IDEAS home Printed from
   My bibliography  Save this paper

A new information theoretical measure of global and local spatial association


  • Karlström, Anders
  • Ceccato, Vania


In this paper a new measure of spatial association, the S statistics, is developed. The proposed measure is based on information theory by defining a spatially weighted information measure (entropy measure) that takes the spatial configuration into account. The proposed S-statistics has an intuitive interpretation, and furthermore fulfills properties that are expected from an entropy measure. Moreover, the S statistics is a global measure of spatial association that can be decomposed into Local Indicators of Spatial Association (LISA). This new measure is tested using a dataset of employment in the culture sector that was attached to the wards over Stockholm County and later compared with the results from current global and local measures of spatial association. It is shown that the proposed S statistics share many properties with Moran's I and Getis-Ord Gi statistics. The local Si statistics showed significant spatial association similar to the Gi statistic, but has the advantage of being possible to aggregate to a global measure of spatial association. The statistics can also be extended to bivariate distributions. It is shown that the commonly used Bayesian empirical approach can be interpreted as a Kullback-Leibler divergence measure. An advantage of S-statistics is that this measure select only the most robust clusters, eliminating the contribution of smaller ones composed by few observations and that may inflate the global measure.

Suggested Citation

  • Karlström, Anders & Ceccato, Vania, 2000. "A new information theoretical measure of global and local spatial association," MPRA Paper 6848, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:6848

    Download full text from publisher

    File URL:
    File Function: original version
    Download Restriction: no

    References listed on IDEAS

    1. Snickars, Folke & Weibull, Jorgen W., 1977. "A minimum information principle : Theory and practice," Regional Science and Urban Economics, Elsevier, vol. 7(1-2), pages 137-168, March.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Global and local measure of spatial association; LISA; S-statistics; Gi statistics; Moran's I; Kullback-Leibler divergence;

    JEL classification:

    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns


    Access and download statistics


    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:pra:mprapa:6848. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter). General contact details of provider: .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.