The effect of grading policies on Italian Universities' attractiveness: A Conditional Multinomial Logit approach

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.

数十年来，全球高等教育体系中学生的平均成绩出现了大幅上升。在众多假说中，本文将着重探讨一种观点：评分是各院系吸引更多学生的工具之一。以意大利为例，教育部在评估大学时会将学位获取速度纳入考量标准，并据此按比例提供资助。缺点在于，这可能导致成绩的人为虚高。因此，对于排名靠后的大学而言，学生数量变得至关重要——它们需通过学费维持运营。另一方面，学生倾向于前往就业机会更多的地区，这一预期合乎情理。换言之，学生流动的动因可能是寻求更优的工作条件，而非院系的“评分宽松度”。为验证这一假说，本文将采用多项条件Logit模型（Multinomial Conditional Logit Model），以衡量学生选择某一目的地的概率——该概率取决于大学的评分严格度与声誉，以及地区失业率。