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 decisionmaking was highly subjective.
This all ended in 2002 when the Oakland Athletics began incorporating evidence‐based, analytical reasoning into decisionmaking, a process now adopted to some extent by every Major League Baseball team.96 Early adopters enjoyed a big advantage before other teams caught up.
Today, U.S. immigration policy looks a lot like baseball once did. Most people form their policy preferences around their gut feelings about immigrants. 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 criminals who come to exploit the resources of rich coun‐ tries and whose presence threatens the national culture.
Immigrants on average are powerful generators of economic growth, disproportionately employed, innovative, entrepreneurial, and law‐abiding. Generally, they quickly integrate and do not compete with American‐born workers for jobs, except at the lowest wages.97 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But the current system is also operating with a clunky, outdated selection strategy.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: employ ment, welfare consumption, criminality, civic engagement, language attainment, educational achievement, and much more.
Officials in the U.S. Department of Homeland Security or other agencies could crunch the numbers to determine the full range of qualities and factors that help an immigrant succeed and contribute. This includes, for example, how much English‐speaking skills upon entry matter for longer‐term workforce participation and whether younger skilled immigrants contribute more tax dollars before retire ment than older skilled immigrants with more estab lished expertise. Officials could then evaluate the entirety of their qualifications rather than focusing on a few characteristics, such as family ties or education. The current focus reduces each immigrant—a person with unique potential and confluence of skills, attributes, and needs—to a single, artificial classification and then files him into a column on a spreadsheet. While particular H-1B visas, for example, might prioritize immigrants who have specific skills and jobs, they take no account of humanitarian concerns or whether immigrants have family in the United States.
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 United States 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 still, would you rather admit that agricultural worker with family ties and English skills or one with a contract offer who has agreed to settle in a rapidly depopulating region but who doesn’t have family in the United States?
An Immigration Moneyball system informed by statistical reasoning and criteria adjustable to current needs would answer these questions better than the current system. It would select 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 and labor market. Ambiguities will always exist, and some cases will be impossible to answer, even with the best data and statistical methods. But Immigration Moneyball gets the United States closer to a true merit‐based system. Backed by such reasoning, the engineer or agricultural worker selected under such a system doesn’t just “look good”; we will have evidence that she is likely to be good.