E P I B R I E F I N G PA P E R
ECONOMIC POLICY INSTITUTE
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FEBRUARY 4, 2010
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BRIEFING PAPER #255
IMMIGRATION AND WAGES
Methodological advancements confirm
modest gains for native workers
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Executive summary
In the ongoing debate on immigration, there is broad agreement among academic economists that it has a small but
positive impact on the wages of native-born workers overall: although new immigrant workers add to the labor supply,
they also consume goods and services, which creates more jobs.
The real debate among researchers is whether a large influx of a specific type of worker (say, workers with a particular level of education or training) has the potential to have a negative impact on the wages of existing workers of that
same type. Some research argues that immigrant competition is quite costly to certain groups of native-born U.S. workers, while other research finds that native workers—even those who have levels of education and experience similar to
new immigrants—may actually reap modest benefits from immigration.
We begin this paper with a review of the scholarly
literature on immigration’s effect on wages, focusing on
TA B L E O F CO N T E N T S
recent methodological advancements. We then use CurExecutive summary
rent Population Survey (CPS) data from 1994 to 2007 to
Introduction
conduct our own empirical analysis of immigration’s efBasic trends in immigration and wages 4
A brief look at the recent advancements in
fect on wages over this period, incorporating these recent
the research 9
methodological advancements. Our analysis finds little
Estimates of the effect of immigration on wages
evidence that immigration negatively impacts native-born
Conclusion
Appendix A: Data
workers.
Appendix B: Methodology
A key result from this work is that the estimated effect
Appendix C
of immigration from 1994 to 2007 was to raise the wages
of U.S.-born workers, relative to foreign-born workers, by
XXXFQJPSH
0.4% (or $3.68 per week), and to lower the wages of foreignborn workers, relative to U.S.-born workers, by 4.6% (or
&$0/0.*$10-*$:*/45*565&t)453&&5 /8t46*5& &"45508&3t8"4)*/(50/ %$tt888&1*03(
$33.11 per week). In other words, any negative effects
of new immigration over this period were felt largely by
the workers who are the most substitutable for new
immigrants—that is, earlier immigrants.
Additional key results from this analysis:
t For workers with less than a high school education,
the relative wage effect of immigration was similar
to the overall effect. U.S.-born workers with less
than a high school education saw a relative 0.3%
increase in wages (or $1.58 per week), while foreignborn workers with less than a high school education
saw a relative 3.7% decrease in wages (or $15.71 per
week). In other words, immigration among workers with
less than a high school degree served to lower the relative
wages of other immigrant workers with less than a high
school degree, not native workers with less than a high
school degree.
t The wages of male U.S.-born workers with less than
a high school education were largely unaffected by
immigration over this period, experiencing a relative
decline of 0.2% due to immigration (or $1.37 per
week). Female U.S.-born workers with less than a
high school education experienced a relative increase
in wages of 1.1% due to immigration ($4.19 per week).
t Around 3% of the increase from 1994 to 2007 in
wage inequality between workers with less than a high
school degree and workers with a college degree or
more can be attributed to immigration.
t This analysis finds no evidence that young workers in
particular are adversely affected by immigration.
t While the methodology used in this paper does not
allow for a racial breakdown of the effect of immigration on U.S.-born workers in different education
groups, we find that the overall effect of immigration
on wages is similar for white non-Hispanic U.S.-born
workers (+0.5%) and black non-Hispanic U.S.-born
workers (+0.4%) .
t From 1994 to 2007, the effect of immigration on
wages did not vary greatly over periods of very
different labor demand, in part, because immigra& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
tion flows respond strongly to the conditions of
the U.S. economy.
t An analysis of the four states with the highest immigration over this period—California, Florida, New
York, and Texas—revealed some interesting departures
from the national average. In these states, like at the
national level, the overall relative effect of immigration was positive on native workers. However, some
subgroups in these states fared worse—particularly
male workers with less than a high school degree.
Introduction
In the ongoing debate over immigration policy in the
United States, the impact of immigrants on the wages
of native-born workers has been a central point of disagreement. There is broad agreement among academic
economists on one point: that immigration has a small
but positive impact on the wages of native-born workers overall. Although new immigrant workers add to
the labor supply, they also consume goods and services,
creating more jobs. In other words, as the labor force expands (as it is always doing, due to both native population growth and immigration), the economy adjusts and
expands with it, and average wages are not hurt.
The actual heart of the debate is whether a large influx
of a specific type of worker (say, workers with a particular level of education or training) has the potential to
have a negative impact on the wages of existing workers
of that type. Some parties in the debate argue that immigrant competition is quite costly to some native-born
U.S. workers, particularly workers with low levels of education, among whom immigrant inflows have been relatively high. Others argue that a simple supply/demand
framework may lead to that conclusion, the real world is
more complicated. In fact, native workers who have similar levels of education and experience to new immigrants
may even reap modest benefits from immigration.
This more-nuanced research has gained sway in recent
years. It argues that it is not simply the increased supply
of one group of workers that determines outcomes for
another group. Were that so, then there would be little
to argue about: a disproportionate increase in the supply
of foreign-born workers of a certain type would lower
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the wages of native-born workers who are also of that
type. Instead, the characteristics of the added workers,
and the specific role they play in the economy, make a
big difference.
In the language of economics, it matters a great deal
whether immigrant workers are substitutes for or complements to native-born workers. The terms refer to how
employers use workers in the production of their goods
and services. If native workers are indistinguishable in
this process from immigrants—if they are substitutes—
it follows that a large influx of immigrant labor may hurt
natives’ earnings prospects. But if natives and immigrants
fulfill different roles in the production process, then they
may play complementary roles, and it is less likely that
the supply shock in one group will hurt the other group,
and it may in fact help them.
The economic literature, as described below, finds
evidence to support both of these scenarios, and is thus
somewhat ambiguous. This analysis, which uses Current
Population Survey (CPS) data from 1994 to 2007 and
incorporates recent advancements in the methodology
used to estimate the effect of immigration on relative
wages, finds little evidence of negative impacts on subgroups of workers.
Note that we are only able to look at the effect
on native wages of increases in foreign-born workers.
Foreign-born workers may be naturalized U.S. citizens,
permanent residents, temporary visa-holders, refugees,
or undocumented workers. While naturalized U.S. citizens
are identified in the CPS, if a foreign-born worker is
not a citizen, it is impossible to determine whether he
or she is a permanent resident, temporary visa-holder,
refugee, or undocumented worker. This unfortunately
limits the policy relevance of the research presented
here, since we are unable to determine the effect of various
subgroups of foreign-born workers on native labor
market outcomes. We cannot, for example, answer the
question of whether the H1B temporary visa program is
suppressing the wages of high tech workers, or whether
undocumented farm workers are suppressing wages in
agriculture. What we estimate is the effect of increases
in the foreign-born labor supply on the relative wages
of native-born workers overall and by education level,
gender, and age. In this analysis, we find little evidence
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of large negative impacts, though we acknowledge that
this may be masking very different outcomes in certain
localities, industries, and occupations.
The methodology used in this analysis is explained in
detail below. Note that we do not estimate the absolute
effect of immigration on wages—instead, throughout this
paper, we estimate the effect of immigration on the wages
of subgroups of workers relative to other subgroups. A
key result from this work is that the estimated effect of
immigration from 1994 to 2007 was to raise the wages
of U.S.-born workers, relative to foreign-born workers,
by 0.4% (or $3.68 per week), and to lower the wages of
foreign-born workers, relative to U.S.-born workers, by
4.6% (or $33.11 per week). In other words, any negative
effects of new immigration over this period were felt largely
by those workers who are the most substitutable for new
immigrants—earlier immigrants.
Additional key results from this analysis:
t For workers with less than a high school education,
the relative wage effect was similar to the overall effect.
U.S.-born workers with less than a high school education saw a relative 0.3% increase in wages, which
translates into an increase in weekly wages of $1.58
for this group, while foreign-born workers with less
than a high school education saw a relative 3.7%
decrease in wages, or $15.71 per week. In other words,
the surge in immigration among workers with less than
a high school degree served to lower the relative wages
of other immigrant workers with less than a high school
degree, but not native workers with less than a high
school degree. This story is retold in each education
category—U.S.-born workers see small positive relative wage effects and foreign-born workers see sizeable
negative relative wage effects.
t
The wages of male U.S.-born workers with less than a
high school education were largely unaffected by immigration over this period, experiencing a relative decline
of 0.2% due to immigration, or $1.37 per week. Female
U.S.-born workers with less than a high school education experienced a relative increase in wages of 1.1% due
to immigration, or $4.19 per week.
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t Around 3% of the increase from 1994 to 2007 in
wage inequality between workers with less than a high
school degree and workers with a college degree or
more can be attributed to immigration.
t This analysis finds no evidence that young workers in
particular are adversely affected by immigration.
t While the methodology used in this paper does not
allow for a racial breakdown of the effect of immigration on U.S.-born workers in different education
groups, we find that the overall effect of immigration
on wages is similar for white non-Hispanic U.S.-born
workers (+0.5%) and black non-Hispanic U.S.-born
workers (+0.4%).
t Immigration flows respond to the conditions of the
U.S. economy. From 1994 to 2000, when labor
demand was very high and job growth averaged 2.5%
per year, 941,000 immigrant workers entered the
United States annually. From 2000 to 2003, when
labor demand was weak and employment declined
0.5% per year, immigration flows plummeted to
342,000 new immigrants per year. From 1994-2000,
a period of high labor demand and high immigration, immigration increased the relative wages of
U.S.-born workers without a high school degree
by 0.02% annually. From 2000-03, a period of
low labor demand and low immigration, immigration decreased the relative wages of U.S.-born workers
without a high school degree by 0.04% annually. The
fact that the relative effect of immigration on wages
does not vary greatly over periods of dramatically
different labor demand offers some limited evidence
that the immigrant-flow response to labor demand in
the United States helps to smooth the effects of immigration on native wages across periods of strength and
weakness in the U.S. labor market.
t An analysis of the four states with the highest immigration over this period—California, Florida, New
York, and Texas—revealed some interesting departures from the national average. In these states, the
overall relative effect of immigration was positive
on native workers, around 0.7%, which was higher
than the overall effect on native workers nationally,
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which was 0.4%. However, some subgroups in these
high immigrant states fared worse—particularly male
workers with less than a high school degree. Research
by Jeffrey Passel and D’Vera Cohn at the Pew Research
Center (Passel et al. 2009) could perhaps shed some
light on this finding. In particular, their work shows
that unauthorized immigrants make up a particularly
large portion of the workforce in these four states
relative to other states. Since, as shown in their work,
unauthorized immigrants are more likely than other
workers to be male and also more likely than other
workers to be without a high school degree, a larger
inflow of unauthorized immigrant workers, who are
easily exploited by employers, may put downward
pressure on the wages of similar native workers in
these states, a pressure that is largely masked in estimates at the national level.
Basic trends in
immigration and wages
Figure A shows the share of the U.S. population between
1900 and 2007 that is foreign-born. In 1910, the peak
immigrant share of the last century, immigrants made up
14.7% of the U.S. population. The immigrant share
declined dramatically, to 4.7%, over the six decades from
1910 to 1970. In the last 40 years, however, immigration
has been on a steady upward climb—by 2007, 12.6% of
the population was foreign born.
As immigrant flows have surged in the last few
decades, interest in the effect of immigration on the labor
market outcomes of native workers has, unsurprisingly,
increased dramatically.
This section focuses on the 14-year period from
1993 to 2007. The data used are from the Current
Population Survey (CPS), which started tracking immigration status in 1994. (Because respondents are asked
information about the previous year, data since 1993
are available. A full description of the data used is given
in Appendix A.)
Figure B shows the immigrant share of total hours
worked each year. In 1993, immigrants contributed 9.9%
of total hours worked in this country; by 2007, immigrants were contributing 15.8%. This increase was driven
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FIGURE A
Foreign-born population as a share of total U.S. population, 1900 to 2007
2007: 12.6%
SOURCE: 900-90 data from Bureau of the Census “We the American...Foreign Born”; 1995-2004 data from Bureau of the Census Foreign Born
Population Annual Data Tables; 2005-07 data from American Community Survey Tables.
FIGURE B
Immigrant share of total hours worked each year, 1993 to 2007
1993: 9.9%
2007: 15.8%
SOURCE: EPI analysis of CPS data.
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FIGURE C
Immigrant share of total annual hours worked by gender, 1993 to 2007
2007: 17.3%
Male
1993: 10.7%
Female
2007: 13.8%
1993: 8.9%
SOURCE: EPI analysis of CPS data.
by the addition of 9.6 million foreign-born workers over
this period.
Gender
There have been increases in both female and male
immigration: from 1993 to 2007, 3.8 million female
immigrant workers and 5.8 million male immigrant
workers were added to the U.S. workforce. Figure C
shows the immigrant share of total hours worked among
men and women separately. Immigrants make up a somewhat larger share of the male workforce, and the difference
had been growing up to 2004. Since then, the difference
has narrowed slightly. By 2007, immigrants made up
13.8% of the labor supply among women and 17.3% of
the labor supply among men.
Education levels
The inflow of immigrants has been unequal across detailed
education categories, a fact of key importance in the debate
on the labor market effects of immigration. Figure D
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shows the immigrant share of total hours worked among
workers with less than a high school degree, a high school
degree but no additional schooling, some college training
but no college degree, and a college degree or more. Immigrants make up a much larger and faster-growing share
of the less-than-high-school category in comparison to
other education categories. The immigrant share among
workers with less than a high school degree rose from
28.4% in 1993 to 47.5% in 2007, while the immigrant
share among workers with a college degree or more rose
from 9.9% to 14.8% from 1993 to 2007.
It is important to note that because workers with
less than a high school degree make up a small (and
shrinking) portion of the labor force (9.9% in 2007),
high immigrant shares in this category do not actually
represent a disproportionate number of new immigrants
relative to other categories. And similarly, since workers
with a college degree make up a relatively large (and growing)
portion of the labor force (32.8% in 2007), low immigrant
shares in this category represent a surprisingly large number
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FIGURE D
Immigrant share of total annual hours worked by level of education, 1993 to 2007
2007: 47.5%
Less than high school
2007: 14.8%
College
High school
2007: 14%
Some college
2007: 9.3%
SOURCE: EPI analysis of CPS data.
of new immigrants. From 1993 to 2007, there was an increase of 2.2 million immigrants with less than a high school
degree, an increase of 2.5 million with exactly a high school
degree, an increase of 1.4 million with some college training,
and an increase of 3.5 million with a college degree.
Table 1 gives, by education category, the percentage
increase from 1993 to 2007 in hours worked that was due
to new immigrants (or the increase from 1993 to 2007 in
hours worked by immigrants relative to the total hours
worked by immigrants and natives in 1993). Immigration
led to a 21.2% increase in total labor supply among workers
with less than a high school degree, an 11.9% increase
among those with a college degree, and much smaller percentage increases among workers with education levels in
between. That is, immigration patterns into the United
States are marked by high immigration at very low levels
TA B L E 1
Percentage increase in hours worked due to immigration by education, 1993 to 2007
Increase in hours worked
due to immigration
Less than high school
High school
Some college
College
Increase in hours worked
due to immigraion
)JHITDIPPMPSMFTT
.PSFUIBOIJHITDIPPM
SOURCE: EPI analysis of CPS data.
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FIGURE E
Average real weekly wages of native workers by level of education, 1993-2007
College
Some college
High school
Less than high school
SOURCE: EPI analysis of CPS data.
of education, high immigration at very high levels of education, and much less immigration between those poles.
The right half of Table 1 shows a further aggregation
by education. When breaking workers into just two education categories, high school or less and more than high
school, we see that immigration has been quite balanced
over these two categories over the last 15 years, with “high
school or less” seeing an increase in labor supply of 10.2%
due to immigration, and “more than high school” seeing
an increase of 8.3%. Perhaps surprisingly, immigration
over the last 15 years has been roughly the same among
“low schooling” and “high schooling” workers.
Figure E shows the average real (inflation-adjusted)
weekly wage from 1993 to 2007 by education category.
Native-born workers with less than a high school degree
made an average of $456 per week in 1993, and that increased by less than 8% to $489 per week in 2007. Workers
with a college degree or more made an average of $1,129
per week in 1993, and that increased by nearly 25%
to $1,404 per week in 2007. Workers with a college
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degree saw much greater gains over this period than any
other group—in 1993, the average college-educated worker
made 2.5 times what a worker without a high school
degree made, but by 2007, the ratio had risen to 2.9.
One question addressed in this paper is how much of this
increased inequality can be attributed to immigration.
Figure F shows average weekly wages for native workers
over time by gender for just two education groups, workers
with less than a high school education and workers with a
college degree or more. In both education categories over
this period, the female average weekly wage is roughly
two-thirds of the male average weekly wage. Inequality
has increased among both men and women—in 1993, the
average college-educated female made 2.6 times what a
female worker without a high school degree made, and
the ratio was 2.5 among men. By 2007, the ratio had risen
to 3.0 for both. The methodology used later in this
paper will allow us to examine the effects of immigration
on wages by gender, including its impact on inequality
among both men and women.
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FIGURE F
Average weekly wages for native workers:
gender and education level comparison, 1993-2007
College, Male
College, Female
Less than high school, Male
Less than high school, Female
SOURCE: EPI analysis of CPS data.
A brief look at the recent
advancements in the research
There is currently no consensus in the economic literature
on the effect of immigration on the labor market outcomes of various groups of native workers. In fact, there
is considerable disagreement among reputable researchers. Raphael et al. (2007) provide a very readable review
of the literature on the effects of immigration on native
labor market outcomes, and a more detailed review of the
literature pertaining to the two advancements in the literature discussed below can be found in Ottaviano and
Peri (2008).
Area vs. national
Broadly speaking, there have been two main methodological
strategies for studying the effect of immigration on the
wages of native workers. The “area approach,” dominated
by the work of David Card, exploits the fact that there are
large differences across regions of the United States in the
relative size of the immigrant population. Essentially, this
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approach compares the wages of native workers in U.S.
metropolitan areas with small immigrant inflows to the
wages of native workers in U.S. metropolitan areas with
large immigrant inflows. Research using this approach
(see, for example, Card (2001) and Card (2007)) generally
finds very modest, and sometimes modestly positive,
effects of immigration on the wages of native workers,
including workers with low levels of education.
The second main approach in this literature is the
“national approach.” Scholars using this approach often
contend that it is impossible to suitably account for the
fact that there may be movement of capital and nativeborn labor between metropolitan areas in response to
immigration, and that this means that an analysis of the
effect of immigration on native wages must use nationallevel data. This approach is dominated by the work of
George Borjas, and tends to use a production function
framework that combines workers of different skills,
estimates the degree of substitutability between workers
of different skills using national data, and simulates the
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impact on wages of relative labor supply shifts due
to immigration. Historically, research using this approach
(see, for example, Borjas, Freeman, and Katz (1997) and
Borjas (2003)) found relatively large negative effects of
immigration on the wages of native workers, especially
those with low levels of education.
Two advancements in
the national approach
Until recently, that is where the main divide in the literature stood, with researchers using the “area approach”
finding no or little effect of immigration on the wages
of native workers, including workers with low levels of
education, and with those researchers using the “national
approach” finding a relatively large negative effect, especially on workers with low levels of education. However,
in the last couple of years there have been two important
advancements in the literature on immigration and wages
that help shed light on the differences in results between
these two approaches. Both are somewhat complicated to
derive but are extremely intuitive conceptually. This paper
provides the intuition; see Ottaviano and Peri (2008) for
a more detailed explanation.
Both advancements have to do with what economists
refer to as “elasticities of substitution.” In a labor market
context, essentially what an elasticity of substitution measures is how substitutable one type of labor is for another.
For example, consider a firm that hires graphic designers.
To the employer, left-handed designers may be perfectly
substitutable for right-handed designers, meaning that the
elasticity of substitution between left-handed and righthanded designers is very large or infinite. Conversely, a
graphic designer who does not know the graphic design
software the firm uses is likely not very substitutable for
one who does, so that the elasticity of substitution between
these two types of workers is small. In other words, the
more substitutable two types of workers are, the higher
the elasticity of substitution between them.
Elasticities of substitution have enormous importance
in estimates of changes in labor supply on wages (which
include estimates of the effect of increased immigrant
labor supply on native wages). If two types of workers are
very substitutable for one another—if the elasticity of substitution between them is high—then an increase in the
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labor supply of one type can cause a reduction in wages
not just in that type but also in the type that they are substitutes for. On the other hand, if two types of workers are
not good substitutes, then an increase in the labor supply
of one type will likely not cause a reduction in wages of
the other. In fact, it may increase the wages of the other if
the two types of workers are complements in some way so
that as the supply of one type increases, the demand for
the other type increases as well (for example, an increase
in the supply of taxi drivers may cause an increase in
demand for dispatchers, and therefore bid up the wages
of dispatchers).
Immigrant/native substitutability. The first recent
advancement in the immigration and wages literature
has been the identification of a small but detectable level
of imperfect substitution between immigrant and native
workers who have the same levels of education and experience (see, for example, Ottaviano and Peri (2008),
Card (2009), Manacorda et al. (2005) and D’Amuri et al.
(2008)). In other words, immigrant and native workers
with the same levels of education and experience are not
perfectly substitutable. This may arise, for example, among
workers with low levels of education if native workers are
more likely to be concentrated in jobs that require strong
English skills and immigrant workers are more likely to
be more concentrated in jobs that do not (for example,
waitstaff versus line cooks). Previous national approach
estimates of the effect of immigration on wages have
assumed that immigrants and natives of similar education
and experience levels are perfectly substitutable. Correctly
characterizing the elasticity of substitution between immigrants and natives is of enormous importance, because, as
explained above, if natives and immigrants are perfectly
substitutable, an increase in immigration in a particular
education/experience class will tend to reduce the wages
in the entire education/experience class, including native
workers in that class. However if, as has been shown to
be the case, immigrants and natives within the same education/experience class are imperfect substitutes, then an
increase in immigration in a particular class will have a
strong adverse effect on the wages of earlier immigrants in
that class—since they are direct substitutes, or competitors—but have a smaller effect on the native workers
in that class.
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Substitutability by educational attainment. The second recent advancement has been the application to the
immigration and wages literature of something that was
already accepted as fact in the rest of the labor economics
literature: that the elasticity of substitution is not constant
across education categories. To understand the intuition
behind this, consider a broad grouping of workers by education level: workers with a high school education or less
and workers with more than a high school education. The
labor economics literature has long established (see, for example, Katz and Murphy (1992)) that these two groups
are not good substitutes for each other—workers with a
high school degree or less tend to do different jobs than
workers with more than a high school degree.
Now consider a subgrouping of the high school or
less category into two additional groups—workers with
no high school degree and workers with exactly a high
school degree. There is a much greater degree of substitutability between these two types of workers. Workers
with less than a high school degree are more likely to do
similar jobs as those with exactly a high school degree.
These comparisons suggest that the elasticity of substitution between two education categories varies depending
on which two education categories are being considered.
Previous national approach estimates of the effect of
immigration on wages have essentially assumed that the
elasticity of substitution between workers in two different
education categories is the same regardless of which pair of
education categories is being considered. But it turns out
that incorporating different elasticities of substitution
between different pairs of education categories is enormously important to estimates of the effect of immigration
on native wages. The main problem with ignoring this
point arises with what it implies—that workers without a
high school degree and workers with a high school degree
have very low levels of substitutability. This is strongly
refuted by the literature (see, for example, Ottaviano and
Peri (2008) and Card (2009)). Both of these studies show
empirically that there is a relatively high degree of substitutability between workers without a high school degree
and workers with exactly a high school degree.1
Ignoring this fact distorts the estimated effects of
immigration on workers without a high school degree,
since it suggests that an increase in immigration among
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workers without a high school degree affects only workers
without a high school degree, which is a very small portion of the labor force (9.9% in 2007), so that essentially
the entire impact of “less-than-high-school” immigration is assumed to be felt by the relatively small number of
“less-than-high-school” workers. If, on the other hand,
we recognize that workers without a high school degree
are relatively substitutable for workers with a high school
degree, then the impact of “less-than-high-school” immigration is more diffused across the much larger share
of the workforce that has a high school degree or less
(38.7% in 2007), greatly reducing the impact on the
least-educated American workers.
These new innovations in the national approach
literature essentially solve the earlier divide between the
national approach and the area approach. When the key
elasticities of substitution are correctly accounted for in
the national approach methodology, the results using
that approach come in line with the results from the
area approach, namely that the effects of immigration on
native workers is modest, including the effect on native
workers with low levels of education.
Estimates of the effect
on immigration on wages
Methodology for computing this effect
This analysis computes the effect of immigration on wages
using an approach outlined in Ottaviano and Peri (2008),
which is based on standard practice in the national
approach literature on immigration and wages but incorporates the two advancements described above. Within
that general approach, we use consensus estimates from
the labor economics literature of the relevant elasticities,
along with our own calculations of changes in immigrant
and native labor supply using the CPS data described in
Appendix A. We then simulate the impact of immigration
on relative wages using these components. As is standard
with this approach, there are no confidence intervals for
the estimates; the methodology employed here does not
easily lend itself to calculating standard errors. To ensure
that sample sizes are large enough for our estimations of
the effect of immigration on wages, we pool 1993 and
1994 data for a “year 1994” sample, and pool 2006 and
2007 data for a “year 2007” sample. We then calculate
●
1" ( &
the impact of immigration over the resulting 13-year
period. A more detailed description of the methodology
is given in Appendix B.
It is important to note that the methodology employed
here estimates only the relative wage effects of immigration
(for example, how immigration affects native high school
dropouts compared to other workers,) and not the absolute
wage effects of immigration. The framework we use (and
that is used in the “national approach” more generally)
assumes that the economy adjusts to absorb new immigrants
and that the overall real wage effect of immigration in the
long run is zero. Note that the results in, for example, Table
2 show that the overall impact is zero; this is an assumption,
not an estimate. Our estimates are in the relative impacts
found between subgroups—in how much immigration
affects one subgroup of workers compared to another.
range, and that the substitutability of natives and immigrants within the same education/experience class is at
the high end of the range, both of which, as discussed
above, will give the gloomiest outlook for the effect of
immigration on the wages of natives with low levels of
schooling. Conversely, the column “high” assumes that
the substitutability of workers in different education
categories is at the high end of the range, and that the
substitutability of natives and immigrants within the same
education/experience class is at the low end of the range,
both of which will give the rosiest outlook for the effect
of immigration on the wages of natives with low levels of
schooling. The column “typical” assumes a typical set of
elasticities, neither at the high end or low end of their
respective ranges, and these columns represent the estimates
we believe to be the most accurate.
Looking first at the “All” category, we find that the
effect of immigration from 1994 to 2007 was to reduce
the wages of workers with less than a high school degree,
relative to other workers, by somewhere between -1.4%
and -0.4%, most likely by -0.7%. But looking at the breakdown by immigration status, we find that the burden of
these losses is shouldered entirely by foreign-born workers,
who saw a relative reduction in wages of -3.7%, compared
to a modest increase of 0.3% among native workers. In
other words, the surge in immigration among workers with
less than a high school degree served to lower the wages of
earlier immigrant workers with less than a high school degree,
not native workers with less than a high school degree.
Education
Table 2 presents the impact of immigration from
1994-2007 on the wages of U.S.- and foreign-born
workers separately and for all workers combined. For each
group (U.S.-born, foreign-born, and all) there are three
columns representing different sets of elasticities. The different sets reflect the fact that for each relevant elasticity,
there is a range of estimates in the labor literature. (The
ranges are given in Appendix B, along with an explanation of how these elasticities are generally estimated.) The
column “low” assumes that the substitutability of workers
in different education categories is at the low end of the
TA B L E 2
Impact of immigration on wages from 1994 to 2007 by education level
U.S.-born
Foreign-born
All
Low
High
Typical
Low
High
Typical
Low
High
Typical
Less than high school
High school
Some college
College
0.3%
0.6
0.4
-3.2
-6.0
-4.6
0.0
0.0
0.0
All
SOURCE: EPI analysis of CPS data.
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
●
1" ( &
TA B L E 3
Results using incorrectly characterized elasticities
U.S.-born
Foreign-born
All
Less than high school
High school
Some college
College
All
0.1%
-0.9%
0.0%
SOURCE: EPI analysis of CPS data.
Mischaracterized elasticities
This story is retold in each education category—the
impact on overall wages in each category is modest, but
when looking at breakdowns by immigration status, we
find that immigrants in the category see sizeable negative
effects and natives see small positive effects. Looking at
all education categories combined, we find that the overall effect of immigration from 1994-2007 was to reduce
the wages of the foreign-born population by 4.6%,
relative to an increase in the wages of the U.S.-born
population of 0.4%.
Table 3 demonstrates the importance of correctly characterizing the elasticities. This table shows what the estimates would be if we were (incorrectly) to assume that
the elasticity of substitution is constant across education
categories, and that immigrants and natives within the
same education/experience class are perfect substitutes.
Results in the table would suggest that the burden of
increased immigration over these 13 years was shouldered
largely by workers without a high school degree, and in
TA B L E 4
Impact of immigration on wages by education level, 1994-2007
U.S.-born
Foreign-born
All
Low
High
Typical
Low
High
Typical
Low
High
Typical
Less than high school
High school
Some college
0.6
0.4
-3.2
-6.3
-4.7
0.0
0.0
0.0
Female
College
All
0.3
Male
Less than high school
High school
Some college
College
All
0.3
0.6
0.4
-3.1
-5.9
-4.5
0.0
0.0
0.0
SOURCE: EPI analysis of CPS data.
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
●
1" ( &
particular that native workers in this category have
experienced large negative wage impacts. What this exercise
demonstrates is that the large negative values found in the
traditional “national” approach to estimating the effect
of immigration on wages are due primarily to incorrect
characterizations of key elasticities.
Gender
Table 4 shows the results (once again with appropriately
characterized elasticities) separately for men and women.
Looking first at the overall effect for U.S.-born workers by
gender, we find that both men and women have seen a relative increase in wages of 0.4% due to immigration from
1994 to 2007, compared to a loss by earlier immigrants of
around 4.6%. However, the breakdowns by education are
somewhat different. U.S. women with lower levels of education gain more from immigration than female workers
with higher levels of education, whereas U.S. men with
lower levels of education see modest declines compared to
male workers with higher levels of education (who have
seen modest increases). In particular, we find that the
effect of immigration from 1994 to 2007 was to increase
the wages of U.S.-born women with less than a high
school degree, relative to other workers, by somewhere
between 0.6% and 1.7%, most likely by 1.1%, and to
change the wages of U.S.-born men with less than a high
school degree, relative to other workers, by somewhere
between -1.5% and 0.5%, most likely by -0.2%.
Table 5 can shed some light on this difference. Table 5
is similar to Table 1, which shows increased hours worked
from 1993 to 2007 due to immigration, but it is broken out
by gender. While the increase in hours worked due to
immigration is fairly balanced between “less than or equal
to high school” and “more than high school,” there are
gender differences. Among women, there have been slightly
greater increases in hours in the more-educated group than
in the less-educated group, whereas among men, there have
been somewhat greater increases in hours in the lesseducated group than in the more highly educated group.
These differences help explain why native women with
lower levels of education gain due to immigration (1.1%
increase in wages), whereas native men with lower levels of
education see modest declines (-0.2% decrease in wages).
Inequality
The estimates presented above show that immigration
from 1994 to 2007 had a modest positive effect on the
overall wages of both male and female native workers (0.4%
relative increase). Within that overall change, women with
less than a high school education experienced a nontrivial
TA B L E 5
Impact of immigration on wages from 1994 to 2007 by gender and education
Increase in hours worked
due to immigration
Increase in hours worked
due to immigraion
Female
Less than high school
High school
Some college
College
)JHITDIPPMPSMFTT
.PSFUIBOIJHITDIPPM
Male
Less than high school
High school
Some college
College
)JHITDIPPMPSMFTT
.PSFUIBOIJHITDIPPM
SOURCE: EPI analysis of CPS data.
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
●
1" ( &
TA B L E 6
How much of the increasing wage inequality from 1994 to 2007
can be explained by immigration?
U.S.-born
Growth in less than high school wages
Foreign-born
All
All
Female
Male
All
Female
Male
All
Female
Male
Growth in college wages
Difference in growth rates
Growth in less than high school wages
due to immigration
Growth in college wages due to immigration
Difference in growth due to immigration
Portion of difference in growth rates
that is due to immigration
SOURCE: EPI analysis of CPS data.
increase (1.1%), while women with a college degree saw
no change due to immigration, so immigration likely
decreased inequality among women over this period. On
the other hand, men with less than a high school education experienced a modest decline (-0.2%), while men
with a college degree saw a modest increase (0.7%), so
immigration likely was a factor in increasing inequality
among men over this period.
Table 6 uses the estimates of the relative wage impacts
of immigration to quantify how much of the growth over
this period in wage inequality between workers with less
than a high school degree and workers with a college degree
or more can be explained by immigration. The table shows
the difference in wage growth rates from 1994-2007 for
workers with less than a high school degree and workers
with a college degree or more, and it shows the difference
in the effect of immigration on wages for both groups (the
latter taken from the “typical” estimates in Tables 2 and
4, above). The final row shows the difference in growth
rates due to immigration divided by the difference in wage
growth rates—in other words, it gives the share of
the difference in wage growth rates that is due to immigration. This is the measure we use of the amount of
increased inequality over this period that can be attributed
to immigration.
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
For native workers, only 0.1 percentage point of the
17.2 percentage-point difference in growth rates between
“less than high school” and “college or more” can be
explained by immigration. However, this overall effect
masks differences by gender. Immigration decreased inequality among native women—the differences in growth
rates between the two education groups would have been
7.5% higher in the absence of female immigration. Among
men, 0.9 percentage points of the 23.1 percentage-point
difference in growth rates between the two education
categories can be explained by immigration.
For foreign-born workers of both genders, but particularly for women, immigration caused larger wage
declines among college workers than among less than high
school workers, so new immigration reduced inequality
among immigrants. However, because immigration is nevertheless concentrated at the high end and low end of the
overall wage distribution, increased immigration increases
overall wage inequality. We find that immigration contributed 2.8% of the increase in inequality overall, though
the effect was concentrated among men. Among women,
the difference in wage growth rates between the two education groups would have been 6.1% higher without immigration, but immigration contributed 5.8% of the overall
increased inequality among men. In sum, immigration has
●
1" ( &
TA B L E 7
Impact of immigration on wages from 1994 to 2007 by gender, education, and age
U.S.-born
Foreign-born
All
All
Female
Male
All
Female
Male
All
Female
Male
Less than high school
All
18-27
28-37
38-47
48-57
High school
All
20-29
30-39
40-49
50-59
Some college
All
22-31
32-41
42-51
52-61
College
All
24-33
34-43
44-53
54-63
All
All
Age Group 1
Age Group 2
Age Group 3
Age Group 4
SOURCE: EPI analysis of CPS data.
not been a significant contributor to wage inequality among
native workers, but about 3% of the overall increase in inequality from 1994 to 2007 between college educated workers
and high school dropouts can be attributed to immigration.
Age
One question that arises in the debate on immigration
and wages is the effect of immigration on the wages of
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
young workers, especially young men with low levels of
education. Table 7 breaks down the effect of immigration
on wages by age category and gender. Here and for the
rest of the paper, unless otherwise noted, results are shown
for the “typical” set of elasticities. Also note that, as is
common practice in the labor economics literature,
definitions of age categories are slightly different across
education categories to reflect the fact that, for example,
●
1" ( &
TA B L E 8
Education shares by age, gender, and race for non-Hispanic native workers , 2007
White non-Hispanic U.S.-born workers
All
Black non-Hispanic U.S.-born workers
All
Female
Male
All
Female
Male
Less than high school
High school
Some college
College
SOURCE: EPI analysis of CPS data.
a worker with only a high school education is generally
available to start work four years earlier than a worker with
a college degree. The categories thus represent 10-year
groupings of “potential labor market experience.”
The results show that in fact older native workers face
bigger impacts of the increasing foreign-born workforce
over this period. Native workers with 31 to 40 years of
potential labor market experience (age group 4) saw a
modest decline of 0.3% in wages relative to native workers
with one to 10 years of potential experience (age group 1)
who saw a modest increase in wages due to immigration of
0.8%. The overall pattern generally holds across education
categories, in particular, for native workers without a high
school degree, 18-27-year olds of both genders gained due
to immigration while it was middle-aged workers—workers
age 38-47—who saw modest declines. These results
provide no evidence that younger workers in any category
are being particularly hard-hit by immigration relative to
older workers.
Race
The methodology used in this paper does not allow for
a breakdown of the effect of immigration on U.S.-born
workers in different education groups separately by race.
However, using the estimated wage effects of immigration
by education and experience group, we can aggregate the
results separately for white and black native workers to
look at the overall impact of immigration on these two
groups. The differences in the overall effects by race will
essentially reflect the fact that educational breakdowns are
different for blacks and whites. Education breakdowns
for 2007 for native blacks and native whites are given in
Table 8. They show that native blacks have somewhat
lower educational attainment than native whites, with
a higher percentage of black native workers than white
native workers not having a high school degree (9.9% vs.
5.3%), and a lower percentage of black native workers
than white native workers having a college degree (21.4%
vs. 36.3%). However, since (as Table 4 shows) the positive
TA B L E 9
Aggregate impact of immigration on wages from 1994 to 2007 of native workers by race
All
White non-Hispanic U.S.-born workers
Black non-Hispanic U.S.-born workers
Low
High
Typical
Low
High
Typical
Female
Male
SOURCE: EPI analysis of CPS data.
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
●
1" ( &
impact of immigration does not rise monotonically across
education groups, it is not a priori obvious what the
aggregate impact will be.
The overall impacts by race are given in Table 9. They
show that in the aggregate, immigration has essentially
the same relative effect on native blacks as it has had on
native whites—a small positive relative impact on wages.
These results reflect the fact that there is not a great deal
of variation across education categories in the relative
impact of immigration on wages, so even though blacks
and whites have different education breakdowns, in
aggregate the effect of immigration on wages is similar.
Does the impact of immigration on
wages vary with overall labor demand?
Over the period from 1994 to 2007, labor demand varied
widely—in particular, from 1994-2000, the labor market
was much stronger than it was in the later period. From
1994-2000, job growth averaged 2.5% per year, whereas
from 2000 to 2003, which captures the period of job loss
associated with the recession of 2001, employment
declined 0.5% per year. From 2003 to 2007, employment
growth picked up somewhat, growing at an average of
1.4% per year.
Immigration flows, unsurprisingly, respond to the
conditions of the U.S. economy: from 1994 to 2000,
941,000 immigrant workers entered the United States each
year, but from 2000 to 2003, the number plummeted to
342,000, and then picked up somewhat to an average of
502,000 per year from 2003 to 2007.
Was the impact of immigration on wages different
over these three periods of very different overall labor
demand? Table 10 shows the impact of immigration on
wages by gender and education separately for these three
TA B L E 1 0
Average annual impact of immigration on wages for
periods of different overall labor demand
U.S.-born
Foreign-born
All
All
Female
Male
All
Female
Male
All
Female
Male
High school
Some college
College
All
Less than high school
High school
1994-2000
Less than high school
2000-03
Some college
College
All
2003-07
Less than high school
High school
Some college
College
All
SOURCE: EPI analysis of CPS data.
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
●
1" ( &
periods. It should be noted that unlike the other tables in
this paper, which report the impact over the entire period
from 1994-2007, this table gives the average impact per
year over each period for ease of comparison.
The results show that the main effect of the different
periods is felt by immigrants themselves, who faced much
larger negative effects during the period of greater immigration in the 1990s. For native workers overall, there
was not large variation in the impact of immigration over
the three periods, though the gains were greatest during
the 90s, since immigration was higher. For workers with
less than a high school education, there were some small
differences: these workers experienced a modest relative
decline of 0.04% per year due to immigration during the
downturn of the early 2000s, compared to a modest relative increase in the other periods (0.02% in the 1990s and
0.04% from 2003-07). By gender, the differences were
slightly larger—male workers with a high school education or less saw a relative decline of 0.1% per year due
to immigration from 2000-03, whereas women with a
high school education or less experienced a relative gain
of 0.04% per year over this period.
The fact that the relative effect of immigration on
wages does not vary dramatically over periods of dramatically different labor demand offers some limited evidence
that immigrant-flow response to labor demand in the
United States helps to smooth the effects of immigration
on native wages across periods of strength and weakness
in the U.S. labor market. While we do not have data that
allow us to conduct our simulation on the current economic downturn, this analysis suggests that it is likely that
the relative impact of immigration on the wages of native
workers during the 2008/2009 recession will not be out of
line with the relative impact experienced in earlier periods.
The effect of immigration
in high-immigration states
Immigrant flows vary widely by state. (Table C1 in
Appendix C shows immigrant flows by state from 1993
to 2007.) Here we examine the four states that have seen
the largest increase in numbers of immigrant workers:
California, Florida, New York, and Texas. Together, these
four states represent 46% of all increases in immigrant
workers over this period, though they made up only 32%
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
of all workers in 2007. California saw an increase of 1.7
million immigrants from 1993 to 2007, Florida saw
824,000 new immigrants, New York 811,000, and Texas
1.1 million. Because these are the four largest states, we
are able to conduct an analysis separately for each of these
states without running into major sample size issues.
Table 11 shows the results by education category
and gender for these four states. In these high immigrant states, the overall effect of immigration is similar to
the effect at the national level—small positive effects for
native workers and nontrivial negative effects for earlier
immigrant workers. By education category, however, there
is some variation. In particular, in California and Texas,
immigration has led to a decline in the relative wages
of U.S.-born workers with less than a high school education—by 1.6% in California and by 1.7% in Texas.
These effects were concentrated among men, with males
without a high school education in California seeing an
estimated relative wage decline of 2.9% due to immigration, and males without a high school education in Texas
seeing an estimated relative wage decline of 1.8% due
to immigration (while “less than high school” women
gained 0.8% in California and lost 0.6% in Texas). Native
workers without a high school education were essentially
unaffected as a group in New York (relative decline of
0.1%), but there was a gender imbalance, with “less than
high school” women gaining 1.7%, while “less than high
school” men lost 1.3%. In Florida, workers with less than
a high school education gained 1.2% due to immigration,
but those gains were entirely among women, who saw a
2.9% relative increase in wages.
In sum, in these very high immigrant states, the
overall relative effect of immigration is positive on native
workers, around 0.7%, which is higher than the overall
effect on native workers nationally, which was 0.4%. Thus,
on average, native workers in these high immigrant
states gain somewhat more than the national average
due to immigration. However, some subgroups in these
high immigrant states fare worse, as described above,
particularly male workers with less than a high school
degree. Research by Jeffrey Passel and D’Vera Cohn at the
Pew Research Center (Passel et al. 2009) could perhaps
shed some light on this finding. Their work shows that
unauthorized immigrants make up a large portion of the
●
1" ( &
TA B L E 1 1
Impact of immigration on wages from 1994 to 2007 in states by gender and education
U.S.-born
Foreign-born
All
All
Female
Male
All
Female
Male
All
Female
Male
High school
Some college
College
All
Less than high school
High school
United States
Less than high school
California
Some college
College
All
High school
Some college
College
All
Less than high school
High school
Florida
Less than high school
New York
Some college
College
All
Less than high school
High school
Texas
Some college
College
All
SOURCE: EPI analysis of CPS data.
workforce in these four states relative to other states. They
estimate that in the United States in 2008, unauthorized
immigrants made up 5.4% of the labor force. However,
they found that in California, for example, 9.9% of the
workforce was an unauthorized immigrant, which was
the largest percent of the workforce in any state except
Nevada. Since, as shown in their work, unauthorized immi& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
grants are more likely than other workers to be male and
also more likely than other workers to be without a high
school degree, a larger inflow of unauthorized immigrant
workers, who are easily exploited by employers, may put
downward pressure on the wages of similar native workers
in these states, a pressure that is largely masked in estimates
at the national level.
●
1" ( &
The impact of immigration
on wages in dollar terms
This paper has presented results in terms of percentage
relative wage gains or losses due to immigration. However, because there is a great deal of variation in average
weekly wages for different subgroups, a similar percentage
effect of immigration on wages may have very different
effects by subgroup in terms of actual dollars gained or
lost. (Table C2 in Appendix C gives the average weekly
wages for 2007 for all of the subgroups in Table 11.) Based
on average weekly wages in 1994, along with the relative
wage effect of immigration in Table 11, Table 12 gives, in
dollar terms, the relative effect of immigration from 1994
to 2007 on the average weekly wages in 2007.
Table 12 shows that at the national level, the effect
of immigration from 1994 to 2007 on wages of native
TA B L E 1 2
Dollar impact of immigration on wages from 1994 to 2007
U.S.-born
Foreign-born
All
Female
Male
All
Less than high school
High school
Some college
College
All
All
Female
Male
All
Female
Male
United States
California
Less than high school
High school
Some college
College
All
Florida
Less than high school
High school
Some college
College
All
New York
Less than high school
High school
Some college
College
All
Texas
Less than high school
High school
Some college
College
All
SOURCE: EPI analysis of CPS data.
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
●
1" ( &
workers was modest—it raised the relative average weekly
wage of native-born U.S. workers by $3.68. However, the
impact varied somewhat across education category and
gender. For workers without a high school education,
immigration increased the weekly wages of women by
$4.19 and reduced the weekly wages of men by $1.37.
Earlier immigrants, on the other hand, experienced large
declines due to new immigration. On average, immigration from 1994 to 2007 reduced the relative weekly wages
of immigrants by $33.11.
For high immigration states, some of the effects on
native workers were more dramatic. In California, male
workers with less than a high school education saw a
relative decline in weekly wages of $18.52 due to immigration, while in Florida, New York, and Texas, their
losses were $2.13, $8.12, and $9.42, respectively. Female
workers without a high school education in California,
Florida, and New York saw increases of $3.52, $9.69,
and $7.12, respectively, while they experienced declines
of $2.10 in Texas.
Conclusion
The methodology used in this paper follows the latest
developments in the “national approach” to analyzing
the effect of immigration on wages. In contrast to the
“area approach,” the national approach has traditionally
found relatively large negative effects of immigration on the
wages of native workers, especially native workers with low
levels of education. However, when recent developments
in the national-approach methodology are incorporated,
the results are very similar to those found in the area
approach—that recent immigration has had little effect
on the relative wages of native workers, including workers
with low levels of education. A key finding in the results
is that the workers who stand to lose the most from new
immigration are those workers most substitutable for new
immigrants, namely earlier immigrants.
To those unfamiliar with the scholarly literature on
the effect of immigration on native labor market outcomes, the findings of little relative impact on native wages
may come as a surprise. The immigrant share of total
hours worked rose from 9.9% in 1993 to 15.8% in 2007.
How is it possible that economists have been unable to
find more evidence of adverse effects on native workers?
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
An important thing to keep in mind is that the labor
force is growing all the time. All else equal, more people,
including more foreigners, do not mean lower wages or
higher unemployment. If they did, every time a baby
was born or a new graduate entered the labor force, they
would hurt existing workers. But new workers do not just
have supply-side impacts, they also affect demand. Those
new graduates buy food and cars and pay rent. In other
words, while new workers add to the supply of labor, they
also consume goods and services, creating more jobs. An
economy with more people does not mean lower wages
and higher unemployment, it is simply a bigger economy.
Just because New York is bigger than Los Angeles does not
in and of itself mean workers in New York are worse off
than workers in Los Angeles.
However, a large influx of a particular type of worker
has the potential to have a negative impact on the wages
of existing workers who are also of that type; workers who
are highly substitutable for new immigrants stand to lose
when there is a large influx of new immigrants. The immigrant share of total hours worked by workers with less
than a high school education rose from 28.4% in 1993 to
47.5% in 2007. How is it that this has not caused large
negative effects on native-born workers with less than a
high school education?
There are two factors that largely shelter native-born
workers with less than a high school education from these
negative impacts. The first is their relatively high degree of
substitutability with workers with a high school education.
While these two types of workers are likely not perfect
substitutes, the fact that their substitutability is relatively
high means that the impact of an influx of less-than-highschool immigrants is not shouldered entirely by the 9.9%
of the U.S. workforce that has less than a high school degree,
but that it is to some extent diffused across the much
larger share of the workforce—38.7% in 2007—that has
a high school degree or less. This greatly reduces the
impact on the least-educated American workers.
The other key factor is that even when considering
workers within the same education/experience “class,”
native-born workers and immigrants are not perfect substitutes. In other words, substituting immigrant workers
for native workers who have the same level of education
and experience is possible, but limited due to the different
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characteristics of these two types of workers, including
fluency in English. The workers who are the most substitutable for new immigrants are earlier immigrants,
so this is the group that ends up shouldering much of
the impact of new immigration, rather than native-born
workers. Native-born workers in a given education/
experience “class,” on the other hand, can in fact be helped
by immigration, if, for example, their language advantage
means they are more likely to be given a supervisory role
when there is a large influx of immigrants with their same
general level of education and experience.
There are a few limitations of the research presented
in this paper that are important to mention. First, this
analysis looks at the effect of immigration on wages, not
on employment. However, the limited effect we find of
immigration on native wages suggests there is also likely
a limited effect on native employment. Second, the
approach used here does not allow for a separate estimation of the effect of immigration on different racial and
ethnic subgroups by education level. While the empirical
challenges are nontrivial, further research into the effect
of immigration on non-Hispanic black U.S.-born workers
by educational attainment is warranted. Third, we are
only able to look at the relative effect on native wages
of increases in foreign-born workers. Foreign-born workers
may be naturalized U.S. citizens, permanent residents,
temporary visa-holders, refugees, or undocumented workers.
If a foreign-born worker is not a naturalized citizen, it is
impossible to determine with our data whether he or she
is a permanent resident, temporary visa-holder, refugee,
or undocumented worker. This unfortunately limits the
policy-relevance of the research presented here, since we
are unable to determine the effect of various subgroups of
foreign-born workers on native labor market outcomes.
Better data are needed to further investigate the effect of
different types of foreign-born workers, in particular
unauthorized immigrants and temporary visa holders.
Finally, this paper estimates the long-run effect of
immigration on wages, assuming the economy has fully
adjusted to absorb new immigrants and that the overall
real wage effect of immigration is zero. It is important
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to note that, since it takes time for capital to adjust to
increases in the labor force, a large unexpected increase
in the labor force will likely depress wages temporarily,
something not accounted for here. Ottaviano and Peri
(2008) find, for example, a 0.3% long-run relative wage
increase of workers with less than a high school education
due to immigration from 1990-2006, but a 0.7% shortrun relative wage decrease. To give an idea of the speed of
the effect of capital adjustment, they find that after five
years, about 40% of the distance between the short-run
effects and long-run effects has been eliminated, with the
medium-term effect of immigration from 1990-2006 on
the wages of workers with less than a high school degree
being a decrease of 0.4%.
Except perhaps for male U.S.-born workers with no
high school degree in California (where we find immigration from 1994-2007 has led to a 2.9% relative real
wage decline), we find little evidence that recent immigration has had sizeable adverse effects on the wages of
U.S.-born workers. Instead, it has generally had modest
positive effects. Declining job quality for the least-educated
American workers is due to a host of factors aside from
immigration, including declining unionization rates,
the eroding real value of the minimum wage, and trade
practices that expose U.S. workers with low levels of education to competition from much lower wage workers
around the globe. While it remains crucial to reform our
broken immigration system, a larger economic agenda
that will spur growth, reduce economic insecurity, and
provide broadly shared prosperity is more central to
improving their economic status.
—We thank Lawrence F. Katz of Harvard University,
Ray Marshall of the University of Texas at Austin, and
David Dyssegaard Kallick of the Fiscal Policy Institute for
extremely helpful comments and discussions. We also thank
Anna Turner for excellent research assistance. We gratefully
acknowledge funding from the Carnegie Corporation of
New York and the Evelyn and Walter Haas, Jr. Fund. The
statements made and views expressed are solely the responsibility of the author.
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Appendix A: Data
The data used are from the March supplement to the Current Population Survey, which asks detailed demographic and
labor market questions about the previous year. We are using March supplement data because with these data we can
compute the total hours worked in a year for each worker, which offers the most comprehensive measure of labor supply.
Note that these data do not distinguish between documented and undocumented immigrants; survey respondents
are not questioned about their legal status. While undocumented immigrants are included in the survey sample, it is
widely considered likely that there is higher survey non-response among undocumented immigrants than among others
in the sample. In any event, we are unable to distinguish between the effects of documented and undocumented immigrant flows on native workers.
Following standard practice, we restrict the sample in the following way: 1) we restrict to workers who are at least 18
years old; 2) we define “potential labor market experience” as age minus 17 for workers without a high school degree,
age minus 19 for workers with exactly a high school degree, age minus 21 for workers with some college training but
no college degree, and age minus 23 for workers with a college degree or more, and restrict the sample to workers with
between one and 40 years of potential experience; and 3) we define annual hours worked as weeks worked in a year times
hours worked per week and drop people who have zero annual hours. When calculating average weekly wages, we further
restrict the sample to people who report positive annual wage and salary income. To compute average weekly wages,
we divide annual wage and salary income by weeks worked in a year, and calculate a mean weighted by the CPS person
weight times annual hours (in order to properly account for varying hours worked across workers).
To ensure that the sample sizes are large enough in each cell for our estimations of the effect of immigration on wages,
we pool 1993 and 1994 data for a “year 1994” sample, and pool 2006 and 2007 data for a “year 2007” sample. For the
section that conducts the impact analysis separately by time period (1994-2000, 2000-03, and 2003-07), we additionally
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pool 1999 and 2000 together for “year 2000” data and pool 2002 and 2003 together for “year 2003” data.
Appendix B: Methodology
We compute the effect of immigration on wages using an approach outlined in Ottaviano and Peri (2008), in which
they simulate the impact of immigration on wages based on a production function structure which combines workers
of different education and experience levels. There are two main education groups, “high school or less” and “more
than high school.” There are two education subgroups within each main education group, “less than high school,”
“exactly high school,” “some college,” and “college or more.” There are eight experience groups, 1-5 years, 6-10 years,
11-15 years, 16-20 years, 21-25 years, 26-30 years, 31-35 years, and 36-40 years.
Let wDbkjt be the average weekly wage of native workers in main education group b, education subgroup k, experience
group j, at time t, and similarly, let wFbkjt be the average weekly wage of immigrant workers in main education group b,
education subgroup k, experience group j, at time t. Let Fbkjt be the total hours worked by immigrants in main education
group b, education subgroup k, experience group j, at time t, and ∆Fbkjt be the change between the two periods in total
hours worked by immigrants in main education group b, education subgroup k, and experience group j. Let sFbkjt be the
share of total wages (both immigrant and native) in year t paid to immigrant workers in main education group b, education
subgroup k, and experience group j. Let sbkjt be the share of total wages in year t paid to workers in main education group
b, education subgroup k, and experience group j. The elasticity of substitution between the two main education groups is
given by sHL , the elasticity of substitution between two education subgroups is given by sbb , the elasticity of substitution
between workers within the same education subgroup with different experience levels is given by sEXP , and the elasticity of
substitution between immigrants and natives within the same education/experience group is given by simmi .
The percentage change in the wages of native worker with education level k and experience level j due to immigration
is given by equation (25) in Ottaviano and Peri (2008). Assuming long run effects (i.e., ignoring the term that accounts
for capital adjustment), it is
Similarly, the percentage change in the wages of immigrant worker with education level k and experience level j due to
immigration, assuming long run effects, is given by
All of the wage and hours terms in the above equations are calculated using CPS data as described in Appendix A. The
different sets of elasticities we use, presented in Table B1, are taken from the literature (see Ottaviano and Peri (2008)
and Card (2009) for detailed discussions). These elasticities of substitution are generally estimated by regressing the
relative wage between two groups on their relative labor supply, exploiting variation over time and (where applicable)
between education and/or experience categories. The intuition behind this methodology is the following: if an increase
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in the labor supply of group A relative to group B leads to very little decline in the wage of group A relative to group B,
then the two groups are highly substitutable, and the elasticity of substitution between them is high. Conversely, if an
increase in the labor supply of group A relative to group B leads to a large decline in the wage of group A relative to group
B, then the two groups are not good substitutes, and the elasticity of substitution between them is low.
Using the percentage wage changes due to immigration in each education/experience group identified above, we
aggregate to various levels (education, education by four experience groups, and overall) using sums weighted by the
share of total wages in each group, as outlined in Appendix A of Ottaviano and Peri (2008). For the aggregations by race,
we weight using wage shares by race.
To compute breakdowns of wage impacts by gender, we use the elasticities in Table B1 but calculate all other
components separately by gender. Finally, to compute breakdowns of wage impacts for the four high-immigration states,
TA B L E B 1
Elasticities
sHL
sHH
sLL
sEXP
simmi
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Low
High
Typical
Table 3
∞
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we use the elasticities in Table B1 but calculate all other components separately by state.
TA B L E C 1
Immigration by state
State
California
Immigrant
share of
workers,
1993
Immigrant
share of
workers,
2007
Increase in
number of
immigrant
workers
(thousands)
State
Immigrant
share of
workers,
1993
Immigrant
share of
workers,
2007
Increase in
number of
immigrant
workers
(thousands)
Iowa
Texas
Missouri
Florida
Kentucky
New York
Kansas
New Jersey
Arkansas
Louisiana
Illinois
New Mexico
Virginia
Nebraska
Connecticut
Mississippi
Georgia
Maryland
Arizona
North Carolina
Delaware
Idaho
Washington
Hawaii
Colorado
New Hampshire
Nevada
Massachusetts
Rhode Island
Ohio
Oklahoma
Pennsylvania
Washington, D.C.
Oregon
Alaska
Tennessee
South Dakota
Minnesota
Montana
Utah
Wyoming
Michigan
West Virginia
Wisconsin
Maine
Alabama
North Dakota
South Carolina
Vermont
Indiana
SOURCE: EPI analysis of CPS data.
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TA B L E C 2
Average weekly wages in 2007
U.S. Born
Foreign-born
All
All
Female
Male
All
Female
Male
All
Female
Male
United States
Less than high school
High school
Some college
College
All
California
Less than high school
High school
Some college
College
All
Florida
Less than high school
High school
Some college
College
All
New York
Less than high school
High school
Some college
College
All
Texas
Less than high school
High school
Some college
College
All
SOURCE: EPI analysis of CPS data.
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Appendix C
Endnotes
1.
The finding that high school graduates and high school dropouts
are close substitutes is a new historical phenomenon. It was not
true in the first half of the 20th century, when there was, instead,
a big divide in production between high school graduates and
those without a high school degree. The historical evidence can be
found in Chapter 8 of The Race between Education and Technology
(Goldin and Katz 2008).
References
Borjas, George. 1994. The economics of immigration. Journal
of Economic Literature. Vol. 32, No. 4, pp. 1667-1717.
Borjas, George. 2003. The labor demand curve is downward
sloping: reexamining the impact of immigration on the labor
market. Quarterly Journal of Economics. Vol. 118, No.4, pp.
1335-1374.
Borjas, George. 2006. Native internal migration and the labor
market impact of immigration. Journal of Human Resources.
Vol. 41, No. 2, pp. 221-258.
Borjas, George and Lawrence Katz. 2007. The evolution of the
Mexican-born workforce in the United States. In Borjas, George,
ed., Mexican Immigration to the United States. Cambridge:
National Bureau of Economic Research Conference Report.
Borjas, George, Jeffrey Grogger and Gordon Hanson. 2008.
“Imperfect substitution between immigrants and natives: a
reappraisal.” National Bureau of Economic Research, Working
Paper No. 13887. Cambridge, Mass.: NBER.
Borjas, George, Richard Freeman, and Larry Katz. 1997. How
much do immigration and trade affect labor market outcomes?
Brookings Papers on Economic Activity 1997. No. 1, pp. 1-90.
Card, David. 1990. The impact of the Mariel Boatlift on the
Miami labor market. Industrial and Labor Relation Review.
Vol. 43, No. 2, pp.245-257.
Card, David. 2001. Immigrant inflows, native outflows and
the local labor market impacts of higher immigration. Journal
of Labor Economics. Vol. 19, No. 1, pp. 22-64.
Card, David. 2007. “How immigration affects U.S. cities.”
CReAM Discussion Paper No. 11/07.
Card, David, and John DiNardo. 2000. “Do immigrant inflows
lead to native outflows?” National Bureau of Economic Research,
Working Paper No. 7578. Cambridge, Mass.: NBER.
Card, David. 2009. Immigration and inequality. American Economic Review. Vol. 99, No. 2, pp. 1-21.
& 1 * # 3 * & ' * / ( 1" 1 & 3 ● ' & # 3 6" 3 :
D’Amuri, Francesco, Gianmarco Ottaviano, and Giovanni Peri.
2008. “The Labor Market Impact of Immigration in Western Germany in the 1990s.” National Bureau of Economic Research,
Working Paper No. 13851. Cambridge, Mass.: NBER.
Friedberg, Rachel, and Jennifer Hunt. 1995. The impact of immigrants on host country wages, employment and growth. Journal of
Economic Perspectives. Vol. 9, No. 2, pp. 23-44.
Friedberg, Rachel. 2001. The impact of mass migration on the
Israeli labor market. Quarterly Journal of Economics. Vol. 116,
No. 4, pp. 1373-1408.
Goldin, Claudia, and Lawrence F. Katz. 2008. The Race Between Education and Technology. Cambridge, Mass.: Harvard
University Press.
Katz, Larry, and Kevin Murphy. 1992. Changes in relative wages
1963-1987: supply and demand factors. Quarterly Journal of
Economics. Vol. 107, No. 1, pp. 35-78.
Longhi, Simonetta, Peter Nijkamp, and Jacques Poot. 2005. A
meta-analytic assessment of the effect of immigration on wages.
Journal of Economic Surveys. Vol. 86, No. 3, pp. 451-477.
Marco, Manacorda, Alan Manning, and John Wadsworth.
2006. “The Impact of Immigration on the Structure of Male
Wages: Theory and Evidence from Britain.” IZA Discussion
paper No. 2352. Bonn, Germany.
Marshall, Ray. 2009. Immigration for Shared Prosperity: A Framework for Comprehensive Reform. Washington, D.C.: EPI.
Passel, Jeffrey S., and D’Vera Cohn. 2009. A Portrait of Unauthorized Immigrants in the United States. Washington, D.C.:
Pew Research Center.
Ottaviano, Gianmarco I.P. and Giovani Peri. 2006a. “Rethinking
the Effect of Immigration on Wages.” National Bureau of
Economic Research, Working Paper No. 12496. Cambridge,
Mass.: NBER.
Ottaviano, Gianmarco I.P. and Giovani Peri. 2007. “The Effect of
Immigration on U.S. Wages and Rents: A General Equilibrium
Approach.” CReAM Discussion Paper No. 13/07. London, UK.
Ottaviano, Gianmarco I.P. and Giovani Peri. 2008. “Immigration
and National Wages: Clarifying the Theory and the Empirics.”
Working Paper No. 14188. Cambridge, Mass.: NBER.
Peri, Giovanni, and Chad Sparber. 2008. “Task Specialization, Immigration, and Wages.” CReAM Discussion Paper No.
02/08. London, UK.
Raphael, Steven, and Lucas Ronconi. 2007. “The Effect of Labor
Market Competition with Immigrants on the Wages and
Employment of Natives: What Does Existing Research Tell Us?”
Working Paper. http://gsppi.berkeley.edu/faculty/sraphael/dubois-review-january-2007.pdf
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Mid-Term Exam Questions
You will answer a total of two (2) questions.
Everyone must answer question number one (1) and then pick one (1) of the two remaining
questions.
Each question is worth 15 points for a total of 30. There are no requirements for how much or how
little you write in order to answer each question. I'm looking for the right answer—logical and coherent
paragraphs and nothing more. So the length is totally up to you, whatever you think it takes to answer
each question and get full credit. (Note: Your answers should include good introductions and
conclusions!)
Q1: You must answer this question—15 Points.
Please explain how and why it is that in New Brunswick NJ, nearly all the workers employed by
temp agencies, warehouses, or light manufacturers are immigrant Latinos, and why are the jobs
so low paying?
Things to consider:
I am looking for an answer that encompasses what you know about the theories of migration (and how
they relate to this particular question) as well as everything we have discussed with regards to racialized
labor markets (how they are organized, what the conditions are like, and why employers organize them)
and anything else that we have discussed that would help you get the maximum number of points for this
question.
Pick one of the two remaining questions-(worth 15 Points)
Q2. In “Transnational Tortillas” the author explains how the employer organizes the work and controls
the workforces in the U.S. and Mexico. In short, she argues that in both places the employer uses “divide
and conquer" strategies to organize and control the workforces. Your task is to explain how these
divide and conquer strategies are applied by the management of Hacienda CA and Hacienda BA.
What does the employer do to ensure that the workers are divided and subservient? What are the
essential components of the strategies in both facilities?
Q3. What is "social distance" and what does social distance have to do with global supply chains, temp
agencies, low-wage labor markets, the "sweating" or "cheating system” and consumers like you and me?
This question is obviously based on last week's readings, videos and class discussion. That said, I
would strongly suggest that you do an outline of your answer before you do anything else!
Purchase answer to see full
attachment