Paper co-author Professor Guy Abel (left) from the Department of Sociology, Faculty of Social Sciences at HKU, and lead author of the paper Dr Thomas Gaskin (right), a postdoctoral researcher at the Department of Methodology at LSE.
Researchers from The University of Hong Kong (HKU) and the London School of Economics and Political Science (LSE) have unveiled a transformative new dataset on human mobility, revealing that global migration has risen sharply from approximately 13 million people per year in 2000 to around 35 million in 2023. Published in the leading scientific journal Nature, the findings demonstrate that the rise in migration significantly outpaces global population growth, reflecting a true per-capita increase in human mobility.
A fundamental challenge in quantifying global migration flows has been the reliance on highly fragmented data. Current analyses heavily depend on migrant population counts published at five-year intervals by the United Nations and ten-year intervals by the World Bank. Because these traditional datasets only offer a snapshot at a fixed point in time, major global events that drive sudden human movement - such as wars, economic recessions, pandemics, or climate shocks - have frequently been missed in the data capture.
To overcome this, the joint research team utilised deep learning to build the first comprehensive dataset of migration flows across all countries for the period of 1990 to 2023. By combining official statistics, census data, and geographic and economic factors through advanced machine learning (deep neural networks), the researchers have successfully filled the missing gaps, offering a far more detailed and dynamic picture of global movement.
Key findings and implications of the research:
- A Consistent Upward Trend: Migration has become significantly more common overall since 2000, with temporary dips occurring only during the 2008–09 global financial crisis and the COVID-19 pandemic.
- Major Migration Corridors: Globally, the Middle East experienced the highest total inflow of migrants, chiefly from South Asia and the Philippines. Since 2010, an estimated 19 million people (averaging 1.35 million per year) migrated from India, Pakistan, and Bangladesh to Saudi Arabia, Qatar, Bahrain, and the UAE. By comparison, there were 13.6 million movements from Mexico to the US over the entire period since 1990.
- Regional Dynamics: Europe consistently ranks as the region with the highest volume of intra-regional migration, surpassed only once by Sub-Saharan Africa in the early 1990s during the Rwandan civil war.
- Illuminating the Global South: The new dataset provides unprecedented visibility into migration movements in the Global South, where data has traditionally been scarce. For instance, it accurately captures the large exodus into Ethiopia caused by the South Sudan civil war (from 2013 onwards) and the displacement of an estimated 79,000 Nigerians fleeing Boko Haram violence between 2013 and 2014.
Commenting on the new dataset and its significance, lead author of the paper Dr Thomas Gaskin, a postdoctoral researcher at the Department of Methodology at LSE, said: "Our estimates were obtained by combining classical flow modelling with deep learning, utilising a wide range of data for model input and training. I think the scale and breadth of this dataset really showcases the potential of this kind of hybrid modelling in the computational sciences."
Paper co-author Professor Guy Abel from the Department of Sociology, Faculty of Social Sciences at HKU, added: "Because previous estimation methods relied on coarse five-year snapshots, they yielded very few data points and created the impression that the rate of global migration flows was stable. Our annual data provides a clearer picture, revealing that this rate has actually risen since 2000. This upward trend appears to be driven by long-term demographic shifts and economic development rather than sudden, isolated crises."
The study was published in the leading journal Nature.
Link to the paper:
