Trump Has Undercut U.S. Refugee Resettlement. Here’s One Way to Restore It.

The first year of the Donald Trump presidency brought a significant amount of attention to a program that hadn’t previously made much news: the U.S. refugee resettlement program. Since the end of the Vietnam War, under both Republican and Democratic administrations, the United States has been the world’s leader in resettling refugees — offering a new life to those who have been persecuted at the hands of repressive governments or warring armies.

Yet at a time when there are more refugees globally than at any time since World War II, the Trump administration has abandoned America’s traditional leadership role. The State Department has slashed refugee admissions by more than half, to 45,000, a historic low. The United States has walked away from the United Nations’ efforts to coordinate an international response. And with fiery rhetoric and provocative travel bans, the administration has stoked anti-immigrant sentiment by playing to people’s fears about terrorism and cultural difference, especially when it comes to the possible admission of Muslim refugees.

While there is no evidence that refugees pose a security threat to the United States — in fact, refugees undergo the most onerous and thorough background checks of anyone entering the United States — the Trump administration’s focus on culture isn’t accidental. For many Americans, the arrival of foreigners who speak another language or belong to another religion surfaces deeply-rooted concerns about integration.

Refugee resettlement also triggers economic anxieties. Because refugees are selected based on vulnerability — in particular, a well-founded fear of persecution — many arrive without the English proficiency or professional skills they need to succeed in the United States. Most of them initially must rely on social services to get on their feet. Taken together, refugees’ cultural difference and economic dependence are powerful ingredients for political backlash. And this isn’t unique to America: Just witness the nationalist hostility toward asylum seekers in Europe.

But while one response to this political reality is to close the doors and pull back from global leadership, there is an alternative. The administration could back up its commitment to innovation and efficiency by embracing critical reforms that more cost-effectively facilitate the integration of refugees into American communities.

In a recent paper from the Immigration Policy Lab at Stanford, published in Science, we offer one place to start: optimizing the process that assigns refugees to resettlement locations across the United States.

That destination is one of the first policy decisions to affect newly admitted refugees who don’t already have ties to the United States, and it turns out to be highly consequential for successful integration. Taking employment as one key measure of integration, we find that a refugee’s likelihood of finding work depends on at least three different factors: personal characteristics like education and language skills; local conditions, such as housing availability, job opportunities, and co-ethnic networks; and harmony between personal characteristics and local conditions, such that different types of refugees do better in different locations.

Allocating refugees to the locations where they are most likely to find quality employment sets them up for successful integration, and this should be a critical element of the U.S. policy approach. Yet the United States currently allocates refugees to locations without systematically assessing how refugees with similar profiles have fared. It would be nearly costless to adopt a flexible, data-driven algorithm that would match new refugee arrivals to the locations where others with comparable characteristics have prospered in the past, without changing the total number of refugees allocated to any particular community.

In our paper, we demonstrate that this simple policy change would have a large impact, doubling the predicted probability of employment from 25 to 50 percent for the median refugee three months after arrival, increasing the average employment rate by 41 percent, and improving employment outcomes in nearly every geographic location. It is difficult to think of another policy intervention — education, job training, or language classes — that could produce such a sizeable effect at such a small cost.

We also show that algorithmic assignment would yield substantial improvements in refugee integration beyond the United States context. In Switzerland, asylum seekers are currently allocated to regions randomly and proportionally, so that different areas share the burden and the benefits of managing new arrivals. Tests suggest that our algorithm would increase asylum seeker employment by about 73 percent three years after arrival. This data-driven approach to refugee assignment holds great promise for any country that must make difficult decisions about how to allocate refugees across resettlement locations.

The refugee crisis demands a generous and effective response. Instead of closing refugee resettlement offices and blocking the entry of people from war-ravaged countries, the United States should maintain its historical commitment to welcoming the most vulnerable, while embracing innovations that can improve the lives of both refugees and the communities that host them. A modern system of matching refugees to the communities where they are most likely to succeed could reduce costs and improve outcomes, forming a critical element of a global reform agenda for refugee resettlement.