Chapter 6. Starting close, growing apart: Why the gender gap in labour income widens over the working life

This chapter begins with an overview of women’s working lives – how they differ from men’s, and how those differences impact their labour income throughout the lifecycle. It then focuses on the reasons behind these different career pathways, pointing to key forks in women’s professional lives that could lead to career traps, and examining the specific roles played by professional mobility, childbirth and part-time work. The chapter also provides a framework to help countries identify their country-specific sources of inequalities so as to meet the complex and multifaceted challenge of gender labour inequality. The chapter finally provides policy recommendations on how to address these country-specific sources of inequalities for further improvements of women’s position in labour markets.

The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.

Key findings

The pursuit of gender equality is an uphill battle (OECD, 2017[1]). The recent OECD assessment of how well countries are doing in implementing policy measures aimed at reaching gender equality goals is crystal clear: they need to do more. In particular, despite major improvements in the education of young girls, the rising labour force participation of women and widespread laws against gender discrimination, women’s position in the labour market severely lags behind that of men, and the gender gap in labour income remains a global phenomenon.

This chapter provides a more in-depth analysis of how labour market gender inequalities evolve over the career of men and women across OECD countries, by providing a life-long analysis of the gender gap in labour income (GGLI hereafter) and investigating the potential causes for the reasons why this gap increases during the working life. The GGLI is the gap between the per capita labour income of all men and women between 20 and 64 years of age and therefore provides an overall measure of women’s position in the labour market relative to that of men. It takes account of gender differences in participation, as well as of hours worked and hourly earnings when employed, and consequently gives a broader picture than the traditional gender pay gap measures which concentrate on the wages of full-time employees and therefore ignore part of the female working population. This chapter also analyses the extent to which life and career events influence women’s income mobility (moves up and down the earnings ladder and in and out of work), and what role these events play in gender pay gaps over the life cycle. It proposes a new framework to measure countries’ performance in various dimensions of labour market gender equality, identifying the main levers of action for improvement and a set of corresponding employment policy guidelines for national governments.

Women continue to have lower labour market incomes than men, and this gap widens over the working life:

Although it has narrowed in the past decade, the gender gap in labour income (GGLI) remains wide. The largest gaps are found in East Asian and Latin American countries (Japan, Korea, Mexico and Chile). Gender gaps are also relatively high (above 40%) in many Mediterranean countries, German-speaking countries, large English-speaking economies, the Netherlands and the Czech Republic. The smallest gaps (less than 30%) are found in many Nordic and Eastern European countries and Portugal.
On average, gaps in employment rates explain the largest share of the GGLI (40%), while the gap in the number of hours worked by men and women accounts for a further 20%. The remainder is accounted by the gap in hourly earnings.
The GGLI widens over the working life. Most of it is generated in the first half of the career. In a number of countries it continues to increase in the second half, although at a slower pace.
Gaps in employment rates and working hours are the consequence of different career patterns. Women’s careers are one-third shorter on average than men’s, and four times as likely to involve part-time work and flexible working time arrangements. Women’s professional careers are not linear, and comprise several different working lives.
The gender gap in hourly earnings is generally widest at around 40 years of age. After 40, low-skilled women catch up, slightly closing the gap. By contrast, the hourly-earnings gap for highly-skilled women often keeps worsening in the final years of working life.

Childbirth and early career events play a crucial role in the widening of gender disparities over the life course:

Not only do women experience slightly fewer job changes than men on average, but the nature of their labour market mobility also differs from that of men. Women do experience in-work transitions – change of employer, job or contract type – but less often than men, and they tend to have fewer in-work transitions that occur at the beginning of men’s careers. By contrast, in almost all countries, women move part-time and enter inactivity more often than men, although they also exit inactivity more often too.
The frequent job changes that occur at an early stage of both men’s and women’s careers have a big impact on future prospects. Women participate less intensely than men in this critical stage of career development. Fewer in-work transitions for women than men during the early years of their careers, particularly around the time of childbirth, translate into lower earnings growth.
In most countries, childbirth leads a large proportion of young mothers to leave the labour market, either temporarily or for a longer period. In some countries, women even withdraw completely from the labour market for several years in the middle of their career in order to have and raise children. Childbirth can have long-lasting effects on a woman's career, in terms of time spent out of the labour market, lost career opportunities, limited hours of work, and earnings. On average, the gender gap in the career length of parents is more than twice as large as that of childless workers.
Greater availability of part-time work a few years after childbirth can prevent women from withdrawing completely from the labour market. However, it can also induce significant earnings dependency on their partner, which becomes prejudicial in cases of separation or divorce. In this context, childbirth generally leads to greater income vulnerability for women in many countries. Moreover, going part-time after childbirth may make mothers miss key job opportunities, thereby resulting in less dynamic career patterns also at later stages of their working life.

Countries can use targeted measures to reduce gender inequalities:

There is a broad policy strategy to foster gender equality that is common across countries. Key elements of this strategy include: i) family policies to improve access to childcare facilities, correct disincentives to work for second wage-earners and move towards a gender-neutral tax/benefit system; ii) measures to encourage behavioural changes among both men and women, including combating long hours, getting fathers more involved in caring, and promoting more equal forms of paid leave; and iii) fostering changes in the workplace, including increased take-up of part-time and flexible working-time arrangements.
Countries should focus their efforts on reducing the quantitatively largest sources of the gender gap in labour income. The relative importance of each component in individual countries (e.g. women's lower labour force participation, lower working hours, or the concentration of women in lower-paid sectors and occupations) provides a valuable guideline for policy action. For example, policies should focus on increasing female labour participation at young ages in countries such as Greece, Spain and Italy, where large shares of older cohorts of women never entered the labour market. However, attention should focus more on policies to reconcile parental care responsibilities with working in Australia, Austria and a number of Eastern European countries, where a larger-than-average share of women withdraw from the labour market following childbirth, and in Germany, the Netherlands and Switzerland, where women often spend large parts of their careers in part-time jobs.

Introduction

One of the major labour market developments in OECD countries over the post-war period has been the continued progress made by women, with female labour force participation and employment expanding considerably and the wage gap relative to men narrowing almost everywhere (OECD, 2002[2])). These developments reflect changes both in the labour supply behaviour of women and on the labour demand side. On the supply side, the transfer of traditional female household tasks to the labour market (OECD, 2002[2]) and the development of time-saving electronic devices (OECD, 2017[1]) reduced the burden of unpaid work faced by women, freeing them to concentrate on different activities and giving them more options. At the same time, a broadening of employment and working-time arrangements available to women eased their transition from home activities to the labour market. On the demand side, the shift of employment from agriculture and manufacturing towards services, where women are over-represented, created new opportunities for them. The constant rise in levels of female education – with women’s educational achievements now surpassing those of their male counterparts – also increased their attractiveness for employers. Nevertheless, further efforts are needed in terms of public support to ensure that women, and especially mothers, have the option of fully participating in the labour market and enjoying the same career opportunities as men.

In 2017, the OECD reviewed progress made by countries in implementing the OECD Recommendations on Gender Equality in Education, Employment and Entrepreneurship and on Gender Equality in Public Life (OECD, 2017[1]). The report concludes that in the past five years, countries have made very little progress in fostering gender equality goals, and that much remains to be done to meet the G20 target of reducing the gender gap in labour force participation between men and women by 25% by 2025. Twenty-one of the 35 OECD countries are well on track to reach this goal, but further action will be needed to enable the remaining 14 countries to cross the finishing line – see OECD (2017[1]), Figure 1.10. Promoting greater participation of women in the labour market and improving the quality of their employment will contribute to stronger and more inclusive growth, and be beneficial to society as a whole.

Much of the attention in the past has focused on increasing female labour market participation by providing better work-life balance, and redesigning tax and benefit systems to avoid unemployment traps. Strong emphasis has also been placed on reducing gender wage gaps among full-time workers, on reducing low pay for women and on ways to curb discrimination as well as occupational and industrial segregation. OECD work examining the qualitative aspects of women’s professional lives showed that while unemployment rates for men and women are broadly similar, employment rates and wages are substantially lower for women but men somewhat more frequently suffer job strain (OECD, 2014[3]). A later survey providing a comprehensive picture of long-term earnings inequality and the importance of earnings mobility across 24 OECD countries, also found that long-term earnings inequalities tend to be greater among women than men. Long-term low pay indeed appears an especially prominent risk for women (OECD, 2015).

Less attention has been devoted to investigating women’s professional trajectories once in the labour market or their transitions into and out of employment, and how these affect the size of the gender pay gap over the course of their careers. The purpose of this chapter is to fill this gap and draw a comprehensive set of country-specific policy recommendations to promote better career paths for women. It is important not only to remove barriers to the participation of women in paid work, but also barriers to their career progression once in work.

This chapter therefore aims at providing an overview of women’s working lives, and their impact on labour income throughout the lifecycle, adopting a dynamic perspective and analysing the main reasons explaining gender gaps in career pathways, and in particular the specific roles played by professional mobility, childbirth and part-time work, which are shown to account for most of the widening of the gap during the working life. By contrast, delivering an exhaustive list of sources for gender inequalities is beyond the scope of this chapter. A complementary analysis of gender equality across OECD countries is presented in OECD (2017[1]). It examines drivers not analysed in this chapter such as: the role played by gender-related education disparities (reverse educational gender gap, under-representation of women in science, technology, engineering and mathematics – STEM – fields); gender gaps in entrepreneurship, financial literacy and financial education; health gender differences; and gender inequalities in unpaid work (childcare, care of older parents and housework obligations).

The rest of the chapter is divided into three parts. Section 6.1 provides a comprehensive overview of women’s employment and earnings pathways, analysing how they differ from men’s. The section also investigates how and when the gender pay gap appears over the life cycle. Section 6.2 concentrates on the reasons for these different career pathways, and identifies key turning points in women’s professional lives that could lead them into career traps. Section 6.3 provides a framework to help countries identify the main sources of gender inequalities in OECD labour markets. This framework illustrates how the very diverse nature of gender labour market inequality calls for appropriate country-specific policy responses, which are then detailed in Section 6.4. The last section provides concluding remarks.

6.1. Gender differences in professional lives

Lifetime earnings differentials are largely determined in the first ten years of workers’ careers (OECD, 2015). Nevertheless, very little is known about how the lifecycle component of earnings trajectories plays a role or not in generating the so-called gender gap. In all OECD countries, women are less often employed than men, and when they do have a job, work fewer hours per month (OECD, 2017[1]). They also experience more interruptions in their careers, the majority of which relating to their family situation. The effect of motherhood on wages is well documented in the literature (family penalty). However, women’s professional lives are not linear and rising gender inequalities over the lifecycle might as well be the consequence of different trajectories of women over their working life.

The traditional gender wage gap for full-time employees increases with age and especially during parenthood (OECD, 2017[1]). Going beyond the wage gap for full-time employees requires focussing on a broader measure of women’s position in the labour market, the gender gap in labour income (GGLI hereafter). The GGLI combines gender disparities along three dimensions: gender gaps in employment rates, hours worked and hourly wage.1 OECD (2017[4]) shows that, in all OECD countries, the GGLI is much larger than the traditional gender wage gap for full-time employees. This difference illustrates how gender differences in employment rates and hours of work reinforce the impact of the gender wage gap in depressing the labour income of women relative to that of men. This section investigates how professional trajectories of men and women worsen the gender inequality picture as a cohort ages, by describing how employment, hours and earnings vary along the life-cycle and in correspondence with specific life events.

6.1.1. Women’s employment pathways: Not linear, and shorter than men’s

The early stages of a woman’s career are crucial

OECD (2015[5]) has shown that the first 10-15 years in the labour market are critical for long-term career and earnings mobility, and that careers begin differently for women and men (Figure 6.1). In all OECD countries, women leave their parents’ home earlier than men on average and they also become involved in a relationship (defined as living with a spouse or partner in the same household) earlier. They have children earlier and more often live with them than men. In all OECD countries except Japan, Portugal, the Netherlands and Turkey, women take shorter educational paths and leave school earlier than men – see also OECD (2018[6]).2 Finally, in most OECD countries, women enter the labour market through temporary jobs more often than men do.

Women’s professional careers in fact combine several working lives

Women’s professional careers are not linear, and combine several different working lives. Figure 6.2 displays the detailed activity status of women by age, based on cross-sectional data (Box 6.1). For reference, Figure 6.2 also indicates the activity rate of men (continuous lines, to be compared with the addition of the four solid-filled layers including employed full-time, employed part-time, unpaid workers and unemployed). For both men and women in most countries, the activity rate displayed in the chart have the classical hump-shaped pattern as a function of age, since labour force participation tend to increase in the first half of the career and decrease afterwards. Yet, these simple charts underlie key moments in women’s careers and the variety of their working lives across countries:

Employment gaps are unequally distributed over the life cycle – Four patterns emerge as regards women’s absence from employment – that is, by comparing in Figure 6.2 the sum of full-timers and part-timers for women with the solid line for men: i) women are largely under-represented in paid employment at the early stage of their career (aged 20 to 40 years) in the Czech Republic, Estonia, Hungary, Latvia, the Slovak Republic and (to a lesser extent) Finland, France, Germany, Poland and the United States; ii) women are under-represented at the middle and later stage of their life cycle in Australia, Greece, Ireland, Israel, Japan, Korea, Switzerland and, to a lesser extent, Luxembourg, the Netherlands, Spain and Portugal – their entry into the labour market resembles that of men (employment rates are similar at age 25-29) but a significant share of women then disappears from the labour market as of age 30; iii) in Austria, Belgium, Canada, Denmark, Iceland, Norway, Slovenia, Sweden and the United Kingdom, the employment gap is constant over the life cycle; and iv) in Mexico and Turkey, and to a lesser extent in Chile and Italy, a significant share of the female population never enters the labour market.
Women often experience a “second working career” – A significant share of women enter or re-enter the labour market at a second stage of life (Austria, the Czech Republic, Estonia, Finland, Hungary, Iceland, Poland, the Slovak Republic and to a lesser extent Denmark, France, Germany, Latvia, Sweden, and the United Kingdom). In these countries, starting around 30-34 years old, employment rises for women but not for men. This increase is mostly driven by permanent contracts in all countries except in Korea, where this second career of women is entirely driven by temporary contracts, self-employment and unpaid work.
Up to ten years before reaching the legal pension age, many women are already inactive – Four patterns emerge: i) the share of women who are inactive but not retired (“other inactive” in Figure 6.2) is significantly larger than the same share for men in Chile, Ireland, the Netherlands, Norway, Sweden, Switzerland and to a lesser extent Austria, Denmark and Germany – see OECD (2018[6]); ii) In a second set of countries, the proportion of early leavers is high for both men and women: early retirement continues to play a large role in Belgium, Hungary, Poland and to a lesser extent Finland; iii) In a third set of countries, neither men nor women withdraw prior to reaching the legal pension age: the Czech Republic, Estonia, Iceland, Latvia, the Slovak Republic, Slovenia and the United Kingdom; iv) In Korea – where the pension system is recent compared to those in other OECD countries (OECD, 2018[7]) – and to a lesser extent in Greece, Italy, Luxembourg, Mexico, Portugal, Spain and Turkey, the proportion of women out of the labour market continuously increases with age, and a considerable share of them never ends up receiving a pension. 3 Gender inequalities in later stages of the life cycle are particularly challenging in these countries, a situation that calls for specific actions to promote women’s participation in the labour market earlier in their career.
Part-time work may also represent a career trap for women. Even if it helps to reconcile work life balance, part-time employment status can become permanent for many women, while it usually remains a transitory one for men. In Australia Austria, Denmark, Finland, Iceland and the Netherlands, part-time status is particularly frequent among active women aged over 45.4

Box 6.1. Strengths and limitations of the available data sources

Ideally, analysing the career paths of women would involve observing their complete working lives and comparing them with the career trajectories of men. The resulting ideal data would reveal career path dependencies allowing assessing how choices made at the start of one’s career continue to impact one’s professional situation, earnings trajectories and well-being several years or decades later. The effects can even extend beyond retirement, as pensions depend on career length and work trajectories over the entire working life. Unfortunately such ideal data do not exist on a cross-country comparable basis, as panel data only follow individuals over a limited period. This chapter makes use of several sorts of microdata, taking advantage of their strengths while not losing sight of their limitations.

Panel data

Panel data follow individuals over time. They allow investigation of year-to-year transitions, as well as transitions occurring between two interviews (by reconstructing monthly calendars based on retrospective questions). In contrast to much of the literature (dealing with yearly transitions), this chapter concentrates on monthly professional transitions drawn from short panel data. For each year/individual, given the person’s activity status in January, it considers any monthly transition that may occur over the year. Several transitions are therefore possible for the same individual from one year to the next. For a subset of countries (Australia, Germany and the United States), available panel data track people over a period of sufficient length to examine longer-term effects of career events, as well as career path dependencies. Based on these long panel data, the chapter investigates cumulative mobility over time, and how childbirth affects women’s professional opportunities over the medium to long-term (seven years).

Long retrospective data

Long retrospective data are powerful alternative sources. This chapter makes use of the Survey of Health, Ageing and Retirement in Europe (SHARE), Wave 3 – SHARELIFE, which provides a rich set of information on the work and personal histories (from marriages and divorces to maternity, health and housing) of 30 000 older workers aged 50 and over in 2009 in 13 European countries (Austria, Belgium, the Czech Republic, Denmark, France, Germany, Greece, Italy, the Netherlands, Poland, Spain, Sweden and Switzerland). SHARELIFE’s major limitation is memory bias: coverage is limited to spells of employment longer than six months, covers a period when the labour markets were much less mobile than they are now, and when people remained with the same company their entire lives. Even so, it is the only dataset that affords a look at entire individual trajectories of workers and non-workers over their life cycle.

Cross-sectional data

Even cross-sectional data can be very informative as regards women’s situation on the labour market at different times in their career. Beyond reporting about employment, unemployment and inactivity, these data allow: i) including an in-between category (“education and work”); ii) specifying the reason for inactivity (solely in education, retirement, military services, other inactive); iii) looking at full-time/part-time/unpaid work as well as permanent/temporary/self-employed. They allow drawing a clear picture of women’s activity status at different moments in their lives and make it easier to remain mindful of the orders of magnitude of the sub-population being dealt with when focusing on career events and paths. Nevertheless, using cross-sectional data, one can easily mix age, career and cohort effects, which play a crucial role in the analysis of gender-related issues (see Box 6.2).

Goldin and Mitchell (2016[9]) argue that the hump shape of labour force participation over the life cycle is disappearing in favour of the emergence of M-shaped curves prevailing for new cohorts. The explanation put forward is that birth events had always produced a temporary withdrawal from employment but are now occurring later because of the delay in marriage and childbirth – see OECD (2018[6]). In Figure 6.2, an M-shaped curve is clearly visible in Korea and Japan, suggesting that women tend to exit the labour force upon childbirth but re-enter once children have grown older. By contrast, in those countries where part-time expands at childbirth age, an M-shaped curve is visible only for the share of full-time employment (the intensive margin), while it remains hump-shaped when both full-time and part-time are taken into account. This, however, is likely due to further evolution of behaviours over time, transforming M-shaped curves on the extensive margin (including both full-time and part-time) into similar curves prevailing only on the intensive margin. For example, Blundell, Bozio and Laroque (2013[10]) found clear M-shaped curves for the United Kingdom in 1977 both on the intensive and extensive margins, and yet these remained visible only on the intensive margin in 2007.

6.1.2. Gender gaps in hourly earnings: an inverted U-curve

Full-time women still earn less than men

Beyond gaps in employment and hours worked, earnings for the same amount of hours of work represent a crucial difference between men and women's labour market success. Gender wage disparities are slowly decreasing but remain considerable.5 On average, among OECD countries, full-time women earned 15% less than their men peers in 2014, while this gap was 16% in 2005 (Figure 6.3). The gender wage gap for full-timers is the largest in Korea (over 35%) and the smallest in Belgium (less than 5%). The latter is also the country with the largest gap reduction (almost 10 percentage points) since 2005. By contrast large increases are observable in Chile and Latvia. However, in these countries larger gaps go hand in hand with a significant increase in female participation, in particular among the low-skilled, which, by increasing the number of women at the bottom end of the wage distribution, mechanically reduce average wages among working women.

Gender wage gaps draw an inverted U-curve over the career

In many countries with sufficient data to estimate gender gaps in hourly earnings for different cohorts (Figure 6.4), these gaps show an inverted U shape over the career with most of the wage gap increase taking place from 30 to 40 years of age (e.g. Australia, Canada, Germany, Korea, Mexico, the United Kingdom and the United States). In English-speaking countries and Korea, gender wage gaps tend to shrink in the later part of the working life, while they stabilise after age 40 in Germany and Mexico. By contrast, in France and Italy, where seniority premiums play a large role in wage setting and lower professional mobility limits new job opportunities at old age (see Section 6.2 below), the gender gap continues to increase over the career.

A narrowing gap for younger cohorts

The age-gender wage gap profiles of recent cohorts lie below those of older ones, implying that the gap tends to narrow over time. Yet, this shift does not occur homogenously in all stages of the working life and in all countries, which implies that it might also be misleading to try to infer life-cycle / career pathways by looking at labour income gaps at different ages at one point in time (Box 6.2). Arrows in Figure 6.4 illustrate how the gap evolved across cohorts.6 Gaps are smaller for younger cohorts in Canada, France, Germany, Mexico, the United Kingdom and the United States. In the United States, the narrowing of the gender wage gap that occurred between 1975 and 2009 is largely due to cohort effects (Campbell and Pearlman, 2013[11]), but convergence has slowed since 2000 (Juhn and McCue, 2017[12]). Interestingly, while gains in female wages contributed to the decline in gender wage gaps for cohorts born before 1950 in the United States, the narrowing for later cohorts is primarily the result of male wages declining (Campbell and Pearlman, 2013[11]). In other countries (notably, France and Mexico) the narrowing of the wage gap appears more pronounced at the end of the working life. The age at which the gap starts decreasing or becomes flat has generally gone down over time for the oldest cohorts, but there are signs of inversion of this process in a few countries (e.g. Canada and the United Kingdom).

Box 6.2. Empirical biases in the analysis of the gap in hourly earnings over the life cycle

Looking at the gender wage gap by age at one point in time (in 2015, for example) can be misleading. The data indeed capture gender wage gaps of different cohorts taken at different moments in the life cycle, but they do not measure the evolution of the gender gap of a cohort over their entire life cycle. There are several explanations for the difference:

First, composition effects render cohorts different from one another. Indeed, megatrends in women’s human capital investment (higher educational attainment), family decisions (declining marriage, delays in fertility decisions, decrease in family size and in the number of children per women), labour supply (increased participation in the labour market over the past decades and changes in amounts of working hours) have considerably changed the composition of the female working population. Therefore, the gender gap for workers aged 50 in 2015 is not the same as the one their parents experienced 20 years previously. Participation in the labour market has increased significantly over the past decades; women are more educated; and they withdraw less from the labour market at childbirth. The gender gap is expected to decrease for more recent cohorts, as working men and working women are more alike now than a few decades ago.
Second, returns to individual characteristics may differ across cohorts, gender and time (for example the effect an additional year of schooling is likely to have on individual earnings), with the result that the gender income gap evolves differently, even for similarly composed cohorts.
Third, time variation effects have been identified through age-period-cohort analysis – see Campbell and Pearlman (2013[11]) for a detailed presentation of these models. There are three types of time-related variation: i) age effects: the physiological or social processes associated with ageing, such as motherhood or tenure, produce changes in wages; ii) period effects: certain events (the global financial crisis, for example) simultaneously affect all cohorts, but at different ages. Several other phenomena might simultaneously affect all cohorts at different moments of the life cycle, such as job polarisation or emerging new forms of work (OECD, 2017[4]); this may bias also the cohort analysis, as shocks may bias the inter-cohort comparison; iii) cohort effects: the timing of life and labour market experiences, such as entering the labour market during a recession, can shift career trajectories for men and women (Campbell and Pearlman, 2013[11]).

Figure 6.4 displays hourly earnings gaps between genders for all workers (full-time and part-time) by age for five cohorts. Cohorts are here defined as all individuals born within a five-year period; the periods selected are 1936-40, 1946-50, 1956-60, 1966-70 and 1976-80. Results are the same with the in-between cohorts, but the juxtaposition of too many cohort curves would make the figure unreadable. Unfortunately, this is a demanding exercise in terms of data availability, as it requires microdata over a very long period. In most countries, microdata are not available over a sufficiently long period to enable building wage gap curves by cohorts. Thus, only nine countries appear in the figure.

The main reason for narrowing wage gaps is the increase in female educational attainment for younger cohorts; young women even outperform young men in many countries, leading to the so-called reversed educational gender gap. Nevertheless, Blau and Kahn (2016[13]) find that while women’s gains in market skills – measured by education and work experience – were important in explaining convergence over the period 1980-2000, these human capital variables now only account for a negligible portion of the remaining gap.7 Other reasons for the shrinking of the gap have also been well documented in the literature and include: increasing employment of women in non-traditionally female occupations (Goldin, 2004[14]; 2006[15]); the role of contraception, accounting for 10% of the convergence of the gender gap in the 1980s and 30% in the 1990s (Bailey, Hershbein and Miller, 2012[16]); and an increase in the returns to women’s career investments in market skills, due to increases in the demand for skills that benefited women relative to men (Blau and Kahn, 1997[17]).

The inverted U-curve is more pronounced for low-skilled workers than for high-skilled ones facing a glass ceiling

The inverted U shape of age-gender wage gaps is more evident in the case of low-skilled workers. In Canada, France and the United States, for example, the gender wage gap starts decreasing at younger age in the case of workers with upper secondary education or less (Figure 6.5, Panel A), than for workers with higher educational attainment (Figure 6.5, Panel B). While this is consistent with the “glass ceiling” and “leaky pipeline” literature, 8 it also points to the possible cumulative consequences on women's careers in professions with a steeper earnings profile of the professional and life choices taken at an early stage of the working life by many highly-educated women. OECD (2017[1]) notes that childless women fare better than others. These path-dependencies are investigated in the next section.

6.2. Women's professional trajectories and career path-dependency: the role of lost opportunities

Gender gaps in the labour market increase for at least the first half of the working life and never decrease afterwards. Previous OECD work (OECD, 2017[1]) has analysed several reasons for the persistence of gender gaps in labour market participation and earnings, including: the lack of progress of girls in science, technology, engineering and mathematics areas, despite improvements in overall educational attainment; the gendered division of housework and care duties; the lack of adequate and affordable childcare facilities; tax-benefit disincentives for second earners to work; gender discrimination; and the deficit of women in managerial positions. All these reasons have been well documented in the literature. Less attention, however, has been paid to women’s professional trajectories and their consequences. To shed some light on this issue, this section analyses gender differences in labour mobility, consequences of a childbirth and professional choices. In particular, it investigates the medium- and long-term consequences of childbirth on women’s propensity to withdrawing from the labour market, opting for part-time work or turning down better-paid job offers, as well as the implications of these labour supply responses for career progression and the gender pay gap at different ages.

6.2.1. Women’s labour mobility differs from men’s

Women have fewer in-work transitions than men

Job-to-job mobility, especially early in a career, is an important source of wage growth because job mobility enables better matches – e.g. OECD (2015[5]).9 Personal decisions that impact career paths relate to job search behaviour, job acceptance, contract type and housework. In particular, potential and actual fertility can have an effect on career events (and career events can affect fertility and the decision to have children).10 Labour mobility can be measured in various ways (Box 6.3).

Every year in OECD countries, 16% of the working-age population experience a change in their professional situation in the labour market. They change employer, change their working time (switching from full-time to part-time or the reverse), lose their job, find (a new) one, become unemployed or inactive, or re-enter the labour market after a period of inactivity. The proportion of individuals experiencing a professional transition ranges from 12% or less in Italy, France,11 Greece, Ireland and Portugal to more than 25% in Finland, Sweden and Iceland. Gender differences are rather small (on average less than half a percentage point) compared to cross-country differences (Figure 6.6, Panel A). Professional transitions are obviously higher among the active than the inactive population, with almost one active person out of five going through a professional change every year.

Women have on average the same number of professional transitions as men over their entire working lives – 9.6 on average in OECD countries – but they are of different nature than men's.12 For example, with the exception of Finland, Germany and Japan, women have fewer in-work transitions (i.e. changes of employer, job or contract type) than men (20% fewer, on average, Figure 6.6, Panel B). By contrast, women more often switch working time than men in almost all countries (an average of 40% more transitions of this type) and have fewer episodes of unemployment (21% fewer on average).

Women also enter inactivity more often than men, but they also exit inactivity more often (29% more episodes than men in both cases; Figure 6.6, Panel C). While the greater tendency for women to experience transitions between employment and inactivity have been much emphasised as being potentially problematic for the career progression of women, less frequent in-work transitions may also represent an important handicap for women.

Women miss crucial professional transitions around childbirth

In-work transitions are important because they have a positive impact on income growth, particularly for younger workers (Figure 6.7, Panel A). In all OECD countries, in-work transitions have a positive impact on earnings all other things equal,13increasing labour income by 7.8% on average. Moreover, transitions seem to pay off more when they occur at young age than later. Job mobility in the early stages of working life has been shown to have particularly strong effects on wage growth and also helps workers to find job matches that open up career ladders.14 OECD (2015[5]) shows, for example, that the first 10-15 years in the labour market are crucial for long-term career and earnings mobility.

Box 6.3. Measuring transitions in labour markets

There are several very different approaches to estimating labour or professional mobility, based on firm-level data, on survey data including retrospective questions, or on longitudinal panel data. Some of these measures focus on employees, others on jobs or even on contracts. Their ultimate goal varies from serving as a management tool for implementing human resource policies, to providing economic statistics that will help in ascertaining the labour market dynamism – see e.g. Davis, Faberman and Haltiwanger (2006[18]) OECD (2015[5]); Bachmann et al. (2014[19]). For the purpose of this chapter, individuals are considered to have experienced a professional transition if they had, from one year to the next, any change in their professional situation on the labour market, meaning that they changed employer, contract type or working time (switching from full-time to part-time or the reverse); lost their job or found (a new) one; became unemployed or inactive; or re-entered the labour market after a period of inactivity. With short panel data that follow individuals over three to four years, it is possible to reconstruct monthly calendars based on retrospective questions and, given the activity status in January, identify any monthly transition that may occur over one year. Several transitions are therefore possible for the same individual from one year to the next.

As a consequence, lower in-work mobility during the early stages of women’s careers, and in particular around childbirth, plays a major role in enlarging the initially quite small gender gap in labour income.15 Not only women are slightly less mobile than men on average, but they especially miss the crucial in-work transitions occurring in the early stages of men’s career, which promote stronger career advancement for them. More specifically, women miss these in-work transitions immediately after childbirth. In fact, mothers with children aged three years or less are 4.2 percentage points less likely to experience an in-work transition than their partner, even conditional on working the year before (Figure 6.7, Panel B). The tendency for women to have a considerable lower share of in-work mobility around the time that they become mothers has the potential to significantly limit women’s careers, 16 and contributes to the gender pay gap generated before age 40 (Section 6.2). 17

6.2.2. Unravelling the role of childbirth on women’s careers

Female labour supply reacts very differently to childbirth in different countries

Women's careers are disproportionately hampered by childbearing and child rearing (OECD, 2017[1]). Women who are mothers are more likely than childless women to work fewer hours, earn less than men, or opt out of the workforce entirely. By contrast, men tend to have a higher probability of work after becoming fathers (OECD, 2016[20]). Childbirth and child rearing significantly change the activity status of women, but mothers’ labour supply elasticities vary significantly across countries and depends to a great extent on social and family policies; social norms regarding mothers in employment and the role of women in raising children;18 the availability and cost of childcare facilities as well as marginal tax rates on second-earners.

Activity statuses of women without children are very similar to men’s in many countries – see OECD (2018[6]) – while mothers’ labour supply is much different, albeit with sizeable cross-country variation. Figure 6.8 6.8 displays the detailed activity status at different ages of women with and without children for six illustrative OECD countries. Panel A shows that in Hungary, as in the Czech Republic, Estonia, the Slovak Republic and to a lesser extent Poland and the United States, a large proportion of young mothers are inactive but they later enter (or re-enter) the labour market. Panel B illustrates that in the Netherlands as in Austria, adjustment to childbirth comes primarily through significant take-up of part-time work. A combination of both patterns appears in Germany (Panel C) as well as in Australia, Ireland and the United Kingdom. In a number countries, where social policies are strongly family oriented, such as in France (Panel D), Belgium, Latvia, Portugal, Slovenia and Spain, the activity statuses of women with and without children are more similar. However, motherhood in these countries can result in education drop-out with consequences later in the careers of women. In Korea (Panel E), Japan and to a lesser extent Luxembourg, young women participate massively in the labour market while mothers withdraw upon childbirth to re-enter later in their career. Finally, in Mexico and Turkey (Panel F), a significant share of the female population never enters the labour market: the employment rate of childless women is particularly low, despite being still twice as large as that of mothers.

Juhn and McCue (2017[12]) provide a review of academic literature focusing on the “motherhood penalty” and the “family gap” in earnings. They show that the wages of mothers are significantly lower than those of non-mothers with similar human capital characteristics. The motherhood penalty amounts to approximately 5-15 log points for mothers compared to non-mothers.19 And it has long-lasting effects: wage gaps indeed accumulate, particularly among highly-skilled women. Wilde, Batchelder and Ellwood (2010[21]) find larger wage gaps of 17 log points at ten or more years after childbirth. Each of these studies focuses on hourly wages rather than annual earnings. Gaps in annual earnings are even larger, as mothers are significantly more likely to work part-time, part year, or not at all. Mothers’ average contribution to households’ overall earnings from employment and self-employment is lowest in German-speaking countries, followed by Southern Mediterranean countries, while mothers in France, Sweden and Denmark contribute over 35% of household income from their earnings on average (OECD, 2017[22]).

Using Danish administrative data, Kleven et al. (2018[23]) show that a long-run penalty in female earnings of 21% can be attributed to the arrival of children, driven in roughly equal proportions by labour force participation, hours of work, and wage rates. Childbirth has a clear long-lasting effect on occupation, promotion to manager, and “the family friendliness of the firm for women relative to men”. The most striking result being that this child penalty worsened over time, as the fraction of the aggregate gender gap that can be explained by children strongly increased from 30% in 1980 to 80% in 2011, showing that non-child reasons for gender inequality have largely disappeared.

Long lasting effects of mothers’ withdrawal from the labour market at childbirth

In most countries, a substantial share of women having a child reduces their labour supply. These withdrawals have long-lasting effects on the careers of women, in terms of time spent out of the labour market and lost opportunities for career advancement.20 Figure 6.9 shows estimates of the effect of childbirth on mothers’ employment, controlling for a number of individual characteristics. The estimated employment probability is presented for up to seven years after childbirth.21 Highly diverse patterns of withdrawal are observed for the different countries analysed. The results show that the withdrawal from the labour market at childbirth is: i) large and quite persistent (more than three years) for the 10 countries shown in Panel A (Australia, Austria, the Czech Republic, Estonia, Finland, Germany, Hungary, Korea, the Slovak Republic); ii) intermediate or large initially but short-lived (only one year) in Denmark, Iceland, Latvia, Luxembourg and Norway, (see Panel B); or iii) intermediate initially but very persistent in the six countries shown in Panel C (Belgium, France, Greece, Ireland, Italy and Poland and the United Kingdom; or, iv) very limited, possibly due to the effect of social policies in preventing women from losing connection with the labour market in the six countries shown in Panel D (Lithuania, the Netherlands, Portugal, Spain, Slovenia and Sweden).

Women’s in-work transitions are also affected for a very long time after childbirth. For example, Figure 6.10 shows the cumulative probability of having an in-work transition (change of employer, job or contract) over seven consecutive years, using the Household, Income and Labour Dynamics in Australia (HILDA) panel, which allows people to be tracked over an extended period (Box 6.1). If the deficit in career advancement opportunities is around 12 percentage points for a change of employer within the first year following childbirth, the cumulated effect over the next six years reaches a 25 percentage point lower probability of changing employer, and a 35 percentage point lower probability of changing contract or working hours. By contrast, childless women have in-work transition rates similar to those of men. As seen before, in-work transitions are crucial for career and wage progression. Therefore the lower frequency of these transitions after childbirth sheds light on how motherhood has a pronounced and persistent effect in limiting career opportunities for mothers.

Part-time work can prevent withdrawal from the labour market…

If some women completely withdraw from the labour market at childbirth ages, another large share adapts their professional career so as to free up enough time to meet their family obligations. A significant share of women around the ages of 30-44 years changes to part-time employment, either within the same job (with the same employer) or by switching jobs. For example Liu (2015[24]) shows that women’s preference for part-time work in the United States increases with marriage and the number of children but that this is not the case for men.

Figure 6.11 shows the short-, medium- and long-term changes in female work intensity after childbirth, as captured by the rate of part-time employment among all working-age women (whether employed or not). In Australia, Austria, Denmark, Finland, Iceland and the Netherlands (Panel A), the increase in the share of employed women who hold part-time jobs following childbirth is large (more than 10 percentage points) and quite persistent. In these countries, part-time take-up tends to increase progressively until children reach approximately the age of five and then it decreases when they enter primary school. In Estonia, Italy, Luxembourg, Norway, Spain, Slovenia, the United Kingdom and the United States (Panel B), women also significantly increase their take-up of part-time employment following childbirth (more than 4 percentage points), but this increased part-time use does not vary much with the age of the youngest child. In Belgium, France, Germany, Ireland and Sweden (Panel C), part-time take-up is not directly linked to the arrival of a child: the part-time employment gap is high relative to men even among childless women, but remains largely unchanged after childbirth. Finally, part-time take-up is rarely used as an adjustment variable by women in the Czech Republic, Greece, Hungary, Korea, Latvia, Lithuania, Poland, Portugal and the Slovak Republic (Panel D). In a few of these countries (e.g. many Eastern European countries), outright withdrawal from the labour force is the most preferred option by women upon childbirth. Since part-time employment can be an effective means to reconcile family responsibilities and paid employment, this pattern suggests that policy measures may be needed in these countries to promote part-time work and provide women with more flexible working time arrangements.

…but both withdrawing from the labour force or working part-time may represent career traps for women

While increased take-up of part-time work for a few years after childbirth can prevent complete labour market withdrawal in many cases, part-time work can also represent a career trap for women. Women working part-time experience significantly fewer professional transitions than men working part-time (on average 7 percentage points less), and this is likely hamper their upward mobility throughout their career. 22 Even if it helps to reconcile work-life balance, part-time employment status can thus become permanent for many women, while it usually remains transitory for men.23 In these countries, the switch to part-time work widens the gender gap in labour income within the family, which may suggest a case for reducing fiscal incentives to part-time (see Section 6.4).

Overall, women, and especially mothers, have shorter and less intensive careers than men

As a result of all these persistent changes in labour supply patterns induced by childbirth, net career length is much shorter for mothers (Figure 6.12):24 mothers spend indeed 46% fewer years in employment than men, and their net careers are about 20% shorter than those of childless women (Panel A).25 However, the average gender gap in career length for parents is more than twice as large as that of childless people, suggesting that children are by far the most important factor accounting for gender differences in career length. Overall, career-length gaps between men and women are very small in the Czech Republic, Denmark and Sweden, while they are the largest in southern European countries (Italy, Spain and Greece). The impact of having children remains limited (around 10% decrease in total career length) in the Czech Republic, Sweden, Denmark Poland and Greece, while it reduces total career length by one-third in Austria, Switzerland, Ireland, Italy and Spain.

Women’s careers are also four times more intensive than men’s in part-time work and flexible working time arrangements (Panel B of Figure 6.12). In Austria, Belgium, Denmark, France, Greece, the Netherlands, Sweden and Switzerland, having a child considerably increases take-up of part-time work, while in the Czech Republic, Germany, Ireland, Italy and Poland, the difference between childless women and women with at least one child is rather small and the part-time option appears to be less driven by the arrival of a child. Nevertheless, even childless women spend almost one-fifth of their career on part-time work or flexible working time arrangements in Germany, the Netherlands and Switzerland, illustrating national preferences for part-time, the importance of tax-benefit disincentives and/or limited use of out-of-school care (Section 6.4).26

6.3. Towards a broad assessment of labour market gender equality

6.3.1. The gender gap in labour income

Gender inequality in labour markets indeed represents a multifaceted challenge for countries (OECD, 2017[1]; 2017[4]). The gender gap in labour income (GGLI), which is considered in this section, is a simple indicator that captures the key element of gender inequality in the labour market. In fact, women’s lower total labour income has consequences for their bargaining power within the household, for their income in case of divorce, and for pension and living standards of widows once their partner’s income ceases to play its buffering role (OECD, 2017[25]). The GGLI summarises in one number, three complementary dimensions of women’s position in the labour market: the gender gap in employment rates; hours worked; and hourly earnings. As seen in the previous sections, all these dimensions may play a role in accounting for gender disparities in the labour market. Decomposing the gap into different components allows identifying the most important sources of gender labour market inequalities in each country. In the next section, tailored levers of action for policy makers are then identified depending on the source of gender differences in each country.

The size of the overall GGLI varies substantially across countries (Figure 6.13, Panel A).27 Considering all women (without restricting the analysis to those working full-time), the largest gaps are found in East Asian and Latin American countries (Japan, Korea, Mexico and Chile). Gender gaps are also relatively high (above 40%) in many Mediterranean countries, German-speaking countries, many large English-speaking economies as well as the Netherlands and the Czech Republic. By contrast, the gender gap in labour income is the smallest (less than 30%) in many Nordic and Eastern-European countries and in Portugal.

The GGLI is decomposable (see Box 6.4), which can help design strategies to reduce gender disparities in the labour market. The decomposition divides the overall gender gap into the following components: i) the gender employment rate gap (also called the extensive margin); ii) the gender hours gap (e.g. the more intensive take-up of part-time work by women, also called the intensive margin); and iii) the gender hourly wage gap. The traditional gender pay gaps usually published by the OECD considerably differ from those shown by the GGLI, mostly because they are based only on hourly wages and focus on full-time workers. On this basis, OECD (2017[1]) provides an interesting focus by analysing the gender gap at different points of the wage distribution. The two approaches focus on very different populations, and are therefore complementary.

Figure 6.13, Panel A presents the decomposition of the GGLI into the three components. The main drivers of gender labour inequality are by far the employment gap and the hourly wage gap (explaining both about 40% of the overall inequality). By contrast, the more intensive take-up of part-time work by women and the derived differential in the number of hours worked by men and women, accounts for 20% of overall gender labour inequality.

The GGLI has shrunk in the past decade in almost all countries, with the contraction of the employment gap being by and large also the main driver of the reduction of the labour income gap (Figure 6.13, Panel B). On average, little progress has been made in the other dimensions of the labour income gap, partly because of changes in the composition of working women (with less skilled and employable women joining the labour force and employment in recent years, sometimes ending up working part-time).

6.3.2. Gender gaps by educational attainment and age group

Low-educated women struggle the most in reaching gender equality

Low-educated women face higher gender divides in the labour market (Figure 6.14, Panel A): in almost all countries, labour income of women is much lower relative to men at low levels of education. This significant educational divide in GGLI is driven by large employment gaps (Panel B) more than counterbalancing the fact that, on average, the gender wage gap is smaller among men and women with low educational attainment (Panel D and Section 6.1.2). Low-educated women struggle the most in reaching gender equality in Belgium, Canada, Greece, Ireland, Italy, Latvia, Mexico, Poland, the Netherlands, Spain and Turkey (more than 20 percentage point difference in GGLI for women with less than upper secondary compared with tertiary-educated women).

Box 6.4. Decomposition of the gender gap in labour income

The gender gap in per capita labour income (GGLI) is the gap between total labour income of men (based on the male population between 20 and 64 years of age) and total labour income of women (of the corresponding female population). Labour income includes monthly earnings of employees including base wages, bonuses, overtime, supplementary payments (thirteenth month payment), paid leave and cash benefits of self-employed. This global gender gap in labour income can be further decomposed into three components: employment gap, part-time effect, and full-time equivalent earnings gap. The latter can be further decomposed into the returns to individual characteristics of workers, job characteristics, sector and occupation, as well as an unexplained residual.

This decomposition provides a global assessment of women’s place and role in the labour market as well as guidance for policy action. Comprehensive, it measures employment and earnings dimensions. Inclusive, it is based on all men and women and not just those working full-time. Analytical, it enables policy makers to compare the relative importance of each component and easily identify the most striking gender issue to tackle with policy action.

The gender gap in per capita labour income (GGLI) can be decomposed as follows:

$G G L I = E G + (1 - E G) * T o t a l E a r n i n g s G a p$

Where $E G$ is the employment gap (i.e. the difference between the employment rate of men and the employment rate of women, divided by the employment rate of men) the total earnings gap is the gender gap of total monthly labour income among the employed. The component $(1 - E G)$ derives from the fact that the total earnings gap is based on the working population while the initial gender gap in labour income relies on the entire population (aged 20-64 in both cases).

Following the analysis of professional segregation in France by (Chamkhi and Toutlemonde, 2015[26]), the total earnings gap is further decomposed into hourly wage gap ( $H W G$ ) and hours gap ( $H G$ , the difference between Total earnings gap and $H W G$ ).

$G G L I = E G + (1 - E G) * [H G + H W G]$

$H W G$ is based on an estimate of full-time equivalent incomes, which relies on country-specific full-time thresholds (40 hours a week in all countries except in Belgium [39 hours], and France [35 hours]). All labour incomes above this full-time threshold remain unchanged, while those below the threshold are converted into full-time equivalent income by multiplying the labour income by the national full-time threshold, and dividing the result by the number of hours usually worked in the reference week. The $H G$ component is therefore the contribution of the lower number of working hours by women (intensive margin) to the overall labour income difference between men and women.

The $H W G$ can then be further decomposed using a classic Oaxaca-Blinder decomposition between $I N D$ a component explained by the individual characteristics of workers (age, education), $J O B$ a component explained by observable job’s characteristics (firm size and contract type), and $O C C S E C T$ a component explained by occupation and sector. The residual part is the unexplained component ( $U N E X P)$ , which accounts for various unobservable factors.

$G G L I = E G + (1 - E G) * [H G + I N D + J O B + O C C S E C T + U N E X P]$

Full results of this finer decomposition are presented in the OECD (2018[6]).

Gender labour inequality increases over the life cycle

Figure 6.15 presents the GGLI separately for three age groups and shows that gender labour inequalities sharply increase with age in a large majority of countries, confirming insights from Sections 6.1 and 6.2. Yet, as discussed, cross-sectional data in Figure 6.15 are also affected by cohort effects, which magnifies the steepness of age-labour-income-gap profiles. These profiles may appear through four possible channels: i) withdrawal from the labour market at childbirth age of a substantial share of mothers, some of whom remaining inactive for a long time or even permanently – Section 6.1.1 and Section 6.2.2; ii) part-time employment becoming the norm at latter stages of mother’s career in some countries – Section 6.1.1, Section 6.2.2 and OECD (2018[6]); iii) the age profile of the gender wage gap among full-time workers – Section 6.1.2; and iv) cohort effects: older cohorts of women participating less in the labour market and being usually much less paid than their male counterparts – see especially Section 6.1.2.

The average gender gap in hourly wage (regardless of occupation of job classification) increases at childbirth age in most countries and then remains broadly constant afterwards (Panel B). The hourly wage gap for youth explains only 20% of the overall gap in labour income for this age category and is even close to zero or negative in many countries (Panel D). Age plays a limited role in gender hours gaps.

The extent to which the GGLI varies with age differs dramatically across countries. The gender gap rises particularly sharply with age in Korea, Japan, Luxembourg, the Netherlands and Switzerland (increasing by more than 40 percentage points between the population aged 20-29 years old and 45 and over). The size of the GGLI components at different ages helps better understand the age profile of the gender income gap and why it varies so much across OECD countries. In Chile, the Czech Republic, Greece, Korea, Italy, Japan and Mexico, gender labour income inequality is driven by an extremely high employment gaps at all ages: a significant share of women is absent from the labour market. In the Czech Republic, Hungary, Poland and the Slovak Republic, women withdraw from the labour market for several years following childbirth (Section 6.2.2) due to long entitlement periods for maternal leave. However, very low take-up in part-time after childbirth leaves some room for improvement of work-life balance for mothers. In Korea, Italy and Greece, women have their first child relatively late (they are among the oldest in OECD countries, over 30 years old on average – see OECD (2018[6]). In these countries, women typically begin their career and work for several years before becoming pregnant, but their withdrawal from the labour market, once they finally start a family, often proves permanent. In the Czech Republic, on the other hand, women tend to have their children first (the average age of women at first birth was 28.1 years in 2014), and only enter the labour market for a late career once their children have entered school. The activity rate of young Czech women with children (around 20%) is among the lowest of all OECD countries, indicating barriers to the participation of mothers in the labour market.

In Australia, Austria, Belgium, Ireland, Germany, Luxembourg, the Netherlands, Switzerland and the United Kingdom, gender disparities are important but employment gaps are of medium size: the earnings that women bring home are much lower than those of men due to frequent take-up of part-time employment (see Figure 6.14). The more frequent take-up of part- time is often a way for women with children to stay in the labour market (see Section 6.2.2), but part-time work is also sizeable among childless women in Australia, Germany, Ireland, the Netherlands and the United Kingdom (at least 14%).

Finally the hourly wage gap is a key component of the large gender disparities in Japan and Korea. In the latter country, however, the wage gap is relatively contained in the case of youth and increases dramatically with age (see also Section 6.1.2). The hourly wage gap play also a key role in many Nordic countries where the overall gender gap in labour income remains contained. This is notably the case of Iceland and Norway, whose GGLI would be among the smallest if it were not for a relatively large wage gap.

6.3.3. Occupational segregation

Men and women remain likely to work in different sectors and occupations across OECD countries (OECD, 2017[1]): women continue to be overrepresented in the service sector, specifically within areas such as retail, health and social work: 84% of employed women worked in the services sector in 2015 (60.7% of men), 11.6% in industry (32.6% of men); and 4% in agriculture (6.3% of men). This occupational segregation derives from: i) on the supply side, the self-selection of women into certain occupations/sectors28 (under-representation of women in STEM fields, early career choices and motherhood, gender gaps in entrepreneurship); and ii) on the demand side, the gendered preferences of employers.

Decomposing further the hourly wage gap, following a standard Oaxaca-Blinder decomposition (see Box 6.4), it is possible to obtain a measure of the contribution of individual and jobs characteristics, as well as occupation/sector gender differences to gender disparities in hourly wages.29 Gender differences in individual characteristics favour women on average (the GGLI would be 3.9% larger without this composition effect), mainly due to the higher educational attainment of women. However, this effect is exactly offset by the impact of occupational and sector segregation, which raises gender inequality by 3.9%. Occupational and sector segregation play an important role in the case of France, Iceland, Norway, and the United Kingdom.30 By contrast, firm-size and contract type are a key driver of the gender wage gap in Japan.

6.4. How can gender labour inequalities be overcome?

Depending on the key drivers of the GGLI in different countries, policy priorities are likely to differ, calling for policy responses that are tailored to country-specific conditions. For example, in a few countries, the main policy priority remains promoting women’s participation in the labour market so as to decrease the employment gap.31 However, success in reducing the employment gap may result in an increased take-up of part-time work by mothers. This outcome would be socially desirable so long as it is voluntary and not the result of constraining social norms, a lack of childcare facilities or insufficient demand for female work. As a consequence, in countries where part-time tends to become a trap for women's careers, countries may wish to adopt policies to mitigate the effect of part-time work on women’s earnings,32 and decrease involuntary part-time work – the goal being to give women free choice of their hours of work and minimise their dependency from the “main breadwinner’s” income. By contrast, in other countries, even without reducing working time, women still cannot take advantage of specific job opportunities around childbirth due to their heavier share of family responsibilities. In these countries, policy priorities should focus on reducing this burden. In all these cases, albeit with a different combination of policy tools depending on policy priorities, policy action should focus on reducing disincentives to work for women with caring responsibilities, providing adequate services and support for families with young children, and enhancing equity of opportunities and flexibility of existing schemes, so as to provide women with greater options on the labour market and freedom for their career choices.33 These policy tools are discussed in order:

Reduce financial disincentives to work: disincentives to work and barriers to female participation play a key role in the existing gender division of labour and in the GGLI. Therefore, providing adequate incentives for women and especially mothers to enter the labour market is key, especially for countries where the employment gap and/or the part-time component of the GGLI are high. Removing the disincentives induced by tax-benefit systems must also be a priority for those countries where raising labour market performance of mothers from lower socio-economic positions is a key priority, since these are the most affected by these disincentives.

Provide adequate paid leave options. Many OECD countries provide extensive paid leave programmes for parents around the time of childbirth – see OECD (2018[6]). Maternity and parental leave are important measures that help mothers combine childcare responsibilities with their work commitments, improving the work-life balance of both women and men (OECD, 2017[1]). Paid parental leave is associated with higher female labour force participation across countries, as it provides incentives to be employed prior to giving birth (to ensure paid leave eligibility) and gives women post-birth job security (OECD, 2017[1]). Leave policies have a significant effect on the employment of mothers, although the loosened connection with the labour market may be detrimental when leave durations are overly long – see Section 6.2.2 and Olivetti and Petrongolo (2016[27]). With the exception of the United States, all OECD countries have national schemes offering mothers a statutory right to paid maternity leave.
Correct disincentives in the tax-benefit systems through “make work pay” measures, 34 and individualisation of taxation. In many countries, work incentives for low-paid second-earner parents are weak due to high marginal effective tax rates for second earners when moving from non-employment to employment – the so-called participation tax rate – see OECD (2018[6]). After various deductions and changes in benefit entitlements, low-paid second-earner parents entering employment often take home less than 40% of their additional gross earnings. The effect of benefit withdrawal rules, and their interaction with taxes, can be significant for single parents and one-earner families. In fact, phasing-out of social assistance, as well as family and housing benefits often brings marginal effective tax rates close to 100%, particularly for families with one earner and two dependent children. Conversely, imperfect neutrality of taxation implies that in many countries sharing work equally amongst the members of the household (for example in the form of two part-time jobs with close-to-full-time hours) is more costly than unequal sharing (e.g. through one full-time and one low-intensity part-time jobs). This is particularly the case in Chile, Belgium and France for low-income households and in Germany and Switzerland for middle-income households – see OECD (2018[6]).
Reduce childcare costs. Childcare costs remain very high in some OECD countries (OECD, 2018[6]), further weakening financial incentives to work and therefore reducing the attractiveness of labour force participation (OECD, 2017[1]). These high costs act as a barrier to paid employment for second earners and single parents, especially those with less-educated women with low potential earnings. Indeed, on average across European OECD countries, more than one-in-five economically-inactive mothers with a very young child report that a lack of affordable childcare prevents them from looking for work (OECD, 2016a). High childcare costs dramatically increase the marginal effective tax rate for second earners when moving from non-employment to employment – see OECD (2018[6]). But the effects on marginal tax rate are also important when increasing working hours of second earners in many countries (Eurofound, 2016[28]).

Provide adequate services and support, also by increasing the flexibility of existing schemes: in order to give women a real choice in their leave and labour supply decisions, providing them with childcare facilities is key. Indeed, time spent on housework affects time spent in the labour market, and vice versa. The large increase in female labour force participation over the past decades was associated with a decline in time spent on unpaid home and care work, but women still bear the brunt of unpaid work and fathers spend a lot less time with children than mothers. In addition, while a considerable part of eldercare work takes place outside the household, some two-thirds of the inside-household carers are women, informal care being particularly prevalent in countries with relatively few paid care workers (OECD, 2013[29]). A disproportionate burden on women to care for children can deter mothers from re-entering full-time work and can make employers less likely to hire mothers or women of childbearing age (OECD, 2017[22]). It can indeed be difficult for working-age carers to combine paid work with caring duties and carers may choose to quit paid works or reduce the work hours. This may compromise their future employability and lead to either permanent drop-out from the labour market or to lower-profile subsequent careers.

Increase childcare availability35 by providing publicly subsidised early childhood education and care (ECEC) to children as a legal right (OECD, 2016[30]).36 Women are often involved in childcare duties, especially when care services are lacking or fail to meet the needs of full-time working parents. Indeed, those countries where the use of formal care is the lowest (such as Austria, the Netherlands, New Zealand, Switzerland or the United Kingdom) are those for which the gender gap in hours worked per worker is the greatest – see OECD (2018[6]). It is therefore necessary to provide alternatives to families caring for children at home by offering care in a form that can be reconciled with parents’ working hours.
Provide further financial support for low-income families, especially when childcare costs are very high (OECD, 2016[30]). Subsidising child care is all the more necessary to reduce inequalities between low- and high-skilled households. Childcare costs can indeed be prohibitively high, in particular for parents with disadvantaged backgrounds whose children are lagging behind in terms of ECEC access. This may explain the large differences in gender labour income gaps across educational levels in some countries (Figure 6.15, panel C).
Develop out-of-school care services. Out-of-school-hours care services remain under-developed in most OECD countries – see OECD (2018[6]) – and explain to some extent the relatively high share of part-time work among working mothers in some countries (such as Australia and Germany). Childcare issues do not disappear once children enter pre-primary or primary school. Children in the educational system do spend a large amount of time at school, but opening hours are frequently incompatible with a full-time working week and school holidays are almost always longer than annual leave entitlements for employees. Informal care services provided by friends or relatives can help, but these are not always available and working families with school-age children often need to find additional formal solutions both before and after school, and also during school holidays. A few OECD countries have developed extensive out-of-school-hours care systems for school-age children – see (OECD, 2017[1]) for more details).
Enable flexible working time arrangements to foster work-life balance. These include the availability of part-time work, working from home on an occasional or regular basis (teleworking), flexitime (allowing employees to adjust their daily working time, possibility to adapt their working time to take care of personal or family matters). OECD (2016[20]) provides an assessment of how workplace flexibility can help employees balance work and family responsibilities. The availability to choose one’s working time (within employer’s predefined limits) enables employees to devote their most productive hours to work, while also deal with their family responsibilities, relieving the pressure as regards family commitments. Flexitime may also decrease the tension of commuting at rush hour for both parents and childless employees. For flexible working time arrangements to be effective and not considered as “mothers’ working arrangements”, governments need to assure that their initiatives to promote workplace flexibility are designed so as to: i) grant all employees (and not just mothers of young child) a right to request flexible working arrangements; ii) encourage social partners to cover workplace flexibility in collective bargaining agreements; and iii) help companies change their work organisation.
Adopt measures to encourage men to spend more time at home caring for their children and their dependants more generally. In that respect, fathers’ leave-taking can be considerably effective. Indeed, while couples today tend to be fairly egalitarian in their division of (unpaid) household labour before children are born, things often change soon after childbirth. Women start doing much more unpaid work upon arrival of the first child, so that fathers’ leave-taking around childbirth can play a crucial role in relieving this burden (OECD, 2017[1]). Promoting men’s use of leave can also be achieved through the introduction or extension of “fathers-only” leave, such as paid paternity leave and longer periods of paid leave reserved for or targeted at fathers within parental leave systems (OECD, 2017[1]). These instruments can significantly contribute to promote re-entry of mothers into the labour market. However, paternity leave entitlements may not suffice if father are not encouraged to take it in their workplace. For example, Korea and Japan have generous paternity leave schemes but only 3% of fathers do take advantage of them. Governments could consider putting in place soft or hard incentives for employers to adopt effectively non-discriminatory practices against fathers taking voluntary paternity leave.
Countries must also strengthen support for informal carers, particularly for the elderly – such as cash benefits, respite care, training and counselling – and ensure that these benefits reach those who need them most, in particular low-income women. To meet those needs, many countries provide employees with a right to either flexible working time or to family-caregiver leave, but often without financial compensation and little flexibility. It is also important that such leave can be granted within a short notice period given that long-term care needs are largely unpredictable.

Other interventions involving actions beyond labour and social policy:

Promote women’s earning potential. Improving the acquisition of valuable market skills by women and enhancing their access to vocational training are key to raise the wages women can command on the market, as well as measures to reduce occupations and sector segregation. Policies to promote female employment in high-wage sectors and occupations are particularly important in countries where women are concentrated in low-paid occupations and sectors – as is the case for two thirds of the countries, see OECD (2018[6]). Considerable progress has been made in closing the education gap, resulting in girls even outstripping boys in educational attainment in many countries. However, further efforts are required to close remaining gender gaps in education (particularly in science, technology, engineering and mathematics) – see (OECD, 2017[1]). Moreover, the returns to these human capital investments will only be realised if women are actually employed.
Address stereotypes, reduce discrimination and promote female leadership. Virtually all OECD countries have put in place policies to address stereotypes and reduce discrimination through anti-discriminatory rules, anti-harassment actions and promoting change in employers’ perceptions and in social norms. The evidence suggests, however, that discrimination is more frequent in career progression and access to senior management positions – see (OECD, 2017[1]). Most OECD countries have initiated policies to promote gender balance on company boards and in senior management, such as gender quota in boards. However, these actions alone are likely insufficient without investing in promoting career progression and leadership development schemes for women, also based on peer-to-peer support – such as sponsorship, mentoring, building confidence and access to networks. But it is also critical to engage men leaders in achieving gender equality. Moreover, because workplace culture is central to sexual harassment, anti-harassment laws and initiatives targeting employers show promise and should be evaluated carefully. Many countries, as part of their awareness-raising campaigns, provide employers with information on employers’ obligations to prevent and respond to harassment and discrimination. Finally, ensuring that both women and men do not experience discrimination when they take leave from work to care for dependents is also key to promote the evolution of social norms (OECD, 2017[1]).

Success/failure factors:

Cultural expectations and values concerning female employment and dominant practices in the gendered division of care and family work may undermine policies (Eurofound, 2016[28]). The ideals regarding care and who is best placed to rear children and care about dependants indeed affect take-up of childcare and the social roles of men and women (Kremer, 2007[31]). Policy reforms should therefore be accompanied by campaigns addressing these cultural factors.
Experimenting with pilot programmes to assess the relative effectiveness of potential policy measures on different types of family households before implementing the nationwide measure should also be considered. Policies based on financial incentives or supportive interventions should be targeted based on evidence on which groups are more responsive to different types of policy actions (Eurofound, 2016[28]). This will allow clear targeting of the beneficiary population, avoid deadweight loss, and increase the effectiveness of the measure. It is also important to implement reforms intended to decrease labour supply disincentives for women gradually, so as to allow sufficient time for families to adjust to the changing incentives offered to them.

6.5. Concluding remarks

Despite sizeable improvements in the situation of women in the labour market during recent decades, gender inequalities remain a major issue for policy makers in OECD countries. This chapter has provided an overview of the working lives of women and how they compare with those of men, as well as an assessment of how those differences contribute to the persistence of significant gender gaps in labour market outcomes. This analysis confirms that the degree of gender labour inequality varies across countries, as does the form it takes and the relative importance of different types of gender gaps. The labour income gap between women and men increases over the course of their careers and is mostly the result of missed opportunities in terms of professional mobility during the early stages of women’s careers, and in particular during the years immediately following the birth of their children. This chapter has also documented the many ways in which childbirth affects female labour supply across countries in terms of labour market participation and the take-up of part-time work, as well as the longer-run implications of those choices for professional mobility and, therefore, income growth. Getting onto a good career track and staying on it is a strong determinant of future income growth, and missed opportunities following childbirth are particularly prejudicial. Life events like child birth, parenting (but also caring for the elderly in the family and family responsibilities more generally) affect both wage progression and the accumulation of earnings over a lifetime, and these career breaks also reduce pension entitlements (OECD, 2017[32]). However, while childbirth and other life events significantly affect women’s professional trajectories everywhere, the way they do so varies across countries. This suggests that policy can have a major impact.

This chapter proposes a framework to help governments better address the complex challenges involved in fostering gender equality by targeting their efforts on the most important gender gaps in labour market outcomes in each country. While this framework identifies the quantitatively most important sources of the overall gender gap in labour income per capita, more research is needed to identify the resulting implications for policy. In particular, new evidence is needed to better understand the respective role played by each policy measure on each of the different components of the gender labour income gap, in particular the gap in working hours. New research is also required to assess the role that collective bargaining can play in further reducing gender gaps through the setting of wages, anti-discrimination rules, and flexible working arrangements. Additional research is also needed to identify the impacts that megatrends such as digitalisation and population ageing will have on occupational segregation and gender gaps in labour markets, and how different policies can shape those impacts in order to promote greater gender equality.

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Supplementary material for Chapter 6

Supplementary material for Chapter 6 is available online only in English at the following DOI: https://doi.org/10.1787/empl_outlook-2018-15-en.

Notes

← 1. The gender gap in labour income is defined as the difference between average annual earnings of men and women as a percentage of those of men. Average earnings are computed by considering the whole working age population, independently of whether effectively working or not during the year. A person with no labour income, therefore, contributes to the denominator of average earnings but not to the numerator (see Section 6.3).

← 2. In the latter countries, which include Australia, Denmark, Finland, Germany, Iceland, the Netherlands, Norway and Switzerland, apprenticeship plays a major role in bridging educational and professional aspects. Interestingly, in the Nordic countries and the United Kingdom, more women than men take on this dual activity at the earliest career stage. In Finland and the United Kingdom, women once again combine education and work at very late stages of their career.

← 3. Retirement status is self-determined in Labour Force Surveys. While it is not possible to say whether all those who declare themselves being retired receive a retirement pension, the opposite is likely to be true.

← 4. Other general gender differences include the fact at all ages, more men are self-employed than women in all countries (OECD, 2018[6]). In some countries – Australia, Austria, Switzerland, the Czech Republic, Germany and the United Kingdom – women tend to be more often self-employed during the later stages of their careers, but this late-career increase in self-employment is much lower than for men. By contrast, unemployment is not particularly gender biased.

← 5. Gaps in full-time earnings are measured using hourly, weekly, monthly or annual earnings, depending on data availability. To the extent that the variability of contractual hours among full-time is limited, the gaps presented in Figure 6.3 can be assumed to proxy gaps in hourly earnings. Tests made on a limited group of countries for which both hourly and monthly earnings are available validate this assumption.

← 6. Doing so risks confounding true age effects with composition effects (e.g. changing educational attainment and labour participation across cohorts), changes in returns to individual characteristics (e.g. earnings differentials of a characteristic), and time variation effects (see Box 6.2).

← 7. Changes in female workforce composition (women’s investment in market skills, leading more able women to select and enter into full-time employment) help explain why growing wage equality between genders coincided with growing inequality within gender (Mulligan and Rubinstein, 2008[49]).

← 8. Glass ceiling is the “unseen, yet unbreachable barrier that keeps […] women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements, that women confront as they approach the top of the corporate hierarchy” (United States Federal Glass Ceiling Commission, 1995[41]). The existence of a glass ceiling to women’s career perspectives which excludes them from high-earnings and high-status positions has been well documented in the literature – e.g. Biewen and Seifert (2016[43]). The term “leaky pipeline” is usually employed to refer to the attrition in the number of women who advance to management levels. OECD (2017[1]) concludes that over the past decade, the glass ceiling remains intact and the “leaky pipeline” to top jobs has contributed to women making up only about one-third of managers in the OECD, though there is considerable variation across countries.

← 9. Addison and Portugal (1989[34]) show that there are gender differences in match quality and changes in match quality over the course of careers: women are more often mismatched than men. This is true even for women with the best early-career matches.

← 10. Based on Norwegian panel data, Kunze (2014[37]) shows that women with children are 25% less likely to be promoted than women without children; what the author calls the “family gap in climbing the career”. Analysing gender differences in job search behaviours, Kunze and Troske (2009[38]) show that displaced women take longer to find a new job than men in a comparable situation, and that these differences are driven by differential behaviour of prime-age women, whereas no significant gender difference is apparent for younger and older workers.

← 11. Every year in France, 12% of the working-age population experience a professional transition and this is the case of 17% of the active population. These results are consistent with Flamand (2016[44]) who finds that in France labour transitions of the active population are relatively stable – around 16% on average each year– and evolve in line with the business and employment cycle.

← 12. The cumulative number of transitions ranges from 6 in Greece, Italy, Portugal and Slovenia to more than 15 in Australia, Finland, Iceland, Japan and Sweden.

← 13. The impact of in-work transitions on income is not gender biased, that is they do not significantly increase men’s income any more than they do for women’s income. The female coefficient presented in Figure 6.7, Panel B is the marginal effect of the female coefficient, not the cross-effect of female with in-work transition (which was not significantly different from zero in almost all countries).

← 14. Alon and Tienda (2005[42]) show that unskilled women who experience frequent job changes during the first four post-school years reap positive wage returns, but turnover beyond this “shopping” period incurs wage penalties. By contrast, unequal returns to job mobility drive the gender wage gaps for skilled women. Adda et al. (2012[33]) also find that sources of wage growth differ by skill level, with learning-by-doing being an important component early on for unskilled workers, whereas job mobility is important for workers who acquire skills in an apprenticeship scheme before labour market entry.

← 15. Age patterns of labour mobility (available upon request) are different for men and women, and can partly explain the gap. It emerges that women: i) experience professional transitions less often than men when they are young (in particular in-work transitions); ii) change their professional situation more often than men at prime age, due to higher entries into and exits from inactivity; and iii) less often go through a professional change than men above the age of 55 years.

← 16. OECD (2015[5]) also shows that earnings mobility (defined as movements in and out the labour market and up and down the wage ladder) is not lower for women than for men, but the incidence of low long-term earnings is much higher among women than men, affecting about one in four working women as compared with only one in twenty men. Equal short-term earnings mobility associated with low long-term earnings among women reveals the role played by career path dependencies, i.e. the impact that early professional mobility have on future career success.

← 17. Available evidence suggests that men and women with the same level of education tend to enter the labour market at similar wage levels, but wages begin to diverge during the early career (Fitzenberger and Kunze, 2005[45]; Manning and Swaffield, 2008[39]).

← 18. The existence of inequalities before the first childbirth suggests that the arrival of a child is not the only factor – see for example Briard and Valat (2018[46]). Social norms and preconceptions about women are likely to play an important role in the formation and evolution of gender inequalities throughout their working lives, although their respective contributions cannot be assessed.

← 19. 6 log points for mothers with one child and 13 log points for mothers with two children according to Waldfogel (1997[40]).

← 20. Briard and Valat (2018[46]) provide a lifecycle analysis of the gender wage gap in France. Gender inequalities appear before the arrival of the first child, especially for non-graduates, and increase further after childbirth. More often than women, men reach a good professional position before becoming parents. Inequality increases the most at the time of the first childbirth, regardless of the final number of children and continues to widen afterwards, but at a slower pace.

← 21. The possible presence of other older children may impact estimates in Figure 6.9. Nevertheless, the age of the youngest child is more likely to have a direct effect on the mother’s labour market attachment and work intensity.

← 22. Andrén (2011[47]) also suggests the existence of an “absence penalty” of part-time work, increasing with the duration of part-time work, which could be interpreted as the effect of slower human capital accumulation for individuals working part-time. The study estimates that, in Sweden, full-time working men earn 26% more than part-time ones, and that full-time working women earn 13% more than their part-time counterparts. However, when observable factors (e.g. occupations) are taken into consideration, only men's wages are significantly affected by part-time work: the pay gap is reduced to 9% for men and 2% for women.

← 23. Figure 6.11 is based on country-specific probit regressions of the dependent variable “employed part-time” with female cross effects for all controls including age categories. All marginal effects are not shown in Figure 6.11, but available upon request.

← 24. As discussed in Box 6.1, while the cross-section data presented in Section 6.1.1 can provide a very detailed snapshot of gender differences in employment and hours worked for different age classes, panel data or retrospective data are necessary to examine the consequences of those employment patterns for individual careers.

← 25. While career lengths are presented to age 50, the conclusions presented remain valid when looking at career lengths up to age 65. Nevertheless, due to the nature of the SHARELIFE dataset (retrospective data) used for these estimates, sample sizes are considerably reduced if the focus is solely on workers who have reached their 65th birthday at the date of the interview. Up to 65 years old, total career lengths of men, childless women and women with children are, on average, 40.3, 29.3 and 21.4 years, respectively.

← 26. These figures rely on long retrospective data which have two limitations. First, there is a sizeable memory bias being based on the recollection by elderly people (at least 50 years old in 2009) of their entire work history. Most importantly, as pointed out in Box 6.1, they reflect the career experiences of a specific cohort that faced social norms about working women and labour market conditions that differ from those that later cohorts face. For example, labour mobility rates in many European countries tended to be lower than their current levels and many people used to remain with the same company for most or all of their careers (the oldest respondents entered the labour market in the 1960s). Second, women now participate much more in the labour market and for a much longer period. Therefore, gaps in career length may have changed considerably and the results reported in Figure 6.11 are unlikely to predict accurately what will happen to more recent cohorts of women. Nevertheless, when looking at the activity status of women in 2014-15 (see Figure 6.2), some of the main stylised facts identified for this older cohort are clearly visible, revealing sizeable inertia: employment gaps remain sizeable even for middle-aged women from recent cohorts in Greece, Ireland, Italy and the Netherlands. Therefore, even if career length gaps may have decreased for younger cohorts, they will remain significant in these countries.

← 27. See also Chapter 1 for the latest available data.

← 28. Women experience higher levels of occupational segregation than men, and are restricted in the jobs they “choose” to go into by a variety of factors, including educational background and gendered socialisation. OECD (2017[1]) provides an “index of dissimilarity” based on the number of different occupations women work in compared with men. Every country shows evidence of occupational segregation by gender, but rankings are somewhat difficult to interpret as they cannot account for factors such as self-selection or cross-country differences in female employment rates. Indeed, the Nordic countries have historically higher levels of occupational gender segregation and Mediterranean countries lower levels, in part because increases in occupational segregation have positively correlated with growth in female labour supply (European Commission, 2009[48]).

← 29. The gender pay gap for full-time employees can be further decomposed into several sub-components – see Box 6.3 and OECD (2018[6]): i) the impact of gender differences in observable individual and job characteristics (e.g. gender differences in educational attainment, employment status and contract type); ii) the impact of gender occupational segregation; and iii) the unexplained component of the hourly wage gap, which represents discrimination and the effect of other non-observed factors (e.g. field of study, attitudes, labour market experience, match quality and the number of previous jobs held). Most of the hourly wage gap nevertheless remains unexplained (38% on average).

← 30. The effect of occupational segregation is likely to extend beyond hourly wage gaps, although this additional effect is not estimated here. Evans (2018[51]), for example, estimates gender pay gap for full-time and part-time workers in different occupations and finds that where the pay gap is largest (skilled trade occupations), men have a much larger share of full-time employment while where it is smallest (sales and customer service occupations), full-time employment shares are almost equal across gender. This pattern reinforces the relative importance of occupational segregation on the gender gap in annual labour income.

← 31. Eurofound (2016[28]) estimates that the total cost arising from women’s lower employment rate in the European Union was around EUR 370 billion in 2013, corresponding to 2.8% of the EU’s gross domestic product (GDP).

← 32. Adema, Clarke and Frey (2015[35]) point out that working part-time, especially when it is of a permanent rather than a temporary nature, has negative effects on career progression. The lack of flexibility within firms also means that women will disproportionately suffer because of working shorter hours or requesting a specific family-friendly work schedule. Goldin (2014[36]) shows that there is a wage penalty attached to working short hours, while in some sectors – particularly the corporate, financial, and legal sectors – many firms offer disproportionate promotions to employees working long, continuous hours at certain times of the day.

← 33. See for example Adema, Clarke and Frey (2015[35]), OECD (2016[30]; 2017[1]), Eurofound (2016[28]), Fernandez et al. (2016[50]), and Olivetti and Petrongolo (2016[27]) for comprehensive assessments of gender employment and earnings gaps, as well as literature reviews on the effectiveness of labour market policies (including ALMP, tax benefit systems, flexible working time arrangements) and family policies (including childcare support measures and leave policies).

← 34. Good practices to reduce these disincentives include the In-Work Credit for Lone Parents (the United Kingdom) and phasing out transferability of general tax credits (the Netherlands) – see Eurofound (2016[28]) for more details.

← 35. Countries’ provision of childcare facilities and subsidies and their elaboration of tax-benefit models and their resulting (dis)incentives set the overall framework to which women react in decisions regarding their working life (their labour supply and working hours). Women should be given a real choice as to whether to work or not, and this choice should not be dictated them by insufficient public provision of early-childhood services. In Denmark for example, parents are entitled to a guaranteed day care place for their children at the end of the parental leave period. Local authorities are responsible for providing places, and must cover parents’ expenses for a private care scheme or a place in another local authority if they fail to do so within a four-week waiting period (Eurofound, 2016[28]). The result is that 65% of Danish children aged 0-2 years are enrolled in childcare or preschool; in this, Denmark is the best OECD performer. Disincentives for mothers to work due to excessive childcare costs and insufficient childcare provision explain in large part women’s deficit in employment.

← 36. OECD (2016[30]) provide an overview of childcare take-up in OECD countries. On average, only one-third of the children under age three have access to early childhood education and care (ECEC), with significant differences across countries. In Sweden and Denmark, public childcare systems provide guaranteed access to a high-quality, flexible service at heavily-subsidised rate. In Sweden, children are guaranteed a place in formal childcare once they are one year old. The service is open to all parents and operates on a full-time basis; most facilities are open over a 12-hour period.