IDEAS home Printed from https://ideas.repec.org/p/kob/dpaper/dp2025-03.html
   My bibliography  Save this paper

Testing for Spatial Autocorrelation in Stata

Author

Listed:
  • Keisuke Kondo

    (Research Institute of Economy, Trade and Industry and Research Institute for Economics and Business Administration, Kobe University, JAPAN)

Abstract

This paper introduces the new Stata command moransi, which allows users to easily compute global and local Moran's I statistics in Stata. The fundamental feature of the moransi command is that the spatial weight matrix is constructed internally within a sequence of the program code. The additional information required in the dataset to implement this command are the latitude and longitude of regions. This paper presents two applied examples of the moransi command to deepen the understanding of global and local spatial autocorrelation.

Suggested Citation

  • Keisuke Kondo, 2025. "Testing for Spatial Autocorrelation in Stata," Discussion Paper Series DP2025-03, Research Institute for Economics & Business Administration, Kobe University.
  • Handle: RePEc:kob:dpaper:dp2025-03
    as

    Download full text from publisher

    File URL: https://www.rieb.kobe-u.ac.jp/academic/ra/dp/English/DP2025-03.pdf
    File Function: First version, 2025
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Moransi; Moran's I; Global indicators of spatial association; Local indicators of spatial association; Spatial lag;
    All these keywords.

    JEL classification:

    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

    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:kob:dpaper:dp2025-03. 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: Office of Promoting Research Collaboration, Research Institute for Economics & Business Administration, Kobe University (email available below). General contact details of provider: https://edirc.repec.org/data/rikobjp.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.