Periodic Reporting for period 2 - INTEGRATE (Identifying the Impact of Asylum Polices on Refugee Integration and Political Backlash in Host Communities)
Reporting period: 2020-05-01 to 2021-10-31
Governments across the globe are still struggling to cope with the aftermath of the largest refugee crisis since the Second World War. For many asylum seekers and refugees, the refugee crisis has turned into an integration crisis with many still waiting for decisions on their asylum applications and struggling to access jobs and a social network in their new home countries. Against this background, we are conducting much needed research into the impact of various asylum and integration policies in Europe.
The goal of this project is to provide systematic evidence that identifies the causal effects of the key parameters of the asylum process on the short and long-term economic, political and social integration of refugees, their families, and children in selected European countries. Specifically, we examine the impact of wait times, labor market access, geographic placement, language courses, integration contracts, and welfare support, and family reunification policies on integration trajectories.
By using causal research designs and innovative statistical methodology to comprehensively evaluate the asylum process in Europe, we aim to establish actionable evidence base that can be used to redesign the asylum process to improve outcomes for both refugees and host societies.
The goal of this project is to provide systematic evidence that identifies the causal effects of the key parameters of the asylum process on the short and long-term economic, political and social integration of refugees, their families, and children in selected European countries. Specifically, we examine the impact of wait times, labor market access, geographic placement, language courses, integration contracts, and welfare support, and family reunification policies on integration trajectories.
By using causal research designs and innovative statistical methodology to comprehensively evaluate the asylum process in Europe, we aim to establish actionable evidence base that can be used to redesign the asylum process to improve outcomes for both refugees and host societies.
Since the beginning of the project, we have performed work on a range of national asylum and integration policies. We published a first paper (Martén, Hainmueller and Hangartner, 2019, Proceedings of the National Academy of Sciences) showing that recently arrived refugees in Switzerland were more likely to be employed if they lived close to a larger group of people who share their nationality, ethnicity or language. We have also examined the impact of two publicly funded language programs in Germany in response to the large increase in the number of asylum seekers in 2015: a rapidly developed, ad hoc program that offered basic language training to over 230,000 newly arrived refugees and a smaller, preexisting program that offered refugees comprehensive language training. We find that the more comprehensive, preexisting program increased refugee employment but document no discernable benefits for the ad hoc program.
In addition, we have implemented important steps in other sub-projects. We have analyzed data about labor market access and welfare support in Switzerland, have interviewed resettlement refugees eligible for the Swiss Pre-Departure Orientation program, refugees that have been encouraged to sign an integration contract in France, and have begun a large-scale randomized control trial to evaluate the benefits of data-driven, algorithmic geographic placement to optimize employment outcomes.
In addition, we have implemented important steps in other sub-projects. We have analyzed data about labor market access and welfare support in Switzerland, have interviewed resettlement refugees eligible for the Swiss Pre-Departure Orientation program, refugees that have been encouraged to sign an integration contract in France, and have begun a large-scale randomized control trial to evaluate the benefits of data-driven, algorithmic geographic placement to optimize employment outcomes.
We are currently pilot testing our data-driven algorithm to optimally match refugees to locations (Bansak et al, 2018, Science) as part of a large-scale randomized control trial in Switzerland with 2,000 refugee families. When the trial is completed as planned, this will constitute one of the first randomized evaluation of human-centered applications of machine-learning for improving refugees’ integration outcomes in an actionable, scalable, and ethically-responsible approach. We also have conducted a series of retrospective impact evaluations to assess the potential of data-driven geographic assignment in the Netherlands.
Additionally, we expect to obtain results on a range of other asylum and integration policies in Europe until the end of the project. Specifically, we will find out more about the impact of the employment ban in Germany, integration contracts in France as well as labor market access, welfare support, asylum process length and a Pre-Departure Orientation program in Switzerland.
Together, these findings will provide answers to the complex and urgent question of how to best facilitate the integration of increasing numbers or refugees, while mitigating political conflict and native backlash in host communities.
Additionally, we expect to obtain results on a range of other asylum and integration policies in Europe until the end of the project. Specifically, we will find out more about the impact of the employment ban in Germany, integration contracts in France as well as labor market access, welfare support, asylum process length and a Pre-Departure Orientation program in Switzerland.
Together, these findings will provide answers to the complex and urgent question of how to best facilitate the integration of increasing numbers or refugees, while mitigating political conflict and native backlash in host communities.