3. The nature of pay gap reporting: What is reported?

Pay reporting regimes require, at the minimum, average or median pay statistics disaggregated by gender. Table 3.1 provides an overview of what pay information is required in the private sector as part of mandatory pay reporting and whether this information is further disaggregated by worker characteristics. For instance, many countries require gender pay gaps or pay information to be further disaggregated by job category, while very few countries – notably Canada and New Zealand (public sector1) – require gender pay gap statistics also be disaggregated by race/ethnicity.

Presenting the overall, firm-level gender pay gap has benefits. It helps to reduce administrative burden on firms, as firms do not need to assess disaggregated information; it encourages businesses to consider how horizontal and vertical segregation contributes to wage discrepancies; and it helps to increase awareness of pay equity with a single, tangible statistic (OECD, 2021[1]). This strategy is used in the United Kingdom and Korea (see Box 3.1).

At the same time, reporting only the total gender pay gap can hide disparities and perhaps even discrimination among employees in comparable positions. This lack of clarity can make equal pay disputes even more difficult to resolve. In other words, reporting only the company-wide gender pay gap might not go far enough to support specific individuals who could be unfairly underpaid for doing equal work or work of equal value (OECD, 2021[1]).

Table 3.1 presents the information required in pay gap reporting, identifies whether countries have implemented non-pay reporting requirements (elaborated further in Table 3.3) and states whether follow-up mechanisms are embedded in pay reporting. Table 3.2 and the related discussion in Section 3.2.1 elaborate on the details of different job categorisations/job classification systems used across the OECD.

In most countries, gender pay differences are reported (at a minimum) as mean or median gender pay gaps across the company. This includes Canada, Chile, France, Iceland, Ireland, Israel, Japan, Korea, New Zealand (public sector, see endnote 1), and the United Kingdom.

The definition of pay varies by country, with some countries including bonuses and other variable components on top of base pay. These countries include Canada (under the Pay Equity Act2), France Iceland, Japan, and Korea. In other countries, bonus and variable pay gaps are reported separately, for instance in Canada (under the Employment Equity Act, see endnote 2), Ireland, and the United Kingdom. This approach of separating base and bonus pay is similar to that in the EU Directive on pay transparency (Chapter 2, Box 2.2).

Another common approach is to have employers report mean or median pay by gender – that is, separately for women and for men. In countries with gender-disaggregated pay reporting, this can either include variable components like bonuses (Denmark, Lithuania, and Norway) or can report on these variable components separately (Belgium, Italy, and Spain).

Finland and Sweden do not specify the exact statistics to be reported in their legislation. However, Finnish rules require that employers show that “salaries (including basic salary and variable component such as bonuses) are equal” between men and women and Swedish rules mandate companies to analyse pay differences between women and men as well as provisions and practices relating to pay. Reporting requirements in both countries are embedded within equal pay audits (see Chapter 4), which demand a thorough and comprehensive understanding of potential gender differences among the organisation’s employees.

Many countries have developed practical tools to help employers calculate and report gender pay gaps, such as gender pay gap calculators, online reporting portals, step-by-step guides, checklists, as well as video recordings. Many countries have also designated a first contact point for when questions arise. A more detailed discussion of guidance offered to employers, as well as practical tools for calculating and presenting gender gaps, are presented in Chapter 7 of this report.

Instructions for how to collect and analyse gender wage gap data can be basic or very detailed. In Japan, for example, employers are simply instructed to divide the female workers’ annual salary by that of male workers. The Irish regulations (Employment Equality Act, 2022, p. 7[6]) provide a good example for detailed instructions on computing gender pay gaps. For instance, the following data relating to mean hourly remuneration should be published in Ireland:

Art. 7(1) (…)

(a) the difference between the mean hourly remuneration of relevant employees of the male gender and that of relevant employees of the female gender expressed as a percentage of the mean hourly remuneration of relevant employees of the male gender;

(b) the difference between the mean hourly remuneration of part-time employees of the male gender and that of part-time employees of the female gender expressed as a percentage of the mean hourly remuneration of part-time employees of the male gender;

(c) the difference between the mean hourly remuneration of relevant employees of the male gender on temporary contracts and that of relevant employees of the female gender on such contracts expressed as a percentage of the mean hourly remuneration of relevant employees of the male gender on temporary contracts.

Art. 7(2) For the purposes of subparagraphs (a), (b) and (c) of paragraph (1), the difference between the mean hourly remuneration of persons of the male gender and that of persons of the female gender, expressed as a percentage of the mean hourly remuneration of persons of the male gender, shall be determined in accordance with the following formula:

[(A – B) / A] x 100, where

(a) in relation to paragraph (1)(a), A is the mean hourly remuneration of all relevant employees of the male gender, and B is the mean hourly remuneration of all relevant employees of the female gender,

(b) in relation to paragraph (1)(b), A is the mean hourly remuneration of all part-time employees of the male gender, and B is the mean hourly remuneration of all part-time employees of the female gender, and

(c) in relation to paragraph (1)(c), A is the mean hourly remuneration of all relevant employees of the male gender on temporary contracts, and B is the mean hourly remuneration of all relevant employees of the female gender on such contracts.

How gender pay gaps are reported to stakeholders matters, too. Using a randomised control trial, the Behavioural Insights Team commissioned by the UK Government Equalities Office tested five alternative ways3 of communicating the wage gap (United Kingdom Government Equalities Office, 2018[7]). The study revealed that benchmarking information – placing a company’s result in the context of other companies’ results – helps readers differentiate between companies with high gender wage gaps and companies with low ones. When statistics are presented in terms of money, rather than a simple percentage, the ability to understand the gender pay gap is maximised. A likely explanation for this is that people relate to monetary comparisons (e.g. 90 pence to every pound) more easily than percentages. The findings of this study have direct implications for the effectiveness of pay reporting rules.

In a few countries, pay information must be reported for all employees – either as a part of pay transparency regulations, or as part of pre-existing data collection efforts. For example, the Australian Workplace Gender Equality Agency analyses average firm-level gender pay gaps for base salary and for total remuneration, i.e. base salary plus all bonuses and other benefits. (Please see Box 3.2 for more information).

A handful of countries use pre-existing data sources with individual-level pay information for their pay gap reporting processes. In Denmark, Statistics Denmark uses linked employer-employee earnings data for every employee to calculate the wage gap. Lithuania also uses individual-level data from social security contributions. Portugal collects and analyses individual workers’ information through a survey called Quadros de Pessoal, which covers all firms with at least one employee in Portugal. Australia is exploring ways by which data already held by the government can be used for similar purposes. For a detailed discussion of these approaches see Chapter 7.

This approach of integrating reported pay information for all employees into a central system enables the comparison within a company, across companies and the sector more broadly, at regional levels, and across time. This strategy has been recommended by other studies of pay transparency (OECD, 2021[1]) (Cowper-Coles et al., 2021[8]).

In some countries, regulation does not specify exactly which statistics need to be reported. For instance, in Switzerland, “beyond pay, it is not specified which variables must be included”. However, the federal government provides an analysis tool called Logib (see Chapter 7 for more information) and recommends its use to employers.

Out of the 21 OECD countries that require pay reporting in the private sector, Korea and the United Kingdom are the only ones that ask for only an aggregate, company-level estimate of the wage gap. In all others, more granular information is required to be reported. This is to help identify the different factors that contribute to gender pay gaps within firms and sectors. By examining different characteristics, such as job position, age, education, parenthood status, and even race/ethnicity, countries can understand which women face higher disadvantage and how to best address the barriers they face (OECD, 2021[1]; Cowper-Coles et al., 2021[8]).

Most countries that require gendered pay information to be further disaggregated are interested in gender gaps by job classification (Table 3.1). This is the case in Austria, Australia, Belgium, Canada, Chile, Denmark, Finland, France, Iceland, Italy, Latvia, Lithuania, Norway, Portugal, Spain, and Sweden.

Job classifications are used to group jobs together based on the tasks and duties they involve. This can include ostensibly “objective” criteria that relate to the knowledge and education required, the effort exerted and working conditions, as well as the relevant responsibilities and the difficulty of a role – among other observable characteristics (OECD, 2021[1]). Various job classification schemes are used across OECD countries following national (see those in Table 3.2) or international guidelines, such as the International Standard Classification of Occupations (ISCO) (ILO, 2010[9]).

Some job classification systems in OECD countries are legally required to be gender-neutral or gender-sensitive (see Section 3.2.2). This means that they must aim to classify work based on objective criteria (see above), regardless of the gender of the person doing the job and of the preponderance of one gender in a given job class. These systems should also take into account the historical context and potential biases that may have affected how different jobs have been valued in the past (OECD, 2021[1]).

It should be noted that when gender pay gaps are disaggregated by job position, the pay gap(s) within a firm may appear smaller. This is because men tend to dominate higher-paying positions while women are more likely to be in lower-paying jobs. It is therefore useful to present both the aggregate and subgroup-decomposed gender wage gap estimates, as well as the gender composition of the workforce by job position (see Section 3.5). By doing so, it allows for a more comprehensive understanding of the gender pay gap and its underlying causes. Disaggregating data by job position helps shed light on the disparities within specific occupations and sectors, bringing attention to the issue of occupational segregation.

The job categories used for reporting on the gender pay gap vary by country. Most countries recommend using a pre-defined job classification system. This can be a standard national or international job classification system, a company job classification system, or a classification system used in collective agreements (Table 3.2). The level of detail in these systems affects how comparable different roles are within each classification.

National job classification systems suggested to employers include the Australian and New Zealand Standard Classification of Occupations (ANZSCO); the Employment Equity Occupational Groups (EEOGs), based on Canada’s National Occupational Classification; the DISCO-08 code, i.e. the Danish version of ISCO-08 with an additional tier that further specifies job functions; and the Portuguese Classification of Occupations.

Pay reporting regulations often allow employers to choose between two or more job classification systems. In Austria, for example, employers can use either the company’s job classification system or sectoral collective agreements. In the New Zealand public sector, employers can use the ANZSCO or opt for roles relevant within the organisation. In France, categories of equivalent positions are used. These either correspond to the predefined socio-professional categories (blue-collar workers; white-collar workers; technicians and supervisors; engineers and managers) or to another alternative categorisation, although most companies use the predefined system (Briard, Meluzzi and Ruault, 2021[10]).

In Portugal, in contrast, employers must disaggregate pay information by both the standard classification system and by job categories defined in the company or in collective agreements, while in Belgium, the employer must give priority to the sectoral job classification. If a sectoral job classification applies, the job classification at company level should not contain any provisions that conflict with the sectoral collective agreement.

Job classification schemes seek to assess objectively the knowledge, effort, responsibilities, working conditions, education, and difficulty of specific jobs. Yet correctly defining which jobs and responsibilities are “of equal value” is not straightforward. The “value” of different jobs today reflects broader historical, societal, and cultural factors. Job classification schemes can therefore also be influenced by societal biases and gender stereotypes – which, in turn, can embed systematically lower pay in some job categories (Acker, 1989[11]).

The principal risk is that jobs that are traditionally performed by women may be undervalued and underpaid compared to jobs that are traditionally performed by men, even if they require similar levels of skill, effort, and responsibility.

Analyses on the gender pay gap across different countries highlight various factors that contribute to the pay gap between men and women, with occupational choice being one of the most significant factors (Farrell, 2005[12]; Bettio, Verashchagina and Camilleri-Cassar, 2009[13]; Hegewisch et al., 2010[14]; Georges-Kot, 2020[15]). Men tend to opt for higher-paying sectors, while women tend to work in less lucrative sectors (such as health and social work or teaching) and, more often than men, in part-time roles. This is a result of both employee and employer behaviour: a review of experimental audit studies finds that potential employers discriminate against women in (relatively better-paying) male-dominated occupations, and discriminate in favour of women in (relatively lower-paying) female-dominated occupations (Galos and Coppock, 2023[16]), thereby reinforcing gender segregation.

A study of gender-segregated occupations in the United States illustrates different wage outcomes for male- versus female-dominated jobs. The authors find that female-dominated occupations are consistently paid less across all skill levels (low, medium, and high)4 (Hegewisch et al., 2010[14]).

Full-time workers in low-skilled, male-dominated professions earned a median of USD 553/week, whereas those in low-skilled, female-dominated professions earned a median of USD 408/week. The pay for “mixed” professions – those with greater gender balance – falls in between. The highest paid low-skilled workers in male-dominated professions earned up to a median of USD 685/week (as “driver/sales workers and truck drivers”), whereas those in female-dominated professions earned only up to a median of USD 438/week (for “nursing, psychiatric and home health aides”) (Hegewisch et al., 2010[14]).

The differences are more marked among high-skilled full-time workers. Those in male-dominated professions earned a median of USD 1 424/week whereas those in female-dominated professions earned a median of USD 953/week (Hegewisch et al., 2010[14]). These occupations include, for instance, computer software engineers for male-dominated professions and registered nurses or elementary and middle school teachers for female. These jobs require at least three years of post-secondary education (i.e. a bachelor degree or equivalent) in most countries. While these female-dominated occupations are more likely to be found in the public sector, such pay differences are striking considering that the women’s roles often carry a high degree of responsibility. Decisions of registered nurses could make the difference between life and death, while teachers, of course, are caring for and educating children.

What’s more, there is some evidence that women entering a field can cause wages to drop. A recent study finds that a ten percentage point increase in female workers into an occupational class leads to an eight percent decrease in average male wage and a seven percent decrease in average female wage in the concurrent census year, and an nine percent decrease in male wages and a 14 percent decrease in female wages over ten years. Using a shift-share instrument that takes into account the rise in women’s educational attainment and workforce participation from 1960 to 2010, the study establishes a causal relationship between declining wages and gender (Harris, 2022[17]). Other studies have shown mixed conclusions when looking at job prestige and wages (OECD, 2023[18]).

Gender-neutral job classification schemes are mandated in at least ten OECD countries (OECD, 2021[1]). “Gender neutrality” matters because traditional job classifications can reinforce gender bias in job valuations, making what is traditionally “men’s work” more highly valued than “women’s work” (OECD, 2021[1]). When designed with equal pay considerations in mind, job classification systems can help to achieve equal pay for work of equal value goals (Wagner, 2020[19]). Beyond simply removing gendered connotations from job titles,5 gender neutrality means connecting pay with the objective skills, experiences and responsibilities required in a job category independently of the traditional gender composition of a job category.

In some countries – such as Belgium, Germany, Portugal, the Slovak Republic, and the United States – job classification systems are not mandatory themselves, but when they are used they should be gender-neutral and/or gender-sensitive (OECD, 2021[1]).

Many countries with equal pay auditing mechanisms (see Chapter 4) use job classifications to detect pay disparities, as in Canada, Finland, France, Iceland, Norway, Spain, Sweden, and Portugal (OECD, 2021[1]). For instance, in Iceland, the Equal Pay Standard necessitates that companies create their equal pay system using a job classification system that is free of gender bias. The government also offers a free job classification tool for employers (Chapter 7). Following the transition from a voluntary to a mandatory Equal Pay Standard (Chapter 6) in Iceland, gender-neutral job classifications have become more common (OECD, 2021[1]).

Similarly, in Norway and Sweden, regulations specify that analysis should concentrate on equal work or on work of similar or equal value, and in Finland and Chile that employee groups should be defined by some objective worker characteristic (e.g. function performed or on the basis of competence) (Table 3.2). In Canada under the Pay Equity Act, regulation specifies that “job classes are determined by the employer, or in the case a pay equity committee has been formed, by the committee, and are made up of positions within the workplace that: 1) have similar duties and responsibilities; 2) require similar qualifications; and 3) are part of the same compensation plan and are within the same range of salary rates” (Table 3.2).

Belgium provides tools like a checklist for ensuring “gender neutrality” in the evaluation and classification of functions for employers6 (Chapter 7).

In Austria, gender-neutral job evaluation has been used to re-evaluate the value of the work of lower-paid cleaners, which previously had separate pay grades for jobs carried out by men and women (Pillinger, 2021[20]). This type of re-evaluation of job classifications helps to correct bias in grading systems and can promote equal pay for work of equal value.

The EU Pay Transparency Directive should give gender-neutral job classifications a push forward in Europe, calling for gender-neutral job classifications that “include skills, effort, responsibility and working conditions, and, if appropriate, any other factors which are relevant to the specific job or position. They shall be applied in an objective gender-neutral manner, excluding any direct or indirect discrimination based on sex. In particular, relevant soft skills shall not be undervalued.” (Article 4[4]7).

Identifying which jobs hold “equal value” is difficult when the skills and education required are completely different. Consider the comparison of low-skilled U.S. workers above. It is not immediately obvious why truck drivers should earn nearly USD 250 more per week than nursing, psychiatric and home health aides – but it is also not straightforward to compare them and address this difference. Both types of jobs suffer from worker shortages, and both face occupational risks. One may argue that truck drivers have physically demanding jobs that require them to lift heavy objects – but this is not dissimilar to nursing aides, who often need to lift people with limited physical mobility. And even if there were a difference in physical demands, should physical demands be valued more highly than the significant interpersonal and organisational skills, as well as emotional demands, required in caregiving jobs?

Assessing what constitutes “equal value,” and consequently achieving equal pay for work of equal value, is therefore a complex issue that requires a range of approaches. Pay transparency legislation, including disaggregated reporting using job classification schemes, is an important tool in promoting equal pay for work of equal value. However, it is important to address biases and stereotypes in job classifications and job evaluation processes with a gender-sensitive lens.

The International Labour Organization provides guidance for employers, HR personnel, and social partners on how to implement gender-neutral job classification systems, emphasising the need to analyse the gendered nature of work (ILO, 2008[21]). To mitigate the risk of bias, researchers in the European and Australian contexts suggest ensuring that job evaluators receive adequate training and come from mixed-gender backgrounds (European Parliamentary Research Service, 2015[22]; Workplace Gender Equality Agency, 2012[23]). Wage negotiation and wage setting, including collective bargaining, should routinely integrate gender-neutral job evaluations (Pillinger, 2021[20]). This is arguably more practical at the firm level than at the sectoral level.

Government bodies have an important role to play by checking and verifying job classification systems for embedded gender biases and developing as well as enforcing penalties for non-compliance (Wagner, 2020[19]). If job classification systems actually were gender-neutral and successfully ensured equal pay for work of equal value, it could potentially eliminate the need for pay equity litigation, saving workers and their representatives time and resources (OECD, 2021[1]).

Based on evidence, good practices, and lessons learned from public service unions in Europe and internationally, good practice in gender-neutral and/or gender-sensitive job classification includes (Pillinger, 2021[20]):

  • Job classification schemes should use a gender-sensitive approach, i.e. they should take into account that women and men have different skills and experiences due to social and cultural factors.

  • Job evaluations should be based on objective criteria, for instance on the skills, effort, and responsibility required to perform the job. Job evaluation should also be conducted by trained professionals who are knowledgeable about the specific job and the skills required to perform it. This can help to ensure that the value of different jobs is assessed objectively and fairly.

  • The process of job classification and evaluation should be transparent and inclusive, meaning that workers and/or their representatives should be involved in and informed about the process.

  • Job classification schemes should be regularly reviewed and updated to ensure that they remain gender neutral and/or gender sensitive. This means that the scheme should be updated to reflect changes in the workforce and the skills required to perform different jobs.

While job classifications, when used, should be designed in a gender-sensitive way, governments and social partners should also ensure that they do not make job classifications overly rigid. Firms need some freedom to set wages in line with productivity and respond to skill demands and supply (OECD, 2018[24]) (OECD, 2021[25]). This again illustrates the value of gender-disaggregated pay reporting, which illuminates gender pay gaps even in the absence of jobs defined as having “equal value”.

In some countries, regulations include a simple list of job categories to be used in pay reporting. For example, in Italy, pay information is reported separately for executives, managers, clerks, and workers (dirigenti, quadri, impiegati, and operai) (see Box 3.5). Belgian reporting rules also offers an option to report by subsidiary function classification (executive, managerial, executive staff). A similar categorisation is also used with France’s socio-professional categories.

In addition to job classification, some countries require the disaggregation of pay data by level of seniority (Australia, Belgium, Lithuania, and Portugal, as well as in Switzerland under recommendations8) and/or by the level of education or qualification achieved (Belgium, Finland, Latvia, Lithuania, Norway, Portugal and Switzerland under recommendations, see endnote 8). Age is also a common factor for disaggregation (Australia, Latvia, and Portugal) and is relevant given that gender gaps typically increase over the life course.

Other worker characteristics used to further disaggregate gendered pay data include working location/region (Australia, Canada under the Employment Equity Act, see endnote 2, and Portugal), remuneration/salary group (Austria, Israel and Lithuania), the level of work responsibility (Chile, Finland and Norway), workload, effort, and working conditions (Finland and Norway), and working patterns (Ireland).

Related to this, women tend to take more and longer breaks from their careers to raise children, which slows down their career progression and affects their pay (Georges-Kot, 2020[15]; OECD, 2022[27]; OECD, 2019[28]). As such, the pay gap is not just a gender issue but also a motherhood issue. Women who become mothers tend to work less in the labour market and often9 earn less than women without children, men without children, and men who become fathers – the so-called “motherhood penalty” and “fatherhood bonus” (Harkness and Waldfogel, 2003[29]; Budig and Hodges, 2010[30]; Glauber, 2018[31]; OECD, 2017[32]). This is likely driven in part by discriminatory behaviour by employers, as has been shown in audit studies (Correll, Benard and Paik, 2007[33]). As such, countries should consider disaggregating gendered pay information by parent status.

To fully understand the intersectional nature of gender pay gaps, it is important to be able to examine how gender interacts with factors such as (self-disclosed) race/ethnicity, language, place of birth, and disability status (Cowper-Coles et al., 2021[8]). Unfortunately, however, only a handful of OECD countries systematically collect data on ethnic and racial background.

Pay information is disaggregated by ethnicity and/or race in Canada under the Employment Equity Act and in the public sector in New Zealand (see Box 3.6). The United States collects information on the gender and racial/ethnic composition of job categories by company via reporting requirements of the Equal Employment Opportunity Commission (EEOC).10 While this presents a picture of diversity in workforce composition, the EEOC does not collect wage information and therefore cannot calculate wage gaps with these gender, racial and ethnic data. For more information on gender-disaggregated non-pay reporting, refer to Section 3.5.

At least 24 OECD countries also require employers to report non-pay information about their workforce that is broken down by gender – in other words, gender-disaggregated non-pay data. This can be part of their pay reporting regulations or another regulation altogether. These measures and their requirements are summarised in Table 3.3, below.

Some countries, including Germany, Luxembourg, the Netherlands, and the United States, have rules for reporting non-pay information that is broken down by gender, but they do not have regulations in place for reporting on pay. This means that it may be relatively simple for these countries to create mandatory pay reporting schemes by simply adding pay to existing requirements. Although these reporting requirements are an important step toward improving diversity within organisations, the lack of reporting on wages limits meaningful action in addressing gender pay gaps.

Most countries require private sector employers to report gender gaps in the number of employees. This is the most common (non-pay) data required, and it is mandated in Austria, Belgium, Canada, Chile, Colombia, France, Germany, Italy, Korea, Lithuania, Norway, Portugal, Spain, Switzerland, and the United States.

These gender gaps in headcounts are often further disaggregated by job category, as in Austria, Australia, Canada, Chile, France, Italy, Korea, Lithuania, Portugal, Norway, Spain, and the United States; by contract type, as in Belgium, Canada, Colombia, France, Germany, Italy, Portugal, Norway, Spain, and the United States; and less often, by salary class (see Figure 3.1 for an overview of country counts).

Other commonly reported non-pay gender-disaggregated data include gender differences in hiring, termination, and promotion rates (Canada, Italy, Luxembourg, and the United States, with promotion rates also required in Australia and France) and worked hours (Belgium, Canada, Italy, and Norway). These are in line with the proposed requirements in the EU Directive (see Chapter 2).

Japan applies an approach tailored to company size and, presumably, capabilities. As part of wage gap reporting rules, Japan requires employers to report several non-pay gender disaggregated statistics depending on sector and size in terms of number of employees (see Box 3.7).

The United States11 does something similar: federal agencies are required to report the number of employees by gender, race/national origin, and disability within the Senior Executive Service (SES), within each salary plan and grade level.

In OECD countries, women make up around one-third of managers on average (OECD, 2021[34]). Women also hold just slightly below 30% of seats on the boards of the largest public businesses (OECD, 2022[35]). This is related to the “leaky pipeline” to top jobs – in short, the number of women who can advance to leadership positions later in their career is much smaller than the number who enter the workforce in the first place, in large part due to career interruptions related to unpaid caregiving.

To help address vertical segregation, many countries’ regulations require non-pay reporting to concentrate on gender differentials in the top positions of companies. For instance, Slovenia’s non-pay reporting measure requires companies to report on the gender composition in management/supervisory boards, and in the Netherlands, companies must provide data regarding the male-to-female-ratio in (sub)top positions. In France, the Professional Equality Index12 includes an indicator which is calculated based on the proportion of workers from the less represented gender among the ten highest paid workers. Switzerland has a specific auditing process for companies with unequal representation of the two genders in top positions (see Box 3.8).

Furthermore, Australia, Chile, Colombia, Denmark, Korea, Lithuania, and Spain require employers to report the number of employees by gender and by seniority.

Pay transparency in job postings refers to the practice of openly disclosing the salary or salary range for a job position. This offers job applicants and employees a clearer understanding of what they can expect to earn in a given role. Salary range transparency laws can erase the culture of pay secrecy, help women (and men) better negotiate their salaries, reduce the gender (and other) pay gaps, as well as improve women’s economic security over their lifetime (Center for American Progress, 2023[37]).

Recognising the potential gender equality value of presenting pay ranges in job advertisements, the EU Pay Transparency Directive grants the right to pay transparency before starting a job. This includes the following:

  1. 1. Applicants should be provided with information about the initial pay or pay range for the position they are applying for, based on objective criteria that are not biased by gender. This information should also include any relevant provisions of the collective agreement that apply to the position. The information should be made available in a way that promotes transparency and allows for informed negotiations on pay, such as through a job vacancy notice before the interview or by other means.

  2. 2. Employers are prohibited from asking applicants about their previous or current pay history in their past employment relationships.

Employers must ensure that job vacancy notices and job titles are gender-neutral and that the recruitment process is conducted without discrimination. This is to protect the right to equal pay for equal work or work of equal value.

Some EU countries, such as Austria, already require the disclosure of salary range in job advertisements.

Eight states have enacted salary range transparency laws across the United States in recent years: California, Colorado, Connecticut, Maryland, Rhode Island, and Washington (Center for American Progress, 2023[37]). Colorado was the first state that implemented this type of pay transparency requirement. This and the requirements in California, New York, Rhode Island, and Washington are summarised below. States considering passing such transparency laws include Hawaii, Illinois, Kentucky, Massachusetts, Montana, New Jersey, Oregon, South Dakota, Vermont, Virginia, Washington D.C. (Center for American Progress, 2023[37]).

California has amended their Labour Code such that, as of January 1st 2023, employers with 15 or more employees need to write salary ranges on job advertisements. This is the case whether the advertisement is found on a company’s hiring page or a third-party website, such a job board website (Cain, 2022[38]).

California is the largest state in the United States with pay transparency in job postings: these rules will affect 19 million workers, and almost 200,000 employers (among which are large and influential companies such as Apple, Disney, Google and Meta (Cain, 2022[38]). This may have downstream consequences in changing norms in this sector globally (Leung, 2022[39]).

In January 2021, Colorado passed a then-novel law, the Equal Pay for Equal Work Act, which requires employers to include compensation information in their online job postings. At the time, Colorado was the only state in the US that had implemented this type of pay transparency requirement (Bruner, 2022[40]).

New York’s pay disclosure in job advertisements law is similar to Colorado's, and mandates companies with more than four employees to display salary ranges. It was originally scheduled to take effect on May 15, 2022, but was postponed to November 2022 due to opposition from businesses. The revised law only applies to hourly and salaried positions that are performed physically in New York City, highlighting the contentious nature of this legislation (Bruner, 2022[40]).

Similarly to California, New York’s pay transparency legislation holds considerable influence due to the dominant banking industry. Other banking industries across the world may follow in New York’s footsteps and also set up pay transparency in job postings (Leung, 2022[39]).

While the amended Pay Equity Act in Rhode Island does not mandate employers to post pay ranges on job ads, businesses are obligated to provide the range to job applicants if requested. Employers must reveal the minimum and maximum salary range before discussing compensation with the candidate during the hiring process, and again if the employee changes their position within the organisation. Additionally, employers must provide the salary range for a current employee's position upon request (Cain, 2022[38]).


[11] Acker, J. (1989), “The problem with patriarchy”, Sociology, Vol. 23/2, pp. 235-240.

[36] Aumayr-Pintar, C. (2019), “Slow start for gender pay transparency in Germany”, Eurofound, https://www.eurofound.europa.eu/nb/publications/blog/slow-start-for-gender-pay-transparency-in-germany (accessed on 26 October 2022).

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← 1. New Zealand requires gender pay gap reporting only in the public sector; there are currently no requirements in place for pay gap reporting in the private sector. While this report principally focuses on private sector pay gap reporting rules, New Zealand is occasionally presented in this report for its novel practices in pay transparency for the public sector.

← 2. Canada’s pay reporting regulation is two-fold. Pay gap reporting under the Employment Equity Act applies to federally regulated private-sector employers with 100 or more employees. These employers submit annual reports to the Minister of Labour by 1 June of each year. Conversely, under the Pay Equity Act, federally regulated employers in both the private (10 employees or more) and public sectors (no employee threshold) are required to submit an annual statement on their pay equity plans to the Pay Equity Commissioner.

← 3. The treatment groups were exposed to the following interventions: 1) the gender pay gap (GPG) presented as percentage and visually in a bar chart; 2) identical to 1st but with benchmarking (against other companies) information; 3) identical to 2, but GPG presented in terms of money and visually as coins; 4) GPG presented as percentages in the type of the UK Energy Performance Certificate. The control group only saw the percentage difference GPG.

← 4. Male-dominated occupations are defined as those in which 25% or fewer workers are female, and female-dominated occupations are defined as those in which 25% or fewer workers are male. Wages are from 2009.

← 5. Interestingly some languages, like Finnish, already have no gender connotation. The Finnish language offers an example of gender neutrality due to its structure and vocabulary. Unlike many other languages, Finnish does not have grammatical gender distinctions for nouns. This absence of gendered nouns means that there are no inherent linguistic gender biases or connotations associated with specific words. Finnish also lacks gender-specific pronouns like “he” or “she”. Instead, it uses a single gender-neutral pronoun, “hän,” which can refer to both males and females. This absence of gendered language could help remove potential assumptions related to job titles and allow for a more objective, gender-neutral evaluation of skills, experiences, and responsibilities in job categories.

← 6. Available at https://emploi.belgique.be/fr/actualites/check-list-non-sexisme-et-classification-des-fonctions.

← 7. The European Union Pay Transparency Directive is available at https://www.europarl.europa.eu/doceo/document/TA-9-2023-0091_EN.html#title2.

← 8. When the gender pay gap analysis is conducted with the Swiss Confederation’s standard analysis tool, gender gaps are disaggregated further by education, seniority, potential work experience, level of qualifications and professional position.

← 9. In the United States, for example, the motherhood penalty has been found to be larger among lower skilled/lower earning workers than for more highly skilled/earning workers (Budig and Hodges, 2010[30]; Killewald and Bearak, 2014[42]; Glauber, 2018[31]).

← 10. For more information on reporting requirements of the US government, see http://eeocdata.org/eeo1.

← 11. Equal Employment Opportunity Commission Management Directive 715 (MD-715) is policy guidance for federal agencies to establish and maintain effective EEO programs, as required by Title VII of the Civil Rights Act of 1964 and the Rehabilitation Act of 1973. 

← 12. Index de l’égalité professionnelle, more information available at https://travail-emploi.gouv.fr/droit-du-travail/egalite-professionnelle-discrimination-et-harcelement/indexegapro.

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