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Abstract:
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Educational attainment and success in the labor market determine access to economic, social, and cultural resources. On the other hand, educational attainment is strongly influenced by existing intergenerational resources. Hence, endogenous dynamics within life courses (also considering the social origin) must be analyzed using panel data to understand the underlying mechanisms.
This can be done with dynamic panel models or growth curve modeling. Recently, approaches have been presented to combine these two types of models. We want to contribute to a better understanding of the usage of such new approaches. We apply them to an analysis of educational and professional pathways of third-generation migrants in Germany (following up a finished project funded by the German Research Foundation). Since the members of this generation are young, we want to forecast different scenarios for the possible pathways through a microsimulation. This brings up the additional challenge of implementing the results from complex panel data models into microsimulations. For this purpose, we have developed strategies that will be presented together with empirical and simulated results.
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