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4 result(s) for "Ghellini, Giulio"
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Movers and stayers in STEM enrollment in Italy: who performs better?
Recently, the mobility behavior of Italian university students has garnered increasing interest from both social scientists and politicians. The very particular geographical characteristics of the country, together with the recognized persistence of a significant economic gap between the southern and northern regions, drive a large number of students to move from the first macro-region to the latter. As this phenomenon has several economic and social implications for policy-makers—at both central and local levels—it has led to various theories and prejudices. The present article will study the differences between the performance of STEM students who have decided to move from the south to the north and those who have decided to stay close to their hometowns. We devised multilevel modelling techniques to analyze this issue using administrative microdata from the Italian Ministry for Universities and Research (MUR), including eight cohorts of students from AY 2008–2009 to AY 2015–16, who enrolled in STEM fields after earning their high school diploma. One of the main findings is that individuals who moved from the south show lower levels of performance than their stayer counterparts who are enrolled in northern or central universities.
Overqualification unreveled: a multidimensional and fuzzy set analysis
This paper proposes a multidimensional and fuzzy set approach for measuring occupational mismatch, testing human capital theory and social closure theory. We propose to use a fuzzy indicator in the range [−1, 1] for each item to quantify the extent of occupational mismatch, which is then used in a factor analysis to identify two dimensions: coherence and satisfaction. Our findings suggest that the multidimensional and fuzzy set approach provides an informative and accurate picture of overqualification, so to disentangle properly the components of job satisfaction and coherence. The fuzzy indicator approach allows for a more nuanced understanding of the concept of occupational mismatch, by accounting for the imprecision and uncertainty inherent in the measurement of this construct. Overall, our study contributes to a better understanding of overqualification and provides a useful methodology for its measurement. The range of the fuzzy indicator highlights the complexity of occupational mismatch and can inform future research in this area.
Out-migration of university enrolment: the mobility behaviour of Italian students
Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.
Linking University Harshness and Students’ Choices: Sociodemographic Differences based on Italian Universities’ Characteristics
Through the decades, the Higher Education System globally experimented a huge increase in the average marks that each student receives. Among several hypothesis, in this article the idea that grading is one of the tool that every department can use in order to attract a larger amount of students will be stressed. Regarding the Italian case, the speed in obtaining a degree is among the criteria considered by the Ministry of Education in order to evaluate universities, financing them proportionally. As a shortcoming, this can boost an artificial increase in marks. So, the number of students becomes important for those universities with the worst ranking positions, in order to finance themselves through fees. On the other side, it is reasonable to expect that a student emigrates toward places which offer higher chances of receiving a job. In other words, mobility might be driven by the search for better working conditions, and not by the ’ease’ of the faculty. Testing this hypothesis, a Multinomial Conditional Logit Model will be implemented in order to measure the probability of choosing a certain destination depending on the harshness and reputation of a University and on the rates of unemployment at a regional level.