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

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  • Giovanni Boscaino
  • Gianluca Sottile
  • Giada Adelfio

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.

Suggested Citation

  • Giovanni Boscaino & Gianluca Sottile & Giada Adelfio, 2022. "Migration and students' performance: detecting geographical differences following a curves clustering approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(4), pages 1018-1032, March.
    • Handle: RePEc:taf:japsta:v:49:y:2022:i:4:p:1018-1032
    DOI: 10.1080/02664763.2020.1845624
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