Composite sustainable development indicators
program of Île-de-France/Paris region
By Iuli NASCIMENTO - Île-de-France - Paris region
September 2007
Association Mondiale des Grandes Métropoles – Métropolis
Commission 5
The SD indicators program
Step 1: The indicators database has been structured and
made available to experts for consultation and validation
Step 2: An Environmental Memento has been published
Step 3: A set of eco-region indicators has been defined
Step 4: UNDP SD indicators (HDI, HPI & GEM) have been
tested at the regional level
Step 5: New options have been explored (ISS & BIP 40)
Step 6: A SD dashboard has been set-up (IQS & IQE)
Normalization: an international comparison
UNDP indices
HDI
HPI
GEM
UNGP and composite indicators
In the late 80s the UN proposed a vision of
human development which was not limited to
traditional monetary indicators like the GDP
New indicators were proposed like:
HDI: Human Development Indicator
HPI: Human Poverty Indicator
GEM: Gender Empowerment Measure
Human development dimensions
UNDP human development definition:
A development that allows people to enjoy long,
healthy and creative lives
This definition includes 3 dimensions:
Capacity to live a long and healthy life
Access to education and knowledge
Access to minimum material resources to reach a
decent living condition
How to build composite indicators?
The Human Development Indicator (HDI)
HDI takes into account 3 dimensions:
Population living level (GDP per capita)
Population education level (adult literacy and
combined primary, secondary and tertiary gross
enrolment)
Population health level (life expectancy)
To aggregate these indicators an international
normalization is done:
Each indicator has a value comprised between 0
and 1, corresponding to minimum and maximum
predefined values
HDI is the arithmetic mean of these 3 indicators
HDI aggregation process
Human
development
dimensions
Selected
indicators
Min.
value
Max.
value
1- Capacity to live a
long and healthy life
Life expectancy at
birth
25
years
85
years
2- Access to
education and
knowledge
Adult literacy rate
(weight = 1/3)
0%
100%
Indicator value =
Adult literacy rate / 100
Gross enrolment
rate (weight = 2/3)
0%
100%
Indicator value =
Gross enrolment / 100
GDP per capita
(PPA)
100
US$
40,000
US$
3- Access to
minimum material
resources to reach a
decent living
condition
Sub-indicator value
determination
Indicator value
determination
(between 0 and 1)
Life expectancy indicator
=
(Life expectancy – 25) /
(85 – 25)
0 % = min. value
100% = max. value
Education indicator =
(2/3 * Adult literacy
indicator) + (1/3 * Gross
enrolment indicator)
GDP indicator =
[log (GDP per capita) –
log (100)] / [log (40.000)
– log (100)]
HDI = (Life expectancy indicator + Education indicator + GDP indicator) / 3
HDI by district
Indice santé
0,940
0,932
0,922
0,918
0,930
0,917
0,907
0,897
0,902
0,910
Indice instruction
0,993
0,987
0,987
0,993
0,940
0,957
0,968
0,965
0,965
0,939
Indice niveau de vie
1,000
1,000
1,000
0,930
0,955
0,939
0,932
0,929
0,906
0,923
Indice de Développement Humain - 2003
1,000
0,980
0,960
0,940
0,920
0,900
0,880
0,860
0,840
0,820
is e
ne
'O
Va
l
-d
ar
M
et
e
Sa
e
in
Se
Se
in
l- d
in
t- D
eM
ar
en
is
ne
es
e
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nn
el
so
ei
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Yv
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au
ts
-
de
-S
Pa
r is
0,800
H
Paris
Hauts-de-Seine
Île-de-France
Essonne
Yvelines
Val-de-Marne
France métropolitaine
Seine Saint-Denis
Seine et Marne
Val-d'Oise
IDH
0,978
0,973
0,970
0,947
0,942
0,938
0,936
0,930
0,924
0,924
HDI by country
1 Luxembourg
Île-de-France
2 Irlande
3 Norvège
4 Etats-Unis
5 Danemark
6 Islande
7 Canada
8 Suisse
9 Autriche
10 Australie
11 Pays-Bas
12 Belgique
13 Japon
14 Allemagne
15 France
16 Finlande
Indice de
PIB
1,000
1,000
0,990
0,990
0,990
0,960
0,959
0,956
0,955
0,953
0,950
0,948
0,942
0,940
0,939
0,939
0,938
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Hong-Kong - Chine
Royaume-Uni
Italie
Suède
Singapour
Nouvelle-Zélande
Emirats arabes unis
Espagne
Nord-Pas-de-Calais
Israël
Grèce
Qatar
Brunei Darussalam
Slovénie
Chypre
Portugal
Corée Sud
Indice de
PIB
0,936
0,935
0,935
0,933
0,918
0,905
0,903
0,903
0,900
0,885
0,884
0,883
0,878
0,877
0,874
0,868
0,866
HDI and GDP
Region Île-de-France HDI
Region Île-de-France has one of the highest HDI
worldwide
One of the reasons to explain this high HDI is the
high GDP per capita
The hight GDP per capita is mirroring the high
concentration of corporate HQs and of companies
in region Île-de-France + the presence of the largest
and most famous French universities
However, this result should be considered with care
since HDI calculations are based on international
statistics which do not necessarily apply well at the
regional level
HDI-2
A second HDI, called HDI-2, has been
computed to raise the statistics limitations
mentioned previously
The HDI-2 is made of the same categories as
the HDI, however:
It is based on data that is more relevant at the
regional level (and available up to town-level)
The mininum and maximum values have been
redefined to reflect the minimum and maximum
values found in Île-de-France
HDI-2 computation
Health: life expectancy at birth
Health indicator = (Life expectancy – 65) / (85 – 65)
Education: % of population more than 15 years old and
olding a degree
Knowledge indicator = (% of pop. > 15 olding a
degree – 50) / (100 – 50)
Living level: median taxable income (US$ PPA)
Living level indicator = (log(median taxable income)
– log(100)) / (log(40,000) - log(100))
HDI-2 = (Life expectancy indicator + Education indicator + Living level indicator) / 3
Region Île-de-France HDI-2
ID H -2
1,000
F o r m u le c a lc u l a t o ir e d e l'in d ic e :
( i n d i c e s a n t é + i n d i c e é d u0,900
c a tio n + in d ic e n iv e a u d e v ie ) / 3
0,800
ID H -2
4
5
6
7
8
0
0
0
0
0
0
0
0
0
0
,8
,7
,7
,7
,7
,7
,7
,7
,6
,6
0
9
8
7
5
5
2
1
7
2
4
9
3
1
3
0
3
6
2
3
0,700
0,600
0,500
0,400
0,300
0,200
0,100
0,000
D eux com m unes :
L a C o u rn e u v e
N e u illy
0 ,4 8 8
0 ,8 6 5
au
P
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La t-D
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ou
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eu
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N
eu
illy
2
3
P a r is
H a u ts - d e - S e in e
Y v e lin e s
Essonne
Île -d e -F r a n c e
V a l- d e - M a r n e
V a l- d 'O is e
S e in e e t M a r n e
F r a n c e m é t r o p o lit a in e
S e in e S a in t - D e n is
H
1
Region Île-de-France HDI-2
Paris
Hauts-de-Seine
Yvelines
Essonne
Île-de-France
Val-de-Marne
France métropolitaine
Val-d'Oise
Seine et Marne
Seine Saint-Denis
Indice santé
Indice éduc.
diplôme
Indice revenu
IDH-2
0,763
0,758
0,703
0,733
0,733
0,740
0,685
0,720
0,678
0,680
0,772
0,758
0,762
0,738
0,716
0,708
0,646
0,678
0,688
0,570
0,878
0,880
0,886
0,842
0,812
0,803
0,684
0,772
0,782
0,621
0,804
0,799
0,783
0,771
0,753
0,750
0,672
0,723
0,716
0,624
0,900
0,800
0,700
0,600
0,500
0,400
0,300
0,200
0,100
Indice santé
Indice éduc. diplôme
M
ar
ne
Sa
in
t-D
en
is
et
Se
in
e
Va
l-d
'O
ise
Se
in
e
Va
l-d
eM
ar
ne
0,000
Es
so
nn
e
0,488
0,865
ei
ne
Yv
el
in
es
0,376
0,995
de
-S
0,408
0,840
Pa
ris
0,680
0,760
Ha
ut
s-
Deux communes :
La Courneuve
Neuilly
Indice revenu
IDH-2
The HDI-2 is more representative of regional social disparities than the HDI
The HDI-2 in 1999
(normalized between 0 and 1)
IDH–2 sampled between 0 et 1
(minimum and maximum values)
Human Poverty Indicator (HPI and IPH-2)
The Human Poverty Indicator (HPI - and HPI-2 for
developed countries-) is an indication of the level of
poverty amongst a social group
HPI is not only an economical indicator: it also reflects
inequalities of access to health services, employment and
education
HPI is based on:
A monetary poverty indicator
The probability at birth to die before the age of 60
The illiteracy rate amongst adults aged 16 to 65
The long-term unemployment rate
HPI-2 computation
Cubic mean
Health and life expectancy: probability at birth to
die before the age of 60 (P1)
Knowledge and education: illiteracy rate amongst
adults aged 16 to 65 (P2)
Living level: monetary poverty rate (P3)
Labor and social exclusion: long term
unemployment rate (P4)
IPH-2 = 1/4 (P13+P23+P33+P43)1/3
HPI-2 by district
HPI-2 by district
Difficulties encountered:
Illiteracy data not available at district level
Use of an amplification coefficient for long-term
unemployment: highly debatable
Partial conclusions:
Human poverty is rather evenly distributed, except in
Seine-Saint-Denis district (higher than everywhere
else)
There is a big difference between the average living
level and the poverty level, especially in Paris (with
questions as regards the reliability of some data DEFM1)
Gender Empowerment Measure
The Gender Empowerment Measure (GEM)
tries to measure participation to the political
and economical life
GEM is not computed for France (apparently
because of some incompatibility between the
French and the international statistical
classification systems)
GEM computation
Dimensions de parité
Hommes-Femmes
Indicateurs retenus
Participation et pouvoir
décisionnaire dans la
sphère politique
Participation et pouvoir
décisionnaire dans le
domaine économique
Pourcentage des femmes (resp. des hommes) dans les
chambres parlementaires nationales (Sénat et Assemblée
nationale en France)
Pourcentage des femmes (resp. des hommes) occupant des
fonctions de représentation parlementaire, de direction et
d'encadrement supérieur (catégorie 1 de la CITP-88)
Pourcentage de femmes (resp. des hommes) occupant des
postes d’encadrement et fonctions techniques (catégories 2
et 3 de la CITP-88)
Pourcentage du revenu estimé (par tête) du travail des
femmes (resp. de celui des hommes)
Maîtrise des ressources
économiques
Exemple :
valeur
Norvège
38,2%
PEER1
30,0%
PEER2
50,0%
0,75
PEER3
Indice de Participation des Femmes (IPF) = (PEER 1 + PEER 2 + PEER 3)/3
Data used to compute GEM
Participation of women in the economic life
The weight hence given to the GDP in the GEM
could be discussed
This data is hard to collect for region Île-de-France
(lack of details in labor studies)
Data estimation based on Yearly Declaration of
Social Data (DADS)
GEM by country
IPF
IPF
1 Norvège
0,928
14 Nouvelle-Zélande
0,769
2 Danemark
0,860
15 Espagne
0,745
3 Suède
0,852
16 Irlande
0,724
17 Bahamas
0,719
Île-de-France
0,849
4 Islande
0,834
18 Royaume-Uni
0,716
5 Finlande
0,833
19 France (2001)*
0,686
6 Belgique
0,828
20 Argentine
0,665
7 Australie
0,826
21 Portugal
0,656
8 Pays-Bas
0,814
22 Israël
0,622
9 Allemagne
0,813
23 Costa Rica
0,606
10 Canada
0,807
24 Grèce
0,594
11 Suisse
0,795
25 Italie
0,589
12 Etats-Unis
0,793
26 Japon
0,534
13 Autriche
0,779
Nord-PDC (2001)*
0,492
Indice de participation des Femmes (IPF) dans quelques pays développés et en ÎleÎle-dede-France
(2003)
Sources : PNUD 2005, *Gadrey et ali. 2006, + notre estimation pour Île-de-France
- Women's participation in the political life for region Île-de-France is
above national average
- Women's participation in the economic life is decent
Conclusion on UNDP indicators use in
region Île-de-France
Results vary enormously:
The indicators appear to be well-adapted to the
international level: this is less true for the regional level
Some data is missing at the sub-regional level
The indicators lack discrimination power at the
regional level; this is particularily true for the HDI
It is very difficult to compare UNDP indicators at a
national level and at a regional level
2 suggestions for further R&D work:
Try to normalize HDI-2 so that it may used up to townlevel
Try to normalize ISS and BIP40 so that we can get time
series
Thank you for your attention!