Investigating Southern Europeans’ Perceptions of Their Employment Status

  • Aggeliki Yfanti
  • Catherine Michalopoulou
  • Aggelos Mimis
  • Stelios Zachariou
Chapter
Part of the The Springer Series on Demographic Methods and Population Analysis book series (PSDE, volume 46)

Abstract

The European Union Labour Force Survey (EU-LFS) measurement of the employment status is based on a synthesized economic construct computed according to the ILO conventional definitions of the employed, unemployed and inactive. Since the late 2000s, a variable measuring people’s perceptions of their employment status has been included in the EU-LFS questionnaire as it is used in all large-scale sample surveys, i.e. one of the occupational background variables. These measurements are not comparable and their results will differ since a composite economic construct would normally deviate from people’s perceptions. The purpose of this paper is, by obtaining a social “profile” of agreement and disagreement between Southern Europeans’ declared self-perceptions of their employment status and the ILO conventional definitions, to investigate whether or not conflicting and coinciding perceptions differ overtime within-nations and cross-nationally. The analysis is based on the 2008–2014 annual datasets for Greece, Italy, Portugal and Spain. The results are reported for the age group 15–74 so as to allow for comparability with the ILO conventional definition of unemployment.

Keywords

Employment status ILO EU-LFS Southern Europe 

References

  1. Brandolini, A., Cipollone, P., & Viviano, E. (2004). Does the ILO definition capture all unemployment? (Temi di discussione del Servizio Studi 529). Roma: Banca d’Italia.Google Scholar
  2. Braun, M., & Mohler, P. P. (2003). Background variables. In J. A. Harkness, F. J. R. Van de Vijver, & P. P. Mohler (Eds.), Cross-cultural survey methods. Hoboken, New Jersey: Wiley.Google Scholar
  3. de la Fuente, A. (2011). New measures of labour market attachment: 3 new Eurostat indicators to supplement the unemployment rate (Statistics in Focus 57), Eurostat, European Commission.Google Scholar
  4. Eurostat. (2008). Labour Force Survey revised explanatory notes (to be applied from 2008Q1 onwards), European Commission.Google Scholar
  5. Eurostat. (2009). Task Force on the quality of the Labour Force Survey: Final report. European Commission.Google Scholar
  6. Eurostat. (2016). EU Labour Force Survey database user guide. European Commission.Google Scholar
  7. Gauckler, B., & Körner, T. (2011). Measuring the employment status in the Labour Force Survey and the German census 2011: Insights from recent research at Destatis. Methoden –Daten–Analysen, 5(2), 181–205.Google Scholar
  8. Hussmanns, R., Mehran, F., & Verma, V. (1990). Surveys of economically active population, employment, unemployment and underemployment: An ILO manual on concepts and methods. Geneva: International Labour Office.Google Scholar
  9. Jones, S. R. G., & Riddell, W. C. (1999). The measurement of unemployment: An empirical approach. Econometrica, 67(1), 147–162.CrossRefGoogle Scholar
  10. Kish, L. (1994). Multipopulation survey designs: Five types with seven shared aspects. International Statistical Review, 62(2), 167–186.CrossRefGoogle Scholar
  11. Oppenheim, A. N. (1992). Questionnaire design, interviewing and attitude measurement (new edition). London: Continuum.Google Scholar
  12. Schwarz, N. (1987). Cognitive issues of Labour Force Surveys in a multinational context: Issues and findings. Paper prepared for the OECD Working Party on Employment and Unemployment Statistics, Paris, April, 14–16.Google Scholar
  13. Stephan, F. F., & McCarthy, P. J. (1958). Sampling opinions: An analysis of survey procedure. Westport: Greenwood Press.Google Scholar
  14. Yfanti, A., Michalopoulou, C., & Zahariou, S. (2017). The decision of how to measure unemployment is a political and not a statistical question: Evidence from the European Labour Force Survey: 2008–2014. Manuscript in preparation.Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Aggeliki Yfanti
    • 1
  • Catherine Michalopoulou
    • 1
  • Aggelos Mimis
    • 1
  • Stelios Zachariou
    • 2
  1. 1.Panteion University of Social and Political SciencesAthensGreece
  2. 2.Hellenic Statistical AuthorityPiraeusGreece

Personalised recommendations