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Over the last ten years, many studies have paid attention to the assessments of the
efficiency and effectiveness of the Italian university system. In this framework, student mobility is a
key feature in promoting competition among universities in terms of attractiveness. The use of
indicators of attractiveness based on student mobility leaves practitioners with many unanswered
questions, including (i) the definitions of the flows of incoming students, (ii) the adjustment for
potential confounding factors external to the university system and (iii) the need to account for
uncertainty in the comparisons of the synthetic measures used to rank institutions. For instance,
though it is well known that it is easier to drain students from closer territories or from territories
without universities, this factor has been never (or only marginally) been considered in the
definition of students’ flows. Based on this evidence and moving from the long-running debate on
the misuse of rankings (the so called, League Tables) in the educational field (see Goldestein and
Spieghelhalther 1996; Goldestein 2008; Leckie and Goldestein 2009), this paper attempt to shed
light on the determinants (at the territorial level) of student mobility. We aim to alert policy-makers
and citizens of the need for an informed reading of any such rankings, whether its aim is to inform
student choices or to monitor institutions for accountability reasons. In this paper, we try to identify
the most important factors that could affect student mobility in Italy by completing a macroperspective
analysis of competing university territorial areas and taking into account the so called
“initial advantage” conditions of different universities areas. We consider a wide range of covariates
related to the socio-economic characteristics of the areas where universities are located and to their
features, in terms of the variety and quantity of their degree programs, financial endowments and
services provided to students. A modelling approach based on the analysis of incoming and outcoming
flows of students from each competing areas has been adopted to define the attractiveness
of universities and to assess how much the detected divergences can be attributed to university
policies and how much is outside the control of the universities’ ruling bodies (for instance on
territorial factors, such as the conditions of the labour market). Further on, to make comparisons
among competing areas using fair indicators (i.e., those that account for the uncertainty in the point
estimates), the information on attractiveness has been summarised using an overall index which
accounts the uncertainty in the point estimates by making comparisons across pairs of attractiveness
parameters. Results show that most of the non-significant differences in point estimates led to
unreliable differences in ranking (in terms of the overlapping confidence intervals of the estimates)
and were thus meaningless. Results have two main implication: (i) assigning monetary resources on
the basis of students’ mobility scores does not reward the university’s capability to attract students
but instead highlights the area where it is located; ii) furthermore, the use of League Tables, which
do not consider the uncertainty in the point estimates and the effect of factors outside the control of
the university’s ruling bodies risks draining students toward the richest provinces. These territories
are also those with a higher cost of living; thus, students’ increased monetary investment bestows
no real advantage in terms of educational opportunities.