Hohenheim team uses machine learning to uncover the relation between age and life satisfaction  [10.07.22]

Life satisfaction depends on numerous variables, many of which are dependent on age. A recent study published in Nature uses a machine learning approach suggests that life satisfaction is underestimated among the young and overestimated among middle-aged individuals. Life satisfaction seems to follow a U-shaped curve across the lifespan, with a minimum around the age of 50, the well-known midlife crisis.

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Original Report

Kaiser, M. (a), Otterbach, S. (b,c), Sousa-Poza, A. (b,c); 2022; Using machine learning to uncover the relation between age and life satisfaction. Nature Scientific Reports, Volume 12, Issue 1, 5263, DOI 10.1038/s41598-022-09018-x.

  • (a) Department of Management, Society, and Communication, Copenhagen Business School, Dalgas Have 15, Frederiksberg, 2000, Denmark
  • (b) Institute for Health Care and Public Management, University of Hohenheim, Fruwirthstrasse 48, Stuttgart, 70599, Germany
  • (c) IZA, Bonn, Germany

 

Abstract

This study applies a machine learning (ML) approach to around 400,000 observations from the German Socio-Economic Panel to assess the relation between life satisfaction and age. We show that with our ML-based approach it is possible to isolate the effect of age on life satisfaction across the lifecycle without explicitly parameterizing the complex relationship between age and other covariates—this complex relation is taken into account by a feedforward neural network. Our results show a clear U-shape relation between age and life satisfaction across the lifespan, with a minimum at around 50 years of age.

© 2022, The Author(s).

Related documents

Otterbach, S. , Sousa-Poza, A. , Møller, V. (2018) A cohort analysis of subjective wellbeing and ageing: Heading towards a midlife crisis? Longitudinal and Life Course Studies

More from the Authors
Prof. Dr. Alfonso Sousa-Poza

Chair for Household and Consumer Economics

Current Projects

Tel.: 0711/459-22863

E-Mail: alfonso.sousa-poza@uni-hohenheim.de

Dr. Steffen Otterbach

Tel.:  +49 711/459-23425

E-Mail: Steffen.Otterbach@uni-hohenheim.de

Ass. Prof. Dr. Micha Kaiser

Current Affiliation: Copenhagen Business School

Tel: +45 38153272, Mobile: +49 17651920261

E-mail: mka.msc@cbs.dk


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