IDEAS home Printed from https://ideas.repec.org/a/ect/emjrnl/v9y2006i1p76-97.html
   My bibliography  Save this article

Simulation-based tests for heteroskedasticity in linear regression models: Some further results

Author

Listed:
  • L. G. Godfrey
  • C. D. Orme
  • J. M. C. Santos Silva

Abstract

As shown by the results of Dufour, Khalaf, Bernard and Genest (2004, Journal of Econometrics 122, 317--347), exact tests for heteroskedasticity in linear regression models can be obtained, by using Monte Carlo (MC) techniques, if either (i) it is assumed that the true form of the error distribution under homoskedasticity is known, or (ii) the null hypothesis specifies both homoskedasticity and the form of the error distribution. Non-parametric bootstrap tests of homoskedasticity alone are only asymptotically valid, but do not require specification of the error law. Since information about the precise form of the error distribution is not often available to applied workers, two questions merit attention. First, if the primary purpose is to check for heteroskedasticity, how sensitive are MC tests to incorrect assumptions/claims about the error distribution? Second, what can be said about the relative merits of MC tests and non-parametric bootstrap tests? Theoretical results relevant to these two questions are derived using asymptotic analysis and evidence is provided from simulation experiments. Copyright 2006 Royal Economic Society

Suggested Citation

  • L. G. Godfrey & C. D. Orme & J. M. C. Santos Silva, 2006. "Simulation-based tests for heteroskedasticity in linear regression models: Some further results," Econometrics Journal, Royal Economic Society, vol. 9(1), pages 76-97, March.
    • Handle: RePEc:ect:emjrnl:v:9:y:2006:i:1:p:76-97
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. E. Fe-Rodríguez & C. Orme, 2006. "On the sensitivity of Kernel-based Conditional Moment Tests to Unconsidered Local Alternatives," Economics Discussion Paper Series 0606, Economics, The University of Manchester.
    2. Chris D. Orme & Takashi Yamagata, 2014. "A Heteroskedasticity-Robust F -Test Statistic for Individual Effects," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 431-471, August.
    3. José Murteira & Esmeralda Ramalho & Joaquim Ramalho, 2013. "Heteroskedasticity testing through a comparison of Wald statistics," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 12(2), pages 131-160, August.
    4. José Murteira & Esmeralda Ramalho & Joaquim Ramalho, 2011. "Heteroskedasticity Testing Through Comparison of Wald-Type Statistics," GEMF Working Papers 2011-05, GEMF, Faculty of Economics, University of Coimbra.
    5. Gignac, Gilles E. & Zajenkowski, Marcin, 2020. "The Dunning-Kruger effect is (mostly) a statistical artefact: Valid approaches to testing the hypothesis with individual differences data," Intelligence, Elsevier, vol. 80(C).
    6. James G. MacKinnon, 2007. "Bootstrap Hypothesis Testing," Working Paper 1127, Economics Department, Queen's University.

    More about this item

    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:ect:emjrnl:v:9:y:2006:i:1:p:76-97. 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: Wiley-Blackwell Digital Licensing or Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/resssea.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.