Gender Equality Index intersectionalities index__index_intersect

Time format:

Years

Unit:

Various (see name of selected indicator) (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 of the Gender Equality Index score.

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

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 the year the Gender Equality Index was published, rather than the year data was available. For example, the 2023 Gender Equality Index was mostly based on data from 2021 as this was often the latest data available at the time the index was calculated. In the Index area of EIGE's database, data for each of the indicators used is always reported under the Index year rather than the actual year that the data refer to.

A table detailing the specific data used to calculate each edition of the Gender Equality Index is available from the link below. It lists each of the indicators used under each domain/sub-domain of the index, the reference year of the data used, and details of any exceptions (e.g. when a different year is used for certain countries or when there is a break in the time-series).

List of indicators used in the Gender Equality Index

Whilst the indicators used to calculate the Index always cover the whole of the relevant population, the combination (or intersection) of gender and other characteristics can confer additional disadvantages and greater gender gaps. For each of the indicators used in the Index for which some additional breakdown is possible, this view presents data on the available intersectionalities such as family type, age group, level of education, country of birth, and disability. The link below provides access to detailed tables of metadata about the indicators and the breakdowns used for each Index edition.

Metadata about the indicators used to measure intersecting inequalities

indic

geo

×

Indicator

Select all	Code	Label
	work_fte	FTE employment rate (%, 15+ population)
	work_empl_ehs	Employed people in education, human health and social work activities (%, 15+ employed)
	work_flex	Ability to take an hour or two off during working hours to take care of personal or family matters (%,15+ workers)
	work_career	Career Prospects Index (points, 0-100)
	money_earn	Mean monthly earnings (PPS, working population)
	money_inc	Mean equivalised net income (PPS, 16+ population)
	money_arop	At-risk-of-poverty rate (%, 16+ population)
	money_incdist	Income distribution S20/S80 (16+ population)
	know_tert	Graduates of tertiary education (%, 15+ population)
	know_life	People participating in formal or non-formal education and training (15+ population)
	time_care	People caring for and educating their children or grandchildren, elderly or people with disabilities, every day (%, 18+ population)
	time_domestic	People doing cooking and/or housework, every day (%, 18+ population)
	time_leisure	Workers doing sporting, cultural or leisure activities outside of their home, at least daily or several times a week (%, 15+ workers)
	time_volunt	Workers involved in voluntary or charitable activities, at least once a month (%, 15+ workers)
	health_stat	Self-perceived health, good or very good (%, 16+ population)
	health_med	People with unmet needs for dental examination (%, 16+ population)
	health_dent	Population with unmet needs for medical examination (%, 16+ population)
	health_smoke	Population who don't smoke (%, 15+ population)
	health_phys	Population doing physical activities (%, 15+ population)
	health_fruit	Population consuming fruits and vegetables (%, 15+ population)
	health_drink	Population not involved in harmful drinking (%, 15+ population)

CloseUpdate

×

Geographic region

Select all	Code	Label
	AT	Austria
	BE	Belgium
	BG	Bulgaria
	CY	Cyprus
	CZ	Czechia
	DE	Germany
	DK	Denmark
	EE	Estonia
	EL	Greece
	ES	Spain
	EU27_2020	European Union - 27 countries (from 2020)
	FI	Finland
	FR	France
	HR	Croatia
	HU	Hungary
	IE	Ireland
	IT	Italy
	LT	Lithuania
	LU	Luxembourg
	LV	Latvia
	MT	Malta
	NL	Netherlands
	PL	Poland
	PT	Portugal
	RO	Romania
	SE	Sweden
	SI	Slovenia
	SK	Slovakia

CloseUpdate

time2024202320222021202020192017

sexWomenMen

intersectSingleLone parentCouple without childrenCouple with children15/16/18-2425-4950-6425-3435-4445-6465-7465+75+Low educatedMedium educatedHigh educatedNative bornForeign bornEU-bornNon-EU-bornWith disabilityWithout disability

AT

BE

BG

CY

CZ

DE

DK

EE

EL

ES

EU27_2020

FI

FR

HR

HU

IE

IT

LT

LU

LV

MT

NL

PL

PT

RO

SE

SI

SK

indic geo	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
AT	51	31	33	66	1969	23893	11	29	36	18	88	93	26	13	83	0	1
BE	60	42	26	68	2554	22930	11	29	50	9	87	88	32	7	86	2	4
BG	68	18	17	67	708	8225	21	12	41	2	93	92	11	1(i)	88	8	8
CY	64	26	14	52	1931	19344	10	24	50	9	92	88	3	13(i)	92	5	10
CZ	63	26	11	64	1120	12988	9	28	30	11	70	86	18	16	86	4	4
DE	47	33	14	67	1609	21199	12	24	26	7	83	93	22	21	79	5	4
DK	71	50	30	72	2961	24326	7	29	53	56	73	92	50	18	80	5	5
EE	61	26	15	69	1195	13496	17	15	48	18	92	90	37	12(i)	79	14	9
EL	50	27	6	54	1438	10773	22	13	32	2	85	96	5	9	93	10	14
ES	52	26	32	58	1776	16272	24	15	45	11	81	98	36	6	87	5	10
EU27_2020	59	32	22	63	1742	17605	16	20	36	12	85	91	25	13	83	6	8
FI	66	43	26	67	2479	22515	6	33	52	35	87	91	58	24	89	5	3
FR	66	37	18	65	2015	22261	11	27	45	24	88	87	26	12	80	6	8
HR	70	25	20	61	1094	8729	17	20	31	2	75	83	11	9	80	6	4
HU	58	30	13	67	912	8310	17	25	33	3	84	72	14	13	78	7	7
IE	50	37	32	67	2476	19740	12	23	50	7	92	93	41	15(i)	87	6	9
IT	48	27	22	52	1878	17048	20	18	21	7	81	96	17	15	86	7	12
LT	67	24	20	68	853	9950	18	17	52	7	90	97	12	4(i)	71	7	5
LU	56	29	20	71	2879	31587	18	23	49	16	87	93	34	10(i)	82	3	3
LV	69	25	27	67	1053	10356	14	17	49	8	85	95	17	7	71	14	17
MT	49	30	40	69	1698	17995	18	23	27	10	85	96	25	13(i)	91	1	3
NL	44	41	56	64	2120	21580	9	30	34	27	93	92	54	28	85	1	2
PL	69	26	16	63	1316	12034	15	18	43	6	90	91	14	5	81	13	10
PT	72	30	16	58	1431	12550	17	16	31	11	87	94	11	6	63	5	16
RO	63	19	19	69	619	4577	27	14	22	1	82	79	7	3	91	5	8
SE	73	45	41	74	2233	22803	9	32	52	14	93	82	63	33	84	11	7
SI	77	26	23	62	1791	15749	13	28	42	17	76	89	45	16(i)	82	0	1
SK	59	26	9	66	1032	10509	15	23	28	3	77	85	10	10	86	4	5

---