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Student mobility from the south to the north/centre of Italy is an increasingly crucial topic because the most important consequence is the continual depletion of universities situated in the southern regions. Using micro-data from the Italian Ministry of Education, University and Research (MIUR), the purpose of this paper is to investigate how contextual factors affect this mobility.

Empirical evidence is provided by developing a multilevel logit model of student decisions to move at university enrolment that allows us to identify the unique effects that student and province characteristics have on out-migration. Multilevel analysis is appropriate because the research questions focus on the role of province characteristics, variables that are measured at the macro level, on student-level outcome (out-migration) while controlling for student-level characteristics, variables that are measured at the micro level.

The present paper intends to contribute to the literature by quantifying the way in which contextual factors affect student mobility from the south to the north/centre of Italy. Findings show that province differences remain significant even after controlling for individual characteristics stressing the importance of the geographical dimension for student mobility. These findings have important policy implications for the future of university system in Italy.

This paper is relevant to the literature concerning this issue because most of the empirical applications are based on spatial models that do not take into account individual characteristics of the students. In addition, the multilevel methodology proposed can be easily generalise to other countries.

Despite the relevance of innovation in entrepreneurship literature, empirical research on the innovation-performance relationship in start-ups is underdeveloped and shows controversial results. To bridge this gap, the aim of this paper is to investigate the role of innovativeness on new venture performance in the early stage of the life cycle.

Regression modelling and propensity score matching are used to reveal systematic differences in growth between innovative start-ups (ISUPs) and non-innovative start-ups. We use an ad hoc dataset obtained through merging the financial database AIDA with data from administrative sources (Italian Chambers of Commerce and the Italian Ministry for Economic Development).

The results show that differences in growth can be explained by the different levels of innovativeness in new ventures. Moreover, unlike in prior studies, the innovation inputs matter more than innovation outputs. Indeed, the results support the idea that innovation policies can contribute to maximising the potential of start-ups.

The findings provide suggestions for policy makers and entrepreneurs to help firms configure ex ante appropriate actions to support the growth of new ventures in the start-up stage.

This study is the first to use the new objective measure of start-up innovation, available from the Italian LD 221 register. Second, different types of innovation are investigated as antecedents of firm growth. Third, we employ propensity score matching, which favours revealing systematic differences in growth between ISUPs and non-innovative start-ups. Fourth, the results of our study are the first to offer evidence on the effectiveness of the new Italian sustaining ISUPs policy.