Gender Equality in a Changing World

5. Persistent gender gaps in paid and unpaid work

Abstract

This chapter presents an overview of key gender gaps in paid and unpaid work, including labour force participation, part-time employment and earnings, as well as key social, economic and institutional factors preventing gender equality in these areas. The chapter then proposes policy options to reduce gender gaps in labour supply; improve gender equality in entrepreneurship; and close gender pay gaps and gaps in pension earnings and income.

Key findings

• Across many indicators of labour market outcomes, women are worse off than men, including in lower labour force participation and employment rates. Women also dedicate fewer hours to paid work and are more likely to work part-time than men, which affects career prospects and eligibility for social protection (e.g. unemployment, family leave). Women, too, are less likely to be entrepreneurs than men, and even when they are self-employed, they are less likely to have employees than men. Women are also more likely to work in low-paid (likely undervalued) occupations than men. And, finally, women earn, on average, lower wages than men.

• Gender gaps in labour market outcomes accumulate throughout the life course to result in lower pension entitlements and lower pension income, which puts older women at greater risk of poverty and social exclusion in most OECD countries.

• The differences in men’s and women’s labour market outcomes reflect gender norms and stereotypes around paid and unpaid work, which are learned at an early age. Gender norms and stereotypes interact with social, policy and economic environments that disadvantage women in the labour market, including a lack of access to affordable, high-quality childcare and out-of-school care; a lack of access to long-term care for relatives; low pay in traditionally women-dominated sectors; the unequal distributions of family leave; and gendered tax-benefit systems that disadvantage second earners.

• To close gender gaps in paid and unpaid work, governments have implemented and continue to invest in work-life balance policies, including better access to high-quality affordable childcare and long-term care and better access to paid parental leave. In addition, governments have intervened to build entrepreneurship ecosystems that seek to support women entrepreneurs and improve the quality of their businesses, to encourage or mandate gender pay gap reporting by firms, and to offer (conditional) care credits to offset the negative impacts of care‑related leave on pension entitlements and earnings.

Every person should be able to participate fully in the labour market. Employment supports financial independence and benefits the overall economy through increased economic growth and prosperity (Fluchtmann, Keese and Adema, 2024[1]). Yet starting at an early age, girls and boys are exposed to gender norms and stereotypes around paid and unpaid work – through various sources – that present a picture of women holding primary responsibility for unpaid work, such as care and household tasks, and men holding primary responsibility for paid work. As children age into adulthood, these internalised gender norms and stereotypes combine with social and policy environments, structural barriers, bias and harassment and discrimination to create, reinforce and widen gaps between women and men in labour market outcomes, including in the type, quality, quantity and remuneration of paid and unpaid work.

This chapter proceeds as follows. Section 5.1 provides an overview of key gender gaps in paid and unpaid work using a life course approach. It also highlights important social, economic and institutional factors preventing gender equality in paid and unpaid work. Section 5.2 explores policy options and policy combinations to reduce gender gaps in labour supply; improve gender equality in entrepreneurship; close gender pay gaps; and reduce gender gaps in pension earnings and income.

5.1. Background: Gender gaps in key outcomes in paid and unpaid work

Using a life course approach, this section describes and attempts to explain gender gaps in paid and unpaid work in childhood, youth and adulthood, focusing on labour force participation, hours worked, non-standard employment, occupational segregation and earnings. Since gender gaps aggregate throughout the life course, including in earnings, it is useful to understand how inequalities compound over time and where public policy can help break the cycle.

5.1.1. Childhood and youth: Girls do more unpaid work than boys

Gender gaps in unpaid care and household responsibilities develop early. These gaps are learned through gendered socialisation processes around housework and caregiving, including the observation of parents’ task assignments, but also directly through parents’ beliefs and expectations regarding the role of their children inside and outside the household (see Chapter 4). According to a 2022 survey in the EU, for instance, only 68% of women and 52% of men aged 16‑74 years strongly agree that boys have the same obligations to help with household chores as girls (EIGE, 2023[2]). Unsurprisingly, then, girls are found to engage in more housework than boys, with gender gaps growing as children grow older. Girls and boys also appear to do stereotypically gendered housework tasks. Girls are more likely to cook, clean, wash dishes and help with childcare, while boys are more likely to spend time gardening, taking out the trash and doing car maintenance (O’Reilly and Quayle, 2021[3]; Dotti Sani, 2016[4]; Álvarez and Miles-Touya, 2011[5]; Schulz, 2019[6]; Hofferth and Goldscheider, 2017[7]; Bonke, 2010[8]; Evertsson, 2006[9]; UNICEF, 2016[10]).

Box 5.1. Gender gaps in “earnings” start in childhood

Several national studies suggest that gender gaps in pay start in childhood. For example, one survey of 10 000 families using the chore app “BusyKid” found that the average boy received USD 13.80 weekly in allowances for doing chores, compared to USD 6.71 for girls (Miller, 2018[11]). Boys were also more likely to be paid to do personal hygiene (e.g. showering, brushing teeth), while girls were more likely to be paid for cleaning. Other surveys and research have found similar results, showing that boys are both more likely to get an allowance, and when they do, they are more likely to get a higher amount (Marcotte, 2014[12]; Leahy, 2022[13]).

5.1.2. Early and middle adulthood: Balancing work and family life creates challenges

Women’s participation in paid work is lower than men’s, especially for mothers

In all EU and OECD countries, women are less likely to be in the labour force than men (Figure 5.1). Gender gaps range from as little as two percentage points or less in Finland, Estonia and Lithuania to more than 25 percentage points in Costa Rica, Mexico and Türkiye.

Figure 5.1. Women participate in the labour market less than men

Labour force participation rates (%), women and men (15‑64), 2023

Note: EU‑24 and OECD‑37 refer to unweighted averages of the 24 EU and 37 OECD countries with available data for this indicator. ↗ indicates that the data is sorted according to this series in ascending order. Data for this figure can be downloaded via Annex 5.A.

Source: OECD Data Explorer “Labour force participation rate” (https://data‑explorer.oecd.org/s/zr).

Although many factors explain differences in labour market outcomes between women and men, the presence of dependent children is one key factor blocking women’s progress in the labour market. Indeed, for women, the presence of dependent children (under the age of 15 years) decreases employment rates in nearly all EU and OECD countries. This is commonly referred to as one type of “motherhood penalty” or “child penalty” (Kleven, Landais and Leite-Mariante, 2023[14]; Lundborg, Plug and Rasmussen, 2024[15]). Although not a causal estimate of the impact of parenthood, a simple comparison of employment rates between women with and without children shows that gaps persist in OECD countries and that gaps have been closing only slowly over time (Figure 5.2). This same exercise for men shows the opposite. In causal studies, this impact is often referred to as the “fatherhood premium” (Yu and Hara, 2021[16]).

Average employment rates for mothers are lower when there are more children and when children are younger. For fathers, there is no discernible difference in employment rates by the number and age of children and employment rates are always larger than for mothers (see Online Annex Figure 5‑A1). Even when looking at equally-qualified candidates in an audit study, motherhood penalties (and fatherhood premiums) are found to exist for perceived competence and recommended starting salary (Correll, Benard and Paik, 2007[17]). Importantly, these gender gaps emerge even though women’s and men’s labour force participation rates and earnings evolve in a similar way in most countries before children enter a home (Kleven, Landais and Leite-Mariante, 2023[14]; Kleven et al., 2019[18]).

Traditional economic models explain the gendered division of work within the household by identifying efficiency gains when the lower-earning opposite‑sex partner (historically the wife) focuses on unpaid work, while the higher-earning opposite‑sex partner (historically the husband) pursues paid employment (Becker, 1985[19]; Becker, 1991[20]). This rationale holds less explanatory power today. In a growing number of opposite‑sex couples, the woman now has an equal or higher level of educational attainment than the man and may earn as much or more (OECD, 2023[21]). There are also an increasing number of families where the woman is the sole breadwinner (Kowalewska and Vitali, 2020[22]). Both of these facts challenge the traditional division of labour. Despite this, gender norms around which parent “should” stay home with the children are persistent. A recent EU survey, for example, finds that over 40% of respondents disagree that a father should give up work to look after the children if his pay is lower than the mother’s and the family wants a parent to stay home with the children (see Online Annex Figure 5‑A2) (Eurobarometer, 2024[23]).

Figure 5.2. Children correspond to lower employment for women, but higher employment for men

Employment rate (%), women and men (25‑54) with at least one child (0‑14) and without children (0‑14), OECD‑21, 2006‑21

Note: OECD‑21 is an unweighted average of 21 countries with comparable data between 2006 and 2021, including Austria, Belgium, Czechia, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Poland, Portugal, the Slovak Republic, Slovenia, Spain and the United States. Data for this figure can be downloaded via Annex 5.A.

Source: OECD secretariat calculations using microdata from the EU Labour Force Survey and the United States Current Population Survey.

Box 5.2. Spotlight on intersectionality: Women in non-metropolitan areas may experience greater barriers to labour force participation

On average, across OECD countries, gender gaps in labour force participation are smallest in the most remote regions, while they are largest in non-metropolitan areas close to small cities. The large gender gap in non-metropolitan areas close to small cities is partly driven by demographics. Suburban locations are close to jobs, have natural amenities and have larger homes, all of which are attractive attributes for large(r) young(er) families, where gender gaps in labour force participation are wide(r). Although families may choose to have one parent – typically the mother – stay at home, a lack of public services, infrastructure and family-friendly policies matters too. Indeed, in non-metropolitan areas close to small cities, a lack of access to childcare could be particularly important in driving gender gaps in labour force participation.

To address these challenges, local policies can focus on improving childcare access and affordability, supporting women’s entrepreneurship and encouraging flexible work arrangements. Shared-service models for childcare may be particularly useful in non-metropolitan areas close to small cities, where multiple services can be offered together to reduce costs.

Source: Marshalian and Raderschall (2023[24]), The final frontier: Why are women further from labour parity in some non-metropolitan areas?.

Box 5.3. Spotlight on intersectionality: Migrant status and employment

Migrants often face disadvantages in the labour market and these disadvantages may interact with gender and the presence of children. OECD (2023[25]; 2020[26]), for example, find that children of migrants are less likely to participate in formal childcare than children of non-migrants, and that migrant mothers see availability and affordability as particularly acute obstacles to formal childcare. The impact of these obstacles likely contributes to gaps in employment rates. In EU‑23 countries, non-migrant mothers with children aged 0‑14 years face smaller gaps in employment than migrant mothers (see Online Annex Figure 5‑A13).

Patterns in part-time work differ between women and men

In all EU and OECD countries, women in paid work are more likely to work part-time than men (see Online Annex Figure 5‑A3), driven in part by women selecting into jobs or reducing their hours once they become mothers in order to meet disproportionate unpaid childcare responsibilities (OECD, 2019[27]; 2017[28]; 2023[21]). Indeed, as with employment rates and pay, there is a notable gap in hours worked between parents and non-parents in many EU and OECD countries (Figure 5.3). The correlation between motherhood (of dependent children) and lower hours worked is reinforced by survey evidence on reasons for part-time work: in 2018, for instance, 15% of women in the EU reported that childcare responsibilities reduced their overall working time, compared to only 3% of men (see Online Annex Figure 5‑A4) (Eurostat, 2022[29]). There are also many other reasons for part-time work – such as an inability to find full-time work, own illness or disability, education or training and non-care family-related reasons. Some of these are considered “voluntary” (such as care work) and others “involuntary” (such as an inability to find full-time work). Measured as a share of employment, women were more than twice as likely as men to be working part-time involuntarily (OECD Data Explorer, 2024[30]), with occupational segregation an important factor explaining this gap (Pech, Klainot-Hess and Norris, 2020[31]).

Even in those countries where gender gaps in part-time employment rates are small (e.g. Bulgaria, Romania, Lithuania), gender inequality in the labour market persists, with women much more likely than men to drop out of the labour force entirely when they become mothers. In addition to gender norms and workplace culture, this is partly explained by generous parental leaves – both in duration and in pay – as well as the relative lack of (well-paid) part-time employment opportunities (OECD, 2023[21]; 2022[32]; 2022[33]).

Figure 5.3. Women tend to work part-time more than men, with parenthood driving larger gaps

Difference in part-time employment rates between people with and without dependent children (parents minus non-parents), women and men (25‑54), percentage points, 2021 or latest

Note: EU‑27 and OECD‑26 averages are unweighted. Parents are defined as people with children aged 0‑14 years. For Canada, Korea and the United States, children are aged 0‑17 years. Data for Türkiye are from 2013. Data for Chile are from 2017. Data for Canada are from 2022. Data for this figure can be downloaded via Annex 5.A.

Source: OECD secretariat calculations using microdata from the EU Labour Force Survey, the Canadian Labour Force Survey, the Chilean Encuesta de Caracterización Socioeconómica Nacional (CASEN), the Turkish Household Labour Force Survey, and the United States Current Population Survey.

Gender gaps in temporary work are small, but impacts on women and men may differ

When it comes to temporary employment, gender gaps average about 2 percentage points, with 10% of women holding temporary jobs in 2023 in OECD‑36 countries, compared to 8% of men (Figure 5.4). In specific cases where gender gaps are higher, higher temporary employment among women may, in some cases, be influenced by reforms that liberalised the use of fixed-term contracts with the express purpose of enhancing or facilitating women’s labour force participation (ILO, 2017[34]). Indeed, there is “some anecdotal evidence that managers may be reluctant to hire [young women] on permanent contracts” due to the anticipated costs of maternity leave (ILO, 2017[34]).

Figure 5.4. Women are slightly more likely to work in temporary jobs than men

Gender gap (men minus women, percentage points) in temporary employment rates (%), women and men (25‑54), dependent employment, 2023 or latest

Note: EU‑27 and OECD‑36 averages are unweighted. Temporary employment rates are calculated by dividing the number of temporary employees of a specific gender by the total number of all employees of that same gender. Data on temporary employment for Australia and the United States are from 2017. Definitions of temporary employment vary considerably across countries. For more details, see OECD (2023[35]). Data for this figure can be downloaded via Annex 5.A.

Source: OECD Data Explorer, “Employment by permanency of the job – Incidence” (https://data‑explorer.oecd.org/s/1mn).

Box 5.4. Looking beyond employment to unemployment

Gender gaps in unemployment and long-term unemployment rates are quite small in most EU and OECD countries, with the unemployment rate for women in EU‑27 countries only 0.5 percentage points higher than that of men in 2023 (see Online Annex Figure 5‑A5). However, unemployment is a fairly restrictive measure. To be considered unemployed, an individual must be jobless, have an interest in working, have been recently seeking work and be available to start work at short notice. Compared to men, women are less likely to meet these conditions due to their disproportionate share of unpaid care and housework responsibilities (ILO, 2019[36]; 2023[37]). Expanding the definition to include all of those who would like to work but who do not currently have a job, in EU‑27 countries in 2022, 13% of women, compared to 10% of men, suffered from a job gap (ILO, 2024[38]). Unpacking the statistics shows that women tend to be excluded from unemployment because they are less likely to meet the availability and the search criteria required to be considered unemployed.

But these figures are from an unexceptional year, and unemployment is an indicator that exhibits more notably gendered patterns during crises. During the Great Recession, for example, men were more affected by unemployment than women (Pissarides, 2013[39]). By contrast, early on in the COVID‑19 pandemic, women experienced greater job losses than men in many countries, leading the period to be called a “she‑cession” (Bluedorn et al., 2023[40]; OECD, 2021[41]). Yet, in many countries, these “she‑cessions” were short-lived (Bluedorn et al., 2023[40]) and women’s employment recovered better and more quickly from the pandemic (OECD, 2023[21]; Queisser, 2021[42]).

There are also gendered perceptions of “entitlement” to jobs during periods of high unemployment. In the 2017‑22 wave of the World Values Survey, for instance, nearly one in five people in EU and OECD countries responded that men have more of a right to work than women when jobs are scarce (see Online Annex Figure 5‑A6) (WVS, 2023[43]). Indeed, Berniell et al. (2024[44]) use microdata from the World Values Survey for a panel of 103 countries over the 1995‑2021 period and find that “an increase in unemployment is associated with more conservative views about gender roles” in the labour market, and that the link is stronger in countries with “higher gender inequality” and lower labour force participation among women.

Women do more unpaid work than men

Unpaid work acts as a barrier to paid work for some women, keeping them out of the labour market. For many other women, unpaid work is a “second shift” after they return home from paid work (Hochschild and Machung, 1989[45]). When this “second shift” – or unpaid work – is combined with paid work, women work, on average, 24 minutes per day longer than men in OECD countries, or about 12 hours per month (OECD, 2024[46]). This is driven by the fact that women are doing almost twice as much unpaid work as men per day (Figure 5.5). Gaps between women and men vary significantly across countries. In Mexico, Portugal and Türkiye gender gaps in unpaid work are over 200 minutes per day, while in Denmark, Norway and Sweden, gender gaps in unpaid work are less than 60 minutes per day. Although large gender gaps persist (Figure 5.5), unpaid work hours have changed dramatically over time for both women and men, with evidence of some gender convergence (Pailhé, Solaz and Stanfors, 2021[47]).

Figure 5.5. Women do almost twice as much unpaid work as men per day

Number of minutes per day of unpaid work, women and men, 2022 or latest

Note: Data for Portugal are from 1999, data for Slovenia are from 2000‑01, data for Denmark are from 2001, data for Latvia and Lithuania are from 2003, data for Ireland are from 2005, data for Australia are from 2006, data for Estonia, Finland, France, New Zealand and Spain are from 2009‑10, data for Hungary and Sweden are from 2010, data for Norway are from 2010‑11, data for Germany are from 2012‑13, data for Belgium, Greece, Luxembourg and Poland are from 2013, data for Italy are from 2013‑14, data for Korea and Mexico are from 2014, data for Türkiye and the United Kingdom are from 2014‑15, data for Canada are from 2015, data for the Netherlands are from 2015‑16, data for Japan are from 2021, data for Austria are from 2021‑22, and data for the United States are from 2022. Time spent in unpaid work includes routine housework; shopping; care for household members; childcare; adult care; care for non-household members; volunteering; travel related to household activities; and other unpaid activities. * indicates the definition differs. Most time‑use data sets are large enough to generate reliable measures of time allocation over the full year, but the accuracy of these estimates as well as the methodology vary significantly from country to country. Differences in survey features, number of diary days sampled, and categorisation of activities may all affect the cross-country comparability of results. For more information on the exact categories used for each country and a detailed breakdown by sub-activity, see the methodology guidelines for the OECD Time Use Database (https://www.oecd.org/gender/data/OECD_1564_TUSupdatePortal.xlsx). Data for this figure can be downloaded via Annex 5.A.

Source: OECD Time Use Database (www.oecd.org/en/data/datasets/time‑use‑database.html).

Although estimated during the COVID‑19 period when patterns of unpaid work hours were different and in many cases more intense for women (OECD, 2021[41]), similar results emerge in the EU among working women (Eurofound, 2022[48]). Gender gaps are particularly pronounced in the presence of children, where total hours worked reach 84 hours and above for women, compared to about 72‑75 hours for men (see Online Annex Figure 5‑A7) (Eurofound, 2022[48]).

Indeed, evidence from Australia shows that before the birth of a first child, the intra-household distribution of time spent on paid and unpaid work is relatively equal between women and men. Upon the birth of the first child, however, women take on markedly more unpaid work at the expense of paid work. And as the child grows older, this gendered division of labour does not appear to be renegotiated, suggesting that a first child is “a turning point in couples’ division of labour towards a highly gendered, long-term pattern,” reinforced in some cases by the “arrival of additional children, which stabilises the established pattern” (Wilkins et al., 2024[49]).

The “second shift” undertaken by women has been shown to contribute to higher levels of stress and lower levels of mental health, and limit the possibility of fully engaging and advancing in paid work (Dugan and Barnes-Farrell, 2018[50]; MacDonald, Phipps and Lethbridge, 2005[51]; Piovani and Aydiner-Avsar, 2021[52]; OECD, 2021[41]; 2023[21]).

Box 5.5. Valuing unpaid work

Unpaid household services (i.e. services for own use and/or consumption, such as childcare, cooking, cleaning) are not counted toward the measurement of Gross Domestic Product (GDP) and often remain unmeasured entirely, masking a significant portion of economic activity. Better measuring (and valuing) of these activities could reshape understandings of household contributions to the economy. Indeed, although estimates vary greatly depending on the methodology used, provisional calculations show that extending the production boundary to include unpaid household services in G7 countries could significantly impact traditional macroeconomic aggregates – including not only GDP, but also household disposable income, household final consumption and investments. For example, estimates of the value of unpaid household activities range from 15% of GDP for Canada to 26% for Italy by replacement cost method, and from 44% for Japan to 69% for Germany by opportunity cost method (van de Ven, Zwijnenburg and De Queljoe, 2018[53]).

Yet, challenges persist in accurately valuing unpaid work using available data, such as the limited availability and frequency of time‑use surveys (van de Ven, Zwijnenburg and De Queljoe, 2018[53]). OECD (2021[54]) provides methodological considerations on valuing unpaid housework activities as well as estimates of the economic contribution of non-care housework.

Recognising the importance of measuring unpaid work for gender equality, policy and decision-making, the System of National Accounts (SNA) recently underwent significant revisions to offer guidance on better capturing the economic value of unpaid work. Through the 2025 updates, the SNA encourages satellite (or thematic) accounts on unpaid work, allowing for the measurement and reporting of unpaid household services without altering the core production boundary and enhancing the visibility of unpaid work. The revisions to the SNA also encourage countries to conduct specialised time‑use surveys to collect gender-disaggregated data on unpaid work – which is essential for developing policies that recognise and support unpaid labour and which can ultimately help to close gender gaps in both paid and unpaid work.

Note: The replacement cost method constructs an average post-tax, hourly wage, representative of the broad range of activities covered in the production of unpaid household services. The opportunity cost method takes the average post-tax hourly wage across the whole economy, thus trying to estimate the market income foregone as a result of spending time on unpaid household activities. See van de Ven, Zwijnenburg and De Queljoe (2018[53]) for more details.

Source: United Nations Statistics Division (2025[55]), Draft System of National Accounts 2025.

Box 5.6. Sandwich caregiving

In the face of demographic headwinds across EU and OECD countries, gender gaps in unpaid childcare are likely to be compounded by increasing unpaid care obligations for older relatives and relatives with disability (Frey, Hyee and Thomas, 2024[56]; OECD, 2023[57]). In a recent study in Canada, of the 13.4 million Canadians aged 15 years and over who provided unpaid care in the previous 12 months, 1.8 million (or 13%) reported providing care both to children and to adults with a long-term condition or disability (Statistics Canada, 2024[58]). This double burden is referred to as “sandwich caregiving.” Of these sandwich caregivers, 62% were women and 38% were men, and women were more likely than men to report negative impacts of caregiving on health, well-being, finances and family relationships (Statistics Canada, 2024[59]). As population ageing continues, monitoring developments in sandwich caregiving, including its prevalence and impacts on work and life should be a priority. Governments should also carefully monitor changes in the impacts of sandwich caregiving on women’s labour supply in response to changes in the accessibility and affordability of early learning and childcare and long-term care.

Explaining observed patterns in paid and unpaid work between women and men

Key factors behind gaps in employment between parents and non-parents and between women and men are explored below.

• Gender norms and stereotypes: Around the world, social norms put pressure on mothers to remain at home with their children during their early years. Indeed, although there has been progress over time, according to the 2017‑22 wave of the World Values Survey, about one‑third of both women and men in EU‑23 and OECD‑33 countries believe that when a mother works for pay, the children suffer (see Online Annex Figure 5‑A8) (WVS, 2023[43]; OECD, 2023[60]). Similar results emerge from a 2022 survey in the EU, where only 43% of men and 57% of women strongly agree that a working mother can establish just as warm and secure a relationship with her children as a mother who does not work (EIGE, 2023[2]). In the face of such beliefs, women may internalise that the only way to be a “good mother” is to forgo working when their child is young (Schmidt et al., 2022[61]). Other perspectives present a similar story. Consider, for example, caregiving responsibilities when a child is sick. In a 2019 survey, 45% of respondents reported that mothers should, in the first place, stay home from work to take care of sick children; 25% neither agreed nor disagreed, and 29% disagreed (Fundamental Rights Agency, 2021[62]). These results all come from deep-rooted cultural beliefs that women are better carers, that the “most important role of a woman is to take care of her home and family” and that the “most important role of a man is to earn money” (see Online Annex Figure 5‑A9) (European Union, 2017[63]; Eurobarometer, 2024[23]). To top this all off, nearly 50% of respondents to a recent EU survey believe that men are naturally less competent than women at household tasks (see Online Annex Figure 5‑A10) (Eurobarometer, 2024[23]). Unsurprisingly, these perceptions and beliefs coalesce into a disproportionate share of unpaid care and housework being borne by women, with particularly pronounced gaps in the presence of children (see Online Annex Figure 5‑A7) (Eurofound, 2022[48]).

• Family leave: Immediately after birth, women are more likely than men to take time off to care for young children, with women representing over 70% of users of publicly-administered paid parental leave across the OECD (OECD, 2024[64]). This gap widens further when considering the total number of days as opposed to individual users (see Online Annex Figure 5‑A11) (OECD, 2024[64]). Time out of the labour market, especially in the early years of a career, can lead to sizeable negative impacts on labour market attachment and earnings, as well as create significant barriers to promotion and advancement. These gender differences in the use of parental leave are strongly influenced by gender norms and stereotypes around caregiving, unpaid work and parenting (Agerström, Carlsson and Erenel, 2023[65]; Li, Knoester and Petts, 2021[66]; OECD, 2023[21]), but these gaps also emerge from the rules and incentives of maternity, paternity and parental leave systems. For instance, while an increasing number of EU and OECD countries offer fathers access to paid leave around childbirth, most of the leave available to parents still privileges mothers. And even when leave can be shared between parents, incentive structures (e.g. replacement rates, benefit generosity) may imply strong negative implications for household finances if the father goes on leave when the father earns more than the mother (Marynissen et al., 2019[67]; Kaufman, 2017[68]; OECD, 2023[21]; OECD, 2024[69]). On top of this, even when fathers have access to (dedicated) leave, incentive structures may play a role in dictating behaviours around leave use, particularly if paternity benefits are lower than maternity benefits.

• Pre‑school and childcare: Without accessible and affordable high-quality childcare during a child’s early years, one parent often needs or chooses to remain at home, and this parent is most often the mother. This is clearly evidenced by the trajectory of employment rates for women by age of youngest child (see Online Annex Figure 5‑A1). Mothers’ employment rates are notably higher after compulsory school starts at around 5 or 6 years of age (OECD, 2024[70]), and in many countries, enrollment in early learning and childcare is low for children under the age of three years (OECD, 2024[71]) in part due to a lack of affordable and accessible high-quality care (OECD, 2023[21]). Additional children in a household only makes the challenge of securing and affording childcare more difficult. This is evidence by women’s reported reasons for inactivity. In the EU‑27, for example, caregiving for children or incapacitated adults is reported by 47% of inactive women with a youngest child aged 0‑2 years as the primary reason for remaining out of the labour market (see Online Annex Figure 5‑A12). By the time children are 6‑14 years old, this drops significantly to 20%. These gender gaps can also be experienced by grandparents (see Section 5.1.3), who may opt out of the labour market to care for grandchildren, and can be further exacerbated by other intersecting characteristics, such as migrant status (Box 5.3).

• Out-of-school childcare: Once children enter primary school, a lack of access to affordable high-quality out-of-school hours (OSH) care can continue to affect women’s employment patterns. Consider, for example, a primary school day that runs from 8:30am until 12:00pm and from 1:00pm until 3:00pm. These school hours do not coincide easily with a regular working day of 9:00am to 6:00pm, making it difficult for parents to combine school pick-up and drop-off and after-school childcare with a full-time job. This has likely contributed to the entrenchment of the part-time work culture among working parents (OECD, 2019[27]). The summer months are no exception, as schools can be closed for weeks or even months at a time (OECD, 2023[72]). In the absence of affordable and available childcare services, these long summer holidays can negatively impact women’s labour supply. In the United States, for example, Price and Wasserman (2023[73]) estimate that during the summer months the employment rate among women falls by 1.1 percentage points, hours worked fall by 9.8% and weekly earnings fall by 3.3%. For men, employment rates actually rise slightly over the summer months, hours worked fall by significantly less (only 3.6%) and weekly earnings fall by only 0.7% (about five time less than the decline experienced by women). Research from France also demonstrates the importance of school schedules for mothers’ labour supply. A 2013 policy reform introduced morning classes on Wednesdays, when historically there had been no classes on Wednesdays at all. After the reform, mothers were more likely to work full-time Monday to Friday, with no change for fathers, and the gender wage gap decreased by 6% (Duchini and Van Effenterre, 2022[74]).

• Tax-benefit systems: The structure of tax-benefit systems can play an important role in advancing (or reducing) gender equality in the labour market. Some systems directly and explicitly treat women and men differently (OECD, 2023[21]). In a 2022 stocktaking, seven of 43 countries indicated cases of explicit gender bias in their tax systems (OECD, 2022[75]). But, even gender-neutral tax-benefit systems may indirectly treat women and men differently as a result of the interaction of the features of such systems with differences in the underlying economic characteristics and behaviours of women and men. Tax systems, for example, can create traps that disincentivise second earners – who are most often women – from entering the labour force. Joint personal income taxation is a well-known source of such implicit bias. Under this type of system, the income of the family is taxed together as one unit (rather than taxed separately for each individual), leading second earners to pay a higher marginal tax rate, which can disincentivise participation in the labour market (OECD, 2023[21]; 2022[75]). In the same way, the progressivity of the tax system, together with the removal of tax credits and allowances when a part-time worker enters full-time work, can lead to high marginal effective tax rates that disincentivise such transitions (Harding, Paturot and Simon, 2022[76]; OECD, 2023[21]). Other taxes – such as capital taxes and consumption taxes – can also create gender inequalities (Box 5.7).

Many – if not all – of these factors stem back to parenthood in one way or another. But despite the apparent labour market advantages to not having children, working women without children may also face backlash at work and in society (Verniers, 2020[77]; Ashburn-Nardo, 2016[78]; Koropeckyj-Cox et al., 2015[79]; Vinson, Mollen and Smith, 2010[80]; McCutcheon, 2018[81]). Understanding the labour market experiences of both women with and women without children will be increasingly important as fertility patterns change and women in (most) OECD countries continue to have fewer children (U.S. Census Bureau, 2022[82]; Sobotka, 2021[83]; Provencher and Galbraith, 2024[84]; OECD, 2024[85]).

Box 5.7. Looking beyond income taxation to other forms of taxation

There are many types of taxes – including labour, capital, wealth and consumption taxes. Depending on their structure and their interactions with other social, economic and individual behaviours and characteristics, each of these taxes has the potential to directly or indirectly contribute to inequality between women and men across a variety of outcomes. Consider, for example, the lower taxation of capital income relative to labour income. Given that men are more likely to have capital income than women, this differential taxation disproportionately benefits men (Coelho et al., 2024[86]; OECD, 2023[21]). Consumption taxes, too, can create gender inequalities. Although single‑rate value‑added taxes (VATs) are likely to be gender-neutral, differences in rates across goods and services could create gender biases since consumption patterns can differ between women and men (Coelho et al., 2024[86]). Feminine hygiene products – as a necessity – and childcare services – as an enabler of labour force participation – have attracted significant attention in this regard.

Yet, compared to labour income taxes, there is much less research on the gendered impacts of capital, wealth and consumption taxes, suggesting the need for continued research, including investment in gender-disaggregated data and the development of methodologies for better assessing the distribution of capital, consumption, income and wealth within households (OECD, 2023[21]; Coelho et al., 2024[86]; OECD, 2022[75]).

Box 5.8. Gender-based violence (GBV) may act as a barrier to employment and contribute to occupational segregation

Many women experience GBV (see Chapter 8), and perpetrators may control or try to control a victim’s employment situation, income or assets. In Australia, for instance, a 2022 study found that 84% of victims/survivors reported that domestic violence impacted their ability to do their job (McNicol, Fitz-Gibbon and Brewer, 2022[87]). Many women may also experience technology-facilitated GBV while at work, with perpetrators using technology to monitor and disrupt women at work from afar. The barriers and challenges faced by women victims/survivors of violence translate into both lower overall employment and lower part-time employment (Summers, Shortridge and Sobeck, 2025[88]). Research from Finland using administrative data and a matched-control event-study design comes to similar conclusions, and puts forth a model to rationalise the findings, a model in which “abusive men have an incentive to use economic suppression to sabotage women’s outside options and their ability to later exit the relationship” (Adams et al., 2024[89]).

GBV may also contribute to occupational segregation and gender pay gaps, with women self-reporting more harassment in men-dominated workplaces where wages are high, and men self-reporting more harassment in women-dominated workplaces where wages are low (Folke and Rickne, 2022[90]). This suggests that GBV may discourage women and men from applying for jobs in workplaces where their gender is underrepresented. This conclusion is further supported by a survey experiment, in which respondents are “highly averse to accepting jobs in workplaces with a higher harassment risk for their own gender, but less averse when people of the opposite sex are at higher risk.” GBV may also contribute to gender inequality in the labour market by making gender minorities leave for new jobs, a conclusion supported by assessments of workplace transitions showing that “women who self-report harassment are more likely to switch to new workplaces with more [women] colleagues and lower pay.” This is supported by findings from linked administrative data in Finland, which shows that men-women violence causes a decline in the share of the employees at a firm who are women, driven by fewer new women hired and current women employees leaving (Adams-Prassl et al., 2023[91]). The aggregate results mask important nuance: only men-managed firms lose women and in women-managed firms, men perpetrators are less likely to remain employed after attacking their women colleagues.

These findings underscore the need for employer and government action, including more supportive workplace policies, such as workplace protections, flexible work options and better access to financial support for victims/survivors (see Chapter 8). The results also underscore the need to continue to push for increased representation of women in leadership across all industries and occupations in both the public and the private sector (see Chapter 6).

Men are more likely to be self-employed – but are also more likely to have employees

Across EU‑17 countries, about 18% of men and 11% of women, on average, are self-employed (Figure 5.6). Self-employment may be a sign of entrepreneurship, but it may also be a sign of “precarious working conditions that may reduce job quality” (OECD, 2019[92]). This risk of precariousness is particularly elevated for self-employed workers without employees, also known as own-account workers or solo self-employed workers. Across EU and OECD countries, women who are self-employed are more likely to be solo self-employed than men (Figure 5.6).

Figure 5.6. Men are more likely to be self-employed and to have employees

Share (%) aged 15+ years who are self-employed (Panel A) and share (%) of self-employed workers who are solo self-employed (i.e. without employees) (Panel B), women and men, 2023 or latest

Note: Self-employed is defined as employers, workers who work for themselves, members of producers’ co‑operatives, and unpaid workers (i.e. those who lack a formal contract to receive a fixed amount of income at regular intervals, but who share in the income generated by the enterprise). Self-employments rates are calculated by dividing the number of self-employment workers of a specific gender by the total number of workers of that same gender. Solo self-employments rates are calculated by dividing the number of solo self-employment workers of a specific gender by the total number of self-employed workers of that same gender. In Panel A, EU‑17 and OECD‑29 averages are unweighted. Data for Germany are from 2021. Data for Türkiye are from 2020. All other countries are from 2023. In Panel B, EU‑22 and OECD‑36 averages are unweighted. Data for Canada, New Zealand and the United States are from 2022. Data for Japan are from 2021. Data for the United Kingdom are from 2019. Data for Australia, Chile, Korea and Mexico are from 2017. Data for Israel are from 2016. All other countries are from 2020. Data for this figure can be downloaded via Annex 5.A.

Source: OECD Data Explorer “Annual labour force survey, summary tables” (https://data‑explorer.oecd.org/s/16p) and OECD Data Archive (https://data‑explorer.oecd.org/s/10w).

Gender gaps in entrepreneurship and in outcomes among entrepreneurs (e.g. size, growth, financing) may reflect that, on average, women and men start different types of businesses in different sectors, with self-employed women over-represented in many service sectors (OECD/European Commission, 2023[93]). But, beyond gender segregation and traditional barriers to labour market access, there are additional factors that may be preventing women from pursuing entrepreneurship and/or growing their businesses.

• Perceptions of risk: Women are less likely than men to report being willing to take the risk of creating their own business (OECD, 2016[94]). Indeed, about 50% of women report that a fear of failure prevents them from starting a business, compared to 43% of men (OECD/European Commission, 2023[93]).

• Perceptions of skills related to entrepreneurship: Women are less likely than men to report that they have the skills, knowledge and experience necessary to start a business (OECD, 2016[94]; OECD/European Commission, 2023[93]). These sentiments reflect, in part, that entrepreneurship and self-employment are linked to masculinity (OECD, 2021[95]), with the notion of the male entrepreneur as the standard (OECD/European Commission, 2017[96]). Women’s lower perceptions of their skills may also reflect that women are less likely to engage in self-promotion and have lower levels of self-confidence than men, especially when pursuing “male”-typed tasks (Casale, 2020[97]; Exley and Kessler, 2022[98]; Fitzsimmons, Callan and Paulsen, 2014[99]).

• Barriers in access to finance: Long-standing social and economic processes linking masculinity with entrepreneurship mean that women entrepreneurs are perceived as less legitimate, which affects their market position, their ability to mobilise critical resources, and consequently, their possibility to reach full entrepreneurial potential (OECD/European Commission, 2017[96]). Access to finance is a key obstacle to self-employment and entrepreneurship for both women and men, but women are more likely to see access to finance as a barrier (OECD, 2016[94]). Women entrepreneurs, for example, tend to have “lower levels of capitalisation and are more reliant on owner equity and insider financing than men” (OECD, 2021[95]). Women also tend to have “lower levels of entrepreneurial experience, [participate] in more marginal female‑dominated sectors, [and face] gender-biased credit scoring and gender stereotyping in the lending process” (OECD/European Commission, 2017[96]). Lower levels of basic financial knowledge, poorer financial literacy and weaker digital skills may further disadvantage women relative to men when seeking access to finance (OECD, 2023[21]). Women entrepreneurs may also be “discouraged borrowers,” lacking self-confidence to seek external funding in the same amounts, at the same rate and/or in the same way as men (OECD, 2021[95]).

• Entrepreneurship support programmes: Biases in entrepreneurship support programmes may create challenges for women entrepreneurs. Support schemes, for example, often favour growth-oriented businesses, and women-owned business are less likely to fit this criterion (Halabisky, 2021[100]). For example, in OECD countries, new women entrepreneurs are significantly less likely than new men entrepreneurs to expect that they will create at least 19 jobs over the next five years (OECD/European Commission, 2023[93]). Women are also less likely to operate in sectors that are conducive to growth (for instance, they are overrepresented in personal services) and to use growth-oriented business strategies (such as exporting) (OECD, 2023[21]). Some of these differences reflect that women and men pursue self-employment for different reasons.

• Motivations for entrepreneurship: Women are more likely to go into self-employment for the flexible working hours, as a way to reconcile work and care commitments (OECD/European Union, 2019[101]; OECD, 2021[95]), even though these care commitments may limit the growth potential of women’s enterprises. Indeed, although self-employed workers tend to work more hours than employed workers, on average, they have more flexibility in how these hours are distributed (OECD/European Commission, 2017[96]).

• Networks: Compared to men entrepreneurs, women entrepreneurs have smaller and less effective networks, which limits their ability to overcome the above‑noted resource constraints (Halabisky, 2021[100]). Women’s networks, for instance, tend to be less diverse and draw less on social capital from previous work experiences, which make these networks less effective than men’s. Women also rely more on family members, friends and educators, as opposed to business service providers or other entrepreneurs (OECD, 2021[95]). This difference in composition partly reflects that women are less likely to have interacted with individuals who control critical resources in previous employment experiences due to the leaky pipeline and the glass ceiling. Indeed, men are more likely to have networks of contacts with greater “social and economic power, which can be advantageous in assisting in the gathering of information, resources and referrals” (OECD/European Commission, 2017[96]).

• Access to social protection: Gendered differences in the rate of entrepreneurship may be partially a result of differences in access to social protection (e.g. family leave) between employees and self-employed individuals. Most social protection programmes – including maternity, paternity and parental leave – treat employees and self-employed individuals differently in terms of eligibility, qualifying criteria, contribution rates, and payment conditions (OECD/European Commission, 2017[96]). To ensure access to social programmes like family leave, women may be disincentivised to transition from employees into entrepreneurs (OECD, 2023[21]).

• Challenges accessing foreign markets: Trading can increase productivity as exporting can boost sales and lead to market expansion, while importing can reduce costs and improve technology (OECD, 2023[102]). In a survey of firms in OECD countries with a presence on Facebook, only 11% of women-led SMEs were engaged in exporting, compared to 19% of men-led firms in 2022. Importing was also more common among men-led firms (15%) than women-led firms (11%). Firm size and sector explain part of these gender gaps, but other factors also play an important role, including attitudes toward entrepreneurship, barriers to access to finance and a perceived lack of entrepreneurship skills. To close gender gaps, policies and programmes can focus on supporting women-led firms with access to finance (e.g. facilitate connections between bank intermediaries and women-led enterprises, with a focus on export loans and guarantees) and on helping women-led firms become export ready (e.g. providing market information, branding, customer relations and business partners and assistance navigating foreign and domestic customs regulations) (OECD, 2023[102]).

Occupational and task segregation remains a key feature of labour markets

Occupational segregation – the unequal distribution of women and men across occupations and industries – is a feature of all EU and OECD labour markets. In most occupations, gender segregation is the norm, with only 7 out of 42 occupations in EU‑27 countries in 2023 showing evidence of gender balance – defined here as a workforce composed of between 40% women and 60% women (Figure 5.7). Of the remaining 35 occupations that show a gender imbalance, 13 show extreme gender segregation – defined here as less than 20% women or more than 80% women. Extremely segregated occupations include many occupations related to the trades, which are men-dominated, and many occupations related to care, which are women-dominated. Since the occupations in which women are concentrated are more likely to be low paid and many have poor working conditions (OECD, 2019[103]; 2023[104]; World Economic Forum, 2023[105]), occupational segregation is an important factor contributing to the gender pay gap (see below) and to other gender inequities in the labour market.

Figure 5.7. Occupational segregation persists in EU and OECD countries

Share (%) of workers (15‑64) who are women by two‑digit occupational category (ISCO‑08), EU‑27 average, 2013 and 2023

Note: EU‑27 average is weighted. “Subsistence farmers, fishers, hunters and gatherers” was dropped due to missing data in 2023. Due to space constraints, not all occupations are reported at the same level. Some occupations are ISCO‑08 Level 1 occupations and some occupations are ISCO‑08 Level 2 occupations. Data for this figure can be downloaded via Annex 5.A.

Source: Eurostat “Employed persons by detailed occupation (ISCO‑08 two‑digit level)” (https://doi.org/10.2908/LFSA_EGAI2D).

Occupational segregation is, in large part, due to a gendered socialisation process that governs interests, aspirations, behaviours, expectations and even career paths (see Chapter 4 and Chapter 6). As children age into young adulthood, these gender norms and stereotypes collide with economic opportunities, as well as policies and practices, ultimately reinforcing existing gender differences.

Legislation matters, too. As of 2024, among the 43 EU and OECD countries, there are a handful of countries with laws against women working in an industrial job in the same way as a man and a few countries with laws against women working in a job deemed dangerous in the same way as a man (see Online Annex Figure 5‑A14) (OECD, 2024[106]; World Bank, 2024[107]). These laws typically stem(med) from (outdated) concerns over women’s health and safety and (outdated) assumptions that women are more vulnerable to physical strain or hazardous conditions than men. In the last 50 years, many countries have relaxed or amended such labour legislation. Nevertheless, the fact that women were legally unable to equally participate in certain occupations for many years may have created a path dependency or stickiness that is difficult to overcome.

Consider, for example, that children and youth have repeatedly shown that they learn about available jobs and aspire to different careers based on what is around them. Indeed, in Drawing the Future, a survey of over 13 000 children aged 7 to 11 years old in the United Kingdom, 39% of children drew a “dream” job performed by someone they knew (e.g. parents, guardians or an extended family member) (Chambers et al., 2018[108]). Of the other 61% who did not know someone who did their dream job, almost half reported that they had heard about the job through TV, film or radio. The importance of media and personal experience and encounters also shines through in the international sample of 7 000 children from 19 additional countries.

Occupational segregation may also be driven by the fact that some occupations may offer greater flexibility (e.g. flexible hours, part-time opportunities, remote work, etc.), which makes them more compatible with unpaid family and caregiving responsibilities (Das and Kotikula, 2019[109]). Evidence further suggests that this gender segregation may extend beyond the choice of occupation to the choice of firm, with women tending to gravitate toward jobs (within a given occupation) that offer greater flexibility, but that may also come with lower wages. These jobs provide a trade‑off between pay and work-life balance, potentially reflecting “compensating differentials” in the labour market around flexible working arrangements (Goldin, 2014[110]).

Beyond occupational and firm segregation, there is also “task segregation” within firms and within narrowly defined occupations. For example, women are more likely than men to volunteer for, to be asked to volunteer for, and to accept low promotability tasks (e.g. notetaking, serving on a committee, planning a party) (Babcock et al., 2017[111]). These tasks – from which everyone benefits – do, however, require time and effort, eating into the time available for high promotability tasks that contribute to career advancement and wage growth. Gender differences in low promotability tasks – which amounted to 200 hours per year in one study (Babcock, Peyser and Vesterlund, 2022[112]) – may, therefore, contribute to slower upward mobility for women within organisations and to vertical gender segregation in the workplace. Many other factors further contribute to vertical segregation in the workplace and the labour market (see Chapter 6), including gender differences in recognition for group work (Sarsons et al., 2021[113]).

Box 5.9. Women in men-dominated industries and occupations

Women in men-dominated industries and occupations may face bias and discrimination in the hiring process (Quadlin, 2018[114]), higher expectations than men with similar levels of education and experience (Hengel, 2022[115]), harmful and hurtful gender-based stereotypes (Funk and Parker, 2018[116]), and harassment and discrimination from colleagues and supervisors (Clancy et al., 2014[117]; Biggs, Hawley and Biernat, 2017[118]; Paul, Sultana and Bosu, 2019[119]; Cyr et al., 2021[120]). Combined, these affect workplace well-being, career prospects and earnings. Many women in these fields describe their workplaces as toxic, and many women who enter these field eventually leave (Spoon et al., 2023[121]). This means that gender gaps that exist in fields of study may be exacerbated in the labour market.

Box 5.10. Care and domestic workers face low pay and poor working conditions

Early childhood education and care (ECEC)

Access to affordable high-quality ECEC is a crucial driver of women’s labour force participation, helping to strengthen economic growth and boost productivity (OECD, 2023[21]). High-quality ECEC can also lead to increased cognitive and non-cognitive development in children (OECD, 2021[122]). Despite these benefits, ECEC work is defined by “low wages, a lack of status and public recognition, poor working conditions, and limited opportunities for professional development” (OECD, 2019[123]). ECEC is also an occupation dominated by women, with women accounting for 96% of staff across OECD‑36 countries (OECD Data Explorer, 2024[124]). This extreme level of occupational segregation reflects, in part, that ECEC is considered a low status and a low pay occupation, but also that it is traditionally regarded as “women’s work.” Diversifying the ECEC workforce by bringing more men into the sector could improve children’s development and learning and shape their attitudes toward gender roles (OECD, 2019[123]).

Care and non-care domestic workers

Care and non-care household services can help women increase their labour supply (e.g. Cortés and Tessada (2011[125])). Yet, many of the jobs in this sector are informal, meaning that workers – most of whom are women – are not covered by employment or social protection arrangements and are at greater risk of exploitation or sub-standard working conditions (OECD, 2021[54]). Reflecting the need for action, the 2013 OECD Recommendation on Gender Equality in Education, Employment and Entrepreneurship encourages countries to improve “employment conditions and access to social support for informal workers, especially those in the most vulnerable categories, such as home‑based and domestic workers” (OECD, 2017[126]). In addition, the ILO Convention 189 on Domestic Work establishes global labour standards to ensure fair working conditions and protections for workers, including provisions for fair wages, decent working hours and access to social security (ILO, 2011[127]).

Long-term care

Unpaid caregiving provided by family and friends is both a complement to and a substitute for paid caregiving provided by the long-term care sector, a sector dominated by women and characterised by low wages and poor working conditions (OECD, 2023[57]; OECD, 2021[128]; OECD, 2023[129]). As populations age, paid employment in long-term care is estimated to need to rise by 32% over the next ten years to meet increased demand (OECD, 2023[57]) – a rate that is unlikely to be met. People are aware of this risk: in the 2022 OECD Risks that Matter (RTM) Survey, the majority of people were concerned about not being able to access good-quality long-term care for themselves (67%) and for elderly family members (65%) over the next ten years (OECD, 2023[130]). It will therefore become increasingly important to value long-term care work appropriately and to reduce gender gaps in unpaid care as much as possible (Frey, Alajääskö and Thomas, 2024[131]). Attracting workers to the sector will require a comprehensive policy strategy, including improvements in wages, compliance with staffing requirements and transparency in the communication of effective staff ratios. Interventions could also include enforcing minimum wages, promoting appropriate wages in collective agreements, strengthening training, promoting social recognition, increasing the use of technology, and promoting transitions of undeclared workers to formal employment (OECD, 2023[57]). At the same time, governments can also better support unpaid caregivers. Many countries have already done so, offering paid leave and cash benefits to carers, those in need of care, or both (Rocard and Llena-Nozal, 2022[132]). Training, counselling, psychological and financial support are also key measures to support informal carers, as highlighted in the European Care Strategy (European Commission, 2022[133]).

Gender wage gaps persist across EU and OECD countries

Gender gaps in earnings are a critical manifestation of gender inequalities. Across EU and OECD countries – and around the world – women earn less than men. In 2023, the median full-time working woman earned, on average, 11% less than the median full-time working man – meaning she earned 89 cents to every euro or dollar earned by her male counterpart. This poor outcome is an 8 percentage point improvement upon 1995, when the gender wage gap was 19% (Figure 5.8).

Figure 5.8. Gender wage gaps have steadily closed over time, but women continue to earn less

Gender wage gap, percent, 10^th decile, median and 90^th decile, OECD average, 1995‑2023

Note: The gender wage gap is unadjusted and defined as the difference between median wages of women and men relative to the median wages of men. The indicator is based on gross earnings of full-time employees by earnings deciles (upper limits) reported in the OECD Distribution of Earnings Database. The most common earnings pay reporting periods are weekly and monthly earnings of full-time employees (for 30 out of 37 countries). Five countries use hourly earnings, and two countries use annual earnings. The distinction between full-time and part-time is according to national definitions as reported in the data source. Data for this figure can be downloaded via Annex 5.A.

Source: OECD Data Explorer “Gender wage gap” (https://data‑explorer.oecd.org/s/16q).

The existence of the gender earnings gap – and its patterns over the life course – reflect the interaction of social, economic and institutional factors, many of which have already been mentioned.

• Career breaks and the motherhood penalty: Career breaks affect earnings levels directly through their impact on the number of weeks worked in any given year, but they also have the potential to significantly alter earnings trajectories by limiting upward momentum and the development of skills and experience. The “motherhood penalty” specifically reflects the negative impact of parenthood on earnings for women. This penalty is partly evidenced by the fact that gender wage gaps within and between firms tend to increase over the life course and particularly during the initial phase of women’s professional careers, which are prime childbearing years (OECD, 2021[134]). For fathers, the opposite is often the case, contributing to the fatherhood premium (Yu and Hara, 2021[16]).

• Work intensity: The overrepresentation of women among part-time workers has important consequences for women’s earnings. First, part-time work tends to pay less than full-time work (Garnero, 2016[135]). Second, even supposing that part-time and full-time work were paid identically, fewer weeks and fewer hours worked for women compared to men mean that gender gaps in annual earnings tend to be larger than gender gaps in hourly earnings. In EU‑27 countries, for instance, gender gaps in median earnings on an annual basis averaged 17%, while on an hourly basis, they averaged 7% (see Online Annex Figure 5‑A15) (Eurostat, 2024[136]; 2024[137]).

• Horizontal segregation: Gender differences in occupation and industry contribute to the gender wage gap since women are more likely to work in low-paid occupations than men (OECD, 2017[28]). This helps to explain the higher incidence of “low pay” among women relative to men, where low pay is defined as less than two‑thirds of gross median earnings of all full-time workers (see Online Annex Figure 5‑A16). The fact that women-dominated industries and occupations tend to be paid less may be because they are undervalued, not because they are inherently less valuable (Bettio and Verashchagina, 2009[138]; OECD, 2023[139]; OECD, 2023[21]). For more on this, see Section 3.2.2. in OECD (2023[140]). There is also evidence that as women do “break in” to men-dominated industries and occupations, wages fall (for both women and men), due in part to a decline in prestige and an increase in flexibility (Harris, 2022[141]). These findings stress the importance of recognising the value of women-dominated jobs and seeking to improve the pay and working conditions in these industries and occupations.

• Vertical segregation: Glass ceilings (or vertical segregation) prevent women from reaching the top – and the highest paid positions – in all areas of work, even when women may be adequately or even overly qualified (see Chapter 6). This partly explains why women are less likely to earn “high pay,” defined as 150% higher than gross median earnings (see Online Annex Figure 5‑A16), and why gender wage gaps are substantially larger at the top of the distribution (Figure 5.8).

• Firm segregation: Even when women and men work in the same very narrowly defined occupations and industries, there remains a gender earnings gap, some of which is explained by sorting across firms. Women, for example, have been found to segregate into lower paying firms (Javdani, 2015[142]; Morchio and Moser, 2024[143]). This phenomenon is sometimes referred to as the “glass door” effect. This is in contrast to the “glass ceiling” effect, which considers vertical segregation within firms. This firm “sorting” may reflect several factors, including discriminatory hiring practices by employers and preferences of women for firms with flexible working-time arrangements (which also tend to offer lower pay) (OECD, 2023[21]; 2021[134]). Yet, at the same time, it has been shown that about three‑quarters of the gender wage gap between similarly skilled women and men reflects differences within firms (OECD, 2021[134]).

• Job transitions: Between their late 20s and early 40s, women are less likely to switch jobs than men and are less likely to experience a pay increase when they do so (OECD, 2022[144]). This fact contributes to the gender wage gap between firms, and suggests that, instead of wage‑ or career-motivated job changes, women may be changing jobs for personal reasons (e.g. more flexible working arrangements, working closer to home, following a partner) (OECD, 2023[21]; 2022[144]).

• Compensating differentials: Some jobs are “greedy,” meaning they involve long and unpredictable working hours in which individuals are not substitutable one for another. Such jobs are not easily compatible with unpaid work responsibilities, and often have pay schedules that increase non-linearly in hours. This trade‑off – or compensating differential – has been found to contributing to the gender wage gap, with gaps highest in those occupations where greedy jobs are more common (Sobeck, 2024[145]; Goldin, 2014[110]). Such compensating differentials may also exist between pay and other job characteristics (e.g. family friendliness of firms, shorter commutes) (Le Barbanchon, Rathelot and Roulet, 2020[146]; Fluchtmann et al., 2024[147]).

• Salary negotiations: Women and men may engage in and experience salary negotiations differently, which may contribute to disparities in earnings (Säve-Söderbergh, 2019[148]). First, women may be less likely to feel comfortable negotiating their salaries and less likely to do so (see Online Annex Figure 5‑A17) (European Union, 2017[63]) – although not all evidence points to a lower propensity to negotiate among women (e.g. Kray, Kennedy and Lee (2024[149]), Dreber, Heikensten and Säve‑Söderbergh (2022[150])). Second, even when women do negotiate, they may ask for less and/or receive lower offers than men (Kray, Kennedy and Lee, 2024[149]; Dreber, Heikensten and Säve-Söderbergh, 2022[150]; Kiessling et al., 2024[151]; Recalde and Vesterlund, 2020[152]). Third, women who negotiate may encounter resistance or backlash that can impact future employment opportunities and earnings growth (Exley, Niederle and Vesterlund, 2020[153]; Recalde and Vesterlund, 2020[152]). Efforts to close gender gaps in negotiation typically focus on either fixing the women (e.g. lean-in recommendations, improvements to women’s negotiation skills) or fixing the institution (e.g. banning negotiations, banning salary history information, imposing transparency regulations). Evidence points to more effective closure of gender differences through “fix the institution” policies and programmes (Recalde and Vesterlund, 2020[152]).

• Discrimination: In 2017, 13% of men and 8% of women believed it was acceptable in some circumstances for a woman to be paid less than a man for the same job (see Online Annex Figure 5‑A18) (European Union, 2017[63]). This means that outright discrimination against women cannot be ruled out as an explanation for the gender wage gap. Indeed, gender-based discrimination (in job and salary offers) has been illustrated in audit studies (OECD, 2023[154]) and a recent meta‑analysis finds that discrimination affirms existing occupational segregation (Galos and Coppock, 2023[155]). Other research comes to a similar conclusion, with women suffering large discrimination penalties in men-dominated professions (Kübler, Schmid and Stüber, 2018[156]). Discrimination and bias may also be particularly challenging around maternity and motherhood (Arena, Volpone and Jones, 2022[157]).

Gender gaps may additionally exist for other income sources and assets beyond earnings, such as government transfers, self-employment income, capital income, property and wealth (Box 5.11). But estimating gender differences in other sources of income and in assets can be challenging. Standard methods typically pool and equally distribute income and assets amongst all family members, but recent research has challenged this assumption, showing that equal income sharing may not be guaranteed within a household (European Commission, 2013[158]). There may also be important intra-household considerations around the control of assets. Irrespective of ownership status, power dynamics and differences in financial knowledge within couples can affect the actual economic control of assets and the benefits derived from them.

Box 5.11. Looking beyond earnings to income and wealth

Much recent research points to a gender gap in wealth. In a paper linking administrative data in Estonia, for example, the unconditional gender gap in mean wealth is estimated at 45% (Meriküll, Kukk and Rõõm, 2020[159]). Using various methodological approaches, gender wealth gaps have also been found in other EU and OECD countries, including Germany, France and Italy, and others (Sierminska, Frick and Grabka, 2010[160]; Kent and Ricketts, 2021[161]; Bonnet, Keogh and Rapoport, 2013[162]; D’Alessio, 2018[163]; EIGE, 2024[164]). Recent evidence from Germany finds that gender wealth gaps are the largest between women and men at the top, suggesting that the transfer of business and financial assets from parents may be strongly gendered (Trinh, 2024[165]). This paper shows that if transfers were simply allocated equally, the gender wealth gap for these well-off individuals could be reduced by about 40%. Other evidence from Germany shows that the gender wealth gap varies notably by age, remaining quite small up to the age of 40, widening until retirement, and then declining thereafter. This reflects that “men tend to inherit larger sums of money during their working lives,” but also that “women tend to outlive their partners, thus receiving larger inheritances at older ages” (Bartels, Sierminska and Schröder, 2024[166]).

Marital property regimes are another important factor that may contribute to and explain gender wealth gaps, as shown by Frémeaux and Leturcq (2022[167]) in the case of France.

Box 5.12. Spotlight on intersectionality: Disability and the gender wage gap

People with disability face significant barriers to entry into the labour market and these barriers may intersect with gender. In Canada, for example, participation rates for people with disability stood at 51% in 2023, compared to 70% for people without disability. For women with disability, participation rates were 49%, compared to 53% for men with disability. Challenges arise not only with participation rates, but also with earnings. Compared to men without disability, men with disability earn 4% less. For women without disability, the gap stands at 13%. For women with disability, the gap grows even further to 17%, with the average woman with disability earning only CAD 29.81 per hour, compared to CAD 36.04 per hour for the average man without disability.

Source: Statistics Canada (2024[168]), Labour market characteristics of persons with and without disabilities, 2023.

5.1.3. Later and older adulthood: Gendered labour supply and retirement patterns

Older women tend to do less paid work than older men

Gender gaps in labour supply remain high among older workers. In the OECD, for instance, gender gaps in employment rates are among their highest for those aged 60‑64 years, while gender gaps in part-time employment rates are among their highest for those aged 65‑69 years and 70‑74 years (Figure 5.9).

Figure 5.9. Gender gaps in labour supply remain among older workers

Employment rates (Panel A) and part-time employment rates (Panel B), percent (%), women and men by age group and gender gap in employment rates (Panel C) and in part-time employment rates (Panel D), percentage points, men less women, OECD, 2023

Note: Data refer to pre‑calculated averages available in online tables. Data for full- and part-time status refer to employees only. Data for this figure can be downloaded via Annex 5.A.

Source: OECD Data Explorer “Incidence of full-time and part-time employment based on OECD-harmonised definition” (https://data‑explorer.oecd.org/s/16s) and “Employment and unemployment by five‑year age group and sex – levels” (https://data‑explorer.oecd.org/s/16r).

Explaining gender gaps in labour supply between older women and older men

Gender stereotypes and norms around unpaid care and household responsibilities play a large role in explaining differences in labour supply between older women and older men. Older women, for example, are more likely to exit the labour market earlier than men (OECD, 2023[169]), and this earlier exit may reflect unpaid care responsibilities for grandchildren. More specifically, becoming a grandmother appears to have a large negative effect on labour supply (Frimmel et al., 2020[170]; Backhaus and Barslund, 2021[171]; Gørtz, Sander and Sevilla, 2024[172]), with some research finding stronger effects when grandmothers live close to their grandchildren and when there is little or low availability of formal childcare (Frimmel et al., 2020[170]; Backhaus and Barslund, 2021[171]). By comparison, the labour supply of men does not significantly adjust to becoming a grandfather. In fact, grandmothers who are younger, fitter, and healthier may be the most likely to exit the labour force to provide care for grandchildren, but they are also the same women that governments want to encourage to remain in the labour force longer (Glaser et al., 2013[173]).

Older women are also more likely to be providing unpaid care to older relatives (e.g. parents, siblings) or relatives with a disability, which can interfere with paid work. Indeed, in EU‑23 countries, older women represent 62% of those providing daily unpaid care (see Online Annex Figure 5‑A19) (OECD, 2021[128]). In a special module of the EU-LFS in 2018 on care responsibilities, older women were more likely than older men to report that caregiving for an incapacitated relative resulted in a work interruption or a reduction in hours worked (Figure 5.10).

Figure 5.10. Older women experience negative labour supply effects due to caregiving for incapacitated relatives

Share (%) of women and men (55‑64) with care responsibilities reporting a work interruption or a reduction in work hours due to care of incapacitated relatives, 2018

Note: EU‑27 average is weighted. “No response” and “Never had care responsibilities” are excluded from the denominator. Data for this figure can be downloaded via Annex 5.A.

Source: Eurostat “Persons in employment or with previous employment experience by effects of care of incapacitated relatives on employment and educational attainment level” (https://doi.org/10.2908/LFSO_18REDSTED).

Gender differences in the impact of caregiving may reflect gender differences in the intensity of care, as well as the type of tasks undertaken. In Canada, for example, men have been shown to participate in “masculine” activities that are more flexible, less regular and demand less time, such as house maintenance and outdoor work, while women are found to participate in “feminine” activities that may be more time intensive and often must be completed on a regular basis or on a set schedule, such as personal care, appointment and medication management, and emotional support (Statistics Canada, 2022[174]).

Another potential factor that may explain gender differences in labour market outcomes among older workers is the intersection of ageism and sexism, with research suggesting that women are perceived as never of the right age – either being too old or too young. In a study in Australia, for example, older women are more likely than older men to be perceived by their peers as “having outdated skills, being slow to learn new things, or doing an unsatisfactory job” (State of Victoria, 2023[175]). Limited or no workforce accommodations for menopause may also negatively impact women, especially when there are “restricted access to toilets, inability to control ventilation and air conditioning, restrictive workwear, and uncomfortable workstations” (State of Victoria, 2023[175]). Similar findings emerge in a survey in the United Kingdom, where over 27% of employed women aged 40‑60 years with menopause symptoms state that such symptoms negatively impacted their career progression, and 17% reported having considered leaving work due to a lack of support in relation to their symptoms (CIPD, 2023[176]). Indeed, recent research finds that menopause leads to a “persistent decline in employment and earnings, along with a greater dependence on social transfers,” but that “greater menopause awareness and improved access to menopause‑related healthcare can help to mitigate its economic costs” (Conti et al., 2025[177]).

Government policy around pension eligibility can further contribute to gender differences in retirement. In Hungary, for example, women can retire early (before reaching the statutory retirement age) with full benefits through a programme called Women‑40. The minimum period of gainful activity is 40 years, but this can fall to 32 years when accounting for caregiving breaks. Men do not have access to such an early retirement option. In 2022, about half of all women in Hungary were using the Women‑40 scheme, leading to notable gender disparities in the effective retirement ages and employment rates for people above age 60 years (OECD, 2024[178]).

Women spend more years in retirement…

Given that women work less, on average, during prime childbearing and childrearing years and are more likely to exit the labour market at earlier ages, they end up having shorter total working lives than men. Indeed, across EU‑27 countries, women work, on average, 36 years of their lives, while men work, on average, 39 years (see Online Annex Figure 5‑A20) (Eurostat, 2024[179]). Earlier retirement combines with longer life expectancies to mean that women spend more years in retirement than men. Across OECD‑38 countries, for instance, women spend 23 years in retirement, compared to 18 years for men (see Online Annex Figure 5‑A21) (OECD, 2023[169]).

…with less pension income

Pension levels for women in OECD countries are, on average, 24% below those of men (Figure 5.11) (OECD, 2021[180]; 2022[181]) and older women are at higher risk of poverty and social exclusion than are older men (see Online Annex Figure 5‑A22) (OECD, 2023[169]).1

Since income levels and pension gaps are estimated for those currently over the age of 65 years, improvements in gender equality in recent decades, especially in labour force participation and in earnings, mean that pension gaps will likely decrease over time. But as long as women earn and work less than men and exit the labour force more often and earlier than men, pension gaps will remain. It is not entirely surprising, then, that in the 27 countries that participated in the 2022 OECD Risks that Matter Survey, 80% of women reported concerns about not being financially secure in old age, compared to 70% of men. Similar results emerge in the 2024 OECD Risks that Matter Survey.

Figure 5.11. Pension gaps persist in all EU and OECD countries

Gender gap in pensions, women and men (65+) (among pension beneficiaries), 2018 or latest year

Note: EU‑22 and OECD‑34 are unweighted averages. The gender gap in pensions is calculated as the difference between the mean retirement income of women and men over the mean retirement income of men, among pension beneficiaries. Calculations are based on the LIS, except for France, Latvia and Portugal, where the HFCS (Wave 3) was used; and Iceland, Sweden and Türkiye where results come from the EU-SILC (published on Eurostat’s website). Data for all EU countries are from 2022. Data for Switzerland, Türkiye and the United States are from 2021. Data for Canada, Colombia, Japan, Norway and the United Kingdom are from 2020. Data for Australia and Iceland are from 2018. In Belgium when partner A’s pension rights are less than 25% of those of partner B, the pension of A is not paid out and B receives a family pension (calculated at 75% of wages instead of 60%). Data for this figure can be downloaded via Annex 5.A.

Source: Figure 6.9 from OECD (2023[169]), see https://stat.link/e13h5q.

Although public pension systems now provide care credits for time away from work for family leave in many EU and OECD countries, such care credits only partially cushion the impact of childcare‑related employment breaks for many workers. This is because pension credits may not fully match the level of contributions the individual would have made while still working, may only cover some years of employment breaks and may only apply to public pension schemes, not to private or occupational schemes (OECD, 2022[181]). In addition, in some countries, working part-time – which women are more likely to do – may mean that a worker is not even eligible to participate in retirement savings plans. Gender differences in behaviour and social and cultural norms may also play a role, such as women’s higher risk aversion, lower financial literacy and lower engagement in retirement planning and decision-making (OECD, 2021[180]). To top it all off, older women are more likely to outlive their spouses and subsequently live alone, which is linked to a higher risk of poverty and social exclusion (Eurostat, 2024[182]).

Box 5.13. Additional data sources on gender equality in paid and unpaid work

Beyond the indicators presented in this chapter and in the Online Annex, relevant data sources include:

• OECD Dashboard on Gender Gaps: Presents key indicators on gender inequalities in education, employment, governance and private and public leadership.

• OECD Employment Database: Provides up-to-date statistics for making comparisons between countries and identifying trends over time.

• OECD Family Database: Collects national and international sources to present key indicators on the structure and the labour market position of families and related public policies.

• OECD Employment Outlook: Provides annual insights into ongoing and forthcoming issues related to employment, most recently covering issues relating to artificial intelligence, inclusive labour markets, COVID‑19 and the future of work.

• OECD Pensions at a Glance: Provides annual insights into pension systems across OECD countries, including regular updates on gender gaps in pension earnings.

• European Institute for Gender Equality (EIGE)’s Gender Statistics Database: Contains information on employment, labour market policies, working conditions and work-life balance, among other key topics related to the labour market.

• International Labour Organization (ILO)’s ILOSTAT: Provides statistics on labour markets for a wide range of countries around the world.

• 2017 and 2024 Eurobarometer Surveys on Gender Stereotypes: Present statistics from EU countries on gender stereotypes at home, in the workplace and in leadership.

• World Values Survey: Explores opinions and attitudes toward women at work and in politics.

• Eurofound’s European (Telephone) Working Conditions Surveys (E(T)WCS): Present insights into questions pertaining to working conditions, including factors associated with job quality, such as work organisation, access to and use of learning and training, prevalence of physical and psychosocial risk factors, occupational health and safety and work-life balance.

• Eurofound’s European Quality of Life Survey (EQLS): Contains data on perceptions of quality of life, society and public services.

• Women, Business and the Law: Provides information on laws pertaining to women’s ability to enter or remain in the labour force, work after childbirth and start and run a business, as well as occupational segregation, the gender wage gap, pensions, the provision of early learning and childcare and sexual harassment in the workplace.

• OECD Social Institutions and Gender Index: Contains data on laws, norms and practices relating to discrimination in the family, restricted physical integrity, restricted civil liberties and restricted access to productive and financial resources.

• OECD Time Use Database: Documents gender differences in time allocation over different daily activities.

5.2. Policy combinations to advance gender equality in paid and unpaid work

Using Table 5.1, this section applies the priority considerations of the conceptual framework included in Chapter 3 to advance gender equality by exploring four examples of policy goals (priority consideration 1): gender equality in paid and unpaid work (Outcome A), entrepreneurship (Outcome B), pay (Outcome C) and pension income (Outcome D). These goals need to be accompanied by a results framework (priority considerations 1 and 4), whose indicators can be drawn from those presented in Section 5.1 and additional sources.

Table 5.1 is designed to assist policy makers in identifying the range of cross-portfolio policy and programme combinations (priority consideration 3) and planning for their evaluation (priority consideration 2). While the list of policy options is extensive, it does not pretend to be exhaustive. At the same time, not all policy options apply in all settings or contexts. Overall, Table 5.1 aims to encourage the consideration of different policy options as part of a cross-sectoral and multi-stakeholder approach that works towards the achievement of gender equality outcomes.

Work-life balance policies – e.g. access to high-quality affordable childcare and long-term care, access to well-paid parental leave, systems to ensure pay equity – are a key example of policy combinations supporting gender equality not only across paid and unpaid work, but also leadership, health, educational attainment and skills and more. Many countries have taken steps in these directions, with major policy developments in EU countries spurred by the recommendation on the revised Barcelona targets on early learning and childcare for 2030 (European Union, 2022[183]), the recommendation on affordable high-quality long-term care (European Union, 2022[184]), the EU Work-Life Balance Directive and the EU Pay Transparency Directive (Box 5.14). As countries face demographic headwinds that will likely increase the care burden, policies supporting better access to and affordability of childcare and long-term care will be increasingly crucial (Frey, Hyee and Thomas, 2024[56]). Policies encouraging greater take‑up of leave around childbirth by fathers are also particularly important as they help to challenge gender stereotypes and norms.

For these key work-life balance policies to fully contribute to gender equality, they need to be complemented by other interventions. Closing gender gaps in entrepreneurship, for example, requires entrepreneurship ecosystems ensuring that women-owned and operated businesses have access to entrepreneurship assistance, networks, mentorship, counselling, knowledge and financial support, incubators and accelerator programmes. Moreover, closing gender gaps in pension income requires policy action such as offering credits to offset the negative impacts of care‑related leave on pension entitlements or earnings.

Table 5.1 also highlights the important feedback loops between policy goals. Occupational segregation, for example, contributes to gender gaps in pay, pensions, leadership and representation (see Chapter 6) and to gender differences in the impacts of the green and digital transition (see Chapter 9). Gender differences in labour market outcomes may also reflect that women are more exposed to gender-based violence, including sexual harassment in the workplace (see Chapter 8) and may receive limited support for gender-specific health challenges, such as menopause (see Chapter 7).

Box 5.14. EU Directives on Work-Life Balance and Pay Transparency

EU Work-Life Balance Directive

The EU Work-Life Balance Directive (European Union, 2019[185]) grants fathers (or “second parents”) at least ten working days of paternity leave around birth, paid at least at the level of national sick leave benefits. Each parent has an individual right to four months parental leave, of which at least two are non-transferable. During the two non-transferable months of parental leave for each parent, an adequate payment or allowance has to be provided, the level of which is to be defined at the national level. The Directive also establishes that all workers have the right to at least five working days of carers’ leave per year, and that all parents with children under at least the age of eight years, and all carers, will have the right to request flexible working arrangements for caring purposes. Member States have been required to comply with this Directive since August 2022, though the shape and form of different countries’ approaches has varied considerably (Zumbyte and Szelewa, 2024[186]).

EU Pay Transparency Directive

The EU Pay Transparency Directive (European Union, 2023[187]) establishes minimum rules to reinforce the principle of equal pay for equal work or work of equal value, the prohibition of direct or indirect gender-based pay discrimination, and pay transparency. Member States must establish these provisions by June 2026.

The Directive establishes that employers will be requested to provide information about the initial pay level or its range in job vacancy notices or before the job interview. Moreover, workers will have the right to request information from their employer on pay levels, disaggregated by gender, for workers doing the same work or work of equal value. Employers of certain sizes will need to report on the gender pay gap by categories of workers doing the same work or work of equal value. If a report shows a gender pay gap greater than 5% that cannot be justified by objective, gender-neutral criteria, the company must conduct a joint pay assessment with worker representatives to address the disparity. This is similar to the concept of an equal pay audit (OECD, 2023[154]). The Directive also mandates better access to justice for victims of pay discrimination.

As of mid‑2023, 21 of 38 OECD countries required certain private sector firms to report on their gender pay gap. Most reporting rules are less than a decade old, with 12 countries enacting new rules or amending existing ones between 2020 and 2023 (OECD, 2023[154]). Much progress has taken place in the EU, reflecting the EU’s 2014 recommendation on equal pay through transparency, but novel policy practices have also occurred in countries as diverse as Australia, Canada, Chile, Israel, Japan, Korea, the United Kingdom and some US states (see Online Annex Figure 5‑A23) (OECD, 2023[154]).

The effectiveness of the policies and programmes outlined in Table 5.1 varies across countries and across time. Continuous monitoring and evaluation that incorporates a gender perspective (priority consideration 5) is essential for governments to understand the gendered effects of policies and programmes (see Chapters 2 and 3); ensure that policies and programmes are achieving their intended outcomes; identify strengths and areas for improvement; improve decision-making, resource allocation and accountability; and inform future strategies (priority consideration 6). While international evidence offers valuable insights on similar interventions, the effectiveness of each policy and programme will depend on their specific design and context – including interactions with other interventions, socio-economic and cultural factors, available resources, and institutional settings.

For example, in the field of paid and unpaid work, extensive research across countries has shown that access to affordable, high-quality ECEC effectively enables women’s labour force participation (Bettendorf, Jongen and Muller, 2015[188]; Baker, Gruber and Milligan, 2008[189]; Bauernschuster and Schlotter, 2015[190]; Goux and Maurin, 2010[191]; Martínez A. and Perticará, 2017[192]) and can contribute to gender equality in work and care (Müller, Neumann and Wrohlich, 2018[193]). Additionally, ECEC contributes to improved cognitive and non-cognitive development among children, particularly those from disadvantaged backgrounds (OECD, 2021[122]). Numerous studies have also analysed the impact of paid family leave – including maternity, parental and paternity leave – on parents and children. Findings indicate that paid family leave contributes to better maternal and child health (Van Niel et al., 2020[194]), as well as stronger maternal labour force attachment and increased maternal labour supply (up to a point) (Canaan et al., 2022[195]). Paternity leave can additionally contribute to a higher involvement of fathers in unpaid work within their family (Tamm, 2019[196]; Knoester, Petts and Pragg, 2019[197]) and fathers who take leave are more likely to be involved in unpaid responsibilities well beyond the actual period of leave (Tamm, 2019[196]; Huerta et al., 2014[198]; OECD, 2019[27]). This may have downstream impacts far into the future as the new generations will be exposed to a more gender equal distribution of paid and unpaid work in the household (Fontenay and González, 2024[199]). However, the design of these policies is crucial, as poorly structured leave can negatively affect women’s labour supply, maternal human capital development and career progression (Canaan et al., 2022[195]). Furthermore, Corekcioglu, Francesconi and Kunze (2024[200]) find no link between leave policies and women’s representation in leadership nor measurable impacts on pay gaps.

Looking at interactions family policies, support systems providing a “continuum of supports” – integrating parental leave, childcare, pre‑school, school, and after-school care – are shown as most effective at reconciling work and family life, boosting birth rates, and enhancing employment predictability (OECD, 2007[201]). However, such comprehensive systems entail high public expenditure and tax levels, making them challenging to implement universally. Other reviews of policy combinations in EU countries show the relevance of the universal caregiver model, which comprises moderate parental leaves, the presence of fathers’ incentives through paid leave, and high levels of perceived affordability and availability of childcare (Lauri, Põder and Ciccia, 2020[202]).

The design of income taxes also affects financial incentives to engage in paid work. While the progressivity of personal income taxes contributes to reduce post-tax income gaps between women and men, as well as between full- and part-time workers, the tax system can also create disincentives for second earners (often women) to (re‑)engage in paid work, or to shift from part- to full-time work (Thomas and O’Reilly, 2016[203]; OECD, 2023[21]). Such effects may derive from joint taxation, which results in second earners paying higher marginal tax rates on their income, or from the removal of family-based allowances or tax credits when the second earner enters the labour force. Yet, routine evaluation of gender outcomes in tax policy processes remains uncommon (OECD, 2022[75]). Evaluation practice is also not systematic when it comes to gender pay gap reporting regimes, as only a few national systems have been evaluated quantitatively, with heterogenous conclusions on effectiveness (OECD, 2023[154]).

5.2.1. Key policy actions across EU and OECD countries

Table 5.1. Existing policy options to tackle gender gaps in paid and unpaid work (Outcome A), entrepreneurship (Outcome B), pay (Outcome C) and pension income (Outcome D)

Outcomes	Policy options	Likely Ministries Involved									EU and OECD country examples
		Education – Culture	Labour – Social – Family	Health – Sports	Economy – Finance	Science – Technology – Digital	Env. – Agri. – Transport – Energy	Foreign – Defence – Interior	National Statistical Offices	Gender – Justice – Human Rights
Challenge gender stereotypes and norms
A, B, C, D	Implement initiatives for girls and boys and women and men to pursue education and careers in non-traditional and high-demand sectors to combat horizontal segregation (see Chapter 4).	X	X	X	X	X	X	X	X	X	Many countries
A, B C, D	Launch awareness campaigns on issues relating to gender equality in the labour market, such as equal sharing of unpaid care work, gendered use of flexible working arrangements, gender wage gaps and barriers faced by women entrepreneurs.	X	X							X	Many countries
Provide opportunities for learning and skills development
A, B C, D	Provide adult and lifelong learning opportunities, including targeted training programmes in entrepreneurship and in high-demand sectors, especially for women returning to the workforce after career breaks or for mothers who have not yet acquired a profession (see Chapter 4 and Chapter 9).	X	X			X	X			X	AUS, CHL, CRI, HUN, JPN, KOR, MEX, MLT, NOR, ROU
B, D	Invest in programmes and digital tools to improve financial literacy, including in topics such as investment strategies, international trade and finance and retirement planning.	X	X							X	AUS, AUT, DEU, ITA, SWE, TUR
B	Integrate entrepreneurship education into school curricula and higher education courses, ensuring that programmes tackle gender norms and stereotypes and equally encourage girls and boys to pursue entrepreneurial paths.	X	X							X	MEX
Support gender equality with labour laws
A, C, D	Implement legislation guaranteeing equal treatment of women and men workers (e.g. ratification of ILO Convention 156) and protecting women from gender-based discrimination in employment and entrepreneurship.		X							X	Many countries
A, C, D	Introduce legislation to ensure equal pay for work of equal value and/or implement pay transparency mechanisms to illuminate pay gaps and support corrective actions.		X							X	Many countries
A, C, D	Increase minimum wages to boost earnings of women, who are overrepresented in low-paid occupations and industries.		X							X	Many countries
C, D	Prohibit employers from asking job applicants about salary history during wage setting.		X							X	AUT, CAN
C, D	Develop and encourage the use of gender-neutral job classification systems and salary scales – and supporting software – to enable employers to undertake pay analyses and implement pay transparency and pay equity legislation.		X							X	BEL, CAN, CHE, CRI, CYP, DEU, ESP, FIN, FRA, ISL, ISR, MLT, POL, PRT, SVK
Foster better work-life balance
A, C, D	Ensure all workers have a right to disconnect and/or a right to request flexible working opportunities (e.g. part-time, telework) and return to full-time work, promoting and incentivising equal take‑up among women and men.		X							X	BEL, CAN, CYP, DEU, ESP, FRA, GRC, HRV, ITA, KOR, LUX, PRT, SVK
A, B C, D	Provide well-paid parental and paternity leave, including to entrepreneurs, and support greater take‑up by fathers.		X							X	Many countries
A, B C, D	Support access to care and non-care household services (e.g. cleaning, laundry, gardening and cooking) by, for example, reducing costs and formalising services.		X		X					X	AUT, BEL, CAN, DEU, ESP, FIN, FRA, ITA, LUX, NLD, SWE
A, C, D	Ensure access to (well-paid) short-term leave for caregiving (e.g. sick child), promoting equal take‑up by both parents.		X							X	AUS, CHE, HUN
A, C, D	Provide leave options for carers of family members with disability or long-term illnesses that enable caregivers to return to paid work, promoting equal take‑up by women and men.		X							X	AUS, CAN, CHE, FRA, HUN, ITA, JPN, LTU, LVA, MEX, NOR, PRT, USA
Build strong and comprehensive care infrastructure
A, B C, D	Provide high-quality flexible, accessible and affordable childcare, including out-of-school care, and long-term and elderly care, including independent living solutions.	X	X	X						X	Many countries
A, C, D	Implement targeted pay raises (e.g. via sector-specific minimum wages) particularly in low-pay, women-dominated industries and occupations, such as health and social care.		X	X						X	AUS, HUN
Build gender-sensitive tax-benefit systems
A, B C, D	Carefully design and review tax systems, tax-based supports and cash benefits to ensure an appropriate balance between adequate income support and minimal work disincentives (especially for second earners).		X		X					X	CAN, CYP, FRA, JPN, MLT
Ensure gender-equitable pensions and savings behaviours
D	Implement tax-based incentives (e.g. credits), awareness campaigns and/or behavioural insights (e.g. auto‑enrolment) to increase private pension contributions, ensuring equal take‑up among women and men.		X		X					X	CAN, CZE
D	Provide basic or minimum pensions to older people with low contributory pensions, striking a balance between adequacy and work incentives, including recognising unpaid caregiving.		X		X					X	COL, ESP, MEX
D	Provide suitable and time‑limited care credits to offset the negative impacts of care‑related leave on pension entitlements or earnings.		X		X					X	Many countries
D	Design spousal pension rights carefully (e.g. split pension benefits upon divorce, survivor’s benefits, etc.) to ensure that partners who do more unpaid work (and less paid work) are fairly compensated in retirement without creating significant work disincentives.		X		X					X	CAN
Design inclusive social protection systems
A, C, D	Ensure equal worker rights for non-standard workers, including self-employed, part-time and temporary workers.		X							X	CAN, CZE, DNK, ESP, FRA, JPN, NOR
C, D	Implement mandatory or “opt-out” social security contributions for non-standard workers.		X		X					X	DEU, ITA
Encourage gender equality within firms
A, C, D	Encourage companies to offer flexible working arrangements (e.g. part-time, flexible hours, teleworking and job sharing), ensuring that access to and use of such arrangements does not reinforce gender norms and stereotypes.		X							X	CHE, CRI, GRC, HRV, HUN, ITA, JPN, KOR, LTU, NZL, PRT, SLV
A, C, D	Encourage employers to limit long working hours and implement and enforce caps on working time.		X							X	AUS, KOR
A, C, D	Support employers as they transpose new legislations and regulations on gender equality and as they embed gender equality into their workplace policies and practices.		X							X	CHE, CYP, CZE, ESP, FRA, HUN, JPN, LUX, MLT, POL
A, C, D	Support women’s career advancement to leadership positions through mentorship, training and career development programmes, as well as through quotas, voluntary targets and complementary measures (see Chapter 6).		X							X	Many countries
A, C, D	Create sectoral action plans for the improvement of gender equality, including linking sector-specific government support (e.g. grants, financing, subsidies) to workplace policies or standards that promote gender equality, especially in industries not traditionally associated with women and where gender gaps are the largest.	X	X	X	X	X	X	X	X	X	AUS, GBR, HRV
C, D	Encourage, support or mandate the discussion of gender equality, including equal pay, during collective bargaining.		X							X	AUT, BEL, BGR, CAN, CHL, CRI, DEU, ESP, FRA, ISL, POL, SWE
Build supportive environments for women entrepreneurs
B	Strengthen entrepreneurship ecosystems, ensuring that women have access to entrepreneurship assistance, networks, mentorship, counselling, knowledge and financial supports and incubators and accelerator programmes, including in green and digital sectors.		X			X	X			X	Many countries
B	Offer flexible business support services, such as on-demand consultancy, virtual coaching, and remote networking.		X							X	MEX
B	Increase women entrepreneurs’ access to finance, including through (targeted) soft loans, loan guarantees, dedicated risk capital initiatives, grants, equity investment and/or digital platforms (e.g. fintech, crowdfunding), with governments acting as sponsors, managers, facilitators or funders.		X							X	AUT, CAN, CYP, DEU, ESP, FRA, GBR, HRV, HUN, IRL, ISL, ITA, KOR, TUR
B	Support networks of venture capitalists and business angels at the subnational, national and international levels focused on investing in women-owned business.		X							X	BEL, ESP, FRA, GBR, ITA, PRT
Ensure accountability and good governance
A, C, D	Introduce simple processes for reporting (perceived) discrimination in pay, hiring and advancement (e.g. embedded within pay transparency systems).		X							X	CZE, FRA
A, C, D	Authorise and train labour inspectors to identify and investigate gender inequality at work, including gender pay gaps, discrimination and sexual harassment.		X							X	BEL, CZE, ESP, FRA, GRC, KOR, ROU, TUR
A, B, C, D	Introduce labels, certifications or awards for companies introducing policies that support gender equality and work-life balance in the workplace (e.g. pay, childcare, family-friendly workplace policies, parental leave, leadership).		X							X	AUT, BGR, CAN, CHL, COL, CRI, CYP, DEU, EST, FRA, GRC, ISL, LTU, MEX, PRT
B	Design and implement procurement systems that advance gender equality (e.g. equal pay).	X	X	X	X	X	X	X	X	X	CHE, JPN, MLT
A, B C, D	Review and design social protection systems, including pension systems, to ensure equal treatment of women and men by using tools from gender mainstreaming (e.g. gender impact assessments).		X		X					X	ESP, JPN, MEX, MLT, SVN
Support women’s health
A, C, D	Provide dedicated leave and support for women to manage menstrual and/or menopausal symptoms, ensuring that such leave and support does not create grounds for discrimination in promotion and retention decisions.		X	X						X	ESP
A, C, D	Provide access to menstrual products in the workplace or reduce their cost (e.g. by reducing the VAT).		X	X	X					X	CAN, CYP, FRA, MLT
A, C, D	Provide women who are lactating with adequate paid breaks and safe spaces to nurse or express milk.		X	X						X	CAN
D	Support healthy ageing to enhance labour force attachment for women and men (see Chapter 7).	X	X	X	X	X	X	X	X	X	Many countries
Protect women and foster safety
A, B, C, D	Combat workplace harassment and violence through prevention, early intervention, response and recovery programmes, ensuring adequate detection and reporting of instances of harassment and violence against women in the workplace, including both for employees and entrepreneurs and including technology-facilitated violence (see Chapter 8).	X	X	X	X	X	X	X	X	X	Many countries
Ensure robust monitoring and evaluation
A, B C, D	Continue to close gender data, research and measurement gaps. Some examples include: pay and earnings, income, wealth; the distribution of work and resources within the household; the evolution of time use over the life course and over time; the pink “tax” and gendered access to goods and services; and the gender distribution of “fringe benefits,” including employer-paid health insurance, family leave “top ups,” additional sick days, vacation days, etc.				X				X	X	Many countries
A, B C, D	Conduct time use surveys frequently to capture the extent and evolution of unpaid work to inform policy related to quality of life, prosperity and gender equality.								X	X	COL, CRI, HUN, ISL, MEX
A, B C, D	Mainstream gender into traditional surveys and/or integrate the care economy into national accounts to better capture gender equality issues (e.g. work-life balance and time use).				X				X	X	MEX

Note: “Env.” stands for Environment and “Agri.” stands for Agriculture.

Source: OECD Secretariat based on desk research and the 2024 OECD Questionnaire on Policy Combinations for Gender Equality, OECD (2022[181]; 2022[204]), Carcillo, Hijzen and Thewissen (2023[205]), Kassam (2024[206]), Deutsche Rentenversicherung (n.d.[207]), OECD (2021[54]) and European Union (2015[208]; 2018[209]; 2019[210]; 2022[211]).

5.2.2. Country case studies of key policy combinations in EU and OECD countries

According to the OECD Secretariat’s 2024 Questionnaire on Policy Combinations for Gender Equality, many EU and OECD countries have implemented policy combinations to advance gender equality in paid and unpaid work. Case studies are provided below, alongside examples of building intersectionality considerations into policy combinations.

Reducing gender gaps in paid and unpaid work

• Colombia has launched initiatives to recognise and address the unpaid care work traditionally shouldered by women. The National Development Plan 2022‑26 prioritises care as vital to social and economic sustainability, leading to the creation of the National Care System. This system aims to recognise, reduce, and redistribute paid and unpaid care work through a shared responsibility model involving the state, private sector, civil society, families, communities and both women and men. This builds on earlier efforts, such as Law 1 413 of 2010, which integrated the care economy into national accounts, and the creation of intersectoral commissions to co‑ordinate care‑related actions. This care‑focused approach is also central to Colombia’s Strategy for Women’s Economic Empowerment in Disadvantaged Areas, which combines measures supporting income generation and economic autonomy. These efforts involve multiple ministries (including Education, Labour, Commerce, Industry and Tourism, and Culture) and women’s organisations. Additionally, the Pension Bond for Community Mothers provides financial recognition to women who have spent over a decade in unpaid caregiving roles within their communities. It offers a subsistence subsidy of 80‑95% of the minimum wage to those who may not meet traditional pension eligibility requirements, acknowledging their economic contributions and addressing pension access inequalities.

• Korea is committed to enhancing gender equality in the workplace as part of its broader national agenda, reflected in the Third Basic Plan for Gender Equality Policy (2023‑27). One key initiative is the establishment of Women’s Re‑employment Centres to support women re‑entering the workforce after career breaks. These centres offer career counselling, job matching and vocational training, helping women regain economic independence and reduce the gender employment gap. Korea has also introduced family-friendly policies such as expanded parental leave and flexible working arrangements. Combined with pay transparency measures and interventions aimed at increasing women’s representation in leadership, these policies are expected to create the basic conditions and incentives for women to be able to engage more equally and fully in paid work.

• Cyprus’ Gender Equality Strategy combines policies supporting work-life balance and equal pay to reduce gender gaps in employment. The Ministry of Social Welfare, for example, has supported the creation and upgrading of childcare centres and the Ministry of Education, Sports and Youth has introduced compulsory pre‑primary education from age four. The Ministry of Labour and Social Insurance has introduced a comprehensive policy on work-life balance, including paid parental leave, carer’s leave, and the right to request flexible work for parents and carers. This has been enhanced by extending parental leave benefits to self-employed parents and increasing maternity leave from 18 to 22 weeks for the first child. Indeed, as of 30 December 2025, the age limit for each child for which parents are entitled to take parental leave is increased from 8 years of age to 15 years of age, with immediate effect. And effective March 2025, the duration of the 8 weeks of parental leave also increases gradually, as follows: 10 weeks for the second; 12 weeks for the third; and 14 weeks for the fourth and each subsequent child. The age limit for children with disabilities is increased from 18 to 21 years. At the same time, the “National Certification Body for the Implementation of Good Practices on Gender Equality at the Workplace,” established by the Ministry of Labour and Social Insurance, promotes gender equality by recognising and certifying workplaces committed to equitable pay and practices. Analyses of the gender pay gap (by the Ministry of Labour and Social Insurance) and job evaluations (by the Office of the Commissioner for Gender Equality) aim to further address structural pay inequalities.

Box 5.15. Spotlights on intersectionality: Migrant women

Several governments have introduced tailored interventions to address the specific labour market disadvantages faced by migrant women. Examples include:

• Targeted employment programmes (e.g. career guidance, counselling, networking, language training, interview practice and job application supports) for migrant women (e.g. Canada (IRCC, 2019[212]), Germany (European Union, 2016[213]) and Sweden (European Union, 2017[214])).

• Dedicated action plans supporting migrant women’s labour force participation (e.g. Finland).

• Affordable childcare services for users of integration centres and those attending employment programmes (OECD, 2017[215]).

• Culturally-sensitive childcare for migrant parents who want to ensure their children are connected to their culture and language in their early years (Valdivia and Adsera, 2023[216]).

• Interventions to formalise domestic work, where low-skilled migrant women are often overrepresented (e.g. Costa Rica, France, Korea, Mexico and Spain) (OECD, 2021[54]).

Source: OECD Secretariat based on the 2024 OECD Questionnaire on Policy Combinations for Gender Equality.

Box 5.16. Time use surveys to measure gender gaps in paid and unpaid work

Time use surveys are invaluable tools for understanding how individuals allocate their time across various activities. Using time diaries, information on daily activities is re‑coded into a set of descriptive categories, so that a 24‑hour period can be split into a sequence of time spent on main activities (OECD, 2016[217]). These surveys can reveal disparities in how women and men spend their time, especially regarding unpaid work, caregiving, and leisure. However, the irregularity and infrequency of these surveys pose a challenge, as consistent data collection is essential for tracking progress and adapting policies effectively.

Recent developments illustrate the significance of these surveys in informing gender equality policies.

• Hungary conducted its last time use survey in 2009‑10 to serve multiple purposes, such as supporting family policy, informing working hour regulations, and assisting in the development of national accounts related to household production. A new survey is planned for 2024‑25.

• Iceland recently conducted its first time use survey, aiming to capture the extent of unpaid domestic and care work.

• Eurostat has run two rounds of surveys for the harmonised European time use surveys (HETUS). The first round was conducted between 1998 and 2006 in 15 European countries, while the second round was conducted between 2008 and 2015 in 18 European countries. A third round is in progress, with the data collection phase concluding in 2026. About 20 European countries plan to conduct a time use survey during this third round (Eurostat, n.d.[218]; n.d.[219]).

• Mexico obtains insights through its regular National Survey on Time Use and the National Survey for the Care System. Although Mexico’s National Survey on Time Use uses a different methodological approach (which may affect international comparability), the survey was declared “Information of National Interest” in 2022, meaning that is must be carried out periodically and be used by government for public policies (Government of Mexico, 2022[220]). This is an important step in ensuring that time use considerations – including around both paid and unpaid work – are reflected in government action.

To help enhance the visibility of the importance of time use surveys and facilitate cross-countries comparisons, the OECD Time Use Database provides information on time use patterns for women and men across 30 OECD countries according to five main categories: unpaid work; paid work or study; personal care; leisure; and other time use.

Note: Differences in survey features, the number of diary days sampled, and the categorisation of activities may affect the cross-country comparability of results in the OECD Time Use Database.

Source: OECD Secretariat based on the 2024 OECD Questionnaire on Policy Combinations for Gender Equality and OECD Time Use Database (www.oecd.org/en/data/datasets/time‑use‑database.html).

Ensuring gender equality in entrepreneurship

• Germany’s Action Plan “More women entrepreneurs for our SMEs” packages measures from 41 different players – federal ministries, associations, networks and academic institutions – to highlight the achievements of women in SMEs, skilled crafts and startups; motivate more women to go into business; establish a joint platform for measures supporting women entrepreneurs in various fields; and enhance the visibility and impact of individual measures. Many of the entrepreneurship support measures are built to consider the personal situations of women (e.g. the higher burden of care provision or the smaller amounts of finance for startup teams which include women). This is complemented by an interministerial initiative focusing specifically on the interests of self-employed women and the compatibility of self-employment and family life – newly launched by the Federal Ministry for Economic Affairs and Climate Action. The Action Plan also targets men (e.g. with grants for childcare services).

• Mexico’s support for female entrepreneurship is exemplified by the “Territorial Strategy for the Reactivation of Autonomy and Economic Empowerment,” which establishes “economic empowerment nodes” in Women’s Development Centres. These nodes offer workshops, counselling, and connections to public and private financing for women entrepreneurs. Specialised staff offer guidance on entrepreneurship, co‑operativism, accounting and digital communication, helping women to strengthen their economic autonomy.

Box 5.17. Spotlights on intersectionality: Rural women entrepreneurs

Women in rural areas may face additional barriers to entrepreneurship, such as limited access to capital and infrastructure, difficulty penetrating men-dominated industries, smaller and less extensive networks, or reduced access to entrepreneurship support programmes (Saavedra, 2024[221]; Yamamura, Lassalle and Shaw, 2022[222]). Several countries have implemented specific initiatives to support rural women, including rural women entrepreneurs.

• Poland introduced a Strategy for Sustainable Development of Rural Areas, Agriculture and Fisheries 2030, led by the Ministry of Agriculture and Rural Development, to support flexible forms of work, counteract discrimination and incentivise longer working lives.

• Through the Icelandic Regional Development Institute, Iceland provides targeted loans for the operation of businesses where women own at least 75% of the shares in rural communities.

• In Croatia, several strategies relating to agriculture have a focus on women in rural areas, including a specific programme that provides employment opportunities to long-term unemployed women in rural areas who are providing care to the elderly and people with disability (OECD, 2022[181]).

• Based on a survey of rural women’s needs, various ministries in Cyprus have committed to design and develop a digital skills training programme for rural women.

• Spain combines awareness raising, counselling, capacity building, skills and competencies training, mentoring and grants to promote women’s entrepreneurship in the green economy and in rural areas, with a special focus on the intersection between the two.

• In Germany, a study on rural women aims to make the achievements of women in agriculture more visible, while also raising awareness of gender-equitable partnership and generational constellations and inheritance patterns; empowering women through the expansion of educational and advisory services; improving the legal and social security of women on farms; providing information on (women-specific) health risks, preventive healthcare and occupational health and safety; and improving public infrastructure and the compatibility of work and family in rural areas.

• In France, in 2023, 83 of the Centers for Information about Women’s Rights (CIDFF) (out of a total of 98) had put in place a special service for women’s integration into the labor market. This service is specifically directed at women in rural or isolated areas and women in precarious or vulnerable situations.

Source: OECD Secretariat based on the 2024 OECD Questionnaire on Policy Combinations for Gender Equality.

Eliminating gender pay gaps

• One of the main objectives of Bulgaria’s gender equality strategy is to reduce gender gaps in pay and income. This is expected to be achieved via a combination of actions: raising public and employer awareness of the gender pay gap and the link between pay, income and social security rights, including pensions; raising awareness of educational and professional opportunities for training and qualification; increasing the adequacy of pensions; and strengthening the role and importance of collective agreements.

• Canada has introduced several measures to reduce gender gaps in pay, including pay transparency and pay equity legislation for federally regulated employers (about 6% of all employees in Canada). These laws require that employers report wage gap information publicly and establish pay equity plans to ensure that women and men receive equal pay for work of equal value. Alongside measures targeting firms, Canada supports households through significant investments in family policies, including the creation of a national childcare system that aims to reduce childcare fees to CAD 10‑a-day by 2026 and improve access by growing the number of childcare spaces. To support lower-income single‑parent families, among which women are overrepresented, the Department of Finance Canada, Canada Revenue Agency and Employment and Social Development Canada also jointly introduced the Canada Child Benefit, which has contributed to lifting more than 653 000 children out of poverty between 2015 and 2021.

• To reduce gender inequality in earnings and income, France combines policies targeting both firms and households, with actions undertaken by the Ministries of Labour, Equality, Economy, Health, Solidarities, and Public Service. At the core of this policy combination is the Professional Equality Index, requiring companies with more than 50 employees to assess the gender pay gap, distribution of pay raises, promotions, and the representation of women among top earners. Low-scoring companies must implement corrective measures within three years or face financial penalties. Managed by the Ministry of Labour, the Index has increased transparency and accountability, with compliance rates rising from 54% in 2020 to 77% in 2024. In 2023, the Ministry of Transformation and Public Service extended the Index to public hospital services, ensuring uniform gender equality standards across sectors. Inter-ministerial efforts, led by the Directorate General for Labour, are underway to review and enhance the Index. Such measures are combined with the individualisation of income tax rates, to be implemented in 2025 by the Ministry of Economy, to promote the economic independence of women and reduce income disparities within households. This policy shift addresses a well-known source of implicit gender bias in tax systems, where joint taxation of household income typically results in higher marginal tax rates for second earners, usually women, disincentivising their labour force participation (OECD, 2023[21]). France also introduced the Rixain law in 2021, which aims to ensure a more equitable representation of women in corporate management bodies by introducing quotas for senior executives and management bodies in large companies by 2030. In addition, schemes such as the Fonds de garantie à l’initiative des femmes (FGIF) facilitate women entrepreneurs’ access to bank financing. In 2021, France signed a 2021‑23 framework agreement in favour of women’s entrepreneurship with the public investment bank Bpifrance, broken down into regional action plans. Another framework agreement was signed in 2021, extending to 2024, between the ministries in charge of Equality and Labour and the public employment service (France Travail) for the integration of women.

Closing gender gaps in pension income

• With initiatives from the Human Rights Directorate and the Ministry for Finance, Malta is introducing policies to ensure equal treatment of women and men. The government is proposing interventions including tax incentives which strengthen women’s participation in the labour market, incentives which entice informal workers to transition to the formal sector, and incentives for women to enter the labour market and become financially independent. Moreover, inland revenue policies, social security policies and gender gaps in pensions are being reviewed and revised to ensure equal treatment between women and men.

• Spain’s Strategic Plan for the Effective Equality of Women and Men 2022‑25 aims to ensure equal access to resources, combat the overrepresentation of women among those in poverty and precariousness, and foster a life‑centred, ecologically and socially sustainable economy focused on care throughout the life course. It addresses gender gaps in earnings across policy areas – including employment (building a quality labour market for women), care and time (promoting the recognition of the right to care and a socially just reorganisation of care and time), resources (fighting against the overrepresentation of women among those in of poverty and precariousness) and ecological and social sustainability (moving towards sustainable living environments). This plan builds on evaluative evidence of the previous gender equality plan, which identified effective actions to close earning gaps in older age – such as a maternity supplement in contributory pensions. Additionally, the Ministry of Inclusion, Social Security and Migration has advanced efforts to close the gender pension gap. Royal Decree‑law 2/2023 equalises part-time jobs (around 75% held by women) with full-time jobs for future social security pensions and allows for temporary positive action for the calculation of benefits in favour of women. Royal Decree‑law 3/2021 introduced a supplement in contributory pensions to reduce the gender gap, acknowledging women’s historical disadvantage in the labour market due to childcare responsibilities. This measure will continue as long as the gender gap in retirement pensions exceeds 5%. Men who can demonstrate reduced contributions due to caregiving responsibilities following the birth or adoption of a child are also eligible for this supplement (Ministerio de Igualdad y Equidad, 2024[223]).

Annex 5.A. List of figures in Online Annex

Annex Table 5.A.1. List of Chapter 5 Online Annex Figures

Figure no.	Figure title and subtitle
Figure 5‑A1	Employment rates for women are more sensitive to the age and number of children in the household Employment rate (%), women and men (25‑54), EU‑26 average, by age of the youngest dependent child (Panel A) and by number of dependent child (Panel B), 2021
Figure 5‑A2	Many people continue to believe women should stay home with the children, even if they earn more Share (%) who disagree that a father should give up work to look after the children if his pay is lower than the mother’s and the family wants a parent to stay home with the children, 2024
Figure 5‑A3	Women are more likely to work part-time than men Part-time employment rates (%) for women and men (15‑64), total employment, 2023
Figure 5‑A4	Women are more likely than men to report negative effects of childcare responsibilities on working hours Share (%) of women and men (25‑64) reporting impacts on employment due to childcare responsibilities, by type of impact, EU‑27 average, 2018
Figure 5‑A5	Women and men tend to have similar unemployment and long-term unemployment rates Unemployment rate (Panel A, percentage) and long-term unemployment rate (Panel B, percentage), women and men (25‑54), 2023
Figure 5‑A6	Many people believe that men are more entitled to a job during periods of job scarcity Share (%) who agree or agree strongly that men should have more right to a job than women when jobs are scarce, 2017‑22 wave of WVS
Figure 5‑A7	Women are more likely than men to engage in unpaid housework and childcare Number of weekly hours of paid and unpaid work, employed women and men, by number of dependent children, EU‑27, 2021
Figure 5‑A8	About one‑in-three people in EU and OECD countries believes that a child suffers with a working mother Share (%) of women and men who believe a child suffers with a working mother, 2017‑22 wave of WVS
Figure 5‑A9	Many people continue to believe that taking care of home and family is the most important role for a woman and earning money is the most important role for a man Share (%) who believe the most important role of a man is to earn money (Panel A) and the most important role of a woman is to take care of her home and family (Panel B), EU‑27 average, 2024
Figure 5‑A10	Nearly half of EU respondents believe men are less competent than women at household tasks Share (%) of respondents who believe men are naturally less competent than women at household tasks, EU‑27, 2024
Figure 5‑A11	Men represent under half of all users of parental leave in nearly all EU and OECD countries Share (%) of recipients of publicly-administered paid parental leave who are men and share (%) of days of leave allowances and benefits paid to men, 2023 or latest
Figure 5‑A12	Caregiving for young children is a barrier to women’s labour force participation Share (%) of inactive women and men (25‑54) who state caregiving for children or incapacitated adults as their reason for inactivity, by age of the youngest dependent child (Panel A) and by number of dependent children (Panel B), EU‑26 average, 2021
Figure 5‑A13	Gaps in employment for mothers are larger for migrant mothers relative to non-migrant mothers Employment rates of women and men (25‑54) by migrant status and presence of children (0‑14), EU‑23 average, 2021
Figure 5‑A14	Legally enshrined occupational segregation is rare, but used to be common practice across OECD countries Share (%) of EU and OECD countries (out of 43) where woman do not face legal constraints to working in the same way as a man, 1971‑2024
Figure 5‑A15	Gender gaps in hourly earnings are typically smaller than gaps in annual earnings Gender gap in median annual and hourly earnings, EU‑27 countries, 2022
Figure 5‑A16	Compared to men, women are more likely to earn low pay and less likely to earn high pay Share (%) of full-time workers classified as “low pay” and “high pay”, EU and OECD countries, 2023 or latest
Figure 5‑A17	Women are less likely than men to feel comfortable with the idea of negotiating their salary and are less likely to attempt to do so Share (%) comfortable with the idea of negotiating their salary (Panel A) and reporting having attempted to negotiate their salary (Panel B), EU‑27 countries, 2017
Figure 5‑A18	Over 1 in 10 men believe that it is acceptable for women to be paid less than men in some circumstances Share (%) who believe it is acceptable in some circumstances for a woman to be paid less than a man colleague for the same job, 2017
Figure 5‑A19	Older women are more likely to be daily unpaid carers than men Share (%) of unpaid daily carers aged 50 years and over who are women, 2019 or latest
Figure 5‑A20	Men tend to have a longer working life than women Duration of paid working life (years) for women and men, 2023
Figure 5‑A21	Women spend more years in retirement than men Expected life years after labour market exit, women and men, 2022
Figure 5‑A22	Older women are at greater risk of poverty than older men in many countries Income poverty rate, share (%) of women and men aged 65 and over with income lower than 50% of median equivalised household disposable income, 2020 or latest available year
Figure 5‑A23	More than half of OECD countries require private sector companies to report gender pay gap statistics Distribution of countries by the presence of regulations requiring private sector pay reporting, pay auditing, or related measures, OECD countries, 2022

Note: Supporting data for all Chapter 5 figures in the main text and the Online Annex are available in the StatLink below.

Statlink

References

[89] Adams, A. et al. (2024), “The Dynamics of Abusive Relationships”, The Quarterly Journal of Economics, Vol. 139/4, pp. 2135-2180, https://doi.org/10.1093/qje/qjae022.

[91] Adams-Prassl, A. et al. (2023), “Violence against Women at Work”, The Quarterly Journal of Economics, Vol. 139/2, pp. 937-991, https://doi.org/10.1093/qje/qjad045.

[65] Agerström, J., M. Carlsson and A. Erenel (2023), “The effect of social gender norms on parental leave uptake intentions: evidence from two survey experiments on prospective fathers and mothers”, Applied Economics, Vol. 55/53, pp. 6277-6293, https://doi.org/10.1080/00036846.2022.2142192.

[5] Álvarez, B. and D. Miles-Touya (2011), “Exploring the relationship between parents’ and children’s housework time in Spain”, Review of Economics of the Household, Vol. 10/2, pp. 299-318, https://doi.org/10.1007/s11150-011-9135-4.

[117] Apicella, C. (ed.) (2014), “Survey of Academic Field Experiences (SAFE): Trainees Report Harassment and Assault”, PLoS ONE, Vol. 9/7, p. e102172, https://doi.org/10.1371/journal.pone.0102172.

[157] Arena, D., S. Volpone and K. Jones (2022), “(Overcoming) Maternity Bias in the Workplace: A Systematic Review”, Journal of Management, Vol. 49/1, pp. 52-84, https://doi.org/10.1177/01492063221086243.

[78] Ashburn-Nardo, L. (2016), “Parenthood as a Moral Imperative? Moral Outrage and the Stigmatization of Voluntarily Childfree Women and Men”, Sex Roles, Vol. 76/5-6, pp. 393-401, https://doi.org/10.1007/s11199-016-0606-1.

[112] Babcock, L., B. Peyser and L. Vesterlund (2022), Are You Taking on Too Many Non-Promotable Tasks?, https://hbr.org/2022/04/are-you-taking-on-too-many-non-promotable-tasks.

[111] Babcock, L. et al. (2017), “Gender Differences in Accepting and Receiving Requests for Tasks with Low Promotability”, American Economic Review, Vol. 107/3, pp. 714-747, https://doi.org/10.1257/aer.20141734.

[171] Backhaus, A. and M. Barslund (2021), “The effect of grandchildren on grandparental labor supply: Evidence from Europe”, European Economic Review, Vol. 137, p. 103817, https://doi.org/10.1016/j.euroecorev.2021.103817.

[189] Baker, M., J. Gruber and K. Milligan (2008), “Universal Child Care, Maternal Labor Supply, and Family Well‐Being”, Journal of Political Economy, Vol. 116/4, pp. 709-745, https://doi.org/10.1086/591908.

[166] Bartels, C., E. Sierminska and C. Schröder (2024), Wealth Creators or Inheritors? Unpacking the Gender Wealth Gap from Bottom to Top and Young to Old, https://docs.iza.org/dp17324.pdf.

[190] Bauernschuster, S. and M. Schlotter (2015), “Public child care and mothers’ labor supply—Evidence from two quasi-experiments”, Journal of Public Economics, Vol. 123, pp. 1-16, https://doi.org/10.1016/j.jpubeco.2014.12.013.

[20] Becker, G. (1991), A treatise on the family, Harvard University Press, https://doi.org/10.4159/9780674020665.

[19] Becker, G. (1985), “Human Capital, Effort, and the Sexual Division of Labor”, Journal of Labor Economics, Vol. 3/1, http://www.jstor.org/stable/2534997.

[44] Berniell, I. et al. (2024), Hard Times, Hard Attitudes? The Effect of Economic Downturns on Gender Norms, https://docs.iza.org/dp17375.pdf.

[188] Bettendorf, L., E. Jongen and P. Muller (2015), “Childcare subsidies and labour supply — Evidence from a large Dutch reform”, Labour Economics, Vol. 36, pp. 112-123, https://doi.org/10.1016/j.labeco.2015.03.007.

[138] Bettio, F. and A. Verashchagina (2009), Gender segregation in the labour market: Root causes, implications and policy responses in the EU, European Commission, Directorate-General for Employment, Social Affairs and Inclusion, https://op.europa.eu/en/publication-detail/-/publication/39e67b83-852f-4f1e-b6a0-a8fbb599b256.

[118] Biggs, J., P. Hawley and M. Biernat (2017), “The Academic Conference as a Chilly Climate for Women: Effects of Gender Representation on Experiences of Sexism, Coping Responses, and Career Intentions”, Sex Roles, Vol. 78/5-6, pp. 394-408, https://doi.org/10.1007/s11199-017-0800-9.

[40] Bluedorn, J. et al. (2023), “Gender and employment in the COVID-19 recession: Cross-Country evidence on “She-Cessions””, Labour Economics, Vol. 81, p. 102308, https://doi.org/10.1016/j.labeco.2022.102308.

[8] Bonke, J. (2010), “Children’s housework - Are girls more active than boys?”, electronic International Journal of Time Use Research, Vol. 7/1, pp. 1-16, https://doi.org/10.13085/eijtur.7.1.1-16.

[162] Bonnet, C., A. Keogh and B. Rapoport (2013), How can we explain the gender wealth gap in France?, https://www.ined.fr/en/publications/editions/document-travail/explain-gender-wealth-gap-france/.

[195] Canaan, S. et al. (2022), Maternity Leave and Paternity Leave: Evidence on the Economic Impact of Legislative Changes in High Income Countries, Institute of Labor Economics, https://www.iza.org/publications/dp/15129.

[205] Carcillo, S., A. Hijzen and S. Thewissen (2023), “The limitations of overtime limits to reduce long working hours: Evidence from the 2018 to 2021 working time reform in Korea”, British Journal of Industrial Relations, Vol. 62/1, pp. 98-126, https://doi.org/10.1111/bjir.12743.

[97] Casale, S. (2020), Gender Differences in Self‐esteem and Self‐confidence, Wiley, https://doi.org/10.1002/9781119547174.ch208.

[108] Chambers, N. et al. (2018), Drawing the Future: Exploring the Career Aspirations of Primary School Children from Around the World, https://www.educationandemployers.org/drawing-the-future-report-published/.

[176] CIPD (2023), Menopause in the workplace: Employee experiences in 2023, https://www.cipd.org/globalassets/media/knowledge/knowledge-hub/reports/2023-pdfs/2023-menopause-report-8456.pdf.

[86] Coelho, M. et al. (2024), “Gendered taxes: the interaction of tax policy with gender equality”, International Tax and Public Finance, Vol. 31/5, pp. 1413-1460, https://doi.org/10.1007/s10797-024-09829-w.

[177] Conti, G. et al. (2025), The Menopause “Penalty”, https://humcap.uchicago.edu/RePEc/hka/wpaper/Conti_Ginja_Persson_etal_2025_menopause_penalty.pdf.

[200] Corekcioglu, G., M. Francesconi and A. Kunze (2024), “Expansions in paid parental leave and mothers’ economic progress”, European Economic Review, Vol. 169, p. 104845, https://doi.org/10.1016/j.euroecorev.2024.104845.

[17] Correll, S., S. Benard and I. Paik (2007), “Getting a Job: Is There a Motherhood Penalty?”, American Journal of Sociology, Vol. 112/5, pp. 1297-1339, https://doi.org/10.1086/511799.

[125] Cortés, P. and J. Tessada (2011), “Low-Skilled Immigration and the Labor Supply of Highly Skilled Women”, American Economic Journal: Applied Economics, Vol. 3/3, pp. 88-123, https://doi.org/10.1257/app.3.3.88.

[120] Cyr, E. et al. (2021), “Mapping social exclusion in STEM to men’s implicit bias and women’s career costs”, Proceedings of the National Academy of Sciences, Vol. 118/40, https://doi.org/10.1073/pnas.2026308118.

[163] D’Alessio, G. (2018), Gender wealth gap in Italy, https://www.bancaditalia.it/pubblicazioni/qef/2018-0433/en_QEF_433_18.pdf?language_id=1.

[109] Das, S. and A. Kotikula (2019), Gender-based Employment Segregation: Understanding Causes and Policy Interventions, https://lawscopelibrary.com/admin/articles/gender-based-employment-segregation-understanding-causes-and-policy-interventions/Gender-Based-Employment-Segregation-Understanding-Causes-and-Policy-Interventions.pdf.

[207] Deutsche Rentenversicherung (n.d.), Minijobs, https://www.deutsche-rentenversicherung.de/DRV/DE/Rente/Allgemeine-Informationen/Wissenswertes-zur-Rente/FAQs/Minijobs/Minijobs.html#.

[4] Dotti Sani, G. (2016), “Undoing Gender in Housework? Participation in Domestic Chores by Italian Fathers and Children of Different Ages”, Sex Roles, Vol. 74/9-10, pp. 411-421, https://doi.org/10.1007/s11199-016-0585-2.

[150] Dreber, A., E. Heikensten and J. Säve-Söderbergh (2022), “Why do women ask for less?”, Labour Economics, Vol. 78, p. 102204, https://doi.org/10.1016/j.labeco.2022.102204.

[74] Duchini, E. and C. Van Effenterre (2022), “School Schedule and the Gender Pay Gap”, Journal of Human Resources, Vol. 59/4, pp. 1052-1089, https://doi.org/10.3368/jhr.0121-11431r2.

[50] Dugan, A. and J. Barnes-Farrell (2018), “Working mothers’ second shift, personal resources, and self-care”, Community, Work & Family, Vol. 23/1, pp. 62-79, https://doi.org/10.1080/13668803.2018.1449732.

[164] EIGE (2024), Financial independence and gender equality: Joining the dots between income, wealth, and power, Publications Office of the European Union, https://eige.europa.eu/sites/default/files/documents/financial-independence-and-gender-equality.pdf.

[2] EIGE (2023), Gender Statistics Database - Beliefs about attitudes and roles of men and women regarding unpaid childcare and housework, https://eige.europa.eu/gender-statistics/dgs/indicator/eige_gap_attit__ggs_attit/datatable.

[23] Eurobarometer (2024), Gender stereotypes, https://europa.eu/eurobarometer/surveys/detail/2974.

[48] Eurofound (2022), Working conditions in the time of COVID-19: Implications for the future, Publications Office of the European Union.

[133] European Commission (2022), A European Care Strategy for caregivers and care receivers, https://ec.europa.eu/social/main.jsp?langId=en&catId=89&furtherNews=yes&newsId=10382#navItem-relatedLinks.

[158] European Commission (2013), Income pooling and equal sharing within the household – What can we learn from the 2010 EU-SILC module?, https://op.europa.eu/en/publication-detail/-/publication/1e8fd3bf-aabf-4f43-91e7-b390912c02ed.

[187] European Union (2023), Directive (EU) 2023/970 of the European Parliament and the Council of 10 May 2023 to strengthen the application of the principle of equal pay for equal work or work of equal value between men and women through pay transparency and enforcement mechanisms, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32023L0970.

[211] European Union (2022), 2022 report on gender equality in the EU, https://op.europa.eu/en/publication-detail/-/publication/0fb69c07-e79d-11ec-a534-01aa75ed71a1.

[184] European Union (2022), Council Recommendation of 8 December 2022 on access to affordable high-quality long-term care 2022/C 476/01, https://eur-lex.europa.eu/legal-content/en/TXT/?uri=CELEX%3A32022H1215%2801%29.

[183] European Union (2022), Council Recommendation of 8 December 2022 on early childhood education and care: the Barcelona targets for 2030 2022/C 484/01, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32022H1220%2801%29.

[210] European Union (2019), 2019 report on equality between women and men in the EU, https://op.europa.eu/en/publication-detail/-/publication/f3dd1274-7788-11e9-9f05-01aa75ed71a1/.

[185] European Union (2019), Directive (EU) 2019/1158 of the European Parliament and of the Council of 20 June 2019 on work-life balance for parents and carers and repealing Council Directive 2010/18/EU, https://eur-lex.europa.eu/legalcontent/EN/TXT/?uri=celex%3A32019L1158.

[209] European Union (2018), 2018 report on equality between women and men in the EU, https://op.europa.eu/en/publication-detail/-/publication/950dce57-6222-11e8-ab9c-01aa75ed71a1/language-en.

[214] European Union (2017), 2017 report on equality between women and men in the EU, https://commission.europa.eu/publications/past-annual-reports-gender-equality_en.

[63] European Union (2017), Special Eurobarometer 465 - Gender Equality 2017, https://data.europa.eu/data/datasets/s2154_87_4_465_eng?locale=en.

[213] European Union (2016), Report on equality between women and men 2015, https://op.europa.eu/publication-detail/-/publication/2ca44101-173b-11e6-ba9a-01aa75ed71a1.

[208] European Union (2015), Report on equality between women and men 2014, https://op.europa.eu/en/publication-detail/-/publication/cc106eb5-4510-40b7-b497-4b4f7b41f22b.

[179] Eurostat (2024), Duration of working life, https://doi.org/10.2908/LFSI_DWL_A.

[182] Eurostat (2024), Number of persons by sex, age groups, household composition and working status (1 000), https://doi.org/10.2908/LFST_HHINDWS.

[136] Eurostat (2024), Structure of earnings survey: annual earnings, https://doi.org/10.2908/EARN_SES_ANNUAL.

[137] Eurostat (2024), Structure of earnings survey: hourly earnings, https://doi.org/10.2908/EARN_SES_HOURLY.

[29] Eurostat (2022), Persons in employment with childcare responsibilities by effect on employment and educational attainment level, https://doi.org/10.2908/LFSO_18CEFFED.

[218] Eurostat (n.d.), Harmonised European Time Use Surveys (HETUS) - Information on Data, https://ec.europa.eu/eurostat/web/time-use-surveys/information-data.

[219] Eurostat (n.d.), Microdata - Harmonised European time use surveys, https://ec.europa.eu/eurostat/web/microdata/harmonised-european-time-use-surveys.

[9] Evertsson, M. (2006), “The reproduction of gender: housework and attitudes towards gender equality in the home among Swedish boys and girls”, The British Journal of Sociology, Vol. 57/3, pp. 415-436, https://doi.org/10.1111/j.1468-4446.2006.00118.x.

[98] Exley, C. and J. Kessler (2022), “The Gender Gap in Self-Promotion”, The Quarterly Journal of Economics, Vol. 137/3, pp. 1345-1381, https://doi.org/10.1093/qje/qjac003.

[153] Exley, C., M. Niederle and L. Vesterlund (2020), “Knowing When to Ask: The Cost of Leaning In”, Journal of Political Economy, Vol. 128/3, pp. 816-854, https://doi.org/10.1086/704616.

[99] Fitzsimmons, T., V. Callan and N. Paulsen (2014), “Gender disparity in the C-suite: Do male and female CEOs differ in how they reached the top?”, The Leadership Quarterly, Vol. 25/2, pp. 245-266, https://doi.org/10.1016/j.leaqua.2013.08.005.

[1] Fluchtmann, J., M. Keese and W. Adema (2024), “Gender equality and economic growth: Past progress and future potential”, OECD Social, Employment and Migration Working Papers, No. 304, OECD Publishing, Paris, https://doi.org/10.1787/fb0a0a93-en.

[147] Fluchtmann, J. et al. (2024), “The Gender Application Gap: Do Men and Women Apply for the Same Jobs?”, American Economic Journal: Economic Policy, Vol. 16/2, pp. 182-219, https://doi.org/10.1257/pol.20210607.

[90] Folke, O. and J. Rickne (2022), “Sexual Harassment and Gender Inequality in the Labor Market”, The Quarterly Journal of Economics, Vol. 137/4, pp. 2163-2212, https://doi.org/10.1093/qje/qjac018.

[199] Fontenay, S. and L. González (2024), Can Public Policies Break the Gender Mold? Evidence from Paternity Leave Reforms in Six Countries, https://bse.eu/sites/default/files/working_paper_pdfs/1422.pdf.

[167] Frémeaux, N. and M. Leturcq (2022), “Wealth Accumulation and the Gender Wealth Gap Across Couples’ Legal Statuses and Matrimonial Property Regimes in France”, European Journal of Population, Vol. 38/4, pp. 643-679, https://doi.org/10.1007/s10680-022-09632-5.

[131] Frey, V., L. Alajääskö and J. Thomas (2024), “Gendered perceptions of social protection across OECD countries”, OECD Social, Employment and Migration Working Papers, No. 311, OECD Publishing, Paris, https://doi.org/10.1787/f3e002c2-en.

[56] Frey, V., R. Hyee and J. Thomas (2024), “Changing societies, changing social policies”, in Megatrends and the Future of Social Protection, OECD Publishing, Paris, https://www.oecd.org/en/publications/megatrends-and-the-future-of-social-protection_6c9202e8-en/full-report/component-6.html#chapter-d1e2985-adbcaa398f.

[170] Frimmel, W. et al. (2020), “Grandmothers’ Labor Supply”, Journal of Human Resources, Vol. 57/5, pp. 1645-1689, https://doi.org/10.3368/jhr.58.1.0419-10144r1.

[62] Fundamental Rights Agency (2021), Fundamental Rights Survey Data Portal, https://fra.europa.eu/en/data-and-maps/2021/frs.

[116] Funk, C. and K. Parker (2018), Women and Men in STEM Often at Odds Over Workplace Equity, https://www.pewresearch.org/social-trends/2018/01/09/women-and-men-in-stem-often-at-odds-over-workplace-equity/.

[155] Galos, D. and A. Coppock (2023), “Gender composition predicts gender bias: A meta-re-analysis of hiring discrimination audit experiments”, Science Advances, Vol. 9/18.

[135] Garnero, A. (2016), Are part-time workers less productive and underpaid?, https://doi.org/10.15185/izawol.249.

[173] Glaser, K. et al. (2013), Grandparenting in Europe: Family Policy and Grandparents’ Role in Providing Childcare, https://kinship.org.uk/wp-content/uploads/2020/02/Grandparenting-in-Europe-0313.pdf.

[110] Goldin, C. (2014), “A Grand Gender Convergence: Its Last Chapter”, American Economic Review, Vol. 104/4, pp. 1091-1119, https://doi.org/10.1257/aer.104.4.1091.

[172] Gørtz, M., S. Sander and A. Sevilla (2024), “Does the child penalty strike twice?”, European Economic Review, p. 104942, https://doi.org/10.1016/j.euroecorev.2024.104942.

[191] Goux, D. and E. Maurin (2010), “Public school availability for two-year olds and mothers’ labour supply”, Labour Economics, Vol. 17/6, pp. 951-962, https://doi.org/10.1016/j.labeco.2010.04.012.

[220] Government of Mexico (2022), Declara INEGI Encuesta de Uso de Tiempo como Información de Interés Nacional, https://www.gob.mx/inmujeres/prensa/declara-inegi-encuesta-de-uso-de-tiempo-como-informacion-de-interes-nacional.

[100] Halabisky, D. (2021), Gender gaps in entrepreneurship are costing economies dearly, https://oecdcogito.blog/2021/11/29/gender-gaps-in-entrepreneurship-are-costing-economies-dearly/.

[76] Harding, M., D. Paturot and H. Simon (2022), “Taxation of part-time work in the OECD”, OECD Taxation Working Papers, No. 57, OECD Publishing, Paris, https://doi.org/10.1787/572b72d3-en.

[141] Harris, J. (2022), “Do wages fall when women enter an occupation?”, Labour Economics, Vol. 74, p. 102102, https://doi.org/10.1016/j.labeco.2021.102102.

[115] Hengel, E. (2022), “Publishing While Female: Are Women Held to Higher Standards? Evidence from Peer Review”, The Economic Journal, Vol. 132/648, pp. 2951-2991, https://doi.org/10.1093/ej/ueac032.

[45] Hochschild, A. and A. Machung (1989), The Second Shift: Working Parents and the Revolution at Home, Viking.

[7] Hofferth, S. and F. Goldscheider (2017), “Reflections on the future of the second half of the gender revolution”, PAA Affairs, Vol. Summer, p. 8.

[198] Huerta, M. et al. (2014), “Fathers’ Leave and Fathers’ Involvement: Evidence from Four OECD Countries”, European Journal of Social Security, Vol. 16/4, pp. 308-346, https://doi.org/10.1177/138826271401600403.

[119] IEEE (ed.) (2019), Expressions of Sentiments During Code Reviews: Male vs. Female, https://arxiv.org/pdf/1812.05560.pdf.

[38] ILO (2024), ILOSTAT Indicator “Jobs gap rate by sex -- ILO modelled estimates, May 2024 (%)”, https://ilostat.ilo.org/data/.

[37] ILO (2023), Spotlight on Work Statistics n°12: New data shine light on gender gaps, https://www.ilo.org/sites/default/files/wcmsp5/groups/public/@dgreports/@stat/documents/publication/wcms_870519.pdf.

[36] ILO (2019), A Quantum Leap for Gender Equality: For a Better Future of Work for All, https://www.ilo.org/sites/default/files/wcmsp5/groups/public/@dgreports/@dcomm/@publ/documents/publication/wcms_674831.pdf.

[34] ILO (2017), Women in Non-Standard Employment, International Labour Office, https://www.ilo.org/wcmsp5/groups/public/---ed_protect/---protrav/---travail/documents/publication/wcms_556160.pdf.

[127] ILO (2011), C189 - Domestic Workers Convention, 2011 (No. 189), https://normlex.ilo.org/dyn/nrmlx_en/f?p=NORMLEXPUB:12100:0::NO::p12100_ILO_CODE:C189.

[212] IRCC (2019), Canada to empower visible minority newcomer women, https://www.canada.ca/en/immigration-refugees-citizenship/news/2019/06/canada-to-empower-visible-minority-newcomer-women.html.

[142] Javdani, M. (2015), “Glass ceilings or glass doors? The role of firms in male‐female wage disparities”, Canadian Journal of Economics/Revue canadienne d’économique, Vol. 48/2, pp. 529-560, https://doi.org/10.1111/caje.12135.

[206] Kassam, A. (2024), A year on, Spain’s ‘historic’ menstrual leave law has hardly been used. Why?, https://www.theguardian.com/world/article/2024/jun/04/spain-historic-menstrual-leave-law-hardly-used-period-pain-endometriosis.

[68] Kaufman, G. (2017), “Barriers to equality: Why British fathers do not use parental leave”, Community, Work & Family, Vol. 21/3, pp. 310-325, https://doi.org/10.1080/13668803.2017.1307806.

[161] Kent, A. and L. Ricketts (2021), Gender Wealth Gap: Families Headed by Women Have Lower Wealth, https://www.stlouisfed.org/publications/in-the-balance/2021/gender-wealth-gap-families-women-lower-wealth.

[151] Kiessling, L. et al. (2024), “Gender differences in wage expectations and negotiation”, Labour Economics, Vol. 87, p. 102505, https://doi.org/10.1016/j.labeco.2024.102505.

[14] Kleven, H., C. Landais and G. Leite-Mariante (2023), The Child Penalty Atlas, NBER, https://www.nber.org/papers/w31649.

[18] Kleven, H. et al. (2019), “Child Penalties across Countries: Evidence and Explanations”, AEA Papers and Proceedings, Vol. 109, pp. 122-126, https://doi.org/10.1257/pandp.20191078.

[197] Knoester, C., R. Petts and B. Pragg (2019), “Paternity Leave-Taking and Father Involvement among Socioeconomically Disadvantaged U.S. Fathers”, Sex Roles, Vol. 81/5-6, pp. 257-271, https://doi.org/10.1007/s11199-018-0994-5.

[79] Koropeckyj-Cox, T. et al. (2015), “University Students’ Perceptions of Parents and Childless or Childfree Couples”, Journal of Family Issues, Vol. 39/1, pp. 155-179, https://doi.org/10.1177/0192513x15618993.

[22] Kowalewska, H. and A. Vitali (2020), “Breadwinning or on the breadline? Female breadwinners’ economic characteristics across 20 welfare states”, Journal of European Social Policy, Vol. 31/2, pp. 125-142, https://doi.org/10.1177/0958928720971094.

[149] Kray, L., J. Kennedy and M. Lee (2024), “Now, Women Do Ask: A Call to Update Beliefs about the Gender Pay Gap”, Academy of Management Discoveries, Vol. 10/1, pp. 11-37, https://doi.org/10.5465/amd.2022.0021.

[156] Kübler, D., J. Schmid and R. Stüber (2018), “Gender discrimination in hiring across occupations: a nationally-representative vignette study”, Labour Economics, Vol. 55, pp. 215-229, https://doi.org/10.1016/j.labeco.2018.10.002.

[202] Lauri, T., K. Põder and R. Ciccia (2020), “Pathways to gender equality: A configurational analysis of childcare instruments and outcomes in 21 European countries”, Social Policy & Administration, Vol. 54/5, pp. 646-665, https://doi.org/10.1111/spol.12562.

[146] Le Barbanchon, T., R. Rathelot and A. Roulet (2020), “Gender Differences in Job Search: Trading off Commute against Wage*”, The Quarterly Journal of Economics, Vol. 136/1, pp. 381-426, https://doi.org/10.1093/qje/qjaa033.

[13] Leahy, O. (2022), How discrepancies in pocket money kick start the gender pay gap at an early age, https://www.notonlypinkandblue.com/the-childhood-gender-pay-gap/.

[66] Li, Q., C. Knoester and R. Petts (2021), “Cross-national attitudes about paid parental leave offerings for fathers”, Social Science Research, Vol. 96, p. 102540, https://doi.org/10.1016/j.ssresearch.2021.102540.

[15] Lundborg, P., E. Plug and A. Rasmussen (2024), Is There Really a Child Penalty in the Long Run? New Evidence from IVF Treatments, https://docs.iza.org/dp16959.pdf.

[51] MacDonald, M., S. Phipps and L. Lethbridge (2005), “Taking Its Toll: The Influence of Paid and Unpaid Work on Women’s Well-Being”, Feminist Economics, Vol. 11/1, pp. 63-94, https://doi.org/10.1080/1354570042000332597.

[12] Marcotte, A. (2014), Even Children Have a Gender Wage Gap - Call It the Allowance Gap, https://slate.com/human-interest/2014/04/allowance-gap-boys-are-making-more-money-than-girls-even-before-they-re-old-enough-to-hold-real-jobs.html.

[24] Marshalian, M. and L. Raderschall (2023), The final frontier: Why are women further from labour parity in some non-metropolitan areas?, https://oecdcogito.blog/2023/04/28/the-final-frontier-why-are-women-further-from-labour-parity-in-some-non-metropolitan-areas/.

[192] Martínez A., C. and M. Perticará (2017), “Childcare effects on maternal employment: Evidence from Chile”, Journal of Development Economics, Vol. 126, pp. 127-137, https://doi.org/10.1016/j.jdeveco.2017.01.001.

[67] Marynissen, L. et al. (2019), “Fathers’ Parental Leave Uptake in Belgium and Sweden: Self-Evident or Subject to Employment Characteristics?”, Social Sciences, Vol. 8/11, p. 312, https://doi.org/10.3390/socsci8110312.

[81] McCutcheon, J. (2018), “Reviewing pronatalism: a summary and critical analysis of prior research examining attitudes towards women without children”, Journal of Family Studies, Vol. 26/4, pp. 489-510, https://doi.org/10.1080/13229400.2018.1426033.

[87] McNicol, E., K. Fitz-Gibbon and S. Brewer (2022), From workplace sabotage to embedded supports: Examining the impact of domestic and family violence across Australian workplaces, Monash University Report, https://doi.org/10.26180/21268686.v1.

[159] Meriküll, J., M. Kukk and T. Rõõm (2020), “What explains the gender gap in wealth? Evidence from administrative data”, Review of Economics of the Household, Vol. 19/2, pp. 501-547, https://doi.org/10.1007/s11150-020-09522-x.

[11] Miller, C. (2018), A ‘Generationally Perpetuated’ Pattern: Daughters Do More Chores, https://www.nytimes.com/2018/08/08/upshot/chores-girls-research-social-science.html.

[223] Ministerio de Igualdad y Equidad (2024), Autonomía económica para las mujeres, https://www.planestrategicodeigualdad.es/.

[143] Morchio, I. and C. Moser (2024), The Gender Pay Gap: Micro Sources and Macro Consequences, https://www.nber.org/papers/w32408.

[193] Müller, K., M. Neumann and K. Wrohlich (2018), “The family working-time model: Towards more gender equality in work and care”, Journal of European Social Policy, Vol. 28/5, pp. 471-486, https://doi.org/10.1177/0958928717753581.

[70] OECD (2024), Education at a Glance 2024: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/c00cad36-en.

[46] OECD (2024), How’s Life? 2024: Well-being and Resilience in Times of Crisis, OECD Publishing, Paris, https://doi.org/10.1787/90ba854a-en.

[69] OECD (2024), OECD Family Database PF2.1 Key characteristics of parental leave systems, https://www.oecd.org/en/data/datasets/oecd-family-database.html.

[64] OECD (2024), OECD Family Database PF2.2 Use of childbirth-related leave beenfits, https://www.oecd.org/en/data/datasets/oecd-family-database.html.

[71] OECD (2024), OECD Family Database PF3.2 Enrolment in childcare and pre-school, https://www.oecd.org/en/data/datasets/oecd-family-database.html.

[106] OECD (2024), Social Institutions & Gender Index Dashboard, https://www.oecd.org/en/data/dashboards/social-institutions-gender-index.html.

[85] OECD (2024), Society at a Glance 2024: OECD Social Indicators, OECD Publishing, Paris, https://doi.org/10.1787/918d8db3-en.

[178] OECD (2024), Strengthening the Hungarian Pension System, https://www.oecd.org/content/dam/oecd/en/topics/policy-sub-issues/structural-reforms/country-tailored-policy-reforms/Strengthening-the-Hungarian-Pension-System.pdf.

[57] OECD (2023), Beyond Applause? Improving Working Conditions in Long-Term Care, OECD Publishing, Paris, https://doi.org/10.1787/27d33ab3-en.

[72] OECD (2023), Education at a Glance 2023: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/e13bef63-en.

[104] OECD (2023), Gender pay gap reporting and equal pay audits: Lessons learned across OECD countries, OECD, Paris, https://www.oecd.org/en/publications/gender-pay-gap-reporting-and-equal-pay-audits_c40455e1-en.html.

[129] OECD (2023), Health at a Glance 2023: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/7a7afb35-en.

[25] OECD (2023), International Migration Outlook 2023, OECD Publishing, Paris, https://doi.org/10.1787/b0f40584-en.

[21] OECD (2023), Joining Forces for Gender Equality: What is Holding us Back?, OECD Publishing, Paris, https://doi.org/10.1787/67d48024-en.

[35] OECD (2023), Labour Force Statistics in OECD Countries: Sources, Coverage and Definitions, https://www.oecd.org/content/dam/oecd/en/publications/support-materials/2023/07/oecd-employment-outlook-2023_904bcef3/lfsnotes_sources.pdf.

[130] OECD (2023), Main Findings from the 2022 OECD Risks that Matter Survey, OECD Publishing, Paris, https://doi.org/10.1787/70aea928-en.

[139] OECD (2023), OECD Economic Outlook, Volume 2023 Issue 1, OECD Publishing, Paris, https://doi.org/10.1787/ce188438-en.

[102] OECD (2023), OECD SME and Entrepreneurship Outlook 2023, OECD Publishing, Paris, https://doi.org/10.1787/342b8564-en.

[169] OECD (2023), Pensions at a Glance 2023: OECD and G20 Indicators, OECD Publishing, Paris, https://doi.org/10.1787/678055dd-en.

[154] OECD (2023), Reporting Gender Pay Gaps in OECD Countries: Guidance for Pay Transparency Implementation, Monitoring and Reform, Gender Equality at Work, OECD Publishing, Paris, https://doi.org/10.1787/ea13aa68-en.

[60] OECD (2023), SIGI 2023 Global Report: Gender Equality in Times of Crisis, Social Institutions and Gender Index, OECD Publishing, Paris, https://doi.org/10.1787/4607b7c7-en.

[140] OECD (2023), “The nature of pay gap reporting: What is reported?”, in Reporting gender pay gaps in OECD countries, OECD Publishing, Paris, https://doi.org/10.1787/ea13aa68-en.

[204] OECD (2022), OECD Employment Outlook 2022: Building Back More Inclusive Labour Markets, OECD Publishing, Paris, https://doi.org/10.1787/1bb305a6-en.

[33] OECD (2022), Reducing the Gender Employment Gap in Hungary, Gender Equality at Work, OECD Publishing, Paris, https://doi.org/10.1787/fe5bc945-en.

[181] OECD (2022), Report on the Implementation of the OECD Gender Recommendations, https://www.oecd.org/mcm/Implementation-OECD-Gender-Recommendations.pdf.

[144] OECD (2022), Same Skills, Different Pay: Tackling Gender Inequalities at Firm Level, OECD Publishing, https://www.oecd.org/gender/same-skills-different-pay-2022.pdf.

[75] OECD (2022), Tax Policy and Gender Equality: A Stocktake of Country Approaches, OECD Publishing, Paris, https://doi.org/10.1787/b8177aea-en.

[32] OECD (2022), The Economic Case for More Gender Equality in Estonia, Gender Equality at Work, OECD Publishing, Paris, https://doi.org/10.1787/299d93b1-en.

[54] OECD (2021), Bringing Household Services Out of the Shadows: Formalising Non-Care Work in and Around the House, Gender Equality at Work, OECD Publishing, Paris, https://doi.org/10.1787/fbea8f6e-en.

[41] OECD (2021), “Caregiving in Crisis: Gender inequality in paid and unpaid work during COVID-19”, OECD Policy Responses to Coronavirus (COVID-19), OECD Publishing, Paris, https://doi.org/10.1787/3555d164-en.

[95] OECD (2021), Entrepreneurship Policies through a Gender Lens, OECD Studies on SMEs and Entrepreneurship, OECD Publishing, Paris, https://doi.org/10.1787/71c8f9c9-en.

[128] OECD (2021), Health at a Glance 2021: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/ae3016b9-en.

[122] OECD (2021), Starting Strong VI: Supporting Meaningful Interactions in Early Childhood Education and Care, Starting Strong, OECD Publishing, Paris, https://doi.org/10.1787/f47a06ae-en.

[134] OECD (2021), The Role of Firms in Wage Inequality: Policy Lessons from a Large Scale Cross-Country Study, OECD Publishing, Paris, https://doi.org/10.1787/7d9b2208-en.

[180] OECD (2021), Towards Improved Retirement Savings Outcomes for Women, OECD Publishing, Paris, https://doi.org/10.1787/f7b48808-en.

[26] OECD (2020), Migration policy debates: How to strengthen the integration of migrant women?, OECD, Paris, https://www.oecd.org/en/publications/how-to-strengthen-the-integration-of-migrant-women_fbc7da3c-en.html.

[123] OECD (2019), Good Practice for Good Jobs in Early Childhood Education and Care, OECD Publishing, Paris, https://doi.org/10.1787/64562be6-en.

[92] OECD (2019), OECD Employment Outlook 2019: The Future of Work, OECD Publishing, Paris, https://doi.org/10.1787/9ee00155-en.

[27] OECD (2019), Part-time and Partly Equal: Gender and Work in the Netherlands, Gender Equality at Work, OECD Publishing, Paris, https://doi.org/10.1787/204235cf-en.

[103] OECD (2019), Women are well-represented in health and long-term care professions, but often in jobs with poor working conditions, https://www.oecd.org/fr/genres/donnees/women-are-well-represented-in-health-and-long-term-care-professions-but-often-in-jobs-with-poor-working-conditions.htm.

[126] OECD (2017), 2013 OECD Recommendation of the Council on Gender Equality in Education, Employment and Entrepreneurship, OECD Publishing, Paris, https://doi.org/10.1787/9789264279391-en.

[28] OECD (2017), Dare to Share: Germany’s Experience Promoting Equal Partnership in Families, OECD Publishing, Paris, https://doi.org/10.1787/9789264259157-en.

[215] OECD (2017), Making Integration Work: Family Migrants, Making Integration Work, OECD Publishing, Paris, https://doi.org/10.1787/9789264279520-en.

[94] OECD (2016), Gender gap in entrepreneurship and entrepreneurial risk, https://www.oecd.org/fr/genres/donnees/gender-gap-in-entrepreneurship-and-entrepreneurial-risk.htm.

[217] OECD (2016), OECD Family Database - LMF2.5: Time use for work, care and other day-to-day activities, https://www.oecd.org/content/dam/oecd/en/data/datasets/family-database/lmf2_5_time_use_of_work_and_care.pdf.

[201] OECD (2007), Babies and Bosses - Reconciling Work and Family Life: A Synthesis of Findings for OECD Countries, OECD Publishing, Paris, https://doi.org/10.1787/9789264032477-en.

[30] OECD Data Explorer (2024), Incidence of involuntary part time employment.

[124] OECD Data Explorer (2024), Share of teachers by gender and age range, https://data-explorer.oecd.org/s/126.

[93] OECD/European Commission (2023), The Missing Entrepreneurs 2023: Policies for Inclusive Entrepreneurship and Self-Employment, OECD Publishing, Paris, https://doi.org/10.1787/230efc78-en.

[96] OECD/European Commission (2017), Policy Brief on Women’s Entrepreneurship, https://www.oecd.org/cfe/smes/Policy-Brief-on-Women-s-Entrepreneurship.pdf.

[101] OECD/European Union (2019), The Missing Entrepreneurs 2019: Policies for Inclusive Entrepreneurship, OECD Publishing, Paris, https://doi.org/10.1787/3ed84801-en.

[3] O’Reilly, C. and M. Quayle (2021), “Gender inequalities in time spent doing housework by children in Ireland: A nationally representative sample across two time points”, Infant and Child Development, Vol. 30/5, https://doi.org/10.1002/icd.2246.

[47] Pailhé, A., A. Solaz and M. Stanfors (2021), “The Great Convergence: Gender and Unpaid Work in Europe and the United States”, Population and Development Review, Vol. 47/1, pp. 181-217, https://doi.org/10.1111/padr.12385.

[31] Pech, C., E. Klainot-Hess and D. Norris (2020), “Part-time by Gender, Not Choice: The Gender Gap in Involuntary Part-time Work”, Sociological Perspectives, Vol. 64/2, pp. 280-300, https://doi.org/10.1177/0731121420937746.

[52] Piovani, C. and N. Aydiner-Avsar (2021), “Work Time Matters for Mental Health: A Gender Analysis of Paid and Unpaid Labor in the United States”, Review of Radical Political Economics, Vol. 53/4, pp. 579-589, https://doi.org/10.1177/04866134211035565.

[39] Pissarides, C. (2013), “Unemployment in the Great Recession”, Economica, Vol. 80/319, pp. 385-403, https://doi.org/10.1111/ecca.12026.

[73] Price, B. and M. Wasserman (2023), The Summer Drop in Female Employment, NBER Working Papers, https://www.nber.org/papers/w31566.

[84] Provencher, C. and N. Galbraith (2024), Fertility in Canada, 1921 to 2022, https://www150.statcan.gc.ca/n1/pub/91f0015m/91f0015m2024001-eng.htm.

[114] Quadlin, N. (2018), “The Mark of a Woman’s Record: Gender and Academic Performance in Hiring”, American Sociological Review, Vol. 83/2, pp. 331-360, https://doi.org/10.1177/0003122418762291.

[42] Queisser, M. (2021), “COVID-19 and OECD Labour Markets: What Impact on Gender Gaps?”, Intereconomics, Vol. 56/5, https://www.intereconomics.eu/contents/year/2021/number/5/article/covid-19-and-oecd-labour-markets-what-impact-on-gender-gaps.html.

[152] Recalde, M. and L. Vesterlund (2020), Gender differences in negotiation and policy for improvement, https://www.nber.org/system/files/working_papers/w28183/w28183.pdf.

[132] Rocard, E. and A. Llena-Nozal (2022), “Supporting informal carers of older people: Policies to leave no carer behind”, OECD Health Working Papers, No. 140, OECD Publishing, Paris, https://doi.org/10.1787/0f0c0d52-en.

[221] Saavedra, A. (2024), “The role of female-only business networks in rural development: Evidence from NSW, Australia”, Journal of Rural Studies, Vol. 106, p. 103236, https://doi.org/10.1016/j.jrurstud.2024.103236.

[113] Sarsons, H. et al. (2021), “Gender Differences in Recognition for Group Work”, Journal of Political Economy, Vol. 129/1, pp. 101-147, https://doi.org/10.1086/711401.

[148] Säve-Söderbergh, J. (2019), “Gender gaps in salary negotiations: Salary requests and starting salaries in the field”, Journal of Economic Behavior & Organization, Vol. 161, pp. 35-51, https://doi.org/10.1016/j.jebo.2019.01.019.

[61] Schmidt, E. et al. (2022), “What makes a good mother? Two decades of research reflecting social norms of motherhood”, Journal of Family Theory & Review, Vol. 15/1, pp. 57-77, https://doi.org/10.1111/jftr.12488.

[6] Schulz, F. (2019), “Trends in Children’s Gendered Housework Performance. Time Use Evidence from Germany, 1991–2013”, Child Indicators Research, Vol. 13/4, pp. 1313-1334, https://doi.org/10.1007/s12187-019-09702-x.

[160] Sierminska, E., J. Frick and M. Grabka (2010), “Examining the gender wealth gap”, Oxford Economic Papers, Vol. 62/4, pp. 669-690, https://doi.org/10.1093/oep/gpq007.

[145] Sobeck, K. (2024), “Greedy Jobs, Labour Market Institutions, and the Gender Pay Gap*”, Economic Record, Vol. 100/331, pp. 462-490, https://doi.org/10.1111/1475-4932.12824.

[83] Sobotka, T. (2021), “World’s Highest Childlessness Levels in East Asia”, Population & Societies, Vol. 595, https://www.ined.fr/fichier/s_rubrique/32255/595_ang.en.pdf.

[121] Spoon, K. et al. (2023), “Gender and retention patterns among U.S. faculty”, Science Advances, Vol. 9/42, https://doi.org/10.1126/sciadv.adi2205.

[175] State of Victoria (2023), Intersectionality at work: Building a baseline on compounded gender inequality in the Victorian public sector, https://www.genderequalitycommission.vic.gov.au/sites/default/files/2023-10/Intersectionality-At-Work-Report.pdf.

[168] Statistics Canada (2024), Labour market characteristics of persons with and without disabilities, 2023, https://www150.statcan.gc.ca/n1/daily-quotidien/240613/dq240613b-eng.htm.

[58] Statistics Canada (2024), Study: “Sandwiched” between multiple unpaid caregiving responsibilities, https://www150.statcan.gc.ca/n1/daily-quotidien/240402/dq240402d-eng.htm.

[59] Statistics Canada (2024), Who are the sandwich caregivers in Canada?, https://www150.statcan.gc.ca/n1/pub/11-627-m/11-627-m2024003-eng.htm.

[174] Statistics Canada (2022), More than half of women provide care to children and care-dependent adults in Canada, 2022, https://www150.statcan.gc.ca/n1/daily-quotidien/221108/dq221108b-eng.htm.

[88] Summers, A., T. Shortridge and K. Sobeck (2025), The Cost of Domestic Violence to Women’s Employment and Education, https://www.annesummersresearch.com/the-cost.

[196] Tamm, M. (2019), “Fathers’ parental leave-taking, childcare involvement and labor market participation”, Labour Economics, Vol. 59, pp. 184-197, https://doi.org/10.1016/j.labeco.2019.04.007.

[203] Thomas, A. and P. O’Reilly (2016), “The Impact of Tax and Benefit Systems on the Workforce Participation Incentives of Women”, OECD Taxation Working Papers, No. 29, OECD Publishing, Paris, https://doi.org/10.1787/d950acfc-en.

[165] Trinh, N. (2024), “Class origin, intergenerational transfers, and the gender wealth gap”, Socio-Economic Review, https://doi.org/10.1093/ser/mwae054.

[82] U.S. Census Bureau (2022), Historical Time Series Tables: Historical Table 1: Percent Childless and Births per 1,000 Women in the Last 12 Months: CPS, Selected Years, 1976-2022, https://www.census.gov/data/tables/time-series/demo/fertility/his-cps.html#par_list.

[10] UNICEF (2016), Harnessing the Power of Data for Girls: Taking Stock and Looking Ahead to 2030.

[55] United Nations Statistics Division (2025), Draft System of National Accounts 2025, https://mdgs.un.org/unsd/nationalaccount/SNAUpdate/2025/2025_SNA_Combined.pdf.

[216] Valdivia, M. and A. Adsera (2023), “Labour market integration of migrant mothers”, in International Migration Outlook 2023, OECD Publishing, Paris, https://doi.org/10.1787/79d0e353-en.

[53] van de Ven, P., J. Zwijnenburg and M. De Queljoe (2018), “Including unpaid household activities: An estimate of its impact on macro-economic indicators in the G7 economies and the way forward”, OECD Statistics Working Papers, No. 2018/4, OECD Publishing, Paris, https://doi.org/10.1787/bc9d30dc-en.

[194] Van Niel, M. et al. (2020), “The Impact of Paid Maternity Leave on the Mental and Physical Health of Mothers and Children: A Review of the Literature and Policy Implications”, Harvard Review of Psychiatry, Vol. 28/2, pp. 113-126, https://doi.org/10.1097/hrp.0000000000000246.

[77] Verniers, C. (2020), “Behind the maternal wall: The hidden backlash toward childfree working women”, Journal of Theoretical Social Psychology, Vol. 4/3, pp. 107-124, https://doi.org/10.1002/jts5.65.

[80] Vinson, C., D. Mollen and N. Smith (2010), “Perceptions of childfree women: The role of perceivers’ and targets’ ethnicity”, Journal of Community & Applied Social Psychology, Vol. 20/5, pp. 426-432, https://doi.org/10.1002/casp.1049.

[49] Wilkins, R. et al. (2024), The Household, Income and Labour Dynamics in Australia Survey: Selected Findings from Waves 1 to 2, https://melbourneinstitute.unimelb.edu.au/__data/assets/pdf_file/0003/5229912/2024-HILDA-Statistical-Report.pdf.

[107] World Bank (2024), Women, Business and the Law 2024, https://wbl.worldbank.org/en/wbl.

[105] World Economic Forum (2023), Global Gender Gap Report 2023, https://www.weforum.org/publications/global-gender-gap-report-2023/.

[43] WVS (2023), World Values Survey Wave 7 (2017-2022), https://www.worldvaluessurvey.org/WVSDocumentationWV7.jsp.

[222] Yamamura, S., P. Lassalle and E. Shaw (2022), “Intersecting where? The multi-scalar contextual embeddedness of intersectional entrepreneurs”, Entrepreneurship & Regional Development, Vol. 34/9-10, pp. 828-851, https://doi.org/10.1080/08985626.2022.2120086.

[16] Yu, W. and Y. Hara (2021), “Motherhood Penalties and Fatherhood Premiums: Effects of Parenthood on Earnings Growth Within and Across Firms”, Demography, Vol. 58/1, pp. 247-272, https://doi.org/10.1215/00703370-8917608.

[186] Zumbyte, I. and D. Szelewa (2024), Assessing Compliance: Implementation of EU’s Work-life Balance Directive in European Countries, https://transeuroworks.eu/wp-content/uploads/2024/10/Assessing-Compliance.-Implementation-of-EUs-Worklife-balance-directive.pdf.

Note

← 1.  Individual estimates of pension income may sometimes assume equal pooling and sharing of resources amongst all family members. This assumption may not be true in all households, which may affect the accuracy of estimates of poverty rates.