GEODE, March 2007

Occupational Analysis – the examples of: - the Youth Cohort Study of England & Wales - ‘By Slow Degrees’ - social mobility research

Grid Enabled Occupational Data Environment

GEODE Project, March 2007

Vernon Gayle and Paul Lambert

University of Stirling

GEODE, March 2007

Part1: Youth Cohort Study 1985-2005

Change and Stability:

* The questionnaire designed to be broadly comparable

* External changes and shifts in policy interests have brought about changes

* Changes – Major and Minor!

GEODE, March 2007

Problems Relating to Occupational Information in YCS

* Generic problems to collecting and coding occupational

information

* Some specific to the YCS

GEODE, March 2007

Examples from Questionnaires

* Parental information is collected

* Although the exact information collected has changed

* Usually information on job title and self-employment

GEODE, March 2007

Examples from Questionnaires

* Remember that this is a postal questionnaire survey

* Asking a 16/17 year old about their parent’s job

YCS 1 apprx 6130 Dads working full-time

apprx 5524 occupational codes (apprx 10% missing)

GEODE, March 2007

Examples from Questionnaires

* Documentation is very poor especially in the older

cohorts – usually handwritten annotation on

questionnaires (pdf)

* Compare this with the BHPS for example

GEODE, March 2007

Examples from Questionnaires YCS1

GEODE, March 2007

Examples from Questionnaires YCS10

GEODE, March 2007

Examples of Analyses

* Drew et al. (1992) analyses earlier data constructed a measure (Professional; Intermediate; Manual)

* Gayle et al. (2000 & 2002) analysis of YCS 3 constructed a measure of family social class (highest - father or mother) using Registrar General

* Raffe et al. (2006) undertaking cross-cohort analyses harmonised a variable based on NS S-EC (Managerial/Professional; Intermediate; Manual)

* Connolly (2006) analysing YCS 9 & 10 relied on a modified version of Registrar General deposited with the data

GEODE, March 2007

What is there?

* Some early cohorts often code parental occupations using C080

* Later cohorts use SOC90

* Some cohorts do not included detail occupational codes

* Generally there is self-employment information - but not detailed employment status information (e.g. Employers; Managers; Supervisors etc).

GEODE, March 2007

What is there?

* Some cohorts include a SEG measure (e.g. standard 16 categories in YCS 7) there is no clear information on how these are derived but other cohorts do not

* Cohort 9 reports SEG but in practice this is a modified version of the Registrar General Schema with (Class I and Class II merged)

* Parental occupation normally asked in sweep 1 – YCS3 asks in sweep 2 and there is apprx. 24% sample attrition

* Later YCS cohorts – more thought into collection of appropriate data but data coding is still problematic

GEODE, March 2007

What is the problem?

* Varying quality of occupational information

* Compared to some other survey little attempt to sort out occupational information

* Raffe et al. tried to work up a ‘time-series’ data set with a harmonised family social class measure – see also team member Croxford (2004)

GEODE, March 2007

Can Geode help?

* In principle yes – overall task of harmonisation

* Definitely for YCS data depositors!

* In practice Gayle et al. could have been helped directly in the construction of their family RG Social Class measure

* In the talk only mentioned family social class – but there is also occupational information on young workers

* In principle the GEODE idea could extend to qualifications – harmonising qualification is equally problematic in the YCS

GEODE, March 2007

Example 2: By Slow Degrees

Lambert, PS., Prandy, K. and Bottero, W. (2007) “By Slow Degrees: Two centuries of social reproduction and mobility in Britain”, Sociological Research Online, 12(1).

http://www.socresonline.org.uk/12/1/prandy.html

GEODE, March 2007

(1): R2=0.55, B=-0.0012, P_1900=0.439, P_2000=0.316

(2): R2=0.09, B=-0.0012, P_1900=0.439, P_2000=0.319

0.1

.2.3

.4.5

.6

1780 1805 1830 1855 1880 1905 1930 1955 1980

FHS data (1) Linear regression, all data

All other surveys (2) Linear regression, excluding FHS

Father-Son correlation by birth cohort and study

(1): R2=0.12, B=-0.0006, P_1900=0.354, P_2000=0.293

(2): R2=0.08, B=-0.0013, P_1900=0.387, P_2000=0.258

-.1

0.1

.2.3

.4.5

.6

1780 1805 1830 1855 1880 1905 1930 1955 1980Birth cohort (by decade)

Father-Daughter correlation by birth cohort and study

Source: Data as Table 2. All ages combined, panel duplicates excluded. N used = 103,357 men; 60,714 women. 10 year cohort-by-study combinations with 50+ cases (light shaded = 50-399 cases; dark = 400+ cases).

Figure 1: Intergenerational CAMSIS correlations

GEODE, March 2007

-50

51

0

(1) LinearOLS

(2) QuadraticOLS

(3) BandedOLS

(4) Robust clusters(survey + region)

(5) Panel (BHPS, PCB only)

M F M F M F M F M F

Source: Data as Table 2, panel duplicates excluded 1-4. Model 1, N=110319 men, 67344 women. Regression: own CAMSIS = father's CAMSIS[F] + age + year of birth[Y] + Y.F interaction. Models 1, 4, 5 fit Y.F as linear effect, model 2 as quadratic, model 3 uses 10-year bands.

Decline in main effects of father's occupation over 200 year periodFigure 6: Intergenerational interaction effects

Main effect (CAMSIS gain for 15 units of father's CAMSIS, if born in 1800)

Interaction effect (Change in relative gain, if born in 2000)

GEODE, March 2007

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GEODE, March 2007

Meta-analysis of occupations – could GEODE help?

Yes of course!! – Documentation of occupational translations

• E.g. Scotland 1974 Stratification survey

• European Social Survey 2003

– ..could have accessed occupational data

Not so sure…– Extended period of research, dedicated manual processing

GEODE, March 2007

Summary: GEODE and occupational data analysis

The data resources are ultimately there

Analysts currently undertake most of the groundwork

GEODE as a data processing service– Access to suitable resources– Documentation of occupational data processing– Quick solutions for simpler jobs..