How individual characteristics affect university students drop-out: a semiparametric mixed-effects model for an Italian case study
How individual characteristics affect university students drop-out: a semiparametric mixed-effects model for an Italian case study
University drop-out is a topic of increasing concern in Italy as well as in other countries. In empirical analysis, university drop-out is generally measured by means of a binary variable indicating the drop-out versus retention. In this paper,we argue that the withdrawal decision is one of the possible outcomes of a set of four alternatives: retention in the same faculty, drop out, change of faculty within the same university, and change of institution. We examine individual-level data collected by the administrative offices of “Sapienza” University of Rome, which cover 117 072 students enrolling full-time for a 3 year degree in the academic years from 2001/2002 to 2006/2007. Relying on a non-parametric maximum likelihood approach in a finite mixture context, we introduce a multinomial latent effects model with endogeneity that accounts for both heterogeneity and omitted covariates. Our estimation results show that the decisions to change faculty or university have their own peculiarities, thus we suggest that caution should be used in interpreting results obtained without modeling all the relevant alternatives that students face.
university drop-out, mixed effects models, multinomial regression, Italian university system
2225-2239
Belloc, Filippo
d123f320-6dab-4b7b-b5d1-4baa77612221
Maruotti, Antonello
7096256c-fa1b-4cc1-9ca4-1a60cc3ee12e
Petrella, Lea
bf351458-2a5a-452e-be73-496a19c4060a
October 2011
Belloc, Filippo
d123f320-6dab-4b7b-b5d1-4baa77612221
Maruotti, Antonello
7096256c-fa1b-4cc1-9ca4-1a60cc3ee12e
Petrella, Lea
bf351458-2a5a-452e-be73-496a19c4060a
Belloc, Filippo, Maruotti, Antonello and Petrella, Lea
(2011)
How individual characteristics affect university students drop-out: a semiparametric mixed-effects model for an Italian case study.
Journal of Applied Statistics, 38 (10), .
(doi:10.1080/02664763.2010.545373).
Abstract
University drop-out is a topic of increasing concern in Italy as well as in other countries. In empirical analysis, university drop-out is generally measured by means of a binary variable indicating the drop-out versus retention. In this paper,we argue that the withdrawal decision is one of the possible outcomes of a set of four alternatives: retention in the same faculty, drop out, change of faculty within the same university, and change of institution. We examine individual-level data collected by the administrative offices of “Sapienza” University of Rome, which cover 117 072 students enrolling full-time for a 3 year degree in the academic years from 2001/2002 to 2006/2007. Relying on a non-parametric maximum likelihood approach in a finite mixture context, we introduce a multinomial latent effects model with endogeneity that accounts for both heterogeneity and omitted covariates. Our estimation results show that the decisions to change faculty or university have their own peculiarities, thus we suggest that caution should be used in interpreting results obtained without modeling all the relevant alternatives that students face.
This record has no associated files available for download.
More information
e-pub ahead of print date: 27 June 2011
Published date: October 2011
Keywords:
university drop-out, mixed effects models, multinomial regression, Italian university system
Organisations:
Statistics, Statistical Sciences Research Institute
Identifiers
Local EPrints ID: 341366
URI: http://eprints.soton.ac.uk/id/eprint/341366
ISSN: 0266-4763
PURE UUID: 5bbcda70-16e4-4767-a601-e0224fd4d86e
Catalogue record
Date deposited: 23 Jul 2012 13:58
Last modified: 14 Mar 2024 11:38
Export record
Altmetrics
Contributors
Author:
Filippo Belloc
Author:
Antonello Maruotti
Author:
Lea Petrella
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics