Gender pay gap in unadjusted form (1994 - 2006) (earn_gr_hgpg)

Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Eurostat, the statistical office of the European Union


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes
Footnotes



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1. Contact Top
1.1. Contact organisation Eurostat, the statistical office of the European Union
1.2. Contact organisation unit Unit F2: Labour market
1.5. Contact mail address 2920 Luxembourg LUXEMBOURG


2. Metadata update Top
2.1. Metadata last certified 04/01/2010
2.2. Metadata last posted 04/01/2010
2.3. Metadata last update 04/01/2010


3. Statistical presentation Top
3.1. Data description

The gender pay gap is given as the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees. The gender pay gap is based on several data sources, including the European Community Household Panel (ECHP), the EU Survey on Income and Living Conditions (EU-SILC) and national sources.

3.2. Classification system

The data disseminated in this table have been compiled using the economic activity classification are classified by NACE Rev. 1.1.

For more information on NACE (Statistical Classification of Economic Activities in the European Community):

http://ec.europa.eu/eurostat/web/nace_rev2/introduction

3.3. Coverage - sector

Overall economy.

3.4. Statistical concepts and definitions

The gender pay gap in unadjusted form is given as the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees.

3.5. Statistical unit

The statistical unit is the employee.

3.6. Statistical population

The target population consists of all paid employees aged 16-64 who are 'at work 15+ hours per week'.

3.7. Reference area

Data are available for the EU Member States, Croatia, Norway and Switzerland.

3.8. Coverage - Time

Data are available for years 1994 to 2006 for most countries.

3.9. Base period

Not applicable.


4. Unit of measure Top

Percentages.


5. Reference Period Top

The reference years are 1994 to 2006 for most countries.


6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

EU-Member States participated in the European Community Household Panel on a gentlemen's agreement basis.

6.2. Institutional Mandate - data sharing

Not applicable.


7. Confidentiality Top
7.1. Confidentiality - policy

Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.

7.2. Confidentiality - data treatment

Not applicable.


8. Release policy Top
8.1. Release calendar

Not applicable.

8.2. Release calendar access

Nor applicable.

8.3. Release policy - user access

In line with the Community legal framework and the European Statistics Code of Practice Eurostat disseminates European statistics on Eurostat's website (see item 10 - 'Accessibility and clarity') respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. The detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users.


9. Frequency of dissemination Top

Annual.


10. Accessibility and clarity Top
10.1. Dissemination format - News release

Not applicable.

10.2. Dissemination format - Publications

Eurostat: The social situation in the European Union - 2005-2006

10.3. Dissemination format - online database

Please consult free data on-line or refer to contact details.

10.4. Dissemination format - microdata access

Not applicable.

10.5. Dissemination format - other
Internet address: http://ec.europa.eu/eurostat
10.6. Documentation on methodology

Documentation on the European Community Household Panel (ECHP) is available from the following web page:

http://circa.europa.eu/irc/dsis/echpanel/info/data/information.html

 

10.7. Quality management - documentation

See concept 3.4 above.


11. Quality management Top
11.1. Quality assurance

Not applicable.

11.2. Quality management - assessment

Not applicable.


12. Relevance Top
12.1. Relevance - User Needs

Not applicable.

12.2. Relevance - User Satisfaction

Not applicable.

12.3. Completeness

Not applicable.


13. Accuracy Top
13.1. Accuracy - overall

Not applicable.

13.2. Sampling error

Not applicable.

13.3. Non-sampling error

Not applicable.


14. Timeliness and punctuality Top
14.1. Timeliness

Not applicable.

14.2. Punctuality

Not applicable.


15. Coherence and comparability Top
15.1. Comparability - geographical

See also items 20.1 and 20.3 below.

Limited as the indicator is based on different national data sources.

15.2. Comparability - over time

See also items 20.1 and 20.3 below.

There are data gaps and methodological breaks in the data series.

15.3. Coherence - cross domain

Not applicable.

15.4. Coherence - internal

Not applicable.


16. Cost and Burden Top

Not applicable.


17. Data revision Top
17.1. Data revision - policy

Not applicable.

17.2. Data revision - practice

In order to improve this indicator, the methodology and source is currently under revision.


18. Statistical processing Top
18.1. Source data

Administrative data are used for Luxembourg and the annual labour force survey is used for France (up to 2002) and Malta. All other sources are national surveys except as follows:

2006 Statistics on Income and Living Conditions (EU-SILC) - IE, EL, ES, AT, PT and UK.

2004, 2005 Statistics on Income and Living Conditions (EU-SILC) - BE, IE, EL, ES, IT, AT, PT and UK.

2003 Statistics on Income and Living Conditions - IE,- EL and AT

2002 European Community Household Panel (ECHP) - EL

2001 and before: European Community Household Panel (ECHP) - BE, DK, DE, IE, EL, ES, IT, AT, PT, FI and UK.

18.2. Frequency of data collection

Annual.

18.3. Data collection

Belgium
Since 2004, data are based on EU-SILC. Data for 2002 and 2003 are not available.

Bulgaria
Gender Pay Gap is reported as the difference between gross hourly earnings of female employees and gross hourly earnings of male employees. Main data source is the Annual Enterprises' Survey on Labour (AES), which is a census type survey covering enterprises of all NACE sections and all size classes. The survey provides information on number of employees and gross earnings broken down by full-time/part-time, occupation and gender. Hours worked are available only for the total number of employees. For the years 2001-2003, the Structure of Earnings Survey (SES2002) results were used as additional information for obtaining the missing breakdown of hours worked by gender. For the years 2004-2006, Labour Costs Survey (LCS2004) in which specific questions on number of hours worked by gender were asked was used as supplementary source for the distribution of AES hours worked by sex.

Czech Republic
Figures are based on median earnings of employees working 30 or more planned hours per week, in enterprises with more than 9 employees. No data are available for 1994 and 1995. The greatest increase of the gender pay gap happened from 1997 to 1998. In these years, the national economy passed through a major depression. Reductions in earnings levels were documented in many groups of employees, especially in the public sector. Also, the earnings of clerks, teachers, shop assistants, etc. fell. The earnings levels of blue-collar workers were not affected as much. Women typically dominate the above-mentioned occupations and also the public sector. In the subsequent years, the situation recovered gradually. The discrepancy between earnings of men and women, in terms of the gender pay gap, had dramatically increased in 1998 (to 25 percentage points). After that, it returned close to the original level (22 percentage points) in 1999. From 2000, the economic situation has been stable and the discrepancy has slowly narrowed.

Denmark
Since 2002, the national structure of earnings survey is used, which covers employees aged 16-64 working 15 or more hours per week in economic activities NACE Rev.1.1 sections C-Q. The weights are based on the number of hours paid and bonuses are excluded. The effect of the change of source on the gender pay gap is estimated to be an increase of 4 percentage points, based on data from 2001. The reason for the change in the gender pay gap between 2001 and 2002 is that the data source was changed. A change in data source also occurred between 1994 and 1995 but it is not possible to explain how much this affected the increase of 4 percentage points over this period.

Germany
From 1994 to 2001 the gender pay gap was calculated using the European Community Household Panel (ECHP), which is based on converted data of the German Socio-Economic Panel (GSOEP) at the DIW (Deutsches Institut für Wirtschaftsforschung) in Berlin). The known possible drawbacks of household surveys are the rather small sample sizes for employees and the quality of measured earnings and hours worked. Hence from 2002, the gender pay gap is calculated using earnings surveys out of official statistics as far as possible. Since the coverage of earnings surveys in Germany is limited to industry and only a few economic activities out of the service sector, the GSOEP is used to complete the coverage. Three reasons for the differences in 2001 are (a) differences in results for hourly earnings of SES and GSOEP; (b) the ECHP sample was only a sub-sample of the full GSOEP; and (c) the weighting of results of Earnings Survey and GSOEP also uses Mikrozensus distributions, not only the sample distributions of GSOEP, ECHP or structure of earnings surveys. There are no explanations for the change between 1998 and 1999. However the change of source in 2002 is estimated to have increased the gender pay gap by 1 percentage point, from 21% to 22%.

Estonia
Since 2002, the national survey (covering NACE Rev.1.1. sections A, B, L-O) and the structure of earnings survey (covering sections C-K) have been combined.

Ireland
Since 2003 the figures are based on EU-SILC. Data for 2002 are not available.

Greece
Since 2003, data are based on EU-SILC. The difference between the results for 2001 and 2003 is attributed to the change in data source.

Spain
Since 2004 GPG figures are based on EU-SILC. For 2002 and 2003 the data are based on earnings data from tax returns and hours worked from the labour force survey. The effect of the change in source after 2001 is estimated to be +3 percentage points. The tax data are from the Agencia Tributaria, which is a census of employees based on the annual income tax returns made by the employers. The population is composed of all employers, enterprises, companies and entities (included the public sector) that pay wages and salaries, except private households with employed persons.  This source provides data classified by gender. All employees with any wage payment are included, irrespective of their working time during the year and the age of the employees. The units from Basque Country and Navarra are not included, but it is estimated that this does not have a significant effect on the gender pay gap figure. The decrease in the gender pay gap in 2003 is due to women's annual earnings increasing faster than men's annual earnings.

France
The annual labour force survey is used as the source for the gender pay gap for 1994 - 2002. Since 2003, the results are based on the quarterly LFS (Labour Force Survey). The effect of this change of source is an estimated reduction in the gender pay gap of 1 percentage point, following a comparison of data for 2002 from both sources.

Italy
Since 2004 data are based on EU-SILC. Data for 2003 are not available. Data for 2002 are available from the European SES 2002, giving a gender pay gap value of 21 per cent. However, this survey is limited in the coverage of economic activities (NACE sections C-K in the private sector) and the results are not comparable to the figures from the ECHP. In a comparison between the ECHP and SES data for 1995, the SES produced a gender pay gap figure which was 14 percentage points above the value from the ECHP.

Cyprus
The Gender Pay Gap is calculated on the basis of the average monthly rates of pay extracted from the annual survey of wages and salaries, since 1995. The survey covers all size groups (including the enterprises with 1-9 employees) and collects data for full-time employees in all economic activities of NACE Rev.1.1, including the government sector.

The specific survey is conducted on a yearly basis and has October as the reference period. Information is collected for the occupation, gender and the gross earnings and employer's social contribution paid for each employee in the enterprise.  An indication is also given concerning the age of the employee. No information is given concerning the educational status and the professional experience of the employees.

According to the specific survey, gross earnings refer to the total gross annual earnings (i.e. normal plus overtime earnings) for actual hours worked, including bonuses paid irregularly during the year.

Latvia
In 2004 the data source has been changed. Since 2004, data are based on hourly earnings of full and part time employees from the Quarterly Survey on Earnings and Employment. The survey covers all NACE sections and all size classes of enterprises.

Data for 1998-2003 are based on hourly earnings for employees in the main job from the Survey on Occupations in October of the respective year. This survey covers full-time and part-time employees who had worked full month in October and their wage or salary was not influenced by absence. 

Lithuania
The data for 2000-2006 are calculated on the basis on Quarterly Survey on Wages and Salaries; sole proprietorships are excluded. Only full-time employees are included for 1995 - 1999. Between 1995 and 1996 the minimum wage was increased significantly, which particularly affected women, as a significant proportion of women earned the minimum wage. The change in the gender pay gap between 1998 and 1999 occurred because women's earnings increased more than men's. This followed government increases in earnings for employees in the educational sector, where there is a significant proportion of female employees.

Luxembourg
Data are based on total gross earnings for March of each year, for all employees covered by the social security system, with no age or working time restrictions, including cross-border employees (from neighbouring countries), working in the Grand Duchy of Luxembourg. Officials/employees working for international institutions or bodies established in Luxembourg are excluded. Gross earnings are wages and salaries (including, as appropriate, bonus) before deduction of income tax and wage-related mandatory social security contributions.

Hungary
Figures for 2004 got revised. A significant decrease of the gender pay gap took place from 2002 to 2003 (from 16% to 12%), which can be explained by the fact that in the public sphere in September 2002 and in May 2003 there was a remarkable pay-rise by the government. As about 70% of the employees in this section are women, the GPG reduced. Only full-time employees in enterprises with more than 20 employees are included for 1995 - 1997. Since 1998, only full-time employees in enterprises with more than 5 employees are included.

Malta
Data are based on the results of the labour force survey. The GPG takes into account the gross annual basic salary received by employees, but excludes payments for overtime, allowances and bonuses. Between 2004 and 2006, means within classes were used for imputation methods based on occupational category, economic activity and type of employment.

Netherlands
Data are based on annual earnings including overtime pay and non-regular payments. The national structure of earnings survey is used.

Austria
Since 2003 figures are based on EU-SILC. No data for 2002 are available.

Poland
The source of data is the Structure of earnings survey (SES). For 1999, only full-time employees in enterprises with more than 5 employed persons are included. For 2001 onwards, only full-time employees in enterprises with more than 9 employed persons are included. For 2006, employees (full-time employees and part-time employees) in enterprises with more than 9 employed persons are included.

Portugal
Since 2004 the results are based on EU-SILC. The gender pay gap results for 2002 and 2003 have been calculated from a national sub-sample of the ECHP. The difference between the results for 2003 and 2004 is attributed to the change in data source.

Romania
The gender pay gap is expressed as ratio between average monthly gross earnings of women and average monthly gross earnings of men in October. Data source is the Annual survey in enterprises on earnings by occupation groups in October. The survey covers all NACE sections and all size classes. Data refers to employees (full-time and part-time) converted into FTEs.

Slovenia
Employees in public enterprises and employees in private enterprises with more than 2 employees are included.

Slovakia
In 2002 the sample was enlarged by 25 per cent and the response rate increased by 20 percentage points, leading to more accurate and representative results. Enlargement was undertaken particularly in economic activities C, E, I, J and L. These branches are characterized by a high labour price and a low proportion of women employed (e.g. 14 per cent in section C or 35 per cent in section I). A rise in the proportion of males (with higher average gross hourly earnings compared to females) in the sample caused an increase of 4 percentage points in the gender pay gap for 2002. The fall in the gender pay gap in 2003 was due to changes in Slovak law. In April 2002 the number of usual working hours stipulated by the Labour Code was changed from 42.5 hours to 40 hours. Moreover, in 2003, according to collective agreements in the public sector and in the state administration, the number of usual working hours for these sectors was decreased to 37.5 hours. This affected sections L, M and N in particular. About one fifth of the total employment relates to these branches, where there is a significant prevalence of females (e.g. 71 per cent in section L, 62 per cent in section M). The lower number of female working hours led to an increase in the average gross hourly earnings of females and consequently reduced the gender pay gap.

Finland
Since 2002 Data, the national structure of earnings data is used to calculate the GPG. Data covers almost all employees despite of their age and working time in all NACE sections. There are some coverage problems especially in micro enterprises and among general managers. Data for 2001 and earlier is based on European Community Household Panel. It is estimated that the structure of earnings data produces around 3 percentage points higher gender pay gap value than the value from the ECHP.

Sweden
Data are based on full-time equivalent monthly salaries, not hourly earnings, for employees aged 18-64. The figures exclude employees working less than 5 per cent of the full-time hours. The data source is the national structure of earnings survey.

United Kingdom
There is a break in series between 1996 and 1997. Until 1996, the European Community Household Panel (ECHP) was used for calculations. From 1997 onwards, the national panel, transformed into ECHP format, was used. From 2002, the national structure of earnings survey is used. An analysis of the data for 2001 indicated that the national structure of earnings survey produced a gender pay gap estimate which is +2 percentage points higher than the figure based on the national panel source.

Croatia
GPG data refer to average monthly paid off earnings by gender are based on regular annual survey on persons in employment and earnings. The survey took place for the first time in 2004 for the reference year 2003. It covers employees in legal entities of all types of ownership (private and public). Data on earnings are collected through a report filled in by the legal entities on the basis of records on earnings, which comprise gross and net earnings of employees who signed a work contract irrespective of the type of work contract and working time, providing that they worked all 12 months of the reference year. Payments of persons employed in crafts and trades and free lances as well as persons who conduct their activities at private family farms are excluded.

Average gross earnings comprise all kinds of net payments on the basis of permanent employment plus participations: contributions, taxes and surtaxes as prescribed by the law. Annual survey on persons in employment and earnings is the only possible source for calculating GPG for now.

GPG is calculated as a difference between average monthly gross earnings per employee of male and female employees as a percentage of average monthly gross earnings per employee of male employees. Data on GPG is calculated for all NACE activities - A to O. Data on average gross hourly earnings by gender is not available.

Norway
Data are based on full-time equivalent monthly salaries, not hourly earnings, using national statistics sources. NACE Rev.1.1 section H is included from 2001 on.

Switzerland
Conducted every two years in October since 1994, the Swiss Earnings Structure Survey (SESS) is based on a written questionnaire sent to companies. It provides representative data for all economic branches (except for agriculture), thereby enabling to describe the structure of salaries in Switzerland on a regular basis. The survey focuses not only on economic branches and company size, it also considers employee- and job-related characteristics such as education, professional position, years of service, level of qualifications required for the job and type of activity carried out within the company.

Amounts reported are converted into standardised gross monthly salaries. In other words, they are recalculated to produce an FTE based on a 40-hour workweek and 4 1/3 weeks a month.

Gross monthly salary for the month of October (incl. employee social security contributions, benefits in kind, regularly paid bonuses, share of turnover or commissions) covers hardship allowances for shift, night and Sunday work, 1/12 of 13th month salary and 1/12 of special annual payments. Family and child benefits are not included in the calculation.

The figures refer to the median.

18.4. Data validation

Not applicable.

18.5. Data compilation

EU-27 and other EU-aggregate estimates are population-weighted averages of the latest available national data, adjusted, where possible, to take into account a change in the data source. Countries without any previous gender pay gap data for a specific year are excluded from the EU-27 and EU-aggregate estimates. Where data have been provided by the National Statistical Offices based on national sources, the indicators for these countries cannot be considered to be fully comparable.

18.6. Adjustment

Not applicable.


19. Comment Top

a) In order to improve this indicator, its methodology had been revised in 2007 with a view to enhance quality and comparability (geographical and over time) of the unadjusted GPG. The old data series (1994-1996) had been frozen but are still kept online.

  

b) From reference year 2006 onwards, the new GPG figures are based on the methodology of the Structure of Earnings Survey (Reg.: 530/1999) carried out with a four-yearly periodicity. The unadjusted Gender Pay Gap (GPG) based on the new methodology represents the difference between average gross hourly earnings of male paid employees and of female paid employees as a percentage of average gross hourly earnings of male paid employees.

 

According to the new methodology the coverage is defined as follows:

- target population: all employees, there are no restrictions for age and hours worked.

- economic activity according to NACE Rev. 1.1.  Statistical Classification of Economic Activities in the European Community: only for the aggregate sections C_O (excluding L); and if available, also for sections C to O and aggregate C to K and C to O.

- size of enterprises: 10 employees or more.

 

The most recent available reference years in NACE Rev. 1.1. are 2002 and 2006 and Eurostat computed the GPG for these years on this basis. For the intermediate years (2007 onwards) countries provide to Eurostat estimates benchmarked on the SES results. Data is classified according to the NACE Rev. 1.1 classification and the only available breakdown is the economic activity (NACE) at section level. Available data cover the reference years 2002, 2006 and 2007.

 

As NACE Rev. 1.1 classification ran out for data collections referring to 2008 and onwards, these series are also frozen but are kept available at Eurostat's online database:

 

earn_gr_gpg - Gender pay gap in unadjusted form in % - NACE Rev. 1.1 (Structure of Earnings Survey: 2002 and 2006 onwards).

  

c) The GPG indicator applying NACE Rev.2 classification is available under:

earn_grgpgr2 - The Gender pay gap in unadjusted form in % - NACE Rev.2 (Structure of Earnings Survey: 2002 and 2006 onwards)

Data is classified according to the NACE Rev.2 classification from reference year 2008 onwards and data are broken down by economic activity (NACE section level), form of economic and financial control (public/private) of the enterprise and ten-years age classes of employees. Data according to NACE Rev. 2 are also available partially for the past years 2002, 2006, 2007.


Related metadata Top


Annexes Top


Footnotes Top