IDEAS home Printed from https://ideas.repec.org/a/kap/jgeosy/v4y2002i2d10.1007_s101090200081.html
   My bibliography  Save this article

Analysing regional industrialisation in Jiangsu province using geographically weighted regression

Author

Listed:
  • Yefang Huang

    (Department of Geography and Resource Management, Center for Environmental Policy and Resource Management, Joint Laboratory for Geoinformation Science, The Chinese University of Hong Kong, Shatin, Hong Kong (e-mail: Lucy-huang@cuhk.edu.hk, Yeeleung@cuhk.edu.hk))

  • Yee Leung

    (Department of Geography and Resource Management, Center for Environmental Policy and Resource Management, Joint Laboratory for Geoinformation Science, The Chinese University of Hong Kong, Shatin, Hong Kong (e-mail: Lucy-huang@cuhk.edu.hk, Yeeleung@cuhk.edu.hk))

Abstract

. Industry is the most important sector in the Chinese economy. To identify the spatial interaction between the level of regional industrialisation and various factors, this paper takes Jiangsu province of China as a case study. To unravel the existence of spatial nonstationarity, geographically weighted regression (GWR) is employed in this article. Conventional regression analysis can only produce `average' and `global' parameter estimates rather than `local' parameter estimates which vary over space in some spatial systems. Geographically weighted regression (GWR), on the other hand, is a relatively simple, but useful new technique for the analysis of spatial nonstationarity. Using the GWR technique to study regional industrialisation in Jiangsu province, it is found that there is a significant difference between the ordinary linear regression (OLR) and GWR models. The relationships between the level of regional industrialisation and various factors show considerable spatial variability.

Suggested Citation

  • Yefang Huang & Yee Leung, 2002. "Analysing regional industrialisation in Jiangsu province using geographically weighted regression," Journal of Geographical Systems, Springer, vol. 4(2), pages 233-249, June.
    • Handle: RePEc:kap:jgeosy:v:4:y:2002:i:2:d:10.1007_s101090200081
    DOI: 10.1007/s101090200081
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s101090200081
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s101090200081?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.

    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:kap:jgeosy:v:4:y:2002:i:2:d:10.1007_s101090200081. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.