Heterogeneity, school-effects and the North/South achievement gap in Italian secondary education: evidence from a three-level mixed model
Tommaso Agasisti (),
Francesca Ieva () and
Anna Maria Paganoni
Additional contact information
Francesca Ieva: Università degli Studi di Milano
Anna Maria Paganoni: Politecnico di Milano
Statistical Methods & Applications, 2017, vol. 26, issue 1, No 7, 157-180
Abstract:
Abstract With the aim of assessing the extent of the differences in the context of Italian educational system, the paper applies multilevel modeling to a new administrative dataset, containing detailed information for more than 500,000 students at grade 6 in the year 2011/2012, provided by the Italian Institute for the Evaluation of Educational System. Data are grouped by classes, schools and geographical areas. Different models for each area are fitted, in order to properly address the heteroscedasticity of the phenomenon. The results show that it is possible to estimate statistically significant “school effects”, i.e., the positive/negative association of attending a specific school and the student’s test score, after a case-mix adjustment. Therefore, the paper’s most important message is that school effects are different in terms of magnitude and types in the three geographical macro areas (Northern, Central and Southern Italy) and are dependent on specific students’ and schools’ characteristics.
Keywords: Child development; Multilevel models; School effectiveness; Value-added model; Contextual effects; Education (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://link.springer.com/10.1007/s10260-016-0363-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:stmapp:v:26:y:2017:i:1:d:10.1007_s10260-016-0363-x
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10260/PS2
DOI: 10.1007/s10260-016-0363-x
Access Statistics for this article
Statistical Methods & Applications is currently edited by Tommaso Proietti
More articles in Statistical Methods & Applications from Springer, Società Italiana di Statistica
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().