Published on Data Blog

Women’s challenges in the age of big data: Our role in making them visible

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Photo of two school girls in uniform, studying. Photo of two school girls in uniform, studying.

March, and more precisely March 8th, is a time to raise awareness about the remaining path toward equal opportunities for women and men. This is especially challenging in the current days of infoxication where algorithms on the Internet nudge us to jump the discussion from one topic to another day after day. March 8th has passed, yet many gender challenges remain.

It is thus ever more important to keep alive the discussion on gender inequities. Many dimensions of the current situation are not only unfair but also unjustifiable. Here is one way to keep the discussion rolling: by bringing renewed light to data published and curated by our teams at the World Bank.

The topics have been with us for a while, evolving. Take for example the gender pay gap: for each dollar males make per hour worked, females with comparable human capital make around just three quarters. This statistic has been part of most gender discussions for decades.

Globally, we saw progress during the 1980s and 1990s, but since the turn of the century, its speed of reduction has stalled. Yet by focusing on this statistic, we have paid insufficient attention to other aspects of the problem of gender equity.

What information, beyond the global average pay gap, would be a valuable addition for a broader discussion on gender equity? Gender plays a role in every facet of life- from social interactions to work opportunities to access to quality public services. Inevitably, this post will fall short in giving attention to all the pending issues, but we highlight two aspects that could be prioritized in the global dialogue.

Here, it is important to recognize that an average does not represent all the richness and diversity of the world. As Deaton concisely put it: “Averages are no consolation to those who have been left behind.”

The pay gap varies substantially across countries and regions. But more importantly, it shows substantial heterogeneity within countries. In many parts of the world, the pay gap varies along earnings distribution, life cycle, educational achievements, occupational choices, economic sectors, and other relevant variables.

Another area of gender equity that needs further discussion is education. Are boys and girls entering school at the appropriate ages at the same rates? Do they graduate equally successfully from elementary, middle, and high school?  Do they graduate equally successfully from colleges and pursue postgraduate studies?

The answers to these questions are a mix of “yes” and “no”. There are almost no gender differences in school attendance in primary and secondary schooling, but the differences arise at the tertiary level (universities and vocational training).

Our data tells the story.

To the probable surprise of many readers, these differences favor females. Then, another question arises: if women are acquiring more education than males, why is it that this is still not well reflected in labor markets? 

The answer has to do with the fields of study that males and females pursue. Gender segregation is still high, with males being a great majority in STEM fields, while females dominate the humanities and services. A better-informed public discussion around this could be valuable in searching for better solutions. 

There is still a long way to go to achieve gender equity. Current public discussions are engineered by the algorithms of the Internet. They pick information from different networks and amplify them. Much has been discussed about their possible lack of neutrality, but the point here is different.

If there is not enough critical mass of information in a topic, the algorithms won’t pick it up and won’t replicate it enough. Therefore, it is our role to generate such critical mass, visualizing and discussing data currently available.

The provision of data is but one way in which the World Bank contributes to this objective. The data example we have shown in this blog post comes from the World Bank Open Data portal. There we visualize data compiled from different official sources.

But the interested reader can dig further and get direct access to the microdata! This is available on our Poverty and Inequality Platform. This video blog shows how to get access and navigate the data provided by Statistics On Line (SOL). There, using basic Stata commands, the reader can explore the microdata performing tabulations of basic statistics.

The portal has data to keep the discussion going on most of the questions raised in this post, beyond the example we are showing on education. Let’s keep the discussion going. You, dear reader, can be an agent of change.


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