On today's increasingly crowded globe, human migration can strain infrastructure and resources. Accurate data on migration flows could help governments plan for and respond to immigrants. Yet these figures, when available, tend to be spotty and error-ridden, even in the developed world. Researchers have developed approaches to estimate migration rates, but even the best of these rely on unrealistic assumptions about the mass movement of people and yield migration rates that can fall far below reality. 

In a paper published the week of Dec. 24 in the Proceedings of the National Academy of Sciences, Professor Adrian Raftery and Dr. Jonathan Azose, his former doctoral student and a current UW affiliate assistant professor of statistics, unveiled a statistical method for estimating migration flows between countries. Using the so-called pseudo-Bayes approach, they show that rates of migration are higher than previously thought, but also relatively stable, fluctuating between 1.1 and 1.3 percent of global population from 1990 to 2015. In addition, since 1990 approximately 45 percent of migrants have returned to their home countries, a much higher estimate than other methods.
These more accurate estimates of migration will ultimately help both migrants and the people who assist them, particularly since government records from immigration forms and censuses contain errors and often fail to collect the types of comprehensive information that demographers need to measure migration accurately.
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