Dr Yaojun LiReader in Sociological Analysis

Department of SociologyBirmingham University

Email: y.li.3@bham.ac.ukTel: 0121-4158625

Professor Anthony HeathDepartment of Sociology

Oxford UniversityEmail: anthony.heath@nuffield.ox.ac.uk

Labour market trajectories of minority ethnic groups

in Britain: 1972-2005 For ESRC/UPTAP Conference, LGA, 28 Nov. 2006

(ESRC RES-163-25-0003)Project website:http://www.uptap.net/project17.html

2

Abstract There has been a continuous increase in the proportion of minority ethnic groups in the general population in Britain and, since 1991, a lot of research has also been done on ‘ethnic penalties’ in the labour market. However, most of the research used data at a snapshot, or over highly aggregated ethnic categories, and no research has been able to trace the trajectories of the minority ethnic groups in the last three decades. This research aims to fill in the gap by using all the data in the General Household Survey and the Labour Force Survey in the last 34 years (1972-2005). We standardized all the key variables on ethnicity, employment status, social class, income, marital status, hours of work, number of dependent children, educational qualifications, health conditions etc. We differentiated nine ethnic groups. With this, we can then trace the trajectories of the different ethnic groups in each of the 34 years in terms of employment, unemployment, inactivity, class, income, etc. and that for men and for women separately.

3

Our findings show that White Other men have always been doing better than White British men, that White Irish men were severely disadvantaged in the first period but have caught up with the White British men; that Black Caribbean men have made remarkable progress in gaining access to the professional managerial positions; that Indian men have almost always been doing as well as the White British men, and that Pakistani/Bangladeshi men have been quite entrepreneurial at seeking self-employment in the last two decades. Actually, even though Pakistani/Bangladeshi men are still behind the other groups in terms of some key indicators, they are doing significantly better now than in the earlier periods and their second generation have been doing significantly better than their first generation. Women’s profiles are similar but the differences among different ethnic groups among women are much smaller than among men, with the exception that Pakistani-Bangladeshi women are overwhelmingly economically inactive throughout the period covered. On the other hand, all 2nd generation South Asian women, just as in the case of their men, have been doing significantly better than their first generation counterparts. Income differences, for both sexes, are more marked amongst different ethnic groups than between the minority and the majority (White British) groups. While the findings from this research have obvious academic interest, the policy implications are also self-evident. This research is supported by the ESRC grant on ‘Socio-economic position and political support of the BMEs in Britain (1971-2004), ESRC (RES-163-25-0003).

4

Aims:• To conduct a systematic research on the labour market positions and

political orientations of the Minority Ethnic Groups (MEGs) in Britain by analysing harmonized variables on ethnicity, socio-economic position and political orientation from the GHS (1972-2005), LFS (1975-2005), BES (1974-2005), BSA (1983-2004).

• To compare inter- and intra- generational experiences of the MEGs both amongst themselves and between them and the White charter population.

• With regard to the positions in the labour market, we shall focus on employment status, self-employment, occupational attainment, and earnings from paid work.

• With regard to political orientations, we shall examine political participation, political orientation and party support of the MEGs.

• From these comparisons, we wish to assess the extent and nature of ‘ethnic penalties’, particularly those by the second generation, to provide evidence for human capital and social capital theories on ethnic disadvantage, and to explore the extent to which socio-economic integration of the MEGs is matched by their socio-political integration.

5

Research on ethnic disadvantages-- where academic and policy interests converge

• Academic interests, esp. since 1991 SAR• The 1965 Race Relations Act, which made discrimination in public

places unlawful, but excluding employment and housing• The 1968 Race Relations Act, which made it unlawful to

‘discriminate on grounds of colour, race, or ethnic or national origins in recruitment, training, promotions, dismissals, and terms and conditions of employment’ (Layton-Henry, 1985)

• The 1976 Race Relations Act, which extended the definition of discrimination to include indirect discrimination

• The 2000 Race Relations (Amendment) Act, placing a general duty on public authorities to eliminate unlawful discrimination

• It is a government 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,’ says Tony Blair and he sets 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’ (Cabinet Office, 2003).

6

Distributions of Ethnic Groups in Britain 1972-2005

Ethnic | groups: | COT9 | Freq. Percent Cum. ------------+----------------------------------- 1. Wh Brit | 4,263,444 85.66 85.66 2. Wh Irish | 42,554 0.85 86.51 3. Wh Other | 119,353 2.40 88.91 4. B Car | 39,239 0.79 89.70 5. B Afr | 21,021 0.42 90.12 6. Indian | 70,464 1.42 91.53 7. Pak/Bang | 57,512 1.16 92.69 8. Chinese | 10,967 0.22 92.91 9. Other | 86,603 1.74 94.65 . | 266,265 5.35 100.00 ------------+----------------------------------- Total | 4,977,422 100.00

About 450k MEGs

7

Ethnic distribution by year: Men(16-64)+Women(16-59)

| Ethnic groups: COT9 year | 1. Wh Bri 2. Wh Iri 3. Wh Oth 4. B Car 5. B Afr 6. Indian 7. Pak/Ba 8. Chines 9. Other | Total -----------+---------------------------------------------------------------------------------------------------+---------- 1972 | 18,786 310 260 149 92| 213 70 24| 878 | 20,782 1973 | 18,657 330 302 184 75| 234 112 37| 909 | 20,840 1974 | 17,109 318 286 145 79| 230 98 34| 702 | 19,001 1975 | 19,046 329 292 218 75| 274 72 30| 729 | 21,065 1976 | 18,606 298 275 174 99| 307 87 34| 866 | 20,746 1977 | 16,641 280 269 194 111 270 55 32| 862 | 18,714 1978 | 16,418 255 254 177 123 367 106 0| 895 | 18,595 1979 | 15,931 266 258 191 116 342 107 0| 768 | 17,979 1980 | 16,388 244 237 238 151 388 95 0| 750 | 18,491 1981 | 16,890 253 271 221 155 445 130 0| 819 | 19,184 1982 | 14,260 191 196 173 107 413 96 0| 719 | 16,155 1983 | 127,444 1,699 3,799 1,431 236 2,079 972 268 1,153 | 139,081 1984 | 97,473 1,216 2,895 1,066 209 1,575 779 202 712 | 106,127 1985 | 100,471 1,222 2,605 1,186 231 1,328 815 240 804 | 108,902 1986 | 100,822 1,230 2,674 1,082 211 1,542 810 218 955 | 109,544 1987 | 99,226 1,218 2,884 1,155 235 1,591 820 266 959 | 108,354 1988 | 99,695 1,365 2,966 1,040 263 1,624 888 302 1,112 | 109,255 1989 | 99,893 1,350 3,066 1,086 291 1,576 980 266 959 | 109,467 1990 | 96,915 1,175 2,777 869 262 1,496 932 276 1,054 | 105,756 1991 | 95,747 1,165 2,699 871 310 1,596 1,089 300 1,124 | 104,901 1992 | 96,874 1,035 3,032 931 449 1,867 1,172 341 1,080 | 106,781 1993 | 143,824 1,613 4,640 1,474 642 2,702 1,776 465 1,748 | 158,884 1994 | 139,607 1,533 4,540 1,427 714 2,670 1,801 462 1,839 | 154,593 1995 | 139,753 1,512 4,530 1,339 740 2,496 1,814 403 1,890 | 154,477 1996 | 140,199 1,504 4,680 1,300 824 2,465 1,898 406 1,944 | 155,220 1997 | 124,306 1,263 4,608 1,136 783 2,223 1,714 446 1,921 | 138,400 1998 | 132,935 1,264 5,113 1,267 841 2,557 1,911 466 2,122 | 148,476 1999 | 119,279 1,013 5,031 1,058 775 2,234 1,865 392 2,012 | 133,659 2000 | 68,570 627 2,324 683 566 1,357 1,194 263 1,356 | 76,940 2001 | 69,668 575 2,876 872 704 1,529 1,388 299 1,455 | 79,366 2002 | 67,383 585 2,749 736 689 1,564 1,409 348 1,701 | 77,164 2003 | 67,731 504 2,780 716 791 1,575 1,508 351 1,844 | 77,800 2004 | 63,883 445 2,722 672 812 1,488 1,474 427 1,796 | 73,719 2005 | 52,830 379 2,609 573 672 1,348 1,261 330 1,721 | 61,723 -----------+---------------------------------------------------------------------------------------------------+---------- Total | 2,533,260 28,566 81,499 26,034 13,433 45,965 31,298 7,928 42,158 | 2,810,141

8

Distribution of ethnicity by sex by period

1972-1980 1981-1996 1997-2005 Men Women Men Women Men Women 1. White British 2. White Irish 3. White Other| 4. Black Caribbean 5. Black African 6. Indian 7. Pakistani/Bangladeshi 8. Chinese 9. Other

80,111 1,261 1,113 810 503 1,372 487 101 5,067

77,471 1,369 1,320 860 418 1,253 315 90 2,292

827,044 9,671 22,736 7,809 2,945 13,986 8,657 2,171 9,738

782,049 9,610 25,518 8,842 2,934 13,479 8,115 2,244 9,133

388,923 3,266 14,299 3,476 3,073 7,904 6,796 1,581 7,559

377,662 3,389 16,513 4,237 3,560 7,971 6,928 1,741 8,369

Total 90,825 85,388 904,757 861,924 436,877 430,370

9

Defining generation Generation: | W British or | MEG (f born| sex +age to UK) | 1. male 2. female | Total -------------+----------------------+---------- W British | 1,296,078 1,237,182 | 2,533,260 G2:UKb|fb<=5 | 50,271 49,141 | 99,412 G1.5:fb&6-16 | 23,130 20,386 | 43,516 G1:fb&>=17 | 62,980 70,973 | 133,953 -------------+----------------------+---------- Total | 1,432,459 1,377,682 | 2,810,141

10

020

40

60

80

10

0P

erc

ent

Time of arrival to Britain

Source: Pooled data of GHS/LFS.

UK born Before 19711972-1980 1981-1996

1997-2005

11

Generational status of MEGs Ethnic: | Generation: W British or MEG(f born + age to UK) COT9 | W British G2:UKb|fb G1.5:fb&6 G1:fb&>=1 | Total ------------+--------------------------------------------+---------- 1. Wh Brit | 100.00 0.00 0.00 0.00 | 100.00 2. Wh Irish | 0.00 20.63 20.91 58.46 | 100.00 3. Wh Other | 0.00 33.73 14.59 51.68 | 100.00 4. B Car | 0.00 52.14 17.27 30.59 | 100.00 5. B Afr | 0.00 24.25 12.25 63.51 | 100.00 6. Indian | 0.00 32.93 18.56 48.51 | 100.00 7. Pak/Bang | 0.00 33.19 19.53 47.28 | 100.00 8. Chinese | 0.00 20.22 18.39 61.39 | 100.00 9. Other | 0.00 52.36 8.08 39.56 | 100.00 ------------+--------------------------------------------+---------- Total | 90.15 3.54 1.55 4.77 | 100.00

12

Separate analysison employment and class

Part 1: Men aged 16-64

13

020

40

60

80

10

0P

erc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Men aged 16-64 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being employed

14

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Men aged 16-64 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being unemployed

15

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Men aged 16-64 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being economically inactive

16

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Men aged 16-64 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being in the service class

17

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Men aged 16-64 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being in the semi/unskilled working class

18

020

40

60

80

10

0P

erc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Men aged 16-64 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being employed

19

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Men aged 16-64 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being unemployed

20

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Men aged 16-64 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being economically inactive

21

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Men aged 16-64 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being in the service class

22

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Men aged 16-64 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being in the semi/unskilled working class

23

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White IrishWhite Other Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Men aged 16-64 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being self-employed

24

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White IrishWhite Other Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Men aged 16-64 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being middle-class (salariat&self-employment)

25

Table 1 Logistic regression coefficients on access to the service class: men aged 16-64 Model 1 Model 2 Model 3 Ethnicity White British (ref) 0 0 0 White Irish -.281*** .009 .009 White Other .519*** .567*** .567*** Black Caribbean -.699*** -.444*** -.885*** Black African .282*** -.222*** .438*** Indian .027 -.124*** .043 Pakistani/Bangladeshi -.794*** -.538*** -.675*** Chinese .089* .001 .349 Other .061*** .232*** .233*** Age Age (=age/10) 1.841*** 1.841*** Age squared -.195*** -.195*** Marital Status Married (ref) 0 0 Separated/divorced/widowed -.289*** -.289*** Single -.104*** -.104*** Education Degree+ 3.811*** 3.811*** Professional below degree 2.623*** 2.629*** A Levels 1.117*** 1.117*** O Levels 1.276*** 1.275*** Primary or no qualification (ref) 0 0 Number of children under 16 in HH -.034*** -.033*** Period Earlier (1972-1980) (ref) 0 0 Middle (1981-1996) .133*** .139*** Later (1997-2005) -.035*** -.034** Interaction effects Black Caribbean in middle period .354* Black Caribbean in later period .636*** Black African in middle period -.714*** Black African in later period -.771*** Indian in middle period -.260** Indian in later period -.061 Pakistani/Bangladeshi in middle period .126 Pakistani/Bangladeshi in later period .157 Chinese in middle period -.445 Chinese in later period -.258

Constant -.648*** -5.856*** -5.859*** Pseudo R2 .003 .244 .244 N 1,147,239 1,019,766 1,019,766

Notes

1. * p<0.05, ** p<0.01, *** p<0.001. Source: The pooled data of GHS/LFS.

26

Table 2 Logistic regression coefficients of generation effects on access to the service class: men aged 16-64 White

Irish White Other

Black Caribbean

Black African

Indian Pakistani/ Bangladeshi

Chinese

No control 2nd Generation .128* -.100*** .909*** -.009 .357*** .356*** .041 1.5th Generation -.312*** -.092** .569*** -.182 .089* -.279*** -.325*** 1st Generation (ref) -.895*** -.079*** -1.928*** -.347*** -.744*** -1.538*** -.456***

With control 2nd Generation -.095 -.326*** .345*** .162 .119* .394*** -.018 1.5th Generation -.259*** -.409*** -.175 .099 -.117* -.129 -.560*** 1st Generation (ref) 0 0 0 0 0 0 0

Age Age (=age/10) .913*** 2.225*** 2.066*** 1.871*** 1.517*** 1.869*** 2.077*** Age squared -.119*** -.258*** -.258*** -.226*** -.172*** -.199*** -.246***

Marital Status Married (ref) 0 0 0 0 0 0 0 Separated/divorced/widowed -.233* -.389*** -.236 -.456** -.013 -.345 -.261 Single .142* -.018 -.054 -.276** .015 .067 -.518***

Education Degree+ 3.814*** 2.617*** 3.976*** 2.468*** 3.254*** 3.192*** 3.227*** Professional below degree 2.866*** 1.601*** 2.671*** 1.589*** 2.109*** 2.451*** 2.281*** Professional below degree .792*** .382*** 1.325*** .641*** 1.102*** 1.281*** 1.209*** No higher qualification .955*** .279*** 1.125*** .046 .652*** .734*** .568** No higher qualification (ref) 0 0 0 0 0 0 0

Number of children under 16 in HH -.083*** -.045** -.059 -.041 -.173*** -149*** -.331*** Constant -3.105*** -4.953*** -6.318*** -4.881*** -4.626*** -6.141 -5.184*** Pseudo R2 .239 .185 .243 .200 .275 .262 .294 N 9,127 27,508 7,107 3,776 15,651 8,250 2,103

27

Separate analysison employment and class

Part 2: Women aged 16-59

28

020

40

60

80

10

0P

erc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Women aged 16-59 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being employed

29

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Women aged 16-59 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being unemployed

30

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Women aged 16-59 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being economically inactive

31

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Women aged 16-59 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being in the service class

32

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White Irish

White Other

Women aged 16-59 in Britain

Source: Pooled data of GHS/LFS.

Probablity of being in the semi/unskilled working class

33

020

40

60

80

10

0P

erc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Women aged 16-59 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being employed

34

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Women aged 16-59 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being unemployed

35

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Women aged 16-59 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being economically inactive

36

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Women aged 16-59 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being in the service class

37

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Women aged 16-59 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being in the semi/unskilled working class

38

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White IrishWhite Other Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Women aged 16-59 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being self-employed

39

020

40

60

80

Perc

ent

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White IrishWhite Other Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Women aged 16-59 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Probablity of being middle-class (salariat&self-employment)

40

Table 1 Logistic regression coefficients on access to the service class: women aged 16-59 Model 1 Model 2 Model 3 Ethnicity White British (ref) 0 0 0 White Irish .249*** .367*** .369*** White Other .561*** .481*** .480*** Black Caribbean .233*** .260*** .636*** Black African .211*** -.185*** .559*** Indian -.161*** -.216*** .112 Pakistani/Bangladeshi -.317*** -.117* .121 Chinese .299*** -.164** -.105 Other .153*** .098*** .098*** Age Age (=age/10) 2.173*** 2.175*** Age squared -.265*** -.265*** Marital Status Married (ref) 0 0 Separated/divorced/widowed .009 .009 Single .029*** .029*** Education Degree+ 0 0 Professional below degree 3.433*** 3.433*** Professional below degree 3.006*** 3.005*** No higher qualification 1.317*** 1.316*** No higher qualification (ref) .844*** .843*** Number of children under 16 in HH -.279*** -.279*** Period Earlier (1972-1980) (ref) 0 0 Middle (1981-1996) .386*** .389*** Later (1997-2005) .192*** .206*** Interaction effects Black Caribbean in middle period -.336** Black Caribbean in later period -.507*** Black African in middle period -.829*** Black African in later period -.809*** Indian in middle period -.435*** Indian in later period -.243* Pakistani/Bangladeshi in middle period .043 Pakistani/Bangladeshi in later period -.439 Chinese in middle period -.078 Chinese in later period -.045

Constant -.811*** -6.148*** -6.164*** Pseudo R2 .002 .245 .245 N 962,849 866,168 866,168 Notes

1. * p<0.05, ** p<0.01, *** p<0.001. Source: The pooled data of GHS/LFS.

41

Table 2 Logistic regression coefficients of generation effects on access to the service class: women aged 16-59 White

Irish White Other

Black Caribbean

Black African

Indian Pakistani/ Bangladeshi

Chinese

No control 2nd Generation -.374*** -.149*** -.047 .066 .669*** .357*** -.101 1.5th Generation -.497*** -.152*** .086 -.014 .385*** -.008 -.303* 1st Generation (ref) -.392*** -.179*** -.572*** -.615*** -1.284*** -1.326*** -.443***

With control 2nd Generation -.272*** -.221*** -.265** -.021 .401*** .282* -.066 1.5th Generation -.249*** -.324*** -.195* .119 .277*** -.041 -.123 1st Generation (ref) 0 0 0 0 0 0 0

Age Age (=age/10) 1.476*** 2.760*** 2.348*** 1.934*** 2.284*** 3.080*** 2.556*** Age squared -.214*** -.347*** -.286*** -.224*** -.273*** -.356*** -.283***

Marital Status Married (ref) 0 0 0 0 0 0 0 Separated/divorced/widowed -.124 -.079 -.089 -.354** -.062 -.131 -.120 Single .015 .059 -.070 -.084 .179** .322** -.024

Education Degree+ 3.097*** 2.238*** 3.234*** 2.560*** 3.162*** 2.989*** 3.930*** Professional below degree 3.179*** 1.869*** 3.043*** 2.333*** 2.794*** 2.139*** 2.574*** Professional below degree 1.012*** .493*** 1.276*** .787*** 1.442*** 1.417*** 1.114*** No higher qualification .671*** .032 .858*** .289* .785*** .775*** .653** No higher qualification (ref) 0 0 0 0 0 0 0

Number of children under 16 in HH -.299*** -.238*** -.121*** -.133*** -.174*** -115** -.188** Constant -3.338*** -5.686*** -5.839*** -5.343*** -6.628*** -8.120*** -6.916*** Pseudo R2 .273 .172 .247 .213 .258 .228 .263 N 8,842 26,774 8,313 3,410 11,664 3,234 2,031

42

Separate analysison income

Part 1: Men aged 16-64

43

010

020

030

040

050

060

0W

eekl

y e

arn

ings

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

Men Women

Men aged 16-64 and women aged 16-59 in Britain

Source: Pooled data of GHS/LFS.

Gross weekly pay from the labour market

44

010

020

030

040

050

060

0W

eekl

y e

arn

ings

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White IrishWhite Other Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Men aged 16-64 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Gross weekly pay from the labour market

45

010

020

030

040

0W

eekl

y e

arn

ings

1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005Year

White British White IrishWhite Other Black CaribbeanBlack African Indian

Pakistani/Bangladeshi Chinese

Women aged 16-59 in Britain

Note: The sample sizes for Chinese too small before 1983.

Source: Pooled data of GHS/LFS.

Gross weekly pay from the labour market

46

Heckman’s selection models

yj = xjβ + u1j regression equation

DV not always observed. The DV for observation j is observed if

zjγ + u2j >0 regression equation

corr(u1, u2) = ρ

Thus, ln(weekpay) = β0 + β1ethnicity + β2educ + β3class + β4age + u1

And the selection model: γ0 + γ1ethnicity + γ2educ + γ3class + γ 4age + γ5marital + γ6children + u2

47

Heckman’s two-step selection model on log weekly earnings for men aged 16-64 in Britain (1972-2005) | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- White Irish | -.0226515 .0143651 -1.58 0.115 -.0508066 .0055036 White Other | .2772072 .0084119 32.95 0.000 .2607201 .2936942 Black Carib | -.075819 .0155914 -4.86 0.000 -.1063777 -.0452603 Black Afric | -.2183353 .0200255 -10.90 0.000 -.2575846 -.179086 Indian | -.0177954 .0111127 -1.60 0.109 -.0395759 .0039851 Pakistani/B | -.0502844 .0157609 -3.19 0.001 -.0811751 -.0193937 Chinese | -.1165143 .0326443 -3.57 0.000 -.1804959 -.0525327 Other | -.0959015 .0117087 -8.19 0.000 -.1188501 -.0729528 Once married | .0732342 .0056613 12.94 0.000 .0621382 .0843302 single | -.1096358 .0034913 -31.40 0.000 -.1164785 -.102793 ndpch16 | -.0641969 .0013704 -46.84 0.000 -.0668828 -.0615109 age/10 | 1.668707 .0073318 227.60 0.000 1.654337 1.683077 (age/10)sq | -.1935162 .0009172 -210.99 0.000 -.1953138 -.1917186 Degree+ | .8215989 .0047615 172.55 0.000 .8122666 .8309312 Professional | .5366704 .0052335 102.54 0.000 .5264129 .5469279 A Level | .6068442 .0036914 164.40 0.000 .5996092 .6140791 O Level | .4314537 .0040309 107.04 0.000 .4235533 .4393541 Salariat | .3685712 .0042709 86.30 0.000 .3602003 .376942 Routine NM | -.0413229 .005254 -7.87 0.000 -.0516205 -.0310253 Petty bour | -1.86633 .0146461 -127.43 0.000 -1.895035 -1.837624 Skilled M | .1313732 .0038681 33.96 0.000 .1237919 .1389545 _cons | 1.320987 .0137963 95.75 0.000 1.293947 1.348028 -------------+---------------------------------------------------------------- rho | 0.45808 sigma | .8562952 lambda | .39225068 .0031473 ------------------------------------------------------------------------------

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Main conclusions on labour market situations of men aged 16-2005 in Britain

• Among the invisible MEGs, Irish men were disadvantaged in the earlier period but caught up with the White British from the 1990s onwards, and the White Others almost always had favourable positions, in terms of access to the professional-managerial positions, avoiding the semi and unskilled manual jobs, and unemployment. The employment rates of the Irish men are still lower than those of the White British men in recent years, though.

• Among the visible MEGs, Black Africans were generally more likely to be in professional-managerial positions than the White British men, and the Indians showed no major differences from the White British. Black Caribbean and Pakistani/Bangladeshi men were less likely to be in the professional-managerial positions but the former were making much steady progress than the latter over the 34-year period. The last two groups were also more likely to face unemployment (and Black Africans in the 1990s, too) and to be in unskilled working class positions.

• Pakistani/Bangladeshi men were keen to take self-employment since early 1980s onwards and are now even more likely to be self-employed than the Chinese men. If both salariat and self-employment are counted, as in the conventional sense, as middle class groups, then Pakistani-Bangladeshi men are somewhat less disadvantaged than men of Black Caribbean origins.

• Black Caribbean and Pakistani/Bangladeshi men faced a lot of difficulties in the earlier period but were doing better in later periods. The 2nd generation men from Black African, Indian, Pakistani and Bangladeshi origins were doing better than their 1st generation counterparts in terms of gaining access to the professional-managerial positions.

• The overall pattern is one of convergence, whether we look at gaining access to the advantaged professional-managerial positions, or in avoidance of semi/unskilled working class positions or unemployment. This said, there are still marked differences between the MEGs and the White British men, especially in terms of employment rates.

• The overall balance of the data suggests that the White Others and Indians were the most successful groups in the labour market with the Black Caribbeans and Pakistani/Bangladeshis being disadvantaged.

• Even though several ethnic minority groups are still disadvantaged, there has been remarkable progress at reducing ethnic disadvantages in British society in the past 3 decades. The government Race Relations Acts (1965, 1968, 1976, 2000) seem to have had some notable impacts.

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My writings on the labour market• Li, Y. and Heath, A. (2006) ‘Generation, education and labour market attainment of minority ethnic

groups in Britain: A tale of 35 years’, ESRC: Britain Today.• Li, Y. and Heath, A.(2006) ‘Ethnic minority men in British labour market (1972-2005)’, International

Journal of Sociology and Social Policy. Li, Y. (2006) Assessing Data Needs and Gaps for Researching Ethnic Minority Entrepreneurship, for the

ESRC/DTI/CRE• O’Leary, R. and Li, Y. (2006) ‘Beyond Unemployment: Further differences in Catholic and Protestant

performance in the Northern Ireland labour market’, Belfast: Conference Proceedings on Equality and Social Inclusion, Working Paper 10.

• Li, Y. and Pollert, A. (2006) ‘The unorganized worker in WERS 2004: socio-demographic attributes, workplace characteristics and work-life experience’, research paper commissioned by DTI and RSS.

• Li, Y. (2005) ‘Exploring income differentials: a comparison between human and social capital approaches’, presentation at the ESDS Government Research Conference, British Academy, 4 Nov. 2005: http://www.ccsr.ac.uk/esds/events/2005-11-04/li.doc

• Li, Y. (2005) ‘Social capital, ethnicity and the labour market’, Proceedings of International Conference on Engaging Community, http://engagingcommunities2005.org/abstracts/Li-Yaojun-final.pdf

• Garrat, D. and Li, Y. (2005) ‘The foundations of experimental/empirical research methods’, in B. Somekh and C. Lewin (eds). Research Methods in the Social Sciences, London: Sage, pp: 198-206.

• Li, Y. and R. O’Leary (2004) ‘Progress in reducing Catholic disadvantages in Northern Ireland’, in Anthony Heath and Sin Yi Cheung (eds), Ethnic Differences across Countries, Oxford: OUP.

• Purdam, K. and Li, Y. with Brown, M. and Wathan, J. (2003) A profile of the housing and socio-economic circumstances of black and minority ethnic people in Wales, Cardiff: National Assembly of Wales.

• Li, Y. (2002) ‘Falling off the ladder? Professional and managerial career trajectories and unemployment experiences’, European Sociological Review, 18(3): 253-70.

• Li, Y., Bechhofer, F., McCrone, D., Anderson, M. and Stewart, R. (2002) ‘A Divided Working Class? Planning and Career Perception in the Service and Working Classes’, Work, Employment and Society, 16(4): 617-636.

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My other writings on social capital• Li, Y. and D. Marsh (2006) ‘New forms of political participation: searching for expert

citizens and everyday makers’, under review.• Li, Y., Savage, M. and Warde, A. (2006) ‘Civic engagement, social network and

social stratification in the UK: a random effects analysis’, under review.• Savage, M., Li, Y. and Tampubolon, G. (2006) ‘Rethinking the politics of social

capital: challenging Tocquevillian perspectives’, in Edwards, R. Franklin, J. and Holland, J. (eds), Social Capital: Concepts, policy and practice, London: Sage.

• Li, Y. (2006) ‘Social capital, social exclusion and wellbeing’, in Angela Scriven and Sebastian Garman (eds), Public Health: Social context and action, London: Sage.

• Li, Y. (2005) ‘Social capital, ethnicity and the labour market’, Proceedings of International Conference on Engaging Community, jointly organized by the United Nations and the Government of the State of Queensland in Australia. http://engagingcommunities2005.org/abstracts/Li-Yaojun-final.pdf

• Li, Y., Pickles, A. and Savage, M. (2005) ‘Social Capital and Social Trust in Britain’, European Sociological Review, 21(2): 109-23.

• Li, Y., Savage, M. and Pickles, A. (2003) ‘Social Capital and Social Exclusion in England and Wales (1972-1999)’, British Journal of Sociology, 54(4): 497-526.

• Li, Y., Savage, M. and Pickles, A. (2003) ‘Social Change, Friendship and Civic Participation’, Sociology Research Online

• Li, Y., Savage, M., Tampubolon, G., Warde, A. and Tomlinson, M. (2002) ‘Dynamics of social capital: trends and turnover in associational membership in England and Wales: 1972-1999’, Sociological Research Online, Vol. 7, No. 3.

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A Comparison between the GHS/LFS and SARs in 1991 and 2001 (for men aged 16-64 and women aged 16-59 resident in England and Wales) 1991 2001 GHS/LFS SARs GHS/LFS SARs Sex Male 51.4 51.7 50.6 51.5 Female 48.6 48.3 49.4 48.5 Marital status Married 68.0 61.4 53.3 49.1 Once married 7.3 8.3 12.1 12.8 Never married 24.7 31.3 34.7 38.1 Ethnicity White 94.5 93.9 91.5 91.1 Black Caribbean 0.9 1.2 1.2 1.2 Black African 0.3 0.4 1.0 1.0 Indian 1.7 1.9 2.1 2.2 Pakistani/Bangladeshi 1.1 1.1 1.9 1.9 Chinese 0.3 0.3 0.4 0.5 Other 1.2 1.2 2.0 2.2 Employment status Working 72.6 69.1 73.5 71.9 Unemployed 6.9 8.3 2.7 4.2 Non-employed 20.7 22.6 22.7 23.9 Class Salariat 33.7 29.8 36.2 38.5 Routine non-manual 19.1 22.4 13.3 13.1 Petty bourgeoisie 10.4 9.0 9.1 9.6 Skilled manual 16.4 15.9 27.8 16.3 Semi-unskilled manual 20.3 22.9 13.7 12.6 Mean hours of work per week 35.7 36.3 36.8 37.5 N 93,561 560,650 74,444 1,003,205