Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/30145
Authors: 
Kosfeld, Reinhold
Eckey, Hans-Friedrich
Lauridsen, Jørgen
Year of Publication: 
2009
Series/Report no.: 
Joint discussion paper series in economics 2009,16
Abstract: 
Traditional measures of spatial industry concentration are restricted to given areal units. They do not make allowance for the fact that concentration may be differently pronounced at various geographical levels. Methods of spatial point pattern analysis allow to measure industry concentration at a continuum of spatial scales. While common distance based methods are well applicable for sub-national study areas, they become inefficient in measuring concentration at various levels within industrial countries. This particularly applies in testing for conditional concentration where overall manufacturing is used as a reference population. Using Ripley’s K function approach to second-order analysis, we propose a subsample similarity test as a feasible testing approach for establishing conditional clustering or dispersion at different spatial scales. For measuring the extent of clustering and dispersion, we introduce a concentration index of the style of Besag’s (1977) L function. By contrast to Besag’s L function, the new index can be employed to measure deviations of observed from general spatial point patterns. The K function approach is illustratively applied to measuring and testing industry concentration in Germany.
Subjects: 
Spatial concentration
clustering
dispersion
spatial point pattern analysis
K function
JEL: 
C46
L60
L70
R12
Document Type: 
Working Paper

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