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Clustering the Swiss Pension Register

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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.

Suggested Citation

  • Layal Christine Lettry, 2023. "Clustering the Swiss Pension Register," FSES Working Papers 529, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    • Handle: RePEc:fri:fribow:fribow00529
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    File URL: https://folia.unifr.ch/unifr/documents/324081
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    1. Dubois, Corinne & Lambertini, Luisa & Wu, Yu, 2022. "Gender Effects of the Covid-19 Pandemic in the Swiss Labor Market," FSES Working Papers 525, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
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    6. 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.
    7. Herz, Holger & Kistler, Deborah & Zehnder, Christian & Zihlmann, Christian, 2022. "Hindsight Bias and Trust in Government: Evidence from the United States," FSES Working Papers 526, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
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    More about this item

    Keywords

    Kamila; Clustering; R; AVS; AHV; OASI; Swiss Pension Register; FSIO; prediction strength criterion; classification; RAMD; AADR; UniFr;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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