The Gender Statistics Database (GSD) of the European Institute for Gender Equality (EIGE) contains data on the numbers of women and men in key decision-making (WMID) positions across a number of different life domains. Data may cover international, European, national, regional and local levels and currently include 38 European countries. The GSD aims to provide reliable statistics that can be used to monitor the current situation and trends over time.
The domains covered include politics, public administration, judiciary, business and finance, social partners and NGOs, environment, media, science and research and sports. The decision-making positions covered are specific to each area.
A decision-making position is a position from which it is possible to take or influence a decision:
The business and finance domain includes statistics on women and men in highest decision-making positions of largest quoted companies, European financial institutions, and national central banks. Data on largest listed companies cover the decision-making positions of the highest ranked nationally registered constituents (max. 50) of the blue-chip index of the national stock exchange in each country.
The largest publicly listed companies in each country.
Publicly listed means that the shares of the company are traded on the stock exchange. The "largest" companies are taken to be the members (max.50) of the primary blue-chip index, which is an index maintained by the stock exchange and covers the largest companies by market capitalisation and/or market trades. Only companies which are registered in the country concerned (according to the ISIN code) are counted. Therefore, the number of companies covered by the data (which is shown in the data table published in the GSD) may be lower than the number of constituents in the relevant blue-chip index.
|b||break in time series||c||confidential|
|d||definition differs, see metadata||e||estimated|
|s||Eurostat estimate||u||low reliability|
|x||dropped due to insufficient sample size (n<20)||y||unreliable due to small sample size (n<50)|