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Last Updated 17 June 2006
Background
This page provides workshop materials from the training session: Regional Industry Cluster Analysis Using Spatial Concepts, organized for ACCRA by Professors Edward Feser (University of Illinois at Urbana-Champaign) and Stuart Sweeney (University of California at Santa Barbara). The one-day training session was held in Charlotte, North Carolina, on 7 June 2006, during ACCRA's 46th Annual Conference.
The concept of Exploratory Spatial Economic Base Analysis (ESEBA) was introduced in the session as a useful framework for designing and conducting quantitative industry cluster analyses in support of economic development planning and policy making. ESEBA is a set of concepts and tools designed to effectively join new exploratory spatial analysis (ESDA) techniques with traditional regional economic analysis approaches. Quantitative industry cluster analysis itself is best viewed as a type of ESEBA.
The materials on this page describe industry cluster analysis techniques practitioners can use to investigate economic interdependence along two dimensions: the functional as revealed in product value chains and the spatial through the study of industrial location and geographic clustering. The techniques are implemented with GeoDa software, a user-friendly, windows-based exploratory spatial data analysis package developed by Professor Luc Anselin at the University of Illinois at Urbana-Champaign.
Our approach does not view industry cluster analysis as offering a single "best" methodology for finding a region's competitive strengths. Rather, it sees industry cluster analysis as a highly flexible mode of inquiry that an economic development organization can use—more or less continously—to better understand its jurisdiction's economic characteristics; position in larger regional, national and global economies; emerging growth trajectory; and economic development planning options.
NOTE: Regional industry cluster studies typically involve much more than quantitative analysis of secondary data. The most effective studies use multiple methods—including secondary data analysis, business and stakeholder interviews, surveys and focus groups—to investigate regional economic trends and identify issues needing development policy attention. Guy Hagen of Innovation Insight has organized training for ACCRA on qualitative methods applied to industry cluster studies. A copy of some of his recent slides are available here.
Slides
Module/Training Session Overview
Module 2: Analyzing Industrial Interdependence
Module 3: Conceptualizing Space
Module 4: Space as a Container
Module 5: Space as an Indicator
Module 6: Applications: Analysis of US Value Chain Geography
Module 7: Applications: Analysis of Value Chain Co-Location
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Datasets
Datasets for experimenting with the methods and techniques in GeoDa are available for workshop registrants. Please send an email request to Edward Feser at feser@uiuc.edu.
Reference Maps. Maps of Bureau of Economic Analysis CEA areas and example custom regions aggregated for an analysis of motor vehicles value chain clustering.
An Updated Set of Benchmark Value Chain Clusters for the United States, 1997. An Excel file containing the detailed value chain cluster definitions.
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Readings
Benchmark value chain industry clusters for applied regional research. Describes the methodology behind the definition of the industry value chain templates used in the workshop.
A descriptive analysis of discrete U.S. industrial complexes. Presents an analysis of the clustering of U.S. value chains using the same conceptual approach presented in the workshop, but a slightly different methodology.
Making sense of clusters: Regional competitiveness and economic development. A recent paper by Joe Cortright for the Metropolitan Policy Program of the Brookings Institution. An extensive review of the cluster literature and discussion of basic concepts and analytical approaches.
Cluster analysis as a mode of inquiry. Discusses cluster analysis as an exploratory regional analysis technique and means of engaging economic development stakeholders in policy design and decisionmaking.
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