Christoph Frohn - Dynamic Microsimulation of the interplay between Physical and Mental Health based on Autoregressive Latent Trajectory Models with Structured Residuals
Presenting author: Christoph Frohn (University of Duisburg-Essen)
Authors: Christoph Frohn
Session: C04A - Health [4] - Wednesday 16:00-17:00 - Ceremonial Hall
Both physical and mental health are important indicators of an individual’s health-related quality of life and provide insight into the health status within a population. Due to demographic changes, there are debates in Germany about how the distribution of these constructs could change in the future. Predictions are difficult to make because trajectories of physical and mental health are not identical across cohorts. Additionally, changes in the social structure of the population will have a dynamic impact on health. Complex techniques to analyze longitudinal data are needed to study the simultaneous development of physical and mental health over the life course. Autoregressive Latent Trajectory Models with Structured Residuals (ALT-SR) are an example of such a technique which have rarely been used in microsimulations. These models can reveal person specific trajectories in physical and mental health, to what extent both constructs interact, whilst accounting for socio-demographic and socio-economic influences and changes across time and cohorts at the same time. In this contribution, data from the German Socio-Economic Panel (GSOEP) is used to estimate an ALT-SR for the co-development of physical and mental health and the results of the empirical analysis are implemented in a dynamic microsimulation. What-if scenarios are used to highlight the implications of the model and to show to what extent health within the population is affected by demographic changes, with a focus on differences between cohorts and later stages of life. On a substantive level, such scenarios show challenges for the healthcare system and the impact of (political) interventions. Methodologically, the contribution highlights strengths and challenges in the implementation of complex longitudinal models in a microsimulation.