As discussed in the previous section on different statistics of gender pay gaps, there are a variety of factors, both structural and individual, that can be used to explain the findings from empirical data. In EU cooperation, a model developed by the European Commission is often used to shed light on women’s and men’s pay as well as underlying factors of particular importance (European Commission, 2022).
The model is based on four different criteria that are intended to be used to support the identification of solutions on the way to equal pay for equal work and work of equal value:
Sectoral segregation – that women and men largely work in different occupations and sectors and that occupations and sectors dominated by women are characterised by lower pay than those dominated by men.
Unequal distribution of paid and unpaid work – as groups, women work more hours per day than men, but a large proportion of the work done by women is in the form of unpaid care and domestic work.
Hierarchical segregation (the ‘glass ceiling’) – the higher up the labour market hierarchy a position is, the lower the proportion of women in that position; increased power and status is correlated with increased pay and other forms of income (e.g. from capital).
Pay discrimination – women are paid less than men even when they do equal or equivalent work, despite all the policies and legislation in place to prevent this.
This model encompasses the various explanatory factors that emerged in the previous chapter but introduces the concept of hierarchical segregation – or the ‘glass ceiling’, i.e. that men more commonly occupy decision-making positions, and these positions are well paid (see, e.g., Kräft, 2022). Sectoral segregation can be seen as composed of a horizontal dimension, i.e. the actual distribution of women and men in different occupations and industries, and a vertical dimension, i.e. a difference in social status between these different occupations and industries (Bettio & Verashchagina, 2009). Researchers have explained these phenomena as reflecting norms of gender essentialism, that women and men are differently suited to different tasks, for example linked to care or technology, and male privilege, that men are associated with higher status and that male-coded areas are more highly valued (Charles, 2003; Charles & Grusky, 2004; Kanter, 1977; Abrahamsson, 2002).
Gender labelling of occupations and industries, based on social norms about the tasks to which women and men are suited, reproduces segregation in the world of work, leading women to tend towards jobs with high female visibility and men towards jobs with high male visibility (Badgett & Folbre, 1999; Breda et al., 2020; Charles & Thébaud, 2018; O’Reilly et al., 2015; Peetz, 2015). Other researchers point to a link between social norms that associate unpaid care and domestic work with femininity and the low pay that characterises ‘female occupations’ in health, education and social care (Nicolás-Martínez et al., 2024; Rubery & Grimshaw, 2015).
Aside from gender, other factors, such as a migrant background, socioeconomic status, etc. have an impact on the conditions people face in the labour market (de los Reyes, 2014; Young Håkansson et al., 2022). These factors affect pay and working conditions for individuals, as well as compounding structural segregation that results in certain individuals being employed in specific roles and industries. The EU Pay Transparency Directive (EU 2023/970) emphasises the importance of taking intersectional discrimination into account. Factors beyond gender need to be used in comparisons of pay between women and men, but national statistics have some limitations in this respect (Salminen-Karlsson & Fogelberg Eriksson, 2025).