IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp648.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.44976.de/dp648.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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).
    4. 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.
    5. 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].
    6. Kenneth Train ., 2000. "Halton Sequences for Mixed Logit," Economics Working Papers E00-278, University of California at Berkeley.
    7. Alfonso Sousa‐Poza, 2004. "Is the Swiss Labor Market Segmented? An Analysis Using Alternative Approaches," LABOUR, CEIS, vol. 18(1), pages 131-161, March.
    8. 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.
    9. Arulampalam, Wiji & Booth, Alison L & Taylor, Mark P, 2000. "Unemployment Persistence," Oxford Economic Papers, Oxford University Press, vol. 52(1), pages 24-50, January.
    10. 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.
    11. 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.
    12. 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.
    13. Prowse, Victoria L., 2005. "State Dependence in a Multi-State Model of Employment Dynamics," IZA Discussion Papers 1623, Institute of Labor Economics (IZA).
    14. 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.
    15. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
    16. 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.
    17. Michaud, Pierre-Carl & Tatsiramos, Konstantinos, 2005. "Employment Dynamics of Married Women in Europe," IZA Discussion Papers 1706, Institute of Labor Economics (IZA).
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Martin Biewen, 2004. "Measuring State Dependence in Individual Poverty Status: Are there Feedback Effects to Employment Decisions and Household Composition?," Discussion Papers of DIW Berlin 429, DIW Berlin, German Institute for Economic Research.
    3. 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.
    4. Alexander Mosthaf & Thorsten Schank & Claus Schnabel, 2014. "Low-wage employment versus unemployment: Which one provides better prospects for women?," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 3(1), pages 1-17, December.
    5. 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.
    6. Sara Ayllón, 2013. "Understanding poverty persistence in Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 4(2), pages 201-233, June.
    7. Deng, Quheng & Ma, Xinxin, 2018. "The Dynamics of Informal Employment in Urban China," CEI Working Paper Series 2018-3, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    8. Martin Biewen, 2009. "Measuring state dependence in individual poverty histories when there is feedback to employment status and household composition," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(7), pages 1095-1116, November.
    9. Shiu, Ji-Liang & Hu, Yingyao, 2013. "Identification and estimation of nonlinear dynamic panel data models with unobserved covariates," Journal of Econometrics, Elsevier, vol. 175(2), pages 116-131.
    10. Manudeep Bhuller & Christian N. Brinch & Sebastian Königs, 2017. "Time Aggregation and State Dependence in Welfare Receipt," Economic Journal, Royal Economic Society, vol. 127(604), pages 1833-1873, September.
    11. Peter Haan, 2006. "Slowly, but Changing: How Does Genuine State Dependence Affect Female Labor Supply on the Extensive and Intensive Margin," JEPS Working Papers 06-002, JEPS.
    12. Alexander Plum, 2018. "Stochastic Expected Utility for Binary Choice: New Representations," Working Papers 2018-08, Auckland University of Technology, Department of Economics.
    13. Syamsul Hidayat Pasaribu, 2016. "Persistence of Individual Unemployment in Indonesia: Dynamic Probit Analysis from Panel SUSENAS 2008-2010," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1239-1246.
    14. Stephani, Jens, 2013. "Does it matter where you work? : employer characteristics and the wage growth of low-wage workers and higher-wage workers," IAB-Discussion Paper 201304, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    15. Schnitzlein, Daniel D. & Stephani, Jens, 2016. "Locus of Control and low-wage mobility," Journal of Economic Psychology, Elsevier, vol. 53(C), pages 164-177.
    16. Victoria Prowse, 2012. "Modeling Employment Dynamics With State Dependence and Unobserved Heterogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 411-431, April.
    17. Kostas Mavromaras & Peter Sloane & Zhang Wei, 2015. "The scarring effects of unemployment, low pay and skills under-utilization in Australia compared," Applied Economics, Taylor & Francis Journals, vol. 47(23), pages 2413-2429, May.
    18. Clark, Ken & Kanellopoulos, Nikolaos C., 2013. "Low pay persistence in Europe," Labour Economics, Elsevier, vol. 23(C), pages 122-134.
    19. Ki-Dong Lee & Seo-Hyeong Lee & Jong-Il Choe, 2018. "State dependence, individual heterogeneity, and the choice of employment status: evidence from Korea," Applied Economics, Taylor & Francis Journals, vol. 50(8), pages 824-837, February.
    20. Aretz, Bodo & Gürtzgen, Nicole, 2012. "The Evolution of Wage Mobility in the German Low-Wage Sector - Is There Evidence for Increasing State Dependence?," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62049, Verein für Socialpolitik / German Economic Association.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:diw:diwwpp:dp648. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.