Key Sectors, Industrial Clustering and Multivariate Outliers
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.
Volume (Year): 20 (2008)
Issue (Month): 1 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/CESR20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/CESR20|
When requesting a correction, please mention this item's handle: RePEc:taf:ecsysr:v:20:y:2008:i:1:p:57-73. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If references are entirely missing, you can add them using this form.