Gender pay gap
The gender pay gap or gender wage gap is the average difference between the remuneration for men and women who are employed. Women are generally found to be paid less than men. There are two distinct measurements of the pay gap: non-adjusted versus adjusted pay gap. The latter typically takes into account differences in hours worked, occupations chosen, education and job experience. In other words, the adjusted values represent how much women and men make for the same work, while the non-adjusted values represent how much the average man and woman make in total. In the United States, for example, the non-adjusted average woman's annual salary is 79–83% of the average man's salary, compared to 95–99% for the adjusted average salary.
The reasons for the gap link to legal, social and economic factors. These include having children, parental leave, gender discrimination and gender norms. Additionally, the consequences of the gender pay gap surpass individual grievances, leading to reduced economic output, lower pensions for women, and fewer learning opportunities.
More recently, other factors have been incorporated in to the measurement of the adjusted pay gap. The World Bank has said that the gap increases even further when taking in to account these factors, and that previous studies may have under-estimated the size of the gender pay gap.
The global gender pay gap now stands at 68.5%. Recently, the pay gap has decreased most rapidly in Global South countries. In the European Union, there has been little change in the gender pay gap in the 21st century. In the United States, the pay gap has likewise held steady, although in 2023 the pay gap actually increased across all age groups, as men's wages have increased at a higher rate than women's.
The gender pay gap can be a problem from a public policy perspective in developing countries because it reduces economic output and means that women are more likely to be dependent upon welfare payments, especially in old age.
Historical perspective
In the United States, women's pay has increased relative to men since the 1960s. According to US census data, women's median earnings in 1963 were 56% of men's. In 2016, women's median earnings had increased to 79% of men's. Analysis from the Institute for Women's Policy Research published in 2017 predicted that average pay would reach parity in 2059.According to a 2021 study on historical gender wage ratios, women in Southern Europe earned approximately half that of unskilled men between 1300 and 1800. In Northern and Western Europe, the ratio was far higher but it declined over the period 1500–1800.
A 2005 meta-analysis by Doris Weichselbaumer and Rudolf Winter-Ebmer of more than 260 published pay gap studies for over 60 countries found that, from the 1960s to the 1990s, raw wage differentials worldwide have fallen substantially from around 65% to 30%. The bulk of this decline, was due to better labor market endowments of women.
Another meta-analysis of 41 empirical studies on the wage gap performed in 1998 found a similar time trend in estimated pay gaps, a decrease of roughly 1% per year.
A 2011 study by the British CMI concluded that if pay growth continues for female executives at current rates, the gap between the earnings of female and male executives would not be closed until 2109.
Calculation
The non-adjusted gender pay gap or gender wage gap is typically the median or mean average difference between the remuneration for all working men and women in the sample chosen. It is usually represented as either a percentage or a ratio of the "difference between average gross hourly earnings of male and female employees as % of male gross earnings".The pay gap may be measured using different metrics: some studies compare hourly wages of all workers, while others restrict to full-time, year-round workers. A 2025 analysis by the Pew Research Center found that in the United States, women earned about 85% of what men earned across hourly earnings.
Some countries use only the full-time working population for the calculation of national gender gaps. Others are based on a sample from the entire working population of a country, in which case the full-time equivalent is used to obtain the remuneration for an equal amount of paid hours worked.
Non-governmental organizations apply the calculation to various samples. Some share how the calculation was performed and on which data set. The gender pay gap can, for example, be measured by ethnicity, by city, by job, or within a single organization.
Causes
Some variables that help explain the non-adjusted gender pay gap include economic activity, working time, and job tenure. Gender-specific factors, including gender differences in qualifications and discrimination, overall wage structure, and the differences in remuneration across industry sectors all influence the gender pay gap.Industry sector
or horizontal segregation refers to disparity in pay associated with occupational earnings.A 2022 research study, conducted by Folbre et al., illustrates how the concentration of women in care occupations contributes significantly to the gender pay gap. Their findings show that, while both women and men are affected by the care services wage penalties, women in these occupations face greater tribulations considering they are more likely to be employed in care services. In Jacobs, Boyd et al. refer to the horizontal division of labor as "high-tech" versus "high-touch" with high tech being more financially rewarding. Men are more likely to be in relatively high-paying, dangerous industries such as mining, construction, or manufacturing and to be represented by a union. Women, in contrast, are more likely to be in clerical jobs and to work in the service industry.
A study of the US labor force in the 1990s suggested that gender differences in occupation, industry and union status explain an estimated 53% of the wage gap. A 2017 study in the American Economic Journal: Macroeconomics found that the growing importance of the services sector has played a role in reducing the gender gap in pay and hours. In 1998, adjusting for both differences in human capital and in industry, occupation, and unionism increases the size of American women's average earnings from 80% of American men's to 91%.
A 2017 study by the US National Science Foundation's annual census revealed pay gaps in different areas of science: there is a much larger proportion of men in higher-paying fields such as mathematics and computer science, the two highest-paying scientific fields. Men accounted for about 75% of doctoral degrees in those fields, and expected to earn $113,000 compared with $99,000 for women. In the social sciences the difference between men and women with PhD's was significantly smaller, with men earning ~$66,000, compared with $62,000 for women. However, in some fields women earn more: women in chemistry earn ~$85,000, about $5,000 more than their male colleagues.
A Morningstar analysis of senior executive pay data revealed that senior executive women earned 84.6 cents for every dollar earned by male executives in 2019. Women also remained outnumbered in the C-Suite 7 to 1.
A 2020 analysis by the Institute for Women’s Policy Research found that gender wage disparities are present across most major occupational groups in the United States. The report noted that women working full-time in similar occupations still earned less than men, indicating that occupational wage gaps cannot be fully explained by differences in hours worked, part-time status, or employment type. Wage penalties were documented in a variety of professional and service sectors, suggesting that industry-level pay disparities persist even among full-time workers with comparable roles.
Discrimination
A 2015 meta-analysis of studies of experimental simulations of employment found that "men were preferred for male-dominated jobs, whereas no strong preference for either gender was found for female-dominated or integrated jobs". However, a meta-analysis of real-life correspondence experiments found that "men applying for strongly female-stereotyped jobs need to make between twice to three times as many applications as do women to receive a positive response for these jobs" and "women applying to male-dominated jobs face lower levels of discrimination in comparison to men applying to female-dominated jobs."A 2018 systematic review of almost all correspondence experiments since 2005 found that most studies found that the evidence for gender discrimination "is very mixed", and that the amount of gender discrimination varies by occupation, though two studies found "a significant penalty for
being pregnant or being a mother".
A 2018 audit study found that high-achieving men are called back more frequently by employers than equally high-achieving women.
In a 2016 interview, Harvard Economist Claudia Goldin argued that overt discrimination by employers was no longer a significant cause of the gender pay gap, and that the cause is instead more subtle cultural expectations which are a legacy of historical discrimination. According to Goldin, these expectations cause women, on average, to prioritize temporal flexibility, take different risks, and avoid situations of expected discrimination. She advocated educational reforms to address the remaining gender pay gap rather than mandates on business, arguing that the latter is simply too difficult to implement given the demands of the current business environment.
A series of four studies from 2019 found that "even if these careers do not pay less, people assume that men will be less interested in any career that is majority female" and that this has "the potential to create a self-fulfilling prophecy in that people are also less interested in promoting pay raises in female-dominated caregiving careers... yet if more men were to enter these occupations, the salaries in these fields might also rise".
Some critics of the notion that discrimination causes the gender wage gap argue that the gender wage gap disappears once analysts control for the characteristics of a job. However, this is considered a textbook error in econometrics because occupational sorting may itself be an outcome of gender discrimination, which would make it a bad control. By controlling for job characteristics, the analyst introduces collider bias into the analysis, making it impossible to draw valid conclusions about the role of gender discrimination on earnings.