Key Sectors, Industrial Clustering and Multivariate Outliers

Antonio Morillas () and Barbara Diaz

Economic Systems Research, 2008, vol. 20, issue 1, 57-73

Abstract: In this paper a reflection is made on the problems that can arise in key sector analysis and industrial clustering, due to the usual presence of outliers when using multidimensional data related to the sectors in an input-output table. Multidimensional outliers are considered as being not only linked to the low number of clusters usually observed in this kind of study, but probably causing invalid results in most of the works involving multivariate statistical techniques, such as cluster and factor analysis. Actually, by comparing the key sectors of the Spanish economy obtained in Diaz et al. (2006) to the ones we get taking into account the problem the outliers pose, one can realize they greatly distort the results. On the other hand, it is shown that identification of outliers can be considered as a good and new procedure to help select the most important sectors in an economy.

Keywords: Key sectors; industrial clustering; multidimensional outliers; input-output analysis; Spanish economy (search for similar items in EconPapers)
Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09535310801890698 (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:taf:ecsysr:v:20:y:2008:i:1:p:57-73

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CESR20

DOI: 10.1080/09535310801890698

Access Statistics for this article

Economic Systems Research is currently edited by Bart Los and Manfred Lenzen

More articles in Economic Systems Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().