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Using EseC to look across and within classes

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. Purposes of Paper. Replicate initial analysis using the new three digit matrix (‘Euroesec’)

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Using EseC to look across and within classes

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  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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