Detecting Spatial Clustering Using a Firm-Level Index

We present a new statistical method that detects industrial clusters at a firm level. The proposed method does not divide space into subunits whereby it is not affected by the Modifiable Areal Unit Problem (MAUP). Our metric differs both in its calculation and interpretation from existing distance-based metrics and shows four central properties that enable its meaningful usage for cluster analysis. The method fulfills all five criteria for a test of localization proposed by Duranton and Overman (2005).