Improved migration algorithm shows 45 percent of migrants return home

Dec. 31 (UPI) -- Until now, demographers and governments have struggled to precisely track migration. The statistical models used to predict the flow of people across borders have proven inaccurate.

Scientists at the University of Washington, however, have developed a better migration-tracking algorithm using the pseudo-Bayes approach.

Their analysis showed that between 1990 and 2015 the migration rate fluctuated between 1.1 and 1.3 percent of global population. Researchers defined migration as crossing an international border and staying for at least a year.

According to the new estimates, the migration rate over the last two-plus decades was higher than anticipated -- but stable. The analysis, detailed in the journal Proceedings of the National Academy of Sciences, also showed nearly half, 45 percent, of migrants eventually return home.

During any given time period, almost half of all migrants are traveling back to their country of origin.

"Our estimate shows a higher global flow of migrants in large part because it indicates that return migration is much higher than previously thought," Jonathan Azose, an affiliate assistant professor of statistics at Washington, said in a news release.

Azose and his research partners built the new algorithm by combining several models using the pseudo-Bayes method. The scientists tested their model against accurate records of migration statistics in 31 European countries. The new estimation method produced more accurate data than competing models.

"For the migration field, this level of accuracy is a significant improvement," said Azose. "Even when you look at data from European countries, it's not uncommon for a single migration flow to have estimates that differ by a factor of three or more depending on whether the sending or the receiving country collected the data."

The new research could help scientists more accurately track the impacts of politics, economics and climate on human movements. The improved algorithm could also help governments better prepare for the coming and going of migrants.

"Planning for migration is no simple task," said Adrian Raftery, a professor of statistics and sociology at Washington. "You need everything from medical infrastructure and trained personnel to elementary schools -- and governments rely on accurate demographic estimates to help them put the right plans and responses into place."