This paper presents a procedure for clustering analysis that combines Kohone’s Self organizing Feature Map (SOFM) and statistical schemes. The idea is to cluster the data in two stages: run SOFM and then minimize the segmentation dispersion. The advantages of proposed procedure will be illustrated through a synthetic experiment and a real macroeconomic problem. The procedure is then used to explore the relationship between private indebtedness and some macroeconomic variables commonly used to measure macroeconomic performance. The experiences of thirty-nine countries in the early nineties are analyzed. The procedure outperformed others clustering techniques in the job of identifying consistent groups of countries from the economic and statistical viewpoints. It found out similarities in different countries concerning their respective levels of private indebtedness when added to well accepted parameters to measure macroeconomic performance.
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Length: 13 pages Date of creation: 04 May 2005 Date of revision: Handle: RePEc:wpa:wuwpco:0505001
Note: Type of Document - pdf; pages: 13. published at 'LEARNING AND NONLINEAR MODELS' ISSN 1676-2789 Vol. 1, No. 4, pp. 264-277, Dec 2004 Contact details of provider: Web page: http://129.3.20.41
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Find related papers by JEL classification: C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
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