IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/78264.html
   My bibliography  Save this paper

The spatial autocorrelation problem in spatial interaction modelling: a comparison of two common solutions

Author

Listed:
  • Griffith, Daniel A.
  • Fischer, Manfred M.
  • LeSage, James P.

Abstract

Spatial interaction models of the gravity type are widely used to describe origin-destination flows. They draw attention to three types of variables to explain variation in spatial interactions across geographic space: variables that characterize the origin region of interaction, variables that characterize the destination region of interaction, and variables that measure the separation between origin and destination regions. A violation of standard minimal assumptions for least squares estimation may be associated with two problems: spatial autocorrelation within the residuals, and spatial autocorrelation within explanatory variables. This paper compares a spatial econometric solution with the spatial statistical Moran eigenvector spatial filtering solution to accounting for spatial autocorrelation within model residuals. An example using patent citation data that capture knowledge flows across 257 European regions serves to illustrate the application of the two approaches.

Suggested Citation

  • Griffith, Daniel A. & Fischer, Manfred M. & LeSage, James P., 2016. "The spatial autocorrelation problem in spatial interaction modelling: a comparison of two common solutions," MPRA Paper 78264, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:78264
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/78264/1/MPRA_paper_78264.pdf
    File Function: original version
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chib, Siddhartha & Greenberg, Edward & Winkelmann, Rainer, 1998. "Posterior simulation and Bayes factors in panel count data models," Journal of Econometrics, Elsevier, vol. 86(1), pages 33-54, June.
    2. James P. LeSage & R. Kelley Pace, 2008. "Spatial Econometric Modeling Of Origin-Destination Flows," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 941-967.
    3. James P. LeSage & Manfred M. Fischer & Thomas Scherngell, 2007. "Knowledge spillovers across Europe: Evidence from a Poisson spatial interaction model with spatial effects," Papers in Regional Science, Wiley Blackwell, vol. 86(3), pages 393-421, August.
    4. Daniel Griffith & Yongwan Chun, 2015. "Spatial Autocorrelation in Spatial Interactions Models: Geographic Scale and Resolution Implications for Network Resilience and Vulnerability," Networks and Spatial Economics, Springer, vol. 15(2), pages 337-365, June.
    5. Tamás Krisztin & Manfred M. Fischer, 2015. "The Gravity Model for International Trade: Specification and Estimation Issues," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(4), pages 451-470, December.
    6. Manfred M. Fischer & Daniel A. Griffith, 2008. "Modeling Spatial Autocorrelation In Spatial Interaction Data: An Application To Patent Citation Data In The European Union," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 969-989.
    7. Daniel Griffith, 2009. "Modeling spatial autocorrelation in spatial interaction data: empirical evidence from 2002 Germany journey-to-work flows," Journal of Geographical Systems, Springer, vol. 11(2), pages 117-140, June.
    8. Daniel Griffith & Manfred Fischer, 2013. "Constrained variants of the gravity model and spatial dependence: model specification and estimation issues," Journal of Geographical Systems, Springer, vol. 15(3), pages 291-317, July.
    9. repec:spr:stemec:978-3-7908-2070-6 is not listed on IDEAS
    10. Maurseth, Per Botolf & Verspagen, Bart, 2002. " Knowledge Spillovers in Europe: A Patent Citations Analysis," Scandinavian Journal of Economics, Wiley Blackwell, vol. 104(4), pages 531-545, December.
    11. Griffith, Daniel A., 2007. "Spatial Structure and Spatial Interaction: 25 Years Later," The Review of Regional Studies, Southern Regional Science Association, vol. 37(1), pages 28-38.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Origin-destination flows; Spatial dependence in origin-destination flows; Spatial econometrics; Spatial filtering; Patent citation flows;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:pra:mprapa:78264. 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: http://edirc.repec.org/data/vfmunde.html .

    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.