Projecting Gender Inequalities in Work-Life Trajectories and Retirement Expectations at Age 55: Estimates for Germany

Linda Vecgaile , Max Planck Institute for Demographic Research
Emilio Zagheni, Max Planck Institute for demographic Research
Luca Badolato, The Ohio State University
Luiz Felipe Vecchietti, Institute for Basic Science

Governments are grappling with demographic shifts, such as an aging population and rising old-age dependency, prompting discussions on delaying retirement age. To safeguard vulnerable groups from prolonged unemployment, policies promoting longer careers need careful planning. Existing research has centered on predicting work-life expectancy, serving as a foundation for policy development. This study extends this work, adopting a life course perspective, by recognizing that retirement is a gradual process characterized by complex transitions. Additionally, we consider the gendered experiences that shape individuals' life courses and aging processes. Gender-specific challenges, such as disparities in career opportunities, caregiving responsibilities, and wage gaps, significantly impact retirement decisions. Using data from the German Pension Insurance, we employ machine learning techniques like Transformers and LSTM models, along with sequence analysis, to predict work-life trajectories from ages 56 to 65. These analyses provide valuable insights for understanding complex retirement transitions with due consideration of gendered experiences.

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 Presented in Session 112. Flash session Gender, Work and Parenthood