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From No Pay to Low Pay and Back Again?: A Multi-State Model of Low Pay Dynamics

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  • Arne Uhlendorff

Abstract

This study analyzes the mobility between three labor market states: working in low paid jobs, working in higher paid jobs and not working. Using German panel data I estimate dynamic multinomial logit panel data models with random effects taking the initial conditions problem and potential endogeneity of panel attrition into account. In line with results from other countries, this first study on Germany finds true state dependence in low pay jobs and confirms previous results of state dependence in non-employment. Moreover, I find evidence for a "low pay no pay cycle", i.e. being low paid or not employed itself increases the probability of being in one of these states in the next year. However, compared to non working, being low paid does not have adverse effects on future employment prospects: the employment probability increases with low pay employment and the probability of being high paid seems to be higher for previously low paid workers. I find no evidence for endogenous panel attrition.

Suggested Citation

  • 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.
  • Handle: RePEc:diw:diwwpp:dp648
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    1. Lorenzo Cappellari, 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. Gong, Xiaodong & Van Soest, Arthur & Villagomez, Elizabeth, 2004. "Mobility in the Urban Labor Market: A Panel Data Analysis for Mexico," Economic Development and Cultural Change, University of Chicago Press, vol. 53(1), pages 1-36, October.
    3. Lorenzo Cappellari & Stephen P. Jenkins, 2004. "Modelling Low Pay Transition Probabilities, Accounting for Panel Attrition, Non-Response, and Initial Conditions," CESifo Working Paper Series 1232, CESifo.
    4. Muhleisen, Martin & Zimmermann, Klaus F., 1994. "A panel analysis of job changes and unemployment," European Economic Review, Elsevier, vol. 38(3-4), pages 793-801, April.
    5. Mark B. Stewart & Joanna K. Swaffield, 1999. "Low Pay Dynamics and Transition Probabilities," Economica, London School of Economics and Political Science, vol. 66(261), pages 23-42, February.
    6. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
    7. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    8. Barry McCormick, 1990. "A Theory of Signalling During Job Search, Employment Efficiency, and "Stigmatised" Jobs," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(2), pages 299-313.
    9. Kenneth Train ., 2000. "Halton Sequences for Mixed Logit," Economics Working Papers E00-278, University of California at Berkeley.
    10. Mark B. Stewart, 2007. "The interrelated dynamics of unemployment and low-wage employment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 511-531.
    11. Peter Haan & Arne Uhlendorff, 2006. "Estimation of multinomial logit models with unobserved heterogeneity using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 6(2), pages 229-245, June.
    12. Jones, Melanie K. & Jones, Richard J. & Murphy, Philip D. & Sloane, Peter J., 2005. "The Dynamics of the National Minimum Wage: Transitions Between Different Labour Market States," IZA Discussion Papers 1690, Institute of Labor Economics (IZA).
    13. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441, Elsevier.
    14. Dean R. Hyslop, 1999. "State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women," Econometrica, Econometric Society, vol. 67(6), pages 1255-1294, November.
    15. Michaud, Pierre-Carl & Tatsiramos, Konstantinos, 2005. "Employment Dynamics of Married Women in Europe," IZA Discussion Papers 1706, Institute of Labor Economics (IZA).
    16. Prowse, Victoria L., 2005. "State Dependence in a Multi-State Model of Employment Dynamics," IZA Discussion Papers 1623, Institute of Labor Economics (IZA).
    17. Peter Haan, 2005. "State Dependence and Female Labor Supply in Germany: The Extensive and the Intensive Margin," Discussion Papers of DIW Berlin 538, DIW Berlin, German Institute for Economic Research.
    18. Rhein, Thomas & Gartner, Hermann & Krug, Gerhard, 2005. "Niedriglohnsektor: Aufstiegschancen für Geringverdiener verschlechtert," IAB-Kurzbericht 200503, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    19. Jürgen Schupp & Gert G. Wagner, 2002. "Maintenance of and Innovation in Long-Term Panel Studies: The Case of the German Socio-Economic Panel (GSOEP)," Discussion Papers of DIW Berlin 276, DIW Berlin, German Institute for Economic Research.
    20. Flaig, Gebhard & Licht, Georg & Steiner, Viktor, 1993. "Testing for state dependence effects in a dynamic model of male unemployment behaviour," ZEW Discussion Papers 93-07, ZEW - Leibniz Centre for European Economic Research.
    21. Alfonso Sousa‐Poza, 2004. "Is the Swiss Labor Market Segmented? An Analysis Using Alternative Approaches," LABOUR, CEIS, vol. 18(1), pages 131-161, March.
    22. Bernd Gorzig & Martin Gornig & Axel Werwatz, 2005. "Explaining Eastern Germany's Wage Gap: The Impact of Structural Change," Post-Communist Economies, Taylor & Francis Journals, vol. 17(4), pages 449-464.
    23. Arulampalam, Wiji & Booth, Alison L & Taylor, Mark P, 2000. "Unemployment Persistence," Oxford Economic Papers, Oxford University Press, vol. 52(1), pages 24-50, January.
    24. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September.
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    More about this item

    Keywords

    low pay dynamics; unemployment dynamics; dynamic random effects models; state dependence; panel attrition; unobserved heterogeneity;
    All these keywords.

    JEL classification:

    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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