U.S. shouldn’t give up benefits of ‘green card lottery’ over low risk of terrorism

It would also end the green card lottery, which awards 50,000 green cards a year to people from countries with low rates of immigration to the U.S.

Importantly, it would also change who gets a leg up when applying for a green card. Currently, family of U.S. citizens and legal permanent residents, including siblings and adult children, are able to apply. The new system would limit that to minor children and spouses.

Instead, the bill would create a point-based system like those used in countries such as the U.K. and Australia that use factors such as English ability, education and job offers to rank applicants. However, it would be stricter than point systems used in those countries, which admit immigrants through other programs as well.

In essence, the plan would make the pool of immigrants more homogeneous and dramatically smaller in number, mirroring the misguided origin-based restrictions from the 1920s.

What economists say
Those who wish to restrict immigration often cite what they naïvely call “supply-and-demand economics” to essentially argue that the economy is a fixed pie that gets divided among a country’s residents. Fewer immigrants means “more pie” for the U.S.-born, as the story goes.

I am an economist, and this is not what my colleagues and I say. The commonplace argument that more immigrants, by themselves, lower wages and take jobs from Americans – an argument which Attorney General Jeff Sessions used to defend ending the “Dreamers” program – has neither empirical nor theoretical support in economics. It is just a myth.
Instead, both theory and empirical research show that immigration, including people with few skills and little English, grows the pie and strengthens the American workforce.

Value in diversity
While all the recently proposed changes to our immigration system will make U.S. workers worse off, the English requirement is likely to be particularly harmful to U.S. workers, especially low-skilled ones.

Indeed, I have found the relative fluency of U.S.-born workers is what keeps them from being harmed from labor market competition from immigrants.

The reason for this is the following. Essentially, immigrants with imperfect English skills tend to specialize in jobs that are less “communication-intensive,” such as manual labor. Americans fluent in the language, on the other hand, tend to take on higher-paying, communication-intensive jobs that are out of reach of those without a strong grasp of English. In other words, these groups aren’t likely to compete for the same jobs, making them more complementary than adversarial.

In contrast, when new immigrants are more fluent in English, something the Trump-backed proposal would encourage, the types of occupations they are qualified for are almost identical to those of American workers. Thus, insisting on strong English skills as a condition of coming to America is likely to increase labor market competition and suppress wages.

Immigration that helps
Immigration that emphasizes diversity, rather than merely merit, tends to attract more people who specialize in occupations uncommon among U.S.-born workers. And, in fact, this is the key source of the well-known economic benefits of immigration.

Studies by economists Giovanni Peri and Chad Sparber, for example, show this tendency toward job specialization is a key reason the large volume of low-skill immigration does not drive down incomes of Americans. Other research by Peri and Gianmarco Ottaviano shows that simply encouraging immigration from diverse origins lifts wages.

Put differently, there is direct evidence that the sort of diversity that the green card lottery encourages makes all Americans better off. It would be a shame to give all of that up because of a tiny risk of terrorism.

Ethan Lewis is Associate Professor of Economics, Dartmouth College. This is an updated version of an article originally published on 15 September 2017, and it is published courtesy of The Conversation (under Creative Commons-Attribution / No derivative).