Family background and university dropouts during the crisis: the case of Italy
Author(s) -
Emanuela Ghigi
Publication year - 2016
Publication title -
higher education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.9
H-Index - 99
eISSN - 1573-174X
pISSN - 0018-1560
DOI - 10.1007/s10734-016-0004-1
Subject(s) - dropout (neural networks) , sample (material) , demographic economics , higher education , probit model , psychology , demography , economics , sociology , econometrics , economic growth , chemistry , chromatography , machine learning , computer science
The Italian university system has long been characterised by high non-completion\udrates, though aggregate data show a slight reduction of dropouts in recent years.\udThe most straightforward theoretical explanation for this lies in the lowering opportunity\udcost of studying due to the financial and economic crisis. Nonetheless, this interpretation is\udlikely to be partly misleading. Indeed, when the crisis hit Italy, enrolment rates had been\uddeclining for years and the sample of freshmen has become increasingly selected according\udto family ‘social class’, family cultural background, type of high school diploma and\udindividual ability. Since a good family background, as well as other individual characteristics,\udsignificantly increases students’ probability of succeeding, the recent decline in\uddropout rates could partly depend on sample selection. By applying probit selection models\udand decomposition techniques to a sample of Italian university students enrolled in different\udperiods of time, I find that changes in students’ background and students’ characteristics\udplay a major role in the recent reduction of the aggregate dropout rate
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