In April 1980, Fidel Castro announced that any Cuban who wanted to leave could do so from the port of Mariel. Roughly 125,000 people took him up on it, most of them landing in Miami between May and September of that year. About half stayed, enough to expand the city’s labor force by about 45,000 workers, or 7%, in a matter of months, and to swell its pool of workers without a high school diploma by close to 20%. It was what economists call a natural experiment, and a methodological gift: a sudden, exogenous shock to a local labor market, uncontrolled by policy, large enough to observe and historically bounded enough to study.
David Card studied it. He found no meaningful wage effect on Miami’s native workers: the city absorbed the arrivals without the labor market moving in any statistically detectable direction. His 1990 paper made the Mariel boatlift one of the most cited natural experiments in immigration economics, and it came to be cited as a demonstration of the labor market’s capacity to absorb large inflows without crushing wages.
In 2017, George Borjas reanalyzed the same event, drawing on the same government survey, and found a wage drop of 10 to 30% for Miami’s high school dropouts. The same boatlift, city, years and survey had produced opposite conclusions.
The temptation is to conclude that even the experts can’t agree, that the science is contested and we are all just choosing whom to believe.
Resist it. The appearance of unknowability in immigration economics has been useful to everyone who has found in the Card-Borjas disagreement a license to dismiss whatever findings they dislike. The researchers themselves are running a real methodological dispute about something specific and traceable. The Mariel dispute concerns a narrow question: which workers should count as substitutable for newly arrived low-skill immigrants, over what sample and time window to measure it, and whether the small survey samples involved can measure it reliably at all. That question is unresolved, and it matters for one sub-debate about wage effects on a specific worker population.
It does not reach the research on crime, on innovation or on fiscal effects across generations. Those parts of the evidence base are substantially more settled than the public debate suggests, and the Mariel controversy has left them more or less untouched.
Crime: where the evidence is clearest and the discourse most wrong
Immigrants, particularly low-skill and undocumented immigrants, are younger, more often male and less educated than host-country native populations. Age, sex and education are three of the most robust predictors of criminal offending that criminology has established; young men without high school diplomas commit crimes at substantially higher rates than middle-aged women with college degrees. Ask a criminologist to forecast the arrest rate of a group with the demographic profile of the average low-skill immigrant, and the forecast would come out substantially above the native-born average.
In the United States, the empirical finding is that this forecast is wrong. The United States has the best individual-level records, and they show that immigrants are arrested and convicted at lower rates than the native-born.
Olivier Marie and Paolo Pinotti reviewed the international evidence systematically, synthesizing studies from Europe, the United States and elsewhere that use several methodological approaches. Their conclusion: even though immigrants are overrepresented among offenders in many host countries, especially in Europe, immigration does not significantly raise local crime rates. That finding recurs across an extensive cross-national literature.
The gap between forecast and finding closes when you look at the mechanism. Economic conditions such as wages, unemployment and poverty are among the strongest drivers of crime at the population level. Immigrants do not settle at random: they move toward booming places for jobs and toward cheaper, often poorer neighborhoods for housing. A research design that correlates immigrant share with local crime rates without accounting for those conditions can mistake a poverty effect for an immigration effect, or hide a real effect behind a local boom. Controlling for local economic conditions removes much of that bias, though not all of it; the stronger studies go further, predicting where newcomers settle from where earlier waves of their compatriots settled decades before, to separate cause from coincidence.
And then there is self-selection. Migration is physically demanding, financially costly, and socially disruptive. The population that attempts it is filtered before it arrives: people with little drive or appetite for risk are systematically less likely to attempt and complete a migration than people with plenty of both. For undocumented immigrants specifically, the filtering is even more severe, and it operates through a mechanism unavailable to native-born citizens: criminal conviction means deportation. A native-born worker who gets convicted of a felony serves a sentence and returns to the labor market. An undocumented immigrant faces that sentence plus removal from the country, which makes a conviction far costlier for them than for a citizen.
The data fit that account. Texas checks the immigration status of all arrestees, which makes it one of the few states where you can separate undocumented immigrants from legal immigrants and native-born citizens in arrest data.
Michael Light, Jingying He and Jason Robey worked through the state’s arrest records from 2012 to 2018. They found that native-born US citizens are more than twice as likely as undocumented immigrants to be arrested for violent crimes, 2.5 times as likely for drug crimes, and more than four times as likely for property crimes. The pattern holds across felony categories. Legal immigrants fall between the two groups, with lower crime rates than native-born Americans and higher ones than undocumented immigrants. That ordering is what the selection argument predicts, and deportation risk, which weighs less on legal immigrants, is one proposed reason for it. It is not the whole story: studies abroad find that gaining legal status reduces immigrants’ offending.
Alex Nowrasteh of the Cato Institute analyzed conviction and arrest records from the same Texas system for 2013 to 2022. His work is a policy analysis from an advocacy-adjacent research institute rather than a peer-reviewed journal article. He puts the homicide conviction rate at 2.2 per 100,000 for undocumented immigrants, 1.2 for legal immigrants and 3.0 for the native-born. Two independent analyses of Texas’s administrative records, a peer-reviewed study of arrests and a policy analysis of homicide convictions, point the same direction: both immigrant groups offend less than the native-born. (On homicide convictions, legal immigrants come out lowest of all, a reminder that the ordering between the two immigrant groups shifts by crime type.) The convergence carries weight because the two studies measure different things and still arrive at the same place.
The finding is a population-level statistical result. Immigrants commit crimes too; as a group, they do so at a lower rate than the native-born average.
The "null by design" problem
There is a structural problem with the most common research design in the immigration-crime literature, and it changes which studies deserve the most weight. Sascha Riaz has analyzed the workhorse empirical approach: aggregate criminal offenses to a geographic unit, regress local crime rates on local immigrant share, interpret the coefficient. The problem is built into the arithmetic. Immigrants are typically a small fraction of the population in any given area, 10% or 15%, sometimes 20% in high-immigration zones. If immigrants commit crimes at a rate meaningfully different from native-born residents, that difference is diluted before it enters the regression.
Riaz ran Monte Carlo simulations calibrated to real-world immigration and crime data. These designs achieve adequate statistical power, enough to reliably detect a true effect, only when the crime differential is implausibly large. Moderate differences, the kind that would matter for policy, fall below the detection threshold.
Area-level studies are built to ask whether total local crime rises when immigrants arrive, and their findings are predominantly null: no statistically detectable increase. But a null from such a design says little about whether immigrants themselves offend more or less than natives, because Riaz shows these designs can only rule out extreme gaps. That question has to be settled with individual-level records that identify each offender's status, which is why the Texas data carry so much weight. Those records point clearly in one direction: undocumented and legal immigrants alike are arrested and convicted at lower rates than the native-born. Which immigrant group comes out lowest depends on the measure: undocumented immigrants on felony arrests, legal immigrants on convictions.Innovation: the evidence the debate ignores
The same self-selection mechanism that explains the crime finding, with migrants filtered for agency, ambition and risk tolerance, operates in the innovation literature too, but there is a second layer. The US immigration system imposes its own filters on who enters the innovating workforce. The H-1B visa, the O-1 for extraordinary ability, the EB-2 national interest waiver and the F-1 student visa that feeds into OPT employment all select for technical credentials and demonstrable achievement, and the O-1 and EB-2 demand explicit evidence of exceptional contribution to a field. Elite US universities add another filter, drawing internationally competitive students who then often enter the US labor force through their institutional networks.
Self-selection describes who attempts migration. Institutional filtering describes who the US admission system accepts from that pool. Both filters are running simultaneously and both are visible in the patent and startup data.
Shai Bernstein, Rebecca Diamond and their colleagues analyzed US patent records from 1990 to 2016. Immigrants were 16% of the US inventor population but generated 23% of all US patents filed in that period, and 25% when patents are weighted by the stock market’s reaction to their grant. Count the boost immigrant inventors give their native-born collaborators as well, and the study’s model credits immigrants with 32% of aggregate US innovation, more than half of it through those spillovers. That is more than twice their share of the US population over the period.
The collaborator finding is the sharpest result in the study. When an immigrant co-inventor died, the productivity of their co-inventors fell by 17%; when a native-born co-inventor died, it fell by 9%. Immigrants add more than their own patents to the total. They are load-bearing within knowledge networks, linking research traditions, technical approaches and collaborative relationships that native-born inventors couldn’t access independently.
In the fast-growing fields of computers and communications, drugs and medical technology, electronics, and chemicals, immigrants account for about a quarter of all US patents, against roughly 15% in traditional fields such as metalworking, transportation and engines. The entrepreneurship data tell the same story. Immigrants account for roughly a quarter of US entrepreneurs: about 24% of new business owners in 2014–2019 in Census business surveys, and close to 29% of new-firm founders in 2020 by a second Census measure. Among leading venture-backed and AI-related firms, the immigrant share of founders can top 40%.
Research by Zhao Jin, Amir Kermani and Timothy McQuade, not yet peer-reviewed, analyzed a large sample of US startups. Companies with mixed founding teams employ 20% more people after three years than native-only ventures; a second analytical method puts mixed-founder startups 44% larger and 35 percentage points more likely to secure funding. The direction is consistent with the patent findings on immigrant-native collaboration.
Immigrants filing patents are also 10% more likely to cite international sources and twice as likely to collaborate with foreign inventors. Foreign researchers, in turn, cite US-based immigrant patents 10% more often than native-authored ones.
This describes a specific immigrant population: the high-skill, institutionally filtered subset that arrived through US visa channels over this period. Different admission criteria would produce a different innovating population. The finding is large and well documented, and it is contingent on the selection regime that produced it.
Fiscal balance: who pays, and when
The crime and innovation literatures say something fairly clear. The fiscal literature says something more complicated, for reasons built into how public budgets are divided.
In 2016 the National Academies of Sciences produced the most comprehensive review of fiscal impacts. Its summary finding is not the one that appears in either side’s public-facing arguments.
First-generation immigrants cost governments more than the native-born do, mainly at the state and local level and mainly because of the cost of educating their children. K-12 education is expensive, immigrant families tend to be larger than native families, and the fiscal burden lands on school districts and state governments. A governor or state budget director who describes first-generation immigration as a fiscal cost to their government is accurately describing their budget reality.
The second generation, those children grown into working adults, is “among the strongest economic and fiscal contributors” in the US economy, as the NAS put it. They pay more taxes than either their parents or the native-born average. Across two generations, the lifecycle picture is substantially positive.
The education gradient within the first generation is as large as any finding in the literature and almost never appears in public debate on either side. In its scenario built on the Congressional Budget Office’s long-term budget projections, with national defense and other public goods not charged to new arrivals, the NAS estimates that an immigrant with a bachelor’s degree who arrives at age 25 generates a net fiscal contribution of about $821,000 over a 75-year horizon, counting all levels of government and the immigrant’s descendants (present value, 2012 dollars). A high-school dropout arriving at the same age is a net cost of about $186,000, a gap of roughly a million dollars. Charge each newcomer an average share of those public goods instead and the graduate’s contribution shrinks while the dropout’s net cost grows, but the gap between them stays the same. Age at arrival matters too. In the first scenario, the estimate for an immigrant with a high school diploma falls from about +$239,000 for arrival before age 25 to about −$42,000 for arrival at 25–64 and −$164,000 for arrival at 65 or older, because later arrivals contribute fewer working-age years before drawing on retirement-related programs.
European countries show a consistent pattern: immigrants admitted through labor channels, meaning employment-based admission rather than family reunification or asylum, tend to be net fiscal contributors. The finding is sensitive to how each country defines “labor migrant,” but the direction across countries is stable.
The time-horizon problem is at the root of most public confusion about immigration’s fiscal effects. Static analyses, which look at immigrant households in a given year, consistently show costs: school-age children, lower initial earnings, social services concentrated in early settlement years. Dynamic analyses over multi-generational horizons generally come out positive, decisively so for educated immigrants, and for the average newcomer once national defense and other costs that do not grow with population are not charged to new arrivals. The two kinds of analysis answer different policy questions. A state budget office asking about next year’s education expenditure correctly gets a negative answer, and a Social Security actuary asking about long-run pension solvency correctly gets a positive one; citing either while suppressing the other is advocacy.
The federal/state accounting problem
The fiscal arithmetic of immigration runs through an accounting architecture that almost guarantees confusion. State and local governments bear the main upfront cost of educating immigrant children, the largest single line item in the fiscal ledger for first-generation immigration. The federal government pays for relatively little of that schooling, because K-12 education is overwhelmingly a state and local function.
The long-run fiscal payoff from that education flows mainly to the federal government: decades of income and payroll taxes from productive adults, including Social Security and Medicare contributions. It does not flow back to the state and local governments that paid the educational bill. Pia Orrenius of the Dallas Fed lays out this structural mismatch: immigration's fiscal impact is typically negative at the state and local level but positive at the federal level, with state and local governments bearing the bulk of education costs while federal revenues capture most of the long-run tax contribution.
A governor who calls immigration a fiscal drain may be accurately describing their jurisdiction's experience while drawing a false conclusion about the aggregate. The division of fiscal responsibilities between levels of government puts costs and benefits in different ledgers, so a state's deficit on immigration says little about the national balance.Wages: small on average, concentrated at the bottom
The wage evidence requires something harder than fiscal accounting: naming concentrated losers while the aggregate finding looks benign. Wages are where engaging with the evidence costs most politically, because it means naming a specific harm that drops out easily when the literature is boiled down to a slogan.
The meta-analytic picture first. Simonetta Longhi, Peter Nijkamp and Jacques Poot pooled hundreds of wage estimates from earlier studies. The average wage elasticity across this body of evidence is −0.1: a 10-percentage-point increase in the immigrant share of the workforce is associated with a decrease of about 1% in native wages. The employment elasticity is even smaller, at −0.02. These are small numbers. A 10-point increase in immigrant share is an enormous supply shock, far larger than what most economies have experienced in any given decade, and the wage response is barely visible.
The National Academies summarized the report’s consensus this way: “When measured over a period of 10 years or more, the impact of immigration on the wages of native-born workers overall is very small. To the extent that negative impacts occur, they are most likely to be found for prior immigrants or native-born workers who have not completed high school — who are often the closest substitutes for immigrant workers with low skills.”
Gianmarco Ottaviano and Giovanni Peri, using US Census data on immigration from 1990 to 2006, found small negative short-run wage effects on natives without a high school degree (around −0.7%) and on average native wages (−0.4%), with small positive long-run effects for both (+0.3% and +0.6%) once capital adjusts. Peri’s later survey reached the same verdict: the overall wage effects of immigration have been small. The mechanism is task specialization. Even within the same nominal skill category, immigrant and native workers tend to occupy different roles, so they complement each other rather than act as pure substitutes. An immigrant and a native construction worker on the same site may be doing tasks different enough (physical labor versus supervisory coordination) that they are less substitutable than their shared occupational label suggests.
Borjas’s estimates are substantially larger. A 10% immigration-induced increase in the supply of workers with a given set of skills, in his framework, reduces the weekly wages of native workers with those skills by approximately 3 to 4%. The methodology treats the US labor market as a single integrated national system segmented by education and work experience, with workers at the same education level competing nationwide regardless of geography. The case against this framework is that labor markets are local, workers don’t move freely across the country in response to immigration-induced wage pressure, and the approach bundles together workers who may never compete with each other.
The Mariel boatlift methodology dispute
Card's 1990 paper found no wage effect following the boatlift. Borjas's 2017 paper found a 10 to 30% wage drop for Miami's high school dropouts from the same event and the same survey data. The divergence traces mainly to one decision: which workers to include in the sample.
Borjas restricted his analysis to non-Hispanic men aged 25 to 59, the population he argued was most directly competing with the arriving low-skill Cuban workers. Card's original 1990 study (workers aged 16 to 61) and Peri and Yasenov's 2015 reanalysis (non-Cuban high school dropouts aged 19 to 65) used broader samples that included women and non-Cuban Hispanics. Neither restriction is arbitrary. Each reflects a theoretical assumption about labor market structure, specifically about which workers are substitutable for newly arrived immigrants with low skills.
Borjas's critics raised a specific empirical objection. His restricted sample showed an anomalous increase in the proportion of Black workers in Miami following the boatlift, something Cuban arrivals could not have caused, since his sample excluded Hispanics. Michael Clemens and Jennifer Hunt traced it to two things happening at once: the 1980 arrival of thousands of low-wage Haitian immigrants in Miami, and a Census Bureau push to improve survey coverage of low-income Black men. Both tilted Borjas's small sample toward lower-paid workers, producing a wage drop his design couldn't distinguish from the boatlift effect. Borjas disputes that reading.
The disagreement turns on which workers count as substitutes for newly arrived low-skill immigrants and on whether the small samples behind the narrower definition pick up a real boatlift effect or measurement noise and shifts in who was surveyed. Both questions are unresolved, and each side's choices can be documented and checked.What both Borjas and the meta-analytic consensus agree on, even as they disagree about size, is the distributional shape of whatever wage effect exists: it falls on prior immigrants and the least-educated native workers. The NAS places it there, and Ottaviano and Peri, working by a different method, place it in the same groups. Even Borjas is making a claim about a specific subgroup rather than workers in general.
Immigration generates an aggregate surplus. Output increases, and prices fall for goods and services produced by immigrant labor, such as construction, agriculture, food service and care work. The surplus is real but unevenly distributed. It flows to employers through lower labor costs, to consumers through lower prices for goods intensive in immigrant labor, and to high-skill native workers whose work complements rather than competes with low-skill immigrant labor. A lawyer in a city with a large immigrant service workforce benefits from cheaper restaurant meals and lower construction costs. The construction worker who used to have less competition before those immigrants arrived does not.
That competitive pressure, even at the modest magnitudes the meta-analysis suggests, lands on the least politically organized people in any rich democracy: prior immigrants facing labor competition from newer arrivals, and native-born workers without high school diplomas whose position was already precarious. The immigration dividend is invisible to most households — lower prices spread thinly across hundreds of millions of people, showing up as marginally cheaper meals and slightly lower construction quotes. The competitive cost to a specific low-wage worker in a specific market is concentrated and legible. It shows up as a lost shift, a stagnant hourly rate, a foreman job that didn’t materialize.
This asymmetry of diffuse gains and concentrated losses is the standard political economy explanation for why policies that raise aggregate welfare produce intense opposition. Seen this way, the intensity of the immigration debate among working-class communities is the rational response of people bearing concentrated costs that aggregate statistics erase.
Now look at what happens when that literature is summarized for the public. The headline finding, a small or negligible effect on native wages overall, is accurate. But the National Academies did not stop there. The very next sentence of their own summary of the report reads: “To the extent that negative impacts occur, they are most likely to be found for prior immigrants or native-born workers who have not completed high school.” The caveat sits in the same sentence block as the headline, not in a different chapter or a technical appendix. Careful advocacy summaries keep both halves: the American Immigration Council’s write-up of the report noted that any detectable negative effects were small and fell mainly on recent immigrants and high school dropouts. The slogan version, “immigration doesn’t hurt wages,” keeps only the first.
Whatever the intent, the omission is easy to check: read any summary that invokes NAS 2016 on wages and see whether the second sentence made the trip.
Borjas’s core concern, that specific workers bear real wage costs from immigration, is separable from his contested methodology. Even accepting the smaller meta-analytic elasticities rather than Borjas’s larger estimates, immigration produces real distributional effects. The statement “aggregate wages are barely affected” does not refute the distributional concern. It answers a question about what happens to average wages, which is not the question the workers at the bottom of the distribution are asking.
Restrictionists cite crime links that administrative data consistently fail to support, treat the Borjas-Card methodological dispute as license to dismiss findings they dislike across the entire literature, and deploy the uncertainty of one contested sub-debate to impute uncertainty to every other corner of the evidence base. The Mariel dispute is real, but it does not reach the crime, fiscal or innovation literatures, and stretching it that far requires ignoring what the dispute is about.
The pro-immigration case, boiled down to “immigration doesn’t hurt wages,” presents the aggregate wage finding, a small, nearly neutral effect on native workers overall, and stops. It cites NAS 2016 as authoritative while dropping what NAS 2016 says about distribution: that whatever wage impacts exist fall on prior immigrants and native workers without high school diplomas. The distributional finding sits in the very documents being invoked, and careful summaries carry it, while the slogan presents the aggregate and omits the shape.
The two patterns are worth distinguishing. The first ignores entire literatures; the second misrepresents the scope of one it explicitly claims to represent in full. They serve different political interests.
The finding most consistent with the restrictionist concern is that immigration creates real distributional costs for specific, identifiable workers. The findings most consistent with the pro-immigration case are that immigration does not measurably raise local crime, aggregate wages are barely affected, innovation per immigrant is well above the national average, and second-generation immigrants are among the strongest fiscal contributors in the economy. Both sets come from the same literature and hold at the same time.
The Mariel boatlift opened this account as an apparent paradox, in which the same survey yielded opposite conclusions. Borjas and Card are not looking at incompatible realities. Borjas’s narrow sample of non-Hispanic men aged 25 to 59 without high school diplomas registered a wage drop after the boatlift, though whether the boatlift caused it is still contested; Card’s broader population showed none. The wider literature points to a single underlying shape: whatever wage pressure low-skill immigration creates is concentrated on the workers who compete most directly with the new arrivals, a specific subset at the bottom of the education distribution rather than workers in general.
The political debate has already made its choice about which workers to count. Restrictionists use that concentrated effect to make claims about immigration’s impact on all workers, which the literature doesn’t support. The slogan version of the pro-immigration case uses the aggregate nullity to imply no one is harmed, which the distributional literature doesn’t support.
Whatever wage cost exists falls on the workers the evidence points to, prior immigrants and native-born workers without a high school diploma, and for them it arrives as a lost shift or a wage that stops rising.
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Key Sources and References
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Michael T. Light, Jingying He, and Jason P. Robey, “Comparing Crime Rates Between Undocumented Immigrants, Legal Immigrants, and Native-Born US Citizens in Texas,” Proceedings of the National Academy of Sciences, Vol. 117, No. 51, December 2020, pp. 32340–32347, https://doi.org/10.1073/pnas.2014704117 · https://pmc.ncbi.nlm.nih.gov/articles/PMC7768760/
Alex Nowrasteh, “Illegal Immigrant Murderers in Texas, 2013–2022: Illegal Immigrant and Legal Immigrant Conviction and Arrest Rates for Homicide and Other Crimes,” Cato Policy Analysis No. 977, Cato Institute, June 26, 2024, https://www.cato.org/policy-analysis/illegal-immigrant-murderers-texas-2013-2022
Sascha Riaz, “Null by Design: Statistical Dilution in Immigration-Crime Research,” British Journal of Political Science, Vol. 56, e25, published online 20 April 2026, https://www.cambridge.org/core/journals/british-journal-of-political-science/article/null-by-design-statistical-dilution-in-immigrationcrime-research/29595CF23A516E1993E0F71EF0094910
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Michael A. Clemens and Jennifer Hunt, “The Labor Market Effects of Refugee Waves: Reconciling Conflicting Results,” NBER Working Paper 23433, 2017 (ILR Review, 2019), https://www.nber.org/papers/w23433
George J. Borjas, “Still More on Mariel: The Role of Race,” NBER Working Paper 23504, 2017, https://www.nber.org/papers/w23504
National Academies of Sciences, Engineering, and Medicine, “New Report Assesses the Economic and Fiscal Consequences of Immigration” (news release), September 21, 2016, https://www.nationalacademies.org/news/2016/09/new-report-assesses-the-economic-and-fiscal-consequences-of-immigration
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OECD, International Migration Outlook 2013, ch. 3 “The fiscal impact of immigration in OECD countries,” OECD Publishing, 2013, https://doi.org/10.1787/migr_outlook-2013-en
