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Econometrics 2014, 2(4), 217-249; doi:10.3390/econometrics2040217

The Biggest Myth in Spatial Econometrics

1
Department of Finance and Economics, McCoy College of Business Administration, Texas State University, 601 University Drive, San Marcos, TX 78666, USA
2
Department of Finance, E.J. Ourso College of Business Administration, Louisiana State University, Baton Rouge, LA 70803, USA
*
Author to whom correspondence should be addressed.
Received: 29 September 2014 / Revised: 18 November 2014 / Accepted: 8 December 2014 / Published: 23 December 2014
(This article belongs to the Special Issue Spatial Econometrics)
View Full-Text   |   Download PDF [403 KB, uploaded 23 December 2014]   |  

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 as if they were partial derivatives, or from use of misspecified models. View Full-Text
Keywords: indirect effects; spatial regression estimates; sensitivity to spatial weights indirect effects; spatial regression estimates; sensitivity to spatial weights
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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LeSage, J.P.; Pace, R.K. The Biggest Myth in Spatial Econometrics. Econometrics 2014, 2, 217-249.

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