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State-Dependence and Stepping Stone Effects of Low Pay Employment in Australia

Author

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  • Cai, Lixin

Abstract

Using the HILDA Survey, this study examines state-dependence and stepping stone effects of low pay in Australia. The results show that both state-dependence and stepping stone effects of low pay are present after observed and unobserved individual heterogeneity is accounted for. The results also show that, other things being equal, people who are on low pay are more likely to be in employment in the future than those who are either unemployed or not in the labour force. On the other hand, people on low pay do not appear to be more likely to become jobless in the future than those on higher pay.

Suggested Citation

  • Cai, Lixin, 2013. "State-Dependence and Stepping Stone Effects of Low Pay Employment in Australia," MPRA Paper 50522, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:50522
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    File URL: https://mpra.ub.uni-muenchen.de/50522/1/MPRA_paper_50522.pdf
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    References listed on IDEAS

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    1. Cappellari, Lorenzo, 2002. " Do the 'Working Poor' Stay Poor? An Analysis of Low Pay Transitions in Italy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(2), pages 87-110, May.
    2. Stewart, Mark B & Swaffield, Joanna K, 1999. "Low Pay Dynamics and Transition Probabilities," Economica, London School of Economics and Political Science, vol. 66(261), pages 23-42, February.
    3. Hielke Buddelmeyer & Wang-Sheng Lee & Mark Wooden, 2010. "Low-Paid Employment and Unemployment Dynamics in Australia," The Economic Record, The Economic Society of Australia, vol. 86(272), pages 28-48, March.
    4. Lorenzo Cappellari, 2007. "Earnings mobility among Italian low-paid workers," Journal of Population Economics, Springer;European Society for Population Economics, vol. 20(2), pages 465-482, April.
    5. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54.
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, April.
    7. Sloane, P. J. & Theodossiou, I., "undated". "An Econometric Analysis of Low Pay Earnings Mobility," Working Papers 98-05, Department of Economics, University of Aberdeen.
    8. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    9. Daniel Perkins & Rosanna Scuttella, 2008. "Improving Employment Retention and Advancement of Low-Paid Workers," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 11(1), pages 97-114, March.
    10. Lorenzo Cappellari & Stephen P. Jenkins, 2008. "Estimating low pay transition probabilities accounting for endogenous selection mechanisms," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(2), pages 165-186.
    11. Arne Uhlendorff, 2006. "From No Pay to Low Pay and Back Again?: A Multi-State Model of Low Pay Dynamics," Discussion Papers of DIW Berlin 648, DIW Berlin, German Institute for Economic Research.
    12. Mark Wooden & Simon Freidin & Nicole Watson, 2002. "The Household, Income and Labour Dynamics in Australia (HILDA)Survey: Wave 1," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 35(3), pages 339-348.
    13. Knabe, Andreas & Plum, Alexander, 2010. "Low-wage jobs: Stepping stone or poverty trap?," Discussion Papers 2010/28, Free University Berlin, School of Business & Economics.
    14. Ken Clark & Nikolaos C. Kanellopoulos, 2009. "Low Pay Persistence in European Countries," SOEPpapers on Multidisciplinary Panel Data Research 207, DIW Berlin, The German Socio-Economic Panel (SOEP).
    15. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-764, May.
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    Cited by:

    1. Claus Schnabel, 2016. "Low-wage employment," IZA World of Labor, Institute for the Study of Labor (IZA), pages 276-276, July.
    2. repec:bla:ecorec:v:93:y:2017:i::p:144-170 is not listed on IDEAS
    3. repec:bla:ecorec:v:92:y:2016:i:299:p:517-547 is not listed on IDEAS

    More about this item

    Keywords

    Low pay; stepping stone effects; state dependence; multinomial logit model;

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J38 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Public Policy

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