Modeling industrial location decisions in U.S. counties

Abstract

Given its sound theoretical underpinnings, the Random Utility Maximization-
based conditional logit model (CLM) serves as the principal method for ap-
plied research on industrial location decisions. Studies that implemented
this methodology, however, had to confront the underlying Independence
of Irrelevant Alternatives (IIA) assumption and were unable to fully ac-
commodate this problem. 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 spatial alternatives. The paper also provides an illustration, demonstrat-
ing the advantages of this relation in investigation of location determinants
of new manufacturing plant births in the U.S. counties.

JEL classification: C25, R12, R39.

<<   1   2   3   4   5   >>

More intriguing information