Clustering analysis on European insurance markets

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F23%3A43906364" target="_blank" >RIV/60076658:12510/23:43906364 - isvavai.cz</a>
Result on the web
<a href="http://omp.ef.jcu.cz/index.php/EF/catalog/book/85" target="_blank" >http://omp.ef.jcu.cz/index.php/EF/catalog/book/85</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Clustering analysis on European insurance markets
Original language description
Clustering can extract valuable information resided in complex and massive data sets. Motivated by thisevidence, this paper provides a multivariate clustering analysis on European insurance markets in terms of theirinsurance penetration rates. In this paper, K-means with the Euclidean distance is adopted to form clusters within asample of 34 European countries observed between 2004 and 2016; that is before, during and post-financial andsovereign debt crises. Clusters reveal that insurance markets of Balkan and Baltic regions suffered the most from financialcrisis, while of those, that belong to Scandinavian and English and French-speaking European countries observed tohave an unstable behaviour.
Czech name
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Czech description
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Studentská vědecká a odborná činnost 2023. Sborník vybraných příspěvků studentů Ekonomické fakulty Jihočeské univerzity v Českých Budějovicích
ISBN
978-80-7694-002-4
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
238-246
Publisher name
Jihočeská univerzita v Českých Budějovicích, Ekonomická fakulta
Place of publication
České Budějovice
Event location
České Budějovice
Event date
Apr 20, 2023
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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