Understanding Trends in Occupational Sex Segregation By Daniel Guinea-Martin Advanced Centre for...

Understanding Trends in Occupational Sex Segregation

ByDaniel Guinea-Martin

Advanced Centre for Scientific Research, Spain(formerly at the Office for National Statistics, UK)

Presented at the Research Methods Festival, Oxford University

1st July 2008

http://www.esrc.ac.uk/

Introduction: Aims and scopes

• Substantive scope: To study occupational sex segregation / occupational mobility in the 1990s

• How? Complementing Census-based indices of segregation (Blackwell and Guinea-Martin 2005) with longitudinal research of one cohort born in the late 1950s:

• NCDS

• A similar cohort from the ONS Longitudinal Study


Introduction: Aims and scopes

• Methodological aims:

– To assess the effect of attrition on representativenes

– To assess ‘founding’ assumption


LS Structure Core Table

Contains basic variables for ‘time constant’ characteristics (sex, decade of entry to or exit from the dataset…)

Around 1 million individuals

Core Table

Contains basic variables for ‘time constant’ characteristics (sex, decade of entry to or exit from the dataset…)

Around 1 million individuals

Census-based tables

Four time points / Four tables: 1971-1981-1991-2001

Around 500,000 individuals each year

Census-based tables

Four time points / Four tables: 1971-1981-1991-2001

Around 500,000 individuals each year

Events tables

Continuous since 1971 until present

Examples:

Births to sample women

Infant Deaths

Widow(er)hoods

Cancer registrations

Deaths….

Events tables

Continuous since 1971 until present

Examples:

Births to sample women

Infant Deaths

Widow(er)hoods

Cancer registrations

Deaths….

Hypothetical example of data from the ONS Longitudinal Study

core number 1 Census-based variables (for example, of 1991 and 2001)

core number 1 Variables related to birth of 1st son in 1992

core number 1 Variables related to birth of 2nd son in 1996

core number 2 Census-based variables

core number 3 Census-based variables

core number 3 Variables related to emigration from the LS

core number 4… ….

Key programming tool:Indexing commands, e.g. [i], [i+1]…


NCDS Structure

NCDS Sweep 6 (2000)

NCDS Sweep 6 (2000)

NCDS Sweep 5 (1991)

NCDS Sweep 5 (1991)

Work-histories database (from 1974 onwards)

- Combines restrospective information from NCDS5 & NCDS6

Work-histories database (from 1974 onwards)

- Combines restrospective information from NCDS5 & NCDS6

• Key programming tool: loops, e.g.- foreach i in 1/25 {do whatever} -

Hypothetical example of data from NCDS data

Start Job1…… Start Job 25 End Job 1…… End Job 25

Member 1 ………………………………………………………………….

Member 2 ………………………………………………………………….

Member 3 ………………………………………………………………….

Member 4 ………………………………………………………………….

Member 5 ………………………………………………………………….

…… …………………………………………………………………


A methodological auto-biography

• The challenge: 1st serious research experience with complex and ‘messy’ longitudinal data

• Easy to be surprised. Examples:– Supposedly time-invariant variables like sex or

ethnicity might actually change across waves.– Easy to mistake ‘past’ variables for ‘current’ variables

in life histories.– Easy to forget harmonising variables which categories

change over time.– Different ways of storing variables in different tables

and across time (e.g., numeric, string with trailing spaces…)


Survival kit

• Read the documentation very closely, particularly the questionnaires.

• Learn serious programming in one or two software packages: SPSS, Stata, R…

• Keep the syntax of all the transformations you operate on the data in strict sequence.

• In the syntax include comments on what you are doing and what you have found out about the data

Occupational sex segregation: Standardised Gini indices for the period 1971-1981

1971 1981 1991 1996 2001 2001 (CO70) (CO80) (SOC90) (SOC90) (SOC2000) (SOC90)

Census - - 0.78 - 0.69 -

LFS - - 0.76 0.75 0.72

ONS LS 0.81 0.80 0.77 - 0.70 0.72 (no person imp.)

Source: Blackwell, L. and D. Guinea-Martin (2005) ‘Occupational segregation by sex and ethnicity

in England and Wales, 1991 to 2001’, in Labour Market Trends, Vol. 113, No. 12, pp. 501-516

Occupational sex segregation in the NCDS & LS50s

1991 2000/1

Gini ID Gini ID Change

Gini Change

ID

NCDS 0.78

(0.76-0.79) 0.61

(0.59-0.63) 0.77

(0.76-0.79) 0.60

(0.58-0.62) -0.01 -0.01

LS50s 0.76

(0.75-0.77) 0.60

(0.58-0.61) 0.75

(0.74-0.76) 0.58

(0.57-0.59) -0.01 -0.02

Notes: Indices based on the 77 minor groups of SOC90, but coefficients standardized to 200 occupations (using the formulae presented in Blackburn and Jarman, 2005) Sources: Authors’ analysis. ONS Longitudinal Study and NCDS

What are these indices of segregation? Example: The Segregation Curve for NCDS 2000

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

Proportion of women

Pro

po

rtio

n o

f m

en

Integration Segregation

AB

Line of Perfect Integration

Distance=D

Gini=A/(A+B)

Male/female ratio

How to calculate the indices

Index of dissimilarity

Gini coefficient

||21

1

Mi

K

i

Fi ppD

||1

1 1

Mi

Fj

Mj

K

i

K

ij

Fi ppppG

Decomposing segregation: Theil’s index

• Theil’s entropy index of segregation (H) is a multi-group measure of segregation

• Allows the incorporation of various dimensions, for example employment status (full time vs. part time) or age groups

• Currently working on these dimensions to disaggregate the changes in occupational sex segregation during the 1990s

Theil’s entropy index of segregation

‘Entropy’ or diversity

Theil’s index

Decomposition of

Theil’s H

E

EET

t

H

k

ii

i

1

)(

cbcba

cbbcbca

cba

bcacba H

E

EQH

E

EH \

\\

\\

\\

\\\

n

r rr QQE

12

1log

Example: Decomposition of segregation among ISCO-88 occs in UK

Multigroup HComponent 0.298% share 100%

Male/Female HComponent 0.256% share 86%

Women full-time/part-time HComponent 0.044% share 14%

Index of DissimilarityMale/Female ID 0.58

Source: Table 3 in Elliott (2005)

Occupational sex segregation in the NCDS & LS50s

1991 2000/1

Gini ID Gini ID Change

Gini Change

ID

NCDS 0.78

(0.76-0.79) 0.61

(0.59-0.63) 0.77

(0.76-0.79) 0.60

(0.58-0.62) -0.01 -0.01

LS50s 0.76

(0.75-0.77) 0.60

(0.58-0.61) 0.75

(0.74-0.76) 0.58

(0.57-0.59) -0.01 -0.02

Notes: Indices based on the 77 minor groups of SOC90, but coefficients standardized to 200 occupations (using the formulae presented in Blackburn and Jarman, 2005) Sources: Authors’ analysis. ONS Longitudinal Study and NCDS

Occupational sex segregation for various quasi-cohorts in the 1990s

Gini coefficientsa Cohort born in 1991b 2001c Diff. 1927-1936 0.82 n/ad n/a 1937-1946 0.82 0.75 -0.07 1947-1956 0.81 0.74 -0.07 1957-1966 0.75 0.73 -0.02 1967-1976 0.72 0.66 -0.06 1977-1986 n/ae 0.60 n/a Overall index 0.78 0.69 -0.09 Notes: People of working age and in employment only. a Coefficients standardised to 200 occupations (using the formulae presented in Blackburn and Jarman 2005) b SOC90 – used 77 minor groups

c SOC2000 – used 81 minor groups

d Part of this quasi-cohort was above working age in 1991

e Part of this quasi-cohort was below working age in 1991 Sources: Author’s analysis. 100 per cent 1991 and 2001 Censuses of England and Wales.

Occupational movers and stayers

NCDS LS50s Men Women All Men Women All Mover 62.9 69 65.5 60.8 67.5 63.5 Stayer 37.1 31 34.5 39.2 32.5 36.5 Total 100 100 100 100 100 100 Notes: People of working age and in employment only. Sources: Author’s analysis. ONS Longitudinal Study and NCDS

Transitions across sex-typed occupations (occupational movers only)

Male transitions across sex-typed occupations (cell percentages)

NCDS LS50s 2001 sex types 2001 sex types

1991 Sex types Male Integrated Female Total Male Integrated Female Total Male 51.9 13.3 3.3 68.5 55.5 12.0 4.1 71.6 Integrated 13.6 8.1 2.3 23.9 11.6 6.6 2.3 20.5 Female 3.5 2.9 1.2 7.6 3.8 2.8 1.4 7.9 Total 68.9 24.3 6.8 100 70.8 21.4 7.8 100 Notes: Data based on occupational movers in employment both years only. Occupations classified into sex-types on the basis of one lookup table with percentage female derived from one 10 per cent sample of the 1991 Census (Hakim 1998). Sources: Authors’ analysis. ONS Longitudinal Study and NCDS

Female transition across sex-typed occupations (cell percentages)

NCDS LS50s 2001 sex types 2001 sex types

1991 Sex types Male Integrated Female Total Male Integrated Female Total Male 3.3 4.2 4.4 11.8 4.8 4.3 4.7 13.9 Integrated 3.7 11.2 13.6 28.5 4.9 9.0 13.3 27.1 Female 5.5 15.8 38.4 59.7 7.4 14.9 36.7 59.0 Total 12.6 31.1 56.3 100 17.1 28.2 54.7 100 Notes: Data based on occupational movers in employment both years only. Occupations classified into sex-types on the basis of one lookup table with percentage female derived from one 10 per cent sample of the 1991 Census (Hakim 1998).

Transitions across sex-typed occupations and non-work

Notes: All members of the LS50s longitudinal sample (1991-2001) included. Occupations classified into sex-types on the basis of one lookup table with percentage female derived from one 10 per cent sample of the 1991 Census (Hakim 1998). Sources: Authors’ analysis. ONS Longitudinal Study and NCDS

Female transitions across sex-typed occupations and non-work (cell percentages)

NCDS LS50s

2001 sex types 2001 sex types

1991 Sex types Male Integrated Female Nonwork Total Marginal diff. Male Integrated Female Nonwork Total Marginal

diff. Male 3.1 1.7 1.7 1.3 7.8 0.4 3.4 1.6 1.7 1.1 7.8 2.0 Integrated 1.5 8.9 5.4 2.4 18.2 3.7 1.8 7.4 4.8 2.4 16.3 2.5 Female 2.2 6.3 27.9 5.6 42.0 7.7 2.7 5.4 25.0 5.2 38.3 9.8 Nonwork 1.4 5.0 14.7 10.8 31.9 -11.8 1.9 4.5 16.5 14.7 37.7 -14.2 Total 8.2 21.9 49.7 20.1 100 9.7 18.9 48.0 23.4 100

Notes: All members of the LS50s longitudinal sample (1991-2001) included. Occupations classified into sex-types on the basis of one lookup table with percentage female derived from one 10 per cent sample of the 1991 Census (Hakim 1998). Sources: Authors’ analysis. ONS Longitudinal Study and NCDS

Male transitions across sex-typed occupations and non-work (cell percentages)

NCDS LS50s

2001 sex types 2001 sex types

1991 Sex types Male Integrated Female Nonwork Total Marginal diff. Male Integrated Female Nonwork Total Marginal

diff. Male 53.9 7.1 1.8 3.5 66.3 -0.1 52.9 6.0 2.1 4.5 65.4 -0.7 Integrated 7.3 10.4 1.2 0.8 19.7 0.2 5.8 8.9 1.1 1.3 17.1 0.2 Female 1.8 1.6 2.2 0.3 5.9 -0.2 1.9 1.4 2.6 0.5 6.4 0.1 Nonwork 3.3 0.8 0.6 3.5 8.1 0.0 4.2 1.1 0.7 5.3 11.2 0.4 Total 66.2 19.9 5.7 8.2 100 64.7 17.3 6.5 11.5 100

Transition tables across SOC90 Major Groups and NIW:

NCDS women (cell percentages)

2001 1991

Managers Professionals Assoc. Professionals Clerical Crafts

Personal / Protective Sales

Plant operatives Other

Out of work Total

Horizontal moves

Degree of stability

Managers 13.6 1.1 1.4 1.0 1.2 0.3 1.1 0.8 0.3 0.6 21.5 36.7 63.3

Professionals 1.7 6.3 0.9 0.1 0.5 0.1 0.1 0.2 0.1 0.4 10.2 38.4 61.6

Assoc. Professionals 2.3 1.1 4.7 0.4 0.6 0.1 0.2 0.3 0.0 0.5 10.2 54.2 45.8

Clerical 1.3 0.4 0.3 1.8 0.2 0.0 0.2 0.6 0.2 0.2 5.1 65.7 34.3

Crafts 2.0 0.3 0.8 0.6 12.4 0.3 0.2 1.4 0.6 1.1 19.6 36.9 63.1

Persona/Protective 1.2 0.1 0.2 0.2 0.2 3.1 0.1 0.2 0.1 0.2 5.6 44.5 55.6

Sales 1.5 0.2 0.3 0.1 0.3 0.1 1.1 0.4 0.1 0.2 4.2 74.1 25.9

Plant operatives 0.8 0.3 0.4 0.5 1.3 0.1 0.2 5.3 0.8 1.0 10.7 50.8 49.1

Other 0.5 0.0 0.2 0.2 0.3 0.1 0.1 0.7 2.0 0.5 4.6 56.7 43.3

Out of work 0.4 0.4 0.7 0.4 1.1 0.1 0.2 0.8 0.5 3.7 8.3 55.3 44.7

Total 25.4 10.3 9.9 5.3 17.9 4.2 3.3 10.7 4.7 8.4 100.0

% vertical moves 11.8 4.0 5.2 3.5 5.5 1.1 2.2 5.4 2.7 4.7

% vert.moves over all moves 25.6 8.6 11.3 7.7 11.9 2.5 4.8 11.7 5.8 10.1

% of 'stayers' (diagonal) 53.8

% movers (off diagonal) 46.2 Source: National Child Development Study

Loglinear modelling of transition tables (men)

Models G2 DF P 1) Main effects 13825.77 180 0 [O] [D] [S] 2) Cond. Independence 207.1784 99 0 [O D] [S] 4) All 2-way 118.6197 81 0.003 [O D] [O S] [D S] 5) Saturated model 0 0 1 [O D S]

Notation: O = Origin (9 SOC90 major groups + not in work) D = Destination (9 SOC90 major groups + not in work) S = Data source (LS50s/NCDS)

Transitions with greatest effect in the lack of fit of Model 2 (St.Residual>=|1.96|)

Transitions with more NCDS menand fewer LS50s men than expected

Transitions with more NCDS womenand fewer LS50s women than expected

Managers to Managers

Associated Professionals to Associated Professionals

Professionals to Professionals

Associated Professionals to Associated Professionals

Personal to Personal

Transitions with fewer NCDS men and more LS50s men than expected

Non-work to: Personal Nonwork

Transitions with fewer NCDS womenand more LS50s women than expected

None

Notes: Only transitions with n>=50 in each dataset are includedSources: Authors’ analysis. ONS Longitudinal Study and NCDS

Bibliography• Blackburn, R et al (2001) ‘Occupational stratification’, in Work,

Employment and Society, 15(3): 511-38.• Blackburn, R. and J.Jarman (2005) ‘Segregation and inequality’. GeNet

Working Paper No.3• Blackwell, L. and D.Guinea-Martin (2005) ‘Occupational segregation by

sex and ethnicity in England and Wales, 1991 to 2001’, Labour Market Trends, 113(12): 501-516.

• Elliott, J. (2005) ‘Comparing occupational segregation in Great Britain and the United States’, Work, Employment and Society, 19(1): 153-174

• Gilbert, N. (1981) Modelling Society. And introduction to loglinear analysis for social researchers. London: George Allen&Unwin

• Guinea-Martin, D. and J. Elliott (2008) ‘Economic position and occupational segregation in the 1990s’, Centre for Longitudinal Studies Working Paper

• James, D. and K.E.,Taeuber (1985) ‘Measures of segregation’, in Sociological Methodology, 15: 1-32

• Ramson, M.R. (2000) ‘Sampling distributions of segregation indexes’, Sociological Methods and Research, 28(4): 454-475

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