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Multilevel Analysis of Job Satisfaction in British Workplaces: Insights from WERS 2004

This presentation outlines a comprehensive analysis of job satisfaction (JS) in British workplaces using data from the 2004 Workplace Employment Relations Survey (WERS). It examines the determinants of JS, the link between JS and economic outcomes, and the significance of unobserved heterogeneity. The study employs advanced multilevel methodologies to analyze various facets of job satisfaction and draws on both employee and management surveys. Key findings emphasize important factors such as training opportunities and flexible work arrangements, highlighting areas for further research.

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Multilevel Analysis of Job Satisfaction in British Workplaces: Insights from WERS 2004

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Presentation Transcript

  1. Workplace job satisfaction: a multilevel analysis WERS 2004 Users Group Meeting, NIESR March 16, 2007

  2. Outline of presentation • Introduction • Data • Methodology • Results • Summary of findings • Further work

  3. Introduction • Job satisfaction as a theme of research in economics • The link between JS and economic outcomes • Determinants of JS: The evidence thus far • Should we explore JS and its determinants further? • How is this study different, is it?

  4. Data • The data used is WERS 2004 • The most comprehensive of the WERS series of surveys • Nationally representative survey of British workplaces • Use is made of data from the management and employee surveys • SEQ: 22,451 (61% response rate) • MQ: 2,295 workplaces (64% response)

  5. Data (cont’d) • Eight different facets of JS have been monitored in wers2004 • An ‘overall’ JS indicator has also been generated • Each of the five scale JS indicators have been collapsed into a dummy (1 if ‘very satisfied’ or ‘satisfied’ & 0 otherwise • A range of exogenous variables (employee & establishment) has been used

  6. Data (Descriptive stat)

  7. Data (corr. Matrix)

  8. Methodology • The methodology employed exploits the data structure • No account has been made for possible endogeneity problems yet • Accounts for unobserved heterogeneity, unlike most in the literature • This version, focuses on unmeasured heterogeneity in overall response

  9. Methodology (cont’d) • Following Hammermesh (1977) & Freeman (1978), utility from work or aspects of work is given as • This is modelled using the basic 2-level ML model that is specified as

  10. Methodology (cont’d) • Unobserved heterogeneity component is modelled as • so that • We’ve binary JS indicators » need for a link function given by • with

  11. Results • Please see results in the handout!

  12. Summary of results • That firm-level unobserved heterogeneity is important for the most part • Important/significant employee & employer effects, particularly • availability of training opportunity (+) • Union membership (-) • Flexible work arrangement (+) • Skills mismatch (-) • Industry of employment (education (+), health (+))

  13. Further work • Refining/reducing the correlates • Investigate whether different results if using the ordinal indicators of satisfaction • Introducing higher levels (‘astatus’ for eg) • Random coefficient models • Account for possible endogeneity ~~~~

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