IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v256y2025ics0165176525004240.html
   My bibliography  Save this article

Bayesian analysis of spatial panel Durbin model with convex combinations of different spatial weight matrices

Author

Listed:
  • Wang, Jiajia

Abstract

This study examines the spatial panel Durbin model with convex combinations of different spatial weight matrices. These combinations are present not only in the spatial lag of the dependent variable but also in the spatial lags of the explanatory variables. Moreover, the combination coefficients in the spatially lagged dependent and explanatory variables may differ. An adaptive MCMC sampling method is used for the Bayesian estimation of this model. Additionally, this study explores model selection issues using the posterior Bayesian information criterion.

Suggested Citation

  • Wang, Jiajia, 2025. "Bayesian analysis of spatial panel Durbin model with convex combinations of different spatial weight matrices," Economics Letters, Elsevier, vol. 256(C).
  • Handle: RePEc:eee:ecolet:v:256:y:2025:i:c:s0165176525004240
    DOI: 10.1016/j.econlet.2025.112587
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176525004240
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econlet.2025.112587?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

    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:eee:ecolet:v:256:y:2025:i:c:s0165176525004240. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.