Spatial point pattern analysis and industry concentration

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: MAGKS Joint Discussion Paper Series in Economics ; No. 2009,16

Classification and Topics

• Classification: Wirtschaft ; Specific Distributions; Specific Statistics ; Industry Studies: Manufacturing: General ; Industry Studies: Primary Products and Construction: General ; Size and Spatial Distributions of Regional Economic Activity
• Subject: Spatial concentration ; clustering ; dispersion ; spatial point pattern analysis ; K function

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Kosfeld, Reinhold ; Eckey, Hans-Friedrich ; Lauridsen, Jørgen
• Event: Veröffentlichung
• (who): Philipps-University Marburg, Faculty of Business Administration and Economics
• (where): Marburg
• (when): 2009

Further information

• Handle: http://hdl.handle.net/10419/30145
• Last update: 10.03.2025, 11:46 AM CET