Clustering the Swiss Pension Register

Layal Christine Lettry ()
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Layal Christine Lettry: Department of Quantitative Economics, Postal: Bd de Pérolles 90, 1700 Fribourg, Switzerland, https://lclettry.com

No 529, FSES Working Papers from Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland

Abstract: The anonymous data of the Swiss Pension Register (CCO/FSIO) (PR) are 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. To better understand it and benefit more from its richness, we propose analysing the raw data by an appropriate clustering method.

Keywords: Kamila; Clustering; R; AVS; AHV; OASI; Swiss Pension Register; FSIO; prediction strength criterion; classification; RAMD; AADR; UniFr (search for similar items in EconPapers)
JEL-codes: C38 (search for similar items in EconPapers)
Pages: 132
Date: 2023-02-24
New Economics Papers: this item is included in nep-age and nep-des
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