Ricerc@Sapienza

Nowadays, one of the main issues in statistics consists of the management of data coming from several different sources. Indeed, during the last years Statistics Institutes and academia have been engaged in the development of data integration techniques that would have allowed merging procedures. The availability of joint information is not only important per se, i.e. to have longer datasets, but it represents an actual need in many fields. Considering social sciences, one of the most interesting examples that clearly shows the cruciality of data integration is the problem of the estimation of the magnitude of the intergenerational mobility phenomenon when familiar data are not available.
The aim of my research is to implement and adapt new data integration techniques such as Record Linkage and Statistical Matching in social sciences' applications, exploiting both Bayesian and frequentist approaches. After a rigorous methodological comparison and the study of the properties of the proposed estimators, I will go further in the analysis relaxing some key assumption at the base of data integration methods that seem to be too binding in social sciences applications.