EIGE

Gender Equality Index intersectionalities index_data__index_intersect

Time format:
Years
Unit:
Individual indicator values (comparable)
Description:

Developed at EIGE, The Gender Equality Index is a unique measurement tool that synthesises the complexity of gender equality as a multi-dimensional concept into a user-friendly and easily interpretable measure. It is formed by combining gender indicators, according to a conceptual framework, into a single summary measure.

The Index measures gender gaps that are adjusted to levels of achievement, ensuring that gender gaps cannot be regarded positively where they point to an adverse situation for both women and men. It assigns scores for Member States, between 1, total inequality and 100, full equality.

The Gender Equality Index consists of six core domains (work, money, knowledge, time, power and health) and two additional domains (intersecting inequalities and violence). Given the different nature of the latter two domains, only the core domains can be used in the computation the Gender Equality Index score.

The Index is computed as follows. First, achievement-adjusted gender gaps are computed for all constituent metrics. Next, these achievement-adjusted gaps for closely related metrics are combined to obtain sub-domain scores. Then, subdomain scores are combined to obtain domain scores. Finally, the domain scores are combined to obtain the overall Gender Equality Index score.

This indicator collates available intersectionalities for each indicator used to calculate the Index Scores. Intersectionalities span across family types, age groups, level of education, country of birth and disability. 

Note that in the Gender Statistics Database, the indicators used to calculate the Gender Equality Index, domain and sub-domain scores are reported according to data availability, rather than the year when the Index report was published. The table below presents an overview of the data used to compute the individual indicators in the Gender Equality Index, the reference year for each edition of the Gender Equality Index, and the availablity of data and exceptions. 

The table below shows: 

  • Domains and sub-domains: How indicators relate to domains and subdomains in the Gender Equality Index. 
  • Code, indicator and reference population: The codes used for each indicator, its reference population for each individual indicator in the Gender Equality Index.
  • Source: The sources used to compute each individual indicator in the Gender Equality Index. In case the individual indicator is computed based on survey data, the table shows which survey data is used. In case publicly available data from Eurostat is used, the table shows the unique dataset code used to identify the relevant Eurostat data.
  • Index edition: The availability of data for each individual indicator used to compute the Gender Equality Index and its exceptions, for each edition of the Gender Equality Index.
  • Note that the data on income only allows for calculations on family base. The figures for mean monthly earnings (money_earn), mean monthly income (money_inc), income distributions S20/S80 (money_incdist), and at-risk-of-poverty rate (money_arop) are therefore equal for men and women for couples with/without children.
  • Note that intersectionality data for people with and without disability, where available,  is always calculated based on EU-SILC instead of EU-LFS for all editions. 
Domain Sub-domain Code Indicator and reference population Source Index edition
          2017 2019 2020 2021 2022 2023
Work

 Participation in work  work_fte 2017-2022: Full-time equivalent employment rate (%, 15+ population)
2023: FTE employment rate (%, 15-89) 		Eurostat, EU LFS
Eurostat calculations according to EIGE's request  (2010-2015). EIGE's calculations 2017, 2018, 2019, 2020, 2021 		2015 2017 2018 2019 2020 2021, SK: 2020
Break in time series - new definition of family type (only 18 year old children)
Segregation and quality of work work_empl_ehs 2017-2022: Employed people in Education, Human Health and Social Work activities (%, 15+ employed)
2023: Employed people in education, human health and social work activities (%, 15-89) 		Eurostat, EU LFS, lfsa_egan2, lfsa_egana 2015 2017 2018 2019 2020 2021, SK: 2020
Break in time series - new definition of of family tyoe (Only 18 year old children)
Segregation and quality of work work_flex Ability to take an hour or two off during working hours to take care of personal or family matters (%, 15+ workers) Eurofound, EWCS
EIGE's calculation with microdata 		2015 2015 2015 2015 2015 2021
Segregation and quality of work work_career Career Prospects Index (points, 0-100) Eurofound, EWCS, Calculated by Eurofound 2015 2015 2015 2015 2015 2015
Money

 Financial resources money_earn Mean monthly earnings (PPS, working population) Eurostat, SES,
earn_ses10_20, earn_ses14_20, earn_ses18_20 		2014 2014 2018 2018
EL: 2014		 2020 2021
SK: 2020 - break in time series
Financial resources money_inc Mean equivalised net income (PPS, 16+ population) Eurostat, EU SILC, ilc_di03 2015 2017 2018 2019 2020 2021
SK: 2020 - LU: break in time series
Economic situation money_arop At-risk-of-poverty rate (%, 16+ population) Eurostat, EU SILC, ilc_li02 2015 2017 2018 2019 2020 2021
SK: 2020 - LU: break in time series
Economic situation money_incdist S20/S80 income quintile share (16+ population)  Eurostat, EU SILC
Eurostat calculations according to EIGE's request 		2015
IE: 2014		 2017 2018 2019 2020 2021
LU: Break in time series
Knowledge


 Attainment and participation know_tert 2017-2022: Graduates of tertiary education (%, 15+ population)
2023: Graduates of tertiary education (%, 15-89) 		Eurostat, EU LFS , Eurostat calculations according to EIGE's request  (2010-2015). EIGE's calculations 2017,2018 2015 2017 2018 2019 2020 2021, SK: 2020
Break in time series - new definition of family type (only 18 year old children)
Attainment and participation know_life People participating in formal or non-formal education and training (%, 15+ population) Eurostat, EU LFS, Eurostat calculations according to EIGE's request  (2010-2015). EIGE's calculations 2017, 2018 2015 2017 2018 2019 2020 2021
Break in time series - new definition of family type (only 18 year old children)
Time

 Care activities time_care People caring for and educating their children or grandchildren, elderly or people with disabilities, every day (%, 18+ population) 2017-2022: Eurofound, EQLS, EIGE's calculation with microdata
2023: EIGE's survey on unpaid care 		2016 2016 2016 2016 2016 2021
Break in time series
Care activities time_domestic People doing cooking and/or housework, every day (%, 18+ population) 2017-2022: Eurofound, EQLS, EIGE's calculation with microdata
2023: EIGE's survey on unpaid care 		2016 2016 2016 2016 2016 2021
Break in time series
Social activities time_leisure 2017-2022: Workers doing sporting, cultural or leisure activities outside of their home, at least daily or several times a week (%, 15+ workers)
2023: Workers doing sporting, cultural or leisure activities outside of their home, at least daily or several times a week (%, 18+ workers) 		2017-2022: Eurofound, EWCS, EIGE's calculation with microdata
2023: EIGE's survey on unpaid care 		2015 2015 2015 2015 2015 2021
Break in time series
Social activities time_volunt 2017-2022: Workers involved in voluntary or charitable activities, at least once a month (%, 15+ workers)
2023: Workers involved in voluntary or charitable activities, at least once a month (%, 18+ workers) 		2017-2022: Eurofound, EWCS, EIGE's calculation with microdata
2023: EIGE's survey on unpaid care 		2015 2015 2015 2015 2015 2021
Break in time series
Health

 Status health_stat Self-perceived health, good or very good (%, 16+ population) Eurostat, EU SILC, hlth_silc_01 2015 2017 2018 2019 2020
IT: 2019
DE, IE, FR, LU: break in time series 		2021
LU: break in time series
Access health_med Population with unmet needs for medical examination (%, 16+ population) Eurostat, EU SILC, hlth_silc_08 2015 2017 2018 2019 2020
IT: 2019		 2021
SK: 2020 - LU: Break in time series
Access health_dent People with unmet needs for dental examination (%, 16+ population) Eurostat, EU SILC, hlth_silc_09 2015 2017 2018 2019 2020
IT: 2019		 2021
SK: 2020 - LU: Break in time series
CY
IT
EL
PT
ES
HR
SI
EU27_2020
PL
CZ
NL
FR
AT
SK
BG
FI
DE
HU
IE
LV
BE
LT
EE
MT
RO
LU
DK
SE
work_fte
work_empl_ehs
work_flex
work_career
money_earn
money_inc
money_arop
money_incdist
know_tert
know_life
time_care
time_domestic
time_leisure
time_volunt
health_stat
health_med
health_dent
CY
72(d)
29(d)
(z)
52
2089(b)
21867
13
25
68(d)
12(d)
79(b)
91(b)
6(b)
5(i)
91
1
3
IT
51(d)
16(d)
(z)
52
1934(b)
18865
22
18
29(d)
9(d)
60(b)
76(b)
27(b)
13(b)
90
2
2
EL
61(d)
25(d)
(z)
54
1610(b)
11163
22
16
46(d)
4(d)
69(b)
75(b)
24(b)
11(b)
94
5
12
PT
88(d)
19(d)
(z)
58
1825(b)
15763
15
17
48(d)
18(d)
74(b)
87(b)
25(b)
9(b)
71
3
7
ES
67(d)
18(d)
(z)
58
1996(b)
18188
22
17
55(d)
17(d)
76(b)
73(b)
35(b)
11(b)
83
3
4
HR
79(d)
24(d)
(z)
61
1544(b)
13595
13
23
41(d)
8(d)
67(b)
90(b)
8(b)
4(b)
90
3
3
SI
84(d)
28(d)
(z)
62
2083(b)
19615
8
33
65(d)
26(d)
53(b)
75(b)
27(b)
12(i)
84
5
6
EU27_2020
65(d)
21(d)
(z)
63
2175(b)
21411
14
21
46(d)
12(d)
65(b)
72(b)
29(b)
12(b)
85
4
4
PL
71(d)
26(d)
(z)
63
1716(b)
17042
11
24
59(d)
7(d)
83(b)
82(b)
46(b)
10(b)
87
9
3
CZ
61(d)
25(d)
(z)
64
1456(b)
15745
7
32
39(d)
6(d)
73(b)
68(b)
23(b)
6(b)
89
1
2
NL
65(d)
23(d)
(z)
64
2706(b)
29870
8
28
57(d)
20(d)
79(b)
76(b)
39(b)
13(b)
84
1
1
FR
71(d)
20(d)
(z)
65
2358(b)
24969
11
22
53(d)
12(d)
57(b)
75(b)
28(b)
8(b)
81
6
9
AT
54(d)
18(d)
(z)
66
2226(b)
26593
13
25
43(d)
16(d)
80(b)
78(b)
26(b)
16(b)
85
0
1
SK
77(i)
27(i)
(z)
66
1001(i)
9401(i)
12(i)
32
47(i)
5(d)
72(b)
73(b)
29(b)
9(b)
84
7(i)
5(i)
BG
77(d)
17(d)
(z)
67
1246(b)
13376
17
13
48(d)
2(d)
73(b)
84(b)
23(b)
6(i)
90
3
3
FI
75(d)
18(d)
(z)
67
2710(b)
24662
6
30
53(d)
34(d)
70(b)
76(b)
34(b)
4(b)
85
3
9
DE
55(d)
22(d)
(z)
67
2514(b)
27981
12
22
35(d)
6(d)
45(b)
47(b)
23(b)
16(b)
83
1
1
HU
77(d)
26(d)
(z)
67
1145(b)
11326
9
25
42(d)
5(d)
54(b)
76(b)
24(b)
12(b)
83
5
2
IE
67(d)
26(d)
(z)
67
2461(b)
23294
9
28
66(d)
15(d)
62(b)
76(b)
9(b)
8(i)
89
3
2
LV
76(d)
28(d)
(z)
67
1656(b)
16940
11
18
61(d)
17(d)
74(b)
87(b)
17(b)
8(b)
73
7
8
BE
70(d)
27(d)
(z)
68
2960(b)
25777
9
32
59(d)
14(d)
63(b)
76(b)
28(b)
11(b)
86
3
5
LT
83(d)
20(d)
(z)
68
1973(b)
19330
10
19
66(d)
12(d)
66(b)
83(b)
15(b)
3(i)
77
3
2
EE
70(d)
26(d)
(z)
69
1723(b)
18831
12
22
58(d)
26(d)
31(b)
67(b)
23(b)
5(i)
83
12
3
MT
69(d)
23(d)
(z)
69
2078(b)
24088
15
17
46(d)
16(d)
51(b)
81(b)
14(b)
4(i)
89
1
0
RO
65(d)
17(d)
(z)
69
1717(b)
10697
20
14
31(d)
5(d)
79(b)
74(b)
25(b)
19(b)
95
3
5
LU
72(d)
25(d)
(z)
71
3698(b)
35695(b)
17(b)
22(b)
62(d)
14(d)
64(b)
82(b)
40(b)
6(i)
83(b)
2(b)
2(b)
DK
83(d)
9(d)
(z)
72
3756(b)
27675
5
34
62(d)
37(d)
37(b)
58(b)
32(b)
22(b)
77
11
9
SE
81(d)
32(d)
(z)
74
2465(b)
23110
12
28
60(d)
43(d)
66(b)
72(b)
29(b)
10(b)
80
5
3

Available flags:

b break in time series c confidential
d definition differs, see metadata e estimated
f forecast i see metadata
m imputed n not significant
p provisional r revised
s Eurostat estimate u low reliability
x dropped due to insufficient sample size y unreliable due to small sample size
z not applicable