Using MSE to Measure Modern Slavery in Developed Countries
In September 2017, the Walk Free Foundation (WFF) and the International Labour Organization (ILO) launched the inaugural joint Global Estimates of Modern Slavery. The report concluded that on any given day in 2016, 40.3 million people were in some form of modern-day slavery. This ground-breaking report was the culmination of several years’ work, including face-to-face surveys with more than 71,000 people in 48 countries conducted through the Gallup World Poll. While this first collaborative effort to measure modern slavery represents a milestone achievement for the field, there remain significant areas of potential growth for national governments to enhance global estimation efforts, particularly among developed countries.
The nationally representative survey research programme underpinning the Global Estimates of Modern Slavery has yielded transformative information on the prevalence of modern slavery. However, surveys are not the most suitable method of measurement in all countries. For survey data to be used in the report, two conditions had to be met: the survey had to conducted face-to-face as well as in countries where prevalence is expected to be high so that a random sample survey could be reasonably expected to find cases of modern slavery.
Surveys are not the most suitable or efficient method to measure the extent of modern slavery in highly developed countries. But in recent years, the use of Multiple Systems Estimation (MSE) has been put forward as a solution to the problem of how we can effectively measure modern slavery prevalence in developed countries.
MSE is a statistical technique that uses the comparison of concurrent and identifiable victim lists typically held by national government offices to produce national prevalence estimates for modern slavery. MSE builds upon the classic capture-recapture method which, according to A Dictionary of Epidemiology, is used for “estimating the size of a target population or a subset of this population that uses overlapping and presumably incomplete but intersecting sets of data about that population”. Though there are limitations, by using several lists of victim data, we can estimate the total population of slavery victims based on how often certain victims appear on one or more lists within a certain time period.
Piloted by Kevin Bales, Bernard Silverman and Olivia Hesketh in 2015 in the United Kingdom, this technique has been replicated by Jan van Dijk and Peter G. M. van der Heijden in 2016 to estimate the number of presumed victims of trafficking in persons in the Netherlands. This procedure was then refined, in partnership with the United Nations Office on Drugs and Crime (UNODC), to include information related to the gender (male, female), type of exploitation (sex, labour, etc.), nationality (foreign or domestic) and age of presumed trafficking victims in 2017. Subsequently, through a pioneering partnership between the Walk Free Foundation and UNODC, MSE has been successfully used to estimate the numbers of presumed victims trafficking in persons in Romania, Serbia and Ireland, with the final reports to be published soon. WFF is also working on a project with the International Organization for Migration on producing MSE estimates.
MSE is a statistical technique that uses the comparison of concurrent and identifiable victim lists typically held by national government offices to produce national prevalence estimates for modern slavery.
Measuring modern slavery in developed countries through MSE presents a tremendous opportunity to develop national ownership and participation in prevalence estimation. Using MSE also provides a new advocacy approach that engages national governments that have existing capacities and data infrastructure to prioritize the importance of this work.
Sometimes, when a nationally coordinated MSE effort faces substantial administrative, political or other obstacles, different solutions may be possible. For example, while the United States has not yet generated a national estimate of modern slavery, MSE is being adopted at the city and state levels. Researchers have effectively measured the number of modern slavery victims in New Orleans, Louisiana by employing MSE, though this research has not yet been published, and researchers and other stakeholders in several other states such as Georgia, Texas and Maryland are considering how this technique may be implemented at the state level.
MSE has also been successfully employed in the United Kingdom in 2014, refined and employed again in the Netherlands in 2016. This refined technique captured demographic information of victim populations that provides more detailed sub-estimates based on these administrative data. This information aligns current MSE efforts with Sustainable Development Goal Target 16.2: End abuse, exploitation, trafficking and all forms of violence against and torture of children and specifically, Indicator 16.2.2 which requests information on “the number of victims of human trafficking per 100,000 population, by sex, age and form of exploitation”.
Now, MSE efforts have begun to include this important demographic information for tailored victim sub-population estimates. These more detailed estimates will enable policy communities in each of these countries to better tailor their intervention efforts to address the victims and to inquire further about known populations that do not seem to be captured as well by government-held data to assist in greater detection efforts.
Overall, this programme has ambitiously achieved multiple objectives:
- Improving estimation of modern slavery in developed countries;
- The support and capacity-building of national governments to utilize their own existing data for these estimates; and
- Demonstrating the cost effectiveness, feasibility and retained victim data protections through MSE.
However, as with any applied statistical technique, there are always improvements that can be made. As a collective, the technical anti-trafficking field needs to consider some of our early successes in MSE and candidly discuss ways that we can best operationalize and adjust this method to ensure that we are reflecting the reality of slavery prevalence in developed countries. Sometimes, there are data gaps in government-held data that must be accounted for. For example, national governments will likely be unable to collect data on crimes that are not criminalized in their legal codes, such as forced marriage. As most applied statisticians will know, there are many ways to develop and refine models, particularly when based on real-world problems and applications, and just as many solutions to challenges that we might face.
Dr Davina Durgana is a Senior Statistician at the Walk Free Foundation.
Jacqueline Joudo Larsen is a criminologist and Head of Research at the Walk Free Foundation.
This article has been prepared by Dr Davina Durgana and Jacqueline Joudo Larsen as contributors 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.