| Country | Migrants (%) | Net migration | Remittances (% GDP) |
|---|---|---|---|
| United Arab Emirates | 76.0 | 92,541 | NA |
| Germany | 18.0 | 203,468 | 0.5 |
| United States | 14.9 | 329,769 | 0.0 |
| Mexico | 1.1 | -147,456 | 3.9 |
Lecture 3: People on the Move
Monday’s hit American towns did not empty out. Mexico’s exposed regions were different — people moved.
Today: why they leave, where they go, and what follows them back.
Surveys in rich countries find people overestimate the share of migrants around them, usually by more than a factor of two.
Asked how many people in the United States were immigrants, respondents said 36%. The true figure was about 10%.
Alesina, Miano & Stantcheva (2023), six-country survey. Their benchmark counts legal immigrants; the foreign-born share on the next map is wider, at 15%. On either definition the guess is more than double the truth.
The interesting fact is not the size. It is the distribution.
| Term | Who it counts | Mexico, 2020 |
|---|---|---|
| Immigrants | arrivals — counted where they now live | 1.3 million, or 1% of people in Mexico |
| Emigrants | departures — counted by where they were born | 11.5 million, or 9% of Mexico’s population |
| Net migration | arrivals minus departures | about −150,000 a year |
Same country, same year: the second number is nine times the first. A single “migration” figure cannot stand in for both.
Figure 1
The extremes are small and rich: Qatar 78%, the UAE 76%, Kuwait 69%. The United States is 15%. Mexico is 1%.
| Country | Migrants (%) | Net migration | Remittances (% GDP) |
|---|---|---|---|
| United Arab Emirates | 76.0 | 92,541 | NA |
| Germany | 18.0 | 203,468 | 0.5 |
| United States | 14.9 | 329,769 | 0.0 |
| Mexico | 1.1 | -147,456 | 3.9 |
Only 1% of people in Mexico were born abroad. But net migration is negative and remittances are 4% of GDP.
Figure 2
To ask who leaves, we have to count people by where they came from, not by where they ended up.
To see the other half, we first need to ask why people leave.
The same worker, doing the same job, earns several times more in a rich country than in a poor one.
Clemens (2011) — today’s reading.
Clemens (2011) calls the unrealised gains from this gap “trillion-dollar bills on the sidewalk.”
If money were all that mattered, far more people would move than actually do.
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flowchart LR
A["Wage gap<br/>abroad"] --> D{"Decide"}
B["Cost of<br/>travel"] --> D
C["Visas and<br/>borders"] --> D
E["Someone<br/>already there"] --> D
D --> F["Migration"]
If that is right, emigration should be low at the bottom of the income scale, higher in the middle, and low again at the top. We can check it.
Figure 4
| GDP per capita | Countries | Median % living abroad |
|---|---|---|
| under $2,000 | 44 | 3.9 |
| $2,000–5,000 | 40 | 5.7 |
| $5,000–15,000 | 37 | 7.4 |
| $15,000–40,000 | 25 | 5.8 |
| over $40,000 | 21 | 3.5 |
The poorest band and the richest band send out about the same modest share. The middle sends out roughly twice as much.
Munshi (2003) shows this for Mexican migrants: those with larger established networks in the United States were more likely to be employed on arrival.
One village. The same job in the United States pays any of them 250,000 pesos a year. Getting there costs 100,000 pesos, all of it paid before you leave — and in this village that is the only way north.
| Household | Earns at home | Can put up now |
|---|---|---|
| Ana | 40,000 | 10,000 saved |
| Beto | 55,000 | 60,000 — four years of saving |
| Carmen | 45,000 | 20,000, and a sister in Houston who will send whatever is missing |
| Diego | 400,000 | 150,000; owns the village shop |
A household leaves if it can cover the whole cost before departure, and would earn more abroad than at home.
1. Who leaves? 2. A new road and a cheaper bus halve the cost, to 50,000. Whose answer changes?
Five minutes, in pairs.
| Household | Leaves? | |
|---|---|---|
| Ana | no | 10,000 against 100,000 — and still no at 50,000 |
| Beto | not yet | saved for four years and is 40,000 short |
| Carmen | yes | poorer than Beto, goes anyway — the sister is the finance |
| Diego | no | the only one who could pay cash, the only one with no gap to close |
Q2: Beto’s answer, and only Beto’s. He earns 55,000 — barely more than Ana. The road reaches the household just above the one it cannot help.
Both ends of the scale stay home, and cheaper travel does not reach the bottom. Migration comes from the middle.
Channel 4 News, Riding ‘The Death Train’ to America’s border (2018), reporter Guillermo Galdos. Excerpt shown for teaching.
We have just concluded that Ana stays: the trip costs more than she has, at either price.
Dunia’s family has almost nothing — and they are already a thousand miles into the journey.
1. Does the video contradict the exercise?
2. If you cannot pay in money, what do you pay in instead?
Three minutes, in pairs.
| In the exercise | In the video |
|---|---|
| People leave for higher wages | Dunia’s family leaves because staying is dangerous |
| One route, one price, paid in cash | Several routes, paid in cash, time or risk |
| Cannot pay → stays | Cannot pay → takes the cheaper, deadlier route |
The constraint does not only decide whether people move. It decides how.
This does not overturn the chart. Poorer countries still send a smaller share of their people, and a tendency across 167 countries was never a claim about every family. What it overturns is the idea that “cannot afford it” means “stays at home”.
Everyone who leaves is still connected to the place they left. That connection has a price, and it is measurable.
Figure 5
Mexico is pale on the first map and clearly visible on the second.
The most dependent economies are small ones: Kyrgyzstan 32% of GDP, Tajikistan 27%, Nepal 24%.
Figure 6
Yang (2011) reviews the evidence: remittances raise consumption and schooling, and cushion shocks.
The insurance only runs one way. When it is the migrant who loses work, or the host economy that turns down, remittances can fall exactly when they are most needed.
Remember who leaves: rarely the poorest. Leaving costs money.
DEBATE: Make the journey cheap and safe, and more people will go. Is that a failure?
FOR: Sending countries lose working-age people they paid to raise and educate.
AGAINST: Those who leave are far better off, and what they send home dwarfs all foreign aid.
You now have both halves of the ledger: what the sending country loses, and the 3.7% of Mexico’s economy that comes back.
Which leaves the question everyone actually argues about.
Do migrants lower wages for workers already there?
The theory is simple: more workers, same jobs, lower pay.
Testing it is hard, because migrants choose where to go — they move to places already doing well.
“More workers, same jobs” assumes the jobs stay the same. Three reasons they do not:
Cuban refugees arriving in Florida during the Mariel boatlift, 1980. Source: Wikimedia Commons, public domain.
So the argument is not about what happened in Miami. It is about which workers you count.
Borjas’s group is a few dozen men a year in the survey. The share of Black workers in that small sample rose sharply after 1980, and Clemens and Hunt show that alone can produce the drop.
One event, two designs:
| Card (1990) | Borjas (2017) | |
|---|---|---|
| Whose wages | whites, Blacks, non-Cuban Hispanics and Cubans, split by income quartile | non-Hispanic men, 25–59, no high-school diploma |
| Compared with | Atlanta, Houston, Los Angeles and Tampa, averaged | several alternative control groups |
| How many people | the city’s workforce | a few dozen men a year |
| Answer | no measurable effect | a large fall |
Neither is cheating. The design choices are the finding — which is why Peri & Yasenov and Clemens & Hunt could re-run the same data and recover Card’s answer.
125,000 people arrive in Miami in four months, and wages change. Did they cause it? You need a second city — one that shows what Miami would have done anyway.
1. Which city would you use? What goes wrong with it?
| Atlanta | Los Angeles | Tampa |
|---|---|---|
| no big arrivals; economy growing fast in the 1980s | a gateway city — new arrivals every year | same state; smaller, older, more retirees |
2. Whose wages would you look at — and what would that choice let you say? all workers · no high-school diploma · construction workers · Cubans already in Miami
Five minutes, in pairs.
The city. Card used four averaged together — Atlanta, Houston, Los Angeles, Tampa — so no single city’s quirks decide the answer.
The workers. There is no single right answer here — each choice answers a different question.
| Whose wages | What it can tell you | What it costs you |
|---|---|---|
| All workers | the average effect on the city | a real effect on a small group disappears into the average |
| No high-school diploma | the effect where competition should bite hardest | the sample shrinks fast — the Borjas problem |
| Cubans in Miami | the effect on the closest substitutes | also the group most tied into the arrivals’ own networks |
| Construction | the effect in one exposed sector | moves with Miami’s building cycle, not just with arrivals |
Card reported several of these, including Cubans and workers by income quartile.
A good comparison is not a city that looks like Miami. It is one that was moving like Miami until 1980.
And matching trends before 1980 is the strongest check available, not a proof. It cannot rule out that something else hit Miami and the control cities differently in exactly those years.
A country can be transformed by migration without a single migrant arriving.
Alesina, A., Miano, A., & Stantcheva, S. (2023). Immigration and redistribution. The Review of Economic Studies, 90(1), 1–39.
Borjas, G. J. (2017). The wage impact of the Marielitos: A reappraisal. Industrial and Labor Relations Review, 70(5), 1077–1110.
Card, D. (1990). The impact of the Mariel boatlift on the Miami labor market. Industrial and Labor Relations Review, 43(2), 245–257.
Clemens, M. A. (2011). Economics and emigration: Trillion-dollar bills on the sidewalk? Journal of Economic Perspectives, 25(3), 83–106.
Clemens, M. A., & Hunt, J. (2019). The labor market effects of refugee waves: Reconciling conflicting results. ILR Review, 72(4), 818–857.
Clemens, M. A. (2014). Does development reduce migration? In R. E. B. Lucas (Ed.), International Handbook on Migration and Economic Development (pp. 152–185). Edward Elgar.
Dao, T. H., Docquier, F., Parsons, C., & Peri, G. (2018). Migration and development: Dissecting the anatomy of the mobility transition. Journal of Development Economics, 132, 88–101.
Docquier, F., & Rapoport, H. (2012). Globalization, brain drain, and development. Journal of Economic Literature, 50(3), 681–730.
National Academies of Sciences, Engineering, and Medicine. (2017). The Economic and Fiscal Consequences of Immigration. Washington, DC: National Academies Press.
Munshi, K. (2003). Networks in the modern economy: Mexican migrants in the U.S. labor market. Quarterly Journal of Economics, 118(2), 549–599.
Peri, G., & Yasenov, V. (2019). The labor market effects of a refugee wave: Synthetic control method meets the Mariel boatlift. Journal of Human Resources, 54(2), 267–309.
Parreñas, R. S. (2005). Children of Global Migration: Transnational Families and Gendered Woes. Stanford University Press.
United Nations, Department of Economic and Social Affairs. (2021). International Migrant Stock 2020. New York: United Nations.
United Nations, Department of Economic and Social Affairs. (2025). International Migrant Stock 2024. New York: United Nations.
World Bank. (2024). World Development Indicators. Washington, DC: World Bank.
Yang, D. (2011). Migrant remittances. Journal of Economic Perspectives, 25(3), 129–152.
Popescu (TEC) Diversity in a Globalized World — Lecture 3: Migration