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The Impact of an Urban Growth Boundary on Land Development in Knox County, Tennessee: A Comparison of Two-Stage Probit Least Squares and Multilayer Neural Network Models

Published online by Cambridge University Press:  28 April 2015

Seong-Hoon Cho ,
Olufemi A. Omitaomu ,
Neelam C. Poudyal  and
David B. Eastwood
Seong-Hoon Cho
Affiliation:
Department of Agricultural Economics, the University of Tennessee
Olufemi A. Omitaomu
Affiliation:
Computational Sciences and Engineering Division at Oak Ridge National Laboratory
Neelam C. Poudyal
Affiliation:
Department of Agricultural Economics, the University of Tennessee
David B. Eastwood
Affiliation:
Department of Agricultural Economics, the University of Tennessee
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Abstract

The impact of an urban growth boundary (UGB) on land development in Knox County, TN is estimated via two-stage probit and neural-network models. The insignificance of UGB variable in the two-stage probit model and more visible development patterns in the western part of Knoxville and the neighboring town of Farragut during the post-UGB period in both models suggest that the UGB has not curtailed urban sprawl. Although the network model is found to be a viable alternative to more conventional discrete choice approach for improving the predictability of land development, it is at the cost of evaluating marginal effects.

Keywords

land developmentmultilayer neural networktwo-stage probit least squaresC35R14
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 39 , Issue 3 , December 2007 , pp. 701 - 717
Copyright
Copyright © Southern Agricultural Economics Association 2007

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