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Choosing between alternative classification criteria to measure the labour force state

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  • Erich Battistin
  • Enrico Rettore
  • Ugo Trivellato

Abstract

Summary. Labour force counting relies on general guidelines that are set by the International Labour Office to classify individuals into three labour force states: employment, unemployment and inactivity. However, the resulting statistics are known to be sensitive to slight variations in operational definitions which are prima facie consistent with the general guidelines. We consider two interpretations of the general guidelines, operationalized by the criterion that is currently followed by Eurostat and a criterion that was followed by the Italian Statistical Office up to 1992. After showing that the labour force statistics resulting from the two criteria differ considerably, we compare individuals whose classification depends on the criterion that is adopted with individuals whose classification is common between criteria to study the boundary between unemployment and inactivity. An application of our strategy is presented using data from the Italian Labour Force Survey, painting a picture neatly against the criterion that is currently followed by Eurostat.

Suggested Citation

  • Erich Battistin & Enrico Rettore & Ugo Trivellato, 2007. "Choosing between alternative classification criteria to measure the labour force state," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(1), pages 5-27, January.
    • Handle: RePEc:bla:jorssa:v:170:y:2007:i:1:p:5-27
    DOI: 10.1111/j.1467-985X.2006.00449.x
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    References listed on IDEAS

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    1. Flinn, Christopher J & Heckman, James J, 1983. "Are Unemployment and Out of the Labor Force Behaviorally Distinct Labor Force States?," Journal of Labor Economics, University of Chicago Press, vol. 1(1), pages 28-42, January.
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    4. David Bartholomew, 1997. "Editorial: The Measurement of Unemployment in the UK: the Position at June 1997," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 385-388, September.
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    Cited by:

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    2. Niall O'Higgins & Marco Stimolo, 2019. "Trust and reciprocity in youth labor markets. An experimental approach to analyzing the impact of labour market experiences on young people," LEM Papers Series 2019/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Marco Guerrazzi & Ilham Ksebi, 2019. "Measuring Unemployment by Means of Official Data and Administrative Records: Empirical and Theoretical Perspectives," QUADERNI DI ECONOMIA DEL LAVORO, FrancoAngeli Editore, vol. 2019(110), pages 17-49.
    4. Bruno Contini & Elisa Grand, 2012. "Workforce disposal, long-term unemployment and out-of-labor force in Italy: new data for economic policy," Politica economica, Società editrice il Mulino, issue 2, pages 135-156.
    5. Andrea Brandolini & Eliana Viviano, 2016. "Behind and beyond the (head count) employment rate," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 657-681, June.
    6. Enrico Ripamonti & Stefano Barberis, 2021. "The association of economic and cultural capital with the NEET rate: differential geographical and temporal patterns," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 55(1), pages 1-17, December.

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