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The Biggest Myth in Spatial Econometrics

Department of Finance and Economics, McCoy College of Business Administration, Texas State University, 601 University Drive, San Marcos, TX 78666, USA
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.
Econometrics 2014, 2(4), 217-249;
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)
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
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MDPI and ACS Style

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

AMA Style

LeSage JP, Pace RK. The Biggest Myth in Spatial Econometrics. Econometrics. 2014; 2(4):217-249.

Chicago/Turabian Style

LeSage, James P., and R. K. Pace. 2014. "The Biggest Myth in Spatial Econometrics" Econometrics 2, no. 4: 217-249.

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