PROGRESS IN GEOGRAPHY ›› 2007, Vol. 26 ›› Issue (2): 1-13.doi: 10.11820/dlkxjz.2007.02.001

• Original Articles •     Next Articles

Geogr aphical Concentr ation and Agglomer ation of Industr ies: Measur ement and Identification

HE Canfei, PAN Fenghua   

  1. Department of Urban and Regional Planning, Peking University, Beijing 100871
  • Received:2006-09-01 Revised:2007-02-01 Online:2007-03-25 Published:2007-03-25


This paper presents a literature review on the measurement of geographical concentration and agglomeration of industries. Indices of concentration should meet the following criteria: (1) being comparable across industries and spatial scales; (2) taking a unique (or known) value under the null hypothesis that there is no systematic component to the location of the industry;( 3) the significance of the results should be reported where appropriate; and (4) measures should be unbiased with respect to arbitrary changes to the spatial classification and industrial classification. There are many concentration indices, including coefficients of variation, Herfind-ahl index, Hoover coefficient, Entropy index, Theil index and Gini coefficient. Those aggregate measures of geographical concentration, however, ignore the impact of plant distributions on geographical concentration of industries. Based on the model of plant locational choices, economists propose agglomeration indices designated to measure the excess of raw geographic concentration on productive concentration. However, both concentration and agglomeration measures only describe the location of industries on a single scale based on administrative regions. Distance- based methods, such as Ripley’s K function, serve to describe the spatial structure of industries at different scales at the same time. Existing literature also attempts to propose quantitative methods to identify industrial clusters. Location quotients and standardized locational quotients, spatial and industrial linkages, factor analysis and graphic methods based on input output have been applied. The identification of industrial clusters not only requires the consideration of industrial linkage, but also geographical proximity.

Key words: industry agglomeration, industry cluster, industry concentration