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Understanding Individual Surveys: Insights into Work, Expenditure, and Social Conditions

Individual surveys, conducted at home or the workplace, collect data for government analysis on employment, spending, and living conditions. Examples include the Labour Force Survey (LFS) and Family Expenditure Survey (FES). These surveys reveal insights into work processes, social divisions (age and gender), occupational status, pay, and quality of life. Analyses may explore trends, causal relationships, and comparative indicators, though they often face limitations related to data quality and scope. Understanding these individual factors can provide crucial context for broader economic and social studies.

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Understanding Individual Surveys: Insights into Work, Expenditure, and Social Conditions

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Presentation Transcript

  1. What are individual surveys? • Surveys of samples of individuals either at home or the workplace • To produce data for governments on work, expenditure etc - LFS, FES • Or specialised surveys – eg Living Conditions • Panels studies – BHPS, GSOEP

  2. What can analysis of individuals add to other research? • Testing structural parameters for example… • Work conditions • Social divisions (age/gender) but also… • Comparative indicators • Trends

  3. Analysis of individuals…. • Looking at work processes? Scope is limited • Need work-based surveys • Inadequate questions (except hours worked and individual work responsibilities) • Is analysis of workers or work units?

  4. Analysis of individuals • Analysis of outcomes • Occupational status • Pay • Quality of working life • Stress • Aggregate change in these (time series) • Within individual change (panels)

  5. Constraints • No single good data source – mix and match • Big issues like globalisation, value chains can’t be addressed • Work processes and structures only glimpsed indirectly

  6. Modes of analysis • Descriptive • Structural parameters and outcomes • Current distributions (eg of skills) • Relations between these and other factors • Trends (where possible)

  7. Modes of analysis • Some causal relationships that can be addressed (example of skills)…. • Is spread of new and niche graduates occupations (Elias) associated with pay differentials between graduates? • Is overqualification the result of the social demand for higher education? • Has increase in supply of female graduates reduced gender inequality?

  8. The growth of graduates in employment, by gender

  9. Graduates in Goldthorpe social classes, by gender, GB (LFS)

  10. Overqualification (%)

  11. Concluding comments • Quantitative analysis based on individuals, especially sampled through households, has to be highly focussed • This will relate most to indicators that identify individuals rather than jobs or work processes – eg qualifications and skills • But inferences about job change can be made • More direct casual analysis possible with panels

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