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Using EseC to look across and within classes Workshop on Application of ESeC Lake Bled, 29-30 June 2006 Eric Harrison & David Rose ISER, University of.

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Presentation on theme: "Using EseC to look across and within classes Workshop on Application of ESeC Lake Bled, 29-30 June 2006 Eric Harrison & David Rose ISER, University of."— Presentation transcript:

1 Using EseC to look across and within classes Workshop on Application of ESeC Lake Bled, 29-30 June 2006 Eric Harrison & David Rose ISER, University of Essex

2 Purposes of Paper Replicate initial analysis using the new three digit matrix (‘Euroesec’) Explore new variables now available in round two of the European Social Survey Trial analysis using the draft Socio- economic groups (SEGs)

3 European Social Survey Rapidly becoming primary European dataset: –A more all-purpose instrument than LFS, with numerous socio- political attitude measures –A more precise set of information for constructing ESeC than ECHP and many more countries Two rounds now available (Round 3 in progress) Round 1: 22 countries, 42,359 cases Round 2: 24 countries, 45,681 cases (Italy still to deposit) Most or all of the information needed to make an ESeC, i.e. 3 or 4 digit ISCO (e.g. French R2), employment status and supervision questions)

4 Sample Sizes in ESS 1 & 2

5 Three Performance Targets for EseC Does it work? Can it be operationalized? Can it measure what it purports to measure, over and over again? Does it discriminate and structure with regard to predicting values of related variables?

6 EseC Distributions in ESS 1&2

7 The Treatment of Employment Status in R2 Self-employed, supervisors, employees Employment relation variable – France and Hungary inserted extra categories. These can be collapsed back into the main dataset No problem with self-employed in R2: –Family workers (small N) treated as employees Supervision – remains ambiguous in social surveys Management – rely on ISCO codes

8 Redistribution of Class 2 Supervisors

9 Redistribution of Class 6 Supervisors

10 ESeC Distributions for ESS countries

11 Measuring Employment relations in the ESS Looking for core variables over numerous rounds of the surveys: Round 1 Citizenship module had two questions now part of core in Round 2 (organisation of work and policy decisions) In Round 1 many questions only asked to those who worked in previous week In Round 2 also asked for information about last job = larger n

12 Influence over organisation of daily work

13 Two measures of asset specificity ‘Using this card, how difficult or easy would it be for you to get a similar or better job with another employer if you wanted to?’ [adapted from Citizenship R1 module] ‘In your opinion, how difficult or easy would it be for your employer to replace you if you left?’ [new question]

14 Two measures of asset specificity

15 Statements about current job (R2) Family, work and well-being module Battery of questions about aspects of job quality: –variety, on the job learning, security, effort bargain, support from co-workers, time-keeping, health and safety (4 point T/F) –work effort, work intensity, promotion opportunities (5 point A/D) Initial analysis suggests tapping quite different constructs

16 ‘ Opportunities for advancement in my job’

17 Subjective General Poor Health

18 Looking Within Classes ESeC was designed as a ‘nested hierarchy’: each class has a number of distinct groups below the top level. Revised ESeC now has 41 active SEGs Coding structure offers chance to make fine distinctions among the inactive groups which can be used in modelling

19 Examples of SEGs Class 1: 11. Employers (non-agric) with 10+ employees 12. Large business farmers 13. Higher managerial and administrative 14. Higher professional occupations (employees) 15. Higher professional occupations (self- employed)

20 Examples of SEGs Class 2: 21. Lower managerial and administrative occupations 22. Lower professional occupations (employees) 23. Lower professional occupations (Self- employed) 24. Higher technician occupations (employees) 25. Higher technician occupations (self-employed) 26. Higher supervisory occupations

21 Employment Relations through Work Autonomy (difficulty of monitoring) The ESS invited respondents to say ‘how much the management at your work allows you…. to be flexible in your working hours? To decide how your own daily work is organised? To influence your environment? To influence decisions about the general direction of your work? To change your work tasks if you wish to?

22 Five-item work autonomy scale: Employees in Class 1 and 2

23 Influence on organising own work: SEGS in class 1 and 2

24 Subjective Poor Health: Classes 1 and 2

25 Conclusions ESeC classes discriminate remarkably well: –a range of ‘employment relations’ questions –significant differences between every class, not just contract types Little or no discernable loss of power in adopting an ESeC based on three digit ISCO SEGs offer chance to discriminate and structure within classes, but more reliant on precise ISCO


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