5. Different statistics of gender pay gaps

Economic gender equality refers to the distribution of economic resources by gender and, as it stands, men – in the Nordic countries included – generally have access to greater economic resources than women, although there are significant differences within groups of women and men (Keeley, 2015; OECD, 2018). In general, men earn more than women – this holds true when looking at unadjusted or adjusted measures, structural pay gaps or, for that matter, disparities in disposable income.

The following section discusses different statistics of the gender pay gap. As different measures can be used to show different aspects of economic inequality, it is important to have an understanding of what each concept means.

An individual’s income can come from labour, capital or transfers through welfare systems (e.g. pensions, sickness or parental payments or benefits of various kinds, such as child or housing allowances). Disposable income is the sum of income from labour, capital and welfare transfers and is a measure of money that is available to spend. This is usually measured at the household level rather than the individual level, which means that it can be difficult to distinguish differences between women and men as groups, but as an illustration, a study by Statistics Sweden (SCB) showed that, in 2020, 69 per cent of total capital income (interest, dividends and capital gains) in Sweden went to men and 31 per cent to women (SCB, 2022; see also Ekberg & Beijron, 2023a; Søgaard et al., 2018).

However, capital income is extremely unevenly distributed among the population, and for the majority of individuals aged 18–64 in the Nordic countries – regardless of gender – income from work, or pay, is the most significant type of income. Here too, there are various measures of differences between women and men as groups, as discussed below.

The unadjusted or unweighted gender pay gap shows the difference in average pay (gross, i.e. before tax and transfers) between women and men, i.e. the difference between the sum of all men’s pay and the sum of all women’s pay expressed as a percentage.

National statistics may differ between countries in terms of whether they compare hourly or monthly pay and which pay supplements, if any, are included in calculations. There are also sometimes differences in comparisons of full- and part-time pay, depending on whether part-time pay is converted to full-time pay or vice versa (see Salminen-Karlsson & Fogelberg Eriksson, 2025, for a more detailed discussion).

Using this measure, the pay gap in the Nordic countries in 2021 was between 10.4 per cent (Iceland) and 16.5 per cent (Finland), compared with the EU average of 12.7 per cent (Eurostat, 2024c).

That this measure of the pay gap is unadjusted means that it does not take factors such as age, education, working hours, occupation or sector into consideration. Women, as a group, are more likely to work part time than men, either voluntarily or involuntarily, which means that the difference in disposable labour income between women and men is greater in practice than the unadjusted pay gap shows. In the Nordic countries, the level of part-time work for women varies between 23 per cent (Finland) and 35 per cent (Norway), compared with the EU average of 29 per cent, whereas for men the figure is between 11 per cent (Finland) and 15 per cent (Norway), compared with the EU average of 8 per cent (Eurostat, 2024f).

The gender pay gap also varies with age, as it tends to be smaller when people enter the labour market and increase over time, for example due to differences in the impact of parenthood for women and men (Barth et al., 2021; see also Salminen-Karlsson & Fogelberg Eriksson, 2025, & Wagner et al., 2020, for a discussion of how age interacts with other factors, such as education). In the Nordic countries, the gender pay gap varies between 0.7 per cent (Iceland) and 5.9 per cent (Finland) for the under-25 age group and between 14.5 per cent (Sweden) and 17.9 per cent (Finland) for the 55–64 age group (Eurostat, 2024b).

Similarly, a figure for the unadjusted gender pay gap being lower does not mean that a labour market is more gender equal compared to if the figure was higher. In the EU, this can be illustrated by comparing Italy and Denmark, where the unadjusted gender pay gaps in 2023 were 5 per cent (Italy) and 14.2 per cent (Denmark) respectively, while the female employment rates in the same year were 52.5 per cent (Italy) and 74.2 per cent (Denmark) (Eurostat, 2024e).

In countries where a lower share of women participate in the labour market, the unadjusted gender pay gap is often smaller, which can be explained by the selection effect; in countries with lower female employment rates, a narrower group of women – for example, single women without children – are part of the labour force, and they tend to be less likely than other groups of women to be underpaid (Olivetti & Petrongolo, 2008). The Nordic countries are all characterised by relatively high female employment rates, well above the EU average, largely due to a history of subsidised and high quality childcare and elderly care, as well as generous parental leave schemes for both parents (Nordic Council of Ministers, 2019; cf. Lewis, 2002; Hegewisch & Gornick, 2011). In 2023, the employment rate in the Nordic countries varied between 74.1 per cent (Finland) and 81.3 per cent (Iceland), compared with the EU average of 65.7 per cent for women and between 73.9 per cent (Finland) and 85.9 per cent (Iceland), compared with the EU average of 75.1 per cent for men (Eurostat, 2024e).

At the same time, labour markets in the Nordic countries – like in other OECD countries (Fluchtmann & Patrini, 2023) – are highly segregated by gender (and other identifiers, such as migrant background, socio-economic status, etc.; see, e.g., de los Reyes, 2014). In 2023, between 71.9 per cent (Denmark) and 79.4 per cent (Finland) of women worked in female-dominated industries, compared to the EU average of 75.1 per cent, while between 76 per cent (Denmark) and 79.2 per cent (Norway) of men, compared to the EU average of 74.7 per cent, worked in male-dominated industries (Nordic Statistics, 2024).

The combination of high female labour force participation and a highly gender-segregated labour market is sometimes referred to as the Nordic gender paradox. This is associated, for example, with gendered study choices; among other things, women in countries characterised by high economic prosperity that rank highly on various gender equality indices are less likely to seek educational paths and careers in science, technology, engineering and mathematics (STEM) (Stoet & Geary, 2018; see also Jansson & Sand, 2021). These male-dominated occupations are generally better paid than, for example, occupations in health and social care, where most women in the Nordic countries work (Reisel et al., 2015; Badgett & Folbre, 1999).

Another measure for comparing women and men as groups is the adjusted pay gap, which takes into consideration various factors – such as age, education, working hours, occupation or sector – that can affect pay, or explain pay differences (see, e.g., Larsen et al., 2020; Ekberg & Beijron, 2023b; Grini & Alseth Fløtre, 2023). It is also referred to as the standard-weighted pay gap, if standard weighting is the method of analysis used. The adjusted measure is often smaller than the unadjusted pay gap, mainly because women and men largely work in different occupations characterised by different pay levels, and when you adjust for that, the figure is lower.

As an illustration, a calculation based on Eurostat data for 2018 shows that the difference between the unadjusted and adjusted pay gap across the Nordic countries can vary between 2.6 (Iceland) and 5.9 per cent (Finland), compared to the EU average of 3.2 per cent. The factored variables are age, education, occupation, years in position, permanent or fixed-term contract, full-time or part-time employment, economic activity classification, private or public sector, size of organisation and regional breakdown (Pérez Julián & Leythienne, 2023). This calculation has been conducted using regression analysis, a commonly used method in labour market research that allows for the use of more detailed information than in standard weightings (see also Ekberg & Beijron, 2023b).

In addition to the fact that women and men largely work in different occupations with different pay levels, part of the unadjusted pay gap was previously explainable by educational attainment. However, this is no longer the case. In recent decades, education levels in OECD countries have risen steadily and in most countries women, in particular, are increasingly educated. In the Nordic countries, as well as some others, the gap in educational attainment between women and men as groups is widening. However, the share of women in STEM-related education paths remains low, with the exception of fields in the natural sciences orientated towards life sciences (biology, medicine, etc.) (Kahlroth, 2018; OECD, 2017; Huyer, 2015). In 2021, the share of female graduates from higher education in the Nordic countries ranged from 56.2 per cent (Denmark) to 68 per cent (Iceland), compared to the EU average of 57.2 per cent (Eurostat, 2024d), while the share of female graduates from tertiary education in STEM subjects the same year ranged from 29 per cent (Norway) to 42.8 per cent (Iceland), compared to the EU average of 32.8 per cent (Eurostat, 2024a). As a study by the Swedish Confederation of Professional Associations (Saco) shows that certain occupations may be unfavourable from a lifetime earnings perspective (taking into account, among other things, the loss of income suffered by academics during their studies, as well as the, in many cases, higher earnings they receive during their working lives). It would be more profitable, for the individual, to start working immediately after upper secondary school, instead of pursuing higher education to qualify for these occupations. In this study, these include biomedical analysis, dental hygiene, library and information science, occupational therapy, physiotherapy, art education and biology. Most of these programmes lead to professions that are heavily dominated by women (Ljunglöf & Simonsen, 2020).

The adjusted pay gap is also referred to as the unexplained pay gap, as it represents a difference in pay between women and men that cannot be explained by the selected variables. These unexplained gender pay gaps are not necessarily the same as unjust pay gaps, as the term is used in discrimination legislation. In 2018, there was an unexplained pay gap in the Nordic countries of between 7.4 per cent (Sweden) and 11.2 per cent (Finland), compared with the EU average of 11.2 per cent (Pérez Julián & Leythienne, 2023). Behind these figures there can be some occurrence of pay discrimination in the legal sense, i.e. that one individual receives lower pay than another in a comparable situation simply due to their gender or based on other discriminatory grounds. Legislation on discrimination aims to address such unjustified pay differences (Ekberg & Beijron, 2023b; see also Kumlin, 2016). The overall, statistical level of wage differences, with their explanatory factors, is not relevant either for the analysis of wages at individual employers or for the legal examination of the same. However, the statistics can be of great importance in gaining insight into and being able to work with the structural factors that can be assumed to have an impact on the wage differences between women and men.

Unexplained pay gaps may also be due to variables that cannot be accounted for in statistical calculations, but which do not necessarily have an undue basis. These may include time an individual has spent outside of the labour market due to, for example, parental leave, or norms and expectations when negotiating starting pay for a job. The EU’s Pay Transparency Directive aims to address some of these (see also Stüber, 2024). The fact that there are unexplained pay differences that are not due to inappropriate pay setting can be assumed to be a result of societal structures and norms related to women’s and men’s expected roles, for example linked to caring responsibilities or perceptions of competence, which shape individuals’ choices.  The existence of wage differences at an overall level is the reason why legislation has been enacted to prohibit wage discrimination, for example with requirements, in all Nordic countries except Denmark, for employers to conduct wage surveys. Despite this, wage differences persist, as statistics show.

In addition to wage discrimination in the legal sense, the term discrimination is also used in a sociological sense, which should not be confused with the legal definition. In contexts where the non-legal meaning of discrimination is used, structural wage differences are sometimes discussed in terms of value discrimination, which refers to occupations mainly held by women being valued, and thus paid, less than occupations with similar qualification requirements mainly held by men (Harriman et al., 2024; Ekberg & Beijron, 2023b). Unlike other forms of discrimination, value discrimination targets groups rather than individuals, and it also affects men in female-dominated occupations to some extent (for examples of pay comparisons between men in female-dominated occupations and those in male-dominated occupations, as well as the equivalent comparisons for women, see Salminen-Karlsson & Fogelberg Eriksson, 2025).

There are no official statistics based on pay comparisons between occupations dominated by women and occupations dominated by men with similar qualification requirements, despite the fact that countries that have adopted the 2030 Agenda have undertaken to provide annual reports on pay differences to fulfil the goal of ensuring equal pay for work of equal value (Target 8.5). Instead, reported statistics relate to pay differences between jobs with the same occupational code, i.e. jobs that are similar rather than of equal value (see also Stüber, 2024).

In the Nordic countries, there are examples of more or less far-reaching attempts to develop indicators of pay differences between work of equal value, or in other words a measure of value discrimination in a gender-segregated labour market.