Abstract

There are over 10 million Mexican migrants in the United States; about half are undocumented. We connect the historical mobility patterns to the United States extreme weather conditions in Mexico. We combine predictive machine learning tools with mechanism-based statistical models. We show that combination and sequencing of droughts are critical to all aspects of the migration process: who migrates, whether migrants use clandestine channels to cross, and when they return to Mexico.

Reference

Filiz Garip (Princeton University), “Climate Change, Migration, and Inequality”, IAST General Seminar, Toulouse: IAST, May 6, 2025, 11:30–12:30, room Auditorium 4 (First floor - TSE Building).