  The multi-cycle organization of modern university systems stimulates the
interest in studying the progression to higher level degree courses during the
academic career. In particular, after the achievement of the first level
qualification (Bachelor degree), students have to decide whether to continue
their university studies, by enrolling in a second level (Master) programme, or
to conclude their training experience. In this work we propose a binary
quantile regression approach to analyze the Bachelor-Master transition
phenomenon with the adoption of the Bayesian inferential perspective. In
addition to the traditional predictors of academic outcomes, such as the
personal characteristics and the field of study, different aspects of the
student's performance are considered. Moreover, a new contextual variable,
indicating the type of university regulations, is taken into account in the
model specification. The utility of the Bayesian binary quantile regression to
characterize the non-continuation decision after the first cycle studies is
illustrated with an application to administrative data of Bachelor graduates at
the School of Economics of Sapienza University of Rome and compared with a more
conventional logistic regression approach.
