University of Wales Swansea Born in Britain: how are native ethnic minorities faring in the British...

University of Wales Swansea

Born in Britain: how are native ethnic minorities faring in the British labour market?

D. H. Blackaby*D. G. Leslie**

P. D. Murphy*N. C. O’Leary*

* Economics Department ** Economics Department

University of Wales Swansea Manchester Metropolitan University Swansea ManchesterSA2 8PP M15 6BGUK UK


Ethnic minorities wage and unemployment gaps

Ethnic minorities wage and unemployment gaps in the 1990s

1970 1980 1990 1990*

Wage Gap 7.3 12.1 10 17

Unemployment Gap 2.6 10.9 10 10

Whites vs. Unemployment Gap Wage Gap

All ethnic minorities 10 17

Black 18 21

Indian 2 11

Pakistani 12 31

Native ethnic minorities 12 6


Earnings Decompositions

Unemployment Decomposition

1973-1979 1983-1989 1992-1996

Wage Offer differential 0.087 0.145 0.130

Unexplained differential 0.121 0.189 0.187

1973-1979 1983-1989 1992-1996

Difference in means 0.026 0.109 0.11

Unexplained 0.023 0.058 0.055


LABOUR FORCE SURVEY USER GROUP MEETINGROYAL STATISTICAL SOCIETYLondon 26 November 2004

INTRODUCTION

Britain’s Ethnic Minorities face two major problems in the labour market. to find employment having found employment their earnings tend to be lower compared

with similar White individuals

Three major factors may explain the above differences Ethnic Minorities may have lower levels of characteristics, such as schooling that increase

earnings and the probability of finding employment For any given characteristic earnings and the probability of employment may be

lower for Ethnic Minorities – this will be referred to as discrimination Thirdly, whilst all Ethnic Minority groups may have experienced discrimination, their

response to it may have been different


Earlier work by the authors found that coefficient differences played the more important

role in explaining both wage and employment differentials.

Tony Blair in a recent government report (Cabinet Office 2003), however, has made it an

objective to eliminate discrimination, “though it is nearly 40 years since the first Race Relations

Act, it is clear that racial discrimination in the labour market still persists”. He set the goal,

“that in ten years’ time, ethnic minority groups should no longer face disproportionate barriers

to accessing and realising opportunities for achievement in the labour market”.

Estimating the level of discrimination against non-white ethnic minorities in Britain has been

complicated by the fact that many are immigrants who may be disadvantaged by poor command of language (Leslie and Lindley, 2001), overseas schooling (Blackaby et. al, 2002),

being less familiar with customs and having poorer access to jobs search networks

(Frijters et. al, 2003).

The implications being that as the proportion of non-white British born ethnic minorities

increases, so the position of ethnic minorities should improve.


An offsetting factor, however, is that as a result of discrimination or choice this group may

adopt a ‘taste for isolation’ (Blackaby et. al, 1999) or ‘oppositional identities’ (Battu et. al, 2003).

As a result measuring discrimination can be likened to the quest for the Holy Grail.

To attempt to get a handle on the size of discrimination, male British born ethnic minorities are

considered.

METHODOLOGY

As is conventional in research on wage discrimination, a human capital approach is adopted

and separate earnings functions are estimated for each ethnic group

Employment and wage differences are then decomposed into the amount due to characteristic

differences and how much is due to coefficient differences – the latter being attributed to discrimination.


We adopt the approach of Neumark (1988) and Oaxaca and Ransom (1994) which relates more

closely to the theoretical literature of Becker (1957) and Arrow (1972) than earlier decompositions.

(1)

(2)

(3)

(4)

* * *ˆ ˆ ˆ ˆ ˆln ln ( ) ( ) ( )w e w e w w e eE E x x x x

*ˆ ˆ ˆ(1 )w e

* * *ˆ ˆ ˆ ˆ ˆ ˆ ˆ( ) ( ) ( ) ( ) ( ) ( )w e w e w w w e e eI I P x P x P x P x P x P x

** *

*

ˆ)ˆ ˆ( ) ( )

ˆ( )

wk ek kk w e

w e

x xExp P x P x

x x


DATA The data are taken from the Office of National Statistics Labour Force Survey (LFS).

earnings information has been collected since 1992Q4. In this paper data from 1993Q4

to 2000Q4 are used, this results in sample of 1,463 non-white British born ethnic minorities. sample is restricted to economically active male employees.

The data reveal wide diversity in the data across ethnic groups 18.7 percentage point employment differential between whites and ethnic minorities 11.5% nominal earnings differential between whites and ethnic minorities ethnic groups are overly represented in the South-East and London where earnings

are higher and unemployment has been lower. ethnic minorities are younger and have higher qualifications. diversity also in industrial structure, marital status, job tenure, plant size and whether

one works in the public sector.


PROBIT RESULTS

A number of personal characteristics are found to be important in predicting unemployment probability of unemployment is clearly related to an individual’s age being higher for the young

and old. the presence of three or more children also increases the probability of unemployment of whites.

This is usually attributed to the work disincentive effects induced by the benefit system that links

benefit to family size. differences are observed in a number of other variables

PROBIT DECOMPOSITION

To complement the familiar decomposition approach matched samples (by age and region) are used

to compare groups using the propensity score approach first discussed by Rubin and Rosenbaum

(1983). A matched sub-sample of whites is generated – that satisfies the balancing condition tests

outlined by Becker and Ichino (2002)


To analyse whether it is differences in mean characteristics or differences in rewards to those

characteristics that determine differences in employment across ethnic groups, ethnic

employment, decompositions are presented in Table 1.

Employment differential is 18.7%, characteristics explain approximately 1/3 of the employment gap

The finding is consistent with research undertaken by Commission for Racial Equality

when submitting fabricated CVs for jobs which differed only be ethnic background. Pakistanis are the most disadvantaged group 24.6% points lower employment rate Majority of difference attributed to coefficient differences

As well as discrimination this finding is consistent with this group choosing to distance itself

from domestic culture even when they know this may well reduce their chances of employment.

Light can be cast on this issue by comparing Indians with Pakistanis. Characteristics explain nearly three-quarters of the employment difference, however,

5.4% points remains unexplained This may reflect a taste for isolation


DECOMPOSITIONS

To analyse whether it is differences in mean characteristics or differences in rewards to these

characteristics that determine differences in earnings across ethnic groups, ethnic earnings

decompositions are presented in Table 2.

wage differential is 11.5%, characteristics now explain 60% of the wage differential

concentration of ethnic minorities in higher earnings regions would suggest their earnings

should be 7% higher than whites. largest raw earnings difference (16%) is found between whites and blacks

the earnings gap for Indians and Pakistanis is much smaller and even marginally favours Indians

characteristics favour Asian groups with qualifications in particular suggesting earnings

should be higher

Indians/Pakistanis decomposition reveals two thirds of 19% earnings gap explained by characteristics – 6.6% coefficient effect consistent with greater taste for isolation and oppositional identities


CONCLUSION

Findings support the work of Borjas (1994) who stated for the US that “ethnicity matters and it

matters for a very long time”. ethnic differences in the labour market cannot be explained solely as a characteristics problem

Such generalizations about the attributes of the ethnic minority populations can reinforce stereotyping,

which may result in the populations being excluded from the most remunerative occupations

and excuse governments from taking appropriate policy initiatives in this area.

The labour market in Britain has performed well since 1993 (unemployment fallen from 10.6% to 5.0%).


Britain’s ethnic minorities should have benefited in two ways: increasing proportion of British born who ought to have advantages over immigrants ethnic disadvantage typically hypercyclical with disadvantage falling disproportionately

in a buoyant labour market

For specific British born ethnic groups and we highlight blacks and Pakistanis, employment

and earnings disadvantage remains particularly severe. This may partly reflect a taste for isolation,

rather than just the consequence of discrimination.

The ten-year objective of estimating labour market differences will be extremely challenging on

the basis of these findings and may require additional discrimination legislation as well as

policies that encourage certain ethnic groups to engage more fully with the dominant culture.

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