Differences in earnings between men and women capture differences across many possible dimensions, including education, experience and occupation. For example, if we consider that more educated people tend to have higher earnings, it is natural to expect that the narrowing of the pay gap across the world can be partly explained by the fact that women have been catching up with men in terms of educational attainment, in particular years of schooling.
When the gender pay gap is calculated by comparing all male and female workers, irrespective of differences in worker characteristics, the result is the raw or unadjusted pay gap. In contrast to this, when the gap is calculated after accounting for underlying differences in education, experience, and other factors that matter for the pay gap, then the result is the adjusted pay gap.
The idea of the adjusted pay gap is to make comparisons within groups of workers with roughly similar jobs, tenure and education. This allows us to tease out the extent to which different factors contribute to observed inequalities. The chart here, from Blau and Kahn shows the evolution of the adjusted and unadjusted gender pay gap in the US.
More precisely, the chart shows the evolution of female to male wage ratios in three different scenarios: i Unadjusted; ii Adjusted, controlling for gender differences in human capital, i. The chart here shows a breakdown of the adjusted gender pay gaps in the US, factor by factor, in and When comparing the contributing factors in and , we see that education and work experience have become much less important in explaining gender differences in wages over time, while occupation and industry have become more important.
This means the observable characteristics of workers and their jobs explain wage differences better today than a couple of decades ago. But is this really the case?
The unexplained residual may include aspects of unmeasured productivity i. For example, suppose that women are indeed discriminated against, and they find it hard to get hired for certain jobs simply because of their sex. This would mean that in the adjusted specification, we would see that occupation and industry are important contributing factors — but that is precisely because discrimination is embedded in occupational differences! Hence, while the unexplained residual gives us a first-order approximation of what is going on, we need much more detailed data and analysis in order to say something definitive about the role of discrimination in observed pay differences.
The set of three maps here, taken from the World Development Report , shows that today gender pay differences are much better explained by occupation than by education. This is consistent with the point already made above using data for the US: as education expanded radically over the last few decades, human capital has become much less important in explaining gender differences in wages. This blog post from Justin Sandefur at the Center for Global Development shows that education also fails to explain wage gaps if we include workers with zero income i.
All over the world women tend to do more unpaid care work at home than men — and women tend to be overrepresented in low paying jobs where they have the flexibility required to attend to these additional responsibilities. Goldin shows that when one looks at the data on occupational choice in some detail, it becomes clear that women disproportionately seek jobs, including full-time jobs, that tend to be compatible with childrearing and other family responsibilities.
In other words, women, more than men, are expected to have temporal flexibility in their jobs. Things like shifting hours of work and rearranging shifts to accommodate emergencies at home. And these are jobs with lower earnings per hour, even when the total number of hours worked is the same. The importance of job flexibility in this context is very clearly illustrated by the fact that, over the last couple of decades, women in the US increased their participation and remuneration in only some fields.
In a recent paper, Goldin and Katz show that pharmacy became a highly remunerated female-majority profession with a small gender earnings gap in the US, at the same time as pharmacies went through substantial technological changes that made flexible jobs in the field more productive e.
The chart here shows how quickly female wages increased in pharmacy, relative to other professions, over the last few decades in the US. Closely related to job flexibility and occupational choice, is the issue of work interruptions due to motherhood. Lundborg, Plug and Rasmussen provide evidence from Denmark — more specifically, Danish women who sought medical help in achieving pregnancy.
We explain the decline in annual earnings by women working less when children are young and getting paid less when children are older. We explain the decline in hourly earnings, which is often referred to as the motherhood penalty, by women moving to lower-paid jobs that are closer to home.
But this was not the case for men with children, nor the case for women without children. These patterns are shown in the chart here. The first panel shows the trend in earnings for Danish women with and without children. The second panel shows the same comparison for Danish men. Note that these two examples are from Denmark — a country that ranks high on gender equality measures and where there are legal guarantees requiring that a woman can return to the same job after taking time to give birth.
This shows that, although family-friendly policies contribute to improve female labor force participation and reduce the gender pay gap , they are only part of the solution. Even when there is generous paid leave and subsidized childcare, as long as mothers disproportionately take additional work at home after having children, inequities in pay are likely to remain.
The discussion so far has emphasised the importance of job characteristics and occupational choice in explaining the gender pay gap. This leads to obvious questions: What determines the systematic gender differences in occupational choice? What makes women seek job flexibility and take a disproportionate amount of unpaid care work? One argument usually put forward is that, to the extent that biological differences in preferences and abilities underpin gender roles, they are the main factors explaining the gender pay gap.
In their review of the evidence, Francine Blau and Lawrence Kahn show that there is limited empirical support for this argument. To be clear, yes, there is evidence supporting the fact that men and women differ in some key attributes that may affect labor market outcomes.
For example standardised tests show that there are statistical gender gaps in maths scores in some countries ; and experiments show that women avoid more salary negotiations , and they often show particular predisposition to accept and receive requests for tasks with low promotion potential. You can influence tastes, and you can certainly teach people to tolerate risk, to do maths, or to negotiate salaries.
In contrast, the evidence does suggest that social norms and culture, which in turn affect preferences, behaviour and incentives to foster specific skills, are key factors in understanding gender differences in labor force participation and wages.
Independently of the exact origin of the unequal distribution of gender roles, it is clear that our recent and even current practices show that these roles persist with the help of institutional enforcement. Goldin , for instance, examines past prohibitions against the training and employment of married women in the US.
These work prohibitions are important because they applied to teaching and clerical jobs — occupations that would become the most commonly held among married women after The map here highlights that to this day, explicit barriers across the world limit the extent to which women are allowed to do the same jobs as men. However, even after explicit barriers are lifted and legal protections put in their place, discrimination and bias can persist in less overt ways.
Many other studies have found similar evidence of bias in different labor market contexts. Biases also operate in other spheres of life with strong knock-on effects on labor market outcomes. This obviously circles back to our earlier point about social norms. In many countries wage inequality between men and women can be reduced by improving the education of women. However, in many countries gender gaps in education have been closed and we still have large gender inequalities in the workforce.
What else can be done? An obvious alternative is fighting discrimination. But the evidence presented above shows that this is not enough. Public policy and management changes on the firm level matter too: Family-friendly labor-market policies may help. Similarly, early education and childcare can increase the labor force participation of women — and reduce gender pay gaps — by alleviating the unpaid care work undertaken by mothers. Changing these incentives is of course difficult because it requires reorganizing the workplace.
But it is likely to have a large impact on gender inequality, particularly in countries where other measures are already in place. Implementing these strategies can have a positive self-reinforcing effect. Nevertheless, powerful as these strategies may be, they are only part of the solution. Social norms and culture remain at the heart of family choices and the gender distribution of labor. Achieving equality in opportunities requires ensuring that we change the norms and stereotypes that limit the set of choices available both to men and women.
It is difficult, but the evidence shows that social norms, too, can be changed. The gender wage gap is often measured as the difference between average earnings of men and average earnings of women expressed as a percentage of average earnings of men. By this measure the gender wage gap can be negative.
This is the definition used by the ILO. We explore the ILO data above. Comparisons of averages can often be misleading because averages are very sensitive to extreme data points.
Hence, it is also common to measure gender gaps by comparing earnings for the individuals at the median — or middle — of the earnings distribution. This is the definition used by the OECD. We explore the OECD data above. In addition to percent differences, it is also common to express the gender pay gap as a simple ratio between wages.
This is the measure adopted by the United States Census Bureau. Summary All over the world men tend to earn more than women. Women are often underrepresented in senior positions within firms. Women are often overrepresented in low-paying jobs.
In many countries men are more likely to own land and control productive assets than women. Women often have limited influence over important household decisions, including how their own personal earned income is spent. In most countries the gender pay gap has decreased in the last couple of decades. Gender-equal inheritance systems, which were rare until recently, are now common across the world.
Composite indices that cover multiple dimensions show that on the whole gender inequalities have been shrinking substantially over the last century. All our charts on Economic inequality by gender Are mothers guaranteed an equivalent position after maternity leave?
Average hourly earnings of male and female employees Borrowing to start or expand business, men vs women Countries with gender-equal inheritance Decomposition of the gender wage gap Decomposition of the gender wage gap Do married men and married women have equal ownership rights to property?
Rivian is now biggest US company by market value with no revenue. Why are giant conglomerates falling out of fashion? Americans keep quitting their jobs in record numbers. US consumer sentiment drops as inflation worries mount. Most Read. Sign up to join a global movement of people fighting inequality to end poverty and injustice. The story of our future starts with you. Want us to keep you updated by text message?
Provide us with your mobile phone number. The growing gap between rich and poor is undermining the fight against poverty, damaging our economies and fueling public anger across the globe. Unfortunately, repeated warnings about the explosion of inequality have not worked to reverse its course. Some governments, including the US, are actually exacerbating inequality by cutting taxes for the richest and for corporations while cutting public services — such as healthcare and education — that actually fight inequality.
Care work is crucial to our societies and to the economy. It includes looking after children, elderly people, and those with physical and mental illnesses or disabilities, as well as domestic work such as cooking, cleaning, washing, and other household chores. Across the world, this unpaid and underpaid care work is disproportionately done by women and girls, especially those living in poverty and from groups who, as well as gender discrimination, experience discrimination based on race, ethnicity, nationality, and sexuality.
Women around the world undertake more than three-quarters of all unpaid care work, adding up to The United States is no exception. Women in the US, like their counterparts around the world, spend considerably more time than men over their lifetime doing unpaid household and care work. On an average day, women in the United States spend 37 percent more time on such unpaid care than men.
0コメント