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How Big Data Can Help Migrants

Why migration data should be the basis for informed decision-making.

Marzia Rango | International Organization for Migration

The international community has been calling for an improvement to the availability and quality of migration statistics for decades.

Just like in every other policy domain, data on migration is, or should be, the basis for informed decision-making.

This is particularly critical in times of displacement crises, such as those currently unfolding around Europe, as people from countries like Syria and Afghanistan risk their lives fleeing conflict and violence, hoping for a better future for themselves and their families.

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Accurate and timely statistics are needed to assist migrants effectively.

Accurate and timely statistics are needed to assist migrants effectively, and to counter common misperceptions that only serve to postpone urgently needed political and humanitarian responses.

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Why does migration data matter?

Migration statistics are also essential for the design of sensible migration policies.

They are necessary if migration is to be mainstreamed into national development planning, which means taking into account the impact of migration on a country’s development process, the impact of development on migration and how policies shape migrant behaviour.

Without migration statistics, a country can’t meaningfully plan how to allocate resources – for instance, to assist asylum-seekers or migrants in need.

Although global migration data is not as poor as commonly claimed, there is a need to improve the data collected through traditional sources while looking at the enormous potential offered by innovative sources, or “big data”. Recent developments in this area look promising.

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Without migration statistics, a country can’t meaningfully plan how to allocate resources.

Currently, the main sources of migration data are national population censuses, sample surveys (such as labour-force surveys) and administrative sources (for instance, population registers). Each of these sources has its advantages and limitations.

Population censuses are useful to measure the stock of international migrants at a point in time, but they are infrequent and can’t always inform policy at the appropriate moment.

Administrative sources can help measure migration flows in and out of a country (in a given period), but they are not entirely reliable as they register events, not people.

Surveys are useful to gauge the impact of migration on aspects like households’ financial situation or migrant labour conditions. However, they are costly and present methodological challenges.

The ability of countries to produce migration statistics has improved. But significant gaps remain, particularly in developing countries.

For instance, only 12 out of 49 sub-Saharan African countries have conducted a census in the past 10 years.

Nations struggling with developmental challenges have limited resources to allocate to the compilation of statistics, and data is usually not shared across the various agencies tasked with the collection of migration data.

Building countries’ capacity for collecting and managing this data is crucial. Meanwhile, how can innovative sources of data complement traditional sources in filling the gaps?

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Big data and innovation

There are now more than 7 billion mobile phone subscriptions globally, at least 5 billion of which are in developing countries.

Mobile phone penetration is growing fast, particularly across Asia and Africa, as is the number of internet users worldwide.

This means that an unprecedentedly large and complex amount of data is being generated in real time every time a call or an online payment is made, or every time people interact on social media. This is what is usually referred to as “big data”.

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Building countries’ capacity for collecting and managing this data is crucial.

Some studies have already shown the relevance and potential of such data for the analysis of migratory phenomena.

Mobile phone call records have been used to track human displacement in the aftermath of natural disasters as they include location details of the calling and receiving end.

Similarly, such records have been used to infer migration patterns within a country, for instance.

Recent studies have looked at repeated logins to the same website, or IP addresses from where emails are sent to gauge migration flows.

The fact that users’ activity on social media is geolocated also allows the estimation of migration trends through statistical modelling.

The huge potential of big data as a complementary source of migration statistics does not go without significant challenges. There are serious ethical and privacy issues in using data inadvertently generated by users for research purposes.

This type of information could fall in the wrong hands and be used for the surveillance of people – for instance by governments – with serious implications for civil liberties.

Policy-makers, researchers and practitioners need to come together to define a regulatory and legislative framework for collection and use of data coming from innovative sources.

The gap in information across countries risks growing wider as the “digital divide” is still a reality. Big data mostly refers to internet and mobile-phone users – not necessarily a representative sample of the population at large. Analytical and technical challenges to extract meaning from such data remain.

There is still a long way to go to use innovative sources of data systematically and effectively in migration studies. However, it is a discussion we need to have. goldbrown2

This article first appeared on the World Economic Forum Agenda and was republished with permission.

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marzia rango sepia
Marzia Rango is a Research Officer at the International Organization for Migration’s Global Migration Data Analysis Centre in Berlin

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1 Comment

  1. Janak Desai

    If it the lack of “Big data” that is the problem in movement of people from Third World to First World, one fact: 102 million people move into India. It’s not data, but the force of the planet that we have to look at like the duping by the market. It is the market that makes the move, not “Big data.”

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