Digital Library

of the European Council for Modelling and Simulation



Clustering EU Countries Based On Death Probabilities


Kolos Csaba Agoston, Agnes Vaskoevi

Published in:



2020). ECMS 2020 Proceedings Edited by: Mike Steglich, Christian Muller, Gaby Neumann, Mathias Walther, European Council for Modeling and Simulation.



ISSN: 2522-2422 (ONLINE)

ISSN: 2522-2414 (PRINT)

ISSN: 2522-2430 (CD-ROM)


ISBN: 978-3-937436-68-5
ISBN: 978-3-937436-69-2(CD)


Communications of the ECMS , Volume 34, Issue 1, June 2020,

United Kingdom


Citation format:

Kolos Csaba Agoston, Agnes Vaskoevi (2020). Clustering EU Countries Based On Death Probabilities, ECMS 2020 Proceedings Edited By: Mike Steglich, Christian Mueller, Gaby Neumann, Mathias Walther European Council for Modeling and Simulation. doi: 10.7148/2020-0091



Background Our research is conducted to identify certain grouping of 24 European countries based on their death probabilities. Gathering 2014 data from Human Mortality Database our research objective was twofold. First, we wanted to find homogeneous groups of countries where mortality is similar and for a financial institution they could be grouped as risk communities. Second, we wanted to identify the optimal number of groups as a basis for strategy making. Two different clustering methods were used in our research, k-means and k-median clustering. We applied asymmetric measure (QDEV) in k-median method to handle the differences in country sizes and age groups. Our results are stable but different in k=3 clusters,
k-means clustering resulted in a big Western-European cluster and two small-medium Eastern groups; however, k-median clustering gave a homogeneous Eastern group and besides a bigger Western cluster Spain, Italy, and France formed a separated group of countries.

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