The report presents the results of a pilot study that investigated how available official statistics can be used to analyse pay differences between women and men for work of equal value at the national level in the Nordic countries. In particular, statistics from Finland, Norway and Sweden were analysed. The pilot study took place within the framework of the Nordic Council of Ministers’ project on equal pay for work of equal value in the Nordic countries.
A review of previous research found that the gender pay gap persists despite laws and regulations. A common explanation for the pay gap is the gender-segregated labour market, i.e. that the labour market is divided into occupations dominated by men and those dominated by women. Occupations dominated by women are often undervalued in terms of pay compared to those dominated by men with equal requirements. Legislation has not been able to achieve equal pay for work of equal value, and the Nordic pay formation model has actually been counterproductive to closing the gender pay gap.
National occupational classifications are important for pay comparisons. Although all countries follow an international standard, occupational classifications vary to some extent between them. The way in which pay is defined, i.e. the pay measures used, in national statistics also varies between countries. There is also some variance in how monthly pay is defined, and hourly pay is sometimes used as a measure of pay in the statistics. This affects the comparability of pay for work of equal value both within and between the Nordic countries. The statistical variables mean and median are both used to measure pay gaps but can yield different results. With regard to national statistics on pay and gender across occupations, each Nordic country has its own specific challenges and shortcomings that affect the comparability of pay between occupations in which work of equal value is performed.
This study examined how statistics can be used based on existing assessments of work of equal value between various occupations. Example comparisons between occupations dominated by men and those dominated by women indicate significant pay gaps. Pay also varies between the private and public sectors, which means that pay gaps between different occupations doing equal work vary when sectoral affiliation is taken into account. While the pay gap has narrowed somewhat over time, there are still significant differences between occupations and sectors.
In general, women in the Nordic countries are more likely to work part time than men, and the general pattern is that part-time work has a negative impact on pay. However, the prevalence of part-time work varies across occupations and the extent of working hours can affect pay in different ways.
Although job requirements, and not the characteristics of the worker, should be the basis for assessing if occupations are equal, factors such as age and having a migrant background affect pay and the pay gap at the national level. Age is also included as an indicator for the UN 2030 Agenda (UN 2025) target. In terms of educational attainment, occupations dominated by women often have higher educational requirements than those dominated by men at the same pay level.
Recommendations
The recommendations from the pilot study set out basic requirements for official national statistics and stipulate the statistics that should be available for analyses on gender and pay for work of equal value at the national level:
Information describing occupations dominated by women and those dominated by men in equal level of detail
Statistics on pay at the most detailed level of occupational classification, as far as possible
Statistics on the number of men and women in various occupations in a shared table with pay
Data on both mean and median pay for occupations included in the classification system
Pay data for the private and public sectors (public sector data should be divided into central and local government) both individually and combined
Readily available data on the number of men and women working full time and part time in each occupation and on full-time and part-time pay
Data on age structures in different occupations in a shared table with pay
The number of domestic and foreign-born workers within an occupation, broken down by gender and mean and median pay, at least in occupations with a significant number of foreign-born workers
Data on education linked to gender and pay
Time series, at least for data on both mean and median pay and the number of men and women in occupations at the four-digit level of the classification systems, by sector and for sectors combined.