A Fuzzy clustering approach to the key sectors of the Spanish economy

Abstract

The search for key sectors in an economy has been and still is one of the more recurrent themes in input -output analysis. When using clustering techniques, sectors can only belong to a group, having a particular performance. But, actually, the same sector could be important from different perspectives at the same time, to a different degree. So, a fuzzy clustering approach is needed. In this work we propose a multidimensional approach to classify the productive sectors of the Spanish input -output table for 1995, based on three groups of variables: those related to their productive integration, others measuring their specific weight in the economy and finally some showing their economic dynamic. We also incorporate into the analysis the technological level, which being a categorical variable presents special methodological problems. All these questions are tackled applying a robust and fuzzy clustering analysis, which gives as a result a classification of sectors illustrating the role that each one plays in the Spanish economy.

Applications of cluster analysis to the creation of perfectionism profiles: a comparison of two clustering approaches

“…From the overlapping clusters in not only the current study, but in other studies as well (e.g., Hwang and Thill, 2009 ; Ghosh et al, 2011 ), fuzzy clustering assisted in the understanding of the population structure, and the similarities of subgroups therein. This is in part due to the flexibility in interpreting the clusters and varying degrees of membership that can be shown in fuzzy clustering (Díaz et al, 2006 ; Coppi et al, 2010 ). Like most areas in psychology, perfectionism profiles can be seen as abstract since the profiles will naturally have similar attributes in certain areas.…”

Triangulation Applied to the Intra-European Union Tomato Market

“…e input-output methodology has been applied in various fields, including industry [7][8][9][10][11][12][13], energy [14], water [15,16], price systems [17], structural changes [18,19], and human capital [20], among others. It has also been used to analyze key sectors, such as the work by Haji [21] related to key sectors in Kuwait's productive structure, the article by Cassetti [22] which identifies sectors by transactions in different countries, and the work by Díaz et al [23] who identify key sectors by means of multiplier, diffusion, topological hierarchy, technological level, diffusion of innovation, and polluting capacity.…”

Key sector analysis by IO networks: Evidence from Turkey

“…D Hewings, Michael Sonis, and Rodney Charles Jensen (1988) introduced the concept of fields of influence in order to examine the effects of a technological change. In some studies, the clustering approach is also used to determine the cluster of industries and identify key sectors accordingly (see Stan Czamanski and Luiz Augusto de Q. Ablas, 1979;Sergio Rey and Daniel Mattheis, 2000;Bárbara Díaz, Laura Moniche and Antonio Morillas 2006).…”