Testing for Clustering of Industries - Evidence from micro geographic data - Tobias Scholl; Thomas Brenner (Philipps-University Marburg, Department of Geography, 2011)
We present a new statistical method that describes the localization patterns of industries in a continuous space. The proposed method does not divide space into subunits whereby it is not affected by the Modifiable Areal Unit Problem (MAUP). Our method fulfils all five criteria for a spatial statistical test of localization proposed by Duranton and Overman (2005) and improves them with respect to the significance of its results. Additionally, our test allows inference to the localization of highly clustered firms. Furthermore, the algorithm is efficient in its computation, which eases the usage in research.
Keywords: C40; C60; R12; 330; Spatial concenctration; localization; clusters; MAUP; distance-based measures