# Inferring fine-grained migration patterns across the United States

## TL;DR

This study creates a high-resolution migration dataset for the US that reveals patterns like movement into high-income areas and racial disparities in mobility.

## Contribution

The novel contribution is a method to fuse proprietary and public data, creating MIGRATE, a dataset with 47.4 billion migration flows between census block groups.

## Key findings

- MIGRATE estimates are highly correlated with ground-truth datasets and more accurate than raw proprietary data.
- The dataset reveals rising migration into top-income block groups and racial disparities in upward mobility.
- MIGRATE uncovers local patterns like wildfire-driven out-migration invisible in coarser data.

## Abstract

Fine-grained migration data illuminate demographic, environmental, and health phenomena. However, United States migration data have serious drawbacks: public data lack spatial granularity, and higher-resolution proprietary data suffer from multiple biases. To address this, we develop a method that fuses high-resolution proprietary data with coarse Census data to create MIGRATE: annual migration matrices capturing flows between 47.4 billion US Census Block Group pairs—approximately four thousand times the spatial resolution of current public data. Our estimates are highly correlated with external ground-truth datasets and improve accuracy relative to raw proprietary data. We use MIGRATE to analyze national and local migration patterns. Nationally, we document demographic and temporal variation in homophily, upward mobility, and moving distance—for example, rising moves into top-income-quartile block groups and racial disparities in upward mobility. Locally, MIGRATE reveals patterns such as wildfire-driven out-migration that are invisible in coarser previous data. We release MIGRATE as a resource for migration researchers.

This study releases a very high-resolution migration dataset that reveals trends that shape daily life: rising moves into high-income neighborhoods, racial gaps in upward mobility, and wildfire-driven moves.