Searching for grouped patterns of heterogeneity in the climate-migration link

This paper uses international migration data and climate variables in a multi-country setting to investigate the extent to which international migration can be explained by changes in the local climate and whether this relationship varies between groups of countries. Moreover, the primary focus is to further investigate the differential effect found by Cattaneo and Peri (2016) for countries with different income levels using a high-frequency dataset. The idea being that country grouping is considered to be data driven, instead of exogenously decided. The estimation technique used to endogenously group the countries of origin is based on the group-mean fixedeffects (GFE) estimator proposed by Bonhomme and Manresa (2015), which allows us to group the origin countries according to the data generation process. The main results indicate that an increasing average local temperature is associated with an increase in that country's emigration rate, on average, but the effect differs between groups. The results are driven by a group of countries mainly located in Sub-Saharan Africa and Central Asia; however, no statistically significant association is found between the average amount of local precipitation and that country's rate of emigration.