Clustering the Swiss Pension Register

Under the supervision of Prof. Dr. L. Donzé

publication
working paper
kamila
clustering
rrclust
prediction strength criterion
R package
UniFr
OASI
FSIO
R
Authors
Affiliations

Layal Christine Lettry

University of Fribourg, Dept. of Informatics, ASAM Group

cynkra GmbH

Laurent Donzé

University of Fribourg, Dept. of Informatics, ASAM Group

Published

February 27, 2023

How can the diverse data of the Swiss Pension Register be clustered and analyzed to understand the sociodemographic characteristics of OASI pensioners and their implications for estimating future OASI finances?

Abstract

The anonymous information from the Swiss Pension Register (CCO/FSIO) (PR) is typically used to estimate (in the short, middle, and long term) the future revenues and expenditures of the Old-Age and Survivors Insurance (OASI).

In this perspective, it is essential to have a clear look at the register’s main statistical features. In order to gain a deeper comprehension of the data and maximize its richness, Lettry and Donzé (2023) suggest analyzing the raw data using a suitable clustering technique.

References

Lettry, Layal Christine, and Laurent Donzé. 2023. “Clustering the Swiss Pension Register.” Research report 529. Fribourg, Switzerland: University of Fribourg. https://folia.unifr.ch/unifr/documents/324081.

Citation

BibTeX citation:
@online{lettry2023,
  author = {Lettry, Layal Christine and Donzé, Laurent},
  title = {Clustering the {Swiss} {Pension} {Register}},
  date = {2023-02-27},
  url = {https://folia.unifr.ch/unifr/documents/324081},
  langid = {en}
}
For attribution, please cite this work as:
Lettry, Layal Christine, and Laurent Donzé. 2023. “Clustering the Swiss Pension Register.” February 27, 2023. https://folia.unifr.ch/unifr/documents/324081.