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  • Original article
  • Open Access

Transnational social mobility of minorities: a comparative analysis of 14 immigrant minority groups

IZA Journal of Development and Migration20188:15

https://doi.org/10.1186/s40176-018-0123-9

  • Received: 11 December 2017
  • Accepted: 14 February 2018
  • Published:

Abstract

There is extensive scholarship on the condition of being a minority in one’s home country and vast literature on the experience of immigrants in host countries. However, almost no attention has been paid to the distinct mechanisms pertaining to immigrants who were minorities in the source country and moved to another. This paper integrates the literature on minorities with that of migration and addresses this gap by developing a theory of a growing phenomenon: the transnational social mobility of minorities. Using the US census and the American Community Survey, 14 groups of minorities (e.g., British Pakistanis) who immigrated to the USA are compared to the corresponding majority groups from the same country (e.g., the British majority). Findings show that all minorities have a lower starting point than the corresponding majority group from the same country. However, non-black minorities succeed faster and, in some cases, even pass majorities over time. In contrast, black immigrant minorities remain disadvantaged in comparison to whites from the same country.

Keywords

  • Migration
  • Minorities
  • Labor markets
  • Race
  • Ethnicity
  • USA

1 Introduction

This study develops an inexplicably understudied question with crucial implications for immigrants’ economic assimilation trajectory: whether an immigrant was a member of a minority group in the country of origin. Minorities such as Turks from Germany or Pakistanis from the UK might have different migration experiences from their majority counterparts when they migrate to another country. Due to drastic demographic changes, investigating minorities who immigrate to another country will become particularly crucial in the foreseeable future. The number of world immigrants has increased dramatically in recent decades from 76 million in the 1960s to over 200 million nowadays (Castles et al., 2013, UNDESA 2016). These increasing inflows diversify host societies and create many new communities of minorities. Now, these communities are starting to send waves of migration to a second destination in growing numbers. In light of these new trends, policymakers and researchers have to ask how these changing flows of immigrants are different and how they affect the population composition in the USA.

Moreover, for minorities, migration to another social context can be a window of opportunity to redefine a new social position. By making the physical relocation, they can relocate along the social hierarchy as well. Previous research exemplified this mechanism in other contexts. Borjas (1982) shows that Cuban refugees assimilate faster than other Hispanic immigrants due to what he calls ‘higher costs of return’ that encourage them to assimilate. They want to secure their place in a country in which their skills get appropriate rewards. A somewhat different perspective comes from Stark and Taylor (1991) who show how an incentive to assimilate is intensified when not only the absolute improvement in wage rates increases but also when the relative improvement compared to a reference group increases. Cohen (1996) expands this argument to absolute and relative improvements in social position, power, and prestige as well. He suggests that, among other factors, the discrimination that Palestinians experience in the Israeli workforce explains the faster pace at which they assimilate in the USA.

The question is whether this explanation holds for immigrant minorities who are not refugees or under an enduring conflict. Thus, the aim here is to construct a third category that stands between the known dichotomy of economic and non-economic (refugee) immigrants (see Chiswick 2000), asking whether minorities succeed in performing social mobility across borders. This study explores this question by investigating migration of 14 groups of minorities from four different regions, Europe, the Middle East, North America, and South America, to the USA. This is in order to allow thorough examination and comparison. This research uses two types of comparisons in order to isolate the unique mechanisms characterizing transnational social mobility. One type of comparison is between immigrant minorities and the corresponding majority group from the same country. The second comparison is between two meta-groups of immigrant minorities: black and non-black minorities.

2 Transnational social mobility and minorities’ migration to the USA

Migration of minorities to the USA is a unique case that allows an examination of transnational social mobility. Blacks, Asians, and other ethnic groups who were minorities in their country of origin (e.g., France, the UK) come to the USA and find different social divides. In the USA, a strong emphasis is given to the white-black divide, which is based on color of skin as opposed to ancestral differences. Bonilla-Silva (2006) as well as Lee and Bean (2010) argue that attitudes towards non-black minorities are distinctly better than towards blacks. This profound distinction rests upon the history of black slavery in the USA on one side and, on the other, a heritage of immigration society that is open to newcomers (see also Hollinger 2003, Omi and Winant 1994, Williams 2006, Winant 2007).

To exemplify the black/non-black divide, one can look at results from the General Social Survey (Smith et al. 2013), in which 30% of respondents think there is ‘a lot’ of discrimination that hurts the chances of blacks to ‘get good paying jobs’. In contrast, data on Asians as a population that usually stands in comparison to blacks shows that only 12% of respondents think the same in regard to Asians. Indeed, data on unemployment rates show that 12.1% of blacks are unemployed while 5.3% of whites and 5.4% of Asians (BLS 2015). These differences continue to appear in rates of intermarriages (Qian and Lichter 2007, Waters and Eschbach 1995), educational achievements (NAEP 2011a, NAEP 2011b), and poverty (Addy and Wight 2012).

While this is the situation in the USA, minorities in participating countries are disadvantaged based on other divides. In the Middle East, minorities have lower status based on ethnic and religious tensions while African immigrants are rare (IAU 2010, Kimmerling 1994, Smooha 2010). In Europe, social attitudes towards minorities are better explained by “history of a hereditary aristocracy at home and a colonial policy abroad” (Model and Ladipo 1996:487). These policies motivated a belief system in which foreigners are excluded as such, disregarding their origins (see Lipset 1991, Model and Ladipo 1996, Model 1997). Indeed, the European Social Survey (ESS 2015) shows that Africans and Middle Easterners feel almost equally discriminated against in Western Europe (approximately 30% feels discrimination). Asians report somewhat lower rates (20%) of discrimination but present higher rates of feelings as a minority. Approximately 70% of Asians in Western Europe report they feel as a minority versus 60% of Africans and 55% of Middle Easterners. This is especially true after the 2008 financial crisis. Since then, right-wing parties across Europe have gained significant amounts of new support (see Kriesi and Pappas, 2015, Polyakova 2015, Wodak and Boukala 2015) and prominent European public figures voicing their concerns over immigration while photos of Syrian refugees were central in the “Brexit” campaign (Green et al. 2016).

This delicate distinction gets further support from a comparative research of two cities: New York and London (Model and Ladipo 1996). This study shows that New York is a better environment than London for immigrants originating in China, Bangladesh, India, and Pakistan. However, immigrants from Africa remain at the end of the queue for social mobility in both New York and London. For more data comparing the USA with the source countries under examination, strengthening the distinction presented above, see Tables 5 and 6 in Appendix.

Therefore, when comparing between the participating source countries and the USA, it is reasonable to assume that the American society is more accepting towards non-black immigrants. Hence, the first and main question of this paper is whether this social situation creates an encouraging environment for non-black minorities who may find the USA especially attractive due to fewer barriers they face in comparison to their origin countries. This might be reflected in performing an accelerated social mobility after arriving to the USA in comparison to the majority group that does not have this higher accessibility from which they benefit. Moreover, this “discrimination gap” is also put to a test in comparing immigration of non-black minorities to the USA to that of blacks. It is hypothesized that because blacks are less accepted in the USA than other minorities and do not enjoy the “discrimination gap”, they do not present an accelerated mobility as their counterpart minorities. Indeed, this “natural experiment” tests the mechanism of “higher costs of return” as Borjas (1982) puts it, or “relative social improvement” as Cohen (1996) defines it, in the case of immigrant minorities.

3 The human capital of immigrant minorities

However, in order to exclude intervening mechanisms of self-selection, there is a need to know more about the pools of minority immigrants versus majority immigrants and ask if and how they are different from each other in terms of their human capital. According to human capital theories (Borjas 1987, Chiswick 1978), the skills of an immigrant upon arrival determine the extent to which he or she will succeed in the country of destination. Immigrants with a high level of education, with better proficiency in language, and those who have work experience succeed in assimilating better economically. Since these characteristics can be acquired over time, those who immigrate younger and have longer tenure in the destination country have more probability to acquire the necessary skills and have greater economic success as a result (Borjas 2001, Castles et al., 2013).

In the case of immigrant minorities, there are several forces that act in parallel and in mixed directions. On one side, being a minority in the homeland is often translated to lower rates of education, income, and participation in the workforce (ESS 2015, Heath and Cheung 2006, Heath, Rothon and Kilpi 2008, Kogan 2006). Thus, the source minority groups in homelands are more likely to have lower human capital and, therefore, affect the pool of immigrants coming from these groups.

On the other side, being a minority also serves as a positive selection mechanism because although minorities in the source country might want to migrate not all of them are able to do so because of a lack of sufficient education and income relative to the majority group (due to the same reasons mentioned above). Emigration is, therefore, much more possible among the highly skilled minority members. Moreover, highly skilled minorities suffer not only from lower wage, but also from higher hiring discrimination, which is more prevalent among them because majority members tend to hire their own people to the more prestigious jobs and tend to pay them better (Aigner and Cain 1977, Kogan 2006, Van Tubergen, Maas and Flap 2004). Therefore, the more skilled the minority immigrant is the more incentive to emigrate and ability to do so he or she has.

Moreover, economists fall into two camps when it comes to the motives for return migration and this might apply to the second-migration move as tested herewith (Borjas and Bratsberg 1996). While the positive-selection perspective predicts that returnees are disproportionately drawn from the more skilled of their incoming cohort (Stark and Bloom, 1985), the negative-selection perspective sees return migration as the correction of mistakes in initial migration decisions and therefore the less successful migrants return (Beenstock 1996, Blejer and Goldberg 1978, Cohen and Haberfeld 2001). Although the latter argument seems less valid in investigating a second-migration move, it should be tested thoroughly because the less successful migrants might want to try once more in another place.

These contradicting sides necessitate an empirical test in order to examine the actual self-selection mechanisms. This will be made here by two prominent indicators found in the literature and are extractable in the current dataset: education and mastering English. Thus, a second but preliminary question is whether these 14 minority groups consistently display different levels of these two indicators from the corresponding majority group.

However, this examination is still not exhaustive because the literature on the quality of scholarly degrees among various groups (see Gesemann 2007, Leslie 2003) clearly shows how majority groups study in better schools (determined, at times, by place of residency) and then get accepted to better universities and more desirable professional degrees (e.g., applied degrees such as engineering and computer sciences). Thus, even when minorities ostensibly have the same level of educational capital (e.g., a BA degree), one still needs to suspect the “ethnic factor” in determining the hidden quality of this capital. One cannot tell how good the institutions in which minorities acquired their BA degree are and what the transferability of this degree is.

Thus, another preliminary question is whether immigrant minorities are economically inferior when coming to the USA, even after accounting for the observed human capital, due to less transferability of their skills, cultural barriers, and unobserved differences in their human capital. This will be addressed by examining their initial economic indicators upon arrival.

4 Method

Data for this study come from the Public Use Microdata Samples (PUMS) of the decennial USA population censuses for 1980, 1990, and 2000 (5% of the population each), and the annual American Community Survey (ACS) for 2005–2009 (5% of the population altogether) (Ruggles et al. 2013). All samples are controlled for the year of survey. The samples were restricted to men and women who were at the prime age of 25 to 64 at the time of enumeration and arrived to the USA between the ages of 25 to 50 enabling them to exploit opportunities for promotion in the American labor force, but still to be raised and educated as a minority in the source country.

This study compares economic outcomes across 14 minority groups from different geographic regions. These groups are divided by two main categories: 1. Blacks (excluding Caribbean blacks): black-British, black-French, black-Germans, black-Brazilians, and black-Canadians (separated by the English and French parts). 2. Non-blacks divided to (a) first-generation minorities: Turkish-Germans, Iranian-Germans, Moroccan-French, and Algerian-French; and (b) second-generation/native minorities: Pakistani-British, Indian-British, Kurdish-Iraqis, and Arab-Israelis. These groups were selected because they have a statistically sufficient number of cases for a reliable investigation as well as a sufficient number of studies in order to gather the necessary information on the source group in the country of origin before coming to the USA (e.g., France, Germany).

These 14 groups are geographically varied (North-America, South-America, Europe, and the Middle-East) and allow thorough examination and comparison. The comparison between black minorities and non-black minorities tests whether the social improvement experienced by non-black immigrant minorities (when moving to the USA) can explain their economic trajectory. This is also true in regard to the comparison of the 14 minority groups to the parallel majority group from the same country. Finally, the comparison between first-generation immigrants, second-generation immigrants, and native minorities tests whether a previous immigration experience influences the way minorities succeed in their immigration to the USA.

These minority groups were identified based on the race, birthplace, ancestry, and language variables as used in previous studies (Cohen 1996, Cohen and Haberfeld 1997, Lieberson 1985, Lieberson and Waters 1985, Neidert and Farley 1985). Blacks were identified by the race variable (in Brazil, Canada, France, and the UK) where the corresponding majority group consists of whites with a shared ancestry as the majority group of the same country (Brazilian, British/English, French, and Canadian/French-Canadian). Turkish-Germans, Iranian-Germans, Moroccan-French, and Algerian-French were identified as such if they were born in the country of origin (Turkey, Iran, Morocco, and Algeria), they have similar ancestry, and their main language is the language of the relevant European country before immigration to the USA (French/German). In order to compare these minority groups to the corresponding majority groups from the same country, I define as a majority group only respondents who were born in Germany/France, who speak mainly German/French, and whose ancestry is German/French. Kurdish-Iraqis, Arab-Israelis, Pakistani-British, and Indian-British were selected based on their birthplace (Iraq, Israel, and the UK) and ancestry (Kurdish, Palestinian/Arab, Pakistani, and Indian). When defining the majority group, I selected only respondents who have a majority ancestry (Iraqi, Israeli, and British/English). All the calculations were made with the personal weights provided by the databases.

In conducting the multivariate analysis, I use three dependent variables to measure the economic and occupational benefit of migration among minorities in this analysis: wage, household income, and occupational status (Eichenlaub et al., 2010, Lubotsky 2007). The first dependent variable is wage income, which is measured for those who worked and reported a positive wage for the year prior to the census enumeration. The second dependent variable is household income, which measures the total income from personal business and farm activity, wages, salaries, cash bonuses, tips, etc. from all individuals in the respondent’s household during the preceding calendar year. I limit my analysis to respondents who reported a non-zero income. These two variables were adjusted to the inflation rate of each census for the preceding year. The third dependent variable is occupational status, as measured by the Hauser and Warren Socioeconomic Index (SEI), which assigns a status score for occupations based on the income and educational attainment associated with each occupation in 1990 (Hauser and Warren 1997). This index is an updated version of the Duncan Socioeconomic Index, which is based on the occupational classification scheme of 1950 (Duncan 1961). For SEI, I limit my analysis to respondents who were in the labor force and who had an SEI score reported, whether or not they were employed at the time of enumeration.

Using a variety of economic outcome measures, rather than a single indicator, allows me to more thoroughly explore the economic success of immigrated minorities. While wage income reflects personal economic success in the labor force, household income reflects more general economic assimilation and includes, for example, economic assimilation by marriages as well (the correlation between these two variables in this specific data set is 0.37).

The multivariate statistical model is a multinomial model formulated in the following way. The socioeconomic condition of an immigrant i depends upon a set of observable explanatory variables in the following form:
$$ {SE}_{\mathrm{i}}={\beta}_1{C}_{\mathrm{i}}+{\beta}_2{S}_{\mathrm{i}}+{\beta}_3{N}_{\mathrm{i}}+{\beta}_4{M}_i+{\beta}_5{A}_{\mathrm{i}}+{\beta}_6A{2}_i+{\beta}_7{G}_i+{\beta}_8{E}_i+{\beta}_9{\mathrm{Et}}_i+{\beta}_9{Y}_i+{\beta}_{10}{\mathrm{Et}}_i\ast {Y}_i+{\beta}_{11}{\mathrm{Co}}_i+{\beta}_{12}{\mathrm{YS}}_i+{U}_i $$
(1)
where C is US citizenship, S is the level of speaking English, N is number of children, M is marital status, A and A2 is age and age squared, G is gender, E is level of education, Et is ethnicity, Y is years in the USA (the latter two appear as an interaction term), Co is country, and YS the year a particular person was surveyed. The Ui variable in Eq. (2) represents an error term that is usually assumed to be randomly distributed among the population. The function above also applies to the log forms of household income/wage:
$$ \mathit{\ln}{W}_i\mid {I}_{\mathrm{i}}={\beta}_1{C}_{\mathrm{i}}+{\beta}_2{S}_{\mathrm{i}}+{\beta}_3{N}_{\mathrm{i}}+{\beta}_4{M}_i+{\beta}_5{A}_{\mathrm{i}}+{\beta}_6A{2}_i+{\beta}_7{G}_i+{\beta}_8{E}_i+{\beta}_9{\mathrm{Et}}_i+{\beta}_9{Y}_i+{\beta}_{10}{\mathrm{Et}}_i\ast {Y}_i+{\beta}_{11}{\mathrm{Co}}_i+{\beta}_{12}{\mathrm{YS}}_i+{U}_i $$
(2)

Note that these regressions also account for the concern that there are different waves/cohorts of immigrants due to changing immigration circumstances and/or policies of the host country as well as the source country (see Borjas 1995, Eldridge 1964). For this reason, the year of survey is calculated with years since migration. The combination of the two variables accounts for the cohort effect. In addition, regressions were conducted for each wave of immigrants separately (three waves with the highest number of cases: the 1960s wave, the 1970s wave, and the 1980s wave excluding particular groups whose number of cases was not sufficient). Indeed, these regressions produced similar results and are available upon request.

5 Findings

5.1 Characteristics of immigrant minorities

In order to examine the characteristics of minorities’ migration, Table 1 presents descriptive statistics of ten main characteristics of the non-black immigrant minorities, which were included in this research in comparison to the corresponding majority group from the same country.
Table 1

Descriptive statistics of immigrant minorities by ethnicity, age 25 to 64

Country

Name of group

M. age

M. arrived age

M. years in the USA

M. number of children

% married

% citizens

% in labor force

% speaks English “very well”

% BA+

% female

N

UK

British

47.4

32.7

14.8

0.8

77.5

30.6

75.9

99.6

39.3

49.7

21,596

Indians

38.8

30

8.9

1.3

79.2

24.9

74.8

96.6

68.6

54.3

134

Pakistanis

34.9

29.1

5.8

1.3

56.1

10.2

68.2

98.6

62.2

34.2

24

France

French

42.3

31.5

10.8

0.9

68.8

25.4

100

75.8

70.2

41

4181

Algerians

42.2

32.1

10.1

1.2

72.1

47.2

100

73.7

61.8

37

120

Moroccans

39.9

31.3

8.5

0.8

64.8

37.6

100

68

45.8

36.5

312

Germany

Germans

46.3

31.9

14.4

0.8

75.8

33.2

69.2

81.7

39.9

63.8

21,852

Iranians

41.6

34.2

7.4

0.7

73.5

26.9

86.7

57.8

62.8

33

80

Turks

41.2

31.7

9.4

0.8

74.9

32

84.9

84.1

50

52

37

Iraq

Iraqis

45.6

34.2

11.5

1.6

72.8

50.8

64.3

56.9

27.7

45.8

2627

Kurds

42.8

31.9

11

2.5

82.9

55.5

54.4

61.7

31

39.3

126

Israel

Israelis

42.4

31.9

10.5

1.4

83.4

38.5

74.9

73.7

57.7

44.8

2340

Arabs

45.1

31.8

13.2

1.8

82.1

59.8

61.8

64.5

30.1

36.8

719

Sources: 1980, 1990, and 2000 US censuses together with 2005–2009 ACS surveys

The analysis of the characteristics of these groups shows that immigrant minorities are not systematically distinct in terms of human capital. For example, the majority group of immigrants from Iraq, the UK, and Germany is less educated than the corresponding minority groups, while the opposite is true among immigrants from France and Israel. The same holds when checking the levels of mastering English. While majorities from France and Israel show higher percentages of mastering English, the Iraqi majority group shows lower percentages. Numbers among German immigrants are mixed. These figures indicate that at least in overt human capital there are no consistent differences across all immigrant minorities compared to the majority group.

Furthermore, in a more general overview, some other important characteristics are also varied. We can see that immigrant minorities are not distinctly and consistently different from their corresponding majority groups in terms of their age, tenure in the USA, and the number of children they have. Next are the descriptive statistics of the six groups of blacks who were included in this research in comparison to the white majority group from the same country (Table 2).
Table 2

Descriptive statistics of immigrant minorities by race, age 25 to 64

Country

Race

M. age

M. arrived age

M. years in the USA

M. number of children

% married

% citizens

% in labor force

% speaks English “very well”

% BA+

% female

N

Brazil

Blacks

41.1

32.7

8.5

0.5

53.2

16.6

87.9

56.5

19.2

38.4

273

Whites

40.6

32.7

7.9

0.8

66.4

16.3

81.6

59.2

33.1

53

5173

Canada (English)

Blacks

41.2

30.6

10.6

0.6

52.4

29.3

100

100

60.0

67.1

163

Whites

46.3

33.1

13.3

0.8

74.9

26.6

100

100

50.1

43.4

12,358

Canada (French)

Blacks

36

29.3

6.7

0.6

50.6

19.3

90

50

55.2

66.3

42

Whites

47.1

33.3

13.7

0.8

73.5

28.3

71.7

81.7

39.3

57.6

5303

UK

Blacks

41.7

31.3

10.4

1.0

45.8

31

89.8

99

52.2

61.9

235

Whites

47.4

32.7

14.8

0.8

77.5

30.6

75.9

99.6

39.3

49.7

21,596

France

Blacks

38.6

31.3

7.3

0.9

65.3

24

100

71.3

40.3

32.3

54

Whites

42.3

31.5

10.8

0.9

68.8

25.4

100

75.8

70.2

41

4181

Germany

Blacks

40.3

31.4

8.9

1.1

53.6

39.5

74.4

89.9

24.4

56.2

29

Whites

48.6

31.3

17.2

0.8

76

50

67

85.8

27.4

43.8

4138

Sources: 1980, 1990, and 2000 US censuses together with 2005–2009 ACS surveys

Here, too, we do not see the same levels of human capital among the various groups. Blacks from France, Germany, and Brazil are less educated than the corresponding white majority group, while blacks from the UK and Canada (both parts) hold a BA degree in larger numbers than the corresponding white majority groups. This holds true in checking the levels of mastering English as well. While whites from Brazil, French Canada, and France show higher percentages of mastering the English language, those from Germany show lower percentages.

This kind of variety continues in other characteristics such as age, arrival age, and years of tenure in the USA. However, one can see some common characteristics among immigrant blacks. For example, the percentage of marriages among blacks is lower than the corresponding white majority groups. These characteristics, among others, will be controlled in the following regressions.

5.2 Economic advancement of immigrant minorities

Tables 3 and 4 consist of three regressions of economic characteristics of immigrant minorities that were estimated for each of the 14 groups of black and non-black minorities in comparison to the corresponding majority group from the same country (42 regressions in total). In order to simplify the presentation, the control variables which include age, age squared, gender, co-residing with a spouse, number of children, education, level of speaking English, citizenship, and year of survey are included in the Appendix tables.
Table 3

OLS regressions of economic characteristics for immigrants to the USA, age 25 to 64, interaction of ethnicity with years in the USA

  

Household income

SEI

Wage

UK

Years in the USA

0.005**

0.02

0.004**

Minority[Pakistanis]

−0.13

−10.456***

−1.288***

Minority[Indians]

−0.235

2.783

0.277*

Years in the USA*[Pakistanis]

0.001

1.879***

0.167**

Years in the USA*[Indians]

0.023

−0.101

−0.012

R 2

0.11

0.24

0.29

N

21,654

21,654

15,058

France

Years in the USA

0.005*

−0.085*

−0.001

Minority[Moroccans]

−0.64**

−14.683***

−1.02***

Minority[Algerians]

−0.69**

−6.715***

− 0.975***

Years in the USA*[Moroccans]

0.015*

0.642**

0.033**

Years in the USA* [Algerians]

0.029**

0.304*

0.029**

R 2

0.3

0.33

0.29

N

4575

4575

4284

Germany

Years in the USA

0.009**

−0.062**

0.004*

Minority[Turks]

0.043

1.466

−0.327

Minority[Iranians]

−1.077***

−6.008**

−0.661**

Years in the USA*[Turks]

0.017

−0.136

0.05*

Years in the USA*[Iranians]

0.071***

0.277

0.032*

R 2

0.12

0.33

0.32

N

21,969

21,969

13,604

Iraq

Years in the USA

0.048**

0.184**

0.014**

Minority[Kurds]

−1.029***

−6.143***

−0.198

Years in the USA*[Kurds]

0.092**

0.401**

0.032

R 2

0.12

0.48

0.24

N

2753

2753.00

1571

Israel

Years in the USA

0.031**

−0.056

−0.002

Minority[Arabs]

−0.317*

−6.982**

− 0.5**

Years in the USA*[Arabs]

−0.006

0.158*

0.02**

R 2

0.16

0.12

0.21

N

3173

3173

2113

Sources: 1980, 1990, and 2000 US censuses together with 2005–2009 ACS surveys. Note: All calculations were made with weights. Wage and socioeconomic index are among those working. Additional covariates included in model but not shown here are as follows: age, age2, sex, marital status, number of children, education, level of mastering English, citizenship, and year of survey

p ˂ .10; *p ˂ .05; **p ˂ .01; ***p ˂ .001

Table 4

OLS regressions of economic characteristics for immigrants to the USA, age 25 to 64, interaction of race with years in the USA

  

Household income

SEI

Wage

Brazil

Years in the USA

0.009**

0.059

0.014**

Race[Blacks]

−0.043

0.165

− 0.112

Years in the USA*[Blacks]

−0.012

0.033

0.008

R 2

0.06

0.26

0.28

N

5446

5446

3735

Canada (English)

Years in the USA

0.002

−0.074**

−0.001

Race[Blacks]

−0.329**

1.144

−0.243**

Years in the USA*[Blacks]

0.009

−0.261**

−0.009

R 2

0.19

0.33

0.24

N

12,521

12,521

12,227

Canada (French)

Years in the USA

0

−0.068

0

Race[Blacks]

− 0.474**

−3.541

−1.699***

Years in the USA*[Blacks]

0.017

0.31

0.097**

R 2

0.21

0.24

0.27

N

5345

5345

3377

UK

Years in the USA

0.005**

0.016

0.003*

Race[Blacks]

−0.23*

−3.102**

−0.326**

Years in the USA*[Blacks]

−0.002

−0.002

0.006

R 2

0.11

0.29

0.29

N

21,727

21,727

15,140

France

Years in the USA

0.004

−0.056

−0.002

Race[Blacks]

−0.405*

−6.565***

−0.314

Years in the USA*[Blacks]

−0.045*

0.24

−0.021

R 2

0.32

0.51

0.29

N

4203

4203

3949

Germany

Years in the USA

0.005** (0.001)

0.016 (0.017)

0.003* (0.001)

Race[Black]

−0.23* (0.101)

−3.102** (1.169)

−0.326** (0.092)

Years in the USA*[Blacks]

−0.002 (0.008)

−0.002 (0.091)

0.006 (0.007)

R 2

0.11

0.29

0.29

N

21,727

21,727

15,140

Sources: 1980, 1990, and 2000 US censuses together with 2005–2009 ACS surveys. Note: All calculations were made with weights. Wage and socioeconomic index are among those working. Additional covariates included in model but not shown here are as follows: age, age2, sex, marital status, number of children, education, level of mastering English, citizenship, and year of survey

p ˂ .10; *p ˂ .05; **p ˂ .01; ***p ˂ .001

Tables 3 and 4 focus mainly on two main indicators. One is how different the initial economic reception of the minority group is from the majority group. A negative sign means that, all things equal, membership in a minority group indicates a less successful economic reception (and an “ethnic penalty” later on) in comparison to the reference group, which is the majority group from the same country. The second important indicator in these tables is the interaction of number of years in the USA with the minority/majority status. This interaction demonstrates the pace with which minorities assimilate in the USA in comparison to the majority group. In other words, this interaction shows how well they achieve economic success for every year they stay in the USA. A positive sign next to this indicator means that, all things equal, being a member of a minority group indicates a steeper slope of economic advancement. Table 3 presents the economic advancement of non-black minorities compared to the corresponding majority group from the same country.

In contrast to the inconsistent human capital levels among the minority groups as shown above, the picture arising from their economic advancement in comparison to the majority groups is clear. Non-black immigrant minorities succeed faster than their corresponding majority group coming from the same country. Out of the eight immigrant minority groups, two groups (Algerian-French and Moroccan-French) have a positive sign, which is statistically significant for all of their economic indicators tested in interaction with the number of years they have been in the USA. Four other groups (Pakistani-British, Iranian-Germans, Arab-Israelis, and Kurdish-Iraqis) have two indicators that are positive and statistically significant. One group (Turks from Germany) has one indicator, which is positive and statistically significant. Only Indians from the UK are not statistically significantly different from their majority group (though even here, one indicator is marginally statistically significant and positive). Not a single group presents a slower economic advancement compared to the majority group. This means that non-black minority groups generally succeed faster than the corresponding majority group.

In addition, the starting point of each group should be noted as well. Except for the Turkish-Germans and the Indian-British, all groups are disadvantaged in comparison to the corresponding majority group. Their economic indicators (reflected in the constants) are lower than those of the corresponding majority groups, which implies that they carry an “ethnic penalty” when coming to the USA.

In sum, when non-black immigrant minorities come to the USA, they start in a lower level of economic achievements than the corresponding majority group. However, their pace of economic advancement over the years is steeper.

In comparison, Table 4 presents the economic achievements of the six black minorities who immigrated to the USA in comparison to the corresponding majority group from the same country. Once again, three regressions were estimated with three types of economic measures: wage income, socioeconomic index, and household income.

Table 4 shows that only one indicator is statistically significant and positive out of all three indicators tested. However, two indicators are statistically significant and actually negative. The rest of the indicators, 15 indicators overall, are not statistically significant in either direction. This hints at the fact that, all things equal, the pace of economic advancement of blacks is not significantly different from that of the corresponding white groups from the same country.

However, this does not mean that the economic condition of immigrant blacks is equal to their corresponding white majority group. The same phenomenon seen among non-black minorities appears here. Blacks are disadvantaged upon arrival and, in general, their economic condition is worse than that of white immigrants. There is not a single indicator that is statistically significant and positive; all 12 indicators that are statistically significant are negative. This shows the repeating disadvantage of blacks as opposed to the corresponding white majority groups. Combining those two findings raises the following summary: blacks carry a “racial penalty” and their situation does not improve with more years in the USA.

In addition, the models presented above assume linearity of economic advancement. However, this is not necessarily the case in reality (see Chiswick 1979). Therefore, as a sensitivity analysis, the models above were re-estimated. This time, interaction of minority/majority origins and five intervals of years in the USA (0–5, 6–10, 11–15, 16–20, and 25+) were included. In Table 7 in the Appendix, all non-black minority groups are aggregated, while controlling for the country of origin. In Table 8 in the Appendix, all black groups are aggregated, also controlling for the country of origin. Note that these tables have the advantage of presenting the regressions with all control variables that were included but not presented in Tables 3 and 4.

Indeed, this sensitivity analysis produces substantively similar results to those in Tables 3 and 4. They continue to show how all minority groups suffer from a “minority penalty” upon arrival. They also show how non-black minority groups assimilate faster with every additional group of years of residency in comparison to the majority groups. However, blacks do not show such a trend. Their pace of economic advancement is insignificant in comparison to the majority groups and their starting point is significantly lower (their starting point in the socioeconomic index is marginally significant).

5.3 Segmentation among immigrant minorities

A final examination takes note of the fact that the labor market is segmented. First, it should be asked if the same patterns of economic advancement presented herein occur among BA and non-BA holders alike. Second, it should be asked whether these patterns occur among minority men and minority women in the same way.

To address these questions, the above economic outcomes are graphed as a function of years in the USA while separating men from women, and BA holders from non-BA holders. Figure 1 presents the results for non-black immigrant minorities versus immigrant majorities.
Fig. 1
Fig. 1

Graphs of economic advancement over the years: non-black immigrant minorities vs. immigrant majorities, age 25 to 64

These graphs show that an accelerated transnational social mobility occurs mostly among non-black minority men, BA and non-BA holders alike. Those who hold a BA degree, even tend to overtake majorities after many years in the USA. In comparison, minority women remain mostly disadvantaged, with one important exception. Minority women who hold a BA degree and work succeed in making faster progress in comparison to immigrant majority women.

The next figure presents variations in economic advancement among immigrant blacks versus immigrant whites.

Figure 2 shows somewhat different characteristics of economic advancement. In general, as opposed to non-black minorities, only immigrant blacks who hold a BA degree succeed in making progress over years in the USA. Even then, it is hard to say that they actually overtake whites over the years or that their pace is significantly faster than the white majority. In contrast, black men who do not hold a BA degree do not succeed in making progress in comparison to whites. At times, they even display downward mobility after a few years in the USA.
Fig. 2
Fig. 2

Graphs of economic advancement over the years: immigrant blacks vs. immigrant whites, age 25 to 64

As for women, they tend to remain disadvantaged even after many years. However, similarly to non-black women, black women who hold a BA degree and work succeed in overtaking their white counterparts over the years. In this sense, the American labor market is an encouraging environment for immigrant minority women who hold a BA degree, blacks and non-blacks alike.

6 Discussion

This study investigates 14 groups of immigrant minorities and 11 groups of the corresponding immigrant majorities. It uses two types of comparisons in order to isolate the unique mechanisms characterizing transnational social mobility. One type of comparison is between immigrant minorities and the corresponding majority group from the same country and the other is between two meta-groups of immigrant minorities: black and non-black minorities.

Three main questions are answered here regarding these comparisons. The first is whether the human capital of immigrant minorities upon arrival is distinctly different from that of the corresponding majority groups. Findings show that when comparing 14 groups of immigrant minorities to their parallel majority group, one cannot see that they hold different characteristics (e.g., education and English mastery). This conclusion means that comparisons are made on an equal ground and that minorities’ phenomenal success in the USA is not based on any superiority in terms of skills.

The second question is whether immigrant minorities have an initial economic disadvantage in the USA compared to the corresponding majority group. Findings show that despite the similarity in terms of skills, the 14 groups of immigrant minorities are disadvantaged in terms of wage income, household income, and occupational prestige at their starting point. This implies that the transferability of their skills is lacking. Mechanisms of cultural barriers, parents’ education, education quality, and marginalization in the source country are among the variables mentioned in studies on these groups (e.g., Gesemann 2007, Heath and Cheung 2006, Heath, Rothon and Kilpi 2008, Kjerum 2009). These mechanisms seem to contribute to the fact that these immigrant minorities are relatively disadvantaged in the US labor market at time of arrival.

Following these two preliminary questions, the third and main question is how well immigrant minorities change their condition and advance over the years. Findings show that while black minorities remain disadvantaged over the years compared to the corresponding white majority groups, non-black minorities have steeper economic integration than their corresponding majority groups from the same country and, in some cases, even pass them over years in the USA.

One possible explanation for this phenomenon is a former experience in migration that helps ethnic minorities to adjust faster. However, recall that these findings hold no matter whether minorities are first-generation minorities and the immigration to the USA is their second immigration, second-generation immigrants, or even natives who did not immigrate before, nor did their parents. Thus, the mechanism of a former migration experience as an explanation is less plausible as an explanation here.

Another possible explanation for this phenomenon is initial difficulties in the transferability of skills among these minorities. The argument is that the “catch up” with immigrant minorities’ counterparts occurs since they overcome these difficulties eventually. Thus, the faster pace of economic advancement is a translation of the growing adjustment they experience. However, the following question arises if this explanation holds true: why do blacks not perform this “catching up”? Moreover, if the dominant mechanism at play is overcoming initial difficulties, then why do some minorities succeed in passing their majority counterparts? They should have reached the same point and cease there (see Chiswick 1979). Yet minorities that have enough tenure in the USA present an extra incentive to advance themselves and achieve even higher than the corresponding majority group as shown in the tables above and in Figs. 1 and 2.

It seems that one must consider the background of these immigrant minorities in order to fully explain their patterns of economic advancement. This paper suggests that these minorities perform transnational social mobility. The mechanism of “higher costs of return” as Borjas (1982) puts it, or “relative social improvement,” as Cohen (1996) defines might explain the case of immigrant minorities. Minorities might have an opportunity in migration. They can find better social environments in which they can pursue self-fulfillment according to their actual skills and, in turn, experience an accelerated social mobility in the destination country. In this sense, this paper demonstrates how an age of globalization brings processes of an increasing mobility to challenge the social structures that constrain minorities.

Indeed, the discrimination gap seems prominent in the case of minorities’ migration to the USA. Non-black minorities succeed better than those who have not experienced discrimination at all: the majority group. They also succeed better than those who are continuing to experience discrimination in the target country: black immigrant minorities. Both groups do not take advantage of the discrimination gap and, thus, display a slower pace of economic advancement. In contrast, non-black minorities, who are better accepted in the USA as shown above, have the opportunity to advance themselves.

7 Conclusions

The phenomenon of transnational social mobility of minorities has important policy implications. The growth prospects of developed countries are crucially related to their migration policies and their ability to identify migrants who will contribute to their economy. The labor market, the educational system, and the social welfare system are all affected by the changing composition of society produced by immigration (Borjas 2001, Castles et al., 2013, Lowenstein 2006). The current paper suggests reconsidering the economic contribution of immigrant minorities and their faster pace of economic integration. Indeed, if the likelihood of economic success is central for rationing admission to the USA and the EU as it seems from recent reports (Ayet-Puigarnau 2011), then more attention should be paid to immigrant minorities.

A second policy implication is in the context of economic integration policy programs. While almost no one claims that minorities are disadvantaged because of their nature, many argue that the disadvantage of minorities is strongly rooted in lower level of human capital—lack of sufficient education, lack of parents’ education, difficulties in acquiring the local language, and a lower social capital (Collett and Petrovic 2014, Fossati 2011, Poppelaars and Scholten 2008). Thus, the immediate conclusion is that in order to promote minorities there is a need to advance their level of education, integrating them into the majority society, and improving their skills.

However, this research joins other important studies (e.g., Banks 2000, Berry 1997, Crul, Schneider and Lelie 2013, Sternberg 2004) and argues that economic integration not only involves minorities themselves, but also their surroundings. In other words, this paper demonstrates how the social environment is crucial in determining the disadvantaged position of minorities and how transnational processes can “reshuffle” the social structure that constrains them. This “reshuffling” might drive minorities and prompt them to succeed.

Indeed, the scope of the investigation here is relatively narrowly focused on a set of economic indicators. A strictly economic focus can certainly be justified, given the primacy of economic forces in migration theory. However, researchers and policymakers must also ask what the cultural characteristics of such a move are. Do these minorities, who, generally speaking, have a more isolated way of life in their source communities, need to pay a heavier cultural toll for such a move? The exposure to a new culture in an attempt to improve their quality of life may have a cultural tradeoff. Former traditions are now exposed to others. This is true for any group of immigrants (Alba and Nee 2005, Giddens 2003), but it is especially true when dealing with minorities who even in their homeland were characterized by a distinct culture and way of life (e.g., Cohen 1996, Dale and Ahmed 2011, Gesemann 2007, Kraay 1998, Milan and Tran 2004, White 1997). While the typical immigrant interacts with two main political and cultural communities: the country of origin and the host country, an immigrant minority member interacts with at least three levels: the host society, mainstream society in the source country, and his or her own ethnic community. Qualitative and quantitative investigations of such a stance will give the research community a deeper understanding of this phenomenon.

Finally, contemplating the future of immigrant minorities’ economic integration in the USA is in need. The reader must take into account a new trend documented in a recent comprehensive study (Parrillo and Donoghue 2005), which claims that social attitudes towards blacks among college students have improved substantially compared to previous similar studies. This might provide the reader with hope that future studies regarding economic integration of immigrant blacks will find that they benefit from a more encouraging environment too, and have an opportunity to succeed in the USA as their host country in a similar way as non-black minorities have.

Declarations

Acknowledgements

I would like to thank the anonymous referee and the editor for the useful remarks. This research has been partly funded by the Truman Institute.

Responsible editor: Hartmut F. Lehmann

Competing interests

The IZA Journal of Development and Migration is committed to the IZA Guiding Principles of Research Integrity. The author declares that he has observed these principles.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
The Federmann School of Public Policy and Government and Truman Institute, Campus Mount Scopus, 91905 Jerusalem, Israel

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