Sometimes research is like going hiking. Whenever Dominik Hangartner embarks on a new trek, he selects his destination, saves the route on an app, and then strikes out into the unknown. This fondness for treading new paths also spills over into Hangartner’s research, where it joins ambition, persistence and the use of new statistical methods.
Hangartner is an Associate Professor of Public Policy at ETH. He says that a healthy mixture of patience and impatience characterises his personality and way of working, but it’s the impatience that drives him forward: he wants answers to his research questions, and he wants them now. “Scientific quality is something that needs time, however,” says Hangartner. “Basic research is a marathon, not a sprint.”
This kind of research requires patience and persistence until the results take shape. The initial assumptions then either crystallise into ironclad facts, or they break down in the face of empirical evidence and have to be discarded – at which point the journey begins anew. In the world of science, this can be just as edifying as staying on the same path.
Hangartner is fascinated by the tension that arises from the desire to have immediate answers and the slower-paced reality of conducting research: it’s one factor that drew him to a career in academia. He also relishes the challenge of putting research findings to the real-world test. “As a scientist I always want to go one step further,” says Hangartner. “This also means being able to translate my research results into actionable policies and testing if they actually work in the real world.”
Challenges in migration
Hangartner is not the type of academic who issues bold theories from the ivory tower. Rather, his approach to research often involves collaborations with governments, international organizations, and immigrant service providers. He analyses hard real-world data to shed new light on topics such as the economic and political impact of migration, asylum procedures and integration, and public attitudes towards immigration.
Some typical case studies from his research include the integration of refugees in local job markets, the effects of the asylum process, and the role of naturalization in immigrant integration. According to Hangartner, one fundamental challenge in this space is that scepticism towards immigration is increasing in many host countries while the push factors for migration show no signs of waning.
For this reason, Hangartner focuses on analysing how well laws and policies work, what effect they have, and how they can be re-designed for the benefit of migrants and their host communities. “Our knowledge should serve as the basis for innovative solutions in asylum and integration policy that improve the situation for as many people as possible,” he explains.
In just the past three years, he has authored various publications showing, for example, that lengthy asylum procedures and employment bans for refugees lead to higher social costs and a reduction in tax revenues.
Together with colleagues from Stanford, Hangartner developed a broadly applicable, data-driven algorithm for improving the geographic allocation of refugees. This algorithmic approach makes use of existing data to harness the synergies between refugees’ characteristics and host communities. This allows for refugees to be settled in regions where they have the best chances of finding employment.
The State Secretariat of Migration (SEM) is currently running a pilot study to test the effectiveness of this data-driven approach, and policymakers from the Benelux countries and Scandinavia have also shown interest in the method.
