European Institute for Gender Equality (EIGE)
European Institute for Gender Equality, Gedimino pr. 16, LT-01103 Vilnius, Lithuania
+370 5 215 7444
31/07/2024
The European Institute for Gender Equality (EIGE) Gender Statistics Database collects data on the numbers of women and men in key decision-making positions across a number of different life domains in order to provide reliable statistics that can be used to monitor the current situation and trends through time.
The domains covered include politics, public administration, judiciary, business and finance, social partners and NGOs, environment, media, science and research, sports, transport, COVID-19, and EU funding. The decision-making positions covered are specific to each area of decision-making and are described in detail in the section on statistical concepts and definitions.
Data on local/municipal councils cover the leaders and members of municipal councils or equivalent bodies (where relevant) in 38 countries.
The women and men in decision-making (WMID) data are organised into life domains and then by types of organisation and the different decision-making positions within the hierarchy of each organisational type. The domains covered are:
Details of the organisations and positions covered are provided in the section on statistical concepts and definitions.
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General definitions:
A decision-making position is a position from which it is possible to take or influence a decision:
Local/municipal councils
Organisations covered:
Positions covered:
Mapping tables:
Notes:
The statistical unit in WMID data is the organisational unit as defined by each specific topic (e.g. a house of parliament or a large listed company). Data are then collected on the numbers of men and women occupying decision-making positions within that unit.
Data cover all persons occupying specified positions in the organisational units covered (see statistical concepts and definitions).
The WMID data cover the 27 EU Member States, United Kingdom, six EU candidate countries (including Bosnia and Herzegovina, Montenegro, North Macedonia, Albania, Serbia, and Türkiye), one potential candidate (Kosovo(*)) and the remaining three EEA countries (Iceland, Liechtenstein and Norway).
(*) This designation is without prejudice to positions on status, and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo Declaration of Independence.
Notes:
Data were first collected in 2011 for 34 countries. The geographic coverage has expanded through time. For Montenegro, the time series starts in 2015 whilst for Albania, Bosnia and Herzegovina and Kosovo, it starts in 2019.
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Number of persons and percentages.
Data on local/municipal councils were collected on a biennial basis (every two years) up to 2019, generally between March and July.
Since 2020, data are collected on an annual basis.
No legal acts are applicable. The Council of the European Union has committed to ongoing monitoring of the implementation of the Beijing Platform for Action and as part of this commitment the European Commission has been collecting data on decision-making since 2003, a task that has been taken over by EIGE since 2017.
The WMID database was managed by the European Commission until end 2016 and then transferred to EIGE.
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Generally, data are disseminated within one month of the data collection (see section on reference period). Data are published on the EIGE Gender Statistics database.
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Data are disseminated to all types of users simultaneously via the EIGE Gender Statistics database.
Annually (since 2020); biennially - every two years - (2011-2019).
No regular news release.
From 2017, EIGE will publish regular bulletins on gender statistics, which may cover data on decision-making. The European Commission's Annual Report on Equality usually includes a section on this topic.
Micro-data are not made available.
WMID data are the primary source of information for indicators to monitor the implementation of Area G of the Beijing Platform for Action.
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WMID data are collected either directly from the organisations covered or from umbrella organisations providing data on behalf of member organisations. The majority of data are collected from the websites or other publications produced by the organisations concerned but some are also collected from direct contacts. There are three main risks in the data collection: ensuring the right decision-making bodies and positions are identified; ensuring that the gender of the people in these positions is correctly recorded; and ensuring that the information is up-to-date.
The data are collected by a team of experienced researchers and are subject to routine validation that includes:
WMID data need to be viewed bearing in mind the inherent diversity of institutional and organisational structures and in the scope of decision-making responsibilities for nominally similar positions. In this sense, there will always be some limitations to the extent to which data can be considered as fully comparable between countries. That being said, the data are considered to be of good quality, collected from reliable sources and with careful application of a common methodology. The data are comprehensive (cover all relevant organisations) and complete (data are available for all relevant positions in each organisation covered) in the majority of cases.
WMID data are the primary source of information for indicators to monitor the implementation of Area G (Power and decision-making) of the Beijing Platform for Action. The data are therefore widely used by the European Commission (DG JUST) and the European Institute for Gender Equality for analysis in this area and for reporting to the Council of the European Union.
The data are also widely used by researchers in this area.
No user satisfaction surveys are carried out.
The completeness of WMID data depends on the extent to which the organisations covered openly publish, or are willing to share, information about their key decision-making personnel. In general, there is increasing pressure on organisations of all types to be completely transparent about their organisational structure and operational practices so that completeness of the data has improved through time.
In the case of local/municipal councils, data are generally complete although there are some gaps:
In principle, the WMID data accurately describe the situation for the area of decision-making concerned, though in some areas the coverage of organisations is restricted to limit the cost and burden of the data collection, and this could potentially impact on overall accuracy.
In some cases, the only data available refer to the latest election results, thus might not reflect the actual composition of municipal councils and share of women among mayors at the time of data collection. In addition, within the same country data may refer to different dates (e.g. for the UK, often data for England refers to latest available election results, whilst for Scotland, Wales and Northern Ireland data refer to the situation as of date of collection). In some countries, local elections do not take place at the same time in all areas (e.g. Germany and Austria). Other cases include:
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Data are released within one month of collection.
Punctuality is 100%.
WMID data are considered comparable between countries but it is necessary to bear in mind the different institutional settings that exist and the fact that decision-making structures vary between organisations within countries as well as between countries. There are, therefore, inherent differences between countries in the way that decision-making is organised but the WMID methodology aims to allow for such variation so that the organisations and positions covered in each country are as comparable as possible.
There is heterogeneity of national systems of local governance. There are differences in the competences, power, financial resources, and average size of municipalities and other local authorities across European countries covered. The differences in size and number of municipalities results in heavy weighting of the EU-27 and all countries aggregates by few countries.
The lowest administrative units do not always correspond to the lowest level of self- government. In some cases (e.g. Portugal and Türkiye), there are two systems of local government in place depending on the size of the municipality, but only the larger level is taken into account because this is the administrative unit with real decision-making power.
In most cases, capital and/or large cities in European countries have a different status than smaller/middle sized cities and hold more competences. However, there is variation in how these are treated depending on the governance system.
In general, WMID data are comparable through time in each area of decision-making and the data accurately reflect the situation at the time according to the methodology. Nevertheless, it is necessary to bear in mind that the organisations covered and the decision-making structures within these may vary through time (e.g. government ministries may be reorganised following a change of government, and the constituents of the blue-chip indices used to define the sample of large listed companies are updated by the responsible stock exchange on a regular basis).
In the case of local/municipal councils, there are often changes in the number of local administrative divisions (and consequently to the number of local/municipal councils) due to mergers or divisions of municipalities, or reforms in the local governance system.
Changes in the number of municipalities in some countries (e.g. Spain, France, and Romania) are frequent and do not have a significant impact on the data. The changes outlined below are considered to have an impact on the comparability of data over time:
Other issues that affect the comparability of data over time are listed below:
It should be noted that the comparability of the EU-27 figure (data aggregated for the 27 EU Member States) over time will be affected by changes to data availability (see section 12.3 Completeness).
In general, there are few other sources of data on decision-making against which to assess the coherence of WMID data. Some national data exist for selected areas of decision-making but often the methodology is not the same (i.e. the coverage of organisations and/or positions within these varies) so that direct comparison is not possible.
The United Nations Economic Commission for Europe (UNECE) compiles data on the numbers of men and women in local councils in Europe from official national sources. Data are published in the UNECE Statistical Database, but only cover up to 2015.
UNECE also collects data on the number of elected women and men in local deliberative bodies, based on national official sources, which is published in the UN Women website Women in Local Government. Sometimes, UNECE data for local councils cover both the administrative level covered in the WMID data on regional assemblies and local/municipal councils. UNECE data are however not disaggregated by level (i.e. municipal and region). In addition, the overlap occurs only for certain countries, and in some cases not for all years (e.g. there are breaks in series). There is thus no direct coherence between the datasets.
UNECE data refer to elected women and may not reflect the current composition of local councils at the time. In addition, in some cases, data cover a different level of local government, either higher or lower level (instead or in addition to the local councils covered in WMID), which might explain differences with the WMID data. Moreover, the UNECE dataset does not include disaggregated data for mayors.
Internal coherence of the data (e.g. through time or across countries) is ensured through careful application of the WMID methodology, and routine validation of data.
Data are collected by a research team contracted by the European Institute for Gender Equality. There is no burden on Member States.
Due to the low frequency of data collection (biennial basis), data on local councils for previous years may be subject to revisions. This may include cases where results of elections of the reference year are made available after the data collection period, or if the statistical office has published relevant figures. In addition, data may be revised if a response to a request to verify the information collected for a particular organisation is received after the data collection has ended and the results were disseminated. If the information leads to a change in the data, then the update is made at the next available opportunity, usually at the latest within one month.
There is no fixed revision schedule. Any necessary revisions are made on an ad hoc basis.
The following revisions were made:
The WMID data are a form of administrative data, being derived from the records that organisations keep regarding the personnel occupying key positions within the organisation. In all areas of decision-making, the data cover all organisations within the scope defined by the methodology. In some areas (e.g. national level politics) all relevant organisations/bodies are covered (e.g. parliaments and governments) whilst in others the methodology restricts coverage so that the data effectively represent a sample of all organisations within the broad type of organisation (e.g. data on decision-making in large companies are restricted to the nationally registered constituents of the main blue-chip index for the country).
Annually (since 2020); biennially - every two years - (2011-2019).
Direct collection of data from official websites (local government, national statistical office, and election registers) and contact persons in relevant organisations.
See section on quality assurance.
Data collected from individual organisations are aggregated to the national level by position.
EU-27 figures are based on an aggregate of data at national level, with the percentages of men and women calculated from these aggregates. The shares of men and women observed at the EU level are therefore weighted averages rather than an average of the shares at country level.
Figures for IPA beneficiaries are based on an aggregate of data at national level for the six candidate countries (Bosnia and Herzegovina, Montenegro, North Macedonia, Albania, Serbia, and Türkiye) and one potential candidate (Kosovo).
Different aggregates can also be computed using the pre-defined table. For example, an “EU candidate countries” aggregate can be created by adding data for Bosnia and Herzegovina, Montenegro, North Macedonia, Albania, Serbia, and Türkiye for the relevant position.
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