Data: The World’s Most Valuable Resource to Fight Child Labour

20 September 2018

Federico Blanco Allais  | Senior Statistician, ILO Fundamental Principles and Rights at Work Branch

In the past two decades the world has witnessed a profound increase in the availability of data on child labour. The Global Estimates of Child Labour 2012-2016 produced by the International Labour Organization (ILO) were based on datasets from 105 countries, covering 1.1 billion children aged 5- to 17-years-old, while the first global estimates, produced in 2000, were based on datasets from only 29 countries.

At the same time, there has been a substantial reduction in the number of 5- to 17-year-olds in child labour in the past two decades, down from 246 million in 2000 to 152 million in 2016. Data have allowed the global community to gain a much deeper understanding of the reality of millions of working children, including their specific work settings, the characteristics of the work they perform, the industries and occupations in which they are engaged, and where they reside. Equally important, better data provide a richer understanding of why children work and the serious negative repercussions of child labour for children’s health and safety as well as for their ability to attend and benefit from school. This improved understanding has informed policies designed to eradicate child labour and has allowed countries to move faster and more effectively when implementing these policies.


School children playing on the road. Unsplash/Himesh Kumar Behera

From a historical perspective, the organizations of the United Nations played a decisive role in boosting the collection of nationally representative data on child labour. Efforts by the ILO’s Statistical Information and Monitoring Programme on Child Labour with specialized child labour surveys and UNICEF’s child labour module included in the multiple indicator cluster survey are invaluable sources of child labour information. USAID’s child labour module included in the demographic and health surveys is another important data source.

National governments have progressively integrated child labour into their statistical programmes, and today they are the main driving force in child labour data collection. For instance, many states now include child labour questions in their existing labour force surveys and other multipurpose household surveys. This is the way forward as it guarantees sustainability, ownership and larger sample sizes than what can be achieved by stand-alone child labour surveys funded by external sources.

Of the 105 country surveys included in the Global Estimates of Child Labour 2012-2016, more than 50 per cent were fully funded by the countries themselves. Today countries have never been more aware of the fact that if all forms of child labour are to be eliminated by 2025—as set out in Target 8.7 of the Sustainable Development Goals—policies must be informed by rigorous child labour measurement and periodic trends assessments and that national budgets must allocate for these activities.

Data have allowed the global community to gain a much deeper understanding of the reality of millions of working children, including their specific work settings, the characteristics of the work they perform, the industries and occupations in which they are engaged, and where they reside.

Nevertheless, challenges persist in collecting child labour data, especially in countries affected by armed conflict or natural disasters. Conflict further exacerbates the vulnerability to some of the most extreme forms of labour exploitation, and it is in precisely these situations where the data stops flowing. Systematic efforts are critically needed to collect information and provide assistance to children and families effected by armed conflict and natural disasters. In addition, household surveys of countries hosting displaced populations need to drastically improve the coverage and visibility of refugee children and their families. Too often, existing methodologies exclude refugee camps, rendering some of the most vulnerable populations of working children invisible. A notable exception is the 2016 National child labour survey in Jordan, which defined refugee camps as a statistical domain in its sampling approach.

Collecting statistical information on the worst forms of child labour other than hazardous work is another challenge. Slavery or practices similarly to slavery, debt bondage, children in armed conflict, commercial sexual exploitation of children including pornography, illicit activities like the production and trafficking of drugs, begging, and other activities among the worst forms of child labour may not be captured using conventional household-survey approaches. Innovative survey methodologies with specific sampling approaches are required to measure what in statistical terms are known as “elusive populations”. The ILO has made some important methodological advances in these areas, such as a sampling of elusive populations manual with a focus on child labour.

Finally, while national data on child labour has expanded dramatically, more work is needed to promote the use of this data by researchers and policymakers. With this goal in mind, the ILO has uploaded a large number of national datasets to its global website, where they can be readily accessed by interested parties.

One child in child labour is a failure of humanity. The implications of child labour are long-lasting and prevent our societies and children from reaching their full potential. Today, there are still 152 million children in child labour, 73 million in hazardous work, 4.2 million in forced labour and an undetermined number in other worst forms of child labour. In all of our efforts we must reaffirm that data is one of our most valuable resources to put an end—for good—to child labour.

Federico Blanco Allais is a senior statistician at the ILO’s Fundamental Principles and Rights at Work Branch.

This article has been prepared by Federico Blanco Allais as a contribution to Delta 8.7. As provided for in the Terms and Conditions of Use of Delta 8.7, the opinions expressed in this article are those of the author and do not necessarily reflect those of UNU or its partners.

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