Estimating and predicting migrations has been a growing issue on the agenda of scholars and policymakers in the last decades. Forecasting irregular migration is of particular interest to policymakers as a tool enabling them to adapt policy to future trends.
The meaning of irregular migration is not always clear as there is no universally accepted definition. It is still often used interchangeably with ‘illegal migration’ even though ‘illegal migration’ is increasingly restricted to cases of smuggling and trafficking of persons. For the International Organisation for Migration (IOM), irregular migration is movement of people that takes place outside the regulatory norms of the sending, transit and receiving countries.1
This report highlights that forecasting irregular migration poses various problems. While data collection on international migration has improved, it is still extremely difficult to estimate the flow or stock of irregular migrants. Moreover, most models focus on regular migration and conceptualise migration as a voluntary act which excludes forced migration. The lack of data (in particular on irregular migration) but also their lack of flexibility to integrate change in the context led to new initiatives such as the ‘Global Migration Futures’ project which uses scenario-building instead of forecasting. Researchers looking at forced migration have developed forecasting models. Attempts have been made to design early warning models to predict refugee flows. However, scholars tend to focus more on early warning models which predict conflict and political crises that are considered the root causes of forced migration. Recently, a project was launched at the University of Georgetown to build an early warning system for detecting forced population displacement.