 |
 |
I
am grateful
to Hans
Johnson, Jed
Kolko, Ethan
Lewis, David
Neumark, Steven
Raphael, Deborah
Reed and
participants to
several seminars
for helpful
comments. Benjamin
Mandel provided
extremely competent
assistance in
editing the
paper and
very valuable
comments. The views expressed
herein are
those of
the author(s)
and do
not necessarily
reflect the
views of
the National
Bureau of
Economic Research.
© 2007
by Giovanni
Peri. All
rights reserved.
Short sections
of text,
not to
exceed two
paragraphs, may
be quoted without explicit
permission provided
that full
credit, including © notice,
is given
to the
source.
ABSTRACT
|
As
of 2004 California employed
almost 30% of all foreign born
workers in the U.S. and was
the state with
the largest percentage of immigrants
in the labor force. It received
a very large number of uneducated
immigrants
so that two thirds of workers
with no schooling degree in
California were foreign-born in
2004. If immigration harms the
labor opportunities of natives,
especially the least skilled
ones, California was
the place where these effects
should have been particularly
strong. But is it possible that
immigrants
raised
the demand for California's
native workers, rather than harming
it? After all immigrants have
different
skills and tend to work in different
occupations then natives and
hence they may raise productivity
and
the demand for complementary production tasks and skills.
We consider workers of different
education and
age as imperfectly substitutable
in production and we exploit
differences in immigration
across
these
groups to infer their impact
on US natives. In order to isolate
the "supply-driven" variation
of immigrants
across skills and to identify
the labor market responses
of
natives we use a novel instrumental
variable
strategy. Our estimates use
migration by skill group to other U.S. states as instrument for migration
to California. Migratory flows
to other states, in fact,
share
the same "push" factors
as those to
California but clearly are
not
affected by the California-specific "pull" factors.
We find that between 1960
and 2004 immigration did
not
produce a negative migratory
response from natives. To
the
contrary,
as
immigrants were imperfect substitutes
for natives with similar education
and age we find that they stimulated,
rather than harmed, the demand
and wages of most U.S. native
workers.
Giovanni
Peri
Department
of Economics
University
of California, Davis
One
Shields Avenue
Davis,
CA 95616
and
NBER
gperi@ucdavis.edu
1
Introduction
|
In
the year 2004, California was home to almost 30% of all foreign-born individuals working in the U.S.;
in turn, these foreign-born
represented
roughly one third of the almost 15 million workers employed
in California, two thirds of
California workers without a
high school degree and almost
half of the California workers
with a doctoral degree. Many U.S.-born Californians
moved out of the state during
the nineties and job competition from
immigrants has sometimes been regarded as a key factor for
this outflow. It stands to
reason that if recent inflows
of immigrants indeed crowded out the labor market options
of U.S. natives, specifically
the low skilled ones, then
such an effect should have been particularly strong in California. But is it possible that immigrants actually
lifted California’s wages,
rather
than harming them? After all,
immigrants have different
skills
and tend to work in different occupations than natives;
they
could make natives performing
complementary production tasks
more productive, thus increasing the demand for those tasks!
The present study analyzes
the effect of the migratory
inflow on the employment,
population and wages of U.S.
natives in California, using
data from the decennial
U.S. Censuses and from the American Community Survey spanning the period 1960-2004. Our approach combines elements of a ”general equilibrium” (more structural) approach to immigration and
wages,
as proposed in recent national studies (Borjas 2003; Aydemir and Borjas 2007; Ottaviano and Peri, 2006) with the study of employment and inter-state migratory response of native workers typical of
the so called ”area approach” (exemplified in Card 1990,
2001, Lewis, 2005 and Borjas, 2006). As in Borjas (2003)
we consider labor as a differentiated input in production and we model the interactions between workers with different
education and age using a nested CES production function. As in Ottaviano and Peri (2006) we allow for imperfect substitution between native and foreign-born
workers within an education-age group (due to differences
in skills, occupational choices and job opportunities) and we estimate the elasticity
of substitution between natives and immigrants. The degree of substitutability between these two groups
is a key parameter to determine whether immigrants increase
or depress the demand for
native workers. For a large degree of substitutability between natives and immigrants, uneducated
immigrants mostly depress the demand for uneducated
natives and augment the
demand for highly educated natives.
However, for a smaller degree of substitutability between
natives and immigrants,
uneducated immigrants have a much smaller depressive
effect on (and may even increase) the demand for uneducated natives while
still increasing the demand
for more educated natives. As pointed out by the critics
(e.g. Borjas et al, 1997) of the ”area approach”
when focussing on a state economy
it is important to account
for the fact that any
labor market effect of
immigration can be ”diffused”
to other
states by out-migration
of native workers. We carefully account for this effect in our empirical
analysis. Moreover, by
focussing on California
over time, we are able
to use a new identification strategy that addresses the
problems of unobserved
demand shocks and measurement
errors; these are often
deemed responsible for
biased
estimates of the impact
of immigration on the
labor market outcomes
of natives in a state
(e.g. Aydemir and Borjas, 2006; Borjas, 2006). Specifically, we use immigration to the other U.S. states by
skill group over decades
as a reasonable instrument to proxy the ”push”-driven component of immigration to California by skill group and decade. While sharing the ”push” factors behind international migrations with California, the flows of foreign-born workers to other U.S. states are not affected by California’s specific pull factors (i.e. unobserved demand shocks). The intuition of such identifying assumption is as follows. Suppose that immigrants with a college degree were “pulled” to California in the 90’s by the boom in the high tech sector, which increased the demand for workers with their qualifications. This would be a “pull factor” specific to California. The same boom probably would also have
attracted (or reduced the
potential outflow of) natives in the same skill group.
It could thus create a positive correlation between foreign immigration and natives’
migration and wages–even if foreign
migrants compete with natives for the same jobs. Such pull, however, would not be shared by other states and hence the instrument would not capture it. On the other hand take the cases of the increased international
mobility
of the college-educated
Chinese middle-class or the worsened job outlook for young uneducated workers in Mexico during the nineties. Both are “push factors” that could increase immigration of some age-education groups to California (a large
receiver of Chinese and
Mexican migrants) as well as to other states. Push factors generate more migrants to California as well as to other states and are not related to changes in California’s local
demand for labor. Thus, how native employment
responded to those immigration changes would correctly estimate how immigrants affect natives’ employment opportunities–for a given local demand. The second purpose served by our instrument is
to
reduce the measurement error bias. As the measure of immigrants to other states is based on large national samples (excluding California), the instrument is also largely exempt from the measurement error affecting state-level measures of immigration by skill due to the
potentially small size of cells1. Hence, we have an instrument for the inflow of immigrants that is potentially uncorrelated (or weakly correlated)
with California-specific labor demand shocks and the measurement errors while still
correlated
with the supply-driven shocks to the composition of immigrants to California. This instrumental variables strategy
that
we adopt is novel
for the ”area” approach and it is an improvement on the ”national”
approach (e.g. Borjas, 2003) in that, while we
cannot rely on some natural experiment, we have a more sophisticated way of isolating supply-driven variations of immigrants going beyond the simple inclusion of education-age, education-year and age-year specific effects
(which we still include). The
rest of the paper is organized as follows: Section 2 presents the data and shows some statistics on the
skills of foreign-born and recent immigrants to California. Section 3 presents the production function used as framework to
estimate the effect of immigration on wages. The skill-structure defined in the production function
is used in the empirical estimations. Section 4 presents the identifying strategy and shows the migration and employment responses of California’s native workers
to immigration for the period 1960-2004. Section 5 1Recent work by Aydemir and Borjas (2006) analyzes the role of measurement
error in generating potential
bias in the estimates of the impact of
immigrants based
on local data. estimates the substitutability between U.S. and foreign born workers within education-age groups. Section 6 uses the estimated parameters to calculate the effects of immigrants on wages of natives (by education) for the 1990-2004 period. Section 7 concludes. 2 Immigration
to California: A Look at the Data The data we use are from the integrated public use microdata samples (IPUMS) of the U.S.
decennial Census and of the American Community Survey (Ruggles et al, 2005).
In particular, we use the
general (1%) sample for
Census 1960, the 1% state sample,
Form 1, for Census 1970, the 5% state sample for
the Censuses 1980 and 1990, the
5% Census sample for year 2000 and the 1/239 American Community Survey (ACS) Sample for the
year 2004.
As those are all weighted samples we use the variable “personal
weight”
to construct all the average and aggregate statistics relative
to California. We consider people aged 17 to 66
not living in group
quarters,
and we included them among the workers
if they worked at least
one week in the previous year and earned a positive amount in salary income. When using
wage data, we converted the current wages to constant wages
(in 2000
U.S. $)
using the CPI (Consumer Price Index)-based deflator across years. We define the four schooling groups
using the variable
that identifies the highest grade attended (called “HIGRADEG” in IPUMS)
for
census
1960 to
1980 while we use
the categorical variable (called “edu99”
in IPUMS) for censuses 1990 and 2000 and ACS 2004.
Age groups
are identified using
the variable
“AGE”. Finally, yearly wages
are based on the
variable for salary and income wage
(called
“INCWAGE” in IPUMS). Weekly wages
are obtained dividing that
value by the number of weeks
worked2. The
status of “foreign-born” is given
to those workers
whose place of birth
(variable “BPL”)
is
not
within the USA (or
its territories
overseas) and did
not have
U.S. citizenship at birth (variable
“CITIZEN”)3
Table 1
illustrates the
evolution of
the percentage
of foreign born
in
employment and population for
the period
1960-2004. Employment
is defined as
the
sum
of individuals aged
17 to
66
years old, not
residing in
group quarters, who worked at
least one week in the previous year. Population
is defined as the sum of individual between 17
and 66 years of
age not residing in
group quarters. We report
the figures for California as
compared to the corresponding
figures for the whole
U.S.A. First, note that
in
California the percentages of
foreign-born already began growing
in the
sixties, while in
the
U.S. as a
whole they
only began to
grow
during the seventies. During the
seventies,
eighties and nineties,
California
experienced
increases in the
share
of foreign-born
workers by about
7%
in each
decade,
with
similar rates
continuing after
the
year
2000;
in the whole
U.S.,
the
increases were
far
more
modest over
that period,
amounting
to
2-3%
per
year.
Second,
over
the
entire
period considered,
2For Census 1960 and 1970 only a categorical variable that measures weeks worked
exists, called ”WKSWRK2”. Individuals are assigned the middle value of the interval
in the variable. 3The variable CITIZEN is not available in Census 1960. For that
year we consider all people born outside the U.S. as foreignborn born. the
share of foreign-born workers
in employment was larger than
their share of population,
denoting higher
employment/population
ratios of immigrants relative
to natives; this was due in
part to their age distribution.
Finally, notice that the percentage of immigrants in California’s population
and employment as of 1980 is similar to the percentage of
immigrants
in population and employment for the nation in 2004. In terms of percentages, a
continuation of the present
trend would imply that the future of the nation may look like
the last 25 years of California’s experience. Moreover,
in addition to their percentages of population and employment, the distribution of foreign-born across
education levels in California
in 1980 is similar to that
for the whole nation in 2004. Table 2 shows the percentage
of foreign-born workers in California by education group between 1960 and 2004. Notice the higher concentration of
foreign-born among the low
(less than high school) and high (college or more) schooling levels and the lower concentration in
the intermediate education
levels. Notice that, as of 2004, two thirds of high
school
dropout workers in California were immigrants as well as
42% of Ph.D.’s, while only 20% of workers with some
college education but no
degree were not U.S. born. The distribution of immigrants,
predominantly at the two ends of the schooling spectrum,
will be dubbed ”U-shaped”. This U-shape is also a feature
of the national data;
Figure 1 shows the percentage
of foreign-born workers by education level in 2004, comparing California and
the whole U.S. One clearly
notices the same qualitative
U-shaped distribution,
but each bar is much higher for
California, denoting a
higher average percentage
of foreign-born. We need to go back to the year
1980 (see Table 2) to find
percentages of foreign
born across education groups
in California similar to the ones for the U.S. today:
back then, in California,
32% of high school dropouts,
12% of high school graduates,
10% of college
dropouts4
and 14% of college graduates
were foreign-born. The numbers
presented above are relative
to the ”stock” of foreign-born
living in California (or nationally).
The
more recent flow of immigrants
to California and to the U.S.
(1990-2004) also has a similar distribution over schooling.
Figure 2 shows the net growth
in employment due to immigrants
as percentage of initial employment by
education group for California
(light shaded columns) and for
the U.S. as a whole (dark shaded
columns). College
graduates, Masters and Ph.D.’s
flowed in much larger percentages of initial employment in the
group
than
college dropouts both in California and the whole U.S. At the opposite
end of the schooling spectrum, the
inflow of high school dropouts
was much larger as a percentage
of the group than inflow of
high school graduates. Overall, aggregating across groups, immigrants to California during the 1990-2004
period equaled 20%
of its total employment in
1990,
while in the U.S. as a whole
they were only 11% of initial employment. These aggregate
numbers provide a good sense
of how large immigration has been in California. The focus
of this paper is the effect
of immigration on the labor
market
outcomes of Californian workers.
It is
useful, therefore, to start by showing the behavior of native worker real wages during
the most recent fourteen 4For
brevity, and somewhat improperly,
we often use the term ”College
Dropouts” to indicate those
people who have some College
education but not a four-year
degree. years
of data (1990-2004); these
years correspond to the period
of largest immigration flows.
Figure 3 shows the
percentage
change in real wage for native workers, by education group,
in California (light shaded
columns) and in the U.S. as a whole (dark shaded columns)
for the 1990-2004 period. We
use real weekly wages calculated
as yearly wage and salary income
divided by weeks worked, and
convert to constant 2000 dollars by dividing for the Consumer Price Index deflator. First
of all, we notice that the
real wage changes across education
groups are very similar in
California compared to the whole
nation; the difference in real
wage growth between California
and
the rest of the nation was
never larger than 4% in any
group. In terms of magnitude
across education groups, high school dropouts’ wages
decreased in real terms over
the period by as much as 17%,
real wages
of
high school graduates were rather
stationary, while real wages
of college graduates and above experienced a substantial increase,
generally above 20%. Aggregating
across groups, the average real
wage grew by 10.7% in California
and by 9.7% in the U.S. as a whole, again denoting a similar performance (less than 0.1%
difference in
growth per year), with no apparent
wage “penalty” at all for the
high-immigration state of California.
California’s
closeness to the national average
in terms of wage dynamics over the last 15 years denotes substantial
integration of the Californian labor market with the rest of
the U.S. Implied are small costs
of moving that arbitrage away
large differences in wage changes
across states. The poor performance
of uneducated worker real wages, contributing to an increase
in wage dispersion and income
inequality, has certainly been
a thorny issue in California
as well as in the rest of the
nation. The question is whether
it was immigration flows that contributed
to these real wage changes
in California and the U.S.
and by how much.
3
The Framework: Production Function
and Imperfect Substitutability
|
To evaluate the effects of immigrants on the wages and employment of native workers
in California we use a framework similar to Ottaviano and Peri (2006). Workers
differ by their education and age; different types of workers and physical capital
are combined in a production function to produce output. The marginal productivity
(wage) of each group depends on skill-specific technology and the supply of each
group is affected by immigration. We extend that framework to allow for changes
in the labor supply of natives (via migration to/from other states and in/out
of employment) in response to immigration, and we estimate these responses and
corresponding wage elasticities maintaining the same groupings by skill in the
production function. Then, we use the estimated responses and the estimated wage
elasticities to calculate the overall effect of immigration on the wages of U.S.
natives in California
|
Following
previous work with Gianmarco
Ottaviano (Ottaviano and Peri,
2006) that, in turn, builds
on Borjas (2003),
we represent output in California as produced by physical capital and different types of labor. Labor
types are grouped according to
education
and age and combined in a
constant elasticity of substitution
(CES) aggregate;
age groups are nested within educational groups that are
themselves nested into the
labor composite
Lt.
U.S.-born and foreign-born
workers are allowed a further
degree of imperfect substitutability
even when they
have the same education and
age. More specifically, the
aggregate production function
is given by the
following
expression:
|
where
Yt is aggregate output , At
is total factor productivity
(TFP), Kt is physical capital,
Lt is a CES aggregateof different
types of labor (described below),
and α ∈ (0, 1) is the income
share of labor. All variables
reflect data for the state of
California in year t. The labor
aggregate Lt is defined as:
|
where
Lkt is an aggregate measure
of workers with educational level
k in year t; θkt are education-specific
productivity
levels (standardized so that Pk θkt = 1 and thus any common multiplying factor can be absorbed
in
the TFP term At). We group educational
achievements into four categories:
high school dropouts (denoted as HSD) , high school graduates
(HSG), college dropouts (COD) and college graduates (COG),
so that k = {HSD,
HSG, COD, COG}. The parameter δ > 0
measures the elasticity of
substitution between workers
with different educational
achievements. Within each
educational group we allow
workers with different experience
levels
to be imperfect substitutes.
In particular, following the
specification used in Card
and Lemieux (2001),
we
write:
|
where
j is an index spanning age intervals
of ten years between 17 and
66, so that j = 1 captures workers
17-26 years old , j = 2 captures
those who are 27-36 years old, and so on. Within an education
group age groups are identical
to groups based on years of
experience and sometimes we will use the terms ”age” and ”experience” interchangeably.
The reason to choose a ten year interval is that, by so
doing, we can track ten year
cohorts
across
censuses and control for their demographic tendencies when
evaluating the impact of immigration on employment,
revealing the internal migratory response of natives to foreign
immigrants. The parameter η > 0
measures
the elasticity of substitution
between workers in the same
education group with different
experience levels and
θkj
are experience-education
specific
productivity
levels
(standardized
so
that
Pj
θkj =
1
for
each
kand
assumed
to
be
invariant
over
time,
as
in
Borjas,
2003)
.
As
we
expect
workers
within
an
education
group to be
closer
substitutes
than workers
across
different
education
groups,
our
prior
(consistent
with
other
findings
in
the
literature)
is
that
η > δ.
Finally,
we
define
Lkjt
as
a
CES
aggregate
of
home-born
and
foreign-born
workers.
Denoting
the
number
of
workers
with
education
k
and
experience
j
who
are,
respectively,
home-born and
foreign-born,
with Hkjt and
Fkjt,
and
the
elasticity
of
substitution
between
them
by σ > 0,
our
assumption
is
that:
|
Foreign-born
workers are likely to have different
abilities pertaining to language,
quantitative skills, relational skills
and so on. These characteristics, in turn, are likely to affect their comparative advantages in production and hence choices
of occupation, therefore foreign-born workers should be differentiated enough to be treated as
imperfect substitutes for U.S.-born workers, even within the same education and experience group.
While in a more general specification the substitutability between
U.S.- and foreign-born workers, σ, may vary across education
groups (k), the findings in
Ottaviano and Peri (2006)
suggest that those differences
are not very relevant; hence, herein we maintain a common elasticity. Finally, the terms
θHkjt and θF kjt measure the
specific
productivity levels of foreign-
and home-born workers, and
they may vary across groups and years (in
the
empirical identification we
impose a systematic structure
on their variations over time)
. They are also standardized
so that (θHkjt + θF kjt) = 1. 3.2
Effects of Immigration on
Employment
and Wages in a State Economy
Using
the production function (1)
we can calculate the wage response
of each group to total immigration
once we know the parameters
δ, η and σ, and have the data
on immigration flows, wage shares and employment. In particular, assuming a given supply of U.S.-born workers in each skill group,
Hkjt, and assuming that physical capital
adjusts to immigration so as to keep its real return constant, one can easily show that the
effect of total immigrants
on the real wages of U.S. natives
of education k and experience j (expressed in units of output
Yt, which
is taken as the numeraire)
is
given by the following expression:
|
and
the effect of immigration
on wages of foreign-born (previous
immigrants) of education k
and experience j is given
by:
|
The
term  is
the percentage change of foreign-born
in skill group k, j due to
immigration; the variable sF kjt is the wage share paid
in year t to foreign workers in group k, j, namely sF kjt  Analogously,  is
the share of wage income in
year t paid to all workers
in skill group k, j. While appropriate when considering the overall U.S. economy, the assumption of fixed labor
supply
of natives, Hkjt, may not
hold when we analyze the effect of immigrants on a state economy.
In response to
an inflow of immigrants,
ΔFkjt, native workers may
move out of or be attracted
to California, depending
on the effect of a larger supply of immigrants on the demand
for natives. We denote as  response
the percentage change of
native employment of education
k and age j in period t
in response to total immigration
during
period t, and we need to
account for this response
when evaluating the overall effect of immigration on wages. It is easy to show that, in this case, the
long-run effect of immigration
on the wages of natives
and foreign-born
would be given by the following
two expressions:
|
The
terms containing  are
identical to those in the
formulas (5) and (6). The terms
containing  ´response
account
for the wage shift due to the
change in native supply of labor in response to
immigration. If the induced
adjustment of native employment has the opposite sign of the change in foreign-born
due
to immigration and a relevant magnitude, accounting for
it will attenuate the impact of immigration on wages. On the other hand, if the induced adjustment is negligible
accounting for it will
not significantly change
the
impact on wages obtained
by the simple application of (5) and (6). The next section describes how we
estimate
the response of native employment
to immigrants,  response
,
and the instrumental variable
strategy
behind those estimates.
4
The Response of Native Labor
Supply
4.1
Specification and Instrumental
Variables
|
While
we do not model in detail
the
mechanism producing the response
of native employment to immigration,
we
estimate the elasticity of
Hkjt (i.e.
the supply of natives in an
education experience group)
to changes in Fkjt by running
the following regression:

ΔHkjt
is the change in native employment
in cell k, j during the decade t. The left hand side of (9)
measures the change in native
employment as a percentage of
overall initial employment in the skill group k, j: Hkjt+Fkjt.
The regression
controls for education
by
age (Dkj) and education
by year (Dkt) fixed effects. These
controls are supposed to
capture systematic differences
in
employment growth across skill
groups as well as those that
are education-decade specific;
for instance, the latter could potentially be due to
skill-biased productivity
changes.
We also control for the predicted
change of employment in each cell,
denoted  that
accounts 10 for
demographic trends (cohort size and mortality rates) and
national employment/population ratios 5. Any deviation of ΔHkjt from the predicted change  in
employment is due either to net migration to/from
other states or changes in the employment/population ratio of the group6. The coefficient γ captures the elasticity of native
employment
changes,  to
immigration flows,  ukjt
are zero-mean cellspecific
shocks.
Once we have an estimate
of the elasticity γ, we
can obtain the response of native employment to
immigration, used above
as  In
order to obtain an estimate
of the coefficient γ that captures the response of native labor supply
to immigration in California we adopt the
following estimation and identification
strategy.
First, as already
noted,
we control for education-specific labor demand shocks (Dkt),
that would induce correlation between
the residual
and the immigrants’ inflow.
Second, we perform an instrumental
variables estimation using
the variable  over
skill groups and decades calculated
for the rest of the U.S. as
an instrument for immigration
flows to California. The flows
of immigrants to any U.S. state by education and experience
groups are determined by the
interaction of ”push” (supply)
factors, relative to the countries
of origin of immigrants and
“pull” (demand) factors specific
to the U.S. states where they move to. By using immigration
by skill in the rest of the
U.S. as
an
instrument for its counterpart
in California we are able to
isolate the supply-driven
variation of immigration (common
for flows to California and
rest of the U.S.) from the demand-driven variation specific
to California. Furthermore,
if the dependent variable is
measured with error due to the
fact that the size of
some skill cells in California
is small and the 1% samples used may have a non-trivial measurement error, the instrument, based
on
national data (excluding California) is likely to have larger size
in all cells and to measure
immigration much more precisely as a percentage of initial
employment. This would drastically
reduce any measurement error
bias. In general, using migration
by cell for the rest of the country as an instrument, we rely on the fact that the
education-age
distribution of immigrants
to
California is correlated
to the distribution for the rest of the U.S. due to common
countries of origin and push-factors.
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