UK, Switzerland 

Statistics | 
Eurostat 
(europa.eu) 

e-Invoices 

2018/2020 

SMEs selling online 

2010-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

e-Commerce turnover 

Statistics | 
Eurostat 
(europa.eu) 

Selling online cross-
border 

2011/13/15/
17/19/2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

e-Government users 

2008-2021 

Pre-filled forms 

2013-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Digital public services 
for citizens 

2013-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Digital public services 
for businesses 

2013-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Open data 

2015-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

European 
Data Portal 

Deaths from infectious 

1990-2019 

204 countries 

IHME 

79 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
diseases 

GHDx 

Child mortality rate 

1980-2021 

204 countries 

IGME UN 

Relates to SDGs 2 
and 3 

Child stunting 

1990-2019 

204 countries 

Maternal mortality rate 

1990-2019 

204 countries 

Undernourishment 

2000-2020 

204 countries 

Access to improved 
sanitation 

Access to improved 
water source 

Unsafe water, 
sanitation and hygiene 
attributable deaths 

1980-2019 

204 countries 

1980-2019 

204 countries 

1980-2019 

204 countries 

Household air pollution 
attributable deaths 

1980-2019 

204 countries 

IHME 
GHDx 

IHME 
GHDx 

FAO 

IHME 
GHDx 

IHME 
GHDx 

IHME 
GHDx 

IHME 
GHDx 

Relates to SDGs 2 
and 3 

Relates to SDGs 2 
and 3 

Relates to SDGs 2 
and 3 

Relates to SDGs 6 
and 12 

Relates to SDGs 6 
and 12 

Relates to SDGs 6 
and 12 

Relates to SDGs 7, 
11 and 3 

Dissatisfaction with 
housing affordability 

1980-2019 

204 countries 

Gallup 
World Poll 

Relates to SDGs 7, 
11 and 3 

Access to electricity 

1990-2020 

204 countries 

Usage of clean fuels 
and technology for 
cooking 

1990-2020 

204 countries 

The World 
Bank Data 

Relates to SDGs 7, 
11 and 3 

Relates to SDGs 7, 
11 and 3 

WHO Data 

Transportation related 
fatalities 

1990-2019 

204 countries 

IHME 
GHDx 

Relates to SDGs 16 
and 3 

Perceived criminality 

2008-2022 

204 countries 

Relates to SDGs 16 
and 3 

Institute for 
Economics 
and Peace 
GPI 

V-Dem 
Dataset 

Relates to SDGs 16 
and 3 

2016-2021 

204 countries 

Political killings and 
torture 

Women with no 
schooling 

1990-2019 

204 countries 

IHME 
GHDx 

Relates to SDG 4 

80 

 
Equal access to quality 
education 

2016-2021 

204 countries 

V-Dem 
Dataset 

Relates to SDG 4 

1970-2019 

204 countries 

Relates to SDG 4 

UNESCO  

1970-2019 

204 countries 

Relates to SDG 4 

UNESCO  

1990-2020 

204 countries 

Relates to SDG 4 

Primary school 
enrollment 

Secondary school 
attainment 

Gender parity in 
secondary attainment 

Access to online 
governance 

204 countries 

2003/04/05/
08/10/12/14
/16/18/20/2
022 

Internet users 

2000-2020 

204 countries 

Media censorship 

2016-2021 

204 countries 

Mobile telephone 
subscriptions 

2000-2021 

204 countries 

Life expectancy at 60 

1990-2019 

204 countries 

Equal access to quality 
healthcare 

2016-2021?  204 countries 

Access to essential 
health services 

Outdoor air pollution 
attributable deaths 

Deaths from lead 
exposure 

1980-2019 

204 countries 

1990-2019 

204 countries 

1990-2019 

204 countries 

Particulate matter 
pollution (Air poluttion) 

1990-2019 

204 countries 

UNDP 

UN 

ITU 

Relates to SDGs 16, 
17 and 9 

Relates to SDGs 16, 
17 and 9 

V-Dem 
Dataset 

Relates to SDGs 16, 
17 and 9 

Relates to SDGs 16, 
17 and 9 

Relates to SDG 3 

ITU 

IHME 
GHDx 

IHME 
GHDx 

V-Dem 
Dataset 

IHME 
GHDx 

IHME 
GHDx 

IHME 
GHDx 

IHME 
GHDx 

Relates to SDG 3 

Relates to SDG 3 

Relates to SDGs 13, 
14, 15, 9 and 12 

Relates to SDGs 13, 
14, 15, 9 and 12 

Relates to SDGs 13, 
14, 15, 9 and 12 

Premature deaths from 
non-communicable 
diseases 

1990-2019 

204 countries 

Relates to SDG 3 

Species protection 

1980-2022 

204 countries 

Map of Life 

Relates to SDGs 13, 
14, 15, 9 and 12 

81 

 
Access to justice 

2016-2021 

204 countries 

Freedom of expression 

2016-2021 

204 countries 

Freedom of religion 

2016-2021 

204 countries 

Political rights 

2013-2022 

195 countries 

V-Dem 
Dataset 

Relates to SDGs 1, 5 
and 16 

V-Dem 
Dataset 

Relates to SDGs 1, 5 
and 16 

V-Dem 
Dataset 

Relates to SDGs 1, 5 
and 16 

Freedom 
House 

Relates to SDGs 1, 5 
and 16 

Property rights for 
women 

2016-2021 

204 countries 

V-Dem 
Dataset 

Relates to SDGs 1, 5 
and 16 

Satisfied demand for 
contraception 

1970-2021 

197 countries 

Early marriage 

1970-2022 

283 countries and regions 

UN 
Population 
Division 

UN 
Population 
Division 

Relates to SDGs 3, 
5, 16, 8 and 10 

Relates to SDGs 3, 
5, 16, 8 and 10 

Vulnerable 
employment 

1991-2019 

266 countries and regions 

ILOSTAT 

Relates to SDGs 3, 
5, 16, 8 and 10 

Equality of political 
power by gender 

2016-2021 

204 countries 

V-Dem 
Dataset 

Relates to SDGs 5, 
16, 11 and 10 

Equality of political 
power by social group 

2016-2021 

204 countries 

V-Dem 
Dataset 

Relates to SDGs 5, 
16, 11 and 10 

Equality of political 
power by 
socioeconomic position 

Discrimination and 
violence against 
minorities 

2016-2021 

204 countries 

2006-2022 

179 countries 

Relates to SDGs 5, 
16, 11 and 10 

Relates to SDGs 5, 
16, 11 and 10 

V-Dem 
Dataset 

Fragil 
States 
Index 

Acceptance of gays 
and lesbians 

Limited 
coverage 

204 countries 

Gallup 
World Poll 

Relates to SDGs 5, 
16, 11 and 10 

Citable documents 

1996-2021 

204 countries 

Academic freedom 

2016-2021 

204 countries 

Relates to SDGs 4 
and 9 

Scimago 
Journal & 
Country 
Rank 

V-Dem 
Dataset 

Relates to SDGs 4 
and 9 

82 

 
Women with advanced 
education 

1990-2019 

204 countries 

IHME 
GHDx 

Relates to SDGs 4 
and 9 

Expected years of 
tertiary schooling 

Quality weighted 
universities 

1970-2021 

204 countries 

2011-2022 

169 countries 

UN SDG 

Relates to SDGs 4 
and 9 

SPI 

Relates to SDGs 4 
and 9 

Security of World Oil 
Reserves 

2008-2020 

Global, one figure for 
World 

Security of World Oil 
Production 

2008-2020 

Global, one figure for 
World 

Security of World 
Natural Gas Reserves 

2008-2020 

Global, one figure for 
World 

Security of World 
Natural Gas Production 

2008-2020 

Global, one figure for 
World 

Security of World Coal 
Reserves 

2008-2020 

Global, one figure for 
World 

Security of World Coal 
Production 

2008-2020 

Global, one figure for 
World 

Security of Petroleum 
Imports 

2008-2020 

Security of Natural Gas 
Imports 

2008-2020 

EU-27 + Ukraine, Moldova, 
Kosovo, Bosnia, Turkey, 
Serbia, Albania, N 
Macedonia, Montenegro, 
UK, Norway, Iceland 

EU-27 + Ukraine, Moldova, 
Kosovo, Bosnia (from 
2014), Turkey, Serbia, 
Albania, N Macedonia, 
Montenegro, UK (until 
2019), Norway, Iceland 

Oil & Natural Gas 
Import Expenditures 
per capita 

Oil & Natural Gas 
Import Expenditures 
per GDP 

2008-2020 

EU-27 

2008-2020 

EU-27 

Energy Expenditures 
per GDP 

2008-2020 

EU-27 

83 

 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
Energy Expenditures 
per capita 

2008-2020 

EU-27 

Retail Electricity Prices 
- HH 

2008-2020 

EU-27 

Crude Oil Prices 

2008-2020 

Global, one figure for 
World 

Crude Oil Price 
Volatility 

2008-2020 

Global, one figure for 
World 

Energy Expenditure 
Volatility 

2009-2021 

EU-27 

World Oil Refinery 
Utilization 

2008-2020 

Global, one figure for 
World 

Petroleum Stock 
Levels 

2008-2020 

EU-27 

Gas Stocks 

2011-2021 

EU-27 

N-1 criteria 

2008-2020 

EU-27 

Energy Consumption 
per Capita 

2008-2020 

EU-27 

Energy Intensity 

2008-2020 

EU-27 

Fossil Energy Intensity 

2008-2020 

EU-27 

Household Energy 
Efficiency 

2008-2021 

EU-27 

Commercial Energy 
Efficiency 

2008-2020 

Bulgaria, Romania, 
Greece, Italy, Germany 

Industrial Energy 
Efficiency 

2008-2020 

EU-27 

Electricity Capacity 
Diversity 

2008-2020 

Bulgaria, Romania, 
Greece, Italy, Germany 

Electricity Capacity 
Margins 

2008-2020 

Bulgaria, Romania, 
Greece, Italy, Germany 

Electricity 
Transmission Line 

EU-27 

2015-2018 
(other data 
is 

84 

 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
Mileage 

extrapolate
d) 

Transmission and 
distribution losses 

2008-2020 

EU-27 

Transportation energy 
use per capita 

2008-2020 

EU-27 

Transportation energy 
use per $ GDP 

2008-2020 

EU-27 

Transportation Non-
Petroleum Fuels 

2008-2020 

EU-27 

CO2 prices 

2008-2021 

Global, one figure for 
World 

CO2 costs 

2008-2020 

EU-27 

Energy-Related CO2 
Emissions per Capita 

2008-2020 

EU-27 

Energy-Related CO2 
Emissions Intensity 

2008-2020 

EU-27 

Electricity non-CO2 
Generation Share 

2008-2020 

EU-27 (with some ninor 
additional work from KR - 
the data is avaialble) 

Land Cover 

2008-2018 

EU-27 

Waste per Capita 

2008-2018 

EU-27 

Waste Recovery 

2008-2018 

EU-27 

Science & Engineering 
Degrees 

2008-2021 

EU-27 

Life expectancy at birth 

1960-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Our World 
in Data 

Relates to SDG 3 

Expected years of 
schooling 

1990-2017 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Our World 
in Data 

Relates to SDG 4 

Mean years of 
schooling 

1870-2017 

EU-27 + Iceland, Norway, 
UK, Switzerland and 

Our World 
in Data 

Relates to SDG 4 

85 

 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
  
 
others 

Gross national income 
(GNI) per capita 

1987-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Poverty rate 

1996-2020 

266 countries and regions 

Our World 
in Data 

The World 
Bank 

Median income 

1970-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

The World 
Bank 

Relates to SDG 8 

Relates to SDG 1 

Relates to SDG 1 

Adjusted Net Savings, 
Excluding Carbon 
Damage (% of GNI) 

1975-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

The World 
Bank 

Dependency ratio 

1960-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

The World 
Bank 

Dwellings without basic 
facilities 

2010-2020 

OECD  

Housing expenditure 

2008-2020 

OECD  

OECD 

OECD 

Relates to SDG 11 

Rooms per person 

2003-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Relates to SDG 11 

Household net Wealth  

2009-2019 

OECD  

Labour Market 
Insecurity 

2005-2016 

OECD  

Personal earnings 

2000-2021 

OECD  

OECD 

OECD 

OECD 

Quality of support network 

Gallup World Poll 

Student skills 

2018 

OECD  

Water quality 

2020 

OECD  

Stakeholder 
engagement for 
developing regulations 

OECD  

EU 2019-
2022, Ireg: 
1998-2008, 
2015, 2018, 
2021 

OECD BLI 

Gallup 
World Poll 

OECD 

86 

 
 
 
 
 
 
 
 
 
 
 
 
Voter turnout 

1945-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Self-reported health 

2010-2021 

OECD  

Life satisfaction 

2020 

Worldwide 

2020 

Worldwide 

Feeling safe walking 
alone at night 

Employees working 
very long hours 

Time devoted to leisure 
and personal care 

Latest year  OECD  

Personal Consumption 
Expenditures 

1970-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Income Inequality 

1960-2010 

Oregon, USA 

Adjusted Personal 
Consumption 

1960-2010 

Oregon, USA 

Cost of Consumer 
Durables 

1960-2010 

Oregon, USA 

Value of Consumer 
Durables 

1960-2010 

Oregon, USA 

87 

IDEA 

OECD 

Gallup 
World Poll 

Gallup 
World Poll 

OECD 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 

 
 
 
 
 
 
 
  
 
 
 
 
 
 
Cost of 
Underemployment 

1960-2010 

Oregon, USA 

Net Capital Investment 

1960-2010 

Oregon, USA 

Cost of Water Pollution 

1960-2010 

Oregon, USA 

Cost of Air Pollution 

1960-2010 

Oregon, USA 

Cost of Noise Pollution 

1960-2010 

Oregon, USA 

Loss of Wetlands 

1960-2010 

Oregon, USA 

Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

88 

 
 
 
 
 
 
 
Loss of farmland, soil 
quality or degradation 

1960-2010 

Oregon, USA 

Loss of Primary 
Forest and damage 
from logging roads 

1960-2010 

Oregon, USA 

CO2 Emissions 

1960-2010 

Oregon, USA 

Cost of Ozone 
Depletion 

1960-2010 

Oregon, USA 

Depletion of Non-
Renewables 

1960-2010 

Oregon, USA 

Value of Housework 
and Parenting 

1960-2010 

Oregon, USA 

Cost of Family 
Changes 

1960-2010 

Oregon, USA 

89 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 

 
 
 
 
 
 
 
 
Cost of Crime 

1960-2010 

Oregon, USA 

Cost of Household 
Pollution Abatement 

1960-2010 

Oregon, USA 

Value of Volunteer 
Work 

1960-2010 

Oregon, USA 

Loss of Leisure Time 

1960-2010 

Oregon, USA 

Value of Higher 
Education 

1960-2010 

Oregon, USA 

Value of Highways and 
Streets 

1960-2010 

Oregon, USA 

Cost of Commuting 

1960-2010 

Oregon, USA 

90 

Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 

 
 
 
 
 
 
 
 
Cost of Auto Accidents 

1960-2010 

Oregon, USA 

Market Consumption 
per capita   adjusted 
for variation in 
household size 

1995-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

(GPI) for 
Oregon 

Estimates 
of the 
Genuine 
Progress 
Indicator 
(GPI) for 
Oregon 

Statistics | 
Eurostat 
(europa.eu) 

Unpaid Work per 
capita   

2000/2010 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

Leisure per capita 

Latest year  OECD 

OECD Stat 

Government Spending 
per capita   

1995-2021 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

less: Regrettable 
Expenditures per 
capita   

Capital Stock per 
capita   

Limited 
coverage 

Limited coverage 

1975-2021 

EU28 

Natural Resources per 
capita   

1970-2020 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Human Capital per 
capita   

2010-2020 

174 countries 

Wong 
(2020) 

Statistics | 
Eurostat 
(europa.eu) 

The World 
Bank  

The World 
Bank - 
Human 
Capital 
Project 

less: Net International 
Investment Position 
per capita   

1995-2022 

EU-27 + Iceland, Norway, 
UK, Switzerland and 
others 

Statistics | 
Eurostat 
(europa.eu) 

less: Cost of 
Environmental 
Degradation per capita   

Limited 
coverage 

Limited coverage 

91 

 
 
 
 
 
 
 
 
 
 
 
  
 
Risk imposed by 
unemployment 

1981-2008 

Canada 

Replacement rate 

2020 

OECD 

OECD 

Financial risk from 
illness 

Medical Care 
Expenses % of 
Disposable income 

1981-2008 

Canada 

2010-2021 

OECD 

Risk from single parent 
poverty 

1981-2008 

Canada 

Poverty rate for single 
parents with children 
under 18 

1981-2008 

Canada 

OECD 

Divorce rate 

1990-2020 

OECD 

OECD 

Risk from poverty in 
old age 

1981-2008 

Canada 

Elderly poverty rate 

2004-2021 

OECD 

OECD 

Environmental 
Performance Index 

1990-2022 

180 countries 

Ecosystem Vitality 

1990-2022 

180 countries 

Environmental Health 

1990-2022 

180 countries 

Climate Change Policy 
Objective 

1990-2022 

180 countries 

Biodiversity 

1990-2022 

180 countries 

92 

Relates to SDGs 3, 
6, 11, 13, 14, 15 

Relates to SDGs 6, 
11, 13, 14, 15 

Relates to SDGs 3, 
6, 11, 13, 14, 15 

Relates to SDG 13 

Relates to SDGs 14, 

Yale 

Yale 

Environmen
tal Health | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Climate 
Change 
Policy 
Objective | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Biodiversity 
& Habitat | 

 
  
 
 
  
 
 
  
 
  
 
 
  
 
 
15 

Relates to SDG 15 

Relates to SDG 15 

Relates to SDG 14 

Relates to SDG 15 

Relates to SDG 15 

Environmen
tal 
Performanc
e Index 
(yale.edu) 

Terrestrial 
biome 
protection 
(national 
weights) | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Terrestrial 
biome 
protection 
(global 
weights) | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Marine 
protected 
areas | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Protected 
Areas 
Representa
tiveness 
Index | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Biodiversity 
Habitat 
Index | 
Environmen
tal 
Performanc
e Index 

Terrestrial biome 
protection (national 
weights) 

1990-2022 

180 countries 

Terrestrial biome 
protection (global 
weights) 

1990-2022 

180 countries 

Marine protected areas 

1990-2022 

180 countries 

Protected Areas 
Representativeness 
Index 

1960-2022 

180 countries 

Biodiversity Habitat 
Index 

1990-2022 

180 countries 

93 

 
Species Protection 
Index 

1990-2022 

180 countries 

Species Habitat Index 

1990-2022 

180 countries 

Ecosystem Services 

1990-2022 

180 countries 

Tree Cover Loss 

1990-2022 

180 countries 

Grassland Loss 

1990-2022 

180 countries 

Wetland Loss 

1990-2022 

180 countries 

Fisheries 

1990-2022 

180 countries 

94 

(yale.edu) 

Species 
Protection 
Index | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Species 
Habitat 
Index | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Ecosystem 
Services | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Tree cover 
loss | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Grassland 
loss | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Wetland 
loss | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Fisheries | 
Environmen
tal 

Relates to SDG 15 

Relates to SDG 15 

Relates to SDG 15 

Relates to SDG 15 

Relates to SDG 15 

Relates to SDG 15 

Relates to SDG 14 

 
Performanc
e Index 
(yale.edu) 

Fish Stock 
Status | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Marine 
Trophic 
Index | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Fish caught 
by trawling 
and 
dredging | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Acid Rain | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Adjusted 
emissions 
growth rate 
for sulfur 
dioxide | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Adjusted 
emissions 
growth rate 
for nitrous 
oxides | 
Environmen

Relates to SDG 14 

Relates to SDG 14 

Relates to SDG 14 

Relates to SDGs 3, 
6, 14, 15 

Relates to SDGs 3, 
6, 14, 15 

Relates to SDGs 3, 
6, 14, 15 

Fish Stock Status 

1990-2022 

180 countries 

Marine Trophic Index 

1990-2022 

180 countries 

Fish caught by trawling 
and dredging 

1990-2022 

180 countries 

Acid Rain 

1990-2022 

180 countries 

Adjusted emissions 
growth rate for sulfur 
dioxide 

1990-2022 

180 countries 

Adjusted emissions 
growth rate for nitrous 
oxides 

1990-2022 

180 countries 

95 

 
tal 
Performanc
e Index 
(yale.edu) 

Agriculture | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Sustainable 
Pesticide 
Use | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Sustainable 
Nitrogen 
Manageme
nt Index | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Wastewater 
treatment | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Air Quality | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

PM2.5 
exposure | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Relates to SDG 3, 
12, 15 

Relates to SDG 3, 
12, 15 

Relates to SDG 3, 
12, 15 

Relates to SDG 6 

Relates to SDGs 3, 
11, 12, 13 

Relates to SDGs 3, 
11, 12, 13 

Agriculture 

1990-2022 

180 countries 

Sustainable Pesticide 
Use 

1990-2022 

180 countries 

Sustainable Nitrogen 
Management Index 

1990-2022 

180 countries 

Wastewater treatment 

1990-2022 

180 countries 

Air Quality (index) 

1990-2022 

180 countries 

PM2.5 exposure 

1990-2022 

180 countries 

96 

 
Household solid fuels 

1990-2022 

180 countries 

Ozone exposure 

1990-2022 

180 countries 

Nitrogen oxides (NOx) 
exposure 

1990-2022 

180 countries 

Sulfur dioxide 
exposure 

1990-2022 

180 countries 

Carbon monoxide 
exposure 

1990-2022 

180 countries 

Volatile organic 
compounds exposure 

1990-2022 

180 countries 

Relates to SDGs 3, 
11, 12, 13 

Relates to SDGs 3, 
11, 12, 13 

Relates to SDGs 3, 
11, 12, 13 

Relates to SDGs 3, 
11, 12, 13 

Relates to SDGs 3, 
11, 12, 13 

Relates to SDGs 3, 
11, 12, 13 

Household 
solid fuels | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Ozone 
exposure | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Nitrogen 
oxides 
(NOx) 
exposure | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Sulfur 
dioxide 
exposure | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Carbon 
monoxide 
exposure | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Volatile 
organic 
compounds 
exposure | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

97 

 
Sanitation and Drinking 
Water 

1990-2022 

180 countries 

Unsafe sanitation 

1990-2022 

180 countries 

Unsafe drinking water 

1990-2022 

180 countries 

Lead exposure 

1990-2022 

180 countries 

Waste Management 

1990-2022 

180 countries 

Controlled solid waste 

1990-2022 

180 countries 

Recycling 

1990-2022 

180 countries 

98 

Sanitation 
and 
Drinking 
Water | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Unsafe 
sanitation | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Unsafe 
drinking 
water | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Lead 
exposure | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Waste 
Manageme
nt | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Controlled 
solid waste 
| 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Recycling | 
Environmen

Relates to SDGs 3, 6 

Relates to SDGs 3, 6 

Relates to SDGs 3, 6 

Relates to SDG 3 

Relates to SDGs 3, 
11, 12, 13, 14, 15 

Relates to SDGs 3, 
11, 12, 13, 14, 15 

Relates to SDGs 3, 

 
11, 12, 13, 14, 15 

Relates to SDG 14 

Relates to SDG 3, 7, 
11, 12, 13, 14, 15 

Relates to SDG 3, 7, 
11, 12, 13, 14, 15 

Relates to SDG 3, 7, 
11, 12, 13, 14, 15 

Relates to SDG 3, 7, 
11, 12, 13, 14, 15 

tal 
Performanc
e Index 
(yale.edu) 

Ocean 
Plastics | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Adjusted 
emissions 
growth rate 
for carbon 
dioxide | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Adjusted 
emissions 
growth rate 
for methane 
| 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Adjusted 
emissions 
growth rate 
for F-gases 
| 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Adjusted 
emissions 
growth rate 
for nitrous 
oxide | 
Environmen
tal 
Performanc
e Index 

Ocean Plastics 

1990-2022 

180 countries 

Adjusted emissions 
growth rate for carbon 
dioxide 

1850-2019 

180 countries 

Adjusted emissions 
growth rate for 
methane 

1850-2019 

180 countries 

Adjusted emissions 
growth rate for F-gases 

1850-2019 

180 countries 

Adjusted emissions 
growth rate for nitrous 
oxide 

1850-2019 

180 countries 

99 

 
Adjusted emissions 
growth rate for black 
carbon 

1990-2022 

180 countries 

Projected GHG 
Emissions in 2050 

1990-2022 

180 countries 

Growth rate in carbon 
dioxide emissions from 
land cover 

1990-2022 

180 countries 

Greenhouse gas 
intensity growth rate 

1850-2019 

180 countries 

Greenhouse gas 
emissions per capita 

1990-2022 

180 countries 

100 

Relates to SDG 3, 7, 
11, 12, 13, 14, 15 

Relates to SDG 3, 7, 
11, 12, 13, 14, 15 

Relates to SDG 3, 7, 
11, 12, 13, 14, 15 

Relates to SDG 3, 7, 
11, 12, 13, 14, 15 

Relates to SDG 3, 7, 
11, 12, 13, 14, 15 

(yale.edu) 

Adjusted 
emissions 
growth rate 
for black 
carbon | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Projected 
GHG 
Emissions 
in 2050 | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Growth rate 
in carbon 
dioxide 
emissions 
from land 
cover | 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Greenhous
e gas 
intensity 
growth rate 
| 
Environmen
tal 
Performanc
e Index 
(yale.edu) 

Greenhous
e gas 
emissions 
per capita | 
Environmen
tal 
Performanc
e Index 

 
Exchange rate per US$  1995-2022 

65 countries 

IMD Competitiveness 
Index 

1995-2022 

65 countries 

Household 
consumption 

Government 
consumption 
expenditure 

1995-2022 

65 countries 

1995-2022 

65 countries 

Food costs 

1995-2022 

65 countries 

(yale.edu) 

IMD World 
Competitive
ness Online 

IMD World 
Competitive
ness Online 

IMD World 
Competitive
ness Online 

IMD World 
Competitive
ness Online 

IMD World 
Competitive
ness Online 

Relates to SDG 8 

Relates to SDGs 1 
and 8 

Relates to SDGs 2, 8 

People at risk of 
poverty or social 
exclusion 

Housing cost 
overburden rate (% 
population) 

2015-2021 

EU-27 

Relates to SDG 1 

Eurostat 

2010-2021 

36 European countries 

Relates to SDG 1 

Eurostat 

Obesity rate, by body 
mass index 

2008,2014,
2017,2019 

34 European countries 

Relates to SDG 2 

Eurostat 

Agricultural factor 
income per annual 
work unit 

Government support to 
agricultural research 
and development 

Area under organic 
farming 

Use of more hazardous 
pesticides 

Ammonia emissions 
from agriculture 

2005-2022 

31 European countries 

Relates to SDG 2 

Eurostat 

2004-2021 

38 European countries 

Relates to SDG 2 

Eurostat 

2000-2020 

34 European countries 

Relates to SDG 2 

Eurostat 

2011-2020 

16 European countries 

Relates to SDG 2 

Eurostat 

1990-2020 

33 European countries 

Relates to SDG 2 

Eurostat 

101 

 
 
 
Share of people with 
good or very good 
perceived health, by 
sex 

2005-2021 

37 European countries 

Relates to SDG 3 

Eurostat 

Smoking prevalence, 
by sex 

2006,2009,
2012,2014,
2017,2020 

31 European countries 

Relates to SDG 3 

Eurostat 

Standardised death 
rate due to 
tuberculosis, HIV and 
hepatitis, by type of 
disease 

Standardised 
preventable and 
treatable mortality 

2000-2019 

36 European countries 

Relates to SDG 3 

2011-2019 

34 European countries 

Relates to SDG 3 

Eurostat 

Low achieving 15-year-
olds in reading, 
mathematics or 
science 

2000,2003,
2006,2009,
2012,2015,
2018 

Eurostat 

41 European countries 

Relates to SDG 4 

Eurostat 

Participation in early 
childhood education 

2000-2020 

36 European countries 

Relates to SDG 4 

Eurostat 

Share of individuals 
having at least basic 
digital skills, by sex 

2015,2016,
2017,2019,
2021 

38 European countries 

Relates to SDG 4 

Eurostat 

Physical and sexual 
violence to women 
experienced within 12 
months prior to the 
interview 

2021 

9 European countries 

Relates to SDG 5 

Eurostat 

Gender overall 
earnings gap 

2002,2006,
2010,2010,
2018 

37 European countries 

Relates to SDG 5 

Eurostat 

Inactive population due 
to caring 
responsibilities, by sex 

Seats held by women 
in national parliaments 

Positions held by 
women in senior 
management 

2000-2021 

35 European countries 

Relates to SDG 5 

Eurostat 

2003-2021 

38 European countries 

Relates to SDG 5 

Eurostat 

2003-2021 

36 European countries 

Relates to SDG 5 

Eurostat 

102 

 
Population having 
neither a bath, nor a 
shower, nor indoor 
flushing toilet in their 
household 

Population connected 
to at least secondary 
waste water treatment 

Biochemical oxygen 
demand in rivers 

2003-2020 

37 European countries 

Relates to SDG 6 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 6 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 6 

Eurostat 

Nitrate in groundwater 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 6 

Phosphate in rivers 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 6 

Water exploitation 
index 

Primary and final 
energy consumption 

Share of renewable 
energy in gross final 
energy consumption 

Energy import 
dependency 

Population unable to 
keep home adequately 
warm 

Investment share of 
GDP 

2000-2021 

30-40 European countries 

Relates to SDG 6 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 7 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 7 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 7 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 7 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 8 

Eurostat 

Fatal accidents at work 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 8 

R&D personnel 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 9 

Patent applications to 
the European Patent 
Office 

Air emissions intensity 
of industry for 
particulate matter 

Share of buses and 
trains in inland 

2000-2021 

30-40 European countries 

Relates to SDG 9 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 9 

Eurostat 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 9 

103 

 
passenger transport 

Share of rail and inland 
waterways in inland 
freight transport 

Income share of the 
bottom 40% of the 
population 

Relative median at-
risk-of-poverty gap 

Disparities in 
purchasing power 
adjusted GDP per 
capita 

Purchasing power 
adjusted GDP per 
capita 

Asylum applications 
and decision 

First time asylum 
applications 

People at risk of 
poverty or social 
exclusion, by degree of 
urbanisation 

People at risk of 
income poverty after 
social transfers 

2000-2021 

30-40 European countries 

Relates to SDG 9 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 10 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 10 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 10 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 10 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 10 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 10 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 10 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 10 

Eurostat 

Training 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 10 

Severe housing 
deprivation rate, by 
degree of urbanisation 

Population living in 
households 
considering that they 
suffer from noise, by 
degree of urbanisation 

Years of life lost due to 
PM2.5 exposure 

2000-2021 

30-40 European countries 

Relates to SDG 11 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 11 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 11 

Eurostat 

104 

 
Settlement area per 
capita 

Consumption of 
hazardous chemicals 

Raw material 
consumption 

Average CO2 
emissions per km from 
new passenger cars 

Share of zero 
emissions vehicles 

Gross value added in 
the environmental 
goods and services 
sector 

Net greenhouse gas 
emissions 

Greenhouse gas 
emissions and 
removals 

Net greenhouse gas 
emissions from land 
use and forestry 

Climate-related 
economic losses (30 
year moving average) 

Population covered by 
the Covenant of 
Mayors for Climate and 
Energy signatories 

Contribution to the 
international USD 
100bn commitment on 
climate-related 
expenditure 

Bathing sites with 
excellent water quality 

2000-2021 

30-40 European countries 

Relates to SDG 11 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 12 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 12 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 12 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 12 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 12 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 13 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 13 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 13 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 13 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 13 

2000-2021 

30-40 European countries 

Relates to SDG 13 

Eurostat 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 14 

Eurostat 

Marine waters affected 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 14 

105 

 
by eutrophication 

Global mean surface 
seawater acidity 

Estimated trends in fish 
stock biomass 

2000-2021 

30-40 European countries 

Relates to SDG 14 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 14 

Eurostat 

Share of forest area 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 15 

Soil sealing index 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 15 

Estimated severe soil 
erosion by water 

2000-2021 

30-40 European countries 

Relates to SDG 15 

Eurostat 

Common bird index 

2000-2021 

30-40 European countries 

Eurostat 

Relates to SDG 15 

Grassland butterfly 
index 

Population reporting 
occurrence of crime, 
violence or vandalism 
in their area 

Population with 
confidence in EU 
institutions 

Official development 
assistance as share of 
gross national income 

EU financing to 
developing countries 

EU imports from 
developing countries 

Share of environmental 
taxes in total tax 
revenues 

High-speed internet 
coverage 

2000-2021 

30-40 European countries 

Relates to SDG 15 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 16 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 16 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 17 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 17 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 17 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 17 

Eurostat 

2000-2021 

30-40 European countries 

Relates to SDG 17 

Eurostat 

106 

 
 
ANNEX 2 – SUMMARY OF IN-DEPTH INTERVIEWS  

Interview I 
Friday, 16 Dec 2022, 11:00-12:00 EEST 
The focus should be on environmental, social, and economic indicators. In the case 
of economic indicators, the ‘Beyond GDP’ community should give more attention to 
inequality  indicators,  such  as  GINI,  but  also  to  gender  inequality  measures. 
Environmental  indicators  are  essential,  but  slightly  underrepresented  in  the  list  of 
selected  indicators.  Emissions  per  capita  must  be  included;  however,  emissions 
should be measured on the consumption side, not on the production side, because 
western  countries,  in  particular,  cause  additional  emissions  abroad  through  their 
consumption of imported goods.  

 All  environmental  indicators  of  the  pre-selected  list  should  be  included  in  the  less 
ambitious  scenario  except  Grassland  loss  because  it  is  too  specific.  A  more 
appropriate  option  would  be  a  measure  for  Loss  of  biodiversity.  In  this  train  of 
thought, the inclusion of the Wilderness Quality Index by the European Environment 
Agency could be a suitable candidate. Other essential indicators are Unemployment, 
Child  mortality  rate,  Self-reported  health,  and  Life  satisfaction,  while  Gross 
expenditure on R&D (% of GDP), Resource productivity (PPP$ per kg) and General 
government gross debt (% of GDP) could be ruled out.  

The  four  dimensions  used  in  the  TPI  are  relevant  and  significant,  however,  the 
problem is not a lack of indices, indicators or tools, but instead a lack of willingness 
by  policy  makers  to  acknowledge  them  as  equally  important  as  GDP.  Overall, 
calculating an aggregate score once a final selection of indicators has been done is 
preferable,  since  a  single  score  is  easier  to  communicate  to  policymakers,  media, 
and the public. When it comes to the choice of indicators most representative of the 
SDGs, it would be better that every SDG has its own index.  

Interview II 
Friday, 16 Dec 2022, 12:00-13:00 EEST 

Having to include GDP  as one of the indicators in the ‘Beyond GDP’ monitoring set 
is  problematic  because  it  is  merely  a  measure  of  production.  Rather,  Consumption 
must  be  included  as  an  economic  indicator  or  at  least  an  adjusted  version  of  GDP 
(e.g.  adjusted  to  depletion  of  natural  resources)  should  be  used.  In  addition  to 
Consumption, Healthy life expectancy, Life satisfaction, GINI, Employment rate and 
a  gender  inclusiveness  indicator  must  be  a  part  of  the  monitoring  tool.  Generally, 
indicators  that  measure  inputs  should  be  substituted  with  those  that  measure 
outcomes  (e.g.  Years  of  schooling  instead  of  Government  expenditures  for 
education). 

Alternative  dimensions  to  those  of  the  TPI  could  be  ‘Well-being’,  ‘Inclusion’  and 
‘Sustainability’, since all ‘Beyond GDP’ indicators could be categorised according to 
those  three  dimensions,  which  measure  the  well-being  of  both  current  and  future 
generations.  Moreover, they  are  easy  to  understand,  easy  to  relate  to,  and  easy  to 
communicate to the general public.  

107 

 
 
 
Too  often  dimensions  used  in  such  indices  evaluate  how  well  systems  are  doing 
(e.g., the economy, the political system, and society) but fall short of measuring how 
well people are doing. If a country performs well in terms of well-being, inclusion and 
sustainability,  this  would  also  reflect  good  governance  and  a  well-functioning 
economy.  These  three  dimensions  should  not  be  aggregated  to  a  single  score 
because they reveal and assess different concepts.  

GDP owes its success to the System of national accounts. Thus, there is a need for 
an  alternative  accounting  framework  to  create  policy  models  that  also  show  the 
trade-offs  between  indicators  and  take  retrospective  data  and  projections  into 
account.  Behind  every  index  and  dashboard,  there  should  be  a  clear  idea  of  the 
meaning of sustainable development and the goal at the end of the process. 

Interview III 
Friday, 16 Dec 2022, 17:30-18:30 EEST 

The  five-indicators  scenario  should  be  comprised  of:  Life  satisfaction  (as  it  tells 
something important); GINI (as a measure of inequality); Greenhouse gas emissions 
(the environmental side);  Life expectancy (which fits better in the 12-indicators list); 
and  Unemployment  rate  (as  a  social  and  economic  indicator).  The  four dimensions 
of  the  TPI  are  appropriate  but  the  social  dimension  could  be  unpacked  (e.g., 
education, health, time use, culture domain, etc.). 

In terms of statistical quality, indicators should be aggregated but weighting them is 
challenging because indicators respond to local jurisdictions, so questions like "Are 
they really equally important? And important for what?" should be answered locally. 
An  aggregated  number  is  useful  politically,  but  in  terms  of  representativeness, 
dimensions  should  be  aggregated  on  a  dashboard  with  no  single  number.  Instead, 
they should be supported by data behind. 

Developing a ‘Beyond GDP’ well-being and economic measuring system should be 
done through a public process of collaboration and debate in local jurisdictions. GDP 
dominance  may  be  explained  by  the  fact  that  GDP  responds  to  the  interest  groups 
represented  in  this  approach.  To  go  beyond,  civil  society  engagement  (i.e.,  NGOs, 
media,  researchers,  etc.)  in  a  top-down/bottom-up  mix  that  collects  all  of  the 
receptivity  critics  of  GDP  have  is  required.  Good  examples  are  Scotland,  Finland, 
New Zealand, and Wales, where political leaders have different approaches. At the 
end of the day, determining the best indicators is a political choice. 

Interview IV 
Monday, 19 Dec 2022, 11:00-12:00 EEST 

Any of the 600 indicators collected by the CSD team could be a valid choice because 
none of them is a complete measure. Thus, a dynamic approach must be a factor in 
the  selection,  considering  "living  indicators".  Climate  (check  The  SEEA  Ecosystem 
Accounting),  Biodiversity  (World  Summit  on  Nature  in  Montreal  will  propose  new 
objectives/indicators), and Chemical emissions (pesticides and plastics, although we 
don’t  have  the  best  indicators  yet)  should  be  included  in  a  short-list  scenario  of 
indicators as they would account for planetary boundaries. In a broader scenario, the 
economic  dimension  has  already  been  well-covered  (including  the  labour  market).  
On the other hand, distributions could be represented by any income indicator; Child 

108 

 
 
 
 
 
mortality  might  cover  health  at  a  global  level;  and  any  dimensional  poverty 
indicator/V-Dem  indicator  or  OECD  Integrity  indicator  could  be  a  proxy  for 
governance. 

The existing TPI dimensions could be expanded to stress more on sustainability and 
the  "Donut  approach"  (input/output  limits).  Yet,  having  different  dimensions  is  an 
artificial distinction because ‘social’ leads to ‘economic’ and ‘environmental’ leads to 
‘social’. In any case, naming and building dimensions are political decisions, as well 
as having an aggregate number. If an index cannot be decomposed (into accounts), 
it will be appealing, but it will not aid in political accountability. 

T  Indicators  should  transcend  limits  from  national  to  supranational  levels  (e.g., 
input/output  aggregated  calculations  from  global  standards  capable  of  being 
translated  to  lower levels).  In  fact,  Eurostat  calculates  footprints  for all  of  the  EU27 
applying  this  approach.  An  independent  statistical  office  should  be  responsible  for 
the  composition  of  a  valid  ‘Beyond  GDP’  in  order  to  avoid  conflict  of  interest  and 
overcome all the difficulties related to this effort. Standardization and Governance in 
this new measuring system will only work if they follow European-level standards. 

Interview V 
Tuesday, 20 Dec 2022, 18:00-19:00 EEST 

The  shortlisted  ‘Beyond  GDP’  scenario  should  consist:  Healthy  life  expectancy, 
Education, Poverty (national poverty line), Inequality 90/10 (or any other ratio other 
than  GINI  because it is  an  average),  and  sustainability  (if  needed,  a  CO2  emission 
on the production side). 

An  important  question  is  how  to  solve  the  trade-off  between  more  indicators,  as 
policy  makers  get  lost  with  more  than  five  of  six,  or  fewer  indicators  that  imply  a 
political decision to be made. Weighting the different dimensions is a real challenge 
because  it  is  unlikely  that  they  would  be  equally-weighted.  Depending  on  the 
purpose and the audience, PCA or Factor Analysis might be practiced. 

GDP  prevails  in  the  economic  discourse  because  the  economy  is  seen  as  a 
corporate  business  where  this  accounting  method  is  appropriate.  If  we  look  at 
individuals  and  countries  together  as  business  units,  it  makes  sense  to  apply  such 
"economic  model"  (referring  to  GDP).  Instead,  indicators  that  incorporate  surveys, 
such  as  Median  income,  Unemployment,  Multidimensional  poverty,  or  Productive 
capacity index should be taken as good measurements of well-being. In this regard, 
GDP  should  not  be  included  in  a  ‘Beyond  GDP’  approach  because  political  and 
geopolitical issues also come with it. 

Including  governance  indicators  is  a  matter  of  values  because  they  depend  on 
territorial needs and values. When a project like ours tries to go for the easy way-out 
by  choosing  a  governance  indicator  for  the  sake  of  including  this  dimension,  a 
ground-based  sense  is  lost  every  time  such  measures  include  subjective  opinions 
from  experts  such  as  the  UN  Governance  indicators.  A  good  set  of  well-being 
indicators  that  solve  the  matching  expectations  vs.  realities  problem  could  include: 
nutrition,  education,  health,  and  poverty.  The  ‘Beyond  GDP’  project  should  keep 
certain flexibility that the PCA and Factor analysis could provide. 

109 

 
 
In-depth Interview Questionnaire  

1. 

If you had to propose a ‘Beyond GDP’ monitoring set with four-five indicators 
including GDP, what would these be? Why?  

2.  The Transition Performance Index (TPI), trying to address the ‘Beyond GDP’ 
approach, measures progress towards a fair and prosperous sustainability on 
four dimensions: economic, social, environmental, and governance.  

What dimensions would you suggest?  

3.  What are the best economic indicators?  

4.  What are the best governance indicators?  

5.  What indicators would you include as measurement of quality of life and 

multidimensional well-being?  

6.  What are the most important indicators (you would include) measuring the 

progress towards the SDGs? 

7.  How should the different dimensions be weighted? Why? 

8.  What are the main challenges in developing a ‘Beyond GDP’ monitoring set in 

terms of conceptual framework?  

9.  How would you suggest a ‘Beyond GDP’ monitoring set be designed? What 

would your approach/methodology be?  

10.  What are the major difficulties in developing a ‘Beyond GDP’ monitoring set in 
terms of communication and stakeholder (e.g., member states, media and 
citizens) engagement?   

11.  How to overcome these challenges?   

12.  The history of ‘Beyond GDP’ is far more complex than the history of 

GDP (Compendium of Sustainable Development Indicator Initiatives listed over 
900 such initiatives). Why have the many alternatives not managed to 
effectively challenge GDP's dominance? What strategy should be adopted to 
make it work?  

13. 

If you had to propose a ‘Beyond GDP’ monitoring set with around twelve 
indicators, providing the completest possible picture, what would these be?  

14.  What are the most important indicators (you would include) within the 

framework of The 8th Environmental Action Programme/ The European Green 
Deal?  

110 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ANNEX 3 – ONLINE EXPERT SURVEY  

Survey results 

The  expert  survey  took  part  between  December  9th  and  December  17th  2022.  The 
survey  was  completely  anonymous.  The  questionnaire  was  completed  by  18 
participants and partially filled in by another 17 participants.  

Most  of  the  experts  (78%  of  18  experts  who  answered  the  question)  consider 
a monitoring set (index) based on a reduced number of indicators to be rather useful 
or very useful to the implementation of EU-wide sustainable transition strategy. 

Do you think that a monitoring set (index) based on 
a reduced number of indicators would be useful to 
the implementation of EU-wide sustainable 
transition strategy?

6%

17%

39%

39%

Very useful

Rather useful

Not very useful

Useless

The consensus on the usefulness of such an index is even more impressive when it 
comes  to  outreaching  a  wider  audience  –  nearly  90%  (89%  of  18  experts  who 
answered  the  question)  think  that  the  monitoring  set  will  be  rather  useful  or  very 
useful  for  achieving  such  a  goal.  None  of  the  experts  answered  “useless”  to  this 
question.  

111 

 
 
 
Do you think that creating such monitoring set 
(index) would be useful for outreaching a wider 
audience?
0%

11%

33%

56%

Very useful

Rather useful

Not very useful

Useless

The mean expert ratings on all 8 dimensions included in the questionnaire as well as 
the  mean  overall  score  and  rank  of  the  32  indicators  included  in  the  survey  are 
below.
the 
presented 

table 

in 

112 

 
 
Indicator 
name / 
Dimensions 
from the 
survey 

Gross 
greenhouse 
gas emissions 
(tonnes per 
capita) 

Energy-
Related CO2 
Emissions per 
Capita 

Energy 
Consumption 
per Capita 

Terrestrial key 
biodiversity 
areas (KBAs) 
protected (%) 

Material 
footprint 
(tonnes per 

Table 7 Expert ratings, overall score and rank of the 32 indicators included in the survey. 

General 
Relevance  

Effecti
ve-
ness 

Policy 
relevance 

Early 
warning 
strength 

Short-term 
changes 
sensitivity 

Foresight 
assessment 
sensitivity  

Robustness 
to Data 
Manipulation 

Robustness to 
Subjective 
Bias 

Overall 
Score 

Overall 
Rank 

1.31 

1.55 

1.57 

1.81 

2.05 

1.84 

2.56 

1.83 

1.81 

Air quality 

1.44 

1.64 

1.62 

1.76 

2.19 

2.11 

2.39 

2.00 

1.89 

1.48 

1.73 

1.81 

1.81 

2.19 

2.05 

2.39 

1.83 

1.91 

1 

2 

3 

1.58 

1.77 

1.86 

1.95 

2.14 

2.26 

2.33 

1.83 

1.97 

4 

1.84 

2.00 

1.90 

2.52 

2.43 

2.58 

2.72 

2.00 

2.25 

1.72 

2.14 

2.14 

2.48 

2.81 

2.58 

2.78 

1.83 

2.31 

5 

6 

113 

 
Indicator 
name / 
Dimensions 
from the 
survey 

capita) 

Government 
expenditure in 
education (% 
of GDP) 

Pesticides use 
per area of 
cropland 
(kg/ha) 

Child mortality 
rate 

Grassland 
loss 

In-work-at-
risk-of-poverty 
rate % 
population 

Unemploymen
t rate % of 
labour force 

General 
Relevance  

Effecti
ve-
ness 

Policy 
relevance 

Early 
warning 
strength 

Short-term 
changes 
sensitivity 

Foresight 
assessment 
sensitivity  

Robustness 
to Data 
Manipulation 

Robustness to 
Subjective 
Bias 

Overall 
Score 

Overall 
Rank 

2.08 

2.05 

2.38 

2.43 

2.67 

2.47 

2.61 

1.89 

2.32 

7 

2.08 

1.95 

2.19 

2.29 

2.52 

2.84 

2.83 

2.00 

2.34 

2.12 

2.23 

2.10 

2.57 

3.14 

2.68 

2.06 

1.83 

2.34 

8 

9 

2.12 

2.36 

2.05 

2.38 

2.67 

2.63 

2.67 

1.89 

2.35 

10 

1.76 

2.36 

2.38 

2.38 

2.67 

2.84 

2.61 

2.11 

2.39 

11 

2.62 

2.32 

2.43 

2.43 

2.67 

2.53 

2.17 

2.00 

2.39 

12 

114 

 
Indicator 
name / 
Dimensions 
from the 
survey 

15-74 

Healthy life 
expectancy at 
birth (years) 

Employment 
rate % of 
population 20-
64 

Gender 
employment 
gap 

Gross 
expenditure 
on R&D (% of 
GDP) 

Gini 
coefficient of 
disposable 
income, after 
taxes and 
transfers 

General 
Relevance  

Effecti
ve-
ness 

Policy 
relevance 

Early 
warning 
strength 

Short-term 
changes 
sensitivity 

Foresight 
assessment 
sensitivity  

Robustness 
to Data 
Manipulation 

Robustness to 
Subjective 
Bias 

Overall 
Score 

Overall 
Rank 

1.84 

2.18 

2.19 

2.81 

3.29 

2.47 

2.22 

2.22 

2.40 

13 

2.40 

2.36 

2.52 

2.57 

2.81 

2.89 

2.06 

1.78 

2.42 

14 

1.88 

2.32 

2.33 

2.62 

3.10 

2.74 

2.39 

2.17 

2.44 

15 

2.24 

2.45 

2.43 

2.43 

3.05 

2.68 

2.56 

1.83 

2.46 

16 

1.88 

2.32 

2.33 

2.71 

3.14 

2.74 

2.78 

2.22 

2.52 

17 

115 

 
Indicator 
name / 
Dimensions 
from the 
survey 

Resource 
productivity 
(PPP$ per kg) 

Real Gross 
domestic 
product (GDP) 
per capita 

Energy 
Expenditure 
Volatility 

General 
government 
gross debt (% 
of GDP) 

Employment 
in technology 
and 
knowledge-
intensive 

Gender 
Equality Index 

General 
Relevance  

Effecti
ve-
ness 

Policy 
relevance 

Early 
warning 
strength 

Short-term 
changes 
sensitivity 

Foresight 
assessment 
sensitivity  

Robustness 
to Data 
Manipulation 

Robustness to 
Subjective 
Bias 

Overall 
Score 

Overall 
Rank 

2.16 

2.50 

2.76 

2.90 

2.95 

2.84 

2.78 

2.06 

2.62 

18 

2.50 

2.91 

3.00 

2.86 

2.68 

2.44 

1.94 

2.62 

19 

2.64 

2.73 

2.95 

2.71 

2.48 

3.05 

2.78 

2.22 

2.70 

20 

2.76 

2.82 

2.90 

2.86 

2.86 

2.83 

2.72 

1.83 

2.70 

21 

2.68 

2.77 

2.86 

2.71 

2.95 

2.89 

2.78 

2.00 

2.71 

22 

1.88 

2.36 

2.48 

2.76 

3.24 

3.00 

3.17 

2.83 

2.71 

23 

116 

 
 
Indicator 
name / 
Dimensions 
from the 
survey 

Employment-
to-population 
ratio gender 
gap 25+ (%) 

Human 
Development 
Index 

Homicide rate 
(per 100000 
inhabitants) 

Dependency 
ratio 

Self-reported 
health 

Life 
satisfaction 

Rule of law 
from the 
Worldbank 
Worldwide 
Governance 

General 
Relevance  

Effecti
ve-
ness 

Policy 
relevance 

Early 
warning 
strength 

Short-term 
changes 
sensitivity 

Foresight 
assessment 
sensitivity  

Robustness 
to Data 
Manipulation 

Robustness to 
Subjective 
Bias 

Overall 
Score 

Overall 
Rank 

2.64 

2.77 

2.71 

3.05 

3.10 

3.00 

2.44 

2.06 

2.72 

24 

2.16 

2.55 

2.67 

3.05 

3.43 

3.00 

3.22 

2.50 

2.82 

25 

2.80 

3.18 

3.00 

3.05 

3.19 

3.47 

2.28 

1.94 

2.86 

26 

2.60 

2.86 

3.00 

3.14 

3.19 

3.26 

2.67 

2.22 

2.87 

27 

2.20 

2.68 

2.67 

2.67 

3.14 

3.05 

3.33 

3.44 

2.90 

28 

2.20 

2.45 

2.76 

2.81 

3.38 

3.05 

3.50 

3.56 

2.96 

29 

2.32 

3.09 

3.10 

3.14 

3.48 

3.53 

3.50 

2.78 

3.12 

30 

117 

 
Indicator 
name / 
Dimensions 
from the 
survey 

Indicators 

The World 
Justice 
Project Rule 
of Law Index 

Freedom 
House's 
Freedom in 
the World 
Index 

General 
Relevance  

Effecti
ve-
ness 

Policy 
relevance 

Early 
warning 
strength 

Short-term 
changes 
sensitivity 

Foresight 
assessment 
sensitivity  

Robustness 
to Data 
Manipulation 

Robustness to 
Subjective 
Bias 

Overall 
Score 

Overall 
Rank 

2.52 

3.09 

3.14 

3.19 

3.52 

3.42 

3.39 

2.83 

3.14 

31 

2.58 

2.91 

3.19 

3.24 

3.33 

3.21 

3.50 

3.22 

3.15 

32 

118 

 
 
Survey Questionnaire  

Developing  an  integrated  assessment  methodology  for  a  ‘Beyond  GDP’  monitoring 
of the EU’s progress to the Sustainable Development Goals 

Tackling  the  wide  spectrum  of  geopolitical,  socio-economic,  energy  and  climate  security 
risks  requires  a  comprehensive  strategy  for  a  deep  transformation  of  the  European 
economy,  with  a  full  harmonisation  between  the  low-carbon  transition,  the  sustainable 
development goals and the need for continued improvement of living standards and human 
well-being.  Bridging 
the 
implementation of EU-wide sustainable transition strategy will be aided by the introduction 
of new evidence-based policy instruments to monitor member-states’ progress, options and 
possible actions. Based on an objective, comparative assessment, the EU would be able to 
further and deepen coordination of national policies across sectors and policy areas on the 
back of a long-term political, financial and social commitment. 

the  policy  ambition  gap  between 

the  development  and 

The Center for the Study of Democracy (CSD), a European public policy institute, has been 
commissioned  by  DG  Research  &  Innovation  to  design  an  integrated  approach  to 
assessing  the  well-being  of European  countries  resting on  a  multitude  of  dashboards  and 
indices  combining  different  indicators  on  socio-economic  development,  environmental 
protection  and  good  governance.  The  current  set  of  indicators  is  not  sufficiently  linked  to 
the monitoring of the implementation of the SDG goals, lacks coherence with existing long-
term  strategy  documents,  and  is  not  well-communicated  to  the  broader European  society. 
There  is  a  lack  of  clear,  measurable  and  time-bound  EU-wide  targets  to  report  on  for  all 
SDGs,  which  is  why  there  is  a  need  for  a  revised  set  of  concrete  measurable,  EU-wide, 
time-bound targets to bolster the EU’s ambition and to achieve the EU Agenda 2030.  

The  following  questionnaire  aims  to  assess  the  policy  relevance,  applicability,  coherence 
and  applicability  of  a  list  of  indicators  that  have  been  pre-selected  based  on  data 
availability,  geographical  coverage  and  statistical 
their  robustness  and 
explanatory  value  vis-a-vis  a  group  of  similar  indicators.  The  objective  of  the  survey  is  to 
further  narrow  down  the  list  of  metrics  to  produce  1)  an  ambitious  scenario  with  four-five 
indicators (including GDP) and 2) a baseline one with 12 existing and new indicators. The 
results  will  feed  into  the  process  of  updating  the  existing  Transition  Performance  Index 
(TPI) of the European Commission. 

testing  of 

Demographic questions: 

1.  

What country are you from? 

2.   What is your main area of expertise? 

3.   Which sector are you working in? 

●  Non-profit organization 
●  Government 
●  Academia 
●  Business 
●  Media 
●  Diplomatic body 
● 
●  Other (please, specify) 

International Organization 

119 

 
  
4.      How  long  have  you  been  studying  economic  and  sustainable  development 
issues? 

● 
● 
● 
● 

0-2 years 
2-5 years 
5-10 years 
More than 10 years 

You  will  see  a  list  of  indicators  and  you  will  be  asked  to  assess  them  along  different 
dimensions. Please provide an answer for each indicator. 

List of indicators (inserted in the questions below) 

Real Gross domestic product (GDP) per capita 
Energy Consumption per Capita 
Gross greenhouse gas emissions (tonnes per capita) 
Freedom House's Freedom in the World Index 
Unemployment rate % of labour force 15-74 
Employment rate % of population 20-64 
General government gross debt (% of GDP) 
Gini coefficient of disposable income, after taxes and transfers 
In-work-at-risk-of-poverty rate % population 
Gross expenditure on R&D (% of GDP) 
Gender employment gap 
Employment-to-population ratio gender gap 25+ (%) 
Government expenditure in education (% of GDP) 
Air quality 
Energy Expenditure Volatility 
Pesticides use per area of cropland (kg/ha) 
Material footprint (tonnes per capita) 
Resource productivity (PPP$ per kg) 
Energy-Related CO2 Emissions per Capita 
Homicide rate (per 100000 inhabitants) 
Healthy life expectancy at birth (years) 
Child mortality rate 
Human Development Index 
Rule of law from the World bank Worldwide Governance Indicators 
Terrestrial key biodiversity areas (KBAs) protected (%) 
Dependency ratio 
Employment in technology and knowledge-intensive 
Grassland loss 
The World Justice Project Rule of Law Index 
Gender Equality Index 
Life satisfaction 
Self-reported health 

1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
11 
12 
13 
14 
15 
16 
17 
18 
19 
20 
21 
22 
23 
24 
25 
26 
27 
28 
29 
30 
31 
32 

1.  How related is each indicator to existing policy objectives on sustainable 

development?  

1 - Very related 
2 - Rather related 

120 

 
 
 
 
3 - Somewhat related 
4 - Somewhat unrelated 
5- Irrelevant 

2.  How effective is each indicator in providing guidelines in monitoring, 

strategic policy making, and/or target setting?  

1 - Very effective 
2 - Rather effective 
3 - Somewhat effective 
4 - Somewhat ineffective 
5 – Useless 

3.  Do you agree that the indicator provides a good measurement of the gap 

between    the current situation and the future policy target in a specific 
area?  

1 - Completely agree 
2 - Rather agree 
3 - Somewhat agree 
4 - Rather disagree 
5 - Completely disagree 

4.  Do you agree that the indicator provides adequate early warning to guide 

policy action?  

1 - Completely agree 
2 - Rather agree 
3 - Somewhat agree 
4 - Rather disagree 
5 - Completely disagree 

5.  How likely is that the indicator will reveal short-term changes indicating 

policies have an effect?  

1 - Highly likely 
2 - Rather likely 
3 - Rather unlikely 
4 - Highly unlikely 
5 – Never 

6.  How effectively can the indicator be used for foresight assessment of 

trends?  
1 - Very effectively 
2 - Rather effectively 
3 - Somewhat effectively 
4 - Somewhat ineffectively 
5 - Useless  

7.  How robust is the indicator against data manipulation? 

1 - Very robust 
2 - Rather robust 
3 - Somewhat robust 
4 - Somewhat weak 
5 - Very weak 

8.  How robust is the indicator against inherent, subjective bias? 

1 - Very robust 
2 - Rather robust 

121 

 
 
 
 
 
 
 
3 - Somewhat robust 
4 - Somewhat weak 
5 - Very weak 

9.  Are there other indicators that you would rate highly, but were not included 

in the questions above? Please list up to five additional indicators.  

10.  Do you think that a monitoring set (index) based on a reduced number of 
indicators would be useful to the implementation of EU-wide sustainable 
transition strategy? 

1 - Very useful 
2 - Rather useful 
3 - Not very useful 
4 – Useless 

11.  Do you think that creating such monitoring set (index) would be useful for 

outreaching a wider audience?? 

1 - Very useful 
2 - Rather useful 
3 - Not very useful 
4 – Useless 

12.  Do you have any general comments or suggestions? 

122 

 
 
 
 
 
 
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− 

Bridging the policy ambition gap between the development 
and the implementation of EU-wide sustainable transition 
strategy could be aided by the introduction of new evidence-
based policy instruments to monitor member-states’ 
progress, options and possible actions. This report develops 
two alternative visions for a ‘Beyond GDP’ monitoring set 
of indicators to continuously assess the global progress to 
achieving the Sustainable Development Goals (SDGs). The 
two versions of the Index were piloted for the EU-27 
Member States with the results showing a moderate 
improvement of sustainable development indicators  
across Europe. 

Studies and reports