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Is there data to measure the future of our girls?

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“And though she be but little, she is fierce.”
William Shakespeare

There are about 1.1 billion girls and some of them, like Greta Thunberg and Malala Yousafzai, are leading the charge on important issues like climate change and education. Seeing these girls leading and mobilizing others to create a better world is inspiring. It is a reminder of the potential within girls that can be unleashed or, as is too often the case for girls around the world, can go unrealized, especially when compared to males. There are many efforts to close those gaps, but how do we know if we are actually making progress in creating that better world for girls.  Are more girls going to school? Are they learning when they’re there? In many places parents send girls to work, marry, or take care of the home instead. But to track progress, it’s important to know which barriers are faced in a given location or context, and to understand whether the situation there is getting better, staying the same, or getting worse. To answer these questions and remove these barriers, we need data.  Data informs our interventions and is foundational to closing gender gaps.

Almost 25 years ago, the Beijing Declaration and Platform for Action was launched, recognizing the rights of women as human rights. The theme for this year’s International Day of the Girl, “GirlForce: Unscripted and Unstoppable,” brings a timely reality check of how far we have come.

Data available today tells us that girls in low- and middle-income countries largely face 3Es: they can be enrolled in school, employed for pay or in often unpaid household production, or engaged to be married. Studies show that child labor can hinder educational attainment of both boys and girls; and child marriage—largely a female phenomenon—is associated with lower educational attainment. But has girls’ enrollment in school successfully increased? Has girls’ likelihood of early marriage and child labor been reduced? 

We can track these trends drawing on efforts to curate and compile cross-country statistics. Here we dip into the World Bank Gender Data Portal—a comprehensive source for comparable cross-country and cross-time sex-disaggregated and gender statistics—on the issues of child marriage, schooling, and labor of girls.

We can measure the progress in girls’ enrollment in school

The enrollment data in the World Bank Gender Data Portal exists for almost all countries in the 1990s and 2010s. The following figure shows that enrollment of girls in secondary schools has risen consistently for each region since the Beijing Declaration of 1995. South Asia witnessed the sharpest rise with more than a 100 percent increase from 33 percent to 70 percent.

These huge improvements are to be celebrated. Still, challenges remain. Beyond enrollment, learning outcomes matter. Attending class is not necessarily indicative of learning   (see World Development Report 2018). The Human Capital Index (HCI) launched last year reflects the same point, but also exposes a challenge related to data. This blog shows that the Index cannot be disaggregated by sex for up to 1 in 5 countries due to missing sex-disaggregated data on expected years of schooling and test scores.

But, we cannot measure the status and progress of reducing child labor and child marriage in many countries

However, for much of the world, data are not available for child labor and child marriage in the Gender Data Portal.

For child labor, the Portal draws on the compiled data of the Understanding Children’s Work (UCW) program by ILO, UNICEF, and World Bank. It is recognized as the best available source for cross-country comparable data on child labor. This source defines child labor as children (boys and girls separately) ages 7-14 employed in economic activity for at least one hour in the reference week. There are many different definitions of the work of children, ranging from the extreme of the worst forms of child labor to the various measures of the employment status of children which are typically a function of the child’s age, number of hours worked, and types of tasks done (see this ILO report and the explanation by Our World in Data).

A status measure on child labor from the UCW—which we define as availability of at least one data point since 2010—is available only for half of the low- and middle-income countries. A progress measure—which we define as availability of at least one data point in the 1990s and at least one data point in the 2010s—is available only for 4 low- or middle-income countries.

More data is available on child marriage for both status and progress measures, but there are still significant data gaps. While a status measure on child marriage is available for 105 economies, a progress measure is available only for 48 of these economies.

We need to understand the underlying reasons for these data gaps

The reason for these data gaps is not only that surveys are non-existent for a given period for specific countries; it is also that data at the global level are not harmonized. Take one example from Zambia: the child labor indicator is missing from the globally harmonized database we use for the post 2010 period, despite a Labor Force Survey carried out in 2012 that collected labor force participation of individuals ages 5 and above. While some indicator of child labor exists, it either did not fit in the internationally consolidated definition under the UCW program or the UCW team could not get access to the survey. Thus, the data challenge is both access (more data collection with the appropriate questions) and harmonization (standardizing variables across collected surveys and making them publicly available).

The paucity of data on child marriage reflects similar challenges. Current marital status is frequently asked in household surveys around the world for all household members above a certain age. But this is not enough to measure the incidence of child marriage which requires asking the age of the first marriage.

Today’s landscape of data availability leaves us with many questions, which limits us from adequately analyzing the progress on child labor and child marriage.

Closing gender gaps: the path forward involves a multi-fold approach that addresses data collection, harmonization, and use

This blog addresses just three important indicators that track the socioeconomic well-being of girls: enrollment, child labor, and child marriage. The broader range of gender data deprivation is well outlined in reports from UNICEF and Data2X.

While we cannot measure progress from 25 years ago, it is not too late to lay the groundwork to measure future progress. But we must start now so that in another 25 years, we are not repeating the same message.

Of course, the end goal is not data for the sake of data: improvements in data availability, harmonization, and measurement need to result in the use of the data for informing and implementing good interventions and policies that will advance the well-being of girls and offer them a brighter future. When girls do better, everyone wins.


Malarvizhi Veerappan

Senior Data Scientist, Development Data Group, World Bank

Divyanshi Wadhwa

Data Scientist, Development Data Group, World Bank

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