President Donald Trump wants to overhaul the U.S. immigration system so that it stops favoring visa applicants with U.S. family ties, and instead gives priority to highly skilled applicants and those with job offers. The proposal is based on the assumption that immigrants’ educational credentials—what the administration calls “merit”—will lead to increased U.S. wages and immigrants who better integrate into U.S. culture.
Immediately after it was announced, the proposal drew criticism from all sides. Many Republicans don’t think it goes far enough to combat illegal immigration, while others on the right want total immigrant admissions to be cut. Many Democrats, meanwhile, don’t want to roll back the system’s humanitarian, family-oriented principles that have worked well over decades, and also want to resolve the status of America’s 11 million undocumented immigrants.
The whole idea of “merit” is a lightning rod in a highly charged issue. But there’s a smarter way for both sides to think about who we let in, and why. The Trump administration is on to something when it says we need a new way to evaluate immigrants, one that predicts their future success as Americans. Indeed, considering future immigrants’ contributions is now commonplace in immigration policies around the world. But the Trump administration’s idea of how to do this is too basic. Many Democrats, for their part, are too quick to dismiss any kind of evaluation as anti-humanitarian: Done right, it actually would consider family and other humanitarian factors, and likely set new arrivals up for greater success in their new country.
Call it Immigration Moneyball. Just as baseball was revolutionized with a multidimensional data-driven system for evaluating and selecting players, the U.S. can analyze far more information than it currently does to decide which immigrants will best thrive in American society and contribute to the economy—something people of all political persuasions want to see.
Right now, both sides are viewing immigrants in entirely one-dimensional ways. Imagine a system that instead considered immigrants more fully as individuals—rather than simply as skilled workers, unskilled workers or family members, as our current immigration framework does. It might, for example, find merit in whether applicants made previous visits to the United States as a student, tourist or temporary worker. Imagine a system that also tracked people’s exits from our airports, harbors and train stations, and then assigned value to an immigrant’s previous on-time departures. The system might find “merit” in youth, in fluent multilingualism, in training or work experience in trades that are in special demand at the moment, or in advanced degrees from American universities. It could prioritize immigrants who pledge to settle in rapidly depopulating regions for their first 10 years after arrival; admits could even be matched to locales likely to produce their successful employment and integration.
Imagine if all this was considered alongside whether immigrants have family in the U.S. to receive them, help them adjust and help them find work. That, too, is a predictor of likely success: Research suggests that family migrants with close existing family ties have similar economic outcomes to migrants admitted on labor visas that screen for credentials and contracts. In this light, family represents a powerful form of merit, too. And importantly—because welcoming people in need is a core tenet of American culture—the criteria might include whether admission will rescue them from countries subject to severe poverty, violence or natural disasters.
We now have the tools to discover what qualities and factors actually make immigrants most likely to succeed in the United States—and then assess would-be immigrants based on those criteria. To call the approach “Moneyball” is oversimplifying, of course; immigration, unlike baseball, doesn’t deliver easily countable runs and wins, and an immigrant’s success can and should be defined in many ways. It could mean law abidance, employment, economic mobility, business ownership, patents filed, sense of belonging or political participation.
What qualities matter most will largely be up to the government in power to decide. While we can debate what constitutes successful integration, it would be better if we actually collected and consolidated information about the extent to which admitted immigrants are making progress in these different ways. If we did, we could see which attributes known at admission best predict these different forms of success, and adjust our criteria accordingly in the future. Right now, we don’t know.
For decades, baseball was managed according to hunches and instinct. For a sport that collects more statistics than any other, much of its recruiting and game-day decision-making was based on a highly subjective je ne sais quoi.
This all ended when the Oakland Athletics began incorporating evidence-based, analytical reasoning into decision-making, an approach documented in Michael Lewis’ 2003 book, and now adopted to some extent by every Major League team. Early adopters held a major advantage before the rest of the game caught up.
Today, U.S. immigration policy looks a lot like baseball once did. Most people orient their policy preferences around their gut feelings about foreigners. Many on the left view immigrants as either hard workers who will reinforce shrinking populations or vulnerable people who must be welcomed in the spirit of humanitarianism. On the nationalist right, many view immigrants as opportunists or even (as the president himself has suggested) criminals, who come to exploit the resources of rich countries, and whose presence threatens the national culture. The debate has mostly been argued from the extremes (see fearmongering about the gang MS-13, and calls to #AbolishICE) and become unmoored from sober reasoning.
The truth is, as countless studies have shown, immigrants on average are powerful generators of economic growth, who are disproportionately employed, innovative, entrepreneurial and law-abiding—and who, on average, quickly integrate and do not compete with American-born workers for jobs, except at the lowest wages. Immigration advocates have repeated these findings more than a pitcher rehearses his windup.
But the current system is also operating with a clunky, outdated selection strategy. This is where critics have an important point: The system we have really is relatively indiscriminate, and unconcerned with predicting good outcomes.
Like baseball teams, governments and researchers already collect extensive data about admitted and prospective immigrants in every dimension of public debate: employment and welfare consumption; criminality and civic engagement; language attainment and educational achievement. Name it.
But the government doesn’t use or consolidate all this data. It hasn’t crunched the numbers to determine the full range of qualities and factors that help an immigrant succeed and contribute—how much, for example, English-speaking skills upon entry matter for longer-term workforce participation, and whether younger skilled immigrants contribute more tax dollars before retirement than older skilled immigrants with more established expertise.
Furthermore, rather than evaluate the entirety of an admission applicant’s qualifications, the U.S. government—like many others—limits their consideration to a few factors and an arbitrary interview at an embassy. Visa types are designated by the primary “purpose” of entry, as if immigrants are either workers or family members, refugees or students. It reduces each immigrant, a person with unique potential and confluence of skills, attributes and needs, to a single, artificial classification and then files her or him into a line. While particular H1-B visas, for example, might prioritize immigrants who have a specific skill and job, they take no account of humanitarian concerns, or whether that immigrant has family in the U.S.
The result is a system that ignores many indicators of immigrants’ potential. It’s like a university that selects students based on their future major, and little else.
Think about this: Would you rather grant admission to an engineer based on no other information, or to an engineer who speaks fluent English, has a sister in Detroit, and was once a high school exchange student in Omaha? The answer seems obvious.
Perhaps less obvious, would you rather grant admission to a qualified engineer without family ties or demonstrated familiarity with the U.S., or to an agricultural worker who speaks proficient English, has a sister in Detroit and was once a high school exchange student in Omaha?
More difficult, would you rather admit that agricultural worker with family ties and English skills or one with a contract offer already, who has agreed to settle in a rapidly depopulating region, but who doesn’t have family in the United States?
An admissions system informed by statistical reasoning and criteria adjustable to current needs would be able to answer these questions, selecting optimal applicants for temporary or permanent visas based on reliable predictions about the applicants’ productivity and social contributions, as well as the state of the U.S. economy at the time.
Backed by such reasoning, the engineer or agricultural worker doesn’t just look good; we will have evidence-based assurances that she is likely to actually be good.
Does all this require an overhaul of the existing admissions system? Yes. In addition to verifying the data we already collect from applicants, we’d need to collect more—and then build the capacity to quickly process admissions decisions. We will also need a system that processes exits as well as entries and studies immigrants’ progress once they are admitted.
Once built, the system can be adjusted according to new legislation, government research or employer recommendations with little lag time. Imagine if there were a shortage of nurses or programmers. Imagine if fertility rates dropped and social security nears insolvency. Imagine if there was a pool of immigrants already with American university credentials who were qualified for open jobs. All of these are known actualities, and a more advanced system would enable quicker adjustments.
Such a new system can also help the country incorporate more visas for circular migration that permits immigrants to regularly or seasonally enter the United States for specific work purposes and then return to their country of origin. If government agencies ever synchronize their data, renewing a visa for these and other temporary immigrants can be more like renewing a driver’s license, subject to a variety of quick checks. This will all reduce the incentive to cross the border without authorization or overstay a visa. Today, employers with low-skilled or seasonal labor needs often rely on undocumented workers, who cannot return to the U.S. if they return to their country of origin and are barred from returning for 10 years thanks to “unlawful presence” rules.
The idea that what we know about immigrants when they apply for admission predicts their ultimate social and economic contributions is one that has informed immigrant admissions in places like Australia and Canada, whose “point-based” systems evaluate applicants based on similar skill-oriented criteria. But even the Canadians—whose points-based system is the world standard—do not include criteria like family guarantors or attempts to match immigrants with certain regions.
As with any immigration policy, there will be political hurdles. Critics on the left will worry that algorithms will replace the current system, which dedicates about two thirds of all visas to family admissions. But algorithms can be weighted or overridden to continue to prioritize spouses and minor children without counting them toward quotas. And they can also be programmed to recognize more extended members of American families, who have been less likely to be admitted over the past couple decades.
Critics on the right might worry that such a meritocratic system will lead to even greater annual flows of immigrants in light of new modes of entry. However, the qualifications for entry can be raised or lowered to hit annual flow targets, and quotas—if desired—can still be applied. It is also worth acknowledging that the foreign-born represent about 15 percent of the American population—about half the share in places like Switzerland (30 percent) and Australia (29 percent), and still lower than New Zealand (23 percent), Canada (22 percent), Austria (19 percent), Sweden (18 percent), Ireland (17 percent) and elsewhere.
Other critics may worry that a system based on algorithms and points may be less transparent than the current one, and may be more subject to bad-faith inputs driven by racism or xenophobia. As I have argued before, a side effect of established points-based systems has been preference for white applicants and others from countries with stronger education systems. Giving credit for previous visits to the U.S. can have the same effect because it is easier to get visas from Western countries. But this would be offset if family ties were substantially taken into consideration. The system could also assign “merit” to people who hail from countries underrepresented in the United States—among the purposes of the diversity visa lottery that the Trump administration has proposed cutting. Furthermore, the current system is hardly transparent anyway. Consular officers and immigration judges possess enormous arbitrary power, and there are reports of line-cutting.
Ideally, a system like this should appeal to many on both sides. It will render a sense of control to those on the right, and justify maintaining current a steady flow of newcomers as the left envisions.
As in baseball, there will be plenty of exceptions, when advanced reasoning still fails to predict good outcomes. Not every immigrant will create as many jobs as Elon Musk; some will commit crimes (likely at lower rates than American citizens, according to U.S. government data). And as in baseball, there will be holdouts who don’t want to modernize the immigration system and maintain current flows, whether because of persistent prejudice or deep-seated mistrust. But as in baseball, such small-mindedness will ultimately lose.
Trump has gotten away with strategies as simplistic as a steel wall and tactics as barbaric as separating children from their parents because the debate has become symbolic and subject to our most basic instincts, which are currently calling for humanity or control.
The best way to simultaneously humanize immigrants and control their admission is to shift to a system that considers their humanity in the most complete way possible.