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

Economic Systems Research

Volumn 18, Issue 3, 2006, Pages 299-318

  Díaz, Bárbara ^a   Moniche, Laura ^b   Morillas, Antonio ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF MÁLAGA   (Spain)

Author keywords

Fuzzy clustering; Input output analysis; Key sectors; Spanish economy

Indexed keywords

CLUSTER ANALYSIS; ECONOMETRICS; FUZZY MATHEMATICS; INPUT-OUTPUT ANALYSIS; PRODUCTIVITY;

EURASIA; EUROPE; SOUTHERN EUROPE; SPAIN;

EID: 33748100899     PISSN: 09535314     EISSN: 14695758     Source Type: Journal    
DOI: 10.1080/09535310600844375     Document Type: Article

References (91)

1. Abbott, T. and Andrews, S.(1990) The classification of manufacturing industries: An input based clustering of activity. In Discussion Paper CES 90-7. Washington DC: U.SH Census Bureau. Available at: http://www.ces.census.gov/ paper.php?paper=100140&PHPSESSID=838fec06e9652892337cde662d45ed5a
2. Aroche-Reyes, F. (2002) Structural transformations and important coefficients in the North American economies Economic Systems Research, 14, pp. 257-273.
3. Augustinovics, M.(1970) Methods of international and intertemporal comparison of structure. In Contributions to Input-Output Analysis. Amsterdam: North Holland.
4. Beynon, M. and Munday, M. and Roberts, A. (2005) Ranking sectors using fuzzy output multipliers Economic Systems Research, 17, pp. 237-253.
5. Bezdek, J.(1981) Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Plenum.
6. Blin, J. and Cohen, C. (1977) Technological similarity and aggregation in input-output systems Review of Economics and Statistics, 59, pp. 82-91.
7. Broersma, L. (2001) The role of services in innovative clusters. Discussion Paper within the framework of the Research Programme Structural Information; Provision on Innovation in Services (SIID) for the Ministry of Economic Affairs, Directorate for General Technology Policy. Available at: http://www.ggdc.net/pub/SIIDp_papers/ innovative_clusters.pdf
8. Cabrer, B. and Contreras, D. and Miravete, E. (1991) Aggregation in input-output tables: How to select the best cluster linkage Economic Systems Research, 3, pp. 99-109.
9. Cai, J. and Leung, P. (2004) Linkage measures: A revisit and a suggested alternative Economic Systems Research, 16, pp. 65-85.
10. Campbell, J. (1975) Application of graph theoretic analysis to interindustry relationships Regional Science and Urban Economics, 5, pp. 91-106.
11. Cella, G. (1984) The input-output measurement of interindustry linkages Oxford Bulletin of Economics and Statistics, 46, pp. 73-83.
12. Chenery, H. and Watanabe, T. (1958) International comparison of the structure of production Econometrica, 26, pp. 487-521.
13. Chiu, T. and Fang, D. and Chen, J. and Wang, Y. and Jeris, C. (2001) A robust and scalable clustering algorithm for mixed type attributes in large database environment Proceedings of the Seventh ACM SIGMOD International Conference on Knowledge Discovery and Data Mining, pp. 263.
14. Czamanski, S.(1974) Study of Clustering of Industries. Halifax: Institute of Public Affairs, Dalhousie University.
15. Dave, R. and Sen, S. (2002) Robust fuzzy clustering of relational data IEEE Transactions on Fuzzy Systems, 10, pp. 713-727.
16. DeBresson, C. and Hu, X.(1999) Identifying clusters of innovative activity: A new approach and a toolbox. In OECD, Boosting Innovation: The Cluster Approach. Paris: OECD.
17. Dietzenbacher, E. (1992) The measurement of interindustry linkages: Key sectors in the Netherlands Economic Modelling, 9, pp. 419-437.
18. Dietzenbacher, E. (1997) In vindication of the Ghosh model: A reinterpretation as a price model Journal of Regional Science, 37, pp. 629-651.
19. Dietzenbacher, E. (2005) More on multipliers Journal of Regional Science, 45, pp. 421-426.
20. Dietzenbacher, E. and van der Linden, J. (1997) Sectoral and spatial linkages in the EC production structure Journal Regional Science, 37, pp. 235-257.
21. Dietzenbacher, E. and Los, B. (2002) Externalities of R&D expenditures Economic Systems Research, 14, pp. 407-425.
22. Dietzenbacher, E. and van der Linden, J. and Steenge, A. (1993) The regional extraction method: EC input-output comparisons Economic Systems Research, 5, pp. 185-206.
23. Dridi, C. and Hewings, G. (2003) Sectors associations and similarities in input-output systems: An application of dual scaling and fuzzy logic to Canada and the United States Annals of Regional Science, 37, pp. 629-656.
24. Dunn, J. (1973) A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters Journal of Cybernetics, 3, pp. 32-57.
25. Eurostat.(1998a) Ressources humaines en haute technologie. La mesure de l'emploi dans les secteurs manufacturiers de haute technologie; une perspective européenne. Serie Statistiques en bref. Recherche et développement. Luxembourg: Eurostat.
26. Eurostat.(1998b) Employment in high technology manufacturing sectors at the regional level. In Document Eurostat/A4/REDIS/103. Luxembourg: Eurostat.
27. Feser, E. and Bergman, E. (2000) National industry cluster templates: A framework for applied regional cluster analysis Regional Studies, 34, pp. 1-19.
28. Feser, E. and Koo, J. and Renski, H. and Sweeney, S.(2001a) Incorporating spatial analysis in applied industry cluster studies. In Working paper. Chapel Hill NC: University of North Carolina. Available at: http://www.planning.unc.edu/pdf/FeserPUBS/EDQ%20Revised.pdf
29. Feser, E. and Sweeney, S. and Renski, H. (2001b) A descriptive analysis of discrete U.S. industrial complexes Prepared for the Journal of Regional Science Available at: http://www.planning.unc.edu/pdf/FeserPUBS/ Complexes.pdf
30. Fukui, Y. (1986) A more powerful method for triangularizing input-output matrices and the similarity of production structures Econometrica, 54, pp. 1425-1433.
31. Ghosh, A. (1958) Input-output approach in an allocation system Economica, 25, pp. 58-64.
32. Harrigan, F. (1982) The relationship between industrial and geographical linkages Journal of Regional Science, 22, pp. 19-31.
33. Hathaway, R. and Bezdek, J. and Hu, Y. (2000) Generalized fuzzy c-means clustering strategies using LP norm distances IEEE Transactions on Fuzzy Systems, 8, pp. 576-582.
34. Hathaway, R. and Bezdek, J. (1994) NERF c-means: Non-Euclidean relational fuzzy clustering Pattern Recognition, 27, pp. 429-437.
35. Hathaway, R. and Davenport, J. and Bezdek, J. (1989) Relational duals of the c-means algorithms Pattern Recognition, 22, pp. 205-212.
36. Hauknes, J.(1999) Norwegian input-output clusters and innovation patterns. In Boosting Innovation: The Cluster Approach. Paris: OECD.
37. Hewings, G. (1974) The effect of aggregation on the empirical identification of key sectors in a regional economy: A partial evaluation of alternative techniques Environment and Planning, 6, pp. 439-453.
38. Hirschman, A.(1958) The Strategy of Economic Development. New Haven CT: Yale University Press.
39. Hoen, A. (2002) Identifying linkages with a cluster-based methodology Economic Systems Research, 14, pp. 131-146.
40. INE.(2000) Tablas input-output de la Economía Española de 1995. Madrid: Spanish Statistics National Institute. http://www.ine.es.
41. INE.(a) Contabilidad Nacional. Base 1995. http://www.ine.es
42. INE.(b) INEbase en la metodología expuesta en Investigación y desarrollo tecnológico. Indicadores de alta tecnología. Available at: http://www.ine.es/inebase/cgi/ um?M=%2Ft14%2Fp197&O=inebase&N=&L=
43. Jacobs, D. and de Man, A.-P. (1996) Clusters, industrial policy and firm strategy: A menu approach Technology Analysis and Strategic Management, 8, pp. 425-437.
44. Kaufman, L. and Rousseeuw, P.(1990) Finding Groups in Data. New York: Wiley.
45. Lainesse, L. and Poussart, B.(2005) Methode de reperage des filieres industrielles sur le territoire quebecois dasee sur les tableux d'entrees-sorties. Montréal Canada: Institut de la Statistique du Québec. Available at: http://www.stat.gouv.qc.ca/publications/ savoir/methode_reperage_pdf.htm
46. Lantner, R.(1974) Théorie de la Dominance Economique. Paris: Dunod.
47. Lantner, R.(2001) Influence graph theory applied to structural analysis. In Input-Output Analysis: Frontiers and Extensions. Basingstoke UK: Palgrave Macmillan.
48. Latham, W. (1976) Needless complexity in the identification of industrial complexes Journal of Regional Science, 16, pp. 45-55.
49. Los, B.(2001). Identification of strategic industries: A dynamic perspective. Paper presented at the 41st European Regional Science Association Congress, Zagreb. In [pp.]. Available at: http://www.ub.rug.nl/eldoc/ccso/200202/200202.pdf
50. MacQueen, J.(1967) Some methods for classification and analysis of multivariate observations. In Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. (pp. 281-297). Berkeley CA: University of California Press.
51. de Mesnard, L.(2001) On Boolean topological methods of structural analysis. In Input-Output Analysis: Frontiers and Extensions. Basingstoke UK: Palgrave Macmillan.
52. de Mesnard, L. (2002) Note about the concept of 'net multipliers' Journal of Regional Science, 42, pp. 545-548.
53. Miller, R. and Lahr, M.(2000) A taxonomy of extractions. In Regional Science Perspectives in Economic Analysis; A Festschrift in Memory of Benjamin H. Stevens. Amsterdam: Elsevier Publishers.
54. Morillas, A.(1983a) La teoría de grafos en el análisis input-output. Malaga: Secretariado de Publicaciones, Universidad de Málaga.
55. Morillas, A. (1983b) Indicadores topológicos de las características estructurales de una tabla input-output. Aplicación a la economía andaluza Investigaciones Económicas, 20, pp. 103-118.
56. Mougeot, M. and Duru, G. and Auray, J.(1977) La Structure Productive Francaise. Paris: Económica.
57. Nagy, G. (1968) State of the art in pattern recognition Proceedings IEEE, 56, pp. 836-882.
58. Ó hUallacháin, B. (1984) The identification of industrial complexes Annals of the Association of American Geographers, 74, pp. 420-436.
59. Oosterhaven, J. (1988) On the plausibility of the supply-driven input-output model Journal of Regional Science, 28, pp. 203-217.
60. Oosterhaven, J.(2004) On the definition of key sectors and the stability of net versus gross multipliers, SOM Research Report 04C01. In. The Netherlands: Research Institute SOM, University of Groningen. Available at: http://som.rug.nl
61. Oosterhaven, J. and Stelder, D. (2002) Net multipliers avoid exaggerating impacts: With a bi-regional illustration for the Dutch transportation sector Journal of Regional Science, 42, pp. 533-543.
62. Oosterhaven, J. and Eding, G. and Stelder, T.(2000) Clusters, linkages and regional spillovers: Methodology and policy implications for the two Dutch mainports and the rural North, SOM Research Report 99C69. In. The Netherlands: Research Institute SOM, University of Groningen. Available at: http://som.rug.nl
63. Papaconstantinou, G. and Sakurai, N. and Wyckoff, A.(1996) Embodied technology diffusion: An empirical analysis for 10 OECD countries. In. Paris: OECD. STI Working Papers 1996/1
64. Peeters, L. and Tiri, M. and Berwert, A.(2001) Techno-economic clusters in Flanders and Switzerland: An input-output analysis. In. Bern Working paper CEST 2001/9, Center for Science and Technology Studies
65. Perroux, F. (1949) Economic spaces: Theory and application Quarterly Journal of Economics, 64, pp. 89-104.
66. Perroux, F.(1973) Pouvoir et Economie. Paris: Bordas.
67. Porter, M. (1990) The competitive advantage of nations Harvard Business Review, 68, pp. 77-93.
68. Rasmussen, P.(1956) Studies in Intersectoral Relations. Amsterdam: North Holland.
69. Rey, S. and Mattheis, D. (2000) Identifying Regional Industrial Clusters in California, Volumes I-III. Reports prepared for the California Employment Development Department, San Diego State University. Available at: http://irsr.sdsu.edu/%7Eserge/node7.html
70. Robles Teigeiro, L. and Sanjuán, J.(2005) Sectores claves. Coeficientes grandes y coeficientes importantes. In Paper presented at I Jornadas de Análisis Input-output. Oviedo
71. Roelandt, T. and den Hertog, P. and van Sinderen, J. and van den Hove, N.(1999) Cluster analysis and cluster policy in the Netherlands. In OECD, Boosting Innovation: The Cluster Approach. Paris: OECD.
72. Roepke, H. and Adams, D. and Wiseman, R. (1974) A new approach to the identification of industrial complexes using input-output data Journal of Regional Science, 14, pp. 15-29.
73. Rosenfeld, S.(1996) Overachievers, Business Clusters that Work: Prospects for Regional Development. Chapel Hill NC: Regional Technology Strategies.
74. Rosenfeld, S. (1997) Bringing business clusters into the mainstream of economic development, European Planning Studies, 5, pp. 3-23.
75. Rossier, E.(1980) Economie Structural. Paris: Económica.
76. Rousseeuw, P. (1987) Silhouettes: A graphical aid to the interpretation and validation of cluster analysis Journal of Computational Applied Mathematics, 20, pp. 53-65.
77. Rousseeuw, P. (1995) Discussion: Fuzzy clustering at the intersection Technometrics, 37, pp. 283-285.
78. Ruspini, E. (1969) A new approach to clustering Information and Control, 15, pp. 22-32.
79. Sakurai, N. and Papaconstantinou, G. and Ioannidis, E. (1997) Impact of R&D and technology diffusion on productivity growth: Empirical evidence for 10 OECD countries Economic Systems Research, 9, pp. 81-110.
80. Scherer, F. (1982) Interindustry technology flows and productivity growth Review of Economics and Statistics, 64, pp. 627-634.
81. Scherer, F. (2003) Technology flows matrix estimation revisited Economic Systems Research, 15, pp. 327-358.
82. Schmookler, J.(1966) Invention and Economic Growth. Cambridge MA: Harvard University Press.
83. Simon, H. (1952) On the definition of the causal relation Journal of Philosophy, 49, pp. 517-528.
84. Simpson, D. and Tsukui, J. (1965) The fundamental structure of input-output tables: An international approach Review of Economics and Statistics, 47, pp. 434-446.
85. Sonis, M. and Guilhoto, J. and Hewings, G. and Martins, E. (1995) Linkages, key sectors, and structural change: Some new perspective, Developing Economies, 33, pp. 233-270.
86. Strassert, G. (1968) Zur bestimmung strategischer sektoren mit Hilfe von Input-Output Modellen Jahrbücher für Nationalökonomie und Statistik, 182, pp. 211-215.
87. Verspagen, B.(1999) The role of large multinationals in the Dutch technology infrastructure: A patent citation analysis. In Mimeo. The Netherlands: University of Maastricht/MERIT.
88. Wold, H. (1954) Causality and Econometrics Econometrica, 22, pp. 162-177.
89. Zadeh, L. (1965) Fuzzy sets Information and Control, 8, pp. 338-353.
90. Zadeh, L.(1977) Fuzzy sets and their application to pattern classification and clustering analysis. In Classification and Clustering. New York: Academic Press.
91. Zhang, T. and Ramakrishnon, R. and Livny, M.(1996) BIRCH: An efficient data clustering method for very large databases. In Proceedings of the ACM SIGMOD Conference on Management of Data. (pp. 103-114). Montreal, Canada