IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v28y2024i4p583-604n1002.html
   My bibliography  Save this article

Estimation and testing of the factor-augmented panel regression models with missing data

Author

Listed:
  • Xiao Difa

    (Shanghai Normal University, Shanghai 200234, China)

  • Wang Lu

    (Shanghai Normal University, Shanghai 200234, China)

  • Wu Jianhong

    (Shanghai Normal University, Shanghai 200234, China)

Abstract

This paper focuses on the factor-augmented panel regression models with missing data and individual-varying factors. A so-called CCEM estimator for the slope coefficient is proposed and its asymptotic properties are investigated under some regularity conditions. Furthermore, a joint test statistic is constructed for serial correlation and heteroscedasticity in the idiosyncratic errors. Under the null hypothesis, the test statistic can be shown to be asymptotically chi-square distributed. Monte Carlo simulation results show that the proposed estimator and test statistic have desired performance in finite samples.

Suggested Citation

  • Xiao Difa & Wang Lu & Wu Jianhong, 2024. "Estimation and testing of the factor-augmented panel regression models with missing data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(4), pages 583-604.
    • Handle: RePEc:bpj:sndecm:v:28:y:2024:i:4:p:583-604:n:1002
    DOI: 10.1515/snde-2022-0042
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/snde-2022-0042
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/snde-2022-0042?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    estimation; factor-augmented regression models; individual-varying factors; missing data; test;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

    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:bpj:sndecm:v:28:y:2024:i:4:p:583-604:n:1002. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.