Note: This post was crossposted from Lauren Policy by the Forum team, with the author's permission. The author may not see or respond to comments on this post.
Some housekeeping first:
This is the first post in a living literature review on migration. Basically, I’ll review what the academic literature has to say about a particular topic in migration. Topics may be as narrow as “the Mariel Boatlift” or as broad as “what is the effect of migration on economic growth”. You can see an example of a more complete living literature review at New Things Under The Sun.
I plan to put up a new post on migration about once a month (though it may be more frequent in the next couple of months, as public interest is high). All migration related posts will live in the migration section of my Substack; you can subscribe to just that if so desired. Since this is a living literature review, I'll also go back and update these posts as new research comes out; those updates will live on a future website - subscribe to keep in the loop.
This post - and the others in the living literature review - are supported by a grant from Open Philanthropy.[1] There is a fringe benefit to readers of this Substack being grant supported - since it is being supported by external funding, this newsletter will be entirely free.
All opinions and analysis are my own, and not Open Philanthropy’s. And so, without further ado:
The Mariel Boatlift
On April 20, 1980, Fidel Castro announced anyone who wanted to leave Cuba via the port of Mariel was welcome to do so.[2] There were no restrictions on exit, other than requiring emigrants to provide their own transportation off the island. Within hours, Cuban-Americans organized missions to go pick up refugees; within days, a flotilla of hastily rented vessels was ferrying Cubans across to Miami.
By the end of the boatlift in October, about 125,000 Cubans had arrived in the US. Almost all landed in Miami;[3] 60% would still be living there a decade later.
This was a large influx; about 1% of Cubans left Cuba for Miami. The influx increased the size of the labor force in Miami by 7%; 16% of all Cubans living in America in 1990 arrived during the Mariel Boatlift. 8% of all Cuban-Americans (that were in the country in 1990) arrived in the single month of May 1980.
So what happens to a city when you add 125,000 immigrants almost overnight? The size and suddenness of the influx has made Mariel a particularly popular way for economists to examine the effects of immigration on destination labor markets.
The Mariel Boatlift was unusual among immigration shocks because the receiving country exercised essentially no selection of those who entered. The US had no control over the composition of the influx.[4]
Countries rarely accept an unexpected influx of 100,000 new migrants. Usually, there are changes in the receiving country that make it more likely to want to receive migrants and there is some policy in place that shapes where they go and what they do. In the case of the Mariel Boatlift, no one was particularly expecting to drastically increase the number of Cuban-Americans and the US was caught largely off-guard.
Mariel is a good natural experiment because Cubans came to Miami not by Miami’s (or the US’) choice; they came to Miami because it was close to Mariel. It was as-if random that Miami gained 100,000 new immigrants and Detroit did not.
What were the labor market effects of a sudden influx of workers in fields with low barriers to entry?
Most of the economics literature on Mariel has focused on the labor market outcomes from a large immigrant influx.
Over the course of five months, the labor force expanded almost 10%; really, since the majority of Marielitos arrived in May, the labor force in Miami expanded about 5% in a single month. Most Marielitos tried to get jobs in fields with low barriers to entry and relatively low wages, such as construction.[5]
Mariel is thus a hard test of how migrants who enter industries with a low barrier to entry can affect the wages of natives in the same industries. If wages of natives did not decline from this large shock, it seems unlikely that there are many - indeed, any - circumstances in which adding additional migrant workers in low-wage positions would drive down native wages in an advanced economy.
The first - and still most famous study - of this question is Card 1990. Card finds no evidence that the influx of Marielitos drove down wages or increased unemployment in low-wage jobs. Card uses a difference-in-differences approach. In this design, you look at how a control group and a treatment group evolve over time, and see how much more (or less) the treatment group changed relative to the control group.[6] In this paper, he compares how labor market outcomes changed in Miami between 1974 and 1984 to how labor market outcomes changed in the relatively similar cities of Atlanta, Los Angeles, Houston, and Tampa-St. Petersburg. The key assumption is that without the boatlift, wages in Miami would have evolved in parallel with wages in these other cities.
However, empirical economics has come a long way since 1990 (with some of those innovations coming from David Card himself). Card doesn’t give a strong reason to choose those comparison cities, and it’s possible Miami differs from them in important ways. There have been two major re-analyses of the labor market impacts of the Mariel Boatlift with decidedly different results: Borjas 2017 and Peri and Yasenov 2019.
Borjas 2017 argues that one should consider the wage effects on native high school dropouts, specifically. Most of the Marielitos did not complete high school; thus, they would compete in the labor market against other high school dropouts. Marielitos probably would have no impact on the market for labor for college graduates; it makes sense to focus specifically on the effects on the workers that were most similar to the Marielitos. He finds that wages for these workers specifically dropped by 10-30%.
Peri and Yasenov 2019 uses a synthetic control method to compare post-Mariel Miami to what Miami might have looked like without Mariel. In a synthetic control design, you construct a fake city that is similar to your treatment city. It’s built as a combination of other cities - for instance, your city might be most similar to Houston, but also a little bit similar to Tampa; your synthetic control will be a weighted average of data from these other (not-treated cities). You can then compare fake-Miami (built out of other cities that didn’t receive the treatment) to real Miami (which did).
Peri and Yasenov find no evidence of a drop in wages or increase in unemployment among high school dropouts in Miami. This is a true null; they can exclude an increase in unemployment and a decrease in wages for high school dropouts.
So what gives? Did high school dropouts suffer or not? Here we turn to Clemens and Hunt 2019. They point out that Borjas and Peri and Yasenov use different samples.[7] In particular, Borjas looks at a small portion of the native labor market, excluding “women, Hispanics, workers under age 25, workers over age 59, and workers who have finished high school or its equivalent” in a small survey set (the March Current Population Survey). That is quite a bit of the population to exclude; Clemens notes he excludes 91% of workers in low-wage jobs.
Furthermore, Borjas’ choice of the Current Population Survey data - and then excluding large portions of it - does seem to matter. At the same time as the Mariel boatlift, Miami experienced an influx of Haitian refugees. These refugees had little formal education - only 5% had completed high school - and struggled to find work, much more so than Marielitos.[8] These refugees make up a substantial portion of Borjas’ sample, because he has excluded almost everyone else.
And if you compare a pre-1980 group of mostly African-Americans, and a post-1980 group of African-Americans and Haitian refugees, the latter group will have lower wages since so many of the refugees struggled to find work. It’s not because Cubans took their jobs, though.[9]
There are other issues with the Borjas sample - for instance, the Census was making an effort to survey all African-Americans, and therefore, there was increased coverage of low-income African-Americans just around the time of the Mariel Boatlift. This meant that mechanically, wages for African-Americans decreased because more low-wage African-Americans were added to the sample. They had already existed before 1980; they just weren’t included in the data.
All of this means that, in my judgement, Peri and Yasenov 2019 contains the best estimates we have on the effect of a sudden influx of workers into fields with low barriers to entry. And their conclusion was: there was no effect on wages for native workers.
One could imagine that there was no wage effect on natives just because Marielitos didn’t find jobs. I don’t think this was the reason, though.
It is true that Marielitos struggled to find work once in the US. In surveys conducted three to four years after the Boatlift, 39% of Cubans were not currently working.[10] But those same surveys seem to indicate that Marielitos were in and out of low-wage jobs, rather than consistently unemployed, as average wages for Marielitos in 1983 were only 20% lower than the average for Cuban-Americans in Florida. Marielitos were also ineligible for government assistance; the Marielitos who didn’t have family in Miami[11] had to work or starve.
So… you added a hundred thousand people to a city nearly overnight. They all needed jobs; the supply of labor has increased dramatically. If one considers pure supply and demand, you would expect wages to fall; your supply has suddenly increased but the demand for them is unchanged. Why didn’t wages fall?
Bodvarsson, Van den Berg and Lewer 2008 has (at least some of) our answer. Workers are not simply suppliers of labor; they also increase demand for labor. They buy food; they go to stores; they interact with the local economy. Adding new people to a city doesn’t just increase supply of labor; it increases demand for the goods and services they provide. Immigrants might take some jobs, but they also create jobs; these effects appeared to cancel out in Miami.
It is possible there are other explanations as well. Card 1990 and Monras 2020 posit the effects of the Mariel Boatlift were lessened because other immigrants and natives moved out of Miami (or at least the rate of inflow slowed). However, Peri and Yasenov 2019 sees no offsetting outmigration of the natives most similar to the Marielitos. There is no Clemens-esque paper reconciling these two results, so I think it remains unclear how - and if - internal migration played a part in how the labor market in Miami reacted to the Mariel Boatlift.
Did the Mariel Boatlift increase crime in Miami?
Of course, jobs aren’t the only reason that people worry about immigration. There is a strong stereotype that allowing immigrants into “our” neighborhoods can increase crime, and Marielitos in particular were perceived to be undesirables.
There was widespread press at the time that Castro used the Boatlift to rid himself of “hardened criminals, mental patients, and other deviants” (Portes and Stepick 1985). The Washington Post estimated ~22,000 of the Marielitos had felony records, about 17% of the influx. The criminal Marielito even shows up in Scarface.
These concerns were overblown, but not entirely baseless. Miami had just accepted 70,000 young(ish) men that were loosely attached to the labor market. This is the demographic group most likely to be involved in criminal activity, and engage in criminal activity they did. And some of them did have criminal records, though nowhere near 17%.[12]
Billy and Packard 2022 use a synthetic control method to estimate crime rates in Miami had the Mariel Boatlift not happened, and compare against Miami’s real crime rate to determine how the Boatlift affected crime. They find the Boatlift caused a “nearly 25-32% expansion in property crime”. Robberies increased by 70% and murders by 41%.
Billy and Packard hypothesize that unemployed young men, some of whom had a criminal background prior to arrival in Miami, turned to property crime as a method of making money. They also note that much of the increase in violent crime appears to have been driven by violence by Marielitos on other Marielitos; other Miami residents may not have experienced an increase in violent crime.
Still: these are very large increases, particularly when one considers baseline crime rates in the 1980s were considerably higher than they are today. For once, then, it seems that fearmongering about immigrants causing an increase in crime was correct. This 1985 Sun Sentinel article seems likely to be correct; the legacy of Mariel was not any labor market impacts, but increased crime.
Does that mean immigrants cause crime? Not necessarily. It is important to report the facts as we know them, even if I don’t particularly want them to be true, and Billy and Packard’s study does indicate that the Mariel Boatlift did increase crime rates in Miami.
But: it is worth noting (as Billy and Packard do) that the Mariel Boatlift was an atypical immigration episode, where a large number of young men (some with felony records) all arrived in one location in a short time period. A future post will look at the broader literature on immigration and crime under more common circumstances.
What were the electoral consequences of the Mariel Boatlift?
In 1980, Jimmy Carter was running for re-election against Ronald Reagan. In November, he lost very badly. 51.9% of Floridians voted for Carter in 1976; only 38.5% voted for him four years later. Did the chaos around the Boatlift contribute to Carter’s loss in Florida?
According to Thompson 2022, probably not. Thompson also uses (primarily) a synthetic control design, this time to look at how electoral outcomes changed because of the Boatlift. He finds that while Reagan did gain vote share in Miami, it doesn’t appear to be because of the Boatlift. Reagan picked up vote share among all Cuban-Americans, not just those in Miami - likely because he was so vocally anti-Communist.
Other Republicans did not gain as much vote share as Reagan did in Miami in the 1980 election. Voters did not seem to blame the county or city’s Democratic mayors; Democrats remained in power in Miami. This is a bit of a surprising result, given the previous section on crime! Why didn’t Miami voters punish Democrats for the increase in crime? I don’t really know.
What don’t we know about the Mariel Boatlift?
There are still quite a lot of things we don’t know about the impacts of Mariel Boatlift. A few stand out:
- 1% of Cubans left the island; what did that do to the Cuban labor market?[13] Did wages in Cuba change?
- What were the long-term outcomes of Marielitos? As far as I’m aware, there are no papers on outcomes for Marielitos after 1990. What happened to Marielitos and their children >10 years after arrival?
So, what can we learn from the Mariel Boatlift?
I have three major takeaways from the Mariel Boatlift:
- This was a weird policy choice that has not that much applicability to other circumstances and types of immigration.
Mariel was a very large, very sudden influx of people with little vetting, some with prior criminal records. This is not how immigrant inflows normally go! Most immigrants have to go through an extensive process to get a visa and there is considerable selection on the part of the receiving country on who gets to enter the country.[14]
The Mariel Boatlift is a good natural experiment because the usual vetting and selection process didn’t happen. But that also means that it’s very different from other immigrant inflows.[15]
We can’t really learn anything about most immigration policies from Mariel.
1. But most likely, immigrants do not drive down the wages of native workers.
As I note above, the Mariel Boatlift is an extremely hard test of how an influx of immigrants affects the wages of native workers. If adding 5% to your city’s labor force in a month doesn’t change wages for even those most similar to the new workers, probably nothing will.
2. Being careful about methodology matters.
As Borjas 2017 and Peri and Yasenov 2019 show, different researchers can look at the same event and draw opposite conclusions based on the methodology they use to study it. Since these conclusions can influence policy decisions, it’s important to be careful and rigorous about how you study a question.
If one took Borjas 2017 at face value, accepting a large number of low-wage workers would really hurt the least educated Americans. That might lead one to pursue policies that limited the number of low-wage workers allowed to enter the US.
But my read of the evidence is that Borjas’ result isn’t true; it’s an artifact of unrelated changes in the dataset he uses. One could then end up making policy based entirely on a change in sample composition, rather than a true effect.
Empirical social science is more than academic; it informs real debates that impact real people’s lives. It is therefore incumbent upon the empirical social scientist to make sure their results are as robust and as accurate as possible, and communicate transparently about how they got the results they did. Methodology matters.
Many thanks to Denise Melchin, Jeff Fong, Karthik Tadepalli, Matt Clancy, Luzia Bruckamp, Richard Nerland, Oscar Sykes, and Jesse Smith for their comments and edits on this post.
- ^
For more information on this program, see this blog post.
- ^
Cuba, unlike many developed countries, requires potential emigrants to get permission to leave the country. This process is difficult even today.
- ^
Approximately 7500 people left Cuba in April 1980 via flights to Costa Rica and then on to the US; this population did not land in Miami.
- ^
Indeed, Card 1990 notes that the exact number of Marielitos was unknown, as was the composition of the Mariel influx. The information we do have suggests that Marielitos were younger than the average Cuban-American (three years younger on average), mostly male (55%), had lower levels of education than the average Cuban-American (~40% less likely to have a high school diploma) and were 40% less likely to speak English well (Portes and Stepick 1985, Card 1990)
- ^
This is partially because language barriers made higher-wage jobs less accessible to them.
- ^
An explanation of DIDs can be found here, but basically, you’re estimating the treatment effect as the difference between P2 and Q in this graph.
- ^
For information about labor market outcomes in Miami, Peri and Yasenov turn to the May Outgoing Rotating Group for data rather than the March Current Population Survey, as it has a larger sample size and measures point in time wages rather than recalled yearly wages. Borjas primarily uses the smaller March Current Population Survey, which had as few as 55 individuals included in his sample in some years (table 1, Peri and Yasenov 2019). Both of these features increase the size of the error in his estimates, because it is a small sample and people’s memories aren’t that great.
- ^
Most of the facts in this piece about the labor market for Haitians and Cubans are from Portes and Stepick 1985. Portes and Stepnick conducted representative surveys of both groups three years after the Boatlift.
- ^
Perhaps unsurprisingly, Borjas still disagrees with this conclusion, as he does with most studies that show null to positive effects from immigration.
- ^
The aforementioned Portes and Stepick 1985 surveys
- ^
Many did have relatives in Miami; indeed, some Miami Cubans went to Mariel specifically to get their relatives and bring them back. However, this was not the case for all Marielitos, and most did need to get a job to support themselves.
- ^
Billy and Packard 2022 estimates that about 5000 Marielitos had previously committed crimes the US would consider felonies; about 2000 of those were eventually deported, so about 3000 Marielitos with previous criminal records were able to stay in the US. This is about 2.5% of the total.
- ^
Richard Nerland, who proofread this post, said “we have like seven papers on possible downward pressure on wages in Miami and none on potential upward pressure in Cuba”.
- ^
Especially unusually, Mariel immigrants were even sometimes negatively selected - people Castro wanted to get rid of - and some did have criminal backgrounds.
This is unusual for immigrant flows, even when one considers undocumented people; the average undocumented person is considerably less likely to commit a crime than the average native-born person.
- ^
Perhaps the only comparable recent event was Germany’s admission of a large number of Syrians in 2015 (most of whom were young men), but the policy consequences there seem to have been different. In Germany, refugees were not particularly likely to commit crimes against Germans but the vote share for right-wing parties did increase - exactly the opposite of what happened in Miami.
Are you sure this is true? I think both state and federal government provided a lot of aid, as is typical for refugees. See for example President Carter's speech:
I am also skeptical of this inference you make:
Castro was a communist dictator. While some of the people leaving I would expect to be criminals, I would also expect those who were opposed to communism and wanted valued the opportunities and freedoms offered by capitalism to be highly represented. If you wanted to work hard and better yourself, why would you not want to move from Cuba to the US? I would expect them to be significantly positively skewed, especially compared to recent refugees into Europe, who have access to generous government benefits.
I am also confused by your claim here:
Despite looking through the paper you cite (and consulting Notebook LM), I could not actually find this comparison in it. It is clear the authors have the data to calculate it - they have crimes tagged by whether they were committed by a refugee or not - but curiously they seem to have forgotten to actually calculate the ratio, instead opting only to show more complicated regression results whose conclusions, I imagine, were more agreeable to them.
However, the basic statistics are easily available elsewhere, despite the German state's attempts to suppress reporting on the subject. Even the BBC publishes them:
As the article in The Critic itself points out, it is hardly surprising that a group that is disproportionately made up of young, single men are more criminal than the general population, since young men are overwhelmingly more criminal than anyone else, and single men are likely plausibly worse. It's not clear what this tells us about immigrants even from Syria or Afghanistan, let alone anywhere else, if we control for that. My guess for what it's worth is that they will still have higher crime rates even if you control if they are Syrians (don't know about Afghans, suspect more positive selection there), but you'd need to actually look.
I haven't read their paper, but the chart sure seems like it establishes a clear correlation. Also, the quotes you are saying seem to be saying something else, claiming that "greater inflow was not correlated with greater crime", which is different than "refugees were not particularly likely to commit crimes against Germans". Indeed, at least on a quick skim of the data that Larks linked, the that statement seems clearly false (though it might still be true that for some reason it is not as clear that greater immigration inflow is necessarily correlated with greater crime, since it might lower crime in other ways, though my best guess is that claim is being chosen as a result of a garden of forking paths methodology).
They say: "We found no impact on the overall likelihood of Germans to be victimized in a crime". That is, refugees were not any likelier than Germans to commit crimes against Germans.
I said: "In Germany, refugees were not particularly likely to commit crimes against Germans". I have accurately reported their results.
Furthermore, in a post I am working on now, I will discuss why such charts - I look at one simply comparing the % of of a given ethnicity in prison to the % in a population - do not tell you all that much:
"We might overestimate the rate of immigrant crime because:
I’m also fairly certain this isn’t the kind of crime most people worry about when they worry about immigrants and crime.
On the other hand, this graph might underestimate immigrant crime if:
There is a huge difference between 'they were at some times not approved for this specific type of aid" and "work or starve". There is no way that the US in the 1980s would tolerate mass starvation like this - even if the federal government hadn't stepped in, the individual states, churches, charities, families etc. would not have allowed that to occur.
If you read the prior sentence in that article, you will see they are basically assuming the negative selection to be true, and don't engage with my argument that positive selection effects also existed at all:
I don't think the fact that some were eventually deported shows very much. I'm not denying that some of them were criminals - I'm just claiming that there are also significant positive selection effects. Since you're not saying that they were all eventually deported, and I'm not saying that every single migrant was a great person, I don't think the mere fact that some were deported is very strong evidence either way.
No, it is not. You discussed whether refugees were "particularly likely to commit crimes". This is a simple statistic - you take crimes committed and divide by population. It is the statistic shown in the chart I included. As far as I am aware, basically every source agrees that this wave of refugees commit crimes at well above the rates of natives.
In contrast, my understanding is the Huang and Kvasnicka paper you quoted do a series of regressions to try to establish whether the scale of immigration changed the amount of crimes that refugees committed. This is a different question. It could (hypothetically) be the case that refugees were committing crimes at a very high rate, and then this fell in 2015 but was still higher than the native rate - if this was the case then this paper would show the opposite result to what we are discussing.
I am also very skeptical of the paper because the garden of branching paths issue seems so large - they declined to publish simple statistics and opted for much more complicated regressions instead which matched the results they clearly ideologically favoured - but this is beside the point because, even if their paper had no issues, it simply answers a different question.
It's possible I've misunderstood this issue. If that's the case I'd love to see the explanation for the difference between this paper's complex methodology and the simple approaches which overwhelmingly suggest the opposite.
I find the whole discourse around this to be very similar to the housing supply price question. Economists will study if random housing shocks affect price. Like… of course it does. Can building more housing induce demand? Absolutely. But this is a local property.
Imagine you have a lonely house out in the woods in the middle of nowhere. I try to sell it to you for 1 mil and you laugh at me and say no. Now imagine I told you that house was in the middle of a city the density and size of New York. All the sudden this looks like a steal.
People like density and total city size. Of course we all have unique density wtp curves, but probably almost all of us can agree that we want to live near like 50 people.
In cities that have a fixed area, adding supply increases density (and always increases total city size). So we don’t get to travel in the 2-d land of supply and price but rather are forced along a specific curve on the surface of this multi dimensional surface. I think the way these economic studies are structured, they inherently miss the forrest for the trees. Each cities multi dimensional surface probably looks sufficiently different and they are on a different enough part of it that I don’t know how much we can really glean (and this isn’t even getting into the imperfections of the studies themselves).
Coming back to the boat lift, we need to know a few things.
If you were to look at the graph of all human output in x city, are we on average in economics or diseconomies of scale?
Which industries/types of labor are in economies or diseconomies of scale?
What is the distribution of the industries/types of labor of the migrants?
How does global demand shift by moving a person from their old city to their new city?
How does the demand for the basket of industries in x city change by moving someone from their old city to their new one? Which industries lose demand? Which gain demand?
What is the labor market share of the companies in the city (monopsonies gonna monopsony) ?
etc.
My point being the surface that describes Miami might be quite different than the surface that describes Dayton, Tennessee. Not only that but I don’t have a strong reason to believe that taking a local chunk of the surface describing wages in Miami would be highly representative of the entire surface, at least to the extent that a 10% increase or decrease in wages locally would be construed as “bumpy”. And the vector we append to our current location on the surface is quite different from one migration event to the next.
This is all one long drawn out way to say that these studies are underpowered, and I don’t update much on them. I say this as someone who is politically very pro immigration. The Mariel boat lift is a fascinating historical event though.
“. But most likely, immigrants do not drive down the wages of native workers.”
This is a broad statement.
Imagine a city that just farms tulips, but does not itself consume tulips. No other output is produced. All consumption goods are shipped in from Amazon. Imagine constant returns to scale of tulip production and at least some elasticity for tulip demand. It’s inevitable tulip farmer wages will go down if we airdrop an additional tulip farmer.
Maybe what is inevitable is the additional person will start producing something else.
In a vague long term sense I’m inclined to agree. However it’s not inevitable, especially locally and in the short run. If tulip farming is still in expectation the best wages the migrant will make what incentive do they have to produce something else?