Overview report on the generation of synthetic universes for microsimulations. Utility and Confidentiality of Synthetically Generated Data Sets (Deliverable D12.6)

Over the past decades, microsimulations have increasingly become an important component of modern empirical research as well as for policy support. These microsimulations are useful and viable only if they are conducted with appropriate data. Modern requirements, however, should allow regional and spatial pattern being included which may automatically lead to synthetic but realistic data generation as a viable source for microsimulations. These data sets shall represent reality as precisely as possible in terms of statistical distributions without posing issues of confidentiality for any real-world individuals. The present research aims at analysing the potential threat of information disclosure in the context of synthetic data and microsimulations, using the Eurofound's European Working Conditions survey as well as the synthetic AMELIA data set