Accounting for Spatial Error Correlation in the 2004 Presidential Popular Vote
AbstractOne problem with describing election vote shares using ordinary least squares (OLS) is that it ignores the possible presence of spatial error correlation, whereby the errors are correlated in a systematic manner over space. This omission can bias OLS standard errors. We examine the 2004 presidential county vote outcome using OLS and a spatial error model (SEM) that accounts for spatial autocorrelation in the error structure. We find that spatial error correlation is present, that the SEM is superior to OLS for making inferences, and that several factors deemed important to the 2004 election outcome are not significant once the spatial error autocorrelation is taken into account.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by in its journal Public Finance Review.
Volume (Year): 35 (2007)
Issue (Month): 4 (July)
Contact details of provider:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Le, Canh Quang & Li, Dong, 2008. "Double-Length Regression tests for testing functional forms and spatial error dependence," Economics Letters, Elsevier, vol. 101(3), pages 253-257, December.
- Robert Lawson & Todd Nesbit, 2013. "Alchian and Allen Revisited: Law Enforcement and the Price of Weed," Atlantic Economic Journal, International Atlantic Economic Society, vol. 41(4), pages 363-370, December.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (SAGE Publications).
If references are entirely missing, you can add them using this form.