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Spatial Point Pattern Analysis and Industry Concentration
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...
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| Опубліковано в:: | MAGKS - Joint Discussion Paper Series in Economics (Band 16-2009) |
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| Автори: | , , |
| Формат: | Arbeit |
| Мова: | англійська |
| Опубліковано: |
Philipps-Universität Marburg
2009
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| Предмети: | |
| Онлайн доступ: | PDF-повний текст |
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| Резюме: | 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 distancebased
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. |
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| ISSN: | 1867-3678 |
| DOI: | 10.17192/es2023.0230 |