Liberals and Immigration

Peter Beinart has an excellent essay in The Atlantic entitled How the Democrats Lost Their Way On Immigration. The article perfectly encapsulates the conundrum faced by liberals when they think about immigration:

Progressive commentators now routinely claim that there’s a near-consensus among economists on immigration’s benefits….There isn’t. According to a comprehensive new report by the National Academies of Sciences, Engineering, and Medicine, “Groups comparable to … immigrants in terms of their skill may experience a wage reduction as a result of immigration-induced increases in labor supply.” But academics sometimes de-emphasize this wage reduction because, like liberal journalists and politicians, they face pressures to support immigration…

The problem is that, although economists differ about the extent of the damage, immigration hurts the Americans with whom immigrants compete. And since more than a quarter of America’s recent immigrants lack even a high-school diploma or its equivalent, immigration particularly hurts the least-educated native workers, the very people who are already struggling the most. America’s immigration system, in other words, pits two of the groups liberals care about most—the native-born poor and the immigrant poor—against each other.

Beinart also raises an issue that is only whispered about in private and swept under the rug in public: Who is paying for all the pro-immigration research in economics? Whoever came up with the phrase “Follow the money” surely had an exquisite sense of where the bodies are buried. There need not be any intellectual corruption for this flow of money to influence the debate. As Beinart aptly puts it, “the prevalence of corporate funding can subtly influence which questions economists ask, and which ones they don’t.”

Finally, anyone who knows me knows that I would not be classified as progressive-leaning on economic policy (although I’m a live-and-let-live type of guy when it comes to social issues). Beinart actually cites the very progressive suggestion for “mitigating the problem” that I proposed in We Wanted Workers:

A better answer is to take some of the windfall that immigration brings to wealthier Americans and give it to those poorer Americans whom immigration harms. Borjas has suggested taxing the high-tech, agricultural, and service-sector companies that profit from cheap immigrant labor and using the money to compensate those Americans who are displaced by it.

This is one of those articles that is worth reading in full and thinking about very carefully.

 

 

 

The New Narrative: Less Immigration Is Bad

If one follows the political debate over a divisive issue for a long time, it is not rare to see ideological advocates switch to making arguments they would never have made years earlier. The political environment changed, and the claims that need to be made to further the ideological objective must change as well.

Maybe it’s just me because I instinctively read in between the lines whenever I read anything about immigration, but I’m beginning to detect such a seismic shift in the immigration debate. We all know the party line by now: Immigrants do jobs that natives don’t want to do. As a result, natives do not lose jobs, and natives do not see their wages reduced. And anyone who claims otherwise is obviously a racist xenophobic moron. They obviously don’t like immigrants, and they obviously are not educated/credentialed enough to understand and appreciate expert opinion.

The flurry of immigration restrictions proposed by the Trump administration demands a switch in tactics–with a corresponding switch in the argument linking immigration and wages. The party line must now be that less immigration is bad. But how can one show that in simple-to-grasp economic terms that can be mass-marketed to the masses? By far the simplest way is to come up with examples that less immigration raises labor costs and makes us miserable because everything becomes more expensive.

I first noticed the tactical switch back in March when the Washington Post published a story headlined After decades in America, the newly deported return to a Mexico they barely recognize, The point of the story, of course, was to imply that Trump’s deportation initiatives are bad because they are making Mexicans worse off. And how exactly are Mexicans made worse off?

More returnees means lower wages for everybody in blue-collar industries such as construction and automobile manufacturing, where competition for jobs is likely to increase, economists say.

I love the “economists say” add-on. Too bad that those economic experts remain unnamed. But don’t be shocked if they are the same exact economic experts who have been claiming the same exact opposite for two or three decades in the context of the American labor market.

Then there’s this story in a local New England paper. The goal again is to demonstrate the economic costs created by Trump’s immigration restrictions. The Bangor Daily News article is headlined Amid foreign worker shortage, Bar Harbor businesses turn to local labor. The article starts off by noting that “Businesses in Maine that rely on summer help are hoping that Congress will come to the rescue.” And what do these businesses have to be rescued from? Higher wages, of course.

Because of new limits on the seasonal worker visa program, restaurants, hotels and other tourist-centered operations are scrambling to find seasonal employees. Until Congress opens the door to more H-2B foreign workers…Bar Harbor area employers are enticing workers in other ways. Higher wages are part of the solution.

The Dallas Morning News joins in the fun with a story blaming the immigration slowdown for higher housing prices. The story is headlined One Reason for Dallas’ soaring home prices and labor shortage: Immigrants aren’t coming to work:

Dallas home prices are climbing rapidly, and homebuilders are complaining about labor shortages and soaring wages for construction workers.

Duh! Who could have possibly guessed that fewer construction workers meant higher construction wages?

Finally, the highly credentialed economic experts at the Federal Reserve are out in force documenting just how costly the immigration-related actions of the Trump administration are. In a recent Bloomberg article headlined Fed Officials Sharpen Concerns Over Trump’s Immigration Policy, those credentialed experts expertly make the point:

Patrick Harker, president of the Philadelphia Fed, became the latest policy maker to call attention to the struggles of companies in finding low-skilled labor…The Chicago Fed said one manufacturing firm raised wages 10 percent to attract better applicants and improve retention of unskilled workers. A freight trucking firm in Cleveland reported granting raises of almost 8 percent in an attempt to retain workers.

There is no upper bound to the hypocrisy of experts. It might be a lot of fun to keep track of this over the next few years, watching the dominos fall and all those “immigration-does-not-affect-wages” experts fall all over themselves as they switch to proving the economic awfulness of Trump’s actions because fewer immigrants mean higher labor costs, higher prices, more inflation.

But don’t hold your breath for any admission that they were wrong in the past. They will instantly switch to the former party line the minute the Trump immigration restrictions fade into history.

The WSJ Weighs In On Mariel

The WSJ weekend edition just published a long essay (here’s an ungated pdf version) on the academic debate sparked by my reappraisal of the Mariel evidence. Ben Leubsdorf, the WSJ reporter, has been working on this story for quite some time. He flew up to Boston back in March to have an extended conversation with me, so this is definitely not an off-the-cuff reaction to whatever happens to be the controversy de jour in this seemingly never-ending (and increasingly tiresome) tale. Ben obviously did his homework, digested all the relevant work, and talked to a lot of people. I think it’s a pretty good account of the state of the debate. It made me wonder yet again where things would be today if the question of whether wages respond to shifts in supply had not been so depressingly politicized.

One of my favorite solutions to this question comes from Paul Samuelson, the Nobel-Prize-winning economist whose Nobel citation noted that he had “done more than any other contemporary economist to raise the level of scientific analysis in economic theory.”

After 1965, laws were passed greatly liberalizing immigration. A flood of immigrants has been admitted since then . . . By keeping labor supply high, immigration policy tends to keep wages low.

………..I know it’s mid June, but April Fools! I tricked you by strategically changing a few words in what Samuelson said. Can one even imagine a world-renowned economist making such a statement in today’s political environment? What Samuelson actually wrote in his introductory economics textbook back in 1964 was:

After World War I, laws were passed severely limiting immigration. Only a trickle of immigrants has been admitted since then . . . By keeping labor supply down, immigration policy tends to keep wages high.

I’ve highlighted the words I changed in the quote. As Paul Samuelson noted long ago, and as the low-skill workforce in Miami learned back in 1980, the labor market is not immune to the laws of supply and demand.

Race And Mariel

I finally finished the paper that addresses the latest Mariel-related brouhaha–the claim that the large drop in the wage of high school dropouts in post-Mariel Miami was spuriously created by a change in the racial composition of the March CPS sample. As I documented in earlier blog posts here and here, not much happens to the results of my Mariel paper when one uses race-adjusted data to look at wage trends in Miami and comparison cities. The new technical paper summarizes much of this evidence, shows that the before-after wage drop remains even if we were to start the analysis in calendar year 1979 (after the unexplained change in the racial composition of the survey), compares what happened in Miami to what happened in over 123,000 alternative placebos, and adds even more data/discussion. Put simply, the claim that the post-Mariel drop in Miami’s low-skill wage was spuriously produced is fake news.

I realize that it is the type of fake news that will be accepted unquestioningly by those who are ideologically wedded to–or financially dependent on–the notion that a 20 percent increase in supply does not change prices (at least in the immigration context). But the paper lays out all the facts and even the most cursory look at the actual data demonstrates the inescapable conclusion that something indeed did happen to low-skill wages in post-Mariel Miami. (All the programs used in the preparation of the paper are here).

One part of the paper is worth discussing more fully now, as it seems to be the direction in which the debate is headed. The point is a bit on the geeky side, but definitely worth thinking about as it shows just how easy it is to torture the data into screaming “PLEASE! STOP! THERE IS NO WAGE EFFECT!” by making what seem to be innocuous assumptions.

In a recent response to my blog posts, Clemens finally estimated the statistical model that corresponds to my analysis and concluded that although he can replicate my regression showing the drop in the “race-adjusted wage,” the ultimate answer depends on just how the race-adjusted wage is calculated. In an important sense, the blog response subtly moves the “goalpost” of the Clemens-Hunt criticism. It is no longer that the change in the black share of the workforce induced a spurious correlation that led to lower wages in post-Mariel Miami; just look at the figures in my paper or the regression evidence and it’s obvious that this particular argument is just plain wrong. It is now instead that the measured wage impact of Mariel could be zero if we calculated the race-adjusted wage in a different way.

Let me explain what a race-adjusted wage is. It is the wage we would see a black worker earn if his employer suddenly became color-blind and saw him as just another white worker. The trend in the race-adjusted wage would then show what happened to Miami’s low-skill wage in a world where race was no longer relevant.

Obviously, the race-adjusted wage is not available in survey data. It needs to be calculated somehow, usually by estimating a regression model. And this is where all kinds of tricks can be played to get different answers. So I cooked up a trivial numerical example in my new paper to get the point across in the simplest way possible.

Tale of Two Cities.png

I’m going to tell a hypothetical tale of two cities, Miami and New York. In this tale, New York did not receive any immigrants, but Miami did. The table shows the average wage of black and white low-skill workers in the two cities before and after the supply shock. Panel A at the top gives the unadjusted wage data–the data that would be available in the CPS. By construction, immigration had a much larger impact on black workers in Miami, reducing their wage from $7 to $4, while the wage of white workers fell by only $1, from $10 to $9.

Panel B shows the race-adjusted wage in each city. As I said earlier, we need to calculate that wage, and to do so we are going to use all the low-skill wage data available across cities, across race groups, and over time. We would then look at the available data in the top panel of the table, see that there is a $3 racial wage gap among low-skill workers in Miami prior to the supply shock, and use that information to infer that the race-adjusted wage of a black worker in Miami in that period should be $10. After the supply shock, we would see a $5 racial wage gap, and use that information to infer that the race-adjusted wage of a black worker in Miami should be $9. (In fancy econometrics jargon, we just ran a fully interactive regression model, allowing wages to fully vary by city × education × race × year).

Suppose that half of Miami’s workforce is black. The average race-adjusted wage in Miami fell only from $10 to $9, or 10 percent. In fact, the average wage in Miami fell from $8.50 to $6.50, or nearly a 25 percent drop. The drop in Miami’s race-adjusted wage is not all that big for a simple reason: If the calculation of the race-adjusted wage ignores that the racial wage gap in Miami might have increased because of immigration we are going to greatly understate the impact of immigration.

Panel C at the bottom of the table shows what would happen if we used an alternative calculation of the race-adjusted wage that does not throw the baby out with the bathwater. Suppose that Miami is a very small city relative to New York. We are now going to use national data on how the racial wage gap for low-skill workers changed over time to calculate the race-adjusted wage. We would again look at the actual data in the top panel and see that the average black worker nationwide earns $3 less than the average white worker both before and after the supply shock. This would imply a race-adjusted post-migration wage for black workers in Miami of $6 (or $3 less than what whites get). If we use this approach, the average race-adjusted wage in Miami fell from $10 to $7.50, or 25 percent. (In econometrics jargon, we ran a regression that allows wages to vary by education × race × year).

In short, the mechanics of calculating the race-adjusted wage matter a lot. But is it proper to calculate the race-adjusted wage by netting out the change in the racial wage gap in Miami when that change could have been caused by immigration? It seems plausible that Mariel affected the wage of black and white workers in Miami differently. There were substantial differences in the jobs the two groups held, in the occupations they entered, and in the industries that employed them. The Marielitos obviously penetrated some sectors more than others, affecting the magnitude of the racial wage gap for a particular education group in Miami relative to other cities. A “race-adjusted wage” that nets out this differential impact removes much of the effect that immigration might have had on the local labor market. As a result, it would not be surprising if the measured impact of immigration became much smaller, perhaps near zero.

The two panels of the table below shows how the bias shows up in real-world data when I calculate the actual wage impact of the Marielitos using alternative calculations of the race-adjusted wage. The top panel uses the fully interactive model, netting out the fact that the racial wage gap for high school dropouts in Miami changed over time (perhaps because of Mariel). As in my cooked-example, the measured wage effects are small, though some are still statistically significant in the ORG.

Interaction Table.png

The bottom panel instead allows for the racial wage gap at a particular point in time to vary across age groups, across education groups, and across cities–but does not net out that the racial wage gap for high school dropouts in a particular city (like Miami) might have changed over time. Note that the wage effects of the Mariel supply shock are strongly negative and statistically significant.

So the question now becomes: do we know anything about whether immigration into a particular city affects the low-skill racial wage gap in that city? In other words, does immigration affect the wages of low-skill blacks and low-skill whites differently? Amazingly enough, only a handful of papers estimate the wage impact of immigration separately for black and white workers. And out of that handful, as far as I know, there is only one paper that estimates the impact for low-skill blacks and whites. Ironically, this happens to be the classic paper by Joe Altonji and David Card. This is the relevant page from the Altonji-Card study (click to enlarge, and the relevant numbers are the ones furthest to the right in the bottom row of each table):

Screen Shot 2017-06-09 at 8.28.18 AM

It sure seems as if the negative impact of immigration on the low-skill black wage is about twice as large as the impact on the low-skill white wage, making my numerical example quite relevant. In fact, this very large estimate of the impact of immigration on low-skill blacks was the one specifically cited in Table 5-2 of the recent National Academy of Sciences report.

I know that this geeky discussion may not be particularly gripping to those who just want to know the answer (especially if one is looking for a different answer). But the statistical exercise used to compute the race-adjusted wage in a city at a point in time should not follow blindly from a kitchen-sink approach to regressions. Careful thought must be given to why racial wage differences might arise, and how the time trend of those racial differences in a particular city might be affected by immigration. It is entirely possible (and much too easy for those tempted to do so) to hide away the wage impact of Mariel by using the wrong conceptual approach.