Educational Outcomes and Intergenerational Mobility of Second ...
Educational Outcomes and Intergenerational Mobility of Second Generation Migrants from the Middle East to the United States: a Comparative Study.
Hisham S. Foad
∗
June 2013
One of the key issues in the immigration debate is the extent to which second generation immigrants (native born, but to immigrant parents) are able to assimilate in terms of education and income. Many of these studies have focused on the di culties and educational achievement gap faced by 2nd generation immigrants from the Middle East (MENA) living in Europe. generation immigrants from the MENA living in the United States.
My studies consider 2nd
These two groups originate in
the same place, but could not be more dierent in terms of their educational outcomes. Whereas 2nd generation MENA migrants in Europe tend to have less education than their native peers, MENA migrants in the US have higher levels of education and are more likely to have undergraduate and graduate degrees. In this study I estimate several models examining the determinants of education. I nd that for the overall US population, parents' education, parents' income, and residence in an ethnic enclave all have positive eects on educational achievement.
The impact of parents' education and
income is no dierent for MENA migrants, suggesting that the education premium accruing to this group is likely to persist. However, any advantage of living in an ethnic enclave appears to disappear for MENA migrants, suggesting that these enclaves are failing to live up to their potential as incubators of immigrant human capital. Keywords: intergenerational mobility, education transmission, ethnic enclaves
∗ Department of Economics and Center for Islamic and Arabic Studies, San Diego State University. This work is preliminary and incomplete, please do not cite. All questions and comments may be directed to the author at [email protected].
1
1
Introduction
In recent years, the debate on immigration has shifted from issues surrounding new migrants to those issues facing existing populations of immigrants and their children. One of these issues is the extent to which second generation immigrants (native born, but to immigrant parents) are able to assimilate in terms of education and income. For example, numerous studies have shown that Middle Eastern migrants in Europe tend to be less educated, have lower wages, and worse employment outcomes than
1 But does the immigrant wage and education penalty
their native born, ethnic European counterparts.
persist across generations? If parent's education is a strong predictor of human capital, then we would expect education gaps between ethnic groups to persist.
However, if intergenerational mobility is
high (i.e. parent's education has less predictive power), then these gaps should not last for as many generations. Numerous studies have documented a gap between the educational outcomes second generation immigrants and natives.
Dustmann and Frattini (2012a) compare test scores of children of Turkish
immigrants in several OECD countries to native children in these countries and to Turkish children whose parents have not immigrated. They nd that the children of Turkish immigrants tend to have lower test scores than natives in the OECD countries sampled. However, their test scores are higher than those of Turkish children in Turkey, an observation they attribute to the higher school and peer quality found in these OECD countries. Ekberg et. al. (2010) present evidence that the gap between immigrants and natives may not be closing across generations. They look at earnings of 1st, 2nd, and 3rd generation immigrants in Sweden. Find that while the immigrant wage penalty does fall from the 1st generation to the 2nd and third, it never completely disappears, suggesting limited economic assimilation. Another study documenting the persistence of this gap is Colding et al (2009), who nd that in Denmark, dropout rates from vocational upper secondary education are much higher among children of immigrants.
1.1 Explaining Dierences in Education Chiswick (1988) oers three explanations for why second generation immigrants may have dierent educational outcomes than their ethnically native peers. First, some communities may have a stronger preference for schooling. In these communities, education is valued more highly and greater investments in children's human capital are made, holding other factors constant. Dierences in preferences could be attributed to cultural factors, native country experiences, or even the fact that immigrants often represent distinct group from both natives and their peers in their countries of birth. These immigrants have already made the choice to leave their native countries behind, and in the case of economic migration, they may have a stronger preference for education. Second, children from some communities may be discriminated against with regard to access to schooling or later in life with fewer job opportunities and advancement. For example, if there is a discrimination based wage penalty for being an immigrant, the return to education is reduced and the quantity of human capital investment is lowered. This is particularly relevant if immigrants face higher barriers in high skill jobs.
1 See
Dustmann and Frattini (2012b) for a comprehensive look at this issue
2
Third, some communities may simply be over-represented in the most disadvantaged socio-economic groups. Thus, dierences across ethnic groups may simply be picking up dierences in socio-economic status. While we can control for some of these socio-economic factors like income, we cannot control for everything, making identi cation di cult. Several studies have examined the question of whether or not culture matters and most have concluded that once we control for non-cultural aspects of dierent communities, culture does not appear to matter. Van Ours and Veenman (2003) look at the educational attainment of Antillean, Moroccan, and Turkish students in the Netherlands.They nd that there are dierences between these groups and they each have worse educational performances than their ethnic Dutch counterparts. However, once the educational level of parents is controlled for, the education gap between these groups (both between dierent immigrant groups and between immigrants and ethnic Dutch) disappears. Schnitzlein (2012) looks at intergenerational mobility amongst rst and second immigrants in Denmark coming from Germany, Morocco, Pakistan, and Turkey. Controlling for a range of socio-economic factors, there are no signi cant dierences in intergenerational mobility between these groups. Whereas culture has met with limited support as an explanation for education dierences between ethnic groups, considerable evidence has been found for discrimination both in education and labor markets. Bisin et. al. (2011) look at the labor market outcomes of non-EU immigrants in Europe. Find that rst generation immigrants are 17% less likely to be employed than natives. However, 2nd generation immigrants are no less likely to be employed than natives.
That said, 2nd generation
immigrants who maintain a strong ethnic identity have a signi cantly lower chance of employment than natives. Carlsson (2010) nds additional support for labor market discrimination based on ethnic identity using a clever experiment in Sweden. He sent out resumes for job openings that were identical in every way except for the fact that one was from an immigrant from the Middle East, one was from a 2nd generation Middle East immigrant (born in Sweden to immigrant parents), and one was a native Swede.
The native Swede had the highest chance of being invited to a job interview, while there
was no dierence in the likelihood of being interviewed between the 1st and 2nd generation migrants. Further support is given by Meunier (2011), who argues that up to a quarter of the observed dierence in test scores between 2nd generation immigrants in Switzerland and ethnic Swiss can be attributed to the lower expected returns to education for immigrant students. Finally, Ludemann and Schwerdt (2010) look at discrimination in educational opportunities in Germany. They nd that 2nd generation immigrants have lower grades and worse teacher recommendations than would be predicted by their scores on student achievement and intelligence tests. Another factor that could drive a gap between immigrants and natives in terms of education and labor market outcomes is pro ciency with the local language.
Domingues Dos Santos and Wol
(2011) high school graduation rates for French children of North African descent are signi cantly lower than those of ethnic French children. As the French language pro ciency of their parents increases, however, graduation rates move closer to the native level. Di Paolo and Raymond (2012) consider how knowledge of Catalan aects earnings of immigrants in the Catalan speaking part of Spain. They nd that knowledge of this language increases immigrant wages by 18%, a remarkable result considering that this a second language in the region (i.e.
most native Catalonians speak both Catalan and
Spanish.) Casey and Dustmann (2008) look at parental language pro ciency in the US. They nd that as as parental language uency increases, labor market outcomes for 2nd generation women improve.
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1.2 The Impact of Living in an Ethnic Enclave Many immigrants live in ethnic enclaves, communities in which immigrants from the same country are overrepresented. What impact does living in an ethnic enclave have on educational and labor market outcomes?
On the positive side, living in an ethnic enclave should reduce the cost of immigration
and limit the discrimination in labor markets that many immigrants face. Furthermore, the returns to pre-immigration human capital should be higher (i.e. native country language skill may be more valuable when surrounded by people who speak that language.) However, there are several reasons to believe that living in an enclave could have negative eects. The need to assimilate is reduced, which could lower human capital investments. The skill set that is acquired for life in the enclave may also not be as transferable to life outside the enclave. For example, a child living in an ethnic enclave will not have as much pressure to learn English, which is ne within the enclave, but harmful if that child were to ever leave. Finally, there may be signi cant neighborhood eects that could have both positive and negative impacts. If those living in the ethnic enclave tend to be well educated and have high incomes, then living in the enclave should have positive eects. If the enclave is of low socio-economic status, then it could have a negative impact on the educational and labor market outcomes of its residents.
2 Early studies
Most studies of ethnic enclaves have focused on the eect of these enclaves on earnings.
of this issue were plagued by simultaneity bias. Does living in an ethnic enclave aect earnings, or are immigrants choosing to live in those enclaves because wages may be higher there? Edin et. al. (2003) overcome this endogeneity problem by looking at refugees in Sweden as a natural experiment. These refugees were placed in a particular location by the Swedish government rather than by their own choice. They nd that for these refugee communities, living in an ethnic enclave increases low skilled wages by 13%. The quality of the enclave also makes a dierence, with high income enclaves having a stronger eect on wages than low income enclaves. Whereas many studies have considered the eect of living in an ethnic enclave on earnings, very few have evaluated their impact on the educational outcomes of immigrant children.
Grönqvist (2006)
looks at immigrants in Sweden and nds that for second generation immigrants, living in an ethnic enclave reduces the probability that they will graduate from high school.
Further evidence of the
negative eect of enclaves on educational outcomes is given by Chiswick and Miller (2001), who nd that living in an ethnic enclave is negatively related to English language pro ciency for immigrants to Canada. However, Gang et. al. (2000) nd that ethnic network size has a positive eect on educational attainment for 2nd generation immigrants in Germany.
1.3 What this Study Contributes Much of the existing literature on intergenerational mobility of migrants from the Middle East (henceforth MENA) focuses on immigration to Europe.
This makes sense as MENA migrants to Europe
represent a very large group and considerable attention has been paid to the di culties and successes of these groups in assimilating into European society. However, considerably fewer studies have focused on the educational outcomes of these migrants living in the United States. I argue that studying this group is important for two reasons. First, MENA migrants to the US are a fundamentally dierent group than their counterparts in Europe.
2 See
Xie and Gough (2009) for an exhaustive list of these studies. 4
Since the cost of migrating to
the US is higher than it is to Europe (longer distance, fewer established ethnic enclaves), only those immigrants that anticipate a signi cantly high return to migration will make the move to the US. As a result, MENA migrants to the US tend to be much better educated, earn higher incomes, and more likely to permanently reside in the US. The socio-economic pro le of MENA migrants to Europe most closely resembles that of Mexican migrants to the US. Thus, we have two groups (MENA migrants to the US and Europe) that are culturally similar, but have dierent socio-economic characteristics. Comparing intergenerational mobility between these two groups allows for better identi cation of these socio-economic factors as well as institutional factors in Europe and the US. The second reason for studying MENA migrants to the US is that this is a rapidly growing immigrant community.
According to Camarota (2002), the immigrant community from the MENA in the US
had a seven-fold increase between 1970 and 2000, growing from fewer than 200,000 to over 1.5 million. Contrast this with the only three-fold increase in the general immigrant population over this period. Given that MENA migrants to the US tend to have higher fertility rates than the average US population (CDC National Vital Statistics System, 2011), the MENA diaspora in the United States is only expected to grow in the coming years. Given the rapid growth of this community, it is important to understand the degree to which the children of these immigrants are able to economically assimilate into American society. In this study, I empirically show that the MENA ethnic group has higher educational outcomes than the general US population. Overall, educational outcomes are increasing in parents' education, parents' income, and residence in an ethnic enclave. The eects of parents' education and income are no dierent for 2nd generation MENA migrants, suggesting that the education premium of being a MENA migrant will persist across generations.
However, I nd that the advantages of living in an ethnic enclave
disappear for MENA migrants, suggesting some fundamental dierences between these enclaves (and thus the people living in them) and the enclaves inhabited by other ethnicities. The rest of the paper proceeds as follows: Section 2 presents the data and variable construction, section 3 outlines the empirical methodology, section 4 discusses the results, and section 5 concludes.
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Data
2.1 Dataset and Variable Construction To assess intergenerational mobility of MENA migrants in the United States, I use individual level data from the 2011 American Community Survey, public use microdata sample. As my study is concerned with second generation immigrants, I restrict my sample to only those people that were born in the United States. Second generation immigrants are de ned as having been born in the United States to
3 2nd generation MENA migrants are de ned as native born children 4 who have at least one parent born in one of twenty on countries in the MENA. at least one parent born abroad.
3 A growing strand of literature dierentiates between 2nd generation and 2.5 generation immigrants. In the former case, both parents were born abroad, while in the latter, one parent is an immigrant and the other is native born. Ramakrishnan and Karthick (2004) argue that we need to distinguish between these two groups as they dier signi cantly in terms of racial identi cation, education, and income. A future draft of this paper will assess the dierence between these groups. 4 The 21 countries are Algeria, Bahrain, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Sudan, Syria, Tunisia, Turkey, UAE, and Yemen
5
For each observation, I collect data on age, years of education, county of residence, parents' education, parents' income, parents' English speaking ability, and parents' birthplace. I restrict the sample to individuals aged 25 years and older.
While this limits the sample size for ethnic groups that are
relatively recent arrivals to the US (Somali refugees for example), it is necessary to not underestimate educational outcomes for these groups. From this dataset, I create the variables de ned below in Table 1. Deleting all missing values (mostly related to parental variables), I end up with a sample of 56,442 observations.
Table 1: Variable De nitions Edi
Years of education.
This variable is computed from the ACS variable
"educd" where, for example, completing 1st grade is equivalent to 1 year of education and completing 6th grade is equivalent to 6 years of education. High school graduates have 12 years of education, college graduates have 16 years of education, and those with a professional degree have 20 years of education. In the empirical analysis, I take the natural log of this variable.
HSi
A dummy variable equal to 1 if the observation has at least a high school diploma
Collegei
A dummy variable equal to 1 if the observation has at least a bachelors degree
P rof essionali
A dummy variable equal to 1 if the observation has completed a professional degree
M omEdi
Similar to
Ed
above, but for the observation's mother
DadEdi
Similar to
Ed
above, but for the observation's father
M omLangi
A dummy variable equal to one if the observation's mother self reports her ENglish langiage ability as "speaks only English," "speaks very well," or "speaks well." Equal to zero if the mother rates her ability as "does not speak English" or "speaks English, but not well."
DadLangi
Similar to
M omLang ,
Enclavei
A dummy variable equal to one if the observation lives in a county that is
but for the observation's father.
considered to be an ethnic enclave. An ethnic enclave is de ned as a county in which immigrants from a particular country are at least three times as
a
likely to live in as the average American resident.
M Ei
A dummy variable equal to 1 if at least one of the observation's parents was born in the Middle East.
a The
results are not too dierent if I lower this threshold to 2 or raise it to 4
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2.2 Pro le of Educational Outcomes across Ethnic Groups Using this methodology, I am able to decompose educational outcomes across several dierent ethnicities.
Table 2 presents the average years of education and the fraction of the sample that has a
high school diploma, college degree, and professional degree. I consider these outcomes between native born and immigrants across the entire sample and between immigrants and native born whites, Middle Easterners, Mexicans, Latin Americans (non-Mexican), Sub-Saharan Africans, South Asians, and East Asians. Natives from each group are de ned as people who were born in the US to either parents from one of these regions or who claim a rst ancestry from these regions. Thus, I am mixing together 2nd and higher generation immigrants in these groups, though the majority are 2nd generation (native born, but to immigrant parents.)
Table 2: Educational Attainment across Immigrant and Ethnic Groups All
Years Education
H.S.
College
Professional
13.1
85.7%
28.0%
10.9%
Foreign Born
12.0
69.9%
28.6%
12.3%
Native Born
13.3
88.5%
27.9%
10.6%
White Immigrants
13.0
80.9%
31.9%
14.6%
White Natives
13.3
88.6%
27.4%
10.3%
MENA Immigrants
13.9
85.2%
46.8%
21.4%
MENA Natives
14.8
95.1%
51.0%
22.1%
Mexican Immigrants
8.8
38.6%
5.2%
1.4%
Mexican Natives
12.2
77.5%
14.3%
4.2%
Latin American Immigrants
11.1
63.4%
16.6%
5.8%
Latin American Natives
13.0
84.7%
23.6%
8.3%
SS African Immigrants
13.6
86.2%
39.0%
17.4%
SS African Natives
12.8
82.0%
19.7%
17.4%
S. Asian Immigrants
15.2
89.0%
66.2%
36.4%
S. Asian Natives
16.2
96.3%
74.3%
39.9%
E. Asian Immigrants
13.4
81.7%
44.5%
16.8%
E. Asian Natives
14.7
95.7%
50.7%
17.4%
Years Education refers to the average years of education attained for each group. 12 years of education is equivalent to a high school degree, 16 years a college degree, and 20+ years a professional degree. H.S., College, and Professional refer to the fraction of each group that have at least a high school diploma, bachelors degree, and professional degree repsectively. Immigrants are de ned as people who were born in a country other than the U.S., while Natives were born in the U.S. with reported ancestries to the speci ed group. Across all ethnicities, immigrants have on average 1.3 fewer years of education, with 12 years on average for immigrants and 13.3 years for natives. A much lower percentage of immigrants have completed high school, with under 70% of immigrants holding a high school degree compared to nearly 90% for natives. Interestingly, those immigrants who have completed high school are much more likely to have completed college and professional degrees. In my sample, about 28% of native born Americans have
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at least a bachelors degree and 10.6% have a professional degree.
For immigrants, these shares are
28.6% and 12.3%. That immigrants tend to have higher rates of tertiary education attainment could simply be a re ection of US immigration policy favoring skilled migration. There are signi cant dierences across ethnic groups. educated than the general US population.
migrants from the MENA tend to be better
MENA migrants average 14 years of education and a
signi cantly higher fraction of these immigrants have college and professional degrees. Ethnic Middle Easterners born in the US are even better educated than their immigrant forebears. MENA natives average nearly 15 years of education, over half have at least a bachelors degree and 22% hold a professional degree, averages well above average American resident. The same pattern that holds for MENA migrants and natives also holds for the East and South Asian diasporas in the US. For each group, both immigrants and natives tend to be better educated than the average American, and the high education of immigrants is transferred over to future generations with increased educational outcomes for natives. Average education tends to be lowest for Mexican immigrants, but there are signi cant increases when going from Mexican immigrants to natives. This suggests that the average education gap for Mexican immigrants will disappear over a few generations. The only group that shows a decline in educational outcomes across generations are sub-Saharan Africans. Immigrants average 13.6 years of education and greater fractions of college and professional school graduates than the average American. However, 2nd generations have worse outcomes than the average American. Table 3 presents parent's educational outcomes across my sample. In every case, the average years of education for parents are lower than average years for their children, indicating an increase in the average education over time for both immigrants and natives in the US. Contrasting mother's and father's education, the biggest gender gaps are for South Asians (fathers have two more years of education), and for the MENA (fathers have 0.9 more years on average).
Interestingly, the largest
education gaps are also for the most educated groups, and even for these groups, average years of mother's education are the two highest in the sample.
At dierent levels of education, the largest
gender gaps are at the college and graduate levels. This pattern is not unique to any ethnic group, however, and is more likely due to traditional gender roles and childbearing decisions.
5
Given the diversity in educational outcomes across groups, it is useful to further break these gures down by speci c MENA countries. Table 4 presents these outcomes across the seven countries with the largest diasporas (immigrants and native born with ancestral ties) in the US. In every case, 2nd (and higher) generation immigrants have more education than immigrants, a remarkable fact given that immigrants themselves are coming in with already high levels of education. Looking across groups, the highest levels of education are for Egyptian and Iranian immigrants. Both of these two groups had large waves of migration in the 1960's and 1970's. The older diasporas like Lebanon and Syria (most of whom arrived in the 1920's-1940's) tend to slightly lower years of education, though still higher than the average US population.
The largest gap between immigrants
and natives is for the Iraqi diaspora. Iraqi immigrants have a relatively low 11.9 years of education, compared to 15.7 years for US born Iraqis. Much of this gap can be attributed to the recent wave of Iraqi refugee migration. Overall, though, the trends across individual countries mirror those for the MENA as a whole and the rest of the analysis will treat these dierent diasporas as a single group.
5 Interestingly, this trend is expected to reverse in the future given the larger fraction of women in American universities
than men.
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Table 3: Parent's Educational Endowments across Ethnicities All
White
MENA
Mexican
Lat. Am.
SS Africa
S. Asia
E. Asia
Mother
11.6
12.3
13.0
9.2
11.1
12.4
13.6
12.5
Father
12.4
12.6
13.9
9.0
11.1
12.6
15.6
13.1
Mother
72.9%
80.3%
81.6%
45.7%
65.5%
75.5%
81.2%
79.6%
Father
78.4%
81.4%
80.4%
45.0%
64.6%
78.9%
91.3%
83.4%
Mother
14.1%
14.1%
31.5%
4.6%
11.1%
22.3%
44.1%
30.6%
Father
20.3%
20.7%
42.6%
6.0%
12.1%
25.8%
64.7%
34.9%
Mother
4.9%
5.2%
12.0%
1.3%
3.9%
9.8%
17.5%
7.3%
Father
8.4%
8.5%
21.5%
2.4%
4.6%
16.3%
38.2%
12.3%
Years Education
High School
College
Professional
Yrs Education refers to the total years of education completed by the observations mother and father. For example, if mother's years of education is 12, then the observation's mother has completed high school. High School, College, and Professional are dumy variables equal to 1 if the observation's parent completed high school, college, or graduate school respectively. English is a dummy variable equal to 1 if the observation's parent rates their English speaking ability as "speaks well" or "speaks very well" and equal to zero if the parent rates their ability as "does not speak English" or "does not speak well."
2.3 De ning Ethnic Enclaves An interesting issue raised in the literature is the extent to which living in an ethnic enclave aects intergenerational mobility and investment in human capital. On one hand, living in an ethnic enclave may increase human capital investment since immigrants will face lower migration costs when moving to an enclave and their children will face less labor market discrimination in these enclaves, increasing the return to education. On the other hand, living in an enclave reduces the need for a migrant to assimilate, limiting English language acquisition and thus reducing educational attainment. Furthermore, if people within the enclave have lower socio-economic indicators, then there may be negative neighborhood eects on educational outcomes.
(AI) j living in county i i0 s share of the US
I use a unique methodology to de ne an ethnic enclave. I construct an agglomeration index for each ethnic group and US county. The agglomeration index for ethnic group is de ned as the fraction of ethnic group
j
living in county
i
divided by county
population:
AIij =
P opji /P opj P opi /P op
(1)
For example, 3.815% of the MENA diaspora lives in Wayne County, Michigan. This county represents 0.674% of the US population. Michigan is thus
The agglomeration index for the MENA diaspora in Wayne County,
M EN A AIW ayneCounty,M I = 3.815%/0.674% = 5.7.
This number can be interpreted as how
much more or less likely a member of a particular ethnic group is to live in a county than the average
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Table 4: Educational Attainment across MENA Countries and Ancestries Years Education
H.S.
College
Mena Immigrants
13.9
85.2%
46.8%
Professional 21.4%
Mena Natives
14.8
95.1%
51.0%
22.1%
Egyptian Immigrants
15.3
95.3%
64.7%
22.8%
Egyptian Natives
16.1
96.5%
74.6%
38.2%
Iranian Immigrants
14.6
90.7%
54.1%
26.4%
Iranian Natives
16.2
96.8%
72.6%
37.5%
Iraqi Immigrants
11.9
71.4%
28.7%
8.2%
Iraqi Natives
15.7
92.3%
69.2%
38.5%
Jordanian Immigrants
13.0
80.4%
33.6%
14.2%
Jordanian Natives
14.3
97.1%
34.3%
11.4%
Lebanese Immigrants
13.7
82.4%
41.4%
22.3%
Lebanese Natives
14.8
95.6%
50.6%
20.9%
Syrian Immigrants
13.2
76.3%
40.0%
20.5%
Syrian Natives
14.1
93.1%
39.7%
17.1%
Turkish Immigrants
14.4
87.6%
55.1%
28.5%
Turkish Natives
14.6
92.6%
46.7%
22.2%
Years Education refers to the average years of education attained for each group. 12 years of education is equivalent to a high school degree, 16 years a college degree, and 20+ years a professional degree. H.S., College, and Professional refer to the fraction of each group that have at least a high school diploma, bachelors degree, and professional degree repsectively. Immigrants are de ned as people who were born in a country other than the U.S., while Natives were born in the U.S. with reported ancestries to the speci ed group. 6 Thus, ethnic Middle Easterners (both immigrants and native born) are 5.7 times
American county.
more likely to live in Wayne County, Michigan than the average American. An agglomeration index less than 1 means that a member of the diaspora is less likely to live in that county than the average American, while an index over 1 suggests that they are more likely. An advantage of this measure is that it is scale free. For example, would expect there to be a large number of ethnic Middle Easterners in New York City, simply because there are a lot of people that live in New York City.
But how signi cant is the MENA community?
Is it tightly organized with
services oered for its residents such as Arabic language schools and ethnically owned businesses? The agglomeration index measures the relative importance of the community in a particular county and is thus more likely to be correlated with the features of an ethnic enclave that would aect educational attainment. Table 5 presents the top 15 and bottom 10 counties in the US for the MENA diaspora based o the agglomeration index (conditional upon there being at least one ethnic Middle Easterner in a county). The results are fairly consistent with anecdotal evidence on where the largest MENA communities are
6 For Western European ancestries, I set the agglomeration index equal to 1. This implicitly assumes that the geographic distribution for people of Western European descent mimics the general US population (of which they are a big part).
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Table 5: Agglomeration Indexes for Middle Eastern Migrants State
County
Agglomeration Index
Top 15 Counties Michigan
Wayne County
5.7
Michigan
Macomb County
5.5
California
Stanislaus County
5.4
New Jersey
Hudson County
5.4
Michigan
Oakland County
5.3
Tennessee
Davidson County
5.1
California
Los Angeles County
4.6
New Jersey
Passaic County
4.6
New Jersey
Bergen County
4.5
Virginia
Alexandria city
4.5
California
San Mateo County
3.9
California
San Diego County
3.9
Virginia
Henrico County
3.9
New York
Richmond County
3.8
Texas
Collin County
3.8
Bottom 10 Counties Oregon
Douglas County
0.06
Texas
Johnson County
0.06
Connecticut
Middlesex County
0.05
North Carolina
Alamance County
0.05
Illinois
Tazewell County
0.05
Utah
Weber County
0.04
Idaho
Canyon County
0.03
Colorado
Weld County
0.03
Texas
Cameron County
0.03
Louisiana
Orleans Parish
0.02
The Agglomeration Index is computed as the fraction of all migrants from the Middle East living in a particular county divided by that county's share of the US population. It can be interpreted as how much more or less likely a Middle Eastern migrant is to live in a particular county. Thus, an Agglomeration Index of 3.0 implies that a MENA migrant is three times as likely to live in that county as the average American, while an index of 0.5 means that the migrant is only half as likely to live there. located. As expected, several counties around Dearborn, Michigan represent the largest ethnic enclaves, re ecting the very large Middle Eastern community in this region.
Stanislaus County in California
also shows up as a signi cant enclave, mostly due to the very large Iraqi Assyrian community there. While there are some expected results in this top 15, there are a few surprises, such as Garrett County, Maryland, which is a fairly rural county in western Maryland.
7
7 This may be an outlier as the ACS only reports 857 ethnic Middle Easterners in this county, which ends up being a large agglomeration index given the relatively small population size of this county. I have estimated the empirical model excluding counties with less than 100,000 people and the results do not qualitatively change, however.
11
Table 6: Agglomeration Indexes for other Ancestries Mexico
Latin America
Imperial County, California
11.3
Hudson County, New Jersey
Hidalgo County, Texas
11.1
Queens County, New York
9.4 8.5
Webb County, Texas
10
Union County, New Jersey
8.3
El Paso County, Texas
9.1
Osceola County, Florida
6.9
Cameron County, Texas
8.2
Broward County, Florida
6.8
Yuma County, Arizona
7.2
Arlington County, Virginia
6.2
Tulare County, California
7
Essex County, New Jersey
5.7
Merced County, California
6.5
Suolk County, Massachusetts
5.2
Madera County, California
6.1
Alexandria City, Virginia
5.1
Santa Barbara County, California
5.9
Montgomery County, Maryland
4.7
Kings County, New York
10.8
Alexandria city, Virginia
24.6
Richmond County, New York
7.5
Montgomery County, Maryland
12.3
Queens County, New York
6.3
Hennepin County, Minnesota
9.8
Cook County, Illinois
6.0
Bronx County, New York
9.4
Bergen County, New Jersey
5.8
Ramsey County, Minnesota
9.1
Sacramento County, California
4.7
DeKalb County, Georgia
7.8
Yolo County, California
4.7
Montgomery County, Tennessee
7.6
Spokane County, Washington
4.7
Clayton County, Georgia
7.6
Passaic County, New Jersey
4.3
Arlington County, Virginia
7.3
DuPage County, Illinois
4.2
Essex County, New Jersey
6.9
Middlesex County, New Jersey
14.6
San Francisco County, California
Fort Bend County, Texas
9.7
Honolulu County, Hawaii
8.3
Hudson County, New Jersey
8.1
Santa Clara County, California
8.2
Queens County, New York
7.9
San Mateo County, California
6.6
Santa Clara County, California
7.8
Alameda County, California
6.4
S.S. Africa
Eastern Europe
South Asia
East Asia 10.7
Somerset County, New Jersey
7.8
Queens County, New York
5
Alameda County, California
6.7
Orange County, California
5
Harford County, Maryland
6.6
Fort Bend County, Texas
4.7
Collin County, Texas
5.5
King County, Washington
4.2
DuPage County, Illinois
5.1
Bergen County, New Jersey
4.2
The agglomeration index is computed as the fraction of country's migrants to the US living in the speci ed county divided by tht county's share of the US population. For example, the index for Mexican migrants living in Imperial County, California is 11.3, implying that migrants from Mexico are 11.3 times more likely to live in Imperial County than the average American resident. I also present the top ten ethnic enclaves for six other ethnicities in my sample in Table 6. The results are again consistent with anecdotal evidence on what communities are ethnic enclaves. For example, Mexicans are heavily represented in Southern California and South Texas, while Latin Americans are prevalent in South Florida. Sub-Saharan Africans are well represented in the Baltimore/D.C. area as
12
well as several counties around Minneapolis with large Eritrean and Somali refugee communities. South Asians have signi cant communities around Silicon Valley, while East Asians are well represented in San Francisco (large Chinese and Korean communities) and Hawaii (signi cant Japanese community).
3
Methodology
It is common in the literature on intergenerational mobility to write the relationship between outcomes of parents and outcomes of children as
yi,t = α + ρyi,t−1 + ui,t yi,t
(2)
yi,t−1 measure outcomes such as education, earnings, or wealth for children (t) and their (t − 1). For example, let y be equal to education. Then, the earnings of family i0 s child is 0 determined by family i s parental education and other in uences u. The parameter α can be thought of as the average eect of these other in uences. If we assume that the variances of yi,t and yi,t−1 are 8 the same, then ρ is the population correlation coe cient between yi,t and yi,t−1 . The estimated coef cient ρ ˆ will then measure the fraction of economic advantage (measured in terms of education in this and
parents
case) that is transmitted across generations. This term is also known as the transmission parameter (Dustmann et. al., 2012). An estimate close to zero suggests high intergenerational mobility, while a coe cient closer to 1 indicates low mobility. We can use this methodology to assess assimilation of immigrant populations over time. De ne equation 1 separately for the native and immigrant populations:
N N yi,t = αN + ρN yi,t−1 + uN i,t I I I I I Immigrants: yi,t = α + ρ yi,t−1 + ui,t Natives:
Allow the two transmission parameter to dier between these groups as: outcome dierential between natives and immigrants in generation
t
ρI = ρN + γ .
The expected
will then be given by:
N I N I I E(yi,t ) − E(yi,t ) = αN − αI + ρN E(yi,t−1 ) − E(yi,t−1 ) − γE(yi,t−1 )
(3)
Suppose that the only dierence between native and immigrant educational outcomes is intergenera-
αN = αI ). Then, equation 2 simpli es to: N I I = ρN E(yi,t−1 ) − E(yi,t−1 ) − γE yi,t−1 .
tional mobility (i.e.
N E(yi,t )
−
I E(yi,t )
Thus, the parameter
ρN
will determine the rate at which the gap between immigrant and native
γ = 0, then if ρN = 1, this gap will persist over time ρ = 0, then the gap disappears from one generation N will be faster for smaller values of ρ . If γ < 0, then
educational outcomes disappears. Assuming that since there is no intergenerational mobility. If to the next. Thus, assimilation of immigrants
N
the transmission parameter is larger for natives than for immigrants and the education gap will persist longer. Of course, this analysis assumes that
N I yi,t > yi,t .
If immigrants have higher educational outcomes than
natives (as is the case with MENA migrants), then the story above will be reversed. A negative value
8 If
the variances are dierent across generations, then the OLS estimator ρˆ measures ρ ∗ σyt /σyt−1 13
for
γ
γ
implies that immigrant education will converge with native education, while a positive value for
suggests that the immigrant education premium will persist longer.
Of course, intergenerational mobility is not the only factor determining the gap between immigrant and native educational outcomes. Such things as language acquisition, dierences in the way educational systems treat immigrant children, discrimination, or dierent educational incentives due to living in an ethnic enclave could all contribute to the education gap between these groups. To account for these other factors, I build an augmented version of the model presented in equation 1. This model relates years of education to parents education, parent's income, parent's pro ciency with English, and whether the observation lives in an ethnic enclave.
Edi = α+ρ1 M omEdi +ρ2 DadEdi +β1 ln P arYi +β2 M omLangi +β3 DadLangi +β4 Enclavei +ui Observation
i0 s
(4)
log years of education is regressed on mother's log years of education and father's log
years of education.
P arYi
is de ned as the observation's parent's family income, calculated as the
9 Language is measured as a dummy variable equal
maximum between mother's and father's income.
to 1 if the observation's parent can speak English either well or very well and equal to zero if the parent either doesn't speak English at all or has trouble with English according to the Census questionnaire. The variable
Enclave is equal to 1 if the observation lives in a county with an agglomeration
10
index greater than 3.0.
To evaluate how intergenerational mobility diers between the average American and ethnic Middle Easterners born in the United States, I create a dummy variable
ME
which is equal to 1 if the
observation was born in the United States, but claims a rst ancestry from a country in the Middle East. I then interacted this dummy with each of the variables in equation 3:
Edi
= α + ρ1 M omEdi + ρ2 DadEdi + β1 P arYi + β2 M omLangi + β3 DadLangi +β3 Enclavei + δ0 M Ei + δ1 M omEdi ∗ M Ei + δ2 DadEdi ∗ M Ei + δ3 P arYi ∗ M Ei
(5)
+δ4 M omLangi ∗ M Ei + δ5 DadLangi ∗ M Ei + δ6 Enclavei ∗ M Ei + ui The parameter
δ0
captures how much more education 2nd generation MENA migrants are predicted
to have than the average American. Speci cally, MENA migrants are predicted to roughly
δ0 %
more
years of education. The interaction terms estimate how much more or less factors like parental income education, and English language ability aect educational attainment. For example, a 1% increase in mother's education is predicted to increase years of education by
(ρ1 + δ1 )%,
compared to
ρ1 %
for the
average American. If the sum of
δ1 + δ2
is negative, then we predict that parental education has a smaller eect for
MENA migrants than for the average American. This is equivalent to the case where
γ
Hisham S. Foad
∗
June 2013
One of the key issues in the immigration debate is the extent to which second generation immigrants (native born, but to immigrant parents) are able to assimilate in terms of education and income. Many of these studies have focused on the di culties and educational achievement gap faced by 2nd generation immigrants from the Middle East (MENA) living in Europe. generation immigrants from the MENA living in the United States.
My studies consider 2nd
These two groups originate in
the same place, but could not be more dierent in terms of their educational outcomes. Whereas 2nd generation MENA migrants in Europe tend to have less education than their native peers, MENA migrants in the US have higher levels of education and are more likely to have undergraduate and graduate degrees. In this study I estimate several models examining the determinants of education. I nd that for the overall US population, parents' education, parents' income, and residence in an ethnic enclave all have positive eects on educational achievement.
The impact of parents' education and
income is no dierent for MENA migrants, suggesting that the education premium accruing to this group is likely to persist. However, any advantage of living in an ethnic enclave appears to disappear for MENA migrants, suggesting that these enclaves are failing to live up to their potential as incubators of immigrant human capital. Keywords: intergenerational mobility, education transmission, ethnic enclaves
∗ Department of Economics and Center for Islamic and Arabic Studies, San Diego State University. This work is preliminary and incomplete, please do not cite. All questions and comments may be directed to the author at [email protected].
1
1
Introduction
In recent years, the debate on immigration has shifted from issues surrounding new migrants to those issues facing existing populations of immigrants and their children. One of these issues is the extent to which second generation immigrants (native born, but to immigrant parents) are able to assimilate in terms of education and income. For example, numerous studies have shown that Middle Eastern migrants in Europe tend to be less educated, have lower wages, and worse employment outcomes than
1 But does the immigrant wage and education penalty
their native born, ethnic European counterparts.
persist across generations? If parent's education is a strong predictor of human capital, then we would expect education gaps between ethnic groups to persist.
However, if intergenerational mobility is
high (i.e. parent's education has less predictive power), then these gaps should not last for as many generations. Numerous studies have documented a gap between the educational outcomes second generation immigrants and natives.
Dustmann and Frattini (2012a) compare test scores of children of Turkish
immigrants in several OECD countries to native children in these countries and to Turkish children whose parents have not immigrated. They nd that the children of Turkish immigrants tend to have lower test scores than natives in the OECD countries sampled. However, their test scores are higher than those of Turkish children in Turkey, an observation they attribute to the higher school and peer quality found in these OECD countries. Ekberg et. al. (2010) present evidence that the gap between immigrants and natives may not be closing across generations. They look at earnings of 1st, 2nd, and 3rd generation immigrants in Sweden. Find that while the immigrant wage penalty does fall from the 1st generation to the 2nd and third, it never completely disappears, suggesting limited economic assimilation. Another study documenting the persistence of this gap is Colding et al (2009), who nd that in Denmark, dropout rates from vocational upper secondary education are much higher among children of immigrants.
1.1 Explaining Dierences in Education Chiswick (1988) oers three explanations for why second generation immigrants may have dierent educational outcomes than their ethnically native peers. First, some communities may have a stronger preference for schooling. In these communities, education is valued more highly and greater investments in children's human capital are made, holding other factors constant. Dierences in preferences could be attributed to cultural factors, native country experiences, or even the fact that immigrants often represent distinct group from both natives and their peers in their countries of birth. These immigrants have already made the choice to leave their native countries behind, and in the case of economic migration, they may have a stronger preference for education. Second, children from some communities may be discriminated against with regard to access to schooling or later in life with fewer job opportunities and advancement. For example, if there is a discrimination based wage penalty for being an immigrant, the return to education is reduced and the quantity of human capital investment is lowered. This is particularly relevant if immigrants face higher barriers in high skill jobs.
1 See
Dustmann and Frattini (2012b) for a comprehensive look at this issue
2
Third, some communities may simply be over-represented in the most disadvantaged socio-economic groups. Thus, dierences across ethnic groups may simply be picking up dierences in socio-economic status. While we can control for some of these socio-economic factors like income, we cannot control for everything, making identi cation di cult. Several studies have examined the question of whether or not culture matters and most have concluded that once we control for non-cultural aspects of dierent communities, culture does not appear to matter. Van Ours and Veenman (2003) look at the educational attainment of Antillean, Moroccan, and Turkish students in the Netherlands.They nd that there are dierences between these groups and they each have worse educational performances than their ethnic Dutch counterparts. However, once the educational level of parents is controlled for, the education gap between these groups (both between dierent immigrant groups and between immigrants and ethnic Dutch) disappears. Schnitzlein (2012) looks at intergenerational mobility amongst rst and second immigrants in Denmark coming from Germany, Morocco, Pakistan, and Turkey. Controlling for a range of socio-economic factors, there are no signi cant dierences in intergenerational mobility between these groups. Whereas culture has met with limited support as an explanation for education dierences between ethnic groups, considerable evidence has been found for discrimination both in education and labor markets. Bisin et. al. (2011) look at the labor market outcomes of non-EU immigrants in Europe. Find that rst generation immigrants are 17% less likely to be employed than natives. However, 2nd generation immigrants are no less likely to be employed than natives.
That said, 2nd generation
immigrants who maintain a strong ethnic identity have a signi cantly lower chance of employment than natives. Carlsson (2010) nds additional support for labor market discrimination based on ethnic identity using a clever experiment in Sweden. He sent out resumes for job openings that were identical in every way except for the fact that one was from an immigrant from the Middle East, one was from a 2nd generation Middle East immigrant (born in Sweden to immigrant parents), and one was a native Swede.
The native Swede had the highest chance of being invited to a job interview, while there
was no dierence in the likelihood of being interviewed between the 1st and 2nd generation migrants. Further support is given by Meunier (2011), who argues that up to a quarter of the observed dierence in test scores between 2nd generation immigrants in Switzerland and ethnic Swiss can be attributed to the lower expected returns to education for immigrant students. Finally, Ludemann and Schwerdt (2010) look at discrimination in educational opportunities in Germany. They nd that 2nd generation immigrants have lower grades and worse teacher recommendations than would be predicted by their scores on student achievement and intelligence tests. Another factor that could drive a gap between immigrants and natives in terms of education and labor market outcomes is pro ciency with the local language.
Domingues Dos Santos and Wol
(2011) high school graduation rates for French children of North African descent are signi cantly lower than those of ethnic French children. As the French language pro ciency of their parents increases, however, graduation rates move closer to the native level. Di Paolo and Raymond (2012) consider how knowledge of Catalan aects earnings of immigrants in the Catalan speaking part of Spain. They nd that knowledge of this language increases immigrant wages by 18%, a remarkable result considering that this a second language in the region (i.e.
most native Catalonians speak both Catalan and
Spanish.) Casey and Dustmann (2008) look at parental language pro ciency in the US. They nd that as as parental language uency increases, labor market outcomes for 2nd generation women improve.
3
1.2 The Impact of Living in an Ethnic Enclave Many immigrants live in ethnic enclaves, communities in which immigrants from the same country are overrepresented. What impact does living in an ethnic enclave have on educational and labor market outcomes?
On the positive side, living in an ethnic enclave should reduce the cost of immigration
and limit the discrimination in labor markets that many immigrants face. Furthermore, the returns to pre-immigration human capital should be higher (i.e. native country language skill may be more valuable when surrounded by people who speak that language.) However, there are several reasons to believe that living in an enclave could have negative eects. The need to assimilate is reduced, which could lower human capital investments. The skill set that is acquired for life in the enclave may also not be as transferable to life outside the enclave. For example, a child living in an ethnic enclave will not have as much pressure to learn English, which is ne within the enclave, but harmful if that child were to ever leave. Finally, there may be signi cant neighborhood eects that could have both positive and negative impacts. If those living in the ethnic enclave tend to be well educated and have high incomes, then living in the enclave should have positive eects. If the enclave is of low socio-economic status, then it could have a negative impact on the educational and labor market outcomes of its residents.
2 Early studies
Most studies of ethnic enclaves have focused on the eect of these enclaves on earnings.
of this issue were plagued by simultaneity bias. Does living in an ethnic enclave aect earnings, or are immigrants choosing to live in those enclaves because wages may be higher there? Edin et. al. (2003) overcome this endogeneity problem by looking at refugees in Sweden as a natural experiment. These refugees were placed in a particular location by the Swedish government rather than by their own choice. They nd that for these refugee communities, living in an ethnic enclave increases low skilled wages by 13%. The quality of the enclave also makes a dierence, with high income enclaves having a stronger eect on wages than low income enclaves. Whereas many studies have considered the eect of living in an ethnic enclave on earnings, very few have evaluated their impact on the educational outcomes of immigrant children.
Grönqvist (2006)
looks at immigrants in Sweden and nds that for second generation immigrants, living in an ethnic enclave reduces the probability that they will graduate from high school.
Further evidence of the
negative eect of enclaves on educational outcomes is given by Chiswick and Miller (2001), who nd that living in an ethnic enclave is negatively related to English language pro ciency for immigrants to Canada. However, Gang et. al. (2000) nd that ethnic network size has a positive eect on educational attainment for 2nd generation immigrants in Germany.
1.3 What this Study Contributes Much of the existing literature on intergenerational mobility of migrants from the Middle East (henceforth MENA) focuses on immigration to Europe.
This makes sense as MENA migrants to Europe
represent a very large group and considerable attention has been paid to the di culties and successes of these groups in assimilating into European society. However, considerably fewer studies have focused on the educational outcomes of these migrants living in the United States. I argue that studying this group is important for two reasons. First, MENA migrants to the US are a fundamentally dierent group than their counterparts in Europe.
2 See
Xie and Gough (2009) for an exhaustive list of these studies. 4
Since the cost of migrating to
the US is higher than it is to Europe (longer distance, fewer established ethnic enclaves), only those immigrants that anticipate a signi cantly high return to migration will make the move to the US. As a result, MENA migrants to the US tend to be much better educated, earn higher incomes, and more likely to permanently reside in the US. The socio-economic pro le of MENA migrants to Europe most closely resembles that of Mexican migrants to the US. Thus, we have two groups (MENA migrants to the US and Europe) that are culturally similar, but have dierent socio-economic characteristics. Comparing intergenerational mobility between these two groups allows for better identi cation of these socio-economic factors as well as institutional factors in Europe and the US. The second reason for studying MENA migrants to the US is that this is a rapidly growing immigrant community.
According to Camarota (2002), the immigrant community from the MENA in the US
had a seven-fold increase between 1970 and 2000, growing from fewer than 200,000 to over 1.5 million. Contrast this with the only three-fold increase in the general immigrant population over this period. Given that MENA migrants to the US tend to have higher fertility rates than the average US population (CDC National Vital Statistics System, 2011), the MENA diaspora in the United States is only expected to grow in the coming years. Given the rapid growth of this community, it is important to understand the degree to which the children of these immigrants are able to economically assimilate into American society. In this study, I empirically show that the MENA ethnic group has higher educational outcomes than the general US population. Overall, educational outcomes are increasing in parents' education, parents' income, and residence in an ethnic enclave. The eects of parents' education and income are no dierent for 2nd generation MENA migrants, suggesting that the education premium of being a MENA migrant will persist across generations.
However, I nd that the advantages of living in an ethnic enclave
disappear for MENA migrants, suggesting some fundamental dierences between these enclaves (and thus the people living in them) and the enclaves inhabited by other ethnicities. The rest of the paper proceeds as follows: Section 2 presents the data and variable construction, section 3 outlines the empirical methodology, section 4 discusses the results, and section 5 concludes.
2
Data
2.1 Dataset and Variable Construction To assess intergenerational mobility of MENA migrants in the United States, I use individual level data from the 2011 American Community Survey, public use microdata sample. As my study is concerned with second generation immigrants, I restrict my sample to only those people that were born in the United States. Second generation immigrants are de ned as having been born in the United States to
3 2nd generation MENA migrants are de ned as native born children 4 who have at least one parent born in one of twenty on countries in the MENA. at least one parent born abroad.
3 A growing strand of literature dierentiates between 2nd generation and 2.5 generation immigrants. In the former case, both parents were born abroad, while in the latter, one parent is an immigrant and the other is native born. Ramakrishnan and Karthick (2004) argue that we need to distinguish between these two groups as they dier signi cantly in terms of racial identi cation, education, and income. A future draft of this paper will assess the dierence between these groups. 4 The 21 countries are Algeria, Bahrain, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Sudan, Syria, Tunisia, Turkey, UAE, and Yemen
5
For each observation, I collect data on age, years of education, county of residence, parents' education, parents' income, parents' English speaking ability, and parents' birthplace. I restrict the sample to individuals aged 25 years and older.
While this limits the sample size for ethnic groups that are
relatively recent arrivals to the US (Somali refugees for example), it is necessary to not underestimate educational outcomes for these groups. From this dataset, I create the variables de ned below in Table 1. Deleting all missing values (mostly related to parental variables), I end up with a sample of 56,442 observations.
Table 1: Variable De nitions Edi
Years of education.
This variable is computed from the ACS variable
"educd" where, for example, completing 1st grade is equivalent to 1 year of education and completing 6th grade is equivalent to 6 years of education. High school graduates have 12 years of education, college graduates have 16 years of education, and those with a professional degree have 20 years of education. In the empirical analysis, I take the natural log of this variable.
HSi
A dummy variable equal to 1 if the observation has at least a high school diploma
Collegei
A dummy variable equal to 1 if the observation has at least a bachelors degree
P rof essionali
A dummy variable equal to 1 if the observation has completed a professional degree
M omEdi
Similar to
Ed
above, but for the observation's mother
DadEdi
Similar to
Ed
above, but for the observation's father
M omLangi
A dummy variable equal to one if the observation's mother self reports her ENglish langiage ability as "speaks only English," "speaks very well," or "speaks well." Equal to zero if the mother rates her ability as "does not speak English" or "speaks English, but not well."
DadLangi
Similar to
M omLang ,
Enclavei
A dummy variable equal to one if the observation lives in a county that is
but for the observation's father.
considered to be an ethnic enclave. An ethnic enclave is de ned as a county in which immigrants from a particular country are at least three times as
a
likely to live in as the average American resident.
M Ei
A dummy variable equal to 1 if at least one of the observation's parents was born in the Middle East.
a The
results are not too dierent if I lower this threshold to 2 or raise it to 4
6
2.2 Pro le of Educational Outcomes across Ethnic Groups Using this methodology, I am able to decompose educational outcomes across several dierent ethnicities.
Table 2 presents the average years of education and the fraction of the sample that has a
high school diploma, college degree, and professional degree. I consider these outcomes between native born and immigrants across the entire sample and between immigrants and native born whites, Middle Easterners, Mexicans, Latin Americans (non-Mexican), Sub-Saharan Africans, South Asians, and East Asians. Natives from each group are de ned as people who were born in the US to either parents from one of these regions or who claim a rst ancestry from these regions. Thus, I am mixing together 2nd and higher generation immigrants in these groups, though the majority are 2nd generation (native born, but to immigrant parents.)
Table 2: Educational Attainment across Immigrant and Ethnic Groups All
Years Education
H.S.
College
Professional
13.1
85.7%
28.0%
10.9%
Foreign Born
12.0
69.9%
28.6%
12.3%
Native Born
13.3
88.5%
27.9%
10.6%
White Immigrants
13.0
80.9%
31.9%
14.6%
White Natives
13.3
88.6%
27.4%
10.3%
MENA Immigrants
13.9
85.2%
46.8%
21.4%
MENA Natives
14.8
95.1%
51.0%
22.1%
Mexican Immigrants
8.8
38.6%
5.2%
1.4%
Mexican Natives
12.2
77.5%
14.3%
4.2%
Latin American Immigrants
11.1
63.4%
16.6%
5.8%
Latin American Natives
13.0
84.7%
23.6%
8.3%
SS African Immigrants
13.6
86.2%
39.0%
17.4%
SS African Natives
12.8
82.0%
19.7%
17.4%
S. Asian Immigrants
15.2
89.0%
66.2%
36.4%
S. Asian Natives
16.2
96.3%
74.3%
39.9%
E. Asian Immigrants
13.4
81.7%
44.5%
16.8%
E. Asian Natives
14.7
95.7%
50.7%
17.4%
Years Education refers to the average years of education attained for each group. 12 years of education is equivalent to a high school degree, 16 years a college degree, and 20+ years a professional degree. H.S., College, and Professional refer to the fraction of each group that have at least a high school diploma, bachelors degree, and professional degree repsectively. Immigrants are de ned as people who were born in a country other than the U.S., while Natives were born in the U.S. with reported ancestries to the speci ed group. Across all ethnicities, immigrants have on average 1.3 fewer years of education, with 12 years on average for immigrants and 13.3 years for natives. A much lower percentage of immigrants have completed high school, with under 70% of immigrants holding a high school degree compared to nearly 90% for natives. Interestingly, those immigrants who have completed high school are much more likely to have completed college and professional degrees. In my sample, about 28% of native born Americans have
7
at least a bachelors degree and 10.6% have a professional degree.
For immigrants, these shares are
28.6% and 12.3%. That immigrants tend to have higher rates of tertiary education attainment could simply be a re ection of US immigration policy favoring skilled migration. There are signi cant dierences across ethnic groups. educated than the general US population.
migrants from the MENA tend to be better
MENA migrants average 14 years of education and a
signi cantly higher fraction of these immigrants have college and professional degrees. Ethnic Middle Easterners born in the US are even better educated than their immigrant forebears. MENA natives average nearly 15 years of education, over half have at least a bachelors degree and 22% hold a professional degree, averages well above average American resident. The same pattern that holds for MENA migrants and natives also holds for the East and South Asian diasporas in the US. For each group, both immigrants and natives tend to be better educated than the average American, and the high education of immigrants is transferred over to future generations with increased educational outcomes for natives. Average education tends to be lowest for Mexican immigrants, but there are signi cant increases when going from Mexican immigrants to natives. This suggests that the average education gap for Mexican immigrants will disappear over a few generations. The only group that shows a decline in educational outcomes across generations are sub-Saharan Africans. Immigrants average 13.6 years of education and greater fractions of college and professional school graduates than the average American. However, 2nd generations have worse outcomes than the average American. Table 3 presents parent's educational outcomes across my sample. In every case, the average years of education for parents are lower than average years for their children, indicating an increase in the average education over time for both immigrants and natives in the US. Contrasting mother's and father's education, the biggest gender gaps are for South Asians (fathers have two more years of education), and for the MENA (fathers have 0.9 more years on average).
Interestingly, the largest
education gaps are also for the most educated groups, and even for these groups, average years of mother's education are the two highest in the sample.
At dierent levels of education, the largest
gender gaps are at the college and graduate levels. This pattern is not unique to any ethnic group, however, and is more likely due to traditional gender roles and childbearing decisions.
5
Given the diversity in educational outcomes across groups, it is useful to further break these gures down by speci c MENA countries. Table 4 presents these outcomes across the seven countries with the largest diasporas (immigrants and native born with ancestral ties) in the US. In every case, 2nd (and higher) generation immigrants have more education than immigrants, a remarkable fact given that immigrants themselves are coming in with already high levels of education. Looking across groups, the highest levels of education are for Egyptian and Iranian immigrants. Both of these two groups had large waves of migration in the 1960's and 1970's. The older diasporas like Lebanon and Syria (most of whom arrived in the 1920's-1940's) tend to slightly lower years of education, though still higher than the average US population.
The largest gap between immigrants
and natives is for the Iraqi diaspora. Iraqi immigrants have a relatively low 11.9 years of education, compared to 15.7 years for US born Iraqis. Much of this gap can be attributed to the recent wave of Iraqi refugee migration. Overall, though, the trends across individual countries mirror those for the MENA as a whole and the rest of the analysis will treat these dierent diasporas as a single group.
5 Interestingly, this trend is expected to reverse in the future given the larger fraction of women in American universities
than men.
8
Table 3: Parent's Educational Endowments across Ethnicities All
White
MENA
Mexican
Lat. Am.
SS Africa
S. Asia
E. Asia
Mother
11.6
12.3
13.0
9.2
11.1
12.4
13.6
12.5
Father
12.4
12.6
13.9
9.0
11.1
12.6
15.6
13.1
Mother
72.9%
80.3%
81.6%
45.7%
65.5%
75.5%
81.2%
79.6%
Father
78.4%
81.4%
80.4%
45.0%
64.6%
78.9%
91.3%
83.4%
Mother
14.1%
14.1%
31.5%
4.6%
11.1%
22.3%
44.1%
30.6%
Father
20.3%
20.7%
42.6%
6.0%
12.1%
25.8%
64.7%
34.9%
Mother
4.9%
5.2%
12.0%
1.3%
3.9%
9.8%
17.5%
7.3%
Father
8.4%
8.5%
21.5%
2.4%
4.6%
16.3%
38.2%
12.3%
Years Education
High School
College
Professional
Yrs Education refers to the total years of education completed by the observations mother and father. For example, if mother's years of education is 12, then the observation's mother has completed high school. High School, College, and Professional are dumy variables equal to 1 if the observation's parent completed high school, college, or graduate school respectively. English is a dummy variable equal to 1 if the observation's parent rates their English speaking ability as "speaks well" or "speaks very well" and equal to zero if the parent rates their ability as "does not speak English" or "does not speak well."
2.3 De ning Ethnic Enclaves An interesting issue raised in the literature is the extent to which living in an ethnic enclave aects intergenerational mobility and investment in human capital. On one hand, living in an ethnic enclave may increase human capital investment since immigrants will face lower migration costs when moving to an enclave and their children will face less labor market discrimination in these enclaves, increasing the return to education. On the other hand, living in an enclave reduces the need for a migrant to assimilate, limiting English language acquisition and thus reducing educational attainment. Furthermore, if people within the enclave have lower socio-economic indicators, then there may be negative neighborhood eects on educational outcomes.
(AI) j living in county i i0 s share of the US
I use a unique methodology to de ne an ethnic enclave. I construct an agglomeration index for each ethnic group and US county. The agglomeration index for ethnic group is de ned as the fraction of ethnic group
j
living in county
i
divided by county
population:
AIij =
P opji /P opj P opi /P op
(1)
For example, 3.815% of the MENA diaspora lives in Wayne County, Michigan. This county represents 0.674% of the US population. Michigan is thus
The agglomeration index for the MENA diaspora in Wayne County,
M EN A AIW ayneCounty,M I = 3.815%/0.674% = 5.7.
This number can be interpreted as how
much more or less likely a member of a particular ethnic group is to live in a county than the average
9
Table 4: Educational Attainment across MENA Countries and Ancestries Years Education
H.S.
College
Mena Immigrants
13.9
85.2%
46.8%
Professional 21.4%
Mena Natives
14.8
95.1%
51.0%
22.1%
Egyptian Immigrants
15.3
95.3%
64.7%
22.8%
Egyptian Natives
16.1
96.5%
74.6%
38.2%
Iranian Immigrants
14.6
90.7%
54.1%
26.4%
Iranian Natives
16.2
96.8%
72.6%
37.5%
Iraqi Immigrants
11.9
71.4%
28.7%
8.2%
Iraqi Natives
15.7
92.3%
69.2%
38.5%
Jordanian Immigrants
13.0
80.4%
33.6%
14.2%
Jordanian Natives
14.3
97.1%
34.3%
11.4%
Lebanese Immigrants
13.7
82.4%
41.4%
22.3%
Lebanese Natives
14.8
95.6%
50.6%
20.9%
Syrian Immigrants
13.2
76.3%
40.0%
20.5%
Syrian Natives
14.1
93.1%
39.7%
17.1%
Turkish Immigrants
14.4
87.6%
55.1%
28.5%
Turkish Natives
14.6
92.6%
46.7%
22.2%
Years Education refers to the average years of education attained for each group. 12 years of education is equivalent to a high school degree, 16 years a college degree, and 20+ years a professional degree. H.S., College, and Professional refer to the fraction of each group that have at least a high school diploma, bachelors degree, and professional degree repsectively. Immigrants are de ned as people who were born in a country other than the U.S., while Natives were born in the U.S. with reported ancestries to the speci ed group. 6 Thus, ethnic Middle Easterners (both immigrants and native born) are 5.7 times
American county.
more likely to live in Wayne County, Michigan than the average American. An agglomeration index less than 1 means that a member of the diaspora is less likely to live in that county than the average American, while an index over 1 suggests that they are more likely. An advantage of this measure is that it is scale free. For example, would expect there to be a large number of ethnic Middle Easterners in New York City, simply because there are a lot of people that live in New York City.
But how signi cant is the MENA community?
Is it tightly organized with
services oered for its residents such as Arabic language schools and ethnically owned businesses? The agglomeration index measures the relative importance of the community in a particular county and is thus more likely to be correlated with the features of an ethnic enclave that would aect educational attainment. Table 5 presents the top 15 and bottom 10 counties in the US for the MENA diaspora based o the agglomeration index (conditional upon there being at least one ethnic Middle Easterner in a county). The results are fairly consistent with anecdotal evidence on where the largest MENA communities are
6 For Western European ancestries, I set the agglomeration index equal to 1. This implicitly assumes that the geographic distribution for people of Western European descent mimics the general US population (of which they are a big part).
10
Table 5: Agglomeration Indexes for Middle Eastern Migrants State
County
Agglomeration Index
Top 15 Counties Michigan
Wayne County
5.7
Michigan
Macomb County
5.5
California
Stanislaus County
5.4
New Jersey
Hudson County
5.4
Michigan
Oakland County
5.3
Tennessee
Davidson County
5.1
California
Los Angeles County
4.6
New Jersey
Passaic County
4.6
New Jersey
Bergen County
4.5
Virginia
Alexandria city
4.5
California
San Mateo County
3.9
California
San Diego County
3.9
Virginia
Henrico County
3.9
New York
Richmond County
3.8
Texas
Collin County
3.8
Bottom 10 Counties Oregon
Douglas County
0.06
Texas
Johnson County
0.06
Connecticut
Middlesex County
0.05
North Carolina
Alamance County
0.05
Illinois
Tazewell County
0.05
Utah
Weber County
0.04
Idaho
Canyon County
0.03
Colorado
Weld County
0.03
Texas
Cameron County
0.03
Louisiana
Orleans Parish
0.02
The Agglomeration Index is computed as the fraction of all migrants from the Middle East living in a particular county divided by that county's share of the US population. It can be interpreted as how much more or less likely a Middle Eastern migrant is to live in a particular county. Thus, an Agglomeration Index of 3.0 implies that a MENA migrant is three times as likely to live in that county as the average American, while an index of 0.5 means that the migrant is only half as likely to live there. located. As expected, several counties around Dearborn, Michigan represent the largest ethnic enclaves, re ecting the very large Middle Eastern community in this region.
Stanislaus County in California
also shows up as a signi cant enclave, mostly due to the very large Iraqi Assyrian community there. While there are some expected results in this top 15, there are a few surprises, such as Garrett County, Maryland, which is a fairly rural county in western Maryland.
7
7 This may be an outlier as the ACS only reports 857 ethnic Middle Easterners in this county, which ends up being a large agglomeration index given the relatively small population size of this county. I have estimated the empirical model excluding counties with less than 100,000 people and the results do not qualitatively change, however.
11
Table 6: Agglomeration Indexes for other Ancestries Mexico
Latin America
Imperial County, California
11.3
Hudson County, New Jersey
Hidalgo County, Texas
11.1
Queens County, New York
9.4 8.5
Webb County, Texas
10
Union County, New Jersey
8.3
El Paso County, Texas
9.1
Osceola County, Florida
6.9
Cameron County, Texas
8.2
Broward County, Florida
6.8
Yuma County, Arizona
7.2
Arlington County, Virginia
6.2
Tulare County, California
7
Essex County, New Jersey
5.7
Merced County, California
6.5
Suolk County, Massachusetts
5.2
Madera County, California
6.1
Alexandria City, Virginia
5.1
Santa Barbara County, California
5.9
Montgomery County, Maryland
4.7
Kings County, New York
10.8
Alexandria city, Virginia
24.6
Richmond County, New York
7.5
Montgomery County, Maryland
12.3
Queens County, New York
6.3
Hennepin County, Minnesota
9.8
Cook County, Illinois
6.0
Bronx County, New York
9.4
Bergen County, New Jersey
5.8
Ramsey County, Minnesota
9.1
Sacramento County, California
4.7
DeKalb County, Georgia
7.8
Yolo County, California
4.7
Montgomery County, Tennessee
7.6
Spokane County, Washington
4.7
Clayton County, Georgia
7.6
Passaic County, New Jersey
4.3
Arlington County, Virginia
7.3
DuPage County, Illinois
4.2
Essex County, New Jersey
6.9
Middlesex County, New Jersey
14.6
San Francisco County, California
Fort Bend County, Texas
9.7
Honolulu County, Hawaii
8.3
Hudson County, New Jersey
8.1
Santa Clara County, California
8.2
Queens County, New York
7.9
San Mateo County, California
6.6
Santa Clara County, California
7.8
Alameda County, California
6.4
S.S. Africa
Eastern Europe
South Asia
East Asia 10.7
Somerset County, New Jersey
7.8
Queens County, New York
5
Alameda County, California
6.7
Orange County, California
5
Harford County, Maryland
6.6
Fort Bend County, Texas
4.7
Collin County, Texas
5.5
King County, Washington
4.2
DuPage County, Illinois
5.1
Bergen County, New Jersey
4.2
The agglomeration index is computed as the fraction of country's migrants to the US living in the speci ed county divided by tht county's share of the US population. For example, the index for Mexican migrants living in Imperial County, California is 11.3, implying that migrants from Mexico are 11.3 times more likely to live in Imperial County than the average American resident. I also present the top ten ethnic enclaves for six other ethnicities in my sample in Table 6. The results are again consistent with anecdotal evidence on what communities are ethnic enclaves. For example, Mexicans are heavily represented in Southern California and South Texas, while Latin Americans are prevalent in South Florida. Sub-Saharan Africans are well represented in the Baltimore/D.C. area as
12
well as several counties around Minneapolis with large Eritrean and Somali refugee communities. South Asians have signi cant communities around Silicon Valley, while East Asians are well represented in San Francisco (large Chinese and Korean communities) and Hawaii (signi cant Japanese community).
3
Methodology
It is common in the literature on intergenerational mobility to write the relationship between outcomes of parents and outcomes of children as
yi,t = α + ρyi,t−1 + ui,t yi,t
(2)
yi,t−1 measure outcomes such as education, earnings, or wealth for children (t) and their (t − 1). For example, let y be equal to education. Then, the earnings of family i0 s child is 0 determined by family i s parental education and other in uences u. The parameter α can be thought of as the average eect of these other in uences. If we assume that the variances of yi,t and yi,t−1 are 8 the same, then ρ is the population correlation coe cient between yi,t and yi,t−1 . The estimated coef cient ρ ˆ will then measure the fraction of economic advantage (measured in terms of education in this and
parents
case) that is transmitted across generations. This term is also known as the transmission parameter (Dustmann et. al., 2012). An estimate close to zero suggests high intergenerational mobility, while a coe cient closer to 1 indicates low mobility. We can use this methodology to assess assimilation of immigrant populations over time. De ne equation 1 separately for the native and immigrant populations:
N N yi,t = αN + ρN yi,t−1 + uN i,t I I I I I Immigrants: yi,t = α + ρ yi,t−1 + ui,t Natives:
Allow the two transmission parameter to dier between these groups as: outcome dierential between natives and immigrants in generation
t
ρI = ρN + γ .
The expected
will then be given by:
N I N I I E(yi,t ) − E(yi,t ) = αN − αI + ρN E(yi,t−1 ) − E(yi,t−1 ) − γE(yi,t−1 )
(3)
Suppose that the only dierence between native and immigrant educational outcomes is intergenera-
αN = αI ). Then, equation 2 simpli es to: N I I = ρN E(yi,t−1 ) − E(yi,t−1 ) − γE yi,t−1 .
tional mobility (i.e.
N E(yi,t )
−
I E(yi,t )
Thus, the parameter
ρN
will determine the rate at which the gap between immigrant and native
γ = 0, then if ρN = 1, this gap will persist over time ρ = 0, then the gap disappears from one generation N will be faster for smaller values of ρ . If γ < 0, then
educational outcomes disappears. Assuming that since there is no intergenerational mobility. If to the next. Thus, assimilation of immigrants
N
the transmission parameter is larger for natives than for immigrants and the education gap will persist longer. Of course, this analysis assumes that
N I yi,t > yi,t .
If immigrants have higher educational outcomes than
natives (as is the case with MENA migrants), then the story above will be reversed. A negative value
8 If
the variances are dierent across generations, then the OLS estimator ρˆ measures ρ ∗ σyt /σyt−1 13
for
γ
γ
implies that immigrant education will converge with native education, while a positive value for
suggests that the immigrant education premium will persist longer.
Of course, intergenerational mobility is not the only factor determining the gap between immigrant and native educational outcomes. Such things as language acquisition, dierences in the way educational systems treat immigrant children, discrimination, or dierent educational incentives due to living in an ethnic enclave could all contribute to the education gap between these groups. To account for these other factors, I build an augmented version of the model presented in equation 1. This model relates years of education to parents education, parent's income, parent's pro ciency with English, and whether the observation lives in an ethnic enclave.
Edi = α+ρ1 M omEdi +ρ2 DadEdi +β1 ln P arYi +β2 M omLangi +β3 DadLangi +β4 Enclavei +ui Observation
i0 s
(4)
log years of education is regressed on mother's log years of education and father's log
years of education.
P arYi
is de ned as the observation's parent's family income, calculated as the
9 Language is measured as a dummy variable equal
maximum between mother's and father's income.
to 1 if the observation's parent can speak English either well or very well and equal to zero if the parent either doesn't speak English at all or has trouble with English according to the Census questionnaire. The variable
Enclave is equal to 1 if the observation lives in a county with an agglomeration
10
index greater than 3.0.
To evaluate how intergenerational mobility diers between the average American and ethnic Middle Easterners born in the United States, I create a dummy variable
ME
which is equal to 1 if the
observation was born in the United States, but claims a rst ancestry from a country in the Middle East. I then interacted this dummy with each of the variables in equation 3:
Edi
= α + ρ1 M omEdi + ρ2 DadEdi + β1 P arYi + β2 M omLangi + β3 DadLangi +β3 Enclavei + δ0 M Ei + δ1 M omEdi ∗ M Ei + δ2 DadEdi ∗ M Ei + δ3 P arYi ∗ M Ei
(5)
+δ4 M omLangi ∗ M Ei + δ5 DadLangi ∗ M Ei + δ6 Enclavei ∗ M Ei + ui The parameter
δ0
captures how much more education 2nd generation MENA migrants are predicted
to have than the average American. Speci cally, MENA migrants are predicted to roughly
δ0 %
more
years of education. The interaction terms estimate how much more or less factors like parental income education, and English language ability aect educational attainment. For example, a 1% increase in mother's education is predicted to increase years of education by
(ρ1 + δ1 )%,
compared to
ρ1 %
for the
average American. If the sum of
δ1 + δ2
is negative, then we predict that parental education has a smaller eect for
MENA migrants than for the average American. This is equivalent to the case where
γ
