IDEAS home Printed from https://ideas.repec.org/p/ris/smuesw/2018_012.html

Diagnostic Tests for Homoskedasticity in Spatial Cross-Sectional or Panel Models

Author

Listed:
  • Badi Baltagi

    (Syracuse University)

  • Alain Pirotte

    (CRED, University Paris II Pantheon-Assas)

  • Zhenlin Yang

    (School of Economics, Singapore Management University)

Abstract

We propose tests for homoskedasticity in spatial econometric models, based on joint or concentrated score functions and an Outer-Product-of-Martingale-Difference (OPMD) estimate of the variance of the joint or concentrated score functions. Versions of these tests robust against non-normality are also given. Asymptotic properties of the proposed tests are formally examined using a cross-section model and a panel model with fixed effects. Monte Carlo results show that the proposed tests based on the concentrated score function have good finite sample properties. Finally, the generality of the proposed approach in constructing tests for homoskedasticity is further demonstrated using a spatial dynamic panel data model with short panels.

Suggested Citation

  • Badi Baltagi & Alain Pirotte & Zhenlin Yang, 2018. "Diagnostic Tests for Homoskedasticity in Spatial Cross-Sectional or Panel Models," Economics and Statistics Working Papers 12-2018, Singapore Management University, School of Economics.
    • Handle: RePEc:ris:smuesw:2018_012
    as

    Download full text from publisher

    File URL: https://ink.library.smu.edu.sg/soe_research/2179/
    File Function: Full text
    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. is not listed on IDEAS
    2. Francesco Giordano & Marcella Niglio & Maria Lucia Parrella, 2024. "Testing Spatial Dynamic Panel Data Models with Heterogeneous Spatial and Regression Coefficients," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(5), pages 771-799, September.
    3. Baltagi, Badi H. & Liu, Long, 2025. "Testing for spatial lag dependence and homoskedasticity in a random effects panel data model," Economics Letters, Elsevier, vol. 254(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    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:ris:smuesw:2018_012. 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: Lovein Teo (email available below). General contact details of provider: https://edirc.repec.org/data/sesmusg.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.