European insurance market analysis via functional data clustering techniques

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

European insurance market analysis via functional data clustering techniques

Popis výsledku v původním jazyce

Insurance penetration as a high-level indicator of an insurance market’s development exhibits significant variations over time across countries. Cross-country comparisons on the link between insurance and economic growth are better off when insurance development homogeneity is present. Motivated by this evidence, this study is aimed to provide a data-driven and meaningful clustering of European countries in terms of their insurance penetration rates that are considered as functions (curves). The ultimate goal is the extraction and visualization of the representative curves that characterize the homogeneous clusters of European insurance market. To this end, we apply functional data clustering methodsthat fall into three major categories: distancebased methods, filtering methods, and adaptive methods. The data consist of insurance penetration rates sampled from 34 European countries and observed between 2004 and 2016; that is before, during and post-financial and sovereign debt crises. Our results - the clusters- are analyzed from a qualitative point of view, detecting visually whether they are distinguishable and preserve the magnitude and shape of the cluster member curves.

Název v anglickém jazyce

European insurance market analysis via functional data clustering techniques

Popis výsledku anglicky

Insurance penetration as a high-level indicator of an insurance market’s development exhibits significant variations over time across countries. Cross-country comparisons on the link between insurance and economic growth are better off when insurance development homogeneity is present. Motivated by this evidence, this study is aimed to provide a data-driven and meaningful clustering of European countries in terms of their insurance penetration rates that are considered as functions (curves). The ultimate goal is the extraction and visualization of the representative curves that characterize the homogeneous clusters of European insurance market. To this end, we apply functional data clustering methodsthat fall into three major categories: distancebased methods, filtering methods, and adaptive methods. The data consist of insurance penetration rates sampled from 34 European countries and observed between 2004 and 2016; that is before, during and post-financial and sovereign debt crises. Our results - the clusters- are analyzed from a qualitative point of view, detecting visually whether they are distinguishable and preserve the magnitude and shape of the cluster member curves.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50206 - Finance

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Conference Proceedings of 37th International Conference on Mathematical Methods in Economics 2019

ISBN

978-80-7394-760-6

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

179-184

Název nakladatele

University of South Bohemia in České Budějovice, Faculty of Economics

Místo vydání

České Budějovice

Místo konání akce

České Budějovice

Datum konání akce

11. 9. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000507570400029