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Methodology 

    The Gender Equality Index (GEI) is a composite indicator that measures how far a society is from achieving full equality between women and men.

    The aim of this indicator is to reflect the reality of gender equality in important aspects of people's welfare and development.

    Idescat produces the GEI for Catalonia in accordance with the methodology established by the European Institute for Gender Equality (EIGE). In 2025, EIGE updated both the methodology and the list of indicators, with the aim of better capturing, assessing and reflecting reality. It calculated the index values for the EU and the European countries for 2025 and 2020. Comparability with the series calculated using the 2017 methodology is not possible and, therefore, there is a break in series.

    The Index is based on 27 indicators, hierarchically structured into 6 domains, which are in turn divided into 13 subdomains. The results provided are of 4 types:

    1. The Gender Equality Index (highest level of aggregation).
    2. The index for each of the 6 domains of analysis: work, money, knowledge, time, power and health.
    3. The index for each of the 13 subdomains into which the 6 domains above are divided.
    4. A total of 27 basic indicators, which are the basis for calculating the levels above.

    The results of the Gender Equality Index and its components (domains and subdomains) are presented on a dimensionless scale ranging from 0 to 100, where 0 means total inequality and 100 means total equality.

    The results of the 27 constituent indicators are shown for the total population, disaggregated by gender, and by the absolute difference between women and men. Each indicator has its own metric.

    Data for 2025, the first year under the new methodology, are being released. To allow retrospective comparability with the EU countries, Idescat has calculated the values for 2020, the same year that EIGE has calculated retrospectively. In addition, to assess Catalonia's short-term trend, Idescat has calculated the values for 2024, although this year is not available for Spain or the EU.

    1. Definitions

    Work

    Domain that measures the conditions under which women and men can benefit from equality in access to employment and in working conditions. It encompasses 2 subdomains:

    • Participation. Subdomain that measures the degree of participation of women and men in the labour market. It combines 2 indicators:

      1. Full-time equivalent employment rate. Percentage of the employed population in full-time equivalent terms. The employed population aged 16 to 89 is considered. Full-time equivalent jobs are defined as the total number of hours worked divided by the annual average number of hours worked in full-time jobs.
      2. Duration of working life. Number of years that a generation is expected to be active under the activity and mortality conditions of the reference year.

    • Segregation and quality of work. Subdomain that measures the level of gender segregation in employment, managerial positions and low-paid work. It combines 3 indicators:

      1. Employed population in ICT. Percentage of employment in this economic sector. The employed population aged 16 to 74 is considered.
      2. Managers. Percentage of women and men in managerial positions. Employed population aged 16 to 74 in major group 1 of the ISCO.
      3. Low paid workers. Percentage of the employed population earning two thirds of the national median employee income or less. It includes gross employee cash or near-cash income, gross non-cash employee income and employers' contributions to Social Security.
    Money

    Domain that measures gender inequalities in access to financial resources and in the economic situation. It encompasses 2 subdomains:

    • Financial resources. Subdomain that measures the earnings and the gender pension gap. It combines 2 indicators:

      1. Median annual earnings. Median of the annual earnings of the employed population aged 18 to 64, calculated as the median of employees' gross cash or near-cash earnings, employees' gross non-cash earnings and cash profits from self-employment. The results are expressed in purchasing power standards to make the information comparable across countries.
      2. Gender pension gap. The gender pension gap is the difference between the average gross pension received by men and the average gross pension received by women, expressed as a percentage of men's average pension. It excludes zero pensions; that is, it is calculated for people with at least one positive gross income value in the pension income variables (old-age benefits, survivors' benefits and regular pensions from individual private plans). It shows the percentage by which women's average pension income is higher or lower than men's.

    • Economic situation. Subdomain measures the median partner earnings ratio and in-work poverty. It combines 2 indicators:

      1. Median partner earnings ratio. The median ratio of annual earnings is expressed as a percentage of a partner's earnings for women and men in couples who are in employment and of working age. Earnings are calculated as the median of employees' gross cash or near-cash earnings, employees' gross non-cash earnings and cash benefits from self-employment. The population aged 18 to 64 is considered.
      2. In-work poverty of adults in single or single-parent households. The in-work-at-risk-of-poverty rate is the percentage of employed people who are at risk of poverty, meaning that their disposable household income (after social transfers) is below 60% of the national median equivalised disposable income.
    Knowledge

    Domain that measures gender inequalities in educational attainment and in segregation by field of study. It encompasses 2 subdomains:

    • Attainment and participation. Subdomain that measures the educational attainment of women and men. It combines 2 indicators:

      1. Graduates of tertiary education. Percentage of the population aged 30 to 34 who have successfully completed tertiary education, corresponding to levels 5–8 of the ISCED.
      2. Graduates in VET (Initial vocational education and training). Percentage of the population aged 25 to 34 who have successfully completed initial vocational education and training as their highest level of education attained, corresponding to levels 3 or 4 of the ISCED.

    • Segregation. Subdomain that measures the thematic bias of the tertiary studies completed, by gender. It combines 2 indicators:

      1. Graduated in tertiary education in EHW (Education, Health and Welfare, Humanities and Art). Percentage of graduates in fields F01 (education), F02 (arts and humanities) and F09 (health and welfare) at levels 5–8 out of total graduates, according to ISCED.
      2. Graduated in tertiary education in STEM (Science, Technology, Engineering and Mathematics). Percentage of graduates in fields F05 (natural sciences, mathematics and statistics), F06 (information and communication technologies) and F07 (engineering, manufacturing and construction) at education levels 5–8 out of total graduates, according to ISCED.
    Time

    Domain that measures gender inequalities in unpaid care activities for people and in housework chores, as well as in time devoted to social activities. It encompasses 2 subdomains:

    • Care activities. Subdomain that measures the caring for people and the implication on household chores. It includes 3 indicators:

      1. Informal childcare. Percentage of the population that cares for their own children. Childcare includes personal care, help with schoolwork, management of children's activities and leisure, supervision and emotional support. For Catalonia, those considered are carers aged 30 to 50 (EIGE considers those aged 16 to 74) and minors (EIGE considers children aged 0 to 11).
      2. Informal long-term care. Percentage of carers aged 45 to 64 providing long-term care. Informal long-term care refers to the care or assistance provided to one or more people with limitations related to age, a chronic illness or an illness, at least once a week. For Catalonia, the frequency of care is not available, and "caring takers" are considered to be people aged over 75 and people with disabilities.
      3. People doing housework chores. Percentage of the population that does housework chores (cooking, cleaning, laundry) every day. The population aged 16 to 74 is considered.

    • Social activities. Subdomain that measures the participation in leisure activities and the time devoted to voluntary activities. It includes 2 indicators:

      1. People undertaking leisure activities. Percentage of the population that spends more than 8 hours per week on leisure activities (entertainment, culture, art and hobbies, among others), excluding sports. The population aged 10 and over is considered (EIGE considers those aged 16 to 74).
      2. People involved in voluntary, charitable or political activities. Percentage of the population that has taken part in voluntary, charitable or political activities in the last four weeks from the survey (EIGE considers "at least once per week"). The population aged 10 and over is considered (EIGE considers those aged 16 to 74).
    Power

    Domain that measures gender inequalities in the exercise of political representation and in the presence on the governing boards of the main economic and social bodies. It encompasses 3 subdomains:

    • Political power. Subdomain that measures the political representation, from government to the local level:

      1. Share of ministers. Percentage of female and male ministers in the Government of Catalonia.
      2. Share of members of parliament. Percentage of female and male members of the Parliament of Catalonia.
      3. Share of members of local assemblies. Percentage of female and male councillors on the Full Councils of local authorities.

    • Economic power. Subdomain that measures the participation in the management of the largest companies listed on the stock exchange. It includes 1 indicator:

      1. Share of members of boards in largest quoted companies.. Percentage of female and male directors on the governing boards of the largest companies listed on the stock exchange.

    • Social power. Subdomain that measures the participation in the management of sports federations. It includes 1 indicator:

      1. Share of members of highest decision-making body of sports organisations. Percentage of women and men on the governing boards of sports federations.
    Health

    Domain that measures gender inequalities in actual and self-perceived health status and in behaviour. It encompasses 2 subdomains:

    • Status. Subdomain that measures health, covering both actual and self-perceived health status. It includes 2 indicators:

      1. Self-perceived health, good or very good. Percentage of the population aged 16 and over assessing their health as good or very good.
      2. Healthy life years at 65. Healthy life years measure the number of remaining years that a person of a specific age is expected to live without severe or moderate health problems. Life expectancy at a given age is the average number of additional years that a person of that age can expect to live. It is calculated as a percentage of the total life expectancy of the age group of 65 years and over.

    • Behaviour. Subdomain that measures healthy habits among the population. It includes 2 indicators:

      1. People who don't smoke and are not involved in harmful drinking. Percentage of the population aged 16 and over who neither smoke nor drink harmfully.
      2. People who are physically active and/or consume fruits and vegetables. Percentage of the population aged 16 and over who do intense physical exercise and/or consume a sufficient amount of fruit and vegetables.

    2. Calculation method

    The calculation of the Gender Equality Index follows a structured process consisting of the following main stages or steps: selection of indicators, processing of indicators, calculation of the gender gap metric, and aggregation to the levels of subdomain, domain and index.

    Step 1: selection of indicators

    Indicators are selected to configure the 6 main domains defined conceptually, on the basis of theoretical foundations and a review of the comparable statistical sources available at EU level. The current Index is made up of 27 individual-level outcome indicators. These are organised into 13 subdomains, which in turn are grouped into the 6 main domains of the Index.

    Step 2: processing of indicators

    Once selected, the indicators are standardised to ensure that they measure gender equality consistently. All indicators must be expressed in a positive direction; that is, higher values indicate greater gender equality and progress towards EU objectives or towards a desirable situation. For example, the variables measuring "participation in tertiary education" or "healthy life years" have a positive orientation, since it is desirable to increase educational attainment or to live a long and healthy life. By contrast, the variable measuring "in-work risk of poverty" carries a negative sign or interpretation; this means that, for the Index, the indicator must be inverted so that it measures the "absence of in-work risk of poverty".

    In addition, all indicators are expressed in relative terms, using the most appropriate reference population to allow comparability between populations of different sizes and structures. For example, the indicator measuring the share of members of parliaments was calculated as the percentage of women in parliaments relative to the population aged 18 and over (closest reference population).

    Step 3: calculation of the gender gap metric

    The Index measures gender gaps by comparing the relative positions of women and men symmetrically. A disadvantage for women (for example, lower earnings) is treated in the same way as a disadvantage for men (for example, a lower level of tertiary education). The gender gap is calculated as follows:

    Gender gap. If the number of women is less than or equal to the number of men, it is calculated by subtracting the number of women from the number of men and dividing the difference by the number of men. If the number of women is greater than the number of men, it is calculated by subtracting the number of men from the number of women and dividing the difference by the number of women.

    An equivalent formulation is the following:

    Gender gap. It is calculated by subtracting from one the ratio of the smaller to the larger of the two values: the number of women and the number of men. In other words, the smaller value is divided by the larger value, and the result is subtracted from one.

    The resulting values lie between 0 and 1, where 0 represents total equality and 1 represents total inequality. To make them easier to interpret, the values are inverted by calculating their complement, so that 1 represents total equality and 0 represents total inequality.

    Step 4: aggregation to the levels of subdomain, domain and index

    In the last stage, the gender gaps are aggregated according to the structure of the Index. Within each subdomain, the arithmetic average of the gaps is calculated with equal weights, thus obtaining a score for the subdomain. The subdomains are then aggregated to the domain level using the geometric average, also with equal weights. Finally, the scores of the 6 domains are aggregated to form the overall Gender Equality Index using a weighted geometric mean.

    The domain weights were obtained through an online survey conducted in the last quarter of 2024, which gathered responses from 125 EIGE stakeholders. The weights were derived using the analytical hierarchy process, a structured method based on expert judgement. The experts compared the importance of each domain with that of the others, taking them in pairs (for example: "Is work more important than health and, if so, to what extent?"). These comparisons were organised in a matrix and processed to obtain a coherent set of weights. In this way, the final weights are guaranteed to reflect expert knowledge and policy priorities:

    Work 0,16
    Money 0,18
    Knowledge 0,13
    Time 0,19
    Power 0,18
    Health 0,16

    The Gender Equality Index takes values between 0 and 100, where 100 represents full gender equality and 0 total gender inequality. It is formulated as follows:

    Formula for calculating index I. The index is obtained by multiplying six factors, one for each dimension, numbered from one to six. Each factor is calculated by multiplying, for each category j, the sum of the quotients of the indicator G with subscripts i, j, k and the value n with subscripts i, j, for all values of k from one to n with subscript i. This sum is raised to the power of one divided by m with subscript i. Finally, each factor is raised to the corresponding weight w with subscript i.

    where:

    I gender equality index;

    Gijk gender gap for indicator k in subdomain j of domain i;

    nij number of indicators in subdomain j of domain i;

    mi number of subdomains in domain i;

    wi expert weight for domain i;

    k = 1, ..., 27;

    j = 1, ..., 13;

    i = 1, ..., 6.

    Quality of the indicators

    For each of the 27 constituent indicators, different aspects of quality have been assessed. First, the level of harmonisation with the original indicator of the European Institute for Gender Equality with regard to the concept measured (2=equivalent, 1=approximation), second, the source used (2=same source, 1=different source) and, third, the comparability and availability of time data (2=complete, 1=break in series and/or partial data).

    Quality of the indicators
    No. Indicator Concept measured Source Series available Score
    1 Full-time equivalent employment rate 2 2 2 6
    2 Duration of working life 2 2 2 6
    3 Employed population in ICT 2 2 2 6
    4 Managers 2 2 2 6
    5 Low paid workers 2 2 2 6
    6 Median annual earnings 2 2 2 6
    7 Gender pension gap 2 2 2 6
    8 Median partner earnings ratio 2 2 2 6
    9 In-work poverty of adults in single or single-parent households 2 2 2 6
    10 Graduates of tertiary education 2 2 2 6
    11 Graduates in VET (Initial vocational education and training graduates) 2 2 2 6
    12 Graduated in tertiary education in EHW (Education, Health and Welfare, Humanities and Art) 2 2 2 6
    13 Graduates in tertiary education in STEM (Science, Technology, Engineering and Mathematics) 2 2 2 6
    14 Informal childcare 1 2 1 4
    15 Informal long-term care 1 2 2 5
    16 People doing housework chores 2 2 2 6
    17 People undertaking leisure activities 1 2 1 4
    18 People involved in voluntary, charitable or political activities at least once per week 1 2 1 4
    19 Share of ministers 2 2 2 6
    20 Share of members of parliament 2 2 2 6
    21 Share of members of local assemblies 2 2 2 6
    22 Share of members of boards in largest quoted companies 2 2 2 6
    23 Share of members of highest decision-making body of sports organisations 1 1 2 4
    24 Self-perceived health, good or very good 2 2 2 6
    25 Healthy life years at 65 2 2 2 6
    26 People who don't smoke and are not involved in harmful drinking 1 2 1 4
    27 People who are physically active and/or consume fruits and vegetables 1 2 2 5

    4. Non-current data

    The data for Catalonia for the years 2005, 2010, 2012, 2015 and 2017–2022 follows the 2017 EIGE methodology, which was updated in 2025. These data are not comparable with the current data.

    According to the EIGE 2017 methodology, the Index is based on 31 indicators, structured in a hierarchical manner in 6 domains, which are then divided into 14 sub-domains. The results offered are of 4 types:

    1. The Gender Equality Index (maximum aggregation level).
    2. The index for each of the 6 domains of the analysis: work, money, knowledge, time, power and health.
    3. The index for each of the 14 sub-domains in which the 6 aforementioned domains are broken down.
    4. A total of 31 basic indicators, which are the basis for calculating the aforementioned levels.

    The results of the Gender Equality Index and its component parts (domains and sub-domains) are presented on a dimensionless scale, in an interval that goes from 1 to 100, where 1 means total inequality and 100 means total equality.

    The results of the 31 basic indicators are shown by the total population, disaggregated by gender, and by the absolute difference between women and men. Each indicator has its own metric.

    The results of the indices for Catalonia are disseminated for the years 2005, 2010, 2012, 2015 and annually since 2017, in accordance with the periodicity used by the European Institute for Gender Equality to disseminate the results of the European Union and its member states.

    The results of the IGG for 2019 have been published in March 2022 and the statistical series available since 2005 have been revised with the incorporation of new sources or improvements in the definition of the following indicators: share in regional assemblies, share in the management of the main companies listed on the stock market, share of board members of research funding organisations and share of members of highest decision making body of the national Olympic sport organisations. With regard to EU data, the statistical information available since 2010 has been replaced with the new composition of the EU after Brexit (EU-27), as reflected in the EIGE with the data published for that period.

    4.1. Definitions

    Work

    Domain that measures the conditions under which women and men may benefit equal access to employment and good working conditions. It encompasses 2 sub-domains:

    • Participation. Sub-domain that combines 2 indicators to measure the degree of participation of women and men in the labour market.

      1. Full-time equivalent employment rate. Percentage of the population in full-time equivalent employment. From 2021, employed population from 16 to 89 years is considered (before 2021 population aged 16 years and over was considered). Full-time equivalent jobs are defined as the total number of hours worked divided by the mean annual hours worked in full time jobs.
      2. Duration of working life. Number of years that a generation expects to be active in the conditions of activity and mortality of the baseline year.

    • Segregation and quality of work. Sub-domain that combines 3 indicators: the level of segregation per gender of the occupation, the flexibility of working patterns to achieve work-life balance, and career prospects.

      1. Employed people in education, human health and social work activities. Percentage of employment in these sectors (divisions 85-88 of the CCAE-2009) with respect to the employed population from 16 to 89 years (before 2021 population aged 16 years and over was considered).
      2. Ability to take one hour or two off during working hours to take care of personal or family matters: Percentage of the population in employment that state they can leave their workplace for at least one hour for family or personal reasons, without having to request special leave.
      3. Career Prospects Index. Likelihood of promotion within the company or organisation, measured on a scale of 0 to 100.
    Money

    Domain that measures the gender inequalities in access to financial resources and in the economic situation. It encompasses 2 sub-domains:

    • Financial resources. Sub-domain that combines 2 indicators: pay and income. The results are expressed in terms of purchasing power parity to make the information comparable among the different countries.

      1. Mean monthly earnings. Mean net monthly income in purchasing power parity of employed and similar people employed in the sectors of industry, construction and services, in companies with 10 or more workers. (sections B-S, except for O, from the CCAE-2009)
      2. Mean equivalised net income. Net equivalent mean annual income (or by consumption unit) in purchasing power parity of the population aged 16 years or over. Includes pensions, investments, benefits and any other source of income, as well as earnings from remunerated work, and from this are deducted taxes, social insurance contributions and transfers made between households. To better compare the income of the different types of households, the concept of the consumption unit is used internationally. Each household's number of consumption units is calculated using the amended OECD's equivalence scale, which converts the number of members resident in a household into the number of consumption units, and imputs a weighting of 1 to the first adult, 0.5 to the rest of the adults and 0.3 to minors under the age of 14. The income per consumption unit is obtained by dividing the total net income of the household by the number of consumption units.

    • Economic situation. Sub-domain that combines 2 indicators: the risk of poverty and the distribution of women and men's income.

      1. Not at-risk-of-poverty. People with an income equal to or greater than 60% of the mean average of the net income per consumption unit of the population aged 16 years or over.
      2. Income distribution S20/S80. Ratio between the total income received by the 20% of the population with the lowest incomes (the 20th quintile) and the 20% of the population with the highest incomes (80th quintile). This is the inverse version of the indicator S80/S20.
    Knowledge

    Domain that measures gender inequalities in access to higher education and continuous training, and segregation according to field of study. It encompasses 2 sub-domains:

    • Attainment and participation. Sub-domain that combines 2 indicators of studies completed and studies in progress of women and men.

      1. Graduates of tertiary education. Percentage of the population with a higher education diploma or degree (categories 5, 6, 7 and 8 of the CCE-2019). From 2021, population from 15 to 89 years is considered (before 2021 population aged 16 years and over was considered).
      2. People participating in formal or non-formal education. Percentage of the population who participate in formal or informal educational activities. From 2021, population from 15 to 74 years is considered (before 2021 population aged 15 years and over was considered).

    • Segregation. Sub-domains that includes a thematic bias indicator according to the gender of the higher studies chosen.

      1. Tertiary students in education, health and welfare, humanities and arts. Percentage of students in those sectors of study (sectors 01, 02 and 09 of the CCE-2019), in relation to the total of higher education students.
    Time

    Domain that measures gender inequalities in non-remunerated work caring for people and domestic tasks, as well as dedication to social activities. It encompasses 2 sub-domains:

    • Care activities. Sub-domain that includes an indicator on the care of people and another indicator on housework.

      1. People caring for and educating their children or grandchildren, elderly or people with disabilities. Percentage of the population who habitually care for infants, grandchildren, the elderly or people with some form of disability without remuneration. From 2021, population from 18 to 74 years is considered (before 2021 population aged 18 years and over was considered).
      2. People doing cooking and/or housework. Percentage of the population who habitually do cooking and housework, without receiving remuneration. From 2021, population from 18 to 74 years is considered (before 2021 population aged 18 years and over was considered).

    • Social activities. Sub-domain that includes an indicator of participation in leisure activities and another indicator of dedication to voluntary activities.

      1. Workers doing sporting, cultural or leisure activities outside of their home. Percentage of workers that play sport, engage in cultural or leisure activities outside the home, every day or several times a month.
      2. Workers involved in voluntary or charitable activities. Percentage of workers involved in voluntary or charitable activities, at least once a month.
    Power

    Domain that measures gender inequalities in the exercise of political representation and presence in governing boards of the main economic and social bodies. It encompasses 3 sub-domains:

    • Political power. Sub-domain that includes 3 indicators of political representation, from the national to the regional government level.

      1. Share of ministers. Percentage of female and male ministers in the Government of Catalonia.
      2. Share of members of parliament. Percentage of female and male members of the Catalan Parliament.
      3. Share of members of regional assemblies. Percentage of female and male members of local councils.

    • Economic power. Sub-domain that includes indicators of participation in the management of the main companies listed on the stock market and public financial bodies.

      1. Share of members of boards in largest quoted companies. Percentage of male and female directors of boards of the leading listed companies.
      2. Share of board members of central bank. Percentage of women and men on the Board of Governors of the Catalan Institute of Finances.

    • Social power. Sub-domain that includes indicators of the share in the management of research-funding bodies, public communications media and the main sports federations.

      1. Share of board members of research funding organisations. Percentage of women and men in the governing bodies of the main research-funding institutions.
      2. Share of board members of publicly owned broadcasting organisations. Percentage of women and men on the Board of Governors of the Catalan Corporation of Audio-Visual Media.
      3. Share of members of highest decision making body of sporting federations. Percentage of women and men on the governing boards of sporting federations.
    Health

    Domain that measures gender inequalities in the real or perceived state of health, behaviour and access to healthcare. It encompasses 3 sub-domains:

    • Status. Sub-domain that includes 3 health indicators, both real and perceived.

      1. Self-perceived health, good or very good. Percentage of the population aged 16 or over who perceive their state of health to be good or very good.
      2. Life expectancy at birth. Number of years of healthy life expectancy at birth.
      3. Healthy life years at birth. Number of years of healthy life expectancy at birth.

    • Behaviour. Sub-domain that includes indicators of the population's healthy life habits.

      1. People who don't smoke and are not involved in harmful drinking. Percentage of the population aged 16 or over who neither smoke nor drink in a harmful manner.
      2. People doing physical activities and/or consuming fruits and vegetables. Percentage of the population aged 16 or over who do intense physical exercise and/or consume a sufficient amount of fruit and vegetables.

    • Access. Sub-domain that includes indicators of healthcare coverage.

      1. Population without unmet needs for medical examination. Percentage of the population aged 16 or over who report that they have received medical attention when they needed it.
      2. Population without unmet needs for dental examination. Percentage of the population aged 16 or over who report that they have received dental attention when they needed it.

    4.2. Calculation method

    The gender equality index is constructed in an ascending manner by the aggregation of 31 basic indicators. Each of these indicators is converted into a measure of equality, which is constructed on the basis of the gender gap of the indicator, weighted by a level factor. The aggregation procedures consecutively obtain the 14 sub-domains, the 6 domains and, finally, the gender equality index.

    4.2.1. Metric to define gender equality by indicator

    For each of the 31 indicators, the Gender Gap (GG) is calculated from the ratio between the value of women and the total value of the basic indicator "i" in question with regard to the year "t" (Xit), converted into a scale from 0 to 1.

    The Gender Gap is equal to 1 minus the absolute value of the women's indicator quotient and the total value of the basic indicator "i" for each year "t", minus 1.

    The gender equality Measure (M) for each basic indicator (Xit) is obtained from the Gender Gap (GG) , which is corrected by means of a level factor and is converted into a scale that goes from the value 1 to the value 100.

    The gender equality measurement for the basic indicator "i" for each year "t" is equal to 1 plus the product of the factor level for each basis indicator and the Gender Gap for each basic indicator, multiplied by 99.

    The Correcting Coeficient is applied to take into account the degree of achievement in an indicator,

    The factor level for each basic indicator is equal to the quotient between the value of the indicator and a reference value established by the European Institute for Gender Equality, raised to 0.5.

    where Xref. is a reference value that the European Institute for Gender Equality has established as the maximum value achieved for a variable X in any of the 28 countries of the European Union and in any of the years 2005, 2010, 2012 and 2015. This level factor is not applied to the indicators of the Power domain nor to the indicators care and housework of the Time domain.

    4.2.2. Aggregation method

    The process of aggregation that leads to the calculation of the gender equality index is conducted in a stepwise manner in ascending order from the basic indicators to the gender equality index.

    The synthetic indices for the 14 sub-domains (S) are obtained by calculating the simple arithmetic mean of the gender equality measure (M) of each basic indicator (Xit):

    The synthetic indices for the sub-domains "S" is equal to the simple arithmetic mean of the gender equality metric "M", calculated by the sum of "i" equal to 1 up to the number of indicators included in each sub-domain of the gender equality metric "M" of each basic indicator, divided by the number of indicators included in each sub-domain.

    where:

    nj is the number of indicators included in each sub-domain

    Sjt is the synthetic index for each sub-domain and year

    The synthetic indices for the 6 domains (D) are obtained by calculating the geometric mean of the corresponding sub-domains (S):

    The synthetic indices for the 6 domains "D" are equal to the geometric mean of the sub-domains "S", calculated as the nth root (number of sub-domains included in each domain) of the product of the synthetic indicator of each sub-domain.

    where:

    nk is the number of sub-domains included in each domain

    Dkt is the synthetic indicator for each domain and moment of time

    The Gender Equality Index (GEI) is obtained by calculating the weighted product of the synthetic indices of the 6 domains (D):

    The Gender Equality Index is equal to the weighted product of the synthetic indices of each domain.

    4.2.3. Weighting

    The weights applied have been calculated by the European Institute for Gender Equality by applying the hierarchical analysis methodology. The weights of each of the domains are as follows:

    Weights according to domains
    Work 0.19
    Money 0.15
    Knowledge 0.22
    Time 0.15
    Power 0.19
    Health 0.10

    4.2.4. Imputation of missing values

    The calculation of the Gender Equality Index requires that all 31 indicators are available in full for each of the reference years. If the indicator is not available, it has been imputed the time value closest to the available series and is indicated with the symbol of estimated data (and) of the tabulation.

    4.3. Quality of the indicators

    For each of the 31 indicators, different quality aspects have been assessed. Firstly, the level of harmonisation with the original indicator of the European Institute for Gender Equality with regard to the item measured (2 equivalent, 1 approximation), the source used (2 same source, 1 different source), the comparability and availability of the temporal data (2 full, 1 series break and/or partial data).

    Quality of the indicators
    No. Indicator Item measured Source Available serie Score
    1 Full-time equivalent employment rate 2 2 2 6
    2 Duration of working life 2 2 2 6
    3 Employed people in education, human health and social work activities 2 2 2 6
    4 Ability to take one hour or two off during working hours to take care of personal or family matters 2 2 1 5
    5 Career Prospects Index 2 2 1 5
    6 Mean monthly earnings 2 2 1 5
    7 Mean equivalised net income 2 2 2 6
    8 Not at-risk-of-poverty 2 2 2 6
    9 Income distribution S20/S80 2 2 2 6
    10 Graduates of tertiary education 2 2 2 6
    11 People participating in formal or non-formal education 2 2 2 6
    12 Tertiary students in education, health and welfare, humanities and arts 2 1 1 4
    13 People caring for and educating their children or grandchildren, elderly or people with disabilities 1 1 1 3
    14 People doing cooking and/or housework 1 1 1 3
    15 Workers doing sporting, cultural or leisure activities outside of their home 1 1 1 3
    16 Workers involved in voluntary or charitable activities 2 1 1 4
    17 Share of ministers 2 2 2 6
    18 Share of members of parliament 2 2 2 6
    19 Share of members of regional assemblies 2 2 2 6
    20 Share of members of boards in largest quoted companies 2 2 2 6
    21 Share of board members of central bank 1 2 2 5
    22 Share of board members of research funding organisations 2 2 2 6
    23 Share of board members of publically owned broadcasting organisations 2 2 2 6
    24 Share of members of highest decision making body of the national Olympic sport organisations 1 2 2 5
    25 Self-perceived health, good or very good 2 2 2 6
    26 Life expectancy at birth 2 2 2 6
    27 Healthy life years at birth 2 1 2 5
    28 People who don't smoke and are not involved in harmful drinking 2 1 2 5
    29 People doing physical activities and/or consuming fruits and vegetables 1 1 1 3
    30 Population without unmet needs for medical examination 2 2 2 6
    31 Population without unmet needs for dental examination 2 2 2 6