Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/215222 
Erscheinungsjahr: 
2019
Schriftenreihe/Nr.: 
IZA Discussion Papers No. 12826
Verlag: 
Institute of Labor Economics (IZA), Bonn
Zusammenfassung: 
Universities use 'first in family' or 'first generation' as an indicator to increase the diversity of their student intake, but little is known about whether it is a good indicator of disadvantage. We use nationally representative, longitudinal survey data linked to administrative data from England to provide the first comprehensive analysis of this measure. We employ parametric probability (logit) and non-parametric classification (random forest) models to look at its relative predictive power of university participation and graduation. We find that being first in family is an important barrier to university participation and graduation, over and above other sources of disadvantage. This association seems to operate through the channel of early educational attainment. Our findings indicate that the first in family indicator could be key in efforts to widen participation at universities.
Schlagwörter: 
socioeconomic gaps
higher education
widening participation
first in family
first generation
educational mobility
machine learning
predictive models
JEL: 
I23
I24
J24
Dokumentart: 
Working Paper

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