IDEAS home Printed from https://ideas.repec.org/p/saq/wpaper/4-20.html
   My bibliography  Save this paper

Family Background, School-Track and Macro-Area: the Complex Chains of Education Inequalities in Italy

Author

Listed:
  • Orazio Giancola

    (Department of Social Sciences and Economics, Sapienza University of Rome)

  • Luca Salmieri

    (Department of Social Sciences and Economics, Sapienza University of Rome)

Abstract

The main aim of this paper is to analyse the effect of social and territorial inequalities on educational outcomes in the Italian upper secondary school. For this purpose, the paper means to respond to 4 general questions: first, to what extent family background affects upper secondary school-choice and whether it has been changing during the last decade. Second, how strong is the school-track effect on learning outcomes net of other main independent variables. Third, to what extent the average family background at school level has an added role in the general explanatory model of inequalities in learning outcomes. Finally, throughout OLS models based on macro-area as a split dependent variable, we aim at accounting for structural explanatory differences between Northern and Southern regions. Findings shows a clear explanatory pattern: rather than the individual factors, it’s a chains of family background, school-choice as well as average school social status to play a determinant role in explaining learning outcomes. This explanatory pattern keeps being valid when splitting up for Italian macro areas (North-West, North-East, Centre, South and South-Islands). Two important exceptions stand out: 1) the effect of school-choice is stronger in South and South-Islands and 2) the effect of the average social status of schools is stronger in Centre and North-East.

Suggested Citation

  • Orazio Giancola & Luca Salmieri, 2020. "Family Background, School-Track and Macro-Area: the Complex Chains of Education Inequalities in Italy," Working Papers 4/20, Sapienza University of Rome, DISS.
  • Handle: RePEc:saq:wpaper:4/20
    as

    Download full text from publisher

    File URL: http://www.diss.uniroma1.it/sites/default/files/allegati/DiSSE_Giancola_Salmieri_wp4_2020.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Daniele Checchi & Luca Flabbi, 2013. "Intergenerational Mobility and Schooling Decisions in Germany and Italy: The Impact of Secondary School Tracks," Rivista di Politica Economica, SIPI Spa, issue 3, pages 7-57, July-Sept.
    2. Eric A. Hanushek & Ludger Wössmann, 2006. "Does Educational Tracking Affect Performance and Inequality? Differences- in-Differences Evidence Across Countries," Economic Journal, Royal Economic Society, vol. 116(510), pages 63-76, March.
    3. Ralph Hippe & Maciej Jakubowski & Luisa De Sousa Lobo Borges de Araujo, 2018. "Regional inequalities in PISA: the case of Italy and Spain," JRC Research Reports JRC109057, Joint Research Centre.
    4. Massimiliano Bratti & Daniele Checchi & Antonio Filippin, 2007. "Geographical Differences in Italian Students' Mathematical Competencies: Evidence from Pisa 2003," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 66(3), pages 299-333, November.
    5. Martins, Lurdes & Veiga, Paula, 2010. "Do inequalities in parents' education play an important role in PISA students' mathematics achievement test score disparities?," Economics of Education Review, Elsevier, vol. 29(6), pages 1016-1033, December.
    6. Agasisti, Tommaso & Cordero-Ferrera, Jose M., 2013. "Educational disparities across regions: A multilevel analysis for Italy and Spain," Journal of Policy Modeling, Elsevier, vol. 35(6), pages 1079-1102.
    7. Veruska Oppedisano & Gilberto Turati, 2015. "What are the causes of educational inequality and of its evolution over time in Europe? Evidence from PISA," Education Economics, Taylor & Francis Journals, vol. 23(1), pages 3-24, February.
    8. Daniele Checchi, 2004. "Da dove vengono le competenze scolastiche?," Stato e mercato, Società editrice il Mulino, issue 3, pages 413-454.
    9. Mariagiulia Matteucci & Stefania Mignani, 2014. "Exploring Regional Differences in the Reading Competencies of Italian Students," Evaluation Review, , vol. 38(3), pages 251-290, June.
    10. Giambona, Francesca & Porcu, Mariano, 2015. "Student background determinants of reading achievement in Italy. A quantile regression analysis," International Journal of Educational Development, Elsevier, vol. 44(C), pages 95-107.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Camanho, Ana S. & Varriale, Luisa & Barbosa, Flávia & Sobral, Thiago, 2021. "Performance assessment of upper secondary schools in Italian regions using a circular pseudo-Malmquist index," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1188-1208.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ralph Hippe & Maciej Jakubowski & Luisa De Sousa Lobo Borges de Araujo, 2018. "Regional inequalities in PISA: the case of Italy and Spain," JRC Research Reports JRC109057, Joint Research Centre.
    2. Antonella D’Agostino & Francesco Schirripa Spagnolo & Nicola Salvati, 2022. "Studying the relationship between anxiety and school achievement: evidence from PISA data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 1-20, March.
    3. Ferraro, Simona & Põder, Kaire, 2018. "School-level policies and the efficiency and equity trade-off in education," Journal of Policy Modeling, Elsevier, vol. 40(5), pages 1022-1037.
    4. Giambona, Francesca & Porcu, Mariano, 2015. "Student background determinants of reading achievement in Italy. A quantile regression analysis," International Journal of Educational Development, Elsevier, vol. 44(C), pages 95-107.
    5. Camanho, Ana S. & Varriale, Luisa & Barbosa, Flávia & Sobral, Thiago, 2021. "Performance assessment of upper secondary schools in Italian regions using a circular pseudo-Malmquist index," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1188-1208.
    6. Simona Ferraro & Tommaso Agasisti & Francesco Porcelli & Mara Soncin, 2021. "Local governments’ efficiency and educational results: empirical evidence from Italian primary schools," Applied Economics, Taylor & Francis Journals, vol. 53(35), pages 4017-4039, July.
    7. Sulis, Isabella & Giambona, Francesca & Porcu, Mariano, 2020. "Adjusted indicators of quality and equity for monitoring the education systems over time. Insights on EU15 countries from PISA surveys," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    8. Susana Faria & Maria Conceição Portela, 2016. "Student Performance in Mathematics using PISA-2009 data for Portugal," Working Papers de Gestão (Management Working Papers) 01, Católica Porto Business School, Universidade Católica Portuguesa.
    9. Giambona, Francesca & Porcu, Mariano, 2018. "School size and students' achievement. Empirical evidences from PISA survey data," Socio-Economic Planning Sciences, Elsevier, vol. 64(C), pages 66-77.
    10. Mladen Stamenković & Ivan Anić & Marijana Petrović & Nataša Bojković, 2016. "An ELECTRE approach for evaluating secondary education profiles: evidence from PISA survey in Serbia," Annals of Operations Research, Springer, vol. 245(1), pages 337-358, October.
    11. Barra, Cristian & Boccia, Marinella, 2019. "“The determinants of students' achievement: a difference between OECD and not OECD countries”," MPRA Paper 92561, University Library of Munich, Germany.
    12. Tommaso Agasisti & Patrizia Falzetti, 2017. "Between-classes sorting within schools and test scores: an empirical analysis of Italian junior secondary schools," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 64(1), pages 1-45, March.
    13. Guarini, Giulio & Laureti, Tiziana & Garofalo, Giuseppe, 2018. "Territorial and individual educational inequality: A Capability Approach analysis for Italy," Economic Modelling, Elsevier, vol. 71(C), pages 247-262.
    14. Mariagiulia Matteucci & Stefania Mignani, 2014. "Exploring Regional Differences in the Reading Competencies of Italian Students," Evaluation Review, , vol. 38(3), pages 251-290, June.
    15. Krause-Pilatus, Annabelle & Schüller, Simone, 2014. "Evidence and Persistence of Education Inequality in an Early-Tracking System: The German Case," IZA Discussion Papers 8545, Institute of Labor Economics (IZA).
    16. Murat Marina, 2012. "Do Immigrant Students Succeed? Evidence from Italy and France," Global Economy Journal, De Gruyter, vol. 12(3), pages 1-22, September.
    17. Marina Murat, 2011. "Do immigrant students succeed? Evidence from Italy and France based on PISA 2006," Department of Economics 0670, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    18. Gustavo A. Marrero & Juan C. Palomino & Gabriela Sicilia, 2022. "Inequality of Opportunity in Educational Achievement in Western Europe: contributors and channels," Working Papers 612, ECINEQ, Society for the Study of Economic Inequality.
    19. Jerrim, John & Lopez-Agudo, Luis Alejandro & Marcenaro-Gutierrez, Oscar D. & Shure, Nikki, 2017. "What happens when econometrics and psychometrics collide? An example using the PISA data," Economics of Education Review, Elsevier, vol. 61(C), pages 51-58.
    20. Borgna, Camilla & Struffolino, Emanuela, 2017. "Pushed or pulled? Girls and boys facing early school leaving risk in Italy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 61, pages 298-313.

    More about this item

    Keywords

    education inequalities; social origins; schooling tracking; Italy; regional divides;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:saq:wpaper:4/20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pierluigi Montalbano (email available below). General contact details of provider: https://edirc.repec.org/data/dtrosit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.