Gender statistics and indicators integrate a gender perspective in the collection, analysis and presentation of statistical data.

What are gender statistics and indicators?

This briefing introduces gender statistics and indicators and explains why they are important tools to promote gender equality and implement a gender mainstreaming approach. Put simply, gender statistics and indicators integrate a gender perspective in the collection, analysis and presentation of statistical data. Gender statistics play a key role in measuring gender gaps on the basis of agreed indicators that are relevant to the lives of women and men. In the EU, for example, they are used to identify gender gaps in education, the labour market, earnings and health, amongst other areas [1].

Gender statistics and indicators are an integral part of gender mainstreaming throughout the entire policy cycle. Firstly, they inform the policymaking process and ensure that interventions respond to the different needs and priorities of women and men. Secondly, they measure changes in the relations between women and men over time in a particular policy area, a specific programme or activity, or changes in the status or situation of women and men. Thirdly,they are an essential part of the monitoring and evaluation of the implementation and outcomes of policies, programmes and projects.

Overview of gender statistics

Gender statistics aim to ‘reflect differences and inequalities in the situation of women and men in all areas of life’ [2]. In providing evidence of gender equalities and gender gaps in key areas they help to make gender inequalities visible, which can in turn inform policymaking to address identified gender gaps. They help to identify data that is relevant to women’s and men’s lives and to key areas of policymaking.

The UN Statistical Divisions’ manual on gender statistics defines gender statistics as encompassing the following characteristics:

  • 'data are collected and presented disaggregated by sex as a primary and overall classification;
  • data reflect gender issues;
  • data are based on concepts and definitions that adequately reflect the diversity of women and men and capture all aspects of their lives; and
  • data collection methods take into account stereotypes and social and cultural factors that may induce gender biases’ [3].

It is important to distinguish between sex-disaggregated data and gender statistics. Sex-disaggregated data refers to collecting data and breaking it down separately for women and men. Gender statistics go further as they take into account wider gender inequalities and gender bias in data collection methods and tools [4]. In addition, gender statistics have the potential to reflect different groups of women and men, taking into consideration that ‘gender intersects with age, education, family composition and parenthood, country of birth and disability’ [5]. This means that gender statistics can reflect a deeper understanding of women’s situations and needs [6], and thereby supports the analysis of intersecting inequalities.

Overview of gender indicators

Gender indicators (sometimes referred to as statistical indicators) are the measure(s) upon which data is collected. In the EU, relevant gender indicators have been devised to show gender gaps in access to resources and opportunities in areas such as education, employment, decision making and gender-based violence. Indicators can be used to show relative positions or positive or negative change. They are also important to show progress over time, for example, changes in women’s participation in the labour market [7].

Gender indicators allow for meaningful comparison over at least one data dimension, such as country or time. More generally, a statistical indicator is defined as a ‘[d]ata element that represents statistical data for a specified time, place, and other characteristics, and is corrected for at least one dimension (usually size) to allow for meaningful comparisons’ [8].

For example, a simple aggregation such as the number of women members of parliament is not in itself an indicator, as it is not comparable between populations. However, if these values are relativized and/or standardised, e.g. women members of parliament as a percentage of the total, then the result meets the criteria for an indicator.

Some sources suggest that to provide meaningful comparisons, indicators should not only be expressed in units that are comparable across space and time, but a reference point (a norm or benchmark) should also be defined against which value judgements can be made (such as the minimal percentage of women members of parliaments to be achieved) [9]. When defined in this way indicators become normative, ‘in the sense that a change from the reference point in a particular direction can be interpreted as “good” or “bad”’ [10].

Thus, gender indicators can be used to measure progress and allow for comparisons in gender equality progress over time, across different geographical areas, countries and between different groups of women and/or men (e.g. younger and older women and men; unemployed and employed women and men) as well as in organisations, institutions and systems. They can measure the relative situation of women and men in areas such as their access to assets, their empowerment and the attitudes of women and men toward gender equality. Gender indicators can also be used to measure the extent to which society is free from gender-based violence and/ or negative gender stereotypes [11].

Approaches to data collection

There are two main methods of data collection relevant for gender statistics and indicators, which are briefly described here.

  1. Quantitative methods of data collection produce quantifiable results. In other words, they focus on issues that can be counted, such as percentages of women and men in the labour market, male and female wage rates or school enrolment rates for girls and boys. Quantitative data can show the magnitude of changes in gender equality over time — for example, the percentage of women married before the age of 15 or the gender pay gap over time [12].
  2. Qualitative methods capture people’s experiences, opinions, attitudes and feelings — for example, women’s experiences of the constraints or advantages of working in the informal sector, or men’s and women’s views on the causes and consequences of underrepresentation of women in senior positions in the economy or in politics. Often participatory methods such as focus group discussions and social mapping tools are used to collect data for qualitative indicators. Qualitative data can also be collected through in-depth surveys measuring perceptions and opinions [13].

Why are gender statistics and indicators important?

Gender statistics and indicators have the potential to contribute to the narrowing of gender inequalities by providing an evidence base that makes gender inequalities visible. Such indicators ensure that women’s and men’s situations and contributions to society are measured correctly and valued equally. They also allow gender aspects to be made visible in areas where they were previously considered irrelevant.

Gender statistics and indicators are important because they:

  • give evidence on progress towards gender equality, contribute to closing persistent gender gaps and to correcting gender bias. For instance, policies for alleviating poverty have traditionally used the concept of household income to measure the distribution of resources. This is based on a gender-biased assumption that income is equally distributed within the household and amongst household members, ignoring gender differences in access to income and resources and the impact of gender roles and relations in the household. In this case, collecting gender relevant data both at individual and household level can help reveal such differences [16];
  • show that gender inequalities are a concern for the whole of society and that they have to be taken seriously by all actors in the public arena;
  • provide evidence for the development of policies, programmes, projects and legislation that respond to the needs of women and men as beneficiaries of an intervention in a specific context;
  • sustain learning processes for policymakers and stakeholders by making gender inequalities visible;
  • contribute to increasing citizens’ and decisionmakers’ awareness on gender inequalities (see gender awareness; link here) that may encourage them to take action [17];
  • provide information on the potential impacts of policies and interventions on women and men [18];
  • contribute to preventing the adoption of policies that perpetuate gender bias and gender inequalities, and/or that avoid the risk of not fulfilling the objectives of the respective intervention [19];
  • provide evidence for monitoring and evaluating the implementation of an intervention (e.g. policy, programme, project, legislation) and for assessing its relevance, efficiency and effectiveness for both women and men [20].

Gender statistics and indicators are important to promote gender mainstreaming at an organisational level. In workplaces, they are essential to inform the development of human resources policies and procedures, and to measure the gender pay gap or the representation of women in decision-making positions in an organisation. International organisations (such as the European Commission, the United Nations, the International Labour Organisation and the World Bank) frequently use gender statistics and indicators to inform gender audits and measure progress in gender equality in their internal structures, procedures, human resources and culture.

Gender statistics and indicators are an integral part of national progress to improve national statistical systems. For instance, when data users require specific gender statistics this helps to reveal gaps in general statistics and raises awareness about how to implement improvements in data collection processes (e.g. in the methodologies, concepts, topics, data series) in order to avoid gender bias and fully reflect women’s and men’s life situations [21].

Additionally, the importance of gender statistics and indicators has been reaffirmed at the international level through:

  • commitments towards the improvement of the collection of gender statistics made under the Beijing Platform for Action, the EU Treaty of Amsterdam and in EU strategic policy commitments such as the Strategic Engagement for Gender Equality 2016-2019, as well as the Council of Europe Convention on preventing and combating violence against women and domestic violence (Istanbul Convention);
  • the creation of guidelines (e.g. Quality Criteria of EIGE’s Gender Statistics Database, UNECE tool for the development of gender statistics), databases on gender statistics (e.g. EIGE Gender Statistics Database, the World Bank Gender Data Portal, the Eurostat database) and support for Member States in mainstreaming a gender perspective in their statistical systems.

Producing and assessing gender statistics and indicators

Gender statistics [26]

As the Quality Criteria of EIGE’s Gender Statistics Database explains: ‘[the] overarching general principle in the production of high quality gender-sensitive data is that of gender mainstreaming’ [27]. This, according to the United Nations Statistical Division, means ‘that gender issues and gender-based biases are systematically taken into account in the production of all official statistics and at all stages of data production’ [28].

Having established the principle of gender mainstreaming, there are a series of steps that can be taken in developing gender statistics [29].

Step 1. Selection of topic from a gender perspective

It is important to select topics that are relevant for gender statistics, namely topics that specifically tackle inequalities between women and men in all aspects of life. Of particular relevance to gender equality are equal decision-making power, equal economic opportunities, pay and status, work-life balance, elimination of gender stereotypes and freedom from gender-based violence [30]. Specific attention should be paid to ensure that the indicators used measure progress in the respective topic.

Step 2. Identification of appropriate concepts, methodologies and measurement tools

In the planning stage of the collection of gender statistics it is important to assess whether existing concepts, theories and methodologies applied to the respective area adequately reflect differences between women and men, reveal gender inequalities and are not gender biased. In cases where they fail to do so, gender-sensitive concepts and methodologies will have to be developed. For instance, while labour force surveys provide information on employment in a country, they only partially reflect gender inequalities if they do not include unpaid work. To better understand gender inequalities in this area, labour force surveys can be complemented by time-use surveys. Coherence and comparability of data must be ensured at this stage, particularly where cross-country comparisons are being made.

Step 3. Definition of the measurement tools for collecting data

The quantitative approach to the collection of data involves the following steps.

Step 4. Collection of gender statistics

There are various methods for data collection (e.g. telephone, face-to-face, computer assisted or personal assisted interviews, door-to-door or online surveys, self-compilation). When selecting a specific method, it is important to assess how gender bias can be avoided in the data collection process. For instance, in interviews the interviewers’  values/beliefs/construction of gender roles may influence the opinions of the interviewee, as mentioned above. The characteristics of an interviewer (e.g. gender, age) may also affect how women and men behave during the interview and the answers they give. An analysis of potential risks in terms of gender should be conducted when selecting the data collection method and measures should be adopted to mitigate them.

Step 5. Analysis of gender statistics

The type of analysis carried out on the collected gender statistics will depend on the purpose of the collection process. For instance, the analysis of gender statistics may be carried out over time and across sectors, policies, programmes, projects, organisations, etc. to provide benchmarking on specific issues. Where gender impact assessments are carried out, the analysis of gender statistics should focus on the potential impact of an intervention on women and men. In gender evaluation, the analysis of gender statistics focuses on the changes brought about by the respective interventions for women and men.

Step 6. Dissemination to a wide range of users (e.g. policymakers, nongovernmental organisations, citizens)

Once the analysis is completed, gender statistics have to be communicated and disseminated. The communication of gender statistics and their analysis from a gender perspective is important to raise policymakers’, stakeholders’ and, in general, citizens’ awareness on gender issues. Communicating the value of gender statistics is also important to enhance their use and show their potential for different users or audiences (e.g. researchers, evaluators, policymakers, stakeholders). When disseminating gender statistics, data summaries and information, they should be made accessible for different target audiences. The dissemination of gender statistics can be carried out through publications related to gender equality, general statistical publications, research reports, journal and newspaper articles, online databases and social media.

Gender indicators

The planning stage needs to take account of how the design of gender indicators can measure progress on broad gender equality objectives, as well as the specific goals of policies, programmes or projects. Gender indicators need to be tailored and appropriate to the policy objectives. The selection of gender indicators also depends on the scale of the intervention, the availability of gender statistics and the capacity of the actors involved in the data collection. In selecting the appropriate gender indicators, the following principles should be adhered to [36].

  • Undertake a gender analysis to support the definition of gender indicators.
  • Use both quantitative and qualitative gender indicators; this should cover all aspects of the respective intervention or topic in question and prevent gaps in the data collection process.
  • Ensure indicators are collectable, as some may prove to be irrelevant or difficult to collect.
  • Ensure relevance and partner ownership. This includes ensuring gender indicators are meaningful for policymakers and stakeholders, as well as for the intervention and context. In particular, gender indicators should be in line with relevant gender equality commitments and gender-specific policy objectives.
  • Involve stakeholders in the definition of gender indicators for the respective intervention through participatory approaches. In order to avoid bottlenecks in the definition and collection of data on gender indicators, it is important to assess the level of commitment and capacity of actors involved.
  • Consider the timeframe for expected changes of policies, programmes or projects analysed, which may take place over a short-term, medium-term and long-term period of time. The expected term should be considered in the definition of the timeframe for the collection and measurement of the indicator.
  • Ensure flexibility and transparency in the development of the gender indicators as objectives and actions of the respective intervention may need to be changed or adjusted.

Once the indicators are selected, baseline information should be collected to provide a reference point to measure changes that take place over time in the respective intervention. This can be very useful in benchmarking and mapping progress over time. Data collected on gender indicators can be assessed against the agreed outcomes to examine whether the intervention triggered the expected changes in women’s and men’s situations.

Further information

Download this brief as a PDF publication

Image copyright: Markus Mainka/