32
[ Journal of Human Capital, 2008, vol. 2, no. 1]
᭧ 2008 by The University of Chicago. All rights reserved. 1932-8575/2008/0201-0002$10.00
Labor Outflows and Labor Inflows in Puerto Rico
George J. Borjas
Harvard University and National Bureau of Economic Research
Although a sizable fraction of the Puerto Rican–born population moved to the
United States, the island also received large inflows of persons born outside
Puerto Rico. Hence Puerto Rico provides a unique setting for examining how
labor inflows and outflows coexist and measuring the mirror-image wage impact
of these flows. The study yields two findings. First, the skills of the out-migrants
differ from those of the in-migrants. Puerto Rico attracts high-skill in-migrants
and exports low-skill workers. Second, the two flows have opposing effects on
wages: in-migrants lower the wage of competing workers, and out-migrants increase
the wage.
Bernardo: I think I’ll go back to San Juan.
Anita: I know a boat you can get on.
Bernardo: Everyone there will give big cheer.
Anita: Everyone there will have moved here.
(Stephen Sondheim, West Side Story)
I. Introduction
In the landmark article that placed migration decisions firmly within
the context of the nascent human capital framework,1
Larry Sjaastad
(1962, 81–82) wrote: “Migration poses two broad and distinct questions
for the economist. The first, and the one which has received the major
attention, concerns the direction and magnitude of the response of
migrants to labor earnings differentials over space. The second question
pertains to the connection between migration and those earnings, that
is, how effective is migration in equalizing inter-regional earnings of
I am grateful to Gary Becker, Mark Bils, Isaac Ehrlich, Gordon Hanson, Petra Todd,
and two referees for helpful comments on a previous draft of this article; to Trent Alexander
of the Minnesota Population Center for generously supplying the Puerto Rican
census microdata files; and to Jason Richwine for research assistance. An earlier version
of this paper was presented at a JHC inaugural conference held in Buffalo on October
26–28, 2006.
1
The hypothesis that migration is determined by regional wage differences dates back
at least to Hicks. In The Theory of Wages (1932, 76), Hicks argued that “differences in net
economic advantages, chiefly differences in wages, are the main causes of migration.”
Labor Outflows and Labor Inflows in Puerto Rico 33
comparable labor? The latter question has received much less attention
than the latter. It is also the more difficult of the two.”
These two questions have, in fact, dominated the study of regional
labor flows over the past half century. Much of the internal migration
literature in the United States documents how regional wage differentials
determine the size and direction of the migrant stream (Greenwood
1997). In contrast, an important part of the international migration
literature focuses on the latter question, that is, measuring the impact
of immigrants on the receiving country’s wage structure (Friedberg and
Hunt 1995). The textbook model of a competitive labor market has
clear and unambiguous implications about how wages and employment
opportunities in a particular region should adjust to migration-induced
labor supply shifts, at least in the short run. In particular, labor inflows
should lower the wage of competing workers, whereas labor outflows
should increase the wage. The prediction that interregional labor flows
help to equalize wages between sending and receiving areas gives migration
a central role in any discussion of labor market equilibrium and
efficiency (Blanchard and Katz 1992).
Despite the commonsense intuition behind these implications of the
laws of supply and demand, the international migration literature has
found it difficult to document the predicted inverse relation between
immigration-induced supply increases and wages in receiving countries.
It turns out that the nature of the empirical exercise used to measure
the wage impact determines the outcome: studies that relate wage differences
across cities to immigration-induced labor supply shocks tend
to find little impact (Card 1990, 2005), whereas studies that examine
the link between immigration and the evolution of the national wage
structure find larger effects (Borjas 2003).
This article examines the determinants and consequences of migration
flows in Puerto Rico.2
These migration flows are of interest for at
least two reasons. First, Puerto Rico, with a land area of 8,959 square
kilometers and 3.9 million inhabitants, is smaller than Los Angeles
County (which has a land mass of 10,518 square kilometers and a population
of 9.8 million). In Puerto Rico, the local labor market is the
national labor market. As a result, one can avoid the technical uncertainty
that plagues the existing literature about how to best measure
the labor market impact of immigration.
Second, even though a sizable fraction of the Puerto Rican–born
population moved to the United States in the past few decades, the
island was concurrently the recipient of large inflows of persons born
outside Puerto Rico.3
The Puerto Rican context, therefore, provides
a unique setting that should allow us to (a) examine the economic
2
Recent studies of the Puerto Rican labor market include Davis and Rivera-Batiz (2005)
and Enchautegui and Freeman (2005).
3
More precisely, this labor inflow is not composed of Puerto Ricans who had left the
island and subsequently decided to return.
34 Journal of Human Capital
factors that permit sizable labor inflows and labor outflows to coexist
and (b) observe the predicted mirror-image impact of these labor flows
on the Puerto Rican wage structure.
The simultaneous presence of the two opposing flows creates obvious
problems for the income-maximizing model of migration, since labor
should presumably flow only in the direction of the highest-paying area.
It is easy to reconcile two-way flows, however, if different regions offer
differential rewards for different types of human capital and if the opposing
labor flows are composed of different types of people.4
The
Puerto Rican experience, in principle, allows an empirical test of these
theoretical implications.
Similarly, the concurrent movement of large numbers of workers into
and out of Puerto Rico makes the island an inimitable setting for observing
how labor flows alter labor market conditions. In most geographic
settings that have been analyzed, the countries are either the
source of immigrants (as in Mexico) or the recipients of immigrants
(as in Canada and the United States). Since labor inflows should reduce
the relative wage of competing workers and labor outflows should increase
those relative wages, the Puerto Rican experience offers a rare
opportunity to determine if relative wages in a particular labor market
exhibit this mirror-image response to the two types of labor flows.
This study uses data drawn from the microdata samples of the 1970–
2000 Puerto Rican and U.S. Censuses. The empirical analysis yields two
important findings—addressing the two distinct questions Sjaastad
posed nearly half a century ago. First, the income maximization hypothesis
can help us understand the coexistence of large labor inflows
and labor outflows. The human capital of persons who move from
Puerto Rico to the United States differs strikingly from the human capital
of persons who migrate into Puerto Rico. Because the Puerto Rican
wage structure offers relatively high rewards to skills, the island attracts
relatively high-skill in-migrants and exports relatively low-skill workers.
Second, the opposing labor flows do have opposing effects on the wage
structure. As predicted by the laws of supply and demand, in-migration
lowers the wage of competing workers in the Puerto Rican labor market,
while out-migration increases the wage. The wage impact of these labor
flows is roughly comparable to that estimated in other countries: a 10percentage-point
migrant-induced shift in supply leads to an oppositesigned
change of 2–4 percent in the wage of competing Puerto Rican
workers.
4
A two-way flow of migrants and return migrants could be rationalized within the
income-maximizing framework if the initial migration was the result of misinformation
about the economic opportunities available in the destination or if the initial migration
was used as a “stepping-stone” to acquire skills that are valuable in the source labor market.
It is also possible that migration flows respond to differences in amenities across areas
and that the optimal sorting of persons across areas reflects heterogeneity in preferences.
Labor Outflows and Labor Inflows in Puerto Rico 35
Figure 1.—Trends in in-migrant and out-migrant shares in the population. An out-migrant
is a person born in Puerto Rico but residing in the United States; an in-migrant is a person
born outside Puerto Rico but residing in Puerto Rico. The 1940–2000 out-migration series
is defined by the ratio of the number of out-migrants to the Puerto Rican population at
a point in time. The denominator in the 1970–2000 in-migrant and out-migrant series is
the total number of Puerto Rican–born persons (i.e., the sum of Puerto Rican–born
persons enumerated in both Puerto Rico and the United States). All statistics are based
on calculations that use the entire population counts.
II. The Setting and the Data
It is instructive to begin by briefly summarizing the history of migration
flows in and out of Puerto Rico.5
The island became a possession of the
United States after the Spanish-American war in 1898. The Jones Act
of 1917 granted U.S. citizenship to all Puerto Ricans, implying that
Puerto Ricans could move freely to the United States without the legal
restrictions facing immigrants from foreign countries.
Despite the absence of legal restrictions, there was relatively little outmigration
until after World War II. High unemployment in postwar
Puerto Rico and the introduction of low-cost air travel (the 6-hour flight
from San Juan to New York City cost less than $50) sparked the initial
out-migration. In 1940 only 59,000 Puerto Ricans lived in the United
States; by 1950 there were 225,900, and by 1960 there were 626,900.
Most Puerto Rican out-migrants chose to settle in New York City. In
1970, for instance, 68.9 percent of the Puerto Rican–born population
in the United States lived in the New York metropolitan area.
Using data from the Puerto Rican Census and the U.S. Census that
will be described in more detail below, figure 1 illustrates the trend in
5
See Fitzpatrick (1980) for a more detailed history of Puerto Rican migration to the
United States.
36 Journal of Human Capital
the out-migrant share between 1940 and 2000. The out-migrant share
is defined as the ratio of the number of Puerto Rican persons living in
the United States to the potential Puerto Rican population (i.e., the
denominator is the sum of the out-migrants and the total population
of Puerto Rico). In 1940, the out-migrant share was 3.1 percent. By
1950, the out-migrant share stood at almost 10 percent, and it then rose
even more rapidly to 21.1 percent by 1960. In view of the very short
time frame in which this remarkable exodus occurred, it is not surprising
that Stephen Sondheim had one of the key characters in the 1961 movie
version of West Side Story predict that the island would soon empty out.
Anita was wrong, however. The outflow of Puerto Ricans to the United
States slowed down greatly in the 1960s. As a result, the out-migrant
share rose only slightly until about 1990, when the outflow seemingly
began to accelerate again.
Return migration is relatively common among the Puerto Rican outmigrants
(Hernandez 1967; Ramos 1992; Enchautegui 1993; Muschkin
1993). In 1990, 11.9 percent of the Puerto Rican–born adults enumerated
by the Puerto Rican Census reported they had resided in the United
States at some point during the past decade.6
The out-migrant share
illustrated in figure 1 is the net outcome of the two-way flows between
Puerto Rico and the United States for the Puerto Rican–born popula-
tion.
In addition to the outflow and return migration of native-born
Puerto Ricans, there is an additional labor flow that has received much
less attention and that could have a substantial economic impact. In
particular, concurrently with the sizable (net) out-migration of Puerto
Rican–born persons, there has also been a sizable in-migration of persons
not born in Puerto Rico. In other words, Puerto Rico is an important
recipient of immigrants.
Since 1970, the Puerto Rican Census microdata report whether a
person residing on the island was born outside Puerto Rico. Figure 1
also illustrates the out-migrant and in-migrant shares defined in terms
of the native-born Puerto Rican population.7
It is evident that this measure
of the out-migrant share is a little larger than the population-based
share; by 2000, nearly 30 percent of the population of persons born in
Puerto Rico resided in the United States. At the same time, the in-
6
Unfortunately, it is not possible to construct a consistent time series of the rate of
return migration. The 1970 Puerto Rican Census reports whether a person lived in the
United States for at least 6 months during the past 5 years; the 1990 Census reports
whether a person lived in the United States at some point between 1980 and 1990; and
the 1980 and 2000 Censuses report where a person lived 5 years prior to the census. In
1970, 13.5 percent of adult (aged 18–64) native-born Puerto Ricans are return migrants;
in 1980, 4.0 percent are return migrants; and in 2000, 2.7 percent.
7
More precisely, the out-migrant share is now defined as the ratio of the number of
out-migrants to the sum of the number of out-migrants and the native-born Puerto Rican
population, while the in-migrant share is defined as the ratio of in-migrants to the sum
of the number of in-migrants and the native-born Puerto Rican population.
Labor Outflows and Labor Inflows in Puerto Rico 37
TABLE 1
National Origin of Inflows into Puerto Rico
1970 1980 1990 2000
% population born outside Puerto Rico 10.3 9.8 9.1 9.4
% foreign-born population in Puerto Rico
born in:
United States 73.0 80.1 75.2 69.3
Colombia .6 .6 .7 1.0
Cuba 9.4 7.2 6.0 5.5
Dominican Republic 4.5 6.5 11.1 17.1
Spain 1.7 1.7 1.1 1.1
% U.S.-born population living in Puerto
Rico that has Puerto Rican ancestry 47.3 80.7 88.8 80.0
Sources.—Calculations from the 1970, 1980, 1990, and 2000 Puerto Rican Censuses. All
statistics are based on enumerations from the entire population counts.
migrant share hovers around 10 percent, so that Puerto Rico had an
immigrant influx that was proportionately similar to that entering the
United States.
Table 1 shows that three national origin groups dominate the inmigrant
population in Puerto Rico: persons born in the United States,
persons born in Cuba, and persons born in the Dominican Republic.
In 1970, almost 10 percent of the immigrants were born in Cuba and
less than 5 percent were born in the Dominican Republic. The pre-1970
Cuban influx can be directly linked to the communist takeover of Cuba,
which led to a sizable refugee flow into both the United States and
Puerto Rico. Over time, the demographic importance of Cuban immigrants
in Puerto Rico diminished. By 2000, only 5.5 percent of the
in-migrants were born in Cuba, but 17.1 percent were born in the Dominican
Republic. The bulk of the remaining immigrants were born in
the United States. Together, these three countries account for 90 percent
or more of the foreign-born population in Puerto Rico.
The ancestry of the population of U.S.-born persons migrating to
Puerto Rico is composed mainly of Americans who have some type of
Puerto Rican ancestry (although the information indicating Puerto Rican
ancestry is not defined consistently across censuses). In 1970, about
half of the U.S.-born immigrants in Puerto Rico had Puerto Rican ancestry.
By the 1990s, the statistic was between 80 and 90 percent.8
Despite the numerical importance of the in-migrant influx into Puerto
Rico, it is worth emphasizing that out-migration was far larger. In 2000,
the in-migrant share stood at 9.4 percent, while 29.4 percent of the
Puerto Rican–born population lived in the United States. As a result,
there has been a substantial net population outflow from the island.
8
The Hispanic origin variable in the U.S. Census provides information on whether a
person has Hispanic ancestry as well as his or her national origin background. The Hispanic
origin information is roughly comparable in the 1980, 1990, and 2000 Censuses. The
anomalous lower rate of Puerto Rican ancestry for the 1970 sample of U.S.-born in-migrants
is probably due to the different definition of Hispanic origin in that census.
38 Journal of Human Capital
Figure 2.—Per capita GDP of Puerto Rico (relative to United States). Source: Heston,
Summers, and Aten (2006). The ratio of per capita GDP is based on GDP estimates that
are adjusted for international prices. The 1950–2003 series is obtained by splicing the
1950–69 estimates from version 6.1 of the Penn World Tables with the post-1970 estimates
from version 6.2.
The net migrant share (i.e., the difference between in-migration and
out-migration) has been on the order of a negative 15–20 percent over
much of the past few decades. In other words, the various labor flows
have reduced the size of the Puerto Rican population by around 20
percent.
Not surprisingly, this sizable net labor outflow has been accompanied
by convergence in per capita incomes between the Puerto Rico and the
United States. Figure 2 shows the trend in the ratio of (international
prices adjusted) per capita GDP in the two countries. Relative Puerto
Rican per capita GDP almost doubled, from 21 percent to 37 percent
between 1950 and 1965, the time that the out-migration flow to the
United States was at its peak. Since the 1960s, relative incomes in Puerto
Rico have continued to rise. By 2003, relatively, per capita GDP in Puerto
Rico stood at 66 percent.
This article uses data drawn from microdata census files available for
both Puerto Rico and the United States. I use all of the available data
files from the 1970–2000 Puerto Rican Censuses. The 1970 file represents
a 3 percent sample of the Puerto Rican population, while all the
other files represent a 5 percent sample. The parallel analysis of the
U.S. data uses the 1970–2000 Integrated Public Use Microdata Sample
(IPUMS) of the decennial U.S. Census. As in Puerto Rico, the 1970 file
represents a 3 percent sample, and the 1980–2000 files represent a 5
percent sample. The empirical analysis is restricted to men who partic-
Labor Outflows and Labor Inflows in Puerto Rico 39
ipate in the labor force. The Data Appendix describes the construction
of the various sample extracts and variables in detail.
When analyzing the Puerto Rican Census data, I classify workers into
two main categories: those born in Puerto Rico and those born outside
Puerto Rico. The persons born outside Puerto Rico are the “in-migrants.”
The persons born in Puerto Rico and enumerated by the Puerto Rican
Census are the “stayers”—the group of Puerto Ricans who chose not to
move to the United States.
The Puerto Rican Census does not enumerate the Puerto Rican–born
persons who moved to the United States and chose to stay there. These
out-migrants, however, are enumerated by the U.S. Census. Hence a
joint analysis of the Puerto Rican Census and U.S. Census data provides
information about the size and composition of the (net) out-migrant
population. Using the place-of-birth information in the U.S. Census, I
define anyone born in Puerto Rico and enumerated by the U.S. Census
as a Puerto Rican out-migrant. It is worth emphasizing that the outmigrants
captured by the U.S. Census tend to be persons for whom the
move was relatively permanent. Out-migrants who have already returned
to Puerto Rico are not part of this population and are included in the
sample of Puerto Rican stayers.
Since the economic impact of labor flows will depend on the skill
composition of the various populations, I classify workers in each of
these three groups (i.e., the stayers, the out-migrants, and the inmigrants)
into various skill categories. As in Borjas (2003), skill groups
are defined in terms of both educational attainment and years of labor
market experience.
The distribution of educational attainment in Puerto Rico differs significantly
from that of the United States in two important ways. First,
high school dropouts make up a much larger fraction of the Puerto
Rican workforce. In 1970, the proportion of high school dropouts
among working men was 62.7 for Puerto Rico–born persons enumerated
in the Puerto Rican Census and 37.6 percent for U.S.-born persons
enumerated in the U.S. Census. Even by 2000, the respective statistics
were 19.3 percent and 8.2 percent.
Second, the typical high school dropout in Puerto Rico has much less
schooling than the typical high school dropout in the United States.
Consider, for instance, the number of high school dropouts who have
8 or fewer years of schooling. In 1970, 71.9 percent of the high school
dropouts enumerated in the Puerto Rican Census had this very low level
of schooling. Even by 2000, 50.7 percent of high school dropouts had
fewer than 8 years of schooling. It is rarer to find persons with fewer
than 8 years of schooling in the population of (U.S.-born) high school
dropouts in the United States: the respective statistics are 46.3 percent
for 1970 and 20.8 percent for 2000.
To account for the notable skewing at the bottom end of the Puerto
Rican education distribution, I use five categories to define the edu-
40 Journal of Human Capital
cation groups: (1) high school dropouts with 8 or fewer years of schooling,
(2) high school dropouts with 9–11 years of schooling, (3) high
school graduates (workers who have exactly 12 years of schooling), (4)
workers who have some college (13–15 years of schooling), and (5)
college graduates (workers who have at least 16 years of schooling).
I also classify workers into a particular years-of-experience cohort by
using potential years of experience, roughly defined as age minus years
of education minus 6. I assume that age of entry into the labor market
is 14 for high school dropouts with fewer than 8 years of schooling, 16
for high school dropouts with 9–11 years of schooling, 18 for high school
graduates, 21 for persons with some college, and 23 for college graduates,
and I then calculate years of experience accordingly.9
The analysis
is restricted to men who have between 1 and 40 years of experience.
Workers are aggregated into 10-year experience groupings (i.e., 1–10
years of experience, 11–20 years, etc.) to capture the notion that workers
who have roughly similar years of experience are more likely to affect
each other’s labor market opportunities than workers who differ significantly
in their work experience. It may be preferable to define narrower
experience bands (e.g., 5-year intervals), but even the 5 percent
Puerto Rican Censuses have relatively few observations.10
The creation
of very narrow skill categories would generate much greater measurement
error when calculating mean outcomes within cells.
The cells corresponding to educational attainment (i), years of work
experience (j), and calendar year (t) define a skill group at a point in
time. Let give the number of Puerto Rican stayers (i.e., the numberN (t)ij
of Puerto Rican–born persons enumerated by the Puerto Rican Census)
in the (i, j, t) cell; be the corresponding number of in-migrantsM (t)ij
in Puerto Rico; and be the corresponding number of Puerto RicansX (t)ij
who out-migrated to the United States. Define
M (t)ij
p (t) p , (1)ij
M (t) ϩ N (t)ij ij
X (t)ij
q (t) p . (2)ij
X (t) ϩ N (t)ij ij
The variable gives the in-migrant share in the Puerto Rican work-p (t)ij
force (i.e., the fraction of the Puerto Rican workforce that was born
9
Because of the assumed age of entry for the various education groups, I restrict the
analysis to workers aged 14–64. I experimented with alternative assumptions (e.g., all high
school dropouts enter the labor market at age 16), and the results are similar to those
reported below.
10
The total number of working men (with positive earnings) enumerated in each of
the Puerto Rican Censuses is as follows: 10,438 in 1970, 16,763 in 1980, 23,029 in 1990,
and 24,313 in 2000. The average cell size in each education-experience group is 522 in
1970, 838 in 1980, 1,151 in 1990, and 1,216 in 2000.
Labor Outflows and Labor Inflows in Puerto Rico 41
Figure 3.—Out-migrant and in-migrant shares for working men. The out-migrant share
gives the ratio of the number of out-migrant working men to the potential number of
Puerto Rican–born working men (defined as the sum of the number of out-migrants plus
the number of Puerto Rican stayers); the in-migrant share gives the ratio of the number
of in-migrant working men to the number of working men in the Puerto Rican workforce
(defined as the sum of the number of in-migrants plus the number of Puerto Rican stayers).
outside Puerto Rico), while gives the out-migrant share (i.e., theq (t)ij
fraction of the Puerto Rican–born workforce that lives in the United
States). For expositional convenience, I initially use the convention of
defining both the in-migrant and the out-migrant shares as positive
numbers.
Figure 3 shows the trends in the estimated in-migration and outmigration
shares defined by equations (1) and (2) and estimated in the
sample of working men. Note that the in-migrant and out-migrant shares
estimated in this sample are far larger than the corresponding population
shares illustrated in figure 1. For example, the out-migrant share
in 2000 for the Puerto Rican population was 29.4 percent, as compared
to an out-migrant share of 38.6 percent for working men. Similarly, the
in-migrant share in the sample of working men (13.6 percent in 2000)
is much higher than the corresponding share in the Puerto Rican population
(9.4 percent). In fact, the in-migrant share in the Puerto Rican
workforce is very similar to the immigrant share in the U.S. workforce.
In 2000, 14.7 percent of working men in the United States were foreign
born. Put differently, the stylized perception of Puerto Rico as a region
that has lost a large fraction of its potential workforce to the United
States is correct, but it is incomplete. Immigrants play as large a role
in Puerto Rico as they do in the United States.
42 Journal of Human Capital
Figure 4.—Out-migrant shares of the Puerto Rican–born population, by education. The
out-migrant share gives the ratio of the number of out-migrant working men to the
potential number of Puerto Rican–born working men (defined as the sum of the number
of out-migrants plus the number of Puerto Rican stayers).
III. Labor Flows by Skill
This section documents how the structure of out-migration and inmigration
differs across skill groups. Figure 4 reports the educationspecific
trends in the out-migrant share of native-born Puerto Rican
working men. The out-migrant share is lowest for college graduates and
highest for workers with 9–11 years of schooling. In 1980, for example,
only about 23 percent of the college-educated workforce had left Puerto
Rico. In contrast, the out-migrant share for high school dropouts with
9–11 years of schooling was over 50 percent during the period (peaking
at an astounding 73 percent in 1980).11
A straightforward application of the Roy model would suggest that
the least-educated workers have the most incentive to leave Puerto Rico
(Borjas 1987; Ramos 1992). After all, regardless of how it is measured,
the rate of return to skills is much higher in Puerto Rico than in the
United States. Table 2 reports various summary measures of the spread
of the wage distribution in Puerto Rico and in the United States, including
the variance of log weekly earnings, the residual variance of log
weekly earnings, and the experience-adjusted wage gap between college
graduates and high school dropouts with 9–11 years of schooling, as
11
Note that the out-migrant share for this particular group declined substantially between
1980 and 2000, suggesting that there was a sizable return migration of these high
school dropouts back to Puerto Rico during those 2 decades.
Labor Outflows and Labor Inflows in Puerto Rico 43
TABLE 2
Summary Characteristics of Spread of Male Wage Distributions in Puerto Rico
and the United States
1970 1980 1990 2000
Puerto Rico:
Variance of log weekly earnings .713 .701 .883 .727
Residual variance of log weekly earnings .559 .541 .710 .569
Experience-adjusted log weekly earnings
differential between college graduates
and workers with 8–11 years of
schooling 1.066 1.066 1.055 1.055
Experience-adjusted log weekly earnings
differential between college and high
school graduates .807 .760 .811 .847
United States:
Variance of log weekly earnings .542 .615 .655 .710
Residual variance of log weekly earnings .414 .477 .480 .533
Experience-adjusted log weekly earnings
differential between college graduates
and workers with 8–11 years of
schooling .747 .726 .957 1.018
Experience-adjusted log weekly earnings
differential between college and high
school graduates .527 .444 .623 .683
Note.—The calculations in the Puerto Rican Census use the sample of Puerto Rican–born
working men aged 18–64, and the calculations in the U.S. Census use the sample of U.S.born
working men aged 18–64.
well as the experience-adjusted wage gap between college graduates and
high school graduates.12
The summary characteristics reported in table 2 document two key
facts. First, the returns to skills are greater in Puerto Rico than in the
United States.13
In 1990, for instance, the experience-adjusted wage gap
between college graduates and high school graduates was 0.811 in
Puerto Rico and 0.623 in the United States. Similarly, the residual variance
of log weekly earnings was 0.710 in Puerto Rico and 0.480 in the
United States. The Roy model would then predict that a relatively higher
fraction of the least-educated Puerto Ricans should be out-migrants.
Second, the returns to skills have increased at a much faster rate in
the United States than in Puerto Rico. For example, the (experienceadjusted)
wage gap between college and high school graduates in Puerto
Rico rose slightly from 0.81 to 0.85 between 1970 and 2000. In the
United States, however, the corresponding log wage gap rose from 0.53
12
The residual variance of log weekly earnings and the experience-adjusted wage gaps
across schooling groups are estimated from a regression of log weekly earnings on fixed
effects indicating the five education categories defined in the previous section and on a
quadratic in years of work experience.
13
The estimated variances for the 1990 Puerto Rican wage distribution do not seem
consistent with the variances estimated in other censuses. I have been unable to identify
the source of this data anomaly.
44 Journal of Human Capital
to 0.68. Similarly, the residual variance in log weekly earnings was 37
percent higher in Puerto Rico than in the United States in 1970 (0.56
as compared to 0.41). By 2000, however, the variances were almost the
same: 0.57 in Puerto Rico and 0.53 in the United States. The relatively
faster increase in the return to skills in the United States would suggest
that the out-migrant share of highly educated workers should have risen
the most during the period under study.
The differences in out-migrant shares across education groups, illustrated
in figure 4, are partly consistent with these predictions of the
Roy model: while the fraction of low-educated Puerto Ricans who moved
to the United States was about the same in 1970 as in 2000 (with some
noticeable ups and downs in between), the out-migrant share for college
graduates was rising rapidly. In 1970, the out-migrant share of college
graduates was 13.4 percent; by 2000, it had more than doubled to 30.4
percent. These trends are consistent with the fact that the returns to
skills were increasing much faster in the United States, encouraging
highly educated workers to leave the island.
Note, however, that the data are not entirely consistent with the prediction
that, on net, the Puerto Rican out-migrants should be negatively
selected. After all, the highest out-migration rate is not observed in the
sample of high school dropouts with 0–8 years of schooling but in the
sample of high school dropouts with 9–11 years of schooling. This nonmonotonicity
in out-migration rates, however, can be explained by a
slightly modified version of the traditional Roy model. In particular,
suppose that liquidity constraints prevent the least-educated Puerto Rican
workers from financing the requisite investments required to move
to the United States. This would imply that the least skilled among the
least-educated workers would find it difficult to move, depressing their
out-migration rate.14
Once the liquidity constraints are relaxed, those
low-educated workers who can afford to leave the island will do so. This
pattern seems to be what the data reveal. Out-migrant shares are generally
higher for low-educated workers, though they are highest for the
“better-off” workers within this disadvantaged population.
These Roy model-related insights are corroborated by the selection
that characterizes the reverse migration of U.S.-born workers who move
to Puerto Rico. As reported in table 1, roughly 7–8 percent of the
workforce in Puerto Rico was born in the United States, with close to
80 percent of these U.S.-born immigrants having some type of Puerto
Rican ancestry.
By judiciously using the available data, it is possible to roughly estimate
14
The hypothesis of liquidity constraints among the least-educated workers also seems
to explain the selection of out-migrants from Mexico (Chiquiar and Hanson 2005). There
is, however, some disagreement on the type of selection that characterizes Mexican emigration;
Ferna´ndez-Huertas Moraga (2006) and Ibarrara´n and Lubotsky (2007) argue
that there is unambiguous evidence of negative selection in the subsample of Mexican
emigrants.
Labor Outflows and Labor Inflows in Puerto Rico 45
Figure 5.—Out-migrant share of U.S.-born persons to Puerto Rico (relative to the number
of U.S.-born persons of Puerto Rican ancestry). The out-migrant share gives the ratio of
the number of U.S.-born out-migrants to Puerto Rico to the potential number of U.S.born
persons of Puerto Rican ancestry (defined as the sum of the number of out-migrants
plus the number of U.S.-born persons of Puerto Rican ancestry who stayed in the United
States).
the out-migrant share in the population of U.S.-born persons of Puerto
Rican ancestry. Since 1970, the U.S. Census reports a measure of Hispanic
ancestry for the native-born population. Persons who report being
Hispanic are then asked to specify the type of Hispanic background.
These data allow the enumeration of the number of U.S.-born persons
of Puerto Rican ancestry who reside in the United States. By combining
this size-of-population statistic with the number of U.S.-born persons of
Puerto Rican ancestry enumerated by the Puerto Rican Census, one can
estimate the out-migrant share of this population (i.e., the fraction of
the U.S.-born population of Puerto Rican ancestry that lives in Puerto
Rico). In 2000, 10.8 percent of male workers in this group lived in Puerto
Rico.15
As figure 5 shows, the skill composition of this population seems to
be a mirror image of that of Puerto Ricans choosing to move to the
United States. Because Puerto Rico generally offers relatively higher
returns to skills than the United States, it is not surprising that the outmigrant
shares of U.S.-born Puerto Ricans are highest for college-
15
It is important to emphasize that this out-migration rate probably contains a lot of
measurement error. First, the definition of Hispanic (and Puerto Rican ancestry) in the
1970 Census is not strictly comparable with the definition in subsequent censuses. Second,
the definition of Puerto Rican ancestry differs significantly between the Puerto Rican and
U.S. Censuses.
46 Journal of Human Capital
Figure 6.—In-migrants in Puerto Rico, as a fraction of the Puerto Rican–born population,
by education. The in-migrant share gives the ratio of the number of in-migrant working
men to the number of working men in the Puerto Rican workforce (defined as the sum
of the number of in-migrants plus the number of Puerto Rican stayers).
educated workers. In 2000, for example, the out-migrant share of college
graduates was 18.9 percent, as compared to 5.5 percent for high school
dropouts with 9–11 years of schooling.16
The inflow of relatively large numbers of both U.S.-born and foreignborn
workers into Puerto Rico substantially altered the skill endowment
of the Puerto Rican workforce. Consider, in particular, the supply shifts
caused by migration into the Puerto Rican labor market. Figure 6 illustrates
the trend in the in-migrant shares for the five education groups.
Evidently, in-migration led to a sizable increase in the number of college
graduates in the Puerto Rican workforce. In 1970, for example, 26.9
percent of college-educated workers in Puerto Rico were foreign born,
as compared to only about 5 percent of high school dropouts.
In addition to these differences in the in-migrant and out-migrant
shares across education groups, there is substantial variation across experience
groups (holding education constant). Figures 7 and 8 summarize
some of these differences in the estimated supply shifts for outflows
and inflows, respectively. The data illustrated in figure 7, for
instance, indicate that for some education groups out-migrant shares
in 1990 tend to be larger for younger workers (e.g., college graduates),
16
It would also be interesting to determine if the skills of immigrants born outside the
United States are consistent with the differences in the wage structures between Puerto
Rico and the sending countries. It is impossible to conduct this exercise, however, because
it requires detailed information on the skill distributions of the populations of the sending
countries.
Labor Outflows and Labor Inflows in Puerto Rico 47
Figure 7.—The out-migrant share in Puerto Rico, 1970–2000. The out-migrant share gives
the ratio of the number of out-migrant working men to the potential number of Puerto
Rican–born working men.
whereas for other groups out-migrant shares tend to be larger for older
workers (e.g., high school dropouts with 0–8 years of schooling). Figure
8 shows equally striking variation in the observed in-migrant shares.
Among less educated workers, there is a tendency for in-migration to
most increase the supply of younger workers. Among more educated
workers, however, in-migrant shares are much more stable across experience
groups.
The evidence presented in this section suggests that the type of worker
leaving Puerto Rico differs from the type of worker that is moving in.
It is easy to provide a striking illustration of just how different the two
opposing flows are. In particular, figure 9 presents a scatter diagram of
48 Journal of Human Capital
Figure 8.—The in-migrant share in Puerto Rico, 1970–2000. The in-migrant share gives
the ratio of the number of in-migrant working men to the number of working men in
the Puerto Rican workforce.
the in-migrant and out-migrant shares—as defined by equations (1) and
(2)—calculated for each of the (i, j, t) cells. There is a strong negative
correlation between the two variables. The skill groups that experienced
the greatest outflows at a particular point in time are also the skill groups
that experienced the smallest inflows. The differential skill composition
of the opposing flows provides a simple and intuitive explanation for
why there can be sizable inflows and outflows in a particular labor market
at the same time: the relatively high returns to skills in the Puerto Rican
labor market attract high-skill workers and encourage the outflow of
low-skill workers.
Labor Outflows and Labor Inflows in Puerto Rico 49
Figure 9.—Relation between in-migrant and out-migrant shares. The out-migrant share
gives the ratio of the number of out-migrant working men to the potential number of
Puerto Rican–born working men (defined as the sum of the number of out-migrants plus
the number of Puerto Rican stayers); the in-migrant share gives the ratio of the number
of in-migrant working men to the number of working men in the Puerto Rican workforce
(defined as the sum of the number of in-migrants plus the number of Puerto Rican stayers).
IV. Determinants of Labor Flows
Before proceeding to discuss the equilibrating effects of labor flows, it
is instructive to investigate if the Puerto Rican experience confirms a
key prediction of economic theory—that the workers who incur the cost
of moving are the ones who have the most to gain. Although the presence
of selection biases in calculating potential wages in alternative
regions prevents a complete analysis (unless much more statistical structure
is imposed on the data), the results clearly suggest that the flows
of workers in and out of Puerto Rico move in precisely the right direc-
tion.
Let denote the mean value of the log weekly wage that PuertoPR
w (t)ij
Rican–born men who have education i and experience j would earn if
employed in Puerto Rico at time t. Let be the alternative log wageUS
w (t)ij
that this group of workers would earn in the U.S. labor market. For
given migration costs, Puerto Rican natives should be more likely to
migrate to the United States the greater the wage gain .US PR
w (t) Ϫ w (t)ij ij
Both the U.S. and the Puerto Rican wage structures changed significantly
between 1970 and 2000. As a result, there is a great deal of
variation in the potential wage gain associated with moving to the United
States across skill groups and over time.
50 Journal of Human Capital
Equation (2) defines the out-migrant share from Puerto Rico asq (t),ij
of time t. Define the decadal change in the out-migrant share and in
the wage gain as and US PR
Dq (t) p q (t) Ϫ q (t Ϫ 1) D[w (t) Ϫ w (t)] pij ij ij ij ij
Consider the regressionUS PR US PR
[w (t) Ϫ w (t)] Ϫ [w (t Ϫ 1) Ϫ w (t Ϫ 1)].ij ij ij ij
model
US PR
Dq (t) p bD[w (t) Ϫ w (t)] ϩ other variables ϩ ␧ (t). (3)ij ij ij ij
Equation (3) relates the decadal change in the out-migrant share to the
decadal change in the relative Puerto Rican wage. The coefficient b
should be positive as long as the probability of migrating from Puerto
Rico to the United States responds to economic incentives. Note that
the differencing of the data within education-experience cells implies
that b is being identified from changes in the relative wage of a particular
skill group. The regressions weigh the observations by the sum of sampling
weights used to calculate the out-migrant share at time t, and the
standard errors are clustered by education-experience cells to adjust for
possible serial correlation.17
One problem with estimating the regression model in (3) is that we
do not observe what the typical worker in cell (i, j, t) would earn if he
were to migrate to the United States. Instead, we observe the mean wage
of the self-selected group of workers who chose to migrate. If the selection
of Puerto Ricans into the out-migrant flow were determined
solely by observed characteristics (in particular, education and experience),
we could define the alternative wage as the wage thatUS
w (t)ij
Puerto Rican out-migrants in that particular cell actually earn in the
United States. This wage can be calculated from the respective U.S.
Census. Similarly, I define as the average log weekly wage thatPR
w (t)ij
native-born Puerto Ricans in cell (i, j, t) actually earn in Puerto Rico.
All earnings are deflated to 1990 constant dollars using either the U.S.
or Puerto Rican CPI.
Using these definitions, the top panel of table 3 reports the estimated
coefficients from two alternative specifications of the model in equation
(3). In column 1, the regression model does not include any other
regressors. There is a positive and significant correlation between the
out-migrant share in a skill group and the net wage gain associated with
moving to the United States. A 10-percentage-point increase in the wage
gain increases the out-migrant share by 1 percentage point. Column 2
adds a vector of period fixed effects to allow for differences in other
factors that are time specific (such as migration costs). The inclusion
of these fixed effects strengthens the basic result: a 10-percentage-point
increase in the wage gap raises the out-migration rate by 1.5 percentage
points.
17
I normalized the sum of weights to equal one in each cross section to prevent the
more recent censuses from contributing more to the estimation simply because Puerto
Rico’s population increased over time.
Labor Outflows and Labor Inflows in Puerto Rico 51
TABLE 3
Determinants of Out-migrant Share in Puerto Rico
Variable
Specification
(1) (2) (3) (4)
Panel A. p wage of Puerto RicanUS
w
immigrants in United States:
US PR
D(w Ϫ w ) .098 .147
(.041) (.111)
US
Dw .026 .151
(.067) (.105)
PR
Dw Ϫ.109 Ϫ.133
(.048) (.233)
Panel B. p wage of native workersUS
w
in United States:
US PR
D(w Ϫ w ) .120 .188
(.039) (.069)
US
Dw .661 .563
(.206) (.202)
PR
Dw Ϫ.173 Ϫ.279
(.068) (.257)
Panel C. p wage of Puerto RicanUS
w
immigrants in New York:
US PR
D(w Ϫ w ) .078 .297
(.041) (.134)
US
Dw Ϫ.061 .313
(.093) (.115)
PR
Dw Ϫ.095 Ϫ.256
(.046) (.246)
Controls for period fixed effects No Yes No Yes
Note.—Dependent variable p decadal change in out-migrant share of Puerto Rican–born
workers from Puerto Rico. Standard errors are reported in parentheses and are adjusted
for clustering within education-experience cells. All regressions are weighted by the sum
of sampling weights in the cell. The regressions have 60 education-experience-year cells.
The out-migrant share gives the ratio of the number of working men who left Puerto Rico
to the potential number of Puerto Rican–born working men. The potential wage in Puerto
Rico is given by the average wage of Puerto Rican stayers. The operator for the regressorsD
indicates that these variables are defined as decadal changes.
Columns 3 and 4 of the top panel of table 3 report the coefficients
from a slightly more general specification of the regression model
in equation (3). In particular, suppose that
US PR
Dq (t) p b Dw (t) ϩ b Dw (t) ϩ other variables ϩ ␧ (t), (4)ij 1 ij 2 ij ij
where p and p .US US US PR PR PR
Dw (t) [w (t) Ϫ w (t Ϫ 1)] Dw (t) [w (t) Ϫ w (t Ϫ 1)]ij ij ij ij ij ij
This specification allows for the separate identification of the push and
pull factors in the determination of out-migration. The coefficients reported
in the top panel of table 3 indicate that the out-migrant share
is higher the greater the wage in the U.S. labor market and is lower the
greater the wage in the Puerto Rican labor market—although some of
the coefficients are not precisely estimated.
An obvious problem with the regression results is that the actual
earnings of the Puerto Rican out-migrants in the U.S. labor market may
not be the correct measure of the alternative wage facing the typical
52 Journal of Human Capital
Puerto Rican worker in Puerto Rico. In principle, one could adjust for
this selection problem by adding more structure to the statistical model.
Such an analysis would likely be unconvincing, since there are relatively
few variables in the data that would allow identification of alternative
wages on the basis of exogenous variation in opportunities rather than
on the basis of statistical assumptions.
A simpler approach is to evaluate the sensitivity of the results to using
alternative definitions of the potential U.S. wage. The middle panel of
table 3 replicates the analysis by defining as the average wageUS
w (t)ij
earned by the typical native-born worker in the United States in cell (i,
j, t). The key difference between the two measures of is that theUS
wijt
one used in the top panel of the table uses only the sample of Puerto
Rican–born workers in the United States, while the one used in the
middle panel aggregates over all U.S.-born workers. Despite the substantive
difference in the two definitions of the alternative wage, the
estimated regression coefficients are roughly similar. A 10 percent increase
in the wage gap between the United States and Puerto Rico still
leads to a 1- to 2-percentage-point increase in the out-migration rate.
Finally, as noted earlier, most of the Puerto Rican immigrants in the
United States settle in the New York metropolitan area. This suggests
that another possible definition for is the average wage earnedUS
w (t)ij
by the typical Puerto Rican immigrant in that region.18
The bottom
panel of table 3 reestimates the regression using this measure of the
alternative wage. It is evident that the coefficient b is still positive. In
the specification that contains the period fixed effects, a 10 percent
increase in the net wage gain from moving increases the out-migration
rate by 3.0 percentage points.
An endogeneity problem may bias the estimate of b in equation (3)
and of and in equation (4). A positive estimate of b in equationb b1 2
(3), for example, implies that the net size of migration flows responds
positively to the wage differential between receiving and sending
regions. It is also the case, however, that the resulting outflow from
Puerto Rico to the United States must have affected the wage structure
in both areas. In particular, the outflow would presumably lower wages
in the U.S. labor market and raise wages in the Puerto Rican labor
market. In other words, the endogeneity of the interregional wage gap
creates a negative correlation between the measured out-migrant share
and the net wage gain resulting from migration. As a result, the coefficients
reported in table 3 underestimate the responsiveness of migration
flows to regional wage differentials. In the next section, I present
one approach for correcting the coefficients for this potential endo-
geneity.
18
Although the 1980–2000 U.S. Censuses report the metropolitan area of residence for
all observations, only a third of the sample in the 1970 U.S. Census reports that information.
To maintain a relatively large sample size, the 1970 New York wage is defined to
be the average wage of native-born workers in New York State.
Labor Outflows and Labor Inflows in Puerto Rico 53
It is of interest to develop a parallel analysis of the determinants of
in-migration flows into Puerto Rico. As noted earlier, there are two main
types of in-migrants: workers who were born in the United States and
move to Puerto Rico (and at least 80 percent of these workers have
Puerto Rican ancestry after 1980) and workers who were born in other
countries (particularly Cuba and the Dominican Republic) and migrate
to Puerto Rico. Although it is impossible to analyze the determinants
of out-migration rates for workers from Cuba or the Dominican Republic,
it is possible to estimate an analogous model for the first group
of workers—the U.S.-born migrants from the United States to Puerto
Rico. To determine the determinants of this influx, consider the regression
model
US PR
Dp*(t) p gD[w (t) Ϫ w (t)] ϩ other variables ϩ ␧ (t), (5)ij ij ij ij
where is the decadal change in the out-migrant share of U.S.-Dp*(t)ij
born workers as a fraction of the number of U.S.-born persons who
have Puerto Rican ancestry. The income maximization hypothesis implies
that the coefficient g should be negative.
The nature of the available data makes it difficult to find operational
definitions for and . I use the Puerto Rican Census to cal-US PR
w (t) w (t)ij ij
culate the average wage earned by U.S.-born immigrants in Puerto Rico,
and I define accordingly. Second, there is no direct informationPR
w (t)ij
about how much the U.S.-born immigrants in Puerto Rico earned in
the United States prior to their migration. I approximate the average
wage by either the average wage of workers in a particular skillUS
w (t)ij
group who have Puerto Rican ancestry, the average wage of native-born
workers in the United States, or the average wage of native-born workers
in the New York metropolitan area.
Table 4 reports the regression results. The estimated coefficient g is
negative and usually significant in the specifications reported in columns
1 and 2. The results, however, are more mixed in the specification that
allows for separate identification of push and pull factors—with the
results depending on the definition of the alternative potential U.S.
wage. Overall, the evidence suggests that a 10-percentage-point increase
in the wage gap between the United States and Puerto Rico reduces
the probability that a U.S.-born person of Puerto Rican ancestry moves
to Puerto Rico by 1–2 percentage points.19
19
Note that even though high-skill workers do relatively better in Puerto Rico, many of
the high-skill migrants from the United States to Puerto Rico may actually be taking a
nominal wage cut because of the sizable difference in wage levels between the two regions.
This implies, of course, that there are important differences in relative prices (e.g.,
housing) or amenities that are being ignored in the analysis. It seems plausible to argue
that these factors may become more important as workers near retirement age. However,
the descriptive data in fig. 5 suggest that there has actually been a reduction in the relative
propensity of older U.S.-born workers to migrate to Puerto Rico.
54 Journal of Human Capital
TABLE 4
Determinants of Out-migrant Share of U.S.-Born Workers
Variable
Specification
(1) (2) (3) (4)
Panel A. p wage of Puerto RicansUS
w
in United States:
US PR
D(w Ϫ w ) Ϫ.148 Ϫ.080
(.050) (.042)
US
Dw .071 Ϫ.296
(.262) (.140)
US
Dw .146 .043
(.056) (.041)
Panel B. p wage of native workersUS
w
in United States:
US PR
D(w Ϫ w ) Ϫ.176 Ϫ.036
(.047) (.048)
US
Dw Ϫ.483 .026
(.294) (.245)
PR
Dw .177 .042
(.050) (.046)
Panel C. p wage of Puerto RicansUS
w
in New York:
US PR
D(w Ϫ w ) Ϫ.096 Ϫ.078
(.044) (.037)
US
Dw .339 Ϫ.291
(.125) (.116)
PR
Dw .087 .048
(.049) (.045)
Controls for period fixed effects No Yes No Yes
Note.—Dependent variable p decadal change in out-migrant share of U.S.-born Puerto
Ricans from the United States. Standard errors are reported in parentheses and are adjusted
for clustering within education-experience cells. All regressions are weighted by the
sum of sampling weights in the cell. The regressions have 60 education-experience-year
cells. The out-migrant share gives the ratio of the number of U.S.-born workers in Puerto
Rico to the potential number of U.S.-born persons of Puerto Rican ancestry. The potential
wage in Puerto Rico is given by the average wage of U.S.-born immigrants in Puerto Rico.
The D operator for the regressors indicates that these variables are defined as decadal
changes.
V. Consequences of Labor Flows: Migration as an Equilibrating
Mechanism
As noted earlier, because immigrants tend to cluster in a small number
of cities in most receiving countries, many studies estimate the labor
market impact of immigration by comparing economic conditions across
localities in the receiving country. These studies calculate the correlation
between measures of immigrant penetration in local labor markets and
measures of economic outcomes, such as wages (Altonji and Card 1991;
LaLonde and Topel 1991; Card 2001). The sign of this spatial correlation
is interpreted as indicating the direction in which supply shifts affect
wages; a negative correlation would suggest that immigration-induced
increases in labor supply lower wages. Although there is a lot of dispersion
across studies, the estimated spatial correlations cluster around
Labor Outflows and Labor Inflows in Puerto Rico 55
zero. This weak correlation has been interpreted as indicating that immigration
has little impact on the receiving country’s wage structure.
The potential problems associated with using regional wage differences
to measure the labor market impact of immigration are now well
understood (Borjas, Freeman, and Katz 1997). For instance, natives (and
preexisting immigrants) may respond to the adverse wage impact of
immigration by moving their labor or capital to other cities. These
regional flows diffuse the impact of immigration across all regions, suggesting
that the labor market impact of immigration may be measurable
only at the national level.20
Borjas (2003) used this insight to examine
how the aggregate wage trends of U.S. workers were related to the
immigrant supply shocks affecting those groups. The national-level evidence
indicated that the wage growth experienced by narrowly defined
skill groups was strongly and inversely related to immigration-induced
supply increases. This approach has now been applied to such diverse
contexts as Canada (Aydemir and Borjas 2007) and Mexico (Mishra
2007) with similar conclusions: supply shifts induced by international
migration lead to an opposite-signed change in the wage of competing
workers.21
In this section, I employ this methodological approach to investigate
if the Puerto Rican wage structure responded to the labor inflows and
outflows documented in the previous sections. It is worth noting that
the application of the Borjas (2003) framework to the Puerto Rican data
may be illuminating because, given Puerto Rico’s size, the local labor
market is the national labor market.
As in my earlier work, I analyze the relation between the evolution
of the wage structure and labor flows by using the education-experience
skill groups defined above. The construction of the various groups, of
course, implicitly assumes that workers with the same level of schooling
but with different levels of experience are imperfect substitutes in production
(Welch 1979; Card and Lemieux 2001).22
20
There is little consensus on whether the internal migration decisions of native workers
are, in fact, influenced by immigration (Card 2001; Borjas 2006). The observed spatial
correlation is also contaminated by the possibility that immigrants choose to settle in highwage
areas of the host country and by measurement error in the observed immigrant
supply shock in the local labor market.
21
Bonin (2005) reports some contradictory evidence using the national-level approach.
Bonin finds that supply shocks in Germany lower wages in the German labor market but
by much less than in the Borjas (2003) study. The German census, however, does not
provide direct information on immigration status, so that the data cannot distinguish
between foreign citizens born abroad and foreign citizens born in Germany. As a result,
it is unclear exactly what type of supply shock is being measured.
22
The analysis also ignores the possibility that labor flows in and out of a particular skill
group affect the wages of other skill groups. The estimation of these cross effects would
require a much more detailed specification of the production technology (such as the
three-level constant elasticity of substitution (CES) framework in Borjas [2003]). Given
the relatively small number of observations available in the Puerto Rican data, the specification
of a full-blown structural model would probably lead to imprecise (and unconvincing)
estimates of the underlying technological parameters.
56 Journal of Human Capital
The analysis focuses on the impact of labor flows on the earnings of
Puerto Rican–born workers enumerated by the Puerto Rican Census—
in other words, I examine the impact of labor flows on the earnings of
stayers. In addition to the sample restrictions noted in Section II, the
construction of mean earnings for each education-experience-time cell
uses only those workers who reported positive earnings in the calendar
year prior to the census. The sample includes both salaried and selfemployed
workers.
Let denote the mean value of a particular labor market outcomey (t)ij
for men who have education i and experience j and who are observed
at time t. The empirical analysis differences these data within each decade,
so that , and estimates the regression modelDy (t) p y (t) Ϫ y (t Ϫ 1)ij ij ij
Dy (t) p v Dp (t) ϩ v Dq (t) ϩ I ϩ J ϩ Tij 1 ij 2 ij
ϩ (I # T) ϩ (J # T) ϩ J (t), (6)ij
where I is a vector of fixed effects indicating the group’s educational
attainment; J is a vector of fixed effects indicating the group’s work
experience; and T is a vector of fixed effects indicating the time period.
The interactions and account for the possibility that(I # T) (J # T)
the returns to education and experience changed over time. Finally, the
regressions weigh the observations by the sum of sampling weights used
to calculate the variable , and the standard errors are clustered byy (t)ij
education-experience cells.
The dependent variables used to estimate equation (6) are the mean
of log annual earnings and log weekly earnings for each skill group, as
well as the fraction of weeks worked during the calendar year prior to
the census (defined as weeks worked divided by 52 in the sample of all
persons, including nonworkers). Model 1 of table 5 reports the estimates
of the coefficients and from ordinary least squares (OLS) regres-v v1 2
sions.
Consider initially the results for the specification that uses the log
weekly earnings of the skill group as the dependent variable. The key
implication of economic theory—that the in- and out-migration rates
should have opposing effects on the earnings of Puerto Rican stayers—
is strongly confirmed by the data. A larger out-migration flow increases
the wage of those who remain in the island, whereas a larger in-migration
flow decreases their wage.
The coefficient of the out-migrant share is ϩ0.537, with a standard
error of 0.185. It is easier to interpret this coefficient by converting it
to an elasticity that gives the percentage change in wages associated with
a percentage change in labor supply. Throughout this article, I have
used the expositional device of defining both in-migrant and outmigrant
shares as positive numbers (hence leading to the opposing
signs of the two coefficients in table 5). To avoid confusion in the
Labor Outflows and Labor Inflows in Puerto Rico 57
TABLE 5
Relation between Labor Flows and Labor Market Outcomes
Specification
Dependent Variable
Decadal Change
in Log
Annual Earnings
Decadal Change
in Log
Weekly Earnings
Decadal Change
in Fraction of
Weeks Worked
Model 1:
D(in-migrant share) Ϫ.631 Ϫ.543 Ϫ.243
(.246) (.269) (.187)
D(out-migrant share) .678 .537 .250
(.246) (.185) (.153)
Model 2:
D(net migrant share) Ϫ.665 Ϫ.539 Ϫ.248
(.175) (.165) (.090)
Note.—Standard errors are reported in parentheses and are adjusted for clustering within
education-experience cells. All regressions are weighted by the sum of sampling weights
in the skill cell and have 60 education-experience-year cells. The out-migrant share gives
the ratio of the number of out-migrants to the potential number of Puerto Rican–born
working men, and the in-migrant share gives the ratio of the number of in-migrants to
the number of working men in the Puerto Rican workforce. The net migrant share gives
the difference between the decadal change in the in-migrant and out-migrant shares. The
D operator for the regressors indicates that these variables are defined as decadal changes.
interpretation of a “wage elasticity,” however, it is best to explicitly define
out-migration as a negative number. Let or thex (t) p ϪX (t)/N (t),ij ij ij
percentage decrease in the size of group (i, j, t) attributable to outmigration.
It is easy to show that the wage elasticity is
Ѩ log w (t)ij 2
p Ϫv [1 Ϫ q (t)] . (7)2 ij
Ѩx (t)ij
In 2000, the out-migrant share from Puerto Rico was 38.6 percent. Equation
(7) implies that the wage elasticity associated with out-migration
(evaluated at the mean value of the out-migrant share) can be obtained
by multiplying by approximately 0.4. The wage elasticity for weeklyϪv2
earnings is then Ϫ0.21 (or with a standard error of 0.07.Ϫ0.537 # 0.4),
Put differently, a 10 percent migration-induced reduction in the number
of workers in a particular skill group increases the wage of the Puerto
Rican workers left behind by 2.1 percent.
The coefficient of the in-migrant share is Ϫ0.543, with a standard
error of 0.269. By using a derivative analogous to that defined in equation
(7), one can calculate the wage elasticity associated with in-migration.
In 2000, the in-migrant share in Puerto Rico was 13.6 percent. The
wage elasticity associated with in-migration can then be obtained by
multiplying the estimated by approximately 0.7. The wage elasticityv1
of in-migration is then equal to Ϫ0.40 (or with a standardϪ0.573 # 0.7),
error of 0.19. A 10 percent immigration-induced increase in supply,
therefore, reduces wages by about 4 percent. Although the estimated
wage elasticity of in-migration is twice the size as the estimated wage
58 Journal of Human Capital
elasticity of out-migration, the hypothesis that the two elasticities are
the same cannot be rejected.23
The estimated wage elasticity of Ϫ0.2 to Ϫ0.4 is roughly similar to
those estimated in other geographic settings using the same conceptual
framework. Borjas (2003) estimated the wage elasticity associated with
immigrant flows in the U.S. labor market to be Ϫ0.40; Aydemir and
Borjas (2007) estimated the corresponding elasticity for the Canadian
labor market to be Ϫ0.32, and Mishra (2007) estimated the wage elasticity
associated with out-migration flows in the Mexican labor market
to be Ϫ0.44. The Puerto Rican context is unique in that it allows the
estimation of equilibrating responses to both inflows and outflows in
the same market at the same time—and these wage responses seem to
be relatively similar to those found in other labor markets despite the
very different institutional, social, and economic settings.
Given the similarity of the effects of in-migration and out-migration
coefficients in the log weekly earnings regression, it is not surprising
that a regression of the log weekly wage on the net migration rate
(defined as the difference between the in-migration and out-migration
rates) leads to a similar wage effect. Model 2 of table 5 reports that the
coefficient of the net migration rate in the log weekly earnings regression
is Ϫ0.539 (0.165). The net out-migrant share in 2000 was 25 percent,
suggesting that the wage elasticity associated with a 10 percent
migrant-induced (net) shift in supply is approximately Ϫ0.30.24
One potential problem with the least-squares estimates of the wage
elasticities is that the in-migrant and out-migrant shares included as
regressors may be endogenous: income-maximizing behavior on the part
of migrants generates a negative correlation between the wage level in
the Puerto Rican labor market and the out-migrant share and a positive
correlation between wages in Puerto Rico and the in-migrant share. In
other words, the estimated wage elasticities (in absolute value) underestimate
the true impact of labor flows on Puerto Rican wages. I will
discuss this issue in more detail shortly.
Table 5 also documents that the labor supply of the Puerto Ricans
23
The difference between the two elasticities is 0.19, and this difference has a standard
error of 0.20.
24
Although the first-difference regression model used to estimate the coefficients reported
in table 5 has 60 skill-group-time cells and includes education-time and experiencetime
interactions, the regression still has 34 degrees of freedom. The evidence suggests
that the regression specification in eq. (6) does not seem “oversaturated” with fixed effects.
However, the estimated wage impact of migration flows is sensitive to the exclusion of
some of the interactions, particularly the education-time fixed effects. To illustrate,suppose
that the education-time and experience-time interactions are both excluded from the
model. The coefficient of the net migrant share then falls to Ϫ0.193 (0.124). Given the
sizable education-related changes in the wage structure during the period, the preferred
specification should include these interactions. The estimated coefficient is robust once
the education-time interactions are included in the regression model. For example, the
coefficient of the net migrant share in the regression that excludes only the experiencetime
interactions is Ϫ0.600 (0.112).
Labor Outflows and Labor Inflows in Puerto Rico 59
who remained on the island is positively affected by the out-migration
of their compatriots and negatively affected by the in-migration of foreign-born
persons. For instance, there is a negative correlation between
the fraction of weeks worked by the typical Puerto Rican stayer and the
in-migrant share and a positive correlation between the fraction of weeks
worked and the out-migrant share. The coefficient of the net migrant
share is Ϫ0.248, with a standard error of 0.090. This coefficient implies
that a 10-percentage-point migrant-induced net reduction in the supply
of workers increases the fraction of weeks worked by 1.4 percentage
points.
In sum, a simple application of the laws of supply and demand helps
to explain how the Puerto Rican wage structure responds to migrationinduced
supply shifts. Labor inflows reduce wages and labor supply;
labor outflows increase wages and labor supply.
The regressions reported in tables 3 and 5 define the system that
simultaneously determines out-migration out of Puerto Rico as well as
the wage in Puerto Rico for workers left behind. For expositional convenience,
I summarize the two-equation regression model here:
US PR
Dq (t) p b Dw (t) ϩ b Dw (t) ϩ other variables ϩ ␧ (t), (4)ij 1 ij 2 ij ij
PR
Dw (t) p v Dp (t) ϩ v Dq (t) ϩ other variables ϩ J (t). (6)ij 1 ij 2 ij ij
As noted above, income maximization on the part of migrants suggests
that the estimated parameters understate the response of migration
flows to wage changes and also understate the impact of labor flows on
the wage.
The model’s specification suggests a simple (though imperfect) solution
to the endogeneity problem faced in estimating the vector
. In particular, let the decadal change in the potential wage in the(b, v)
United States be an exogenous shifter in the out-migrant share equation,
and let the decadal change in the in-migrant share into Puerto Rico be
an exogenous shifter in the Puerto Rican wage equation. Because the
assumption that and are valid instruments may not beUS
Dw (t) Dp (t)ij ij
strictly correct, I will discuss below how any resulting biases might change
the nature of the conclusions.
Table 6 reports the instrumental variable (IV) coefficients estimated
from two alternative specifications of the two-equation system.25
Columns
1a and 1b estimate the model as summarized in equations (4) and (6),
while columns 2a and 2b estimate the model in terms of the impact of
net differences (i.e., by using the net wage gain and the net migrant
share). The “other variables” in the regression models include the vector
of education-time and experience-time interactions in equation (6).
By comparing the results reported in table 6 with the corresponding
25
All of the regression models estimated in table 6 define the potential U.S. wage as
the average wage earned by native workers in the skill group.
60 Journal of Human Capital
TABLE 6
Joint Determination of Out-migration and Weekly Wages in Puerto Rico
(IV Estimates)
Regressor
Dependent Variable/
Specification
Decadal
Change in
Out-migrant
Share of
Puerto Ricans
Decadal
Change in Log
Weekly Earnings
in Puerto
Rico
(1a) (2a) (1b) (2b)
D(mean log wage in United States) .679
(.205)
D(mean log wage in Puerto Rico) Ϫ.524
(.234)
D(net log wage gain: (United States) Ϫ (Puerto Rico)) .285
(.079)
D(in-migrant share) Ϫ.523
(.263)
D(out-migrant share) .687
(.362)
D(net migrant share: (in) Ϫ (out)) Ϫ.769
(.577)
Note.—Standard errors are reported in parentheses and are adjusted for clustering within
education-experience cells. All regressions are weighted by the sum of sampling weights
in the skill cell and have 60 education-experience-year cells. The out-migrant share gives
the ratio of the number of out-migrants to the potential number of Puerto Rican–born
working men, and the in-migrant share gives the ratio of the number of in-migrants to
the number of working men in Puerto Rico. The out-migrant share model uses the wage
of native workers in the United States as the alternative wage. The D operator for the
regressors indicates that these variables are defined as decadal changes. See the text for
a detailed description of the instruments.
results reported in tables 3 and 5, it is evident that the endogeneitycorrected
effects are often numerically larger than those obtained from
the earlier specifications. Consider the impact of the U.S. and Puerto
Rican wage on the out-migrant share The coefficients reported inq (t).ij
table 6 imply that a 10 percent increase in the potential U.S. wage raises
the net migrant share by 2.9 percentage points. The labor flows in and
out of Puerto Rico also tend to have larger effects on Puerto Rican wages.
A 10 percent increase in the net migrant share reduces the average Puerto
Rican wage by 4.3 percent.
These results should be interpreted with caution as there are reasons
to suspect that the instruments are not strictly valid. The key instrument
in equation (6) is the mean alternative wage in the U.S. labor market
(which affects the out-migration rate, but it is assumed not to directly
influence Puerto Rican wages). If Puerto Rican and U.S. wages move
in tandem (perhaps because of the interconnectedness between the two
economies), the IV coefficient of would likely be positively biased.v1
Given the disparity in economic outcomes between the two regions over
Labor Outflows and Labor Inflows in Puerto Rico 61
many decades, however, it may well be that this correlation is not very
strong.
Similarly, the key instrument used to estimate equation (4) is the inmigrant
share in the Puerto Rican workforce (which affects Puerto Rican
wages, but does not directly influence the out-migration decision of
Puerto Ricans). In this case, the IV estimate may be underestimating
the true impact of a change in the Puerto Rican wage on out-migration
rates. There is a very strong negative correlation between in-migrant
and out-migrant shares in the data. If the unobserved factors that lead
to more Puerto Ricans leaving Puerto Rico also discourage foreigners
from migrating to Puerto Rico, it is easy to show that the IV estimates
of the parameter would be positively biased. Hence the negativeb2
coefficients reported in table 6 may underestimate the response elas-
ticity.
VI. Simulating the Wage Effects of Labor Flows
I now use the regression coefficients estimated above to simulate how
the labor inflows and outflows altered the Puerto Rican wage structure.
Suppose that the estimated coefficient in a regression of the log weekly
age on the in-migrant share is and that the corresponding coefficientˆv1
on the out-migrant share is . Equation (7) then implies that theˆv2
reduced-form impacts of an in-migration flow that shifts the supply of
education group i by percent and of an out-migration flow that shiftsmi
the supply by percent can be approximated byxi
M 2ˆD log w p v (1 Ϫ p) m , (8)i 1 i
X 2ˆD log w p Ϫv (1 Ϫ q) x , (9)i 2 i
where and are the mean values of the in-migrant and out-migrantp q
shares observed in 2000. To simulate the impact of the inflows and
outflow observed in Puerto Rico between 1980 and 2000, I define the
supply shocks as
M Ϫ Mi,2000 i,1980
m p , (10)i
0.5(N ϩ N ) ϩ Mi,1980 i,2000 i,1980
X Ϫ Xi,2000 i,1980
x p Ϫ , (11)i [ ]0.5(N ϩ N ) ϩ Mi,1980 i,2000 i,1980
where Mit gives the number of in-migrants residing in Puerto Rico with
education i at time t, Nit gives the number of Puerto Rican stayers, and
Xit gives the number of Puerto Rican out-migrants residing in the United
62 Journal of Human Capital
States. Note that the baseline population used to calculate the percent
supply shifts in equations (10) and (11) averages the number of Puerto
Rican stayers over the 1980–2000 period and treats the preexisting immigrant
population as part of the “native” stock. By definition, the variable
mi is a positive number if in-migration increases the supply of
workers in Puerto Rico, and xi is a negative number if out-migration
results in a net outflow of Puerto Rican–born workers from Puerto Rico.
Table 7 summarizes the results of the simulation. Consider the evidence
summarized in the top panel of the table, which uses the OLS
wage elasticities estimated separately for in-migration and out-migration
(reported in model 1 of table 5). The wage elasticity associated with inmigration
is approximately –0.4, whereas the wage elasticity associated
with out-migration is Ϫ0.2.
As columns 1 and 2 of table 7 show, in-migration increased the number
of workers in the Puerto Rican labor market by 10.6 percent and
out-migration reduced the number by 19.2 percent. This flow of inmigrants
lowered wages by 4.2 percent, whereas the out-migrant flow
increased wages by 3.8 percent (see cols. 3 and 4). On aggregate, therefore,
labor flows had only a negligible impact on the average Puerto
Rican wage.
This result, however, masks a lot of variation across education groups.
In particular, the supply shifts differ substantially by skill. Although the
supply of the least-educated workers (high school graduates with 0–8 years
of schooling) was barely affected by in-migration, the number of workers
with more than a high school diploma rose by around 15 percent. Similarly,
the out-migration of highly educated workers reduced the number
of workers in those skill groups by 40–50 percent. However, net flows of
Puerto Rican–born workers between the United States and Puerto Rico
actually increased the supply of the least-educated workers in Puerto Rico!
The direction of the net flow of low-educated Puerto Rican–born workers
flowed from the United States to Puerto Rico between 1980 and 2000.
As a result, the process of “out-migration” increased the size of the lowskill
workforce in Puerto Rico by 25–50 percent.
Inevitably, these very different supply shifts had very different wage
effects. Consider, for example, the wage impact of in-migration. The
wage of the least-educated workers (i.e., high school dropouts with 0–
8 years of schooling) is barely affected by in-migration, whereas the
1980–2000 in-migrant influx is predicted to have reduced the wage of
college-educated workers by almost 6 percent.
The differences are much larger in the predicted impact of outmigration.
The flow of Puerto Rican–born workers between Puerto Rico
and the United States lowered the wage of the least-educated workers
by 5–10 percent, but it raised the wage of the most-educated workers
by 8–10 percent. In other words, the two-way flow of Puerto Rican–born
TABLE7
PredictedWageImpactofIn-migrationandOut-migration,1980–2000
SupplyDueto:%DDDueto:logw
ActualDlogw
(6)
In-migration
(1)
Out-migration
(2)
In-migration
(3)
Out-migration
(4)
AllMigration
(5)
WageelasticityϪ0.4forin-migrationand
Ϫ0.2forout-migration:
Allworkers10.6Ϫ19.2Ϫ.042.038Ϫ.004.283
Highschooldropouts,0–82.4ϩ51.7Ϫ.010Ϫ.102Ϫ.112.351
Highschooldropouts,9–1115.1ϩ25.0Ϫ.061Ϫ.050Ϫ.111.308
Highschoolgraduates7.5Ϫ34.9Ϫ.030.070.040.243
Somecollege17.4Ϫ55.0Ϫ.070.110.040.237
Collegegraduates13.9Ϫ38.7Ϫ.056.077.021.330
WageelasticityϪ0.3forin-andout-migration:
Allworkers10.6Ϫ19.2Ϫ.032.058.026.283
Highschooldropouts,0–82.4ϩ51.2Ϫ.007Ϫ.154Ϫ.161.351
Highschooldropouts,9–1115.1ϩ25.0Ϫ.045Ϫ.075Ϫ.120.308
Highschoolgraduates7.5Ϫ34.9Ϫ.023.105.082.243
Somecollege17.4Ϫ55.0Ϫ.052.165.113.237
Collegegraduates13.9Ϫ38.7Ϫ.042.116.074.330
Note.—Thevariablemeasuringthegroup-specificin-migrantsupplyshockisdefinedasthenumberofin-migrantsarrivingbetween1980
and2000dividedbyabaselinepopulationequaltotheaveragesizeofthePuertoRicanstayerworkforce(over1980–2000)plusthe
numberofin-migrantsin1980.Thevariablemeasuringtheout-migrantsupplyshockisdefinedasthenumberofpersonswhoout-migrated
between1980and2000dividedbyabaselinenativepopulationequaltotheaveragesizeofthePuertoRicanstayerworkforce(over1980–
2000)plusthenumberofin-migrantsin1980.Theweightedaveragesreportedfor“allworkers”usethenumberofworkersineach
educationgroupasweights.
64 Journal of Human Capital
workers had a substantial impact on the wage gap across skill groups,
increasing the relative wage of college graduates by at least 15 percent.26
The bottom panel of the table replicates the simulation exercise using
the wage elasticity estimated in the regression reported in model 2 of
table 4, which uses the net migrant share as the independent variable.
This specification constrains the wage elasticity to be the same for both
in-migration and out-migration. It is evident that the qualitative nature
of the empirical evidence is unaffected.
Finally, column 5 of table 7 adds the predicted wage effects of inmigration
and out-migration to calculate the net impact of all labor
flows on the Puerto Rican wage structure (while col. 6 reports what
actually happened to the real wage of the various skill groups). In rough
terms, the wage impact of the opposing flows of highly educated workers
(foreign-born college graduates migrating in at the same time that
Puerto Rican–born college graduates migrate out to the United States)
either washes out or results in a slight positive gain. In contrast, the
wage impact of the various labor flows on the wage of low-skill Puerto
Ricans works in the same direction, resulting in a sizable decline in the
relative wage of this group. In the end, the sizable labor flows that were
a key feature of the Puerto Rican labor market during the 1980s and
1990s reduced the relative wage of low-skill workers, perhaps by as much
as 15–20 percent.
VII. Summary
One of the central questions in the economics of migration concerns the
impact of migrants on the labor markets of sending and receiving areas.
Economic theory suggests that, at least in the short run, migrant-induced
shifts in labor supply should lead to opposite-signed changes in the wage
of competing workers. This wage response is a crucial parameter not only
in the study of the efficiency and distributional impact of migration but
also in the policy debate over how to best regulate the population flows.
Puerto Rico presents a unique laboratory for testing these implications
of economic theory since it has both large inflows and outflows of workers.
The immigrant population in Puerto Rico now makes up around
14 percent of its male workforce. Put differently, immigration into
Puerto Rico is as important a demographic phenomenon as it is in the
United States. However, in contrast to the United States (and other
26
The ultimate effect of migration on absolute wage levels depends on how capital flows
respond to the labor supply shifts. Under some separability assumptions, the relative wage
impact on different education groups is the same regardless of the extent of capital
adjustment. For example, in the three-level CES framework introduced by Borjas (2003),
the predicted wage effects for each skill group in the short and long runs differ only by
a constant, so the relative wage effect of the labor flows can be easily calculated by simply
differencing the group-specific wage effects.
Labor Outflows and Labor Inflows in Puerto Rico 65
immigrant-receiving countries), nearly 40 percent of the potential male
workforce has left the island and lives in the United States.
Using data drawn from the microdata censuses of Puerto Rico and
the United States, this article examines the determinants and consequences
of these labor flows. The empirical analysis documented a number
of findings. First, the in-migrants and the out-migrants differ significantly
in their skill composition. In particular, at least until recently,
in-migrants tend to be relatively skilled and out-migrants tend to be
relatively unskilled. This difference helps to resolve the question of how
sizable inflows and outflows can coexist if all migrants are income maximizers.
The answer is clear: the types of workers flowing in one direction
are almost the opposite (in terms of their skills) of the types flowing in
the other direction. In the end, all migrants make a sensible human
capital investment, but they collect the returns in different places.
The study also documented that inflows and outflows have opposing
effects on the Puerto Rican wage structure. Immigrants tend to reduce
wages, and out-migrants tend to increase wages. The numerical response
to these opposing flows was roughly the same: a 10 percent labor supply
shift is associated with about a 2–4 percent opposite-signed change in
wages. These wage shifts are sufficiently large for migration flows to
have a numerically important impact on the Puerto Rican wage structure.
If the wage elasticity were on the order of Ϫ0.3, a net out-migration
of 30 percent would, by itself, increase the average Puerto Rican wage
by nearly 10 percent—implying that labor flows played an important
role in the narrowing of the income gap between Puerto Rico and the
United States.
Data Appendix
Puerto Rico
The data are drawn from the 1970, 1980, 1990, and 2000 Public Use Samples
of the Puerto Rican Census. The 1970 Census extract forms a 3 percent sample
(obtained by pooling the state, municipal, and neighborhood files). The 1980–
2000 Census extracts form a 5 percent sample. The analysis is restricted to men
aged 14–64. A person is classified as a native-born Puerto Rican if he was born
in Puerto Rico. He is classified as an in-migrant from the United States if he
was born in the United States, and he is classified as an in-migrant from other
countries if he was born in other countries. Sampling weights are used in all
calculations.
Definition of education and experience.—I convert the census-provided education
variables into the IPUMS recoded variable educrec using the code provided by
the Minnesota Population Center. The workers are classified into five education
groups as follows: high school dropouts with 0–8 years of schooling (educrec ≤
high school dropouts with 9–11 years of schooling high3), (4 ≤ educrec ≤ 6),
school graduates persons with some college and(educrec p 7), (educrec p 8),
college graduates I assume that high school dropouts with 0–8(educrec p 9).
years of schooling enter the labor market at age 14, high school dropouts with
9–11 years of schooling at age 16, high school graduates at age 19, persons with
some college at age 21, and college graduates at age 23, and I define work
66 Journal of Human Capital
experience as the worker’s age at the time of the survey minus the assumed age
of entry into the labor market. I restrict the analysis to persons who have between
1 and 40 years of experience. Workers are classified into one of four experience
groups, defined in 10-year intervals.
Counts of persons in education-experience groups.—The counts are calculated in
the sample of men who worked at some point in the past year (i.e., have a
positive value for weeks worked in the calendar year).
Annual and weekly earnings.—I use the sample of men who reported positive
annual earnings and weeks worked, are not in the military in the reference
week, are not enrolled in school, and are aged 18–64. The measure of earnings
is the sum of the IPUMS variables incearn, incbus, and incfarm in 1970 and 1980
and is given by incearn for the period 1990–2000. In the 1970 and 1980 Censuses,
the top-coded annual salary is multiplied by 1.5. In the 1970 Census, weeks
worked in the calendar year prior to the survey are reported as a categorical
variable. I imputed weeks worked for each worker as follows: 6.5 weeks for 13
weeks or less, 20 for 14–26 weeks, 33 for 27–39 weeks, 43.5 for 40–47 weeks,
48.5 for 48–49 weeks, and 51 for 50–52 weeks. The average log annual earnings
or average log weekly earnings for a particular education-experience cell is
defined as the mean of log annual earnings or log weekly earnings over all
workers in the relevant population.
Fraction of time worked.—This variable is calculated in the sample of men. The
fraction of time worked for each person is defined as the ratio of weeks worked
(including zeros) to 52.
United States
The data are drawn from the 1970, 1980, 1990, and 2000 IPUMS of the U.S.
Census. The 1970 Census extract forms a 3 percent sample (obtained by pooling
the state, metropolitan area, and neighborhood files). The 1980–2000 Census
extracts form a 5 percent sample. The analysis is restricted to men aged 14–64.
A person is classified as a Puerto Rican out-migrant if he was born in Puerto
Rico. A person is classified as U.S.-born of Puerto Rican ancestry if he was born
in the United States and is Hispanic of Puerto Rican background (hispand p
Sampling weights are used in all calculations.200).
Definition of education and experience.—I use the IPUMS variable educrec to first
classify workers into five education groups: high school dropouts with 0–8 years
of schooling high school dropouts with 9–11 years of schooling(educrec ≤ 3),
, high school graduates persons with some college(4 ≤ educrec ≤ 6) (educrec p 7),
and college graduates I assume that age of entry(educrec p 8), (educrec p 9).
into the labor market is 14 for high school dropouts with fewer than 8 years of
schooling, 16 for high school dropouts with 9–11 years of schooling, 18 for high
school graduates, 21 for persons with some college, and 23 for college graduates,
and I define work experience as the worker’s age at the time of the survey minus
the assumed age of entry into the labor market. I restrict the analysis to persons
who have between 1 and 40 years of experience. Workers are classified into one
of four experience groups, defined in 10-year intervals.
Counts in education-experience groups.—The counts of out-migrants are calculated
in the sample of Puerto Rican–born men who do not reside in group quarters
and who worked at some point in the past year (i.e., have a positive value for
weeks worked in the period calendar year).
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