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Federal Reserve Bank of Chicago

The Impact of Mexican Immigrants on
U.S. Wage Structure
Maude Toussaint-Comeau

WP 2007-24

The Impact of Mexican Immigrants on U.S. Wage Structure
Maude Toussaint-Comeau
Federal Reserve Bank of Chicago

Working Paper 2007

Key Words: Immigration, Wages, Occupation
JEL Classification: J61, J62

The views expressed are the author’s they do not reflect the views of the Federal
Reserve Bank of Chicago or the Board of Governors of the Federal Reserve System.
The author thanks Phil Doctor for valuable research assistance.

Abstract
Previous study by Card and Lewis (2005) has found (puzzling) that inflows of Mexican
immigrants into “new” metropolitan areas have had no effect on the relative wages of
very low-skill (high school dropouts). Rather, Mexican workers do affect relative wages
for high school graduates. Whereas Card and Lewis’ study uses variations across
geographies, this paper considers variations across occupations. Recognizing that
Mexican immigrants are highly occupationally clustered (disproportionately work in
distinctive “very low wage” occupations), we use this fact to motivate the empirical
approach to analyze the relationship between the composition of Mexican immigrants
across occupations/industries and average wages in the occupations/industries. To
summarize our finding, we confirm that in spite of the fact that Mexican immigrants are
disproportionately in “low-skill” occupations, (which we define as occupations where the
average workers have no high school education), we find no significant impact of
Mexican immigrants on wages in those occupations. By contrast, inflows of Mexican
immigrants have some small effects on the wages of native workers in “medium-skill”
occupations (which we define as occupations where the average worker has at least some
high school education or is a high school graduate). These results suggest potential “spill
over effects” as natives may be reallocating their labor supply into non-predominant
Mexican occupations. An analysis of employment changes of natives into different
occupation groupings in response to an inflow of Mexican immigrants, confirms that
natives’ employment in occupations where the average worker has a high school
education increases in response to Mexican inflows in the U.S labor force from previous
periods.

Introduction and Overview
During the 1990s, the number of Mexican immigrants living in the U.S. rose by
more than five million. By the 2000 Census, Mexican immigrants made up more than 4
percent of the working age population, close to twice more than the proportion a decade
earlier, in 1990. The growing importance of Mexican immigrants in the labor force has
catalyzed a research and policy debate regarding their impact on wages and employment
outcomes of U.S.-born workers. It remains unclear whether less-educated Mexican

1

immigrants simply merely fill jobs that are unappealing to native workers, displace, or
serve as complement in the production process. It is also unclear whether they have
contributed to the overall downward wage pressures experienced in recent decades by all
low-skilled workers.
There is no consensus regarding the impact of immigrants in general on natives’
wages. Depending on the methodological approach, some studies have found a negative
impact of immigrants on natives. Others have found no significant impact on natives.1
Focusing on Mexicans immigrants, Card and Lewis (2005) found that inflows of
Mexican immigrants into “new” metropolitan areas have had no effect on the relative
wages of very low-skill (high school dropouts). Rather, Mexican workers do affect
relative wages for high school graduates. They suggest that this may be due to 2
possibilities. First, Mexican workers may be closer substitutes to natives with high school
diploma, as such their impact may be felt over a broader wage structure than intuition
might first dictate. Second, firms may be absorbing new “inflow” of low-skilled Mexican
workers in local labor markets by adjusting for skill requirements in the workplace.
Building upon Card and Lewis’ results, in this paper, we propose an additional
consideration. Whereas Card and Lewis’ study uses variations across geographies and
considers firms’ absorption capacity of the supply of Mexicans in their local labor
markets, we propose to look at variations across occupations. We ask whether
movements across occupations (i.e., native workers’ moving into non-Mexican
occupation niches) may play a role in the fact that Mexican immigrants do not appear to
affect wages of very low-skill workers. To summarize our finding, we confirm that
Mexican immigrants, in spite of the fact that they are disproportionately in “very low
1

For example, some previous studies exploit variations across geographies and estimate
immigration and changes in natives’ employment outcome across cities or states (Altonji and Card, 1991;
Butcher and Card, 1991; LaLonde and Topel, 1991; Card, 2005). These studies have generally found no
sizable effect on natives. Other studies take a national factor proportion approach and estimate the changes
in the supply of different skill (education) groups brought about by immigration and combining these
changes with estimates of labor demand elasticity, calculate the effects on natives’ wages (Borjas et al
1992, 1996, 1997; Jaeger, 1996; Card, 2005; Orrenius and Zavodny, 2006). These studies have found a
significant effect of immigration on wages of natives. Some researchers have also used natural
experiments on immigration that are driven by political events in the host country, such as the Mariel
Boatlifts and Russian mass migration to Israel (Card 1990; Hunt 1992; Carrington and DeLima, 1996;
Friedberg, 2001). These studies have found no adverse impact of immigration on native employment
outcomes.

2

skill” occupations (which we define as occupations where the average workers have no
high school education), they have no significant impact on wages in those occupations.
Consistent with Card and Lewis’s finding, we also find a negative and significant impact
of an inflow of Mexican immigrants on average wages in “low skill” occupations (which
we define as occupations where the average worker has at least some high school
education or is a high school graduate). As Card and Lewis suggested, this result may
reflect the fact that Mexican immigrants are greater substitutes in the “low-skill”/high
school level occupations. In the context of this paper, this suggests further potential “spill
over effects” as natives reallocate their labor supply into “non-Mexican” occupations, or
occupations in which they have a relative comparative advantage. An analysis of
employment changes of natives into different occupation groupings in response to
inflows of Mexican immigrants, confirms that employment in occupations where the
average worker has a high school education increases in response to Mexican inflows in
previous periods.
This paper is organized as follows. The next section gives an overview of the
theoretical relationship between immigrants and wages of natives, based on previous
literature. Next, we present methodological specifications for this study, describe the
data, and then discuss the empirical results. The final section contains a summary of the
paper and the potential implications of the study.

II.

Theoretical Background
A large economic literature exists that has debated and identified various channels

through which immigrants could potential affect wages and other labor market outcomes
for natives workers (e.g., Borjas, 1999; Greenwood and Hunt 1995; Johnson, 1998;
Ottavano and Peri, 2005; Chiswick et al., 1992). One thing that seems obvious is that,
assessing the impact of immigrants is a difficult and complex problem—as it is before all
a general equilibrium question. The effect depends on a number of interrelated factors.
First, the size of the immigrant flows into a given area must be large enough to have any
measurable impact. In addition, the extent to which factors of production are mobile will
dictate whether immigrants can have any local labor market impact. In the extreme case,
if factors of production are perfectly mobile, this means that there will be no local effects

3

of immigration—these effects would be entirely mediated through general equilibrium
impacts on the larger market.2 It is debatable whether natives are in fact mobile by
responding to an influx of immigrants by moving to other areas (Card, 2001; Kritz and
Gurak, 2001; Frey, 1995).
The impact of immigrants on labor market outcomes for natives depends on the
substitutability between natives and immigrants. If immigrants and natives are perfect
substitutes, an increase in the supply of immigrants will lower wages for natives. This
negative impact is magnified if immigrants are willing to work for less than natives. On
the other hand, if immigrants and native workers are not gross substitutes for each other,
but rather, are complements in production, then an increase in immigrants’ inflow into
the labor market could raise the wages of native workers, if the latter reallocate into
occupations with higher wages.
Convention suggests that low-skill immigrants and natives are potentially greater
substitutes for one another. This is because low-skilled occupations tend to have lower
training costs, and require less institutional knowledge. While, high-skilled professional
occupations, in the health and legal fields, for instance, require licensing and other entry
barriers, which lower the degree of transferability of skills acquired by immigrants in
their countries of origin (Friedberg, 2000; Duleep and Regets, 1999; Gallo and Bailey,
1996)). An interesting brand of newer and more recent researches has however begun to
look at “task specialization” and suggest that low-skilled immigrants and natives may not
be competing for similar jobs. To that effect, Peri and Sparber, (2007) provides a formal
model in which low-skill natives reallocate their labor by specializing into jobs that are
intensive in “interactive production tasks” as opposed to “manual tasks” in which
immigrants specialize in. They show that “task specialization” by immigrants causes
natives with similar education to reallocate their own task supply into jobs requiring more
interactive and communication skills. They show that as a result of increased

2

This follows from trade theory; if economies are perfectly integrated, then local quantities are unrelated to
local prices—the law of one world price for all factors will prevail. In order words, if one assumes that
there is perfect factor price equalization, (FPE) and no international factor price equalization, this means
that immigration can affect aggregate wage but not relative wages across areas within a country.

4

specialization of immigrants, downward pressure on wages for less-educated natives has
been reduced in states with large immigration flows.
The methodological approach presented next follows the study of Peri and
Sparber (2007) in spirit. Recognizing that Mexican immigrants disproportionately work
in distinctive “very low wage” occupations, we use this fact to motivate the empirical
approach to analyze the relationship between the composition of Mexican immigrants
across occupations/industries and average wages in the occupations/industries, as well as
wages earned by natives in those occupations/industries. If the clustering of Mexican
immigrants is indicative of “task specialization” or comparative advantage in those
distinct occupations (such as manual occupations where the English language
requirement is low), this would suggest that their impact on wages of “comparable”
natives would be mitigated. Potential downward pressures of low-skilled Mexican
immigrants on wages of “comparable” natives should be reduced, as the native workers
reallocate their task supply into jobs, such as those where they have a comparative
advantage due to language and communication ability.

III.

Methodological Specification
We first consider an occupation-level wage model where we postulate that

immigrants impact occupation wages through their proportional/density in the
occupation/industry, relative to the native labor force. This basic relationship can be
expressed as follows:

wjt = αt + γrjt + β Xjt + εjt
Where wjt is the average log of real hourly wage in occupation/industry j at time t,

rjt is the ratio of (Mexican) immigrants to native workers in occupation j at time t. Χjt, a
vector of occupation/industry level variables that may also affect occupation wage (e.g.,
average education and average age).
A well-known econometric issue is that the density of immigrants in an
occupation may not be independent of εjt, the unobserved determinants of wages. For
example, “new” Mexican immigrants with lower “unmeasured skills” (captured in the
error terms) are more likely to be sorted into “low-skill Hispanic” jobs. The error term

5

also captures unobserved taste differences among workers. New Mexican workers may
choose to work in occupations that do not penalize them for low English proficiency or
jobs where wage “penalty” for not speaking English is relatively low. To the extent that
this is the case, the exogeneity assumption in the model would be violated. The
conditional correlation of wages and Mexican density would confound the two direction
of causality, making the estimate of γ biased downward, and leading to an overestimate
of any potential negative effect of Mexicans.
It is therefore necessary to control for potential endogeneity bias in case Mexican
immigrants are found in occupations on the basis of wage level. Our methodological
approach is to control for the potential endogeneity of unobservable characteristics of
Mexican immigrants with a standard 2-stage least square instrumental variable estimation
technique. In the first stage, we model labor supply of Mexican immigrants, following
Roy (1951) and Autor et al (2001), by assuming, in the context of this paper, that “new”
Mexican workers would choose occupations to maximize earnings according to their
relative comparative advantage in those occupations. As a working hypothesis, “new”
Mexican immigrants are likely to have comparative advantage in occupations, whose
English language skill requirement is low. Therefore their labor supply is likely to be
relatively higher in such occupations.
In the first stage, we model the occupation penetration of Mexican immigrants as
a function of the “manual” task intensity of the occupation. We use as our indicator
variables for the “manual” task, a task intensity index developed by Autor et al (2001).
This is a composite index, which ranges from zero to 10, where the lower numbers mean
lesser values of the task measure. The “manual” task intensity index measures the extent
to which the task content involves “eye hand foot” or “non-routine manual” operations.
These occupations have very low or no English language skill requirements. We
therefore expect that “new” Mexican immigrants would have relative comparative
advantage in those “manual” occupations as opposed to the counterparts of this indicator.
(The other skill intensity indices are "finger dexterity, set limits, tolerances and
standards” which measures “routine manual tasks and cognitive tasks.” There is also an
indicator of “direction control planning, math aptitude,” which measures non-routine

6

cognitive/interactive tasks and analytical tasks or abstract tasks.3
The first stage where we model occupation penetration must contain an
instrument, which is a source of independent variations in immigration that is correlated
with occupation inflow, but uncorrelated with the unobserved component of wages,
subsequent to the immigrants’ arrival. This study exploits the fact that Mexican
immigrants are highly occupationally segregated in the U.S. and assumes, along these
lines, that such segregation reveals something about preferences or comparative
advantage of the group in certain occupations, which is more or less independent of
unobserved determinants of the wage structure in the US. “New” Mexican immigrants (at
least in the short run before they invest in additional host-country specific human capital
or language skills) are likely to take jobs where previous cohorts have established a selfreinforcing niche. Hence we use the past occupation densities of Mexican immigrants in
the U.S as instrument for the inflow of “new” Mexican immigrants in a later period.4 The
probability that lagged occupation distributions of Mexicans will predict later inflows
increases if the size of Mexicans in the occupations in the past is large enough to
influence the choice of the recent waves and if there is a continuous and homogeneous
inflow of Mexican immigrants. We will confirm that there has been persistence in the
Mexican occupation composition in the U.S over time, as Mexico continued to be an
important sender of immigrants throughout the period under study.
The choice of lagged occupation density as instrument is consistent with previous
empirical economic studies that use historical immigrant allocation patterns in industries,
or historical concentration in various location choices as instruments (e.g., Lewis, 2003;
Card and Lewis, 2005). There is also an interesting sociology literature that suggests how
certain immigrant, ethnic, or minority groups become occupationally clustered and
3

These composite indices were developed based on Dictionary of Occupational Titles. David Autor
provided these indices data for this study.
4

Previous research by Friedberg (2001) uses the occupation of the Russian immigrants prior to migrating
to Israel as an instrument variable. The logic being, the occupations of the Russian Jews were independent
of wages expectation, they were chosen on the basis on labor market condition in Russia and not that of
Israel, since their migration was quite sudden. For that purpose the previous occupation of Russian Jews in
Israel is assumed correlated with their occupation distribution in Israel, and uncorrelated with unobserved
determinants of changes in wage in Israel, subsequent to their arrival, thus making it an acceptable
instrument.

7

develop “occupational niches,” as a by-product of an historical process, which also
supports the choice of all these instruments in these studies.5

IV.

Data and Sample Statistics
As in previous research, we make use of Public Use Micro Statistics (PUMS) data

from the 1980, 1990, and 2000 U.S Censuses, 5% sample. The primary advantages of
using these data files are sample size and occupation coverage.6 Undercounting of
Mexicans due to the undocumented can however be a drawback in these data, as noted in
Card and Lewis (2005). Calculations by Borjas, Freeman, and Lang (1991) suggest that
the 1980 Census missed approximately 40 percent of unauthorized Mexican immigrants,
leading to a 25% undercount in the overall Mexican immigrant population. Van Hook
and Bean (1998) estimate a 30% undercount rate of unauthorized Mexicans in the 1990

5

We have learned for instance that occupational clustering may emerge from the tendency of certain
immigrant groups to concentrate historically in ethnic enclaves, where there may be comparative advantage
in the production of “ethnic goods”. Occupation niches also arise from the process of “ethnic succession” in
the job market. This process may reflect dynamics of “residential segregation,” whereby natives (e.g., nonwhites) would exit certain sectors as immigrants enter them. (e.g., the case noted in New York City
between Whites and Cubans (Waldinger, 1996; Wright and Elllis, 1996)). Occupational clustering is
reinforced as immigrants share information about employment opportunities through self-reinforcing ethnic
networks. Clustering of occupation by an immigrant group may also be facilitated by the heterogeneity of
occupations in their use of language. In occupations traditionally held by immigrants, employers may be
less likely to screen out those who have a lack of English knowledge (Kossouji, 1998). Such occupations
can thus be viewed as being segregated by language ability of the dominant workforce employed. Finally,
an ethnic occupation niche can arise from historic practices of recruitment of workers (e.g., the Bracero
program), and other special provisions in immigration policy or accord between the sending and host
countries (Park, 2004; Waldinger and Der-Martirosian, 2001; Mouw, 2003).
6

There have been significant changes in the classification of occupations between the 1990 and 2000
Censuses that warrant careful attention when making comparisons. The 1990 Census occupational codes
are based on the 1980 Standard Occupational Classification (SOC) system in which occupations are
organized hierarchically in terms of the skill level and the experience considered necessary for individuals
engaged in the occupations. By contrast, the 2000 Census occupational codes are based on the 1998 SOC,
which classifies occupations by ‘job families’—job families combine occupations where people involved
work together regardless of their respective skill level (i.e., doctors, nurses, and nurse assistants are
grouped together). In addition, the 1998 SOC has more professional and technical occupations due to
advances in technology and shifts in service-oriented sectors of the economy. Some 1990 occupations have
become obsolete and do not figure in the 1998 SOC. In addition, some occupations have been “upgraded”
or “downgraded.” For example, farm, ranch and other agricultural managers are found in the major groups
of management occupations in the 2000 Census whereas in 1990 they were listed under farming
occupations. Without ensuring that occupational categories across Censuses are comparable, it is
impossible to get an accurate measure involving change in the occupational classifications over the period.
Peter B. Meyer and Anastasiya Osborne of BLS converted Census occupation codes from 1970, 1980, 1990
and 2000 to 1990 scheme, available at the University of Minnesota "IPUMS Project"
(ipums@pop.umn.edu). This data set is used in the empirical analysis.

8

Census and a 20% undercount of all Mexicans. Norwood et al (2004) estimate suggest
that the 2000 Census was substantially more successful in counting unauthorized
immigrants. They estimated an undercount rate for unauthorized immigrants on the order
of 10 percent, implying an undercount of total Mexican immigrants of 6-8%. With these
caveats in mind, we turn to an overview of the occupation landscape in the United States
and the relative position of Mexicans, compared to other various, racial ethnic groups
based on descriptive statistics.
Figure 1 shows the occupational distribution in the U.S. in the year 2000 based on
1-digit occupation group aggregates by racial/ethnic groups. The data suggest that a
higher proportion of Hispanics (including Mexicans) are in service, farming,
construction, and production occupations. Differences by country of origin also surface
in Figure 2. There, we note that the predominance of Hispanics in farming, construction,
and production can be attributed mostly to the disproportionate presence of Mexicans in
those occupations. These patterns are reinforced if we condition the Hispanics on
whether they are immigrants (they were not born in the U.S) in Figure 3. For example,
whereas in Figure 2, we note that 13.3 percent of Mexicans are in professional
occupations, conditioned on being an immigrant, the percentage falls to 7.5 percent in
Figure 3.
We compute a composite index of socioeconomic status to assess the quantitative
meaning of each occupation. This composite index is adapted from the methodology of
Sicherman and Galor (1990), whereby we derive a score or an ordinal scale from
regression analyses of wages and the human capital requirements of the job. Ranging
from 0 to 100, the scores represent the socioeconomic standing of a particular
occupation in the universe of detailed occupations of all individuals in the labor force.
The average socioeconomic score across all 475 occupations reported in the
Census is 34.8. (Non-Hispanic white males have an average score of 37). In Table 1, we
report the respective average scores for 23 major occupational categories, by decreasing
socioeconomic status order. This table also shows the relative concentration of Mexican
immigrants in each occupation grouping, compared to the whole labor force. The results
show that a relatively lower proportion of Mexicans are in occupations that fall within the
professional categories that include management, education, training and library, business

9

and financial operations, and computer and mathematical science. These occupations tend
to have the highest socioeconomic scores, ranging from 36 to 61. By contrast, Mexicans
are overrepresented in building and grounds cleaning, food preparation and serving
occupations, and farming occupations. These occupations score very low in terms of
socioeconomic status.
Figure 4 reports the average socioeconomic status scores of occupations by
immigrant cohort. We note that in general, the occupational status scores decline with
successive cohorts, which is consistent with the idea that immigrants tend to “assimilate”
overtime, that is, be in occupations with status more similar to natives’. Even so, Mexican
immigrants have relatively lower scores, irrespective of the entry cohort, compared with
other Hispanic groups. For example, Mexicans who have been in the country for less than
5 years are employed in occupations with a score of 17 on average. Mexicans who have
been in the country for 30 years or more are employed in occupations with an average
score of 30, which is below the average for U.S-born workers. Table 2 reports the top 20
detailed occupations where “new” Mexican immigrants went into over the last 3 decades,
in 1980, 1990 and 2000. Over 60 percent of “new” Mexican immigrants are in similar
occupations with each successive period considered. These suggest that occupational
mobility may be more limited for Mexican immigrants (Toussaint-Comeau, 2006).

V.

Empirical Results
Table 3 reports the results from first stage regressions that test the strength of the

relationship between Mexican occupation density and the inflow of Mexicans with their
proposed determinants. The results suggest that the occupation density as well as the
penetration of Mexicans in different occupations is positively related with lagged or past
occupation distributions from previous decades. The results also suggest that the task
intensity of an occupation is correlated with Mexican labor supply into the occupation.
The higher the “manual” or “routine” task intensity of an occupation, the higher is
Mexican density in the occupation. Higher “abstract” task intensity of an occupation is
significantly negatively correlated with the propensity of “new” Mexican immigrants to
penetrate the occupation.
Table 4 shows the impact of Mexican immigrant occupation concentration on

10

average wages, based on OLS estimates. The OLS results suggest a negative relationship
between the presence of Mexicans in an occupation and average wages in the occupation,
overall. The impact of an increase in Mexican immigrants on the wages of natives is
significant for the most recent census year of 2000, but not for previous decades. Since
Mexican immigrants tend to be disproportionately in low wage occupations, it is likely
that the OLS estimates overstate the negative effect.
We turn our attention to whether “inflow” of “new” Mexican immigrants, post
1990—a proxy for the labor supply shock to an occupation—affected wages in the 1990s
for natives. To that effect, we report both OLS and IV estimates in Table 5. The results
are consistent in both OLS and IV estimates, that is, inflows of “new” Mexican
immigrants appeared to have had a small negative impact on wages for natives. The fact
that both the OLS and the IV are consistent suggests that the negative OLS coefficient is
not entirely due to the fact that Mexican immigrants are disproportionately found in lowwage occupations.
In Table 5, we also condition the model specification on three different skill level
to test whether the occupational composition of Mexican immigrants, impact differently
wages of natives with different skill sets. We classify as “low skill” those occupations
whose average wages of workers are less than high school; “medium-skill” consists of
those whose average education of workers is high school; and “high skill” occupations
are those with average workers having college education or college degrees. The results
suggest that the inflow of post 1990 Mexican immigrants is significantly negatively
correlated with wages for those in “medium-skill” occupations, that is, those with high
school level education. We found no statistically significant impact on natives in “low
skill” occupations, or those in “high skill” occupations.7
The finding that Mexican immigrants have no significant impact for the “low
skill” occupations, where they have strong concentration, but have some significant

7

We also considered a specification where we take the first difference of wages over 1990 and 2000 to test
whether the inflow of Mexicans affected the rate of growth of wages for workers in different skill level
occupations. The results suggest that there is a positive correlation between Mexican immigrants and wage
growth for natives in “low-skill” occupations (with less than high school education), and those in “high
skill” occupations. By contrast, the wages for “meidum-skill” natives, with an average high school
education is negatively impacted by inflow of Mexican immigrants. None of these effects, however, were
found to be statistically significant.

11

impact on “medium-skill” occupation groups where their relative concentration is much
more smaller is again puzzling. As proposed in Card and Lewis, part of the explanations
may be that Mexican immigrants are much closer substitutes to natives in those
“medium-skill” occupation subsets. We submit that an additional possibility may be
“spill over” effects from Mexican immigrants’ inflow in “low skill” occupations. It is
possible that native workers reallocate from “low-skill” occupations to “medium-skill”
ones, resulting into crowding out or greater wage pressure in “medium skill” occupations.
To begin (crudely) investigating this possibility, we considered an analysis of change in
employment for natives. We ran an OLS model specification where we regress the
growth in employment in each of the three occupation groups, respectively, for natives as
a function of the entry of “new” Mexicans in the U.S. The findings suggest that
employment of natives in “medium-skill” occupations where the average worker has a
high school education increases in response to Mexican inflows from a previous period
into the labor market in the U.S. We found no significant relation between the inflow of
Mexican immigrants from a previous period and changes in employment of natives in
“low-skill” occupations, or “high skill” occupations.

VI.

Conclusion
In summary, the results suggest that the impact of Mexican immigrants has

become more significant in more recent years, consistent with the increasing importance
of Mexicans in the labor force. Contrary to what one would expect, Mexican immigrants
have no significant impact on wages at the “low-skill” occupation groups, where they
tend to dominate. We propose that one factor may be that greater task specialization
among native and Mexican workers at the very low-skill level occupations mitigate the
impact of Mexicans on wages at the very bottom of the occupation lather. We found
consistent with previous research by Card and Lewis (2005), that Mexican immigrants
have a significant (negative) impact on wages for natives in occupations with high school
level education requirements. Native workers may be potentially readjusting their labor
supply into “medium-skill” occupations, where they have a relative comparative
advantage (in communication for instance). At this stage, of the analysis, it is however
too tentative to suggest that the apparent wage pressures for natives in “medium-skill”

12

occupations is directly linked with Mexicans, given their relative low presence in those
occupations. A combination of other factors is also likely to come in place. This remains
an area ripe for future research.

Figure 1: Occupation Distribution by
Race/Ethnicity

Hispanics tend to have lower wages than Whites, and slightly lower wages than
50

Percent

40
30
20
10
0

Source: 2000 PUMS

Prof.

Service

Sales

NH White
NH Black

Farming

Constr. Production

NH Asian
Hispanic

13

Figure 2: Occupation Distribution by Hispanic Ethnicity

30
25

Percent

20
15
10
5
0

Prof.

Source: 2000 PUMS

Service

Sales

Mexican

Farming

Constr. Production

P. Rican

Cuban

Figure 3: Occupation Distribution by Immigrant Status

30

Percent

25
20
15
10
5
0

Prof. Service Sales FarmingConstr.Production

Source: 2000 PUMS

Mex.Imm.

PR Imm.

Cub.Imm.

14

Table 1: Concentration of Mexican Immigrants Relative to the Labor force

Socioeconomic
Index Score
61
54
52
51
49
49
45
44
42
39
37
36
33
30
27
26
24
24
22
18
17
14

Occupation Categories
Education, Training and Library
Management
Business and Financial Operations
Computer and Mathematical Science
Life, Physical, and Social Science
Architecture and Engineering
Community and Social Services
Arts, Design, Entertainment, Sports and Media
Legal
Sales
Protective Services
Healthcare
Installation, Maintenance, and Repair
Office and Administration Support
Construction and Extraction
Production
Healthcare Support
Transportation and Material Moving
Personal Care and Service
Building and Grounds Cleaning
Food Preparation and Serving
Farming, Fishing, and Forestry

Percent of labor force
5.3
8.2
3.9
2.2
0.9
1.9
1.4
1.9
1.0
11.5
1.9
4.2
3.9
15.5
5.8
8.8
2.1
6.4
2.9
3.7
5.6
0.9

Percent of Mexican
immigrants
1.3
2.7
0.9
0.3
0.2
0.4
0.4
0.6
0.1
6.1
0.5
0.6
3.8
6.9
14.1
19.5
1.2
9.8
2.3
11.4
10.1
6.9

15

Figure 4: Socioeconomic Status of Occupations
by Immigrant Cohort
Males
MEXICAN IMMIGR
<=5 years

17
18

6-10 years

21

10-20 years

24

20-30 years

30

>30 years
P. RICAN IMMIG
<=5 years

27
27
28

6-10 years
10-20 years

31

20-30 years

34

>30 years
CUBAN IMMIG
<=5 years

28
30
32

6-10 years
10-20 years

38

20-30 years

46

>30 years
OTHER HISP
<=5 years

22
23

6-10 years

26

10-20 years

32

20-30 years

39

>30 years

0

10

20

30

40

50

Average Score

16

Table 2: Detailed occupations where "new" Mexican immigrants go to
1980
1990
2000
Construction laborers

Miscellaneous agricultural workers

Miscellaneous agricultural workers

Miscellaneous agricultural workers

Chefs and head cooks

Production workers all other

Chefs and head cooks

Construction laborers

Construction laborers

Grounds maintenance workers

Grounds maintenance workers

Electrical electronics and
electromechanical assemblers

Carpenters
Dishwashers

Production workers all other
Electrical electronics and
electromechanical assemblers

Chefs and head cooks
Rail-track laying and maintenance
equipment operators

Painters construction and
maintenance

Dishwashers

Welding soldering and brazing
workers

Production workers all other

Counter attendants cafeteria food
concession and coffee shop

Dishwashers

Electrical electronics and
electromechanical assemblers

Carpenters

Grounds maintenance workers

Drywall installers ceiling tile install-ers
and tapers
Janitors and building cleaners

Carpenters

Roofers

Rail-track laying and maintenance
equipment operators

Counter attendants cafeteria food
concession and coffee shop

Carpet floor and tile installers

Painters construction and
maintenance

First-line supervisors/ managers of
production and operating workers

Janitors and building cleaners

Sewing machine operators

Sewing machine operators

Counter attendants cafeteria food
concession and coffee shop

Roofers

Grinding lapping polishing and
buffing machine tool setters
operators and tenders

Rail-track laying and maintenance
equipment operators

Drywall installers ceiling tile installers and tapers

Industrial truck and tractor operators

Rail-track laying and maintenance
equipment operators

Waiters and waitresses

Packers and packagers hand

Metalworkers and plastic workers all Driver/sales workers and truck
other
drivers

Painters construction and
maintenance

Waiters and waitresses

Rail-track laying and maintenance
equipment operators

Driver/sales workers and truck
drivers

Automotive service technicians and
mechanics

Driver/sales workers and truck
drivers

Janitors and building cleaners

17

Table 3: First Stage Regressions
Determinants of Mexican Occupation Concentration and Penetration
Dependent Variables

Mexican Density in
occup in 2000

Independent Variables
Mexican density in occup, 1990
Mexican density in occup, 1980
lagged Mexican inflow: post1980

0.065***
0.048***

Task intensity: manual-eye, hand,foot
Task intensity: routine
Task intensity: abstract

0.205***
0.149***
-0.345***

ln(New Mexican
"inflow" in occup,
post1990)

(0.009)
(0.13)
1.48***
(0.76)
(0.47)
(0.45)

(0.215)

0.023
0.013
-0.051***

(0.033)
(0.023)
(0.024)

Table 4: OLS estimates of the Impact of Mexican Immigrants on average level of wages

Average wages, all

Mexican Occup density
control for educ and age
control for year
Rsquare
N

pulled crosssection
-0.001***
(0.0004)
yes
yes
0.5758
14745

2000
-0.03***
(0.001)
yes
no
0.3926
4730

1990
-0.013***
(0.0003)
yes
no
0.402
5186

Average wages,natives

1980
-0.006
(0.01)
yes
no
0.3173
4829

pulled crosssection
-0.005
(0.005)
yes
yes
0.5686
14745

2000
-0.002*
(0.01)
yes
no
0.3875
4730

1990
-0.003
(0.004)
yes
no
0.3849
5186

18

1980
0.001
(0.001)
yes
no
0.3136
4829

Table 5: The Impact of inflow of "new" Mexican Immigrants
average Wages for all

OLS

all skill
all skill
ln(inflow of Mexican, post 1990) -0.096*** -0.021***
control for education, and/or age
no
yes
Rsquare
0.2202
0.6758
N
1904
1895

All skill
-0.08
yes
0.6688
1207

2SLS IV
medium
low skill
skill
high skill
-0.07
-0.109***
-0.02
yes
yes
yes
0.4719
0.2663
0.4781
439
567
201

All skill
0.099
(0.073)
yes
0.588

medium
skill
high skill
-0.116**
0.125
-0.061
(0.170)
yes
yes
0.2007
0.2187

Average Wages for Natives

ln(inflow of Mexican, post 1990)
control for education, and/or age
Rsquare

all skill
-0.011***
(0.004)
yes
0.6603

low skill
-0.131
(0.106)
yes
0.1904

19

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