Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/73087 
Year of Publication: 
2012
Series/Report no.: 
MAGKS Joint Discussion Paper Series in Economics No. 14-2012
Publisher: 
Philipps-University Marburg, Faculty of Business Administration and Economics, Marburg
Abstract: 
More recently, there has been a renewed interest in cluster policies for supporting industrial and regional development. By virtue of the linkage between growth and innovation, R&D intensive industries play a crucial role in cluster development strategies. Empirical cluster research has to contribute to the understanding the process of cluster formation. Some experiences with the use of local spatial methods like local Moran's Ii and Getis-Ord Gi tests in pattern recognition are already available. However, up to now the utilisation of spatial scan techniques in detecting economic clusters is largely ignored (Kang, 2010). In this paper, the performance of the above-mentioned local spatial methods in identifying German R&D clusters is studied. Differences in cluster detection across the tests are traced. In particular, the contribution of Kulldorff's spatial scan test in detecting industry clusters is critically assessed.
Subjects: 
Spatial Clusters
R&D Intensive Industries
Local Spatial Methods
Spatial Scan Test
JEL: 
R12
R15
Document Type: 
Working Paper

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