IDEAS home Printed from https://ideas.repec.org/p/kud/kuiedp/1905.html

The analysis of marked and weighted empirical processes of estimated residuals

Author

Listed:
  • Vanessa Berenguer-Rico

    (Department of Economics, University of Oxford, UK)

  • Soeren Johansen

    (Department of Economics, University of Copenhagen, Denmark)

  • Bent Nielsen

    (Department of Economics, University of Oxford, UK)

Abstract

An extended and improved theory is presented for marked and weighted empirical processes of residuals of time series regressions. The theory is motivated by 1-step Huber-skip estimators, where a set of good observations are selected using an initial estimator and an updated estimator is found by applying least squares to the selected observations. In this case, the weights and marks represent powers of the regressors and the regression errors, respectively. The inclusion of marks is a non-trivial extention to previous theory and requires refined martingale arguments.

Suggested Citation

  • Vanessa Berenguer-Rico & Soeren Johansen & Bent Nielsen, 2019. "The analysis of marked and weighted empirical processes of estimated residuals," Discussion Papers 19-05, University of Copenhagen. Department of Economics.
    • Handle: RePEc:kud:kuiedp:1905
    as

    Download full text from publisher

    File URL: https://www.economics.ku.dk/research/publications/wp/dp_2019/1905.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Jiao, Xiyu & Pretis, Felix & Schwarz, Moritz, 2024. "Testing for coefficient distortion due to outliers with an application to the economic impacts of climate change," Journal of Econometrics, Elsevier, vol. 239(1).
    2. Vanessa Berenguer-Rico & Soeren Johansen & Bent Nielsen, 2019. "Uniform Consistency of Marked and Weighted Empirical Distributions of Residuals," Discussion Papers 19-09, University of Copenhagen. Department of Economics.
    3. Xiyu Jiao & Felix Pretis, 2022. "Testing the Presence of Outliers in Regression Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1452-1484, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    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:kud:kuiedp:1905. 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: Thomas Hoffmann (email available below). General contact details of provider: https://edirc.repec.org/data/okokudk.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.