IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp564.html
   My bibliography  Save this paper

On the Returns to Occupational Qualification in Terms of Subjective and Objective Variables: A GEE-type Approach to the Estimation of Two-Equation Panel Models

Author

Listed:
  • Martin Spieß

Abstract

This article proposes an estimation approach for panel models with mixed continuous and ordered categorical outcomes based on generalized estimating equations for the mean and pseudo-score equations for the covariance parameters. A numerical study suggests that efficiency can be gained as concerns the mean parameter estimators by using individual covariance matrices in the estimating equations for the mean parameters. The approach is applied to estimate the returns to occupational qualification in terms of income and perceived job security in a nine-year period based on the German Socio-Economic Panel (SOEP). To compensate for missing data, a combined multiple imputation/weighting approach is adopted.

Suggested Citation

  • Martin Spieß, 2006. "On the Returns to Occupational Qualification in Terms of Subjective and Objective Variables: A GEE-type Approach to the Estimation of Two-Equation Panel Models," Discussion Papers of DIW Berlin 564, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp564
    as

    Download full text from publisher

    File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.44118.de/dp564.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Beth Reboussin & Kung-Yee Liang, 1998. "An estimating equations approach for the LISCOMP model," Psychometrika, Springer;The Psychometric Society, vol. 63(2), pages 165-182, June.
    2. Spiess, Martin & Hamerle, Alfred, 2000. "A comparison of different methods for the estimation of regression models with correlated binary responses," Computational Statistics & Data Analysis, Elsevier, vol. 33(4), pages 439-455, June.
    3. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588.
    4. Gueorguieva R. V. & Agresti A., 2001. "A Correlated Probit Model for Joint Modeling of Clustered Binary and Continuous Responses," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1102-1112, September.
    5. D. B. Dunson, 2000. "Bayesian latent variable models for clustered mixed outcomes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 355-366.
    6. Bengt Muthén & Albert Satorra, 1995. "Technical aspects of Muthén's liscomp approach to estimation of latent variable relations with a comprehensive measurement model," Psychometrika, Springer;The Psychometric Society, vol. 60(4), pages 489-503, December.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Generalized estimating equations; mean and covariance model; multiple imputation; pseudo-score equations; status inconsistency; weighting;

    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:dp564. 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: (Bibliothek). General contact details of provider: http://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 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.

    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.