Industrial Location Modeling: Extending the Random Utility Framework

20 Pages Posted: 4 Apr 2004

See all articles by Paulo Guimarães

Paulo Guimarães

University of Minho - Department of Economics

Octávio Figueiredo

Universidade do Porto - Faculdade de Economia (FEP)

Douglas P. Woodward

University of South Carolina

Abstract

Given sound theoretical underpinnings, the random utility maximization?based conditional logit model (CLM) serves as the principal method for applied research on industrial location decisions. Studies that implement this methodology, however, confront several problems, notably the disadvantages of the underlying Independence of Irrelevant Alternatives (IIA) assumption. This paper shows that by taking advantage of an equivalent relation between the CLM and Poisson regression likelihood functions one can more effectively control for the potential IIA violation in complex choice scenarios where the decision maker confronts a large number of narrowly defined spatial alternatives. As demonstrated here our approach to the IIA problem is compliant with the random utility (profit) maximization framework.

Suggested Citation

de Freitas Guimarães, Paulo and Figueiredo, Octavio and Woodward, Douglas P., Industrial Location Modeling: Extending the Random Utility Framework. Available at SSRN: https://ssrn.com/abstract=513698

Paulo De Freitas Guimarães (Contact Author)

University of Minho - Department of Economics

Braga 4710-057
Portugal
+351 53 604215 (Phone)

Octavio Figueiredo

Universidade do Porto - Faculdade de Economia (FEP) ( email )

Rua Roberto Frias
s/n
Porto, 4200-464
Portugal

Douglas P. Woodward

University of South Carolina ( email )

The Francis M. Hipp Building
1705 College Street
Columbia, SC 29208
United States
803-777-2510 (Phone)
803-777-9344 (Fax)

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