Measuring Global Migration Flows using Online Data

2025-04-16

AI Summary

Existing international migration statistics suffer from significant limitations in coverage, timeliness, and reliability. To address these gaps, this paper develops the first global-scale, monthly-resolution model for estimating international migration flows across 181 countries, leveraging anonymized behavioral data from 3 billion Facebook users. The methodology incorporates privacy-preserving preprocessing, correction for selection bias, multi-source data fusion, and counterfactual migration rate inference—overcoming the latency inherent in conventional statistical systems, especially during crises such as pandemics and geopolitical conflicts. Our 2022 estimates indicate 39.1 million international migrants (0.63% of the population in sample countries), accurately capturing a 64% decline during the pandemic, a subsequent 24% rebound, and a tenfold surge attributable to the Ukraine crisis. The dataset will be publicly released via the Humanitarian Data Exchange (HDX) platform, enabling real-time, high-resolution support for evidence-based policy and humanitarian response.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Humans and AI: Intelligent User Interfaces
• Machine Learning: Large Multimodal Models (LMMs)

Application Category

• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Web Mining and Content Analysis: Large pretrained models with web data
• Security and Privacy: Large-scale security measurements

Abstract

Existing estimates of human migration are limited in their scope, reliability, and timeliness, prompting the United Nations and the Global Compact on Migration to call for improved data collection. Using privacy protected records from three billion Facebook users, we estimate country-to-country migration flows at monthly granularity for 181 countries, accounting for selection into Facebook usage. Our estimates closely match high-quality measures of migration where available but can be produced nearly worldwide and with less delay than alternative methods. We estimate that 39.1 million people migrated internationally in 2022 (0.63% of the population of the countries in our sample). Migration flows significantly changed during the COVID-19 pandemic, decreasing by 64% before rebounding in 2022 to a pace 24% above the pre-crisis rate. We also find that migration from Ukraine increased tenfold in the wake of the Russian invasion. To support research and policy interventions, we will release these estimates publicly through the Humanitarian Data Exchange.

Problem

• Estimating global migration flows with limited existing data
• Using Facebook data to measure monthly migration between countries
• Tracking migration changes during COVID-19 and Ukraine war

Innovation

• Uses Facebook data for migration estimates
• Provides monthly granularity for 181 countries
• Matches high-quality measures with less delay