1. Introduction: Ethnic Disparities in COVID-19 Risks in England

2. Occupational Patterns across Ethnic Groups: Men and Women

I start by simply illustrating for each ethnic group those five jobs that had the highest shares of all workers from that group. I look at these ‘top five jobs’ for men (Table 2) and women (Table 3) separately and within each sex for the first generation and the UK born. I show how these jobs were distributed prior to the pandemic—specifically across the period 2016–2019. The White British comparison group was constructed to only include the UK born, so there is only a UK born row for this group. Conversely, 90% of the working age in the ‘Other White’ category were foreign born. I therefore do not include a UK born row for this group. As well as showing what percentage of each ethnic group is covered by each of these five occupations, I also provide the Herfindahl index, which represents a summary measure of the overall degree of ethnic diversity across all the occupations worked in for each ethnic group and migrant status combination. The Herfindahl index takes account of the shares of all the different ethnic groups in each occupation and provides a score between 0 and 1, where a higher score represents less diversity—or dominance of the majority group—and a smaller score represents more diversity, where numbers of minority groups have relatively high shares.

Several points should be noted from these tables. First, we see that women’s jobs are concentrated more intensely among the top five jobs than are men’s jobs. For example, 19% of White British women are in the five jobs that have the highest shares of White British women, compared to under 10% of White British men being concentrated in their five ‘top jobs’. Second, we see that the first immigrant generation tends to be more intensely concentrated among their top five jobs, with the second generation working across a broader range of industries. This is the case across the ethnic groups and sexes. For example, 33% of first-generation Pakistani men are concentrated in their top five jobs, compared to 20% of second generation men. Similarly, the five jobs with the highest shares of Black African women occupy a full 50% of these women, but among UK-born Black African women, only 23% work in their five most concentrated occupations. However, we can see, thirdly, that (with the exception of Indian women where only 15% are concentrated in just the top five jobs), UK-born ethnic minorities are still more heavily concentrated in their top five occupations than their White UK majority peers of the same sex. For example, 17% of UK-born Indian men, compared to around 10% of White British men, are concentrated in just five jobs, and 27% of UK-born Bangladeshi women are concentrated in five occupations compared to 19% of White British women. Fourth, minorities are not necessarily concentrated in low status occupations, with Indians and Pakistanis in particular also having relatively high concentrations in high status jobs like doctors and programmers. Therefore, while much of the discussion of ethnic inequalities due to COVID-19 have (rightly) focused on the role of longstanding deprivation, discrimination, and marginalisation driving the negative consequences for minority ethnic groups [46], there is also substantial heterogeneity that should be acknowledged. That is not to say that higher status jobs are necessarily without risks. But they are likely to be different risks. For example, Nagpaul [47] argues that occupational risks within the health profession are systematically different for ethnic minority doctors.

Fifth, we see that there is substantial decline in the extent to which minorities are concentrated in a relatively small number of selected occupations across generations. This is particularly visible from the Herfindahl index, which demonstrates much lower diversity (and therefore a higher concentration of the numerically dominant White majority) in the second generation. By contrast, in the first generation the level of diversity in the occupations in which immigrants work is high, indicating that these are occupations that include much higher shares of (various) minority groups. Nevertheless, inspection of the most common jobs shows that there is also generational persistence in occupational patterns. For example, 21% of first-generation Pakistani men are taxi drivers, but even among the UK born, 8% are taxi drivers.

Such intergenerational change and persistence is important for understanding ethnic differentials in COVID-19—both the causes of COVID-related inequalities and the longer term implications for the welfare of the different groups as circumstances change and different ‘shocks’ arise. On the one hand, the typically more ‘niche’ labour market opportunities, accessible to and occupied by immigrants, are less dominantly filled by the second generation. This indicates that intergenerational processes reduce occupational segregation and suggests that these occupational distributions among first-generation immigrants are not solely driven by ethnically driven labour market exclusion. Instead, the patterns of immigrant labour market entry and clustering in certain sectors have been documented more widely as part of the immigration process [see e.g., 48, 49].

On the other hand, some degree of persistence across the generations in self-employment, including taxi-driving, and in occupations, such as hospitality and catering work, which command low rates of pay and challenging working conditions, suggests that ethnic minorities do continue to face restricted labour market opportunities, and this leads to concentrations in those industries that may be somewhat more accessible through parental or community links. For the second generation taking up employment in these sectors, the consequences are lower pay and larger ‘ethnic penalties’ [e.g., 49]. That is, the wage penalties at similar levels of educational achievement that have been noted for both first and second generation ethnic minorities [e.g., 44] are more pronounced in the second generation when accompanied by participation in more segregated, ethnically-specific occupations. This is despite the fact that among UK-born ethnic minorities as a whole there are substantial levels of upward mobility, driven primarily by high levels of qualifications [50].

In terms of the occupations themselves, just looking at the top five sources listed here makes it clear that many ethnic minority groups are concentrated in roles that face greater risks of COVID-19 exposure (e.g., care workers) and those that are recorded as having heightened COVID-19 mortality (e.g., security guards). They also include those that have been particularly hard hit economically by the pandemic (e.g., hospitality workers) [cf. also 4]. Indeed, if we look at certain occupations, it is possible to identify how far they are dominated by foreign born and/or minority ethnic group workers. Nearly 2 in 5 male care workers are foreign born, despite foreign born men making up only 20% of the working age male population in paid work, while one in four female care workers are foreign born, despite foreign born women making up 20% of the female working age population. In line with this, White male care workers are underrepresented in contrast to their percentage of the working population, as they make up two thirds of care workers but three quarters of men in paid work. As such, when we combine information on ethnicity and whether or not foreign born, men and women who are both non-White and foreign-born are twice as likely to be care workers as their shares of the working age population in paid work would suggest. The ways in which care work is dependent on foreign born workers has been noted before; however, this reliance on minority care workers extends to UK-born ethnic minorities, with second generation Black African and Black Caribbean men in particular remaining highly over-represented among male care workers and second-generation Black Caribbean, Black African, and Pakistani women among female care workers. Although care work is much more common among women, the differences between minority and majority women are less substantial than they are for majority and minority men, reflecting the gendered nature of inequalities in work more generally. Migrant and minority status then partially aligns with and partly compounds those patterns. This occupation therefore provides a window on the ways in which immigrant labour inserts into longstanding occupational niches but is also reproduced in subsequent generations’ employment patterns.

Table 4 illustrates this issue further, showing the overrepresentation of both foreign born and ethnic minorities in occupations that have been demonstrated to be ‘vulnerable’ in terms of mortality and/or economic risks. As the table shows, all of these command a wage that is between 49% and 70% of average hourly pay. The enduringly high ratios of ethnic minorities in these roles again speaks to some perpetuation of occupational clustering—at least for those who are in work. Moreover, these roles are often taken by the main or principal earner in the household, with implications for the welfare of others should they get sick or lose their work. The household dimension of occupational distributions is taken up in the next section.

3. Occupational Patterns and Household Context

I now move on to consider the household context and again distinguish those families where the workers are UK born from those where they are not. This is in order to shed further light on how far household-level inequalities across ethnic groups are, more specifically, immigrant inequalities. It raises the question of how far immigrants are integrated into or excluded from society and how far we see replication across generations and what the potential longer-term implications may be.

First, to illustrate the ways the UK’s ethnic groups differ by age, Figure 1 shows the age structure of the ethnic groups but distinguished by whether they are foreign born. This shows the very youthful nature of the UK-born Indian, Pakistani, Bangladeshi, and, especially, Black African populations. It also shows how first-generation immigrants are predominantly working age. Only the Black Caribbean group has a substantial share of over-65s, reflecting the relatively early arrival period of the primary immigrant cohort of this group [30].

Moving on to think about the family and the household implications of occupational patterns, Figure 2 shows the family composition of working age households for the different ethnic groups. Working age is defined on the basis of the age of the household reference person—that is, the identified member of the household in whose name the accommodation is owned or rented or, if joint householders, the person with the higher income. Figure 2 again separates out the foreign born and the UK born. It shows both the UK- and foreign-born South Asian groups have a greater likelihood of having children, while Black African and Black Caribbean working age households are more likely to be lone parent families. This suggests that there is some continuity in household formation across specific ethnic groups, regardless of whether they are born in the UK or abroad, when we restrict the comparison to working families for both generations. Clearly, the differences in age structure, driven by different patterns of immigration and settlement as well as family formation, mean that there are large differences in the shares of people who fall into the working age population and therefore are excluded from this comparison. Figure 2 presents indicative evidence, however, that the extent to which workers have dependants varies by ethnic group, across both the UK and foreign born. This is relevant when considering differences in economic risk, health risk, and housing context.

I now turn to consider how occupational position, which as I have discussed is linked to economic vulnerability to COVID-19, varies within these family settings. Moving from individual occupations to sectors of employment, I first identify what share of households have a worker in one of the sectors predicted to be hardest hit economically: accommodation and food services; wholesale and retail; arts and entertainment; recreation; and construction. While these are broad sectors covering a wide range of occupations, they include some of those, such as those working in the hospitality sector, which are heavily over-represented among certain ethnic groups. Given the severe consequences of the pandemic for those in self-employment [27], I also include them in my overarching measure of economic risk.

Table 5 illustrates the share of members of each ethnic group—of whatever age—who are living with someone who is either in one of these at-risk sectors or is self-employed. The third column, commensurate with this, shows the average household size of those where someone is in the ‘economic risk’ category. Because larger household sizes may contain both dependants and other workers who may also compensate for household risks born by others, the fourth column gives the average number of workers in those households where there is someone in the economic risk category. The final column gives the average number of children in the family.

There is substantial variation across groups, with some having rather lower chances of being in one of the sectors that has absorbed the major economic impacts of the pandemic. What is also noticeable is, somewhat surprisingly, how consistent the patterns are between the foreign born and the UK born. Circumstances that lead to greater or lesser economic risks do not seem to be markedly different between the generations of the same ethnicity. Additionally, what is clear is how considering the household context shifts the perspective onto who is likely to be at risk of the economic consequences. This is not to say that the individual experience is not important, and much has been written about the potentially deep scarring issues faced by young people experience this economic context. However, it can also be informative to think further about capacity (or not) for risk pooling [4, 51] or, conversely, the extent to which risks impact others in the household.

We see that Bangladeshis and Pakistanis are not only more likely to be in these at-risk sectors of employment, but also that they are more likely to have more people living with them but with fewer of them in employment. The numbers of dependent children are also higher. These characteristics are remarkably similar across the generations, suggesting that there is no mitigation of risk from the first generation to the UK born using this broad measure. The implication is, therefore, that the economic impacts will be borne by multiple family members in these groups and that the risks are not tied to the specifics of migration status.

4. Conclusions: Looking Ahead

So what do we take away from this? This study suggests that occupational sorting has implications for both health and economic welfare and that the negative consequences of such occupational segregation are revealed to be particularly acute in the extreme circumstances of the pandemic. While such insights into the occupational patterning of ethnic groups’ labour market experience and its interconnection with historical, regional patterns of settlement is, as noted, not new [30, 31], what this analysis has revealed is the extent to which such occupational patterns persist into the subsequent generation. The household focus of the analysis has also shown how such occupational concentration has implications not only for individual’s life chances, but also impacts multiple household members, not simply the worker who is often the primary focus of economic analysis.

Looking ahead, it is important to reflect on these vulnerabilities for subsequent generations. There is substantial and increasing evidence that UK-born ethnic minorities are performing well in school, are entering higher education at increasing rates, and are achieving strong levels of upward mobility [50]. At the same time, labour market exclusion persists [52], and ethnic minority graduates do not get equal returns to their degrees. Such exclusion could be translating into the relative persistence in specific occupational niches, as well as in self-employment, that this analysis has shown.

As a result, differential valuation of forms of work, and the vulnerability of the self-employed ‘alternative’ labour market to economic shocks suggest that there will be ongoing economic pressures on minority groups, particularly Pakistani and Bangladeshis, meaning that future generations of the UK’s minority ethnic groups will continue to grow up in poverty. Figure 3 shows the differential rates of child poverty across ethnic groups over the period since 2002/3. Those who were poorest experienced substantial declines over the first decade of the 21st century but at no point reached parity with the White UK majority. More recently, rates have begun to increase again. The consequences of the pandemic for children growing up now is dramatic on many fronts, with the educational consequences for those of different ethnic groups still to be fully grasped. For many minority ethnic group children, the longstanding occupational segregation experienced by their forebears may consign them to substantial childhood deprivation and further delay the chances of economic parity.

Is there anything that can stem or change such vulnerability to economic and health shocks? Are such cycles of vulnerability inevitable? The evidence suggests that there are positive indications for the future and that policy can make a difference, but there also has to be the political will to do so. The success in reducing the child poverty of the poorest groups in the first decade of the 21st century showed that concerted poverty reduction strategies can be effective and illustrates where they have most effect. It was a set of political choices, changing entitlements as part of the move to universal credit among others, that has stemmed or even reversed that progress up until now, and such choices could do so again. Second, the extent of educational success and upward social mobility of minority ethnic groups indicates that disadvantaged backgrounds are not necessarily constraining and that access to good quality education does have potential for levelling the playing field. At the same time, there are also indications that the loss of schooling and its impact on education, as well as widening the attainment gap between more and less advantaged pupils [53], may also have driven a wedge between the attainment of minority ethnic groups and their majority peers [54]. An effective strategy for addressing learning losses will be crucial if we are not to see long-term impacts of the school closure in creating ethnic attainment gaps and in reversing the successes achieved in recent years [50, 34].

In terms of the labour market, it is clear that discrimination remains a persistent issue for access to employment [52], even if occupational attainment among those employed is increasing for ethnic minorities. This is despite the fact that the UK has some of the longest-standing and most robust anti-discrimination legislation in Europe. As this paper indicates, ‘blocked’ opportunities may be leading to some of the perpetuation of occupational segregation, which in turn makes minority ethnic groups more vulnerable to labour market shocks. Mandating better use of what we know about what improves outcomes—including reporting—is likely to be essential to address the persistent differences in access to work. For example, limiting scope for discretion in evaluation applications is recognised as reducing biased decision-making [55]. Incorporating self-employed workers more explicitly within the social security system has been indicated as being welcome to self-employed workers [27] and could offer some protection. For employees, minimum wages provide a floor for those in lower-paid work, while tax credits allowed for the fact that families of different composition had different living standards from wage-earners. Reversing some of the changes accompanying Universal Credit, such as the two-child limit, which penalised larger families, could help to ensure family living standards [56].

This paper has shown that occupational concentration is much greater among foreign-born ethnic minorities, and many immigrants are working in roles for which they are over-qualified. While match of employment to level of qualification improves with duration of stay [43], this over-qualification still represents a waste of potential, as well as a fiscal loss. Discussion around the valuation of particular forms of work, particularly caring work, has become more intense since the pandemic. These go beyond the question of the substantial concentration of certain groups of immigrant workers in caring occupations, but the two are clearly interlinked. Cogent arguments have been made that the UK cannot resolve the ‘crisis of care’ by looking to immigrant labour [57]. But until a more comprehensive reconsideration of the valuation of care—and other ‘essential’ roles—is engaged in [58], it seems likely that we will continue to see these occupational patterns and the consequent vulnerabilities persist.