Using SOMbrero to examine the economic convergence of European Countries from 2001-2013

Joel I. Deichmann; Abdolreza Eshghi; Dominique Haughton; Mingfei Li

doi:10.1109/WSOM.2017.8020007

Using SOMbrero to examine the economic convergence of European Countries from 2001-2013

Joel I. Deichmann, Abdolreza Eshghi, Dominique Haughton, Mingfei Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper uses SOMbrero visualizations to examine two socio-economic dimensions of European states, generated by a factor analysis of time-series data from 2001-2013. We analyze SOMs for 41 countries with regard to “Old Capital” and “New Capital”, two factors that are generated from 12 variables. SOMbrero reveals evidence of various convergence paths over time for these two factors. This approach also clearly uncovers the differential impacts of the European recession upon clusters of European countries. In conclusion, we demonstrate that SOMs are a useful tool for better understanding European convergence.

Original language	English
Title of host publication	12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings
Editors	Jean-Charles Lamirel, Madalina Olteanu, Marie Cottrell
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509066384
DOIs	https://doi.org/10.1109/WSOM.2017.8020007
State	Published - Aug 29 2017
Event	12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Nancy, France Duration: Jun 28 2017 → Jun 30 2017

Publication series

Name	12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings

Conference

Conference	12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017
Country/Territory	France
City	Nancy
Period	06/28/17 → 06/30/17

Keywords

European Convergence
SOMbrero
Self-Organizing Maps

Access to Document

10.1109/WSOM.2017.8020007

Cite this

Deichmann, J. I., Eshghi, A., Haughton, D., & Li, M. (2017). Using SOMbrero to examine the economic convergence of European Countries from 2001-2013. In J.-C. Lamirel, M. Olteanu, & M. Cottrell (Eds.), 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings Article 8020007 (12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSOM.2017.8020007

Deichmann, Joel I. ; Eshghi, Abdolreza ; Haughton, Dominique et al. / Using SOMbrero to examine the economic convergence of European Countries from 2001-2013. 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings. editor / Jean-Charles Lamirel ; Madalina Olteanu ; Marie Cottrell. Institute of Electrical and Electronics Engineers Inc., 2017. (12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings).

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title = "Using SOMbrero to examine the economic convergence of European Countries from 2001-2013",

abstract = "This paper uses SOMbrero visualizations to examine two socio-economic dimensions of European states, generated by a factor analysis of time-series data from 2001-2013. We analyze SOMs for 41 countries with regard to “Old Capital” and “New Capital”, two factors that are generated from 12 variables. SOMbrero reveals evidence of various convergence paths over time for these two factors. This approach also clearly uncovers the differential impacts of the European recession upon clusters of European countries. In conclusion, we demonstrate that SOMs are a useful tool for better understanding European convergence.",

keywords = "European Convergence, SOMbrero, Self-Organizing Maps",

author = "Deichmann, \{Joel I.\} and Abdolreza Eshghi and Dominique Haughton and Mingfei Li",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Deichmann, JI, Eshghi, A, Haughton, D & Li, M 2017, Using SOMbrero to examine the economic convergence of European Countries from 2001-2013. in J-C Lamirel, M Olteanu & M Cottrell (eds), 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings., 8020007, 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017, Nancy, France, 06/28/17. https://doi.org/10.1109/WSOM.2017.8020007

Using SOMbrero to examine the economic convergence of European Countries from 2001-2013. / Deichmann, Joel I.; Eshghi, Abdolreza; Haughton, Dominique et al.
12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings. ed. / Jean-Charles Lamirel; Madalina Olteanu; Marie Cottrell. Institute of Electrical and Electronics Engineers Inc., 2017. 8020007 (12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2017/8/29

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N2 - This paper uses SOMbrero visualizations to examine two socio-economic dimensions of European states, generated by a factor analysis of time-series data from 2001-2013. We analyze SOMs for 41 countries with regard to “Old Capital” and “New Capital”, two factors that are generated from 12 variables. SOMbrero reveals evidence of various convergence paths over time for these two factors. This approach also clearly uncovers the differential impacts of the European recession upon clusters of European countries. In conclusion, we demonstrate that SOMs are a useful tool for better understanding European convergence.

AB - This paper uses SOMbrero visualizations to examine two socio-economic dimensions of European states, generated by a factor analysis of time-series data from 2001-2013. We analyze SOMs for 41 countries with regard to “Old Capital” and “New Capital”, two factors that are generated from 12 variables. SOMbrero reveals evidence of various convergence paths over time for these two factors. This approach also clearly uncovers the differential impacts of the European recession upon clusters of European countries. In conclusion, we demonstrate that SOMs are a useful tool for better understanding European convergence.

KW - European Convergence

KW - SOMbrero

KW - Self-Organizing Maps

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M3 - Conference contribution

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BT - 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings

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A2 - Olteanu, Madalina

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PB - Institute of Electrical and Electronics Engineers Inc.

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Deichmann JI, Eshghi A, Haughton D, Li M. Using SOMbrero to examine the economic convergence of European Countries from 2001-2013. In Lamirel JC, Olteanu M, Cottrell M, editors, 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. 8020007. (12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings). doi: 10.1109/WSOM.2017.8020007

Using SOMbrero to examine the economic convergence of European Countries from 2001-2013

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