IDEAS home Printed from https://ideas.repec.org/a/taf/regstd/v48y2020i4p727-743.html
   My bibliography  Save this article

Industrial Location and Spatial Dependence: An Empirical Application

Author

Listed:
  • Daniel Liviano
  • Josep-Maria Arauzo-Carod

Abstract

Liviano D. and Arauzo-Carod J.-M. Industrial location and spatial dependence: an empirical application, Regional Studies. This paper tries to resolve some of the main shortcomings in the empirical literature on location decisions for new plants, that is, spatial effects and over-dispersion. Spatial effects are omnipresent, being a source of over-dispersion in the data as well as a factor shaping the functional relationship between the variables that explain a firm's location decisions. Using count data models, empirical researchers have dealt with over-dispersion and excess zeros by developments of the Poisson regression model. This study aims to take this a step further by adopting Bayesian methods and models in order to tackle the excess of zeros, spatial and non-spatial over-dispersion, and spatial dependence simultaneously. Data for Catalonia (Spain) are used and location determinants are analysed to that end. The results show that spatial effects are determinant. Additionally, over-dispersion is decomposed into an unstructured independently and identically distributed (i.i.d.) effect and a spatially structured effect.

Suggested Citation

  • Daniel Liviano & Josep-Maria Arauzo-Carod, 2020. "Industrial Location and Spatial Dependence: An Empirical Application," Regional Studies, Taylor & Francis Journals, vol. 48(4), pages 727-743, July.
    • Handle: RePEc:taf:regstd:v:48:y:2020:i:4:p:727-743
    DOI: 10.1080/00343404.2012.675054
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00343404.2012.675054
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00343404.2012.675054?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. repec:tur:wpaper:10 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huasheng Song & Min Zhang & Ruqu Wang, 2016. "Amenities and spatial talent distribution: evidence from the Chinese IT industry," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 9(3), pages 517-533.
    2. Minghao Li & Stephan J. Goetz & Mark Partridge & David A. Fleming, 2016. "Location determinants of high-growth firms," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 28(1-2), pages 97-125, January.
    3. Sara C. Santos Cruz & Aurora A. C. Teixeira, 2021. "Spatial analysis of new firm formation in creative industries before and during the world economic crisis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(2), pages 385-413, October.
    4. Andrzej CieĊšlik, 2013. "Determinants of the Location of Foreign Firms in P olish Regions: Does Firm Size Matter?," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 104(2), pages 175-193, April.
    5. Chandra R. Bhat & Rajesh Paleti & Palvinder Singh, 2014. "A Spatial Multivariate Count Model For Firm Location Decisions," Journal of Regional Science, Wiley Blackwell, vol. 54(3), pages 462-502, June.
    6. Nielsen, Hana, 2021. "Coal and Sugar: The Black and White Gold of Czech Industrialization (1841-1863)," Lund Papers in Economic History 229, Lund University, Department of Economic History.

    More about this item

    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:taf:regstd:v:48:y:2020:i:4:p:727-743. 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.

    If CitEc recognized a bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CRES20 .

    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.