Abstract

http://ssrn.com/abstract=1725503
 
 

References (16)



 
 

Citations (3)



 


 



The Biggest Myth in Spatial Econometrics


James P. LeSage


Texas State University - McCoy College of Business Administration

R. Kelley Pace


Louisiana State University - E.J. Ourso College of Business Administration

December 1, 2010


Abstract:     
There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based on the true partial derivatives for a well-specified spatial regression model. We conclude that this myth may have arisen from past applied work that incorrectly interpreted the model coefficients \emph{as if} they were partial derivatives, or from use of mis-specified models.

Number of Pages in PDF File: 42

Keywords: direct and indirect effects estimates, sensitivity to spatial weights

JEL Classification: C11, C21, C23

working papers series


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Date posted: December 16, 2010  

Suggested Citation

LeSage, James P. and Pace, R. Kelley, The Biggest Myth in Spatial Econometrics (December 1, 2010). Available at SSRN: http://ssrn.com/abstract=1725503 or http://dx.doi.org/10.2139/ssrn.1725503

Contact Information

James P. LeSage (Contact Author)
Texas State University - McCoy College of Business Administration ( email )
Finanace and Economics Department
601 University Drive
San Marcos, TX 78666
United States
512-245-0256 (Phone)
512-245-3089 (Fax)
HOME PAGE: http://www.spatial-econometrics.com
R. Kelley Pace
Louisiana State University - E.J. Ourso College of Business Administration ( email )
Department of Finance
2164 B Patrick F. Taylor Hall
Baton Rouge, LA 70803-6308
United States
(225)-578-6256 (Phone)
(225)-578-9065 (Fax)
HOME PAGE: http://www.spatial-statistics.com
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