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European Insurance Market Analysis via a Joint Functional Clustering Method

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  • Stavros Athanasiadis

Abstract

The enlargement of the European Union (EU) to include Central and South-Eastern European countries in 2004 and 2007 launched an integration process that unifies the economies and financial markets of member states and enables the convergence of these two areas. This study focuses on analyzing the development and similarity of the European insurance sector after the EU enlargement. We study 34 European insurance markets from 2004 until 2021 based on a certain set of indicators that characterize insurance markets, such as Insurance Density, Insurance Penetration and Gross Written Premiums to name a few. With a functional clustering method applied to such indicators, we try to reveal whether there are similarities between the individual countries that could explain the European insurance market homogeneity and convergence via the EU integration process. The proposed method has also a practical importance since it provides visualization of the clustering results through the construction of global envelopes. This study supports the works of EU policy makers that have a major impact on the ability of further integration of the European insurance market.Keywords: European insurance markets,

Suggested Citation

  • Stavros Athanasiadis, 2023. "European Insurance Market Analysis via a Joint Functional Clustering Method," Economics Working Papers 2023-06, University of South Bohemia in Ceske Budejovice, Faculty of Economics, revised 30 Nov 2023.
    • Handle: RePEc:boh:wpaper:06_2023
    DOI: 10.32725/ewp.2023.006
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    References listed on IDEAS

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    1. Christian Hennig & Tim F. Liao, 2013. "How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(3), pages 309-369, May.
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    4. W. Jean Kwon & Leigh Wolfrom, 2016. "Analytical tools for the insurance market and macro-prudential surveillance," OECD Journal: Financial Market Trends, OECD Publishing, vol. 2016(1), pages 1-47.
    5. Dai, Wenlin & Mrkvička, Tomáš & Sun, Ying & Genton, Marc G., 2020. "Functional outlier detection and taxonomy by sequential transformations," Computational Statistics & Data Analysis, Elsevier, vol. 149(C).
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    Keywords

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    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • F15 - International Economics - - Trade - - - Economic Integration
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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