Detecting agglomeration processes using space–time clustering analyses

Abstract

Although spatial concentration is understood as the premise of agglomeration economies, it hardly observes the changing aspect of externalities. Based on previous studies in which space–time clustering was observed during the initial stage of the product life cycle and sudden changes of historic accident and discovery, the study hypothesizes that space–time clustering better represents the occurring agglomeration economies than spatial concentration alone. For the empirical test, two methods, the space–time K-function and Kulldorff’s scan statistic, were applied using the ES-202 data of the Columbus MSA. The study discovered that knowledge-based industries represent the agglomeration process due to the product life cycle and sudden change, and that restructuring of industries, from traditional manufacturing industries to knowledge-based industries, is taking place in the study area. In addition, using the space–time K-function, the study identified the threshold of space–time clustering in which the agglomeration process is taking place.