Modeling Migration and Global Population Patterns
Natural disasters drive migration less than thought: new data offers a more realistic picture
Natural disasters do influence internal migration in the United States, but the effect appears to be smaller than is often assumed. According to climate scientist Marijn Ton, this is because neighboring regions tend to resemble one another closely, and natural disasters do not stop at administrative borders. By taking this interconnection between regions into account, it becomes possible to make a more realistic estimate of migration—one that will often be lower than previously expected.
In addition, Ton’s research shows that it is important to understand where people live and what opportunities they have. He therefore developed a global dataset. For approximately two billion households and more than seven billion individuals, he compiled a wide range of information. This includes demographic data such as age, household size, and gender, as well as socioeconomic data such as education and income. This provides insight into where households are located and what options are available to them.
By combining this information with migration models, we can better assess who is able to relocate after a disaster, who remains, and where measures or support are most urgently needed.
More information on the thesis
