MODELING SPATIAL AUTOCORRELATION IN SPATIAL INTERACTION DATA: AN APPLICATION TO PATENT CITATION DATA IN THE EUROPEAN UNION*
Manfred Fischer and
Daniel A. Griffith
Journal of Regional Science, 2008, vol. 48, issue 5, 969-989
Abstract:
ABSTRACT Spatial interaction models of the gravity type are widely used to model origin–destination flows. They draw attention to three types of variables to explain variation in spatial interactions across geographic space: variables that characterize an origin region of a flow, variables that characterize a destination region of a flow, and finally variables that measure the separation between origin and destination regions. This paper outlines and compares two approaches, the spatial econometric and the eigenfunction‐based spatial filtering approach, to deal with the issue of spatial autocorrelation among flow residuals. An example using patent citation data that capture knowledge flows across 112 European regions serves to illustrate the application and the comparison of the two approaches.
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (61)
Downloads: (external link)
https://doi.org/10.1111/j.1467-9787.2008.00572.x
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jregsc:v:48:y:2008:i:5:p:969-989
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0022-4146
Access Statistics for this article
Journal of Regional Science is currently edited by Marlon G. Boarnet, Matthew Kahn and Mark D. Partridge
More articles in Journal of Regional Science from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().