IDEAS home Printed from https://ideas.repec.org/p/cor/louvco/2004076.html
   My bibliography  Save this paper

A full heteroscedastic one-way error components model allowing for unbalanced panel : Pseudo-maximum likelihood estimation and specification testing

Author

Listed:
  • LEJEUNE, Bernard

Abstract

This paper proposes an extension of the standard one-way error components model allowing for heteroscedasticity in both the individual-specific and the general error terms, as well as for unbalanced panel. Onthe grounds of its robustness to distributional misspecification, its robustness to possible misspecification of the assumed scedastic structure of the data, its computational convenience and its potential efficiency, we argue for estimating this model by Gaussian pseudo-maximum likelihood of order two. Further, we review how, taking advantage of the powerful m-testing framework,the correct specification of the prominent aspects of the model may be tested. So are surveyed potentially useful nested, non-nested, Hausman and information matrix type diagnostic tests of both the mean and the variance specification of the model. Finally, we illustrate the practical relevance of our proposed model and estimation and diagnostic testing procedures through an empirical example in the production analysis field.

Suggested Citation

  • LEJEUNE, Bernard, 2004. "A full heteroscedastic one-way error components model allowing for unbalanced panel : Pseudo-maximum likelihood estimation and specification testing," CORE Discussion Papers 2004076, Universit√© catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2004076
    as

    Download full text from publisher

    File URL: https://uclouvain.be/en/research-institutes/immaq/core/dp-2004.html
    Download Restriction: no

    More about this item

    Keywords

    error components model; heteroscedasticity; unbalanced panel data; pseudo-maximum likelihood estimation; m-testing;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    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:cor:louvco:2004076. 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: (Alain GILLIS). General contact details of provider: http://edirc.repec.org/data/coreebe.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.

    We have no 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.

    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.