6533b7d2fe1ef96bd125f78c

RESEARCH PRODUCT

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

Giada AdelfioGiovanni BoscainoGianluca Sottile

subject

Statistics and ProbabilityComputingMilieux_THECOMPUTINGPROFESSIONApplication NotesComputer scienceClustering of curveeducationJob marketQuantile regressionCensored and truncated dataQuantile regressionComputingMilieux_COMPUTERSANDEDUCATIONEconometricsSettore SECS-S/05 - Statistica SocialeStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaCluster analysisStudents’performance

description

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.

yearjournalcountryeditionlanguage
2020-11-09Journal of Applied Statistics
https://doi.org/10.1080/02664763.2020.1845624