Abstract
Understanding the impact of climate change on human migration is critical for policymakers. Yet climate change can both incentivize people to migrate and reduce their ability to move, making its effect on human migration theoretically ambiguous. We propose a new approach that combines causal inference methods with cross-validation techniques to reliably estimate effects of weather on migration within and across borders. This approach highlights the key role of migrant demographics in the weather-migration relationship. We show that allowing weather effects to differ by age and education improves out-of-sample performance by a factor of five or more compared with a homogeneous effect. Demographic heterogeneity is critical in explaining this discrepancy. Projections based on our empirical estimates indicate that the effects of climate change on future cross-border migration will be an order of magnitude larger for most demographics than the average effect, but responses of different groups largely offset one another.
Link Microsoft Teams
Organisation
Raya Muttarak