Where is gender inequality happening

The answers vary, from poverty to cultural norms to sexual harassment to a lack of basic resources such as bathrooms and feminine hygiene products. It's glaring inequalities like these that have fueled movements such as Michelle Obama's Let Girls Learn, an initiative that seeks to put an end to the gender gap in quality education. Women in the World: Where the United States falters in the quest for equality.

Over the summer, Obama traveled to Morocco and Liberia with that goal in mind, wanting to see the barriers young women are facing and to encourage them as they overcome the odds. But those two countries are far from the only nations struggling with gender inequality. The World Economic Forum has devised a system to keep track of the issue to show how fundamental gender equality is for growth and development.

Called the Global Gender Gap report, this system examines countries and ranks them according to the size of the gap between men and women in education, health, political power and economic opportunity.

Michelle Obama: This issue is personal for me. When it comes to countries where girls have a difficult time finding equal opportunities, the WEF says these are the five with the most gender inequality:.

On education alone, Iran isn't the worst. Women in Iran face disparities in political power and economic opportunity.

Yet overall, writes Minky Worden of Human Rights Watch , women across Iran "face significant discrimination in law and in practice, as well as restrictions on exercising their rights. This Central African country is the lowest-ranked nation for gender equality in sub-Saharan Africa. And when it comes to its gender gap in education, Chad is the lowest-ranked nation in the world. A girl walks next to a herd of cows close to the village of Guite in Chad's lake region, north of the capital NDjamena in However, the ILO data shows similar trends for the period The conclusion is that in most countries with available data, the gender pay gap has decreased in the last couple of decades.

The United States Census Bureau defines the pay gap as the ratio between median wages — that is, they measure the gap by calculating the wages of men and women at the middle of the earnings distribution, and dividing them.

By this measure, the gender wage gap is expressed as a percent median earnings of women as share of median earnings of men and it is always positive. The next chart shows available estimates of this metric for full-time workers in the US, by age group. First, we see that the series trends upwards, meaning the gap has been shrinking in the last couple of decades. Secondly, we see that there are important differences by age. The second point is crucial to understand the gender pay gap: the gap is a statistic that changes during the life of a worker.

The scatter plot here shows available ILO estimates on the gender pay gap vertical axis vs GDP per capita on a logarithmic scale along the horizontal axis.

As we can see there is a weak positive correlation between GDP per capita and the gender pay gap. However, the chart shows that the relationship is not really linear. Actually, middle-income countries tend to have the smallest pay gap. The fact that middle-income countries have low gender wage gaps is, to a large extent, the result of selection of women into employment.

Olivetti and Petrongolo show that this pattern holds in the data: unadjusted gender wage gaps across countries tend to be negatively correlated with gender employment gaps. That is, the gender pay gaps tend to be smaller where relatively fewer women participate in the labor force.

So, rather than reflect greater equality, the lower wage gaps observed in some countries could indicate that only women with certain characteristics — for instance, with no husband or children — are entering the workforce. The chart here plots the proportion of women in senior and middle management positions around the world.

It shows that women all over the world are underrepresented in high-profile jobs, which tend to be better paid. The next chart provides an alternative perspective on the same issue. Here we show the share of firms that have a woman as manager. As we can see, all over the world firms tend to be managed by men. Firms with female managers tend to be different to firms with male managers.

For example, firms with female managers tend to also be firms with more female workers. Despite having fallen in recent decades, there remains a substantial pay gap between the average wages of men and women.

But what does gender inequality look like if we focus on the very top of the income distribution? How did this change over time? Answers to these questions are found in the work of Atkinson, Casarico and Voitchovsky Using tax records, they investigated the incomes of women and men separately across nine high-income countries.

As such, they were restricted to those countries in which taxes are collected on individual basis, rather than as couples. Whilst investment income tends to make up a larger share of the total income of rich individuals in general, the authors found this to be particularly marked in the case of women in top income groups.

The open circle represents the share of women in the top income brackets back in ; the closed circle shows the latest data, which is from The other chart shows the data over time for individual countries. Overall, despite recent inroads, we continue to see remarkably few women making it to the top of the income distribution today. Above we show that women all over the world are underrepresented in high-profile jobs, which tend to be better paid.

As it turns out, in many countries women are at the same time overrepresented in low-paying jobs. The fact that women in rich countries are overrepresented in the bottom of the income distribution goes together with the fact that working women in these countries are overrepresented in low-paying occupations. The chart shows this for the US. The chart plots cross-country estimates of the share of women who are not involved in decisions about their own income.

The line shows national averages, while the dots show averages for rich and poor households i. As we can see, in many countries, particularly in Sub-Saharan Africa and Asia, a large fraction of women are not involved in household decisions about spending their personal earned income. And this pattern is stronger among low-income households within low-income countries.

Above we focus on whether women get to choose how their own personal income is spent. In the next chart we plot the share of currently married women who report having a say in major household purchase decisions, against national GDP per capita.

We see that in many countries, notably in Sub-Saharan Africa and Asia, an important number of women have limited influence over major spending decisions. Economic inequalities between men and women manifest themselves, not only in terms of wages earned, but also in terms of assets owned.

For example, as the chart shows, in nearly all low and middle-income countries with data, men are more likely to own land than women. Closely related to the issue of land ownership is the fact that in several countries women do not have the same rights to property as men. These countries are highlighted in the map. This map from the World Development Report provides a more fine-grained overview of different property regimes operating in different countries.

Inheritance is one of the main mechanisms for the accumulation of assets. In the map we provide an overview of the countries that do, and do not have gender-equal inheritance systems. If you move the slider to , you will see that while gender equal inheritance systems were very rare in the early 20th century, today they are much more common. And still, despite the progress achieved, in many countries, notably in North Africa and the Middle East, women and girls still have fewer inheritance rights than men and boys.

Above we show that there are large gender gaps in land ownership across low-income countries. Here we show that there are also large gaps in terms of access to borrowed capital. The chart shows the percentage of men and women who report borrowing any money in the past 12 months to start, operate, or expand a farm or business. As we can see, almost everywhere, including in many rich countries, women are less likely to get borrowed capital for productive purposes.

This can have large knock-on effects: In agriculture and entrepreneurship, gender differences in access to productive inputs, including land and credit, can lead to gaps in earnings via lower productivity. Indeed, studies have found that, when statistical gender differences in agricultural productivity exist, they often disappear when access to and use of productive inputs are taken into account.

The previous discussion focused on particularly aspects one by one. What is the the picture on economic inequality in the aggregate? Tracking progress across multiple dimensions of gender inequalities can be difficult, since changes across dimensions often go in different directions and have different magnitudes. Because of this, researchers and policymakers often construct synthetic indicators that aggregate various dimensions. Here is a map showing scores on this index higher scores denote more economic opportunities for women.

The Human Development Report produced by the UN includes a composite index that captures gender inequalities across several dimensions, including economic status.

This index, called the Gender Inequality Index, measures inequalities in three dimensions: reproductive health based on maternal mortality ratio and adolescent birth rates ; empowerment based on proportion of parliamentary seats occupied by females and proportion of adult females aged 25 years and older with at least some secondary education ; and economic status based on labour market participation rates of female and male populations aged 15 years and older. Considering this, Sarah Carmichael, Selin Dilli and Auke Rijpma, from Utrecht University, produced a similar composite index of gender inequality, using available data for the period , in order to make aggregate comparisons over the long run.

As we can see, the second half of the 20th century saw global improvements, and the regions with the steepest increase in gender equality were Latin America and Western Europe. Interestingly, this chart also shows that in Eastern Europe there was important progress in the period , but there was a reversal after the fall of the Soviet Union.

In almost all countries, if you compare the wages of men and women you find that women tend to earn less than men. These inequalities have been narrowing across the world. In particular, over the last couple of decades most high-income countries have seen sizeable reductions in the gender pay gap. 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.

Some 1 in 20 girls between the ages of 15 and 19 — around 13 million globally — have experienced forced sex in their lifetimes. Harmful gender norms are perpetuated at the highest levels. Boys also suffer from gender norms: Social conceptions of masculinity can fuel child labour, gang violence, disengagement from school, and recruitment into armed groups. Despite major hurdles that still deny them equal rights, girls refuse to limit their ambitions.

Since the signing of the Beijing Declaration and Platform for Action in — the most comprehensive policy agenda for gender equality — the world has seen uneven progress. More and more girls are attending and completing school, and fewer are getting married or becoming mothers while still children themselves. But discrimination and limiting stereotypes remain rife.

Technological change and humanitarian emergencies are also confronting girls with new challenges, while old ones — violence, institutionalized biases, poor learning and life opportunities — persist. Girl-led movements are stopping child marriage and female genital mutilation, demanding action on climate change , and trail-blazing in the fields of science, technology, engineering and math STEM — asserting their power as global change-makers.

Reducing inequality strengthens economies and builds stable, resilient societies that give all individuals — including boys and men — the opportunity to fulfil their potential. In all areas of our work, we integrate strategies that address gender-specific discrimination and disadvantages. This means partnering with national health sectors to expand quality maternal care and support the professionalization of the mostly female front-line community health workforce.

It means promoting the role of women in the design and delivery of water, sanitation and hygiene WASH ecosystems. And it means working with the education sector to ensure girls and boys thrive in their learning and find pathways to meaningful employment. For adolescent girls especially, UNICEF invests in skills building to further their economic empowerment — as entrepreneurs, innovators and leaders. We also work on assistive technologies for girls with disabilities, and on the expansion of digital platforms, vocational training and apprenticeships.

It requires keeping girls safe from all forms of violence, in and out of school. Our targeted initiatives to prevent and respond to gender-based violence help end child marriage, eliminate female genital mutilation, provide safe spaces, support menstrual health management, deliver HIV and AIDS care, meet psychosocial needs and more.

We invest in innovative models that protect even the hardest-to-reach girls — like virtual safe spaces and apps that allow them to report violence and connect to local resources for support. To guide investment and programming decisions at the national and global levels, we collect, quantify and share data critical for understanding ongoing and emerging challenges and solutions.