Labour statistics on women

Equal opportunity and equal treatment in the labour market are at the core of decent work. Unfortunately, women around the world still face additional hurdles to access employment, and once in employment, to access decision-making positions and jobs in certain sectors or of certain characteristics. This horizontal and vertical gender segregation of employment, combined with the unequal distribution of unpaid work (including household and childcare activities), results in differences in working conditions such as the gender pay gap and the over-representation of women in part-time jobs.

Gender equality is crucial to economic growth and sustainable development. It is recognized as a cross-cutting objective within the ILO’s Decent Work Agenda, and as a key goal within the 2030 Agenda for Sustainable Development. In fact, Goal 5 of the SDGs is devoted specifically to achieving gender equality and the empowerment of women and girls, but gender equality is also mainstreamed throughout the other sixteen goals.

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Gender data is critical for monitoring progress on gender equality and ensuring the successful implementation of the entire SDGs Agenda. ILOSTAT contains a wide range of indicators disaggregated by sex, as well as breakdowns relevant to gender issues and indicators on gender gaps. 

The statistical standards adopted by the 19th International Conference of Labour Statisticians (19th ICLS) in 2013 have significant implications for measuring women’s participation in all forms of work and for assessing differences in their access to full and productive employment, particularly in low-income contexts.  Learn more in the section Gender and the 19th ICLS.

New indicators show the gendered effects of marriage and child rearing on labour market outcomes

ILOSTAT presents a wide range of labour indicators allowing for the study of gender patterns in the labour market. However, until recently, these indicators focused on the individual, without any information on their family situation and its effect on their labour market outcomes. The ILO and UN-Women joined forces to surmount this limitation by producing labour indicators taking into account not only the characteristics of each individual, but also the characteristics of the household they live in. This novel database includes data on 84 countries (derived from labour force surveys or similar household surveys available in the ILO Harmonized Microdata Collection). It allows data users to explore how women’s and men’s labour force participation changes according to, for instance, whether they live alone, with a partner, with or without children, and the number and age of the children.

Gender and the 19th ICLS

Since the adoption of the standards at the 19th International Conference of Labour Statisticians, the ILO has engaged in an extensive programme of work to develop guidance and tools to support compilers and users of labour data on the implementation of the standards and the use of the data generated when they are applied. Below are key resources focused on the implications for gender data.

Lessons from the COVID-19 pandemic: Gender relevance of the 19th ICLS statistical standards

This brief gives a summary overview of the impact of the introduction of the 19th ICLS statistical standards on labour statistics, as compared with the previous standards from the 13th ICLS. The key gender differences between the frameworks are illustrated using data collected from pilot studies completed between 2015 and 2017.

Lessons from the COVID-19 pandemic: Closing gender data gaps in the world of work – role of the 19th ICLS standards

This report provides a detailed overview of the relevance of the 19th ICLS for gender analysis of participation in work and the labour market. It uses data from the pilot studies completed between 2015 and 2017 to illustrate the wide range of analytical potential when the new standards are implemented.

Measuring women's paid and unpaid work under ICLS 19

Why did the definitions of work and employment change and why is this change important for women? Find out in this policy brief.

Featured publication

This publication, drawing on a global dataset and new indicators developed by the ILO and UN Women, shows that women’s employment is shaped by domestic and caregiving responsibilities in ways that men’s is not.


Below is a subset of the indicators available by sex. For all available indicators, refer to the data page.

Partners for more and better data

In 2019, the ILO partnered with UN-Women to create a series of novel labour market indicators, key to gender analysis. The main innovation resulting from this project was the inclusion of a variable on the household type in ILOSTAT, revealing how people’s labour market outcomes change based on their family situation (whether they are single or not, whether they have children, the number and age of children, etc.).

Women’s Work and Employment Partnership

In 2014, the ILO partnered with the Food and Agriculture Organization and the World Bank under the Women’s Work and Employment Partnership, supported by Data2X, with the goal of addressing challenges in measuring work and employment to ensure that women are counted. The partnership supports research in two core areas: subsistence production and unpaid care work.


Exploring Light Time-Use approaches for measuring productive activities

Exploring Light Time-Use approaches for measuring productive activities

The ILO has launched efforts to develop guidance to promote accurate measurement of time use in different settings. A particular focus is the development of a data collection strategy centred on the attachment of a Time-Use module to the LFS. The successful design of such an approach offers many potential advantages given the topic overlap between the LFS and TUS, common target populations, high prevalence of LFS internationally, etc. An in-depth review of methods and country practises has been undertaken to inform the design of such a data collection strategy. This review has focussed in most depth on Light Time-Use Diary (LTUD) approaches to assess their suitability. This Brief highlights results, lessons learned and main challenges identified stemming from that review.

Indicator description: Household type

Indicator descriptions provide a concise overview of concepts and definitions, uses, sources and limitations.

Resolution concerning statistics of work, employment and labour underutilization

Adopted by the 19th ICLS (2013), this resolution sets standards for work statistics to guide countries in updating and integrating their existing statistical programmes in this field. It defines the statistical concept of work for reference purposes and provides operational concepts, definitions and guidelines for: (a) distinct subsets of work activities, referred to as forms of work; (b) related classifications of the population according to their labour force status and main form of work; (c) measures of labour underutilization.

Survey methods to improve measurement of paid and unpaid work: Country practices in time-use measurement

Survey methods to improve measurement of paid and unpaid work: Country practices in time-use measurement

This Review documents national practices in measuring productive activities through time-use methods. Covering the period between 2000 and 2016, it shows the extent of time-use data collection across countries around the world and highlights the main methods used in their implementation. The Review focuses in particular on modular time-use approaches that have been integrated with related household surveys, including Labour Force Surveys (LFS) and other socio-economic household surveys.

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Select a frequency to find monthly, quarterly, or annual indicators. While all indicators are available for annual periods, only a subset are available as monthly or quarterly. You can also filter the database or use the search feature to enter key words.

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Data available in the Excel summary files are for indicators only (not available for countries or regions) for selected classification items for 2010 onward for annual data and 2018 onward for short-term indicators. For historical data or additional classifications, either use the Data Explorer or download the CSV file. 

Download a zipped CSV file (gzip) to get data in bulk. These files contain only codes. Download the dictionary with labels here

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