Migration and Students’ Performance: detecting geographical differences following a curves clustering approach

Research output: Contribution to journalArticlepeer-review

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 themigration 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.
Original languageEnglish
Number of pages15
JournalJournal of Applied Statistics
Publication statusPublished - 2020

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Fingerprint

Dive into the research topics of 'Migration and Students’ Performance: detecting geographical differences following a curves clustering approach'. Together they form a unique fingerprint.

Cite this