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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
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    References listed on IDEAS

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    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.
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    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

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