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How many labour force states? An analysis based on the British Household Panel Survey (BHPS)

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  • Elisabetta Marzano

Abstract

The motivation of this paper is to investigate the characteristics of the British labour force, using data from the BHPS (British Household Panel Survey). The goal is to examine whether there are statistically significant differences between the unemployed and non participants, as well as inside each of the two groups, considering their transitions in the job market. Using logistic regression for a pooled cross section-time series sample of employed as well as non employed persons, 3 different Out of Work subgroups are identified: Seeking Out of Work, Attached Out of Work, and Voluntary Out of Work. The first group can be broadly assimilated to the official definition of unemployment, ILO unemployment, while all the others are usually classified as economically inactive. Nonetheless, the last two groups are characterised by significantly different transition rates, showing a behaviourally distinct attitude in their labour market dynamics. This result points out that the aggregate non employment has several dimensions, which are not caught by the distinction between unemployment and economic inactivity, and should be accounted for by policy makers and researchers.

Suggested Citation

  • Elisabetta Marzano, 2006. "How many labour force states? An analysis based on the British Household Panel Survey (BHPS)," Discussion Papers 14_2006, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
    • Handle: RePEc:prt:dpaper:14_2006
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    References listed on IDEAS

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    1. Sergi Jiménez-Martín & Franco Peracchi, 2002. "Sample attrition and labor force dynamics: Evidence from the Spanish labor force survey," Spanish Economic Review, Springer;Spanish Economic Association, vol. 4(2), pages 79-102.
    2. Marzano, Elisabetta, 2003. "Looking for a job: is there any homogeneity among those not seeking work?," ISER Working Paper Series 2003-25, Institute for Social and Economic Research.
    3. Andrea Brandolini & Piero Cipollone & Eliana Viviano, 2006. "Does The Ilo Definition Capture All Unemployment?," Journal of the European Economic Association, MIT Press, vol. 4(1), pages 153-179, March.
    4. Steve Nickell & Jan van Ours, 2000. "The Netherlands and the United Kingdom: a European unemployment miracle?," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 15(30), pages 136-180.
    5. Christopher J. Flinn & James J. Heckman, 1982. "Models for the Analysis of Labor Force Dynamics," NBER Working Papers 0857, National Bureau of Economic Research, Inc.
    6. Garrido, Luis & Toharia, Luis, 2004. "What does it take to be (counted as) unemployed? The case of Spain," Labour Economics, Elsevier, vol. 11(4), pages 507-523, August.
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    Cited by:

    1. Toshihiko Mukoyama & Richard Rogerson & Aysegul Sahin & Per Krusell, 2009. "Labor supply in a frictional labor market," 2009 Meeting Papers 54, Society for Economic Dynamics.
    2. García-Gómez, Pilar & Jones, Andrew M. & Rice, Nigel, 2010. "Health effects on labour market exits and entries," Labour Economics, Elsevier, vol. 17(1), pages 62-76, January.
    3. Krusell, Per & Mukoyama, Toshihiko & Rogerson, Richard & Sahin, Aysegül, 2011. "A three state model of worker flows in general equilibrium," Journal of Economic Theory, Elsevier, vol. 146(3), pages 1107-1133, May.

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    More about this item

    Keywords

    inactivity; attachment; transition probabilities.;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J82 - Labor and Demographic Economics - - Labor Standards - - - Labor Force Composition
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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