Detecting Spatial Clustering Using a Firm-Level Index

Arbeitspapier

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).

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Working Papers on Innovation and Space ; No. 02.12

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Econometric and Statistical Methods: Special Topics: General ; Mathematical Methods; Programming Models; Mathematical and Simulation Modeling: General ; Size and Spatial Distributions of Regional Economic Activity
• Thema: Spatial concentration ; localization ; clusters ; MAUP ; distance-based measures

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Scholl, Tobias ; Brenner, Thomas
• Ereignis: Veröffentlichung
• (wer): Philipps-University Marburg, Department of Geography
• (wo): Marburg
• (wann): 2013

Weitere Informationen

• Handle: http://hdl.handle.net/10419/111878
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ