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New evaluation tool for predicting disability pension risk among Finnish public sector employees

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  • Petra Sohlman
  • Risto Louhi
  • Janne Salonen

Abstract

Using unique research data, we investigate disability retirement risk under the statutory public sector pension scheme in Finland. The statistical analysis yields two indicators: risk for upcoming permanent disability pension and critical duration of sickness absence days for public sector occupations. Statistical analysis is based on logistic regression model where the outcome is the disability pension, using sickness benefit spells and other individual background information as covariates. The results underline the importance of minimizing the sickness spells and their duration to the risk and reveal differences in risk across occupations. We conclude that the proposed risk model is a promising tool which can help employers and the pension industry in preventing permanent disability.

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  • Petra Sohlman & Risto Louhi & Janne Salonen, 2024. "New evaluation tool for predicting disability pension risk among Finnish public sector employees," Papers 2410.19890, arXiv.org.
    • Handle: RePEc:arx:papers:2410.19890
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    File URL: http://arxiv.org/pdf/2410.19890
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    1. Benjamin Welby & Ethel Hui Yan Tan, 2022. "Designing and delivering public services in the digital age," OECD Going Digital Toolkit Notes 22, OECD Publishing.
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