This study applies a machine learning (ML) approach to around half a million 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 55 years of age.
|Number of pages||22|
|Publication status||Published - 6 Oct 2021|
Bibliographical notePublished online: 06 October 2021
Preprint is under consideration at Scientific Reports
- Age and Life
- Machine learning