Economic development strategies and methods for identifying leading industries and industrial clusters

Thomas J. Webster

International Journal of Economics and Business Research, 2013, vol. 5, issue 1, 55-74

Abstract: This paper reviews several popular economic development strategies and discusses the practical problem of identifying leading industries and innovation clusters for government regulatory and financial support. Although there is no substitute for in-depth industry-by-industry analysis, several statistical techniques are available that can assist in the identification process, including principal component analysis, k-means clustering, hierarchical clustering, medoid partitioning and fuzzy clustering. The Republic of Indonesia is used as a case study to illustrate the strengths and weakness of each of these procedures.

Keywords: economic development; export-led growth; fuzzy clustering; hierarchical clustering; Indonesia; innovation clusters; k-means clustering; leading industries; medoid partitioning; principal component analysis; PCA; exports; industrial clusters. (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=50642 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijecbr:v:5:y:2013:i:1:p:55-74

Access Statistics for this article

More articles in International Journal of Economics and Business Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().