The Great Mexican Emigration

Gordon H. Hanson
University of California, San Diego and NBER
Craig McIntosh
University of California, San Diego
August 2008

Abstract. In this paper, we examine net emigration from Mexico over the period 1960 to2000. The data are consistent with labor-supply shocks having made a substantial
contribution to Mexican emigration, accounting for two fifths of Mexican labor flows to
the U.S. over the last two decades of the 20th century. Net emigration rates by Mexican
state birth-year cohort display a strong positive correlation with the initial size of the
Mexican cohort, relative to the corresponding U.S. cohort. In states with long histories of
emigration, the effects of cohort size on emigration are relatively strong, consistent withthe existence pre-existing networks.

We thank seminar participants at Columbia University, Princeton University, and UCSD
for valuable advice and Jeffrey Lin for excellent research assistance.

1. Introduction
In the last two and a half decades, migration from Mexico to the U.S. has surged.
As a share of Mexico’s national population, the number of Mexican immigrants living in
the U.S. remained at 1.5% from 1960 to 1970, before rising to 3.3% in 1980, 5.2% in
1990, and 10.2% in 2005. Mexico is by far and away the largest source country for U.S.
immigration, accounting for one third of the current U.S. foreign-born population.
Mexico-to-U.S. labor flows are a major policy issue for both countries. The U.S.
spends large sums on enforcing borders against illegal immigration. In Mexico, theexodus of labor has reduced the population of working-age adults (Hanson, 2006), while
creating a financial windfall in the form of remittances (Woodruff and Zenteno, 2006).
Given the importance of migration for labor markets in North America, it is surprising
there is little academic research on the scale of regional labor flows. Existing literatureprovides scant analysis of why–despite longstanding income differences between Mexicoand the U.S.–labor outflows from Mexico have grown dramatically only recently.
There is work on other aspects of Mexican emigration, including how labor flows
affect U.S. and Mexican wages (Mishra, 2006; Borjas and Katz, 2007; Aydemir andBorjas, 2007), the self-selection of emigrants (Chiquiar and Hanson, 2005; Ibarraran and
Lubotsky, 2007; Fernandez-Huertas, 2006), and the assimilation of immigrants in the
U.S. (Borjas, 1996; Grogger and Trejo, 2002; Smith, 2003; Blau and Kahn, 2007).1 While
there is research on individual migration decisions (Taylor, 1987; Massey and Espinosa,
1997; Orrenius and Zavodny, 2005; McKenzie and Rapoport, 2007), much of this work
uses data from Mexican communities chosen for having high migration rates, making the1

See Hanson (2006) for a review of literature on Mexico-U.S. migration and Massey and Zenteno (1999)
for work on migration dynamics using the Mexican Migration Project data.

1

results difficult to generalize to the country as a whole.
In this paper, we examine net emigration from Mexico from 1960 to 2000. To
measure net labor outflows, we compare the size of birth cohorts in Mexican states
between decennial censuses. By taking state birth cohorts as the unit of analysis, we
ignore how migration varies with schooling, income, or other individual characteristics,
on which previous literature dwells. The advantage of our approach is that we can study
emigration across regions within Mexico over long time periods, during which there havebeen large changes in labor-market conditions in the country relative to the U.S.
One seemingly obvious explanation for labor outflows from Mexico–which todate has received little attention in the literature–is that labor supply in Mexico has
grown relative to the U.S., putting downward pressure on relative wages and making
emigration more attractive.2 Figure 1 shows that the U.S. baby boom matched rapid
population growth in Mexico between 1940 and 1960. Subsequently, Mexican birthcohorts continued to grow for another two decades, while the size of U.S birth cohorts
actually began to fall. Between 1960 and 1980, there was a large shift in the relative sizeof U.S.-Mexican cohorts, from 4:1 to less than 2:1. Given that birth cohorts enter thelabor market with a 15-20 year lag, the labor supply effects should have triggered
emigration from Mexico beginning in the late 1970s, consistent with observed patterns.
The focus of our analysis is to assess the contribution of relative labor supply shocks overthe last four decades to Mexico’s great wave of emigration.
There are clearly other factors besides labor supply that affect Mexican labor
outflows. Since 1980, Mexico has been beset by periodic financial crises. Its per capita

2

There is cross-country evidence on the relationship between demographic structure and internationalmigration. See Hatton and Williamson (2003, 2005).

2

GDP fell sharply in 1983 (after the onset of the Mexican debt crisis) and again in 1995
(after the Mexican peso crisis), leaving the difference in Mexico-U.S. per capita income
in 2005 little changed relative to two-and-a-half decades before (Table 1). Previous workfinds that Mexico-to-U.S. migration increases following real wage declines (Hanson andSpilimbergo, 1999; Orrenius and Zavodny, 2005). U.S. immigration policy and migrant
networks also affect migration. Illegal immigrants appear to account for most new
arrivals from Mexico in the U.S. With the buildup in U.S. border enforcement since
1990, the fees smugglers charge migrants at the border have risen (Gathman, 2004). At
the same time, expanding migrant networks have made moving abroad more attractive(Munshi, 2003; Orrenius and Zavodny, 2005). In the presence of network effects,
migration may be self-reinforcing (Carrington et al., 1996). Our empirical frameworkattempts to control for how these other shocks have affected Mexican emigration.
In section 2, we present data on net labor outflows. In section 3, we outline a
simple dynamic model of emigration, which yields an estimating equation that specifies
the current emigration rate for a cohort in Mexico as a function of initial differences in
Mexico-U.S. labor supply, plus other controls. The model allows for migration networks
and for internal migration within Mexico. In section 4, we present estimation results, inwhich we control for the initial level of development in Mexican states, subsequent
shocks to GDP, migration costs, and other factors.
To preview the findings, the data are consistent with labor-supply shocks having
made a substantial contribution to Mexican emigration to the U.S. Our estimates indicatethat Mexican population growth can account for two fifths of total out-migration for the
20 years prior to 1997. Initial cohort size in Mexico (relative to the U.S.) has a strong3

positive correlation with net emigration rates by Mexican state. The effects of cohort size
are strongest in states with long histories of migration, consistent with network effects.
Looking forward in time, as we do in section 5, recent rapid declines in Mexican fertility
should diminish binational differences in labor-supply growth as a motivation for
emigration from Mexico. The total fertility rate in Mexico was 7 in 1965, which thenplummeted over the next several decades, dropping to 2.5 by 2000, close to the U.S. levelof 2.1 (Tuiran et al, 2002). Holding other factors constant, the dramatic decline in
Mexico’s population growth implies that emigration rates from Mexico should peak withthe 1980 birth cohort and decline for successive birth cohorts, such that those born in2010 would have emigration rates less than half as large as those born in 1980.

2. Data
To calculate labor outflows from Mexico, we use the net-migration method,which takes Mexican state/gender/birth-year cohorts as the unit of analysis, and apply it
to data from Mexico’s population censuses in 1960, 1970, 1990, and 2000.3 We begin byidentifying the base size for a cohort, which is the population the first time a cohort isobserved in the census. For example, we can count the number of men born in the stateof Zacatecas aged 8 who appear in the 1960 Mexican census. By then observing how
many men born in Zacatecas are age 18 in the 1970 census, age 38 in the 1990 census,
and age 48 in the 2000 census, we are able to construct a series of 10-year emigration
rates that are specific to gender, age, state of birth, and year of birth. For birth year i,gender j, and birth state s, the fraction of individuals which has emigrated as of time t is,3

Data are from www.Ipums.umn.edu. The 1980 census was conducted but never made available.

4

(1)

mijst =

base cohort sizeijs − current cohort sizeijst
base cohort sizeijs.

The ten-year time difference in mijst is the decadal emigration rate.4 In the regression
analysis, we exclude cohorts younger than 16, since their emigration is likely due todecisions made by their parents, or older than 50, after which age few individuals
emigrate. These restrictions leave us with 6,081 observations on 10-year net emigration
rates for cohorts born between 1920 and 1984.
The net-migration method has several advantages. At a mechanical level, because
the Mexican census asks both the state of birth and the state of residence, we cancalculate net emigration over the state of birth and avoid the bias in population by state ofresidence that results from internal migration within Mexico.5

A more nuanced

advantage can be seen in the debate over the composition of Mexican migrants to the
U.S. Studies on Mexican immigrants using U.S. data find that emigrants have schoolinglevels close to Mexico’s national mean (e.g., Chiquiar and Hanson, 2005; Orrenius andZavodny, 2005), while some analyses based on Mexican data (which contain information
on which family members have emigrated) find emigrants have below mean schooling(e.g., Ibarraran and Lubotsky, 2007; Fernandez-Hertas, 2007). Either data source issubject to bias, as the U.S. census may undercount lower-skilled recent immigrants, andestimates of migration based on Mexican household data miss higher-skilled households
that have emigrated in their entirety. Martinez and Woodruff (2007) find that the netmigration method generates estimates of total emigration and emigrant schooling
4

Wherever possible the base cohort size is taken from a cohort between the ages of one and ten. Howeverin the case of cohorts born before 1950 or born between 1970 and 1980 we have no census which lets us
measure this quantity, and so we use instead the population at the time the cohort first appears in the data.
5
The U.S. census asks the country but not the state of birth for immigrants, and hence does not allow us toobserve sub-national Mexican variation in labor supply or migration.

5

between those arising from U.S. and Mexican data, suggesting this method may be lesssubject to biases affecting other approaches.6
One concern about the net-migration method is that estimates tend to be noisy,
particularly when constructed from the 1% population samples available for the 1960 and1970 censuses.

Also, older respondents appear to round their age (Martinez andWoodruff, 2006), which could cause us to misestimate age-specific net migration rates.
The following table on cohort sizes and age illustrates this problem in a simple way:

Log base MX cohort size
Subsequent migration rate

Age ends in 0,5

Age doesn't end in
0,5

Test of difference

9.588(0.034)9.632(0.016)0.044(0.038)0.145(0.003)0.114(0.006)**0.032(0.006)
Standard errors in parentheses, ** significant at 1%

There is no significant difference in base size between cohorts whose age ends in 0 or 5
and other cohorts, meaning there is little misreporting in the ages of young children.
However, the subsequent net emigration of cohorts ending in 0 or 5 is less than a quarterthe rate of other cohorts. As respondents age, misreporting may cause them to ‘leave’unrounded cohorts and ‘enter’ rounded cohorts. We address the issue by aggregating
cohorts around years in which rounding occurs, using three- or five-year intervals.7
A final concern arises as a result of cohort-specific mortality. Martinez andWoodruff (2006), who use only 1990 and 2000 data, correct their net-migration estimates

6

See Buck et al. (2007) for an application of the net-migration method in Brazil and Mexico.
Age-specific fixed effects will absorb systematic errors in estimates of net migration which are particular
to individuals of a given age. The three-year aggregation scheme calculates cohorts using birth years 1959,
60, and 61; then 62 and 63; then 64, 65, and 66; etc.; and the five-year scheme calculates cohorts usingbirth years 1958-62, then 63-67, etc. The intent is to center cohorts around years in which rounding occurs,
thereby decreasing the likelihood that an individual is placed in the wrong birth cohort.
7

6

using cohort- and age-specific mortality rates. However, no such data exist for 1960 or
1970, and Mexican mortality data are based on the state in which the individual dies,making it impossible to ascribe mortality to the state of birth. For the period from 1990
to 2000, mortality is a non-negligible share of the observed net migration. In cohorts
aged 23-27, only 8.8% of the observed decrease in cohort size comes from mortality, but
in cohorts aged 43-47 observed net migration has fallen to 7.4% and mortality is 3.1%,
meaning that deaths account for 42% of the missing individuals. Since we use state andbirth-year fixed effects, mortality would introduce bias into our parameter estimates only
if there is variation that is both cross-state and cross-time. To examine this possibility,
we regress 2000 state/cohort-level mortality rates on 1990 rates, including fixed effects
for the state and five-year birth-year cohorts. The R2 in the regression is 0.96, suggestingthat the fixed effects absorb most (but not all) of the regional heterogeneity in mortality8
Subject to these caveats, what do estimates of net-migration tell us?

Not

surprisingly, net labor outflows from Mexico have increased sharply over time. In 1970,
57,000 individuals aged 26 had left Mexico over the previous decade, in 1990 165,000
26-year olds had left over the previous decade, and in 2000 336,000 individuals had left
over the previous decade.

Figure 2 plots smoothed age- and gender-specific net

emigration rates. For men, a substantial fraction of individuals migrate by age 16, withemigration increasing sharply until around 30 and decreasing thereafter, presumably as aresult of return migration. The pattern for women is different. There is less emigration
by age 16, with subsequent rates being relatively stable over the course of their lives. By
age 50, women have a net emigration rate that is similar to that for men.

8

In addition, an unreported analysis of the 1990-2000 changes in birth cohort ratios and cohort-levelmortality rates found the cross-state, cross-time correlation in these variables to be insignificant.

7

To examine how labor supply affects emigration from Mexico, we exploit intertemporal and inter-regional variation in the relative size of birth cohorts. Table 1 shows
the data behind Figure 1. The increase in Mexico’s population relative to the U.S. is a
result of differences in the timing of the demographic transition in the two countries. In
the U.S., fertility rates began to fall in the late 1950s, while in Mexico they did not drop
for another two decades. Between 1950 and 1980, the Mexico-U.S. ratio of birth cohort
size grew from 0.31 to 0.66.
Table 1 also shows the number of U.S. natives that fail to complete high school
according to birth year (where the number of high school dropouts is measured the firsttime a cohort is observed after age 19).9 U.S. high school dropouts are the group
Mexican immigrants appear mostly likely to compete with (Aydemir and Borjas, 2007).
As the share of U.S. natives without a high school education has declined, Mexico’s
relative labor supply has grown. In 1970, the ratio of 20-year olds born in Mexico to 20year old high school dropouts born in the U.S. was 2.45; by 1990, it was 4.99.
Within Mexico, there is considerable regional variation in the timing of fertility
declines. Figure 3 plots the number of children ever born to women over age 40 by yearof birth for the states that represent the quintiles of the 1960 distribution of fertility rates.
Fertility is lower and the demographic transition occurs earlier in wealthy, industrializedstates, such as the Federal District, whereas states in Mexico’s poor south, such as
Chiapas, have a quite different fertility trajectory. This cross-state, cross-time variationin the timing of the demographic transition provides the identification for our analysis of
Mexican labor supply shocks.

Explanations for heterogeneity in timing include

9

For cohorts aged 16-19 we use the number of US high school dropouts observed in the following US
census so as to avoid miscounting the size of cohorts which are still acquiring high school education.

8

differential changes in female job opportunities, industrialization, mortality, or inequality
across states (Tuiran et al, 2002).

Because realizations on migration are observed

between 16 and 50 years after the shifts which caused the changes in birth cohort size, wetake these changes to be pre-determined for our analysis. We assume that, given state,year, and cohort fixed effects, the most plausible explanation for correlation between
state-level birth cohort size and subsequent migration is the cohort size itself. Of course,
the size of birth cohorts may summarize more about a state than its labor supply. In
section 4, we discuss alternative interpretations of our results.
Another source of variation among Mexican states is the strength and persistenceof migration networks. The correlation in state-level emigration rates to the U.S. from themid 1950s with those from the mid 1990s is 0.72 (Hanson, 2006). The literature relates
the emergence of migration networks in Mexico to the hiring practices of U.S.
agriculture, which utilized Mexico’s railroad network to recruit workers in the country’s
interior. Communities close to rail lines have had the highest emigration rates in the
country since at least the 1920s (Durand, Massey, and Zenteno, 2001).

Following

Woodruff and Zenteno (2006), we proxy for the strength of migration networks using
historical state-level migration rates and state access to Mexico’s railroad network.

3. Theory
3.1 Model
To understand emigration from Mexico, consider a model of two national labormarkets that are linked by migration. In each economy, there is one sector of production.
Workers from Mexico are differentiated by age but are not otherwise distinguished by

9their skill.10 To highlight the workings of the model, we suppress internal migration in
Mexico.

An appendix extends the model to allow for internal migration.

Our

specifications of labor demand and labor-mobility costs build on the models of internalmigration in Blanchard and Katz (1992) and Borjas (2006).
In Mexico, the national wage for age group i at time t is given by,(2)

Wit = X it ( Lit )η ,where Wit is the wage, Xit is a labor-demand shifter, Lit is the population of working-age
adults in Mexico, and η ≤ 0 is the inverse labor-demand elasticity. The supply of labor in
Mexico is the population of group i that has not emigrated, such that(3)

Lit = Li 0 − M it

where Li0 is the pre-emigration population of group i and Mit is the number of individuals
in i that have emigrated to the U.S. by period t. Putting (2) and (3) together,(4)ln Wit = ln X it + η ln Li 0 − ηmit ,where mit=Mit/Li0 is the fraction of group i in Mexico that has emigrated.11
An individual in Mexico has the option of staying in the country or moving to the
U.S., in which the wage for experience group i is
(5)

Wit* = X it* ( L*i 0 + τM it )η ,where W*it is the U.S. wage, X*it is the U.S. labor-demand shifter, τ ∈ [0,1] is the
productivity discount associated with immigrant labor, L*i0 is the U.S. labor supply(assumed equal to the population of U.S. native-born high school dropouts), and η is theinverse labor-demand elasticity, assumed equal to that in Mexico.
10

We ignore other aspects of skill because in order to measure net migration by state of birth in Mexico weneed to track populations by characteristics which are invariant to time.
11
In (4), we utilize the approximation that, for small values of X/Y, ln(X+Y) ≈ lnX + Y/X.

10

The wage equation in (5) implies that when expressed in productivity-equivalent
units, native and immigrant labor in the U.S. are perfect substitutes.12 However, theproductivity discount, τ, ensures that one immigrant worker substitutes for less than one
native worker.

Immigrant workers may be less productive because they are less-educated, have a weaker command of English, or are less knowledgeable about U.S.
production practices. Expressing (5) in log form,(6)

ln Wit* = ln X it* + η ln L*i 0 + ητλmit ,where λ=Li0/L*i0 is the relative size of Mexico’s initial population.
To allow for adjustment costs in labor mobility between countries, we assume that
migration from Mexico to the U.S. in any period t is a function of the lagged difference inwages between the two countries:(7)vit* = σ* ( ln Wi *,t −1 − ln Wi ,t −1 − Ci ,t −1 ) ,where vit* = ΔM it / Li 0 is the net emigration rate for group i in Mexico at time t, σ* is the
supply elasticity, and Ci,t-1 is a wage discount that Mexican nationals associate with livingin the U.S. The wage discount reflects the disamenity of living in the U.S. To capture
network effects associated with emigration, we assume this disamenity is decreasing in
the fraction of an individual’s cohort that has previously migrated abroad, such that
t −1

(8)

Ci ,t = C − γ ∑ vis
s =1

where we assume 0 ≤ γ ≤ C (to ensure migration stops at or before U.S. and Mexican
wages are equalized). Using (7) and (8), the period t emigration rate from Mexico is,
12

U.S. evidence on the substitutability of native and immigrant labor is mixed. While Aydemir and Borjas(2007) find native and immigrant workers are perfect substitutes (within skill groups), Ottaviano and Peri
(2006) find they are not. Borjas, Grogger, and Hanson (2008) show that once one adopts conventional
definitions of who is in the labor force, Ottaviano and Peri’s results also support perfect substitutability.

11

(9)

t −1
⎛
⎞
vit* = σ* ⎜ ln Wi *,t −1 − ln Wi ,t −1 + γ ∑ vir −C ⎟ .
r =1
⎝
⎠

A larger existing stock of emigrants in the U.S. makes future emigration more attractive.
In (9), migration networks operate within cohorts (through siblings and cousins) rather
than between cohorts (through fathers and uncles).13 In the empirical analysis, we control
for networks between cohorts by allowing for birth-state fixed effects and by letting the
supply elasticity, σ*, vary according to the strength of historical migration networks.
To solve the model, define the pre-migration effective wage differential between
the U.S. and Mexico as,(10)ω*i 0 = ln Wi*0 − ln Wi 0 − C = η ln A*i 0 + ln xi*0 − C .

where ln A*i 0 = ln L*i 0 − ln Li 0 is the log difference in U.S. and Mexico initial labor supplies
and ln xi*0 = ln X i*0 − ln X i 0 is the log difference in U.S. and Mexico initial labor demand
shifters. The U.S.-Mexico pre-migration wage difference is decreasing in U.S.-Mexico
relative labor supply (since η < 0), increasing in U.S.-Mexico relative labor demand, anddecreasing in the migration disamenity.14 Using (4), (6), and (9), we solve for the t = 0
emigration rate, and then iterate forward, solving for the wage and emigration rate in eachperiod. This reveals that the emigration rate for age group i in period t is,15(11)vit* = ω*i 0 σ* + ω*i 0 θ ( t − 1) .

where θ = ( σ* ) ⎡⎣ γ + η (1 + τλ ) ⎤⎦ . The first term on the right of (11) indicates that the2

13

Orrenius and Zavodny (2005) find that the likelihood a young Mexican male migrates to the U.S. ispositively correlated with the father having migrated and with the number of siblings that have migrated.
14
Here, we assume that labor demand is constant over time such that Xit=Xi0 and X*it=X*i0. In an appendix,
we generalize the model to allow for time-varying labor demand shocks.
15
The precise solution to the model is vit* = σ*ω*i 0 (1 + σ* [ γ + η (1 + τλ )])t −1 . We obtain the expression in (11)by applying the approximation that (1+x)t ≈ 1+tx.

12

emigration rate is higher the larger is the initial wage differential between the U.S. andMexico. Larger monetary gains to emigration naturally make emigration more attractive.
Thus, emigration from Mexico will be greater the smaller is U.S. labor supply relative to
Mexico (ℓ*i0) or the stronger is U.S. labor demand relative to Mexico (x*i0).
The second term in (11) captures emigration dynamics. Over time, emigration
pushes wages up in Mexico and down in the U.S.16 Assume for a moment that γ = 0,such that there are no network effects. In this case, θ = ( σ* ) η (1 + τλ ) < 0 , which implies2

that the emigration rate for group i declines over time as emigration across successive
periods erodes the binational wage difference. Now, allow for network effects, such that
γ > 0. The emigration rate may accelerate or decelerate over time. If γ < −η (1 + τλ ) ,then θ < 0 (recall that η<0). Network effects are weak and/or labor demand is inelastic(η<<0), meaning that networks effects are not strong enough to counteract the depressive
effect that emigration has on the wage differential. Alternatively, if γ > −η (1 + τλ ) , thenθ > 0 . Network effects are sufficiently strong to compensate for the emigration-induced

decline in the wage differential, indicating that emigration accelerates over time until
U.S.-Mexico wage parity (adjusted for the emigration disamenity) is reached.17 The
estimating equation follows directly from (11).

3.2 Specification Issues

For estimation purposes, we use (10) to rewrite (11) as(12)vit* = ln A*i 0 ⎡⎣ησ* + ηθ ( t − 1) ⎤⎦ + ⎡⎣ln xi*0 − C ⎤⎦ ⎡⎣σ* + θ ( t − 1) ⎤⎦16

The key predictions of the model for Mexican emigration still apply even if migration from Mexico to
the U.S. leaves U.S. wages unchanged. This case is equivalent to setting λ equal to zero in (11).
17
Implicit in our setup is that emigration is reversible, in which case individuals re-optimize their migration
decision in each period. There is no option value to delaying emigration, as in Carrington et al. (1996).
Our approach thus allows for return migration, though it does not explicitly model why it might occur.

13

We use U.S. high school dropouts to measure U.S. labor supply (the numerator of A*i 0 ).
Treating U.S. high school dropouts as the relevant labor market for Mexican immigrants
follows the literature (e.g., Aydemir and Borjas, 2007). However, it may introduce
endogeneity into the estimation. If the decision by U.S. natives to complete high school
depends on the U.S. wage for high school dropouts, then shocks to Mexican emigration
may play a role in determining the number of U.S. high school dropouts. Mexican
emigration and the supply of low-skilled U.S. natives would then be jointly determined.
A related concern is that the number of high school dropouts may be a poor measure of
the supply of low-skilled U.S. workers, introducing measurement error into theestimation. Many high school dropouts in the U.S. appear to have a weak attachment to
the labor force (see, e.g., Borjas, Grogger, and Hanson, 2008), meaning they may notcompete with full-time immigrant workers for jobs.
We address concerns regarding endogeneity and measurement error in U.S. labor
supply by instrumenting for the number of U.S. high school dropouts using the size of thecorresponding U.S. birth cohort. Our identifying assumption is that the size of current
U.S. birth cohorts is uncorrelated with expected immigration from Mexico (20 years in
the future). In the first stage estimation, the log size of U.S. birth cohorts, along withdummy variables for gender, census year, and birth year, can account for 97% of thevariation in the log number of U.S. native high-school dropouts.
We model the initial wage in a Mexican state relative to the U.S. as a function of
the size of a state birth cohort relative to the size of the corresponding U.S. birth cohort(as well as initial differences in labor demand). To allow for the fact that similarly aged
individuals are likely to be highly substitutable in production, we group birth cohorts by

14

three or five-year intervals (which also mitigates rounding error in birth years). The
implicit assumption is that each age group has its own production function and that otherproduction factors, including younger or older groups, can be subsumed into state percapita GDP, or the gender, birth-year, and birth-state fixed effects included in the
regression. In the estimation, we consider the robustness of the results to this assumption
by adding controls for the size of adjacent birth cohorts. We also examine how theresults are affected by different aggregation schemes.

4. Empirical Results
4.1 Empirical Specification

The dependent variable for our analysis is the flow of net emigration, Δmijst ,which is the ten-year time difference in the emigrant stock in (1) and which corresponds
exactly to vit* in (12). This value is the net share of a birth year (i), gender (j), and birthstate (s) cohort that has emigrated during the previous ten-year interval. In the main
results, we group birth cohorts by three-year intervals and in later results we use one- andfive-year intervals. Following (12), the regression equation we estimate is(13)

Δmijst = ln lijs ⎡⎣α1 + α 2 ( t − 1) ⎤⎦ + ln xis ⎡⎣ β1 + β 2 ( t − 1) ⎤⎦ + zstφ + I + J + S + T + ε ijst ,where lijs is the size of a Mexican state birth cohort relative to the number of U.S. highschool dropouts in that birth cohort, xis is initial labor demand for a state birth cohort
relative to the U.S., zst captures labor-market shocks to state s in year t, and I, J, S, and T
are fixed effects for birth year, gender, birth state, and census year.18

By (12), therelative initial size of a Mexican birth cohort (lijs) should be positively correlated with
18

To be precise, comparing (12) and (13) lijs is the inverse of A*i 0 and xis is the inverse of xi*0 . We use theinverses to make the regression results easier to interpret (such that in Mexico positive labor supply shocks
increase emigration and positive labor demand shocks decrease emigration).

15

emigration, while relative initial labor demand in Mexico (xis) should be negatively
correlated with emigration. We specify the initial difference in labor demand as the log
ratio of state per capita GDP to U.S. per capita GDP in the year a cohort first enters thelabor market (assumed to be age 16). This is an admittedly crude measure of labordemand and we view the variable as controlling for initial conditions in a state more
broadly. We control for current-period labor-market shocks in a state using the 10-yearchange in state per capita GDP. We discuss results using other variables, as well.
From (12), the coefficient on initial relative labor supply in (13), α1 = ησ*,depends on the emigrant supply elasticity, σ*, which may vary by gender, age, or region.
We begin with results that pool across gender, age, and state, and then disaggregate
across Mexican states and report results for specific age and gender subgroups. Under
the dynamics specified by the model, the impact of initial labor-market conditions on theemigration rate may increase or decrease as a cohort ages, depending on whether network
effects dominate wage-convergence effects. As specified by (13), we interact initiallabor-market conditions with the time since a cohort entered the labor market (t-1).
Networks may also affect the responsiveness of emigration to labor-market shocks (σ*),
which we allow for by interacting initial state labor-market conditions with measures ofhistorical state migration networks.

4.2 Baseline Estimation Results

We begin with results for a sample of national aggregate birth cohorts for Mexicoand the U.S., shown in Table 2. Though we have only 166 observations on one-yearbirth/gender cohorts at the national level, the specification is useful for seeing whether
there is any correlation between emigration and relative labor supply in aggregate data.

16

In Table 2, there is a strong positive correlation between the size of a Mexican
birth cohort (relative to the number of U.S. high school dropouts in that cohort) and theemigration rate for the cohort. Our dependent variable is expressed as a share and the
explanatory variables are in logs, so our parameter estimates give the decadal labor
supply elasticity of net migration. In column (1), which is based on OLS, a 10% increasein the relative size of a Mexican cohort is associated with an increase in the decadal
emigration rate of 0.3 percentage points, with the effect precisely estimated. Consistent
with theory, larger Mexican birth cohorts have higher emigration rates. Initial relative
per capita GDP in Mexico is negatively correlated with emigration, also as predicted bytheory. State-level changes in per capita GDP enter with a negative sign, as predicted bytheory, but are imprecisely estimated. Column (2) gives instrumental variable estimates,
where we control for measurement error or endogeneity in the U.S. supply of low-skilledlabor by instrumenting for the ratio of Mexican birth cohort size to U.S. high school
dropouts with the ratio of Mexican birth cohort size to U.S. birth cohort size. The IV
estimates are twice as large as the OLS estimates and are precisely estimated.19 Columns(3) and (4) break out cohorts by gender, revealing that the effects of cohort size on
emigration are larger for men than for women, a result we discuss below.
Next, we turn to the main results for the sample of three-year birth cohorts using
individual Mexican state birth cohorts as the unit of analysis. Given small cohorts aremeasured with less precision, estimates using state-level census data are noisy, making
net emigration heteroskedastic. To address measurement error, we use robust standard

19

These results suggest that in OLS regressions inconsistency is due more to measurement error in the
supply of low-skilled U.S. native labor (which would tend to bias coefficient estimates on relative cohort
size toward zero) than to the endogeneity of U.S. labor supply to shocks to Mexican migration (which
would tend to introduce positive bias in the coefficient on relative cohort size).

17errors clustered at the level of birth states and trim the 2.5% tails of net-emigration flows.
The first column of Table 3 controls for birth-state fixed effects only. Mexico hasa long history of regional differences in income levels, income growth, and population
growth (Chiquiar, 2005). Birth-state fixed effects remove these and related sources ofstate-level heterogeneity from the regression. Labor supply continues to work in themanner theory predicts: increases in Mexico’s cohort size (relative to the U.S.) drive
emigration up. The correlation between emigration and initial GDP remains negative andprecisely estimated. In column (2) of Table 3, we introduce controls for gender, census
year, and 10-year birth cohorts.20 Census year fixed effects remove the effect of changes
in border enforcement by U.S. immigration authorities, such as those introduced by the
Immigration Reform and Control Act in the late 1980s and the expansion in U.S. borderfortifications in the 1990s (Hanson, 2006), provided the impact of these changes isexperienced in a common way across cohorts in our study (those aged 16-50). Birth-year
fixed effects control for the size of the average Mexican birth cohort, cohort-specificeffects of U.S. enforcement policies, and other unexplained differences in migration
propensities between earlier and later-born cohorts.21
These additional controls amplify the effect of labor supply on emigration but
drive the effect of initial per capita GDP to zero. Given the lack of substantial crossstate, cross-time variation in Mexican GDP per capita (Chiquiar, 2005), census-year andbirth-year fixed effects appear to remove most of the explanatory power of the initial
20

Since a full set of birth-year fixed effects would eliminate all variation in U.S. labor supply, we limit thecontrols to dummies for 10-year birth groups. In unreported results, we find that relative cohort size
remains positively and significantly correlated with emigration, even with the full set of birth-year
dummies in the regression. In this specification, the effect of cohort size on emigration is identified
entirely on variation in population growth across Mexican states.
21
Based on theoretical results reported in an appendix, birth-year fixed effects also control for cohortspecific pressures to migrate internally.

18

level of development. We do not interpret these results as evidence that labor demand is
unimportant, but rather that even conditioning on initial average income there is a
powerful independent channel through which labor supply drives emigration.
In column (3), we move from OLS to IV, following a similar strategy of
instrumentation as in Table 2. The IV estimates for labor supply are again larger. A 10%
increase in the base size of a Mexican cohort results in a 1.3% increase in out-migration
per decade over the working years of that cohort. Columns (4) and (5) indicate that the
impact of labor supply on emigration is roughly twice as large for men as for women.
The migration decisions of men appear to be more responsive to labor-market conditions
upon entry into the labor force, perhaps reflecting the tendency of families to invest in the
migration of fathers and sons over mothers and daughters. Later results suggest that overtime, migration rates for women increase, allowing them to catch up (consistent with thesimilar long run migration rates for men and women seen in Figure 2).
Based on the results in Table 3, the correlation between initial labor supply andemigration appears to be robustly positive. The coefficient estimates in column (3) imply
that moving a Mexican state from the 25th to the 75th percentile of relative labor supply
would raise the decennial emigration rate by 25 percentage points, against a mean
emigration rate of 7%.22

4.3 Network Effects and Migration Dynamics

So far, we have constrained the estimated elasticities to be constant across regionsof Mexico. Pre-existing migration networks could affect the emigration elasticity, σ*, inequation (19), by making regions with stronger networks more sensitive to changes in
22

To perform this calculation, we express state cohort sizes as deviations from each state’s mean over the
sample period and take the 25th and 75th percentiles of the distribution of these within-state deviations.

19

labor-market conditions. We capture the strength of pre-existing migration networks
either by the state emigration rate in 1924 or the distance of a state to the railroad that ran
down Mexico’s spine in 1910, which U.S. labor contractors initially used to locate
potential Mexican workers (Cardoso, 1980).23
The first two columns of Table 4 show results in which we interact relative cohort
size with pre-existing migration networks (all regressions in Table 4 are based on IV
estimation).24 In column (1), the interaction term is positive, indicating that Mexican
states with a longer history of emigration are more responsive to variation in cohort size.
There is a similar result in column (2), where the interaction term is negative, implyingthat states closer to the migration railroad respond more strongly to relative cohort size.
In unreported results, we found no precisely estimated interaction effect between
migration networks and initial relative per capita GDP.
The interaction between cohort size and pre-existing migration patterns capturesintergenerational migration networks. Father and uncles may relay their experiences tosons and nephews (and daughters and nieces), helping create regional persistence inmigration patterns. Munshi (2003), Orrenius and Zavodny (2005) and McKenzie andRapoport (2007) also provide evidence that networks (either within families orcommunities) lower the cost of emigrating from Mexico.
By their nature, intergenerational networks change slowly over time. Equation(11) allows for intra-generational networks, which produce a dynamic migration response

23

Consistent with a large literature on the subject, we find that distance to the U.S. border is not a goodproxy for the strength of migration networks, whereas distance to the railroad is.
24
As in previous regressions, the high school dropout cohort size ratio is instrumented using the entire US
native born population cohort size ratio. Each column in Table 4 interacts the HS dropout ratio with anexogenous variable, and in each case we instrument for this using the interaction of the native population
ratio with the same exogenous variable.

20

to initial labor-market conditions. The shock caused to initial migration will have effects
that are dampened as a cohort ages if labor demand is relatively inelastic (η<<0), suchthat θ < 0, or that are amplified as a cohort ages if network effects from migration arestrong (γ>>0), in which case θ > 0. The dynamic labor-supply elasticity, θ, can be
estimated by interacting initial labor-market conditions with the number of years since acohort entered the labor force, assumed to be the current cohort age minus sixteen.25
The third column of Table 4 shows these interactions estimated on the full sampleof birth cohorts. For shocks to relative labor supply, the pooled results indicate aninteraction effect which is in the same direction as the marginal effect, but insignificant.
The labor demand interaction, on the other hand, is in the opposite direction from theuninteracted effect and strongly significant.

This suggests that the depression of

migration caused by a positive GDP shock at age 16 is transitory, and over subsequent
decades migrants compensate by leaving these states in larger numbers.
Columns (4)-(6) repeat this exercise, dividing the sample according to the strengthof pre-existing migration networks.

These disaggregated results display intriguing

heterogeneity in the dynamic response to labor supply. In states with the strongest
history of migration (top tercile) the interaction effect is negative, suggesting that thedampening response of wages to migration is dominant. States with intermediate levelsof historical migration display a strongly positive interaction between labor supply andyears since turning 16, indicating that migration accelerates over time. In states with

25

The analysis in Table 4 is the place that our theory tells us that internal Mexican migration will play arole. However, birth-year fixed effects remove the mean impact of Mexican cohort size from the data. The
remaining effects of aggregate Mexican cohort size are difficult to identify because each state cohort size is
independently included, and so the sum across states introduces a complicated form of differencing into thedata. We therefore omit aggregate Mexican cohort size from the analysis shown.

21

non-existent networks (bottom tercile), the dynamic interaction is insignificant. Taken
together, these results suggest that the networks created by labor supply-driven migration
are self-reinforcing over time only if those networks are new; states in which those
networks were already extant show a dampening, rather than an acceleration, over time.
Where historical migration networks are weakest, the migration networks initiated bylabor supply shocks may be too small to create new, self-reinforcing flows.

4.4 Robustness Checks

Estimates of net migration are noisy, especially for smaller states in the sample.
We implement robustness checks to examine the extent to which measurement error may
be affecting the estimation. A particular concern is raised by the fact that the base cohort
size appears in the numerator and denominator of the dependent variable as well as in log
form as an independent variable. It might be the case that we are picking up a spurious
correlation arising from the fact that the base cohort size is observed with error and afunction of this measure error is then regressed on itself. Fortunately, we have a simple
way to modulate the degree of measurement error present in the data, which is toaggregate over larger or smaller cohorts than the three-year birth-year groups used so far
in the analysis. As we calculate base cohort sizes and net migration rates on one-year(five-year) cohorts we should increase (decrease) the measurement error, which allows us
to gauge the extent to which this matters for our results.
In Table 5, we re-create the fixed effect regression presented in column (3) of
Table 3, using one-year, three-year, or five-year birth cohorts. As we move from lessaggregated to more aggregated cohorts, the magnitude of the coefficient on relative
cohort size increases, which is the exactly opposite pattern we would expect if

22measurement error were responsible for our results. Also, the precision of the coefficientestimates increases as we move to more aggregated cohorts, despite the fact that thethree-year cohort sample has 60% fewer observations than the one-year sample and thefive-year sample has 80% fewer observations. The clear implication from this exercise isthat rather than measurement error driving our results through spurious correlation, it
may understate the strength of the relationships due to attenuation bias.
The use of five-year cohorts in Table 5 helps address another issue, related to thefact that our specification assumes that possibilities for labor substitution between
younger and older cohorts can be subsumed into state, census-year, and birth-year fixed
effects. As we expand the size of a birth cohort, we allow for more flexible patterns oflabor substitution, though at the cost of reducing the sample size. Another way to address
the issue of labor substitutability is to include the size of adjacent cohorts in theestimation directly. In unreported results, we added as regressors the log size of theprevious and following state birth cohorts, each expressed relative to the size of thecohort pertaining to an observation. This addition leaves our qualitative results on theimpact of relative labor supply on emigration unchanged.
Another issue has to do with omitted variables that could be related to state
population growth. Because changes in the timing of the demographic transition are notrandomly assigned, we may be concerned that some third factor exists which is driving
both changes in cohort size and the decision to migrate out of Mexico. In this case thecorrelations we measure between Mexican cohort size and net migration would be biased.
Perhaps the most obvious underlying source of heterogeneity in Mexico during thisperiod is differences in the timing of industrialization. In 1970, 12% of Mexican GDP

23

derived from agriculture, but by 2000 this number had fallen to 5%.

While earlyindustrializing states, such as the Federal District and the state of Mexico, saw littlechange in their agricultural share, other states saw a sharp decline. In unreported results,
we examine whether the movement out of agriculture may have mutually driven
population growth and migration during the period of our study by including the share ofstate GDP that comes from agriculture to the specification in column (3) of Table 3. Our
results on relative labor supply are unchanged, suggesting they are not being driven byunobserved heterogeneity in the timing of industrialization across Mexican states.

4.5 The Final Stock of Migration and Possible Future Trends

All of our results so far have followed the theoretical model in analyzing the flowof migration over time. We summarize our empirical section by presenting results on theimpact of labor supply and demand shifts on the stock of migrants, meaning the total
share of a cohort that has migrated out at by the time they reach age 50. In order tomeasure these long-term effects we must observe the cohort prior to migration age andthen be able to follow them until they reach the end of their migration years. We
therefore restrict this analysis to cohorts aged between 40 and 50 which were firstobserved in the data younger than age 15. This group of 843 cohorts gives us the ability
to measure the impact of labor supply shocks on the long-term net stock of migrants. We
include as demand controls the GDP ratio when these cohorts turned 16 as well as themost recent change in state per capita GDP that they had experienced.
In this regression (shown in Table 6), he coefficient estimate of 0.37 for relativelabor supply indicates that for every three ‘extra’ Mexican nationals (relative to thenumber of U.S. natives) born in a given state one of them will eventually migrate to the24

U.S. Different from the results on migration flows in Table 5, the effects of labor supply
shocks are somewhat larger for women than for men. The most likely explanation forthis is reverse migration; while men have a higher propensity to migrate at younger ages
they are also more likely to return to Mexico later in life, and hence the use of older
cohorts enhances the apparent sensitivity of women to labor-supply shocks.
One way of understanding long-term emigration magnitudes is to simulate total
out-migration using the parameter estimates from Table 3. We use the marginal effectfrom column 3, which gives a decadal coefficient of 0.144 on the log base cohort size.
From here we can calculate the aggregate base cohort size for each birthyear for thecountry as a whole, and multiply the log of this quantity times the marginal effect and thenumber of decades over which they are observed. Of the 37.5 million Mexicans born
between 1960 and 1980, this method suggests that just over 2.2 million emigrated as aresult of labor supply growth. Using independent estimates that the stock of Mexican
immigrants in the U.S. increased by 5.2 million during the years 1977-1997 (that is, theyears after these cohorts had turned 16), this implies that 42% of total migration can be
explained by labor supply growth in these 21 cohorts. This figure is likely to be anunder-estimate both because it uses only a subset of cohorts to form the numerator of thefraction, and because it ignores the subsequent network-driven migration caused by these
individuals. Hence, labor supply growth in Mexico alone can account for one third of thetotal migration from that country to the U.S. over the past quarter century.
Going forward in time, growth in Mexico’s labor supply relative to the U.S. islikely to slow substantially. With Mexican fertility rates having fallen from 7 in 1960 to
2.5 in 2000, labor supply shocks are likely to become a much less significant push factor

25

in Mexican labor outflows.

Given the substantial role of labor supply in Mexican

emigration to date, this is an important development.
To examine the implications of Mexico’s slowdown in population growth for
migration, we use the regression results to forecast future emigration rates by birthcohort. First, we sum the data by Mexican state and gender to arrive at aggregate labor
supply in Mexico (and in the U.S.) for each year, from which we calculate the log labor
supply ratio, with Mexico in the numerator. In order to construct the forecast of this log
labor supply ratio, we ran an Arima model that included a first-order autoregressive and afirst-order moving average component as well as a linear and quadratic time trend. Using
the Arima model, we then projected relative labor supply from 2000 through 2020. The
net migration rates across age for each cohort were then predicted using the parameter
estimates from column (3) of Table 4, which gives us the dynamic effects of cohort size
estimated using the entire Mexican population.

Figure 4 plots the resulting net

emigration rates by decade from 1960-2020, expressed relative to the 1940 cohort (i.e.,
subtracting values for 1940 from each cohort). This exercise is equivalent to forecastingchanges in emigration due to labor supply, holding labor demand, enforcement policies,
and other factors constant. By expressing emigration relative to a base cohort, we isolatechanges in past and future emigration that the empirical results suggest are associatedwith changes in relative labor supply.
In Figure 4, labor-supply-induced emigration falls for cohorts born between1940
to 1960, owing to the large increase in U.S. population associated with the baby boom.
From 1960 to 1980, relative labor supply growth in Mexico leads to a dramatic surge inemigration. But this surge peaks for the 1980 birth cohort, which would have begun to26

enter the labor market in the late 1990s. Emigration rates fall for all subsequent cohorts,
as population growth in Mexico begins to decline to U.S. levels. By the time the 2020
birth cohort comes of age, emigration rates would have returned to levels equal to thoseof the 1940 birth cohort. Holding labor demand and enforcement policies constant, it
would appear that emigration from Mexico is peaking today and that labor-supply-driven
pressures for labor outflows will weaken in subsequent decades. Of course, shocks tolabor demand or U.S. immigration policy could produce much larger or much smaller
emigration rates, depending on their realizations. Also, while the forecast in Figure 4
controls for intra-generational migration networks, it does not control for dynamicchanges in intergenerational networks, which fall outside our framework.

5. Discussion

The surge in labor flows from Mexico to the U.S. over the last 25 years has madeinternational migration the subject of intense policy debate in the two countries. Mexico
accounts for fully one-third of post 1980 U.S. immigration and the U.S. is now thecountry of residence for nearly one-fifth of young working-age Mexican males. Despite
the magnitude of these labor movements, there is little academic research that attempts toaccount for the scale of Mexican emigration.
Our approach is to examine the contribution of labor-supply shocks to the labor
exodus from Mexico by exploiting variation across Mexican states in the evolution of
population growth. Larger birth cohorts in Mexico have higher rates of emigration,
consistent with positive labor supply shocks contributing to outmigration. Differential
growth in labor supply between Mexico and the U.S. over 1960-1984 can account for one
third of observed Mexican migration to the U.S. over 1977-2000.
27

Looking ahead, population growth in Mexico has decreased dramatically. Indeed,
the 1970 to 2000 decline in fertility in Mexico is one of the fastest ever recorded. Will
slowing population growth contribute to slower increases in emigration rates in the
future? Absent network effects (and holding labor demand constant), the answer would
appear to be yes. The direct effects of differential labor supply growth should already be
dwindling. The sharp increase which started in 1960 came to an end in 1980, and socohorts coming of migration age today are not experiencing the shocks which those only
a decade ago faced. The mechanical migration pressures caused by population growth
are now pressing on Mexico's southern border, because neighboring Central Americancountries have not undergone the rapid demographic transition seen in Mexico
However, emigration from Mexico shows evidence of network effects.
Emigration is more responsive to Mexico-U.S. differences in labor supply in states thathave stronger historical migration networks, and the response of emigration to initiallabor-supply differences appears to accelerate over time in a manner consistent with earlymigrants encouraging later migrants to move abroad. Networks effects could make theimpact of differential Mexico-U.S. labor-supply growth over the 1960-1980 period long
lived, as the current generation of migrants eases migration for later generations. In thisevent, emigration from Mexico may continue to accelerate for some time, even as
population growth in the two countries continues to converge.

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30

Appendix: Allowing for Internal Migration and Labor Demand Shocks

Here, we introduce internal migration within Mexico into the theoretical modelfrom section 2. The motivation is to allow low-wage Mexican states to shed labor toother Mexican states and the U.S. and to allow high-wage Mexican states to take in laborfrom poorer states and send labor abroad. The persistence in earnings differentials acrossstates in Mexico suggests internal migration works slowly to equilibrate wages (Chiquiar,2005), consistent with internal labor mobility being costly.
Let the wage for group i in state s be given by(A1)

ln wsit = ln X sit + η ln Lsi 0 + ηmsit ,where Lsi0 is the pre-migration state population and msit=Msit/Lsi0 is the fraction of the
population that has left the state on net at time t (due to either internal or externalmigration). Individuals in state s may migrate within Mexico, in which case they earn thenational average wage given by (4), or they may emigrate to the U.S., in which case theyearn the wage given by (6). There are adjustment costs to moving labor either between
states in Mexico or between a Mexican state and the U.S. Following similar logic as in(9), the external migration rate (from the state to the U.S.) for group i in state s at time t is
t −1
⎛
⎞
*
= σ* ⎜ ln wi*,t −1 − ln wsi ,t −1 + γ ∑ vsir −C ⎟ ,
(A2)
vsit
r =1
⎝
⎠
where we again allow for network effects in emigration and assume these are specific toindividual states in Mexico. The group i rate of internal migration (out of state s toanother state in Mexico) is given by
vsit = σ ( ln wi ,t −1 − ln wsi ,t −1 ) ,(A3)where for simplicity we assume there are no network effects for internal migration and
we normalize the disamenity associated with internal migration to zero.
To solve the model, we combine (4), (6), (A2) and (A3), derive the internal andexternal migration rates in period 1, and proceed iteratively to later periods.26 Define thepre-migration effective wage difference between the U.S. and Mexican state s as,
X i*0
L*i 0
*
*
(A4)
ωsi 0 = ln wi 0 − ln wsi 0 − C = ln
+ η ln−C ,X si 0Lsi 0and the pre-migration wage difference between Mexico overall and state s as,(A5)

ωsi 0 = ln wi 0 − ln wsi 0 = ln

X i0L
+ η ln i 0 .
X si 0Lsi 0

26

With internal migration, the solution to the model is complicated by the fact that the rate of wage
convergence across Mexican states may differ from that between Mexico and the U.S., which introduces aseries of second-order terms into the expressions for internal and external migration rates. We derivemigration rates ignoring these second-order terms, which makes our solution an approximation.

31

The resulting approximate solution (see note 24) for the migration rate to the U.S. forgroup i in state s at time t is,

(

*
vsit
= ω*si 0σ* 1 + σ* ⎡⎣ γ + η (1 + τλ ) ⎤⎦(A6)

) + ω σ ( ⎡⎣1 + σ η⎤⎦ − 1) ,
t −1

*

t −1

si 0

for which we adopt the following linearization (as in (11)),vit* = ω*i 0σ* + ω*i 0 ( t − 1) ( σ* ) ⎡⎣ γ + η (1 + τλ ) ⎤⎦ + ωsi 0 (t − 1)σσ*η .
2(A7)

The factors driving state emigration to the U.S. are similar to the national case in (11):the weaker is a Mexican state’s labor demand or the larger is its labor supply (relative to
the U.S.) the higher will be the state emigration rate, as captured by the first two terms on
the right of (A7).27 The third term on the right of (A7) captures how internal migration
within Mexico modifies labor flows abroad. If state s has a pre-migration wage that is
below the national average, such that ωsi0 > 0, then internal migration dampens
emigration to the U.S. (owing to the fact that (t − 1)σσ*η < 0 ). This occurs because
relative to the case in which all state labor outflows were to the U.S. some externalmigration is diverted to internal migration.
Finally, we allow for labor demand to change over time, such that Xsit, Xit, and X*itare no longer constant. Define
X it*
X i*0
X
X
*
xsit = ln− ln, xsit = ln it − ln i 0 ,X sit
X si 0X sit
X si 0which are, respectively, the growth in U.S. and Mexican national labor demands relative
to state s between the pre-migration period 0 and time t.28 The solution to the migration
rate to the U.S. for group i in state s at time t now becomes,
(A8)

t −1

t −1

v = ω σ + ω ( t − 1) ( σ ) ⎡⎣ γ + η (1 + τλ ) ⎤⎦ + ωsi 0 (t − 1)σσ η + ∑ θ x + ∑ θ r xsir .
*
it

*
i0

*

*
i0

* 2

*

r =1

* *
r sir

r =1

Allowing for labor-demand shocks introduces a series of distributed lag terms into theexpression for the emigration rate. It is straightforward to show that θ*r (θr) is positive(negative) and that the magnitude of the coefficients decrease in r (such that labordemand shocks further back in time have larger effects on current emigration).

27

We ignore institutional responses by Mexican states to labor outflows. If educational opportunities in astate are unresponsive to cohort size (as shown for the U.S. by Bound and Turner, 2006), then a further
reason why positive labor supply shocks in a Mexican state may contribute to out-migration is that
individuals are crowded out of local opportunities to continue their schooling and move elsewhere to do so.
28
Since we assume that individuals re-optimize their migration decisions in each period and we ignore
fixed migration costs, we do not need to address expectations about future labor-demand shocks.

32

Figure 1

0

1

2

3

4

5

Labor Supply, US vs MX, 1910=1

1900

1920

1940

1960

1980

2000

Birth year
US native born

MX

Figure 20Migration in percent
5
10

15

Decadal migration rates by gender, 2000

16

21

26

31

36

41

age
Males

Females33

Children ever born to women over 402468

Figure 3

Timing of Demographic Transition, by Mexican State

1910

1920

1930
1940
Year of Birth
ChiapasCampeche
Zacatecas

1950

1960

Distrito Federal
Mexican Average
B.C. Sur

Rank of 1960 Fertility: Chiapas=1, Zacatecas=9, Campeche=16, B.C. Sur=24, DF=32

Figure 4: Future Emigration and the Slowdown in Mexican Population Growth

Predicted net migration rates by birth year and age.3

Stock of net migration, relative to 1940 birth cohort

Additional fraction migrated
0
.1
.2

1980
1970
1990
2000
2010

-.1

2020

1960
16

26

36

46

Age
Birth cohort sizes for 2000-2020 are forecast34

Table 1: Population and GDP (PPP) in Mexico and the U.S.
Mexico

Year
1920
1930
1940
1950
1960
1970
1980
1990
2000

GDP per
capita

4,498
5,385
6,138
8,341
11,976
12,594
15,279Size of Birth
Cohort584,776
753,616
743,566
1,002,387
1,438,300
1,792,770
2,153,340
2,273,444
2,018,483

USGDP per
capita8,820
12,00913,84018,391
22,66628,42934,759GDP in both countries is measured in 2000 US dollars.

No. of highschoolSize of Birthdropouts
Cohort2,281,441 1,115,098
2,223,977
884,869
2,097,851
605,7113,209,845
408,878
4,107,562
381,367
3,221,446
350,870
3,250,323
431,330
4,041,951
3,703,392

Ratio, MX/USMX Birth
GDP per Size of Birth Cohort / USHS dropouts
capitaCohorts
0.26
0.52
0.34
0.85
0.51
0.35
1.23
0.45
0.31
2.45
0.44
0.35
3.77
0.45
0.56
5.11
0.53
0.66
4.99
0.44
0.56
0.44
0.55

Table 2: Baseline Results for Net Migration, National Birth Cohorts
(1)

(2)

Dep. variable: decadal change in net migration rate

OLS

IV

log (MX cohort size/US HS dropouts)

0.030(2.24)*

0.071(4.12)**

0.147(5.09)**

0.017(0.83)log (MX GDP/US GDP) at age 16-0.219(3.32)**-0.263(3.94)**-0.359(3.74)**-0.193(2.25)*

10-yr change log(MX GDP/US GDP)

-0.055(0.27)-0.146(0.71)-0.054(0.16)-0.127(0.48)

Time trend

0.001(0.24)-0.002(1.51)-0.005(2.34)*

0.001(0.53)

Female cohort dummy-0.039(3.62)**-0.045(4.08)**

166
0.17

166
0.13

83

83
0.15

Observations
R-squared(3)(4)
Men Only Women OnlyIV
IV

Mexican cohort size is fixed at its initial value; the number of native US high school dropouts is
contemporaneous. The analysis is performed using one-year birth cohorts. GDP refers to GDP per capita. In
IV regressions, log (MX birth cohort size/ US birth cohort size) is used as an instrument for log (MX birthcohort size/US HS dropouts).
T statistics in parentheses, * significant at 5%; ** significant at 1%.

1

Table 3: Baseline Results for Net Migration, State Birth Cohorts(1)

Dependent variable: decadal change in net migration ratelog (MX State cohort size/US HS dropouts)

OLS
0.0359(12.17)**(2)
All Cohorts
OLS
0.049
(4.49)**log (MX State GDP/US GDP) at age 16-0.0788(6.23)**-0.0307(2.38)*-0.0217(1.46)-0.0261(1.13)-0.0168(1.01)

10-yr change log(MX State GDP/US GDP)

-0.0148(0.63)

0.0031(0.12)-0.0179(0.62)-0.0297(0.59)-0.0028(0.09)

Observations
R-squared

2258
0.19

2258
0.29

2258
0.23

1124
0.25

1134
0.31

Fixed Effects Used:

State

(3)

IV
0.1443(12.99)**(4)(4)
Men Only Women OnlyIV
IV
0.18760.1053(11.51)**(7.54)**

State, census State, census State, census State, census
yr, Sex, 10yr yr, Sex, 10yr yr, Sex, 10yr yr, Sex, 10yr
birth cohort birth cohort birth cohort birth cohort

Mexican state cohort size is fixed at its initial value; the number of native US high school dropouts is contemporaneous. The analysis
is performed using three-year birth cohorts. GDP refers to GDP per capita. In IV regressions, log (MX state birth cohort size/ US birthcohort size) is used as an instrument for log (MX state birth cohort size/US HS dropouts).
T statistics in parentheses, * significant at 5%; ** significant at 1%.
Regressions in all tables use robust SEs clustered at the cohort level and are weighted by birth cohort size.

2

Table 4: Migration Dynamics and Network Effects

Mexican States:
Dep. variable:
decadal change in net migration ratelog (MX State cohort size/US HS dropouts)log (MX State GDP/US GDP) at age 16
10-yr change log(MX State GDP/US GDP)log cohort size ratio * 1924 migration rate

Interaction Effects
All
All

0.151
(13.85)**-0.022(1.48)-0.004(0.15)
18.001(3.19)**

log cohort size ratio * Distance to train

0.158(13.76)**-0.033(2.86)**-0.050(2.27)*

All

0.205(11.30)**-0.043(3.06)**-0.065(2.63)**Top Tercile(highest migration)
0.249(7.55)**-0.060(2.70)**-0.129(2.88)**

Middle Tercile
0.248(7.90)**-0.009(0.22)-0.110(2.35)*

Bottom Tercile(lowest migration)
0.270(7.67)**-0.032(1.96)-0.009(0.33)

0.001(1.92)
0.004(5.53)**
0.012(4.13)**-0.0001(1.24)-0.001(2.01)*
0.005(4.48)**
0.014(3.16)**-0.0002(2.89)**

0.003(5.42)**
0.001(1.37)
0.016(3.07)**-0.0001(0.65)-0.001(1.17)
0.004(3.27)**
0.012(2.27)*
0.00001(0.07)

2258
0.2

837
0.09

642
0.31

779
0.01

-0.0001(4.85)**

log cohort size ratio * Years since 16
log GDP ratio (at 16) * Years since 16
Years since 16 (demeaned)(Years since 16)^2
Observations
R-squared

Dynamic Effects
By Terciles of 1924 migration

2258
0.21

2187
0.2

All regressions include Mexico state, census year, gender, and 10-year birth year fixed effects. All regressions are based on instrumental variables, using
three-year birth cohorts; see text for discussion of instruments.
T statistics in parentheses, * significant at 5%; ** significant at 1%.
Regressions in all tables use robust standard errors clustered at the cohort level and are weighted by birth cohort size.

Table 5: Alternative Specifications and Samples for Net Migration
Unit of Aggregation:

1-year cohorts

2+3-year cohorts

5-year cohortslog (MX State cohort size/US HS dropouts)

0.069(9.50)**

0.144(12.99)**0.202(11.32)**log (MX State GDP/US GDP) at age 16-0.032(2.88)**-0.022(1.46)

0.007(0.38)

10-yr change log(MX State GDP/US GDP)

-0.011(0.55)-0.018(0.62)-0.042(1.56)

Observations
R-squared

5545
0.18

2258
0.23

1173
0.34

All regressions include Mexico state, census year, gender, and 10-year birth year fixed effects, and are based on instrumental
variables, using log (MX state cohort size/ US native total) as an instrument for log (MX state cohort size/US HS dropouts).
T statistics in parentheses, * significant at 5%; ** significant at 1%.
Regressions in all tables use robust standard errors clustered at the cohort level and are weighted by birth cohort size.

Table 6: The Final Stock of Net Emigrants

All cohorts
aged 40-50

Menaged 40-50

Women
aged 40-50

log (MX State cohort size/US HS dropouts)

0.372(7.54)**

0.261(4.14)**

0.451(6.23)**log (MX State GDP/US GDP) at age 16

0.134(2.10)*

0.08568(1.00)

0.171(1.88)

10-yr change log(MX State GDP/US GDP)

-0.021(0.35)

0.014(0.18)-0.051(0.59)

Observations
R-squared

840
0.43

413
0.38

427
0.44

Dependent variable: stock of net migration

All regressions are based on one-year birth cohorts, include Mexico state, census year, and 10-yearbirth year fixed effects, and are based on instrumental variables, using log (MX state cohort size/
US native total) as an instrument for log (MX state cohort size/US HS dropouts).
T statistics in parentheses, * significant at 5%; ** significant at 1%.
Regressions in all tables use robust standard errors clustered at the cohort level and are weighted bybirth cohort size.