Do Parents Matter? Revisiting Ethnic Penalties in Occupation among Second Generation Ethnic Minorities in England and Wales

Abstract

The article studies the role of the class of origin in the occupational outcomes of second generation ethnic minorities and white British in England and Wales. In so doing, it reconsiders the relationship between ‘ethnic penalties’ and intergenerational social reproduction (or the reverse: intergenerational social mobility) by combining approaches from the migration and social stratification literatures. Two main hypotheses are tested. The first states that the class of origin, or parental social background, helps explain differences in occupational outcomes between ethnic minorities and white British; the second says that intergenerational social reproduction processes vary between groups. Based on data from the United Kingdom Housing Longitudinal Study (UKHLS: 2009–2010), the article finds partial evidence for both hypotheses. In particular, it reveals that the lower social reproduction of Pakistani, Caribbean and African men has particularly negative consequences for higher educated minorities, who do not gain – as the white British do – from more advantageous origins.

Keywords

class of origin ethnic minorities ethnic penalties intergenerational social mobility migration occupation second generation

Introduction

It is generally understood that parents play a role in the educational and labour market outcomes of their children; those with a higher class of origin usually perform better than those from a lower class of origin. This concern, central in the literature on social stratification, is less often voiced in the migration literature. While the origin of individuals in terms of parental education and occupation is increasingly incorporated into studies of ethnic inequalities in education (Brinbaum and Cebolla-Boado, 2007; Dustmann, 2008; Dustmann et al., 2012; Heath et al., 2008; Kristen and Granato, 2007; Van de Werfhorst and Van Tubergen, 2007), it is seldom considered in studies of labour market outcomes.

The migration literature has defined ‘ethnic penalties’ as any remaining difference between ethnic minorities and native populations¹ – with respect to various outcomes – after background characteristics have been taken into account (Heath and Cheung, 2007). Ethnic penalties can mean different things: for example, employers not valuing the level of education acquired by the minorities (in the case of those who arrived), minorities not having enough information on jobs or the right networks, or discrimination in the labour market. But talking about ethnic penalties means implicitly that there is something intrinsic to being an ethnic minority that explains differences with respect to the native populations. This article argues that before defining a difference as an ethnic penalty, we need to have a better description of ‘background characteristics’.

Most studies of ethnic penalties in the labour market use education as the main explanatory background variable (e.g. Algan et al., 2010; Cheung and Heath, 2007; Crul and Vermeulen, 2003; Heath and Li, 2010). Arguably, education is the main predictor of labour market outcomes and most of the parental effect on them occurs through the positioning of individuals in the educational system (that is, in an indirect way). However, there is evidence that parents exert a direct effect on an individual’s outcomes as well, particularly occupation (Blau and Duncan, 1967; Breen, 2004; Breen and Jonsson, 2005; Bukodi and Goldthorpe, 2011; Goldthorpe, 2000; Kuha and Goldthorpe, 2010). Studies of ethnic penalties make, therefore, two assumptions: the class of origin or parental social background is equal for ethnic minorities and natives and its effect is equal for both of them. However, these assumptions are not realistic. First, ethnic minorities differ from native populations in terms of their parental backgrounds, which are usually lower on the social scale. Second, the mechanisms of intergenerational social reproduction (or the reverse: intergenerational social mobility) may vary between groups.

Previous studies of ethnic penalties in the UK (Cheung and Heath, 2007; Heath and Li, 2010) show that the fortunes of second generation ethnic minorities in the labour market vary. While results are generally quite pessimistic with respect to access to jobs (most ethnic minorities are less likely to be employed than the white British), they are more diverse when occupation is considered, with Indians doing as well as or even better than the white British and Pakistani and Bangladeshi populations experiencing the highest penalties. A smaller body of research (Heath and McMahon, 2005; Heath and Ridge, 1983; Platt, 2005a, 2005b, 2007) has added to the understanding of the second generation’s labour market outcomes by evaluating the contribution of the parental social background. These studies find that ethnic minorities tend to be on average more mobile than the white British, and Platt also argues that they are a more ‘meritocratic group’, with their achievements depending more on education and less on social origins. However, in a non-meritocratic society, this has also prevented some groups – like Caribbean – from gaining from advantaged origins, generating an ethnic penalty among those with higher parental social backgrounds.

Building on this literature, this article analyses the role played by class of origin in penalties (or gains) experienced by ethnic minorities in the labour markets of England and Wales, asking the following questions: a) Does the class of origin help explain ethnic penalties in occupational outcomes? b) Do social reproduction processes and, more specifically, the direct effects of the class of origin on occupational outcomes vary by ethnic group?

The article advances previous knowledge in a number of ways. First, it updates previous findings with more recent data from the first wave of the United Kingdom Household Longitudinal Study, which interviewed people in 2009–2010. In so doing, it reconsiders the relationship between ethnic penalties and intergenerational social reproduction by combining approaches from the migration and social stratification literatures. Second, it complements the study of access to the service class, the most popular variable for studying occupation in the UK, by exploring the International Socio-Economic Index (Ganzeboom and Treiman, 1996), a measure that considers the entire distribution of occupations. Finally, it sheds light on groups about which less is known, including Pakistanis and Bangladeshis (often studied together) and Africans. The survey has an oversample of the largest non-white ethnic minorities; this allows the identification of a number of minorities with both parents born abroad and showing results separately for men and women.

Theoretical Background and Hypotheses

Figure 1 shows a reduced version of the classical Blau and Duncan model (1967) with an ‘ethnic group’ component (G) included. Blau and Duncan show that the intergenerational social reproduction, the process through which parents transfer socio-economic and cultural resources to their children, helping therefore to reproduce the social structure in a society, occurs along two causal pathways: direct and indirect. An indirect effect occurs because high-class families (O) more successfully position their children in higher education (E) than low-class families, and education determines occupational outcomes (D). A direct effect covers all intergenerational reproduction outside education. This effect may include both genetic and social aspects: for example, parents can influence their children by giving them job advice, helping them to look for a job or providing them with economic resources; they can also transfer ability and cognitive skills (not entirely captured by education), offer social and relational aptitudes and supply a wide range of networks and connections. The amount and characteristics of this content vary between social classes. For example, even if two individuals have achieved the same education, if one has parents with professional/managerial occupations he/she might be able to wait longer to find a job more suitable for his/her capacities, or to use his/her parents’ connections for better matching jobs or jobs with a higher remuneration (compared to an individual whose parents belong to the working class).

Figure 1.

Ethnic penalties and intergenerational social reproduction.

When studying ‘net’ differences between ethnic minorities and native populations (i.e. ethnic penalties), expressed in Figure 1 in the GD arrow, most studies omit arrow A, thereby disregarding possible differentials in terms of ‘composition effects’ due to group-specific parental social backgrounds. Most also omit arrow B, the most relevant of the two in the present study. This arrow indicates that the mechanisms of intergenerational social mobility (on top of education) might vary between groups, and, in consequence, ethnic penalties might vary according to the class of origin.

In this article, I introduce the class of origin, measured as parental occupational status, in these two ways, testing two hypotheses (the second divided in two sub-hypotheses) corresponding to arrows A and B and to the research questions proposed above. A summary appears in Table 1.

Table 1.

Research questions, arrows, hypotheses and explanations.

Research question	Arrow	Hypotheses	Explanations
a	A	1) ‘Compositional effect’	1) Ethnic minorities are more likely to have parents with low-status jobs
b	B	2) Variation in social reproduction processes: 2a) Lower social reproduction of ethnic minorities 2b) Higher social reproduction of ethnic minorities	2) Variation in mechanisms: 2a) Higher motivation among the lower classes and/or lack of ‘extra’ parental resources among the higher classes 2b) Cultural and community factors, external constraints

First, I expect that including the parental occupational status as control variable should help reduce ethnic penalties for some groups (hypothesis 1). It is a common finding that, upon arrival, first generations do worse in the labour market than the native population (Algan et al., 2010; Kogan, 2006; Van Tubergen et al., 2004). In addition to possible discrimination, immigrants have difficulty transferring their cultural capital – especially education and language – to the destination society. They frequently end up doing jobs that do not correspond to their abilities and education. The fact that the parental or first generation is overrepresented in low qualified jobs could have a direct impact on the second generation’s occupational outcomes and might help explain the disadvantages observed for some groups.

Second, I expect that at least some of the mechanisms of social reproduction that apply to the general population do not apply to some groups or work in different ways, which will lead to group differences in intergenerational social reproduction (hypothesis 2). This general hypothesis is tested by means of two sub-hypotheses: one states that ethnic minorities are less dependent on their parental social backgrounds than natives (hypothesis 2a); the other says the opposite (hypothesis 2b).

According to Goldthorpe (2000), one of the main driving forces behind the stability of the class structure and the reason why the children of high-class parents do better than the children of low-class parents is that people’s priority is to achieve the parental class or, more specifically, to avoid downward mobility. In this context, achieving upward social mobility is a second-level concern. However, this reasoning might not apply to some ethnic minorities. Arguably, immigrants who arrive in a country, then decide to stay and raise a family, will want to see better lives for their children and will therefore invest in them (Dustmann, 2008). Motivation and high parental aspirations are often used to explain educational mobility among ethnic minorities (Heath et al., 2008). This parental pressure might also be expressed in a direct encouragement to find a good job and progress in a career. In the case of minorities with low-class backgrounds (the majority), higher motivation might mean less dependence on parental social backgrounds and, in some cases, over-performance with respect to natives (also a bid to recover the family’s lost occupational status).

Less dependence on the parental social background might occur among the higher classes as well, although this is likely to be related to other mechanisms. Among the higher classes, the avoidance of downward mobility is done primarily through education. For example, a university degree is necessary if the aim is to continue in a certain family professional tradition. However, higher classes also have a repertoire of strategies on top of education that might influence the labour market outcomes of their children. Parents, for example, might pay for the best universities or have connections in certain work areas. They might transfer certain lifestyles and manners, and particular social skills that have a ‘signalling’ effect in the labour market. These factors – more relevant among those aspiring to higher qualified jobs – might play a crucial role in comparisons of natives and ethnic minorities. Even if the parents of ethnic minorities have good jobs, they might lack all or some of these ‘extra’ properties that natives have presumably gained by being raised in the local culture and knowing the social rules. This, in turn, may make their children more dependent on education, and less dependent on parental social backgrounds.

The migration literature, however, notes other ethnic-specific mechanisms (especially for those with lower/middle-class parental backgrounds) that might push the relationship between parents and children in the opposite direction. Goldthorpe (2000) argues that the lower classes tend to reproduce their class because this is less ‘risky’ than aiming at a university degree that leads to a higher status job. In contexts of discrimination or where the labour market is more selective (or in contexts of crisis), ethnic minorities might be pushed to do jobs that are closer to their family tradition or more familiar to them, rather than seeking to improve through their careers. In other words, the rationale of following the parental background due to its inherently lower risk could be more salient among ethnic minorities in an unfavourable context (note: this argument counters the ‘motivational argument’).

Cultural factors and the community environment might also contribute to a stronger relationship between parents and children. In fact, even if minorities adapt to the cultural premises of the receiving society, this does not mean that their own cultural backgrounds and those of their co-ethnics have lost their effect (Vermeulen and Perlmann, 2000). For example, south Asian communities tend to follow a ‘patriarchal model’ (Peach, 2005) where concepts such as control, family honour and status are crucial, and men are meant to be the main ‘providers’. Women in these communities might be more disadvantaged in access to jobs or in the types of jobs they can perform (Brah, 1993; Dale et al., 2002), making them more dependent on family tradition. Strong relationships with co-ethnics might also lead ethnic minorities to relate more closely to jobs typically attached to their family or community. A similar argument can be made for those born in communities with a tradition of ethnic entrepreneurship or where ethnic niches (specialization in certain occupations by certain ethnic groups) are common sources of jobs (Portes, 1998). All these mechanisms will be reflected in stronger intergenerational social reproduction among ethnic minorities.

Two final comments: first, a general expectation, which derives from hypotheses 2a and 2b, is that differences in social reproduction will imply different levels of ethnic penalties (or gains), depending on the class of origin; second, there might be processes that affect ethnic minorities irrespective of their social origins, such as discrimination in the labour market (Heath and Cheung, 2006; Wrench and Modood, 2000).

Data and Methodology

The article uses data from the United Kingdom Household Longitudinal Study. It uses cases included in Wave 1 (2009–2010), although Wave 2 (2010–2011) has been used to complete missing information on parental background. This survey has a high number of cases (around 40,000 household interviews) and an oversample of five ethnic minorities (around 1000 per group): Indians, Pakistanis, Bangladeshis, Caribbeans and Africans. The article compares white British to these five ethnic minorities; the population includes only second and 1.5 generations (those born in the UK or arriving before age seven). Groups are constructed through combining information on self- and parental ethnic identification and parental country of birth. White British are individuals declaring themselves as ‘white British/English/Scottish/North Irish’ and having British parents born in Britain. From the five ethnic minorities, I have selected those with foreign-born (non-British) parents,² coding individuals according to whether they self-identify as Indian, Pakistani, Bangladeshi, Caribbean or African.³ Using the information on parental ethnic identity, I then re-classify into the five groups those self-declaring as other Asian, other black, other, British and missing.

The study explores two dependent variables: occupational status and access to the service class. I also look at employment (people that worked in the past week compared to the active population) but only to get a better picture of occupational outcomes. Occupational status is measured with the International Socio-Economic Index – ISEI (Ganzeboom and Treiman, 1996), derived from the International Standard Classification of Occupations (ISCO-88) (Ganzeboom and Treiman, 2013). The ISEI ranges from 16 to 90 and measures the attributes of occupations that convert a person’s education into income. The highest score is given to judges, the lowest to low qualified farm workers and helpers and cleaners in establishments. The access to the service class is a dummy variable through which I identify people that belong (1) or not (0) to such a class. The service class refers to the highest two categories of the National Statistics Socio-Economic Classification (NS-SEC); it includes: employers in large establishments, higher and lower professional, managerial and administrative occupations and higher technical and supervisory occupations. For comparative purposes, note that around 50 per cent of people in the service class have an ISEI of 65 or more and 80 per cent have an ISEI above 50 (those below 50 are mainly teachers). Conversely, almost all cases with an ISEI above 65 are in the service class.

The two key explanatory variables are education of the individual and occupational status of the parents. The education of the individual has the following categories: degree, other higher, A-level etc., GCSE etc., other qualification and no qualification (for the descriptive statistics, I group some categories). The parental occupational status is built from parental occupations, available for both father and mother when the individual is 14 years old. The occupations, measured with the Standard Occupational Classification (2000) are recoded to ISCO-88 and then transformed into ISEI scores. The variable shown in the tables considers the maximum between both parents.

The total sample covers persons between 18 and 60 years of age. The analysis uses currently employed people and unemployed or inactive people who had their last job in 2000 or later (around 80% of currently unemployed/inactive people).⁴ The models are based on linear and logistic regressions and I differentiate between men and women.⁵ Age is included as a control.

Descriptive Statistics

Tables 2 and 3 show descriptive statistics for the groups, separated by gender. Ethnic minorities are, on average, younger than the native population (except for Caribbeans) and they also tend to be more educated. This is especially pronounced among women and among Indians and Africans, who have the highest proportion of individuals with a university degree, easily surpassing the native population. Indians and Africans also have relatively higher parental occupational statuses; Pakistanis, Bangladeshis and Caribbeans tend to have parents with lower ISEI than natives.

Table 2.

Descriptive statistics for men. Means (M) and percentages (%).

	Native	Indian	Pakistani	Bangladeshi	Caribbean	African
Background characteristics
(M) Age	39.6	32.6	30.0	28.7	40.8	33.4
(M) Parental ISEI	44.9	42.6	37.0	36.0	36.0	50.7
(%) No qualification	11.3	1.2	9.0	5.4	9.2	0.0
(%) GCSE & other	28.3	13.8	21.5	36.0	26.3	14.7
(%) A-level & other higher	35.0	35.3	32.9	32.5	39.9	27.5
(%) Degree	25.3	49.7	36.5	26.2	24.6	57.8
Employment
(%) Employed	90.3	88.9	79.5	90.5	73.7	83.5
(%) Employed (with controls)¹	90.3	88.1	85.0	93.4	72.1*	81.5*
Occupation and social reproduction
(M) ISEI	45.4	54.0	43.7	45.9	43.8	45.9
(%) Service class	41.7	56.2	31.5	38.7	34.1	43.6
Totals (unweighted)
Total population	7103	206	127	64	144	47
Active population	6529	188	124	55	131	44
Valid occupation	7019	199	124	61	142	44

Notes: Parental ISEI, education and age refer to the total sample; employed is calculated as a fraction of the active population; ISEI and service class refer to those with a valid occupation.

Controls for age, education and parental ISEI. Estimated for a 33-year-old person with average parental ISEI and education.

Difference with respect to natives is statistically significant at 95%.

Table 3.

Descriptive statistics for women. Means (M) and percentages (%).

	Native	Indian	Pakistani	Bangladeshi	Caribbean	African
Background characteristics
(M) Age	39.8	32.2	30.8	26.1	41.6	34.6
(M) Parental ISEI	44.7	40.6	38.6	39.5	34.7	52.9
(%) No qualification	8.6	2.3	2.4	8.8	1.0	2.1
(%) GCSE & other	31.6	16.4	27.9	27.3	27.6	8.4
(%) A-level & other higher	35.2	39.8	35.8	34.9	37.7	33.0
(%) Degree	24.6	41.5	33.9	29.0	33.7	56.5
Employment
(%) Employed	94.2	88.6	82.6	65.8	88.7	89.5
(%) Employed (with controls)¹	94.2	89.9	86.3*	79.0*	85.5*	86.7*
Occupation and social reproduction
(M) ISEI	44.7	50.5	46.9	48.2	47.5	51.1
(%) Service class	37.9	42.9	31.1	20.9	51.4	53.5
Totals (unweighted)
Total sample	8979	239	147	62	245	70
Active population	7246	193	96	43	210	57
Valid occupation	8921	233	138	53	239	67

See notes in Table 2.

Tables 2 and 3 also show results for employment⁶ (before and after controlling for background characteristics) and occupation. The results on employment levels indicate both group and gender differences, and show an improvement over time for most groups. For example, while in the 1990s, differences in employment levels between Indians and natives were around 4 per cent (men) and 10 per cent (women) in favour of the latter (Cheung and Heath, 2007), we observe that that these have reduced and are statistically non-significant after controlling for background characteristics. This improvement is also observed for Pakistani men, who do not suffer ethnic penalties in their access to jobs. Bangladeshi men are in a similar situation. A different scenario is revealed for Asian women. Although there are no good previous estimations for female Pakistanis and Bangladeshis, note the low levels of employment for Bangladeshi women; and although Pakistani women do not present extremely low employment levels, they have high levels of inactivity, which have been maintained over time (data available on request). Differences with natives remain after controlling for background characteristics. Pakistani and Bangladeshi women therefore suffer ethnic penalties in access to jobs: they have between 8 per cent and 15 per cent less probability of being employed than natives. Previous literature suggests that there is a tension between cultural norms in Muslim immigrant communities and the norms in the host society (Dale et al., 2002) whereby men are expected to assume the financial responsibility and women are not expected to work. This might imply that Muslim women who declare themselves active might not try as hard as native women to find work.

Among the black populations, the results show that Caribbeans have not improved much over the past decade. Both genders suffer ethnic penalties in access to jobs: men have 18 per cent points less probability of being employed, while for women the penalty is around 9 per cent. The same is observed for Africans, who have around 8–9 per cent points less probability of being employed than natives. Penalties observed for these groups might be linked to processes of discrimination based on skin colour.

As regards occupation, ethnic minorities do not tend to be disadvantaged when the average ISEI is considered: only Pakistani and Caribbean men have a slightly lower ISEI, while other groups, like Indians and Africans, have an advantage. However, when access to the service class is estimated, we observe some group differences. Indians are advantaged over white British, for both men and women. This pattern has been constant over the decades among men, but women have only recently reached levels that are above those of natives; this trend might be related to gains in education. The disadvantage observed for Pakistani and Caribbean men is another result that has been maintained over time, and, like this study, other researchers have noted an advantage observed for Caribbean women (Cheung and Heath, 2007). For the remaining groups, Bangladeshis (especially women) have a lower share of service jobs than natives, while Africans are more advantaged, on average. A comparison of respondents’ and parental ISEI shows that most groups (Africans are an exception) have improved on their parents’ occupations.

Occupation and Class of Origin

In this section, I look at the occupation of respondents and explore, first, the extent of ethnic penalties before and after accounting for parental background and, second, social reproduction processes among ethnic minorities and British. Previous studies have considered unemployment as one extra category in the occupational scale (Platt, 2005b). Here, I have prioritized the occupation of individuals, be it current or past.

Models 1a and 1b of Tables 4 and 5 show the effect of being an ethnic minority as it is studied in most of the literature on ethnic penalties in the labour market, namely, only controlling for education. The results show that Indians have a higher occupational status than white British (around three to four ISEI points more); after controlling for parental background (Models 2a and 2b), these effects become stronger and, in the case of men, a positive effect appears in access to the service class. This suggests that having lower parental backgrounds is advantageous for Indians. A similar result is observed for Bangladeshis when studying the ISEI: for example, among men, the effect is doubled (from two points difference to four) after the parental background is included. Note, however, that Bangladeshi women experience the highest penalty in access to the service class, and the lower class of origin does not compensate for this. Pakistanis do not seem to experience penalties in terms of occupational status and the class of origin explains part of the penalty observed in access to the service class (the negative effect reduces for both genders; although it remains statistically significant in the pooled version of the model - not shown). Note that previous findings for these two groups (Heath and Li, 2010; Platt, 2007) have been more pessimistic in terms of occupational achievements: the results presented here partially contradict these. Moreover, my results show that Pakistanis and Bangladeshis are different, a good reason to study them separately. The results for Caribbeans in terms of access to the service class show that the disadvantage experienced by men is probably related to their class of origin, while women experience a small advantage once background characteristics are controlled for. The results for the ISEI do not reveal ethnic penalties for this group. Finally, Africans show quite strong penalties among men, which, given the higher class of origin and educational levels of this group, is quite a negative result.

Table 4.

ISEI and access to service class for men. B-coefficients and average marginal effects (standard errors).

	Ethnic penalties ISEI		Ethnic penalties Service Class		Social reproduction ISEI
	Model 1a	Model 2a	Model 1b	Model 2b	Model 3a	Model 3b
(Constant)	30.742	27.342			34.004	27.231
	(0.483)***	(0.536)***			(0.424)***	(0.536)***
Indian	4.269	5.464	0.043	0.071	14.639	7.706
	(1.205)***	(1.171)***	(0.033)	(0.032)**	(2.104)***	(2.056)***
Pakistani	−1.781	0.042	−0.098	−0.059	9.327	6.664
	(1.657)	(1.694)	(0.053)*	(0.056)	(3.041)***	(3.222)**
Bangladeshi	2.067	3.907	0.025	0.068	2.910	3.629
	(2.358)	(2.289)*	(0.068)	(0.070)	(4.015)	(3.784)
Caribbean	−2.334	−0.807	−0.092	−0.058	7.449	2.508
	(1.428)	(1.363)	(0.048)*	(0.045)	(2.450)***	(2.466)
African	−6.390	−6.497	−0.122	−0.123	8.252	0.367
	(2.894)**	(2.826)**	(0.065)*	(0.062)**	(5.681)	(5.654)
Parental ISEI		0.169		0.004	0.361	0.174
		(0.012)***		(0.000)***	(0.012)***	(0.012)***
Indian*Parental ISEI					−0.141	−0.085
					(0.066)**	(0.059)
Pakistani*Parental ISEI					−0.301 (0.119)**	−0.322 (0.129)**
Bangladeshi*Parental ISEI					0.151 (0.157)	0.016 (0.141)
Caribbean*Parental ISEI					−0.305 (0.083)***	−0.163 (0.081)**
African*Parental ISEI					−0.247 (0.153)	−0.196 (0.150)
R2	0.31	0.33			0.12	0.33

Notes: Models 1a, 1b, 2a, 2b and 3b control for education; all models control for age. References for categorical variables: native; no qualifications. Constant refers to a 30-year-old native with parental ISEI of 16 and no qualifications. Unweighted N = 7589. ***p-value<.01 **p-value<0.05 *p-value<0.10.

Table 5.

ISEI and access to service class for women. B-coefficients and average marginal effects (standard errors).

	Ethnic penalties ISEI		Ethnic penalties Service Class		Social reproduction ISEI
	Model 1a	Model 2a	Model 1b	Model 2b	Model 3a	Model 3b
(Constant)	31.698	29.270			36.500	29.272
	(0.531)***	(0.551)***			(0.349)***	(0.552)***
Indian	3.473	4.399	−0.006	0.007	6.692	3.091
	(1.197)***	(1.172)***	(0.033)	(0.033)	(2.195)***	(2.088)
Pakistani	1.075	2.168	−0.082	−0.066	8.387	4.605
	(1.332)	(1.342)	(0.042)*	(0.043)	(2.614)***	(2.344)**
Bangladeshi	4.139	4.934	−0.131	−0.121	−2.848	−2.748
	(2.381)*	(2.247)**	(0.056)**	(0.057)**	(3.589)	(3.527)
Caribbean	0.084	1.497	0.045	0.066	8.562	2.760
	(1.266)	(1.267)	(0.032)	(0.033)**	(2.356)***	(2.618)
African	1.058	0.610	0.005	−0.001	7.067	2.001
	(2.319)	(2.316)	(0.053)	(0.055)	(3.989)*	(3.705)
Parental ISEI		0.121		0.002	0.268	0.121
		(0.010)***		(0.000)***	(0.010)***	(0.010)***
Indian*Parental ISEI					0.042	0.054
					(0.080)	(0.072)
Pakistani*Parental ISEI					−0.159(0.108)	−0.109(0.100)
Bangladeshi*Parental ISEI					0.364(0.173)**	0.313(0.166)*
Caribbean*Parental ISEI					−0.177(0.116)	−0.068(0.141)
African*Parental ISEI					−0.064(0.123)	−0.037(0.113)
R2	0.22	0.23			0.07	0.23

Notes: See notes in Table 4. Unweighted N = 9651. ***p-value<.01 **p-value<0.05 *p-value<0.10.

In what follows, I explore in more detail arrow B from Figure 1, which accounts for group differences in social reproduction processes. I only consider the ISEI, prioritizing, therefore, the measure that considers the entire distribution of occupations. Models 3a and 3b from Tables 4 and 5 show the parental effect on occupation for the various ethnic groups, before and after controlling for education. Among men, the interaction shown in Model 3a in Table 4 indicates that the occupational statuses of Indians, Pakistanis, Caribbeans and Africans⁷ are much less dependent on the parental ISEI: subtracting these coefficients to the main coefficient for natives (0.361) gives values close to zero (or a smaller value in the case of Indians). After controlling for education (Model 3b), the now direct parental effect is smaller for most groups, denoting the mediating role of education; for Caribbean and African it is even close to zero, implying that the class of origin does not have a direct effect for these groups. For Pakistanis, the introduction of education causes the direct effect of parental background to have a negative effect on individuals’ ISEI, an unusual result. Among women, the results go in the same direction for most groups. The most interesting result is that Bangladeshi women are much more dependent on the class of origin than are natives (or other groups).

Figure 2 illustrates the relationship between parents’ and respondents’ occupations, revealing the extent to which ethnic penalties vary according to the class of origin of individuals. The graphs are derived from Model 3b (hence, they control for education) and represent predicted ISEI scores for a 33-year old person. I have put together the groups with similar social reproduction patterns and have differentiated between genders. On the one hand, Indians and Bangladeshis show positive and stronger effects of parental background on ISEI; on the other hand, Pakistanis, Caribbeans and Africans show negative or weaker effects (among men, close to zero).

Figure 2a.

Predicted ISEI by parental ISEI – Men.

Figure 2b.

Predicted ISEI by parental ISEI – Women.

As mentioned earlier, Indian men and women and Bangladeshi men have social reproduction patterns similar to white British. This can easily be observed in the graphs, which show no differences in the slopes. Bangladeshi women depend more on parental background, leading to a higher (and positive) gap among those with a higher status. For example, while the predicted ISEI score among those with parental ISEI of 20 is 40 for both groups, among those with a parental status of 50 it is around 44 for natives and 52 for Bangladeshis. In other words, a one point increase in the parental ISEI gives a greater advantage to Bangladeshi women than to native women.

In the other three groups, women are very similar to white British; among men, Pakistanis show a negative relationship between respondents’ and parental ISEI, while Caribbeans and Africans have a relationship close to zero. The negative effect of parental background on the occupations of Pakistanis leads to equal (or better) opportunities for those with lower class backgrounds; this comprises the majority of Pakistanis (60% of Pakistanis have a parental ISEI below 50). However, this also leads to negative gaps with natives for those with a higher class of origin; for natives there is a positive effect of parental ISEI. Caribbean minorities are doing quite well if we consider that most have a parental ISEI below 50. Earlier, Platt (2005b) suggested that a service class origin among Caribbeans gives them no advantage: this certainly seems to apply to men. In fact, the fact that the class of origin gives no advantage leads to an ethnic penalty among those with a higher class status. The results found for Africans resemble those for Caribbeans: for them as well, a higher class of origin yields no benefits. A main difference, however, between Africans and the other groups is that they have relatively higher parental backgrounds, even higher than that of the white British. This means that the penalization affects a higher proportion of this population: for both groups, the highest gaps are observed for those with a parental ISEI above 50; these constitute around 10 per cent of Caribbeans but around 40 per cent of Africans.

Next, I add interaction effects with education to explore a context in which returns to education – i.e. the effect of education on occupation – might vary between the groups. While mainly exploratory, the analysis sheds light on the previous findings. Table 6 shows the results of the ‘full models’, for men and women, including interactions between the groups, parental ISEI and education. Given the large number of individuals acquiring higher educational levels, I explore returns to education only for the effect of having a university degree.

Table 6.

ISEI: social reproduction and returns to degree level. B-coefficients (standard errors).

	Men	Women
(Constant)	33.810	36.149
	(0.385)***	(0.328)***
Indian	11.241	4.908
	(1.999)***	(2.012)**
Pakistani	7.549	6.400
	(3.004)**	(2.497)**
Bangladeshi	4.245	−2.316
	(3.874)	(3.494)
Caribbean	5.659	5.653
	(2.505)**	(2.688)**
African	7.856	2.559
	(5.657)	(3.776)
Parental ISEI	0.224	0.155
	(0.012)***	(0.010)***
Indian*Parental ISEI	−0.136	0.053
	(0.069)**	(0.077)
Pakistani*Parental ISEI	−0.274	−0.112
	(0.122)**	(0.100)
Bangladeshi*Parental ISEI	0.011	0.376
	(0.148)	(0.150)**
Caribbean*Parental ISEI	−0.189	−0.097
	(0.075)**	(0.138)
African*Parental ISEI	−0.119	−0.112
	(0.155)	(0.113)
Degree	16.945	14.508
	(0.460)***	(0.396)***
Indian*Degree	−2.466	−2.909
	(2.737)	(2.589)
Pakistani*Degree	−4.657	−3.605
	(3.127)	(2.834)
Bangladeshi*Degree	−1.496	−7.058
	(4.332)	(3.483)**
Caribbean*Degree	−6.476	−3.108
	(3.656)*	(2.694)
African*Degree	−15.547	4.537
	(5.027)***	(4.481)
R²	0.28	0.20

Notes: Models control for age. Ref. for categorical variables: native; no degree. Constant refers to a 30-year-old native with parental ISEI of 16 points and no qualifications. Unweighted Ns: 7589 (men), 9651 (women). ***p-value<.01 **p-value<0.05 *p-value<0.10.

Table 6 shows that, with the exception of African women, all groups have lower returns to a university degree. The groups with the lowest returns are black African and Caribbean populations (and Pakistanis, but not statistically significant) among men and Bangladeshis among women. For these groups, having a university degree (vs. not having it) gives less advantage, in terms of occupational status, than for natives; for Africans this effect is close to zero. Figure 3 plots these results in four graphs. Ethnic minorities are grouped as shown as in Figure 2.

Figure 3a.

Predicted ISEI by parental ISEI and degree – Men.

Figure 3b.

Predicted ISEI by parental ISEI and degree – Women.

The graphs in Figure 3 add interesting information on the role of class of origin. First, among Bangladeshi women, the higher dependence on parental background leads to a positive gap only among those with no university degree; among those with a university degree, native and Bangladeshi women are similar (those with the lowest social backgrounds are slightly disadvantaged). Second, the null effect of parental social background observed among Pakistanis, Caribbeans and Africans, combined with the lower returns to education, creates an ethnic penalty for those with a university degree. In fact, among those without a degree, groups are more similar in terms of average achievements; those with the lowest social backgrounds even have an advantage. Note that among Pakistanis, the negative effect of the parental ISEI found in the previous analysis is now close to zero, like that observed for the black Caribbean and African male populations.

Discussion

In this article, I argue that the role of the class of origin is crucial for understanding differences between ethnic minorities and native populations. First, because some ethnic minority groups have parents with lower social backgrounds, creating a ‘compositional effect’; second, because social reproduction processes might vary between groups. These concerns were expressed in two research questions and hypotheses.

In my first question (a) and hypothesis (hypothesis 1), I explore whether the class of origin helps explain differences in occupational outcomes between ethnic minorities and natives, expressed in arrow A of Figure 1. The second question (b) asks whether social reproduction processes vary by ethnic group; I especially consider the direct effect of class of origin on labour market outcomes. This question is expressed in arrow B of Figure 1. The general expectation of an affirmative response (hypothesis 2) was tested by means of two sub-hypotheses: one expects lower social reproduction (lower dependence on parental background) among ethnic minorities (hypothesis 2a); the other expects higher social reproduction (hypothesis 2b).

In response to the first question, we saw that most of ethnic minorities have lower average parental occupational statuses than white British. Considering this in the analysis generally favours minorities, either by reducing the ethnic penalty (among Caribbean and Pakistani men), or by widening a positive gap (among Indian and Bangladeshi). In the first process, the outcome supports hypothesis 1, which assumed ethnic penalties would be found for some groups. The second process reveals that coming from a low social background has a certain advantage if one belongs to an ethnic minority. This interesting finding suggests motivational factors, typical of ethnic minorities who have lost occupational status in the host country and want to see their children ‘recover’ the initial status at origin. Bangladeshi women are an exception; for them, considering the effect of the class of origin does not modify the penalty they suffer gaining access to the service class. Africans also have a different outcome. This group has much higher social origins than other ethnic minorities. For them, the class of origin does not seem to play a role, and the effect goes in the opposite direction: it either widens the ethnic penalty or reduces a positive gap. This surprising result points to a penalty associated with higher social origins.

As regards the second question, I suggested that Goldthorpe’s arguments (2000) to explain the stability and reproduction of the social structure for the general population might not always apply to ethnic minorities. Differences in motivation and aspirations, manners and ways of behaving, constraints related to the economic context and family, community and cultural factors might contribute to the development of divergent social reproduction patterns that affect ethnic penalties. The results partly support these arguments.

Indians and Bangladeshis more closely resemble the native population in social reproduction patterns, as do women in general. For them, a higher class of origin means a higher occupational status. This contradicts the view that ethnic minorities are a more ‘meritocratic’ group (Platt, 2007). Bangladeshi women are the only case that supports hypothesis 2b. They depend more strongly on their parental background as compared to natives. Possible explanations might be related to family and community factors. Among these groups, the family well-being is usually a male responsibility, which may explain women’s high levels of inactivity and their penalty in employment (possibly linked to less effective job searches). However, for some (potentially) active women, these same community factors seem to play a positive role. The data show that among Bangladeshis, there is a strong concentration in occupations typically related to ethnic entrepreneurship, as, for example, the management of restaurants. Having parents in these jobs might give Bangladeshi women access to occupations that their education might not necessarily allow: as a matter of fact, the advantage observed with respect to natives is only evident among women without a degree. Perhaps the compensatory effect of having entrepreneurial parents explains why there is an average ethnic penalty in access to the service class (also slightly stronger among those without a degree), but an advantage in the ISEI.

Pakistani, Caribbean and African men display the social reproduction patterns expected in hypothesis 2a. Parental occupation does not affect their ISEI; a higher social background provides no advantages. However, the consequence this has in terms of ethnic penalties varies for groups with and without a university degree. In fact, while minorities with no degree are quite similar to equivalent British, even presenting an advantage for those with the lowest parental backgrounds, for those with a degree the picture is different: those with lower origins are similar to natives and, therefore, are not penalized in the labour market; those with higher origins are penalized, that is, have a lower occupational status than natives. This might be due to a lack of ‘signalling’ resources among ethnic minorities (something enjoyed by British higher classes). It may also be revelatory of selective processes of discrimination, only occurring in certain occupational niches or sectors of the economy. Among Pakistanis, it could also point to community constraints: those who experience penalties are mostly the children of either self-employed parents or parents working in retail, typically of ethnic niches. This could be pushing these individuals to work within their ethnic network, even if this implies giving up better possibilities outside (note that the same argument had positive consequences for less educated Bangladeshi women). A general conclusion for these three groups, in any case, is that the class of origin matters more, and therefore has stronger consequences in terms of the size of ethnic penalties, among those with a university degree.

This article shows that the role of the parental background is important for understanding how second generation ethnic minorities perform in the labour market. Not considering it implies not only overestimating ethnic penalties for some groups, but also assuming that all individuals within a certain minority group have the same chances in terms of occupational outcomes. The article also shows that the study of occupational status (ISEI) paints a rosier picture in terms of labour market outcomes, suggesting that the service class might not be the best unique measure of performance in the labour market.

Footnotes

Acknowledgements

I would like to thank Professor Fabrizio Bernardi, for his guidance during the initial stages of this article, and to Professor Lucinda Platt, for sharing her expertise with me. Thanks also to Professors Raul Jorrat and Harry Ganzeboom for their theoretical support.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Notes

Carolina V Zuccotti is a sociologist and PhD candidate at the European University Institute (expected defense: 2014). Her areas of specialization are social inequality, international migration, urban studies and quantitative methods. Carolina has been involved in research projects at the University of Buenos Aires, the Free University of Amsterdam and the London School of Economics and Political Science, and has carried out joint research on migration with professors Harry Ganzeboom, Ayse Guveli and Lucinda Platt. Her current research explores the link between social and spatial inequalities among second generation ethnic minorities in England and Wales, covering the following topics: social mobility, spatial segregation, neighborhood effects and residential mobility.

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