IDEAS home Printed from https://ideas.repec.org/p/ctl/louvre/1992033.html
   My bibliography  Save this paper

The Demographics of Labour Turnover : A Comparison of Ordinal Probit and Censored Count Data Models

Author

Listed:
  • Lucie MERKLE

    (Universität München)

  • Klaus F. Zimmermann

    (Universität München and CEPR, London)

Abstract

As has been found in previous studies, the labor market performance of individuals is often affected by demographic determinants like cohort size, age, marriage status and family size. While most of this analysis was studied for earnings, the paper investigates the issue for labor mobility. Mobility is measured here by the number of new employers and the frequency of unemployment of an individual in a particular period. Given the discrete nature of the data, the ordinal probit model and the censored Poisson as the censored negative binomial model was estimated. Since the choice of the statistical model is not clear a priori, various model comparisons are carried out and some new pseudo-R2 measures are proposed and used in the analysis. Results indicate that demographic determinants matter for labor mobility.

Suggested Citation

  • Lucie MERKLE & Klaus F. Zimmermann, 1992. "The Demographics of Labour Turnover : A Comparison of Ordinal Probit and Censored Count Data Models," Discussion Papers (REL - Recherches Economiques de Louvain) 1992033, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  • Handle: RePEc:ctl:louvre:1992033
    as

    Download full text from publisher

    File URL: http://www.jstor.org/stable/40723996
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rainer Winkelmann & Klaus Zimmermann, 1998. "Is job stability declining in Germany? Evidence from count data models," Applied Economics, Taylor & Francis Journals, vol. 30(11), pages 1413-1420.
    2. Colin Cameron, A. & Windmeijer, Frank A. G., 1997. "An R-squared measure of goodness of fit for some common nonlinear regression models," Journal of Econometrics, Elsevier, vol. 77(2), pages 329-342, April.

    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General

    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:ctl:louvre:1992033. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sebastien SCHILLINGS (email available below). General contact details of provider: https://edirc.repec.org/data/iruclbe.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.