This blog has been written in parallel with the release of the latest episode of The Migration Oxford Podcast titled "Global Migration Data: Making Sense of the Numbers".
The UN has been publishing recommendations on how countries should define and measure international migration since 1953. Yet we still know relatively little about global migration. Even though more data are being collected than ever before, we still struggle to answer basic questions. For example, the latest figure for the global number of migrants is for mid-2020, and only 45 countries reported sharing data with the UN on migration flows. In Africa, 17 per cent of countries have not produced official statistics on the number of international migrants since 2005. Why is this? In this blog, we explore a few common obstacles to effectively collecting, managing and analysing migration data.
What are some of the key data challenges?
Uneven adherence to definitions
Migration has been defined in different ways over the years. The 1998 UN recommendations did this comprehensively, defining an international migrant as:
“any person who changes his or her country of usual residence”, distinguishing between “short-term migrants” – those who change their country of usual residence for at least three months but less than a year – and “long-term migrants” – those who do so for at least one year.”
While countries are encouraged to follow these recommendations, not all do. Instead, many use different concepts and definitions. For example, some countries use a different minimum duration of stay to define migrants. Out of 36 countries reporting international migration flow data to the OECD in 2018, only 11 used a 12-month definition as internationally recommended.
This all affects global comparability of data and means we cannot compile national migration data meaningfully; it isn’t possible to compare one country’s migrants statistics with another’s if the way migrants are defined and measured is different.
The landscape of migration is always changing. To reflect the growing complexity of migration, increasingly we speak not only about migration but also about “human mobility,” a wider concept – for example, including those regularly undertaking cross-border movements for study or work, or living across countries. A process is underway to update the 1998 recommendations to reflect this – revised statistical concepts and definitions are already available.
Hard-to-measure populations
Even with official definitions, accurately counting who a migrant is not always straightforward. For example, those with double citizenship are sometimes double counted in different countries, and will be recorded differently depending on which passport they use. The three authors of this book have five countries of citizenships between them – the UK, Hungary, Spain, Germany and Italy – by marriage two more – France and Brazil – and live in two further countries of residence – Switzerland and the US. What does this mean for how they are counted? People live increasingly complex lives.
Some migrant populations are especially hard to reach with classic data collection methods. For example, unaccompanied minors, homeless migrants and irregular migrants, who may be at particular risk of poor wellbeing, do not always appear in official statistics. Often they are not included in survey or census sampling frames, or are excluded from population registers and residence permits. Seasonal workers who may not change their primary place of residence may also be statistically invisible. Some migrants may be unwilling to be included in data collection exercises, for fear of possible detection or deportation by law enforcement.
Fragmentation and poor coordination
In any given country, different types of migration data is collected from across areas of government and through everyday civic and administrative life, and additionally through regular statistical exercises like surveys and censuses. Often migration data producers (such as National Statistical Offices, or NSOs) don’t interact regularly with migration data users (such as a health ministry). Without a special structure, such as a working group, it is difficult for the right people to convene and collaborate regularly to share, discuss and improve migration information
This can lead to a high degree of fragmentation in data, which makes it harder to get a full picture of migration trends as each data source can only provide information about specific aspects of the phenomenon. This fragmentation in migration data explains much of the limited understanding of migration that we have today. Some countries have used innovative methods to integrate information. Canada’s Longitudinal Immigration Database (IMDB) connects data on immigration and citizenship with longitudinal data on socioeconomic outcomes.
Limited capacity
Another challenge is governments’ limited capacity related to migration data, as many lack capacities to generate quality migration statistics. Issues can look like anything from not having advanced enough statistical analysis software, to staff not having all the knowledge necessary to, for example, integrate data protection considerations. Migration data may be given insufficient priority, meaning that in turn, funding to improve it is limited.
These challenges are all workable – read next week’s blog post to find out how to improve migration data.
