Migration and students' performance: detecting geographical differences following a curves clustering approach

Giovanni Boscaino, Gianluca Sottile and Giada Adelfio

Journal of Applied Statistics, 2022, vol. 49, issue 4, 1018-1032

Abstract: Students' migration mobility is the new form of migration: students migrate to improve their skills and become more valued for the job market. The data regard the migration of Italian Bachelors who enrolled at Master Degree level, moving typically from poor to rich areas. This paper investigates the migration and other possible determinants on the Master Degree students' performance. The Clustering of Effects approach for Quantile Regression Coefficients Modelling has been used to cluster the effects of some variables on the students' performance for three Italian macro-areas. Results show evidence of similarity between Southern and Centre students, with respect to the Northern ones.

Date: 2022
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DOI: 10.1080/02664763.2020.1845624

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