Location quotients versus spatial autocorrelation in identifying potential cluster regions

Most cluster-based economic development programs use co-location to initially identify the spatial footprint of cluster areas. Geographic proximity (co- location) is a necessary, but not a sufficient, condition for potential clustering activity. Therefore, an assessment of industry location and density patterns becomes the first phase in the identification of potential cluster regions to be included in a cluster driven development policy. This paper compares the use of location quotients and Getis–Ord Gi* in the identification of potential cluster regions in the transportation equipment industry of four states in the Midwestern USA. Also, both location quotients and Gi* are used to classify counties with respect to their concentration of transportation equipment manufacturing.

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