| Willy Brandt School of Public Policy

Will Jones: Refugees and Municipalities. Rethinking the Distribution Process.

In 2015, the German Interior Minister, Thomas de Maizière, told press that “[asylum seekers] cannot choose the states where they are seeking protection.” This statement, focused on what ‘cannot’ be done, catalyzed a critical reconception of the current refugee allocation system. Research on this shift was spearheaded by Dr. Will Jones and Dr. Alex Teytelboym, the former of which gave a guest lecture on January 16th at the Brandt School. The spirited lecture took the audience through the basics of market design, matching markets, and the application of the two concepts on the Refugee Match. Dr. Jones was joined by Christine Sommer from the Thuringian Office of the Commissioner for Integration, Migration and Refugees. She shed light on the current refugee allocation process in the state, the challenges that the office is facing, and the synergy with the Refugee Match concept.

Refugee Match is timely in the European context in the wake of the increase in migration to Europe since 2015. Of the 3.6 million asylum seekers since 2015 in Europe, 1.8 million have been allocated. Migration, however, is an ongoing phenomenon; in the first ten months of 2019 alone, there were 600,000 new asylum applications. What is more, the current refugee allocation process is an often cumbersome one and a less than adequate system for ensuring the maintenance of dignity, the prioritization of preferences, and the reduction of burden on people in an already vulnerable state. Imagine an office filled with slips of paper with names of refugees being shuffled around by administrators to fill open slots in host municipalities. The Refugee Match system at its core is meant to instill a sense of agency for refugees in the allocation process. Municipalities in which refugees are allocated have certain capacities and preferences for new community members. In turn refugees also have certain capacities and preferences. The Refugee Match system as outlined by Dr. Jones is based an algorithm that optimizes the two ‘sides’ in order to 1) speed up the allocation process relative to the current manual and heavily bureaucratic process; 2) ensure that refugees are not allocated to communities that are no able to meet their needs (for example in terms of sufficient primary school spots or special health conditions); 3) reach pareto efficiency—not making one party better off at the expense of the well-being of another party; and 4) create a system that protects the information of parties to enable them to safely disclose their true preferences. Similar matching market algorithms are already in use and saving lives in the US system for matching kidney donors and other contexts such as land tenure and public-school student allocation (Jones & Teytelboym, 2018).

In Germany, refugees are allocated to the federal states and then the local agency processes and resettles them within the territory. Ms. Sommer emphasizes that Thuringia needs immigration: "We therefore want to create a good basis and welcoming conditions so that refugees who come to Thuringia feel well here, are offered good and tailored opportunities for integration and want to stay in Thuringia. Dr. Jones's matching is therefore also very interesting for Thuringia. If the refugees are accommodated in municipalities in a way that the needs and desires of both refugees and municipalities are properly met, this is a mutual benefit and an opportunity for Thuringia."

There are certainly potential benefits in Thuringia to integrate the Refugee Match system to lead to better allocation outcomes for both refugees and the municipalities. Unfortunately, the external factors such as rising xenophobia and the political obstacles are salient barriers. Yet taking the allocation of refugees to Thuringia as a given, if Refugee Match can be shown to save resources in the allocation process, there is the potential that the discussion will be revisited. Further to get community buy-in to the refugee allocation process, an audience member who grew up in Thuringia suggested that identifying the needs of Thuringian small businesses through a town hall process may be a democratized application of the Refugee Match system. This could be particularly relevant in municipalities in Thuringia that are difficult to motivate to accept refugees. This begs the question what is the right level of bottom-up, top-down, automation, or bureaucracy in the process of refugee allocation?

Sources & further Information
Eurostat. (2020, January 14). Asylum and first time asylum applicants—Monthly data (rounded). Eurostat. https://ec.europa.eu/eurostat/databrowser/view/tps00189/default/table?lang=en
Jones, W., & Teytelboym, A. (2018). The Local Refugee Match: Aligning Refugees’ Preferences with the Capacities and Priorities of Localities. Journal of Refugee Studies31(2), 152–178. https://doi.org/10.1093/jrs/fex022
Thuringian State Office for Statistics. (2019). State election 2019 in Thuringia—Final result. Elections in the Free State of Thuringia. https://wahlen.thueringen.de/datenbank/wahl1/wahl.asp?wahlart=LW&wJahr=2019&zeigeErg=Land
Tondo, L. (2019, August 25). Nearly 900,000 asylum seekers living in limbo in EU, figures show. The Guardianhttps://www.theguardian.com/world/2019/aug/25/asylum-seekers-limbo-eu-countries