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 (colocation) 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 G(i)* in the identification of potential cluster regions in the transportation equipment industry of four states in the Midwestern USA. Also, both location quotients and G(i)* are used to classify counties with respect to their concentration of transportation equipment manufacturing.