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Inequality in education: Can Italian disadvantaged students close the gap?

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  • Agasisti, Tommaso
  • Longobardi, Sergio

Abstract

The relationship between socio-economic status and school achievement is well documented and extensive literature indicates that students from more advantaged backgrounds perform better at school. Despite this relationship, several international assessments have highlighted that in every country there are a relevant number of “resilient students”, i.e. students from a disadvantaged socio-economic background who achieve relatively high levels of performance in terms of education. In this paper, the determinants of resilience in the Italian educational system are investigated through the analysis of data from the OECD-PISA 2009 cycle, with a specific focus on the role of school-level variables that could help more students perform to a higher standard. The aim is to target a specific category of resilient students, namely those from a low socio-economic background at both family and school level, proposing an innovative statistical procedure to derive a sample of disadvantaged students attending disadvantaged schools. After this, a multilevel logistic approach is adopted to determine which specific characteristics of students, families and schools tend to give disadvantaged students a higher probability of becoming resilient students. Our results confirm that individual-level characteristics play a role, but also that some school factors (i.e. extra-curricular activities and school leadership) are equally involved, suggesting policy- and management-related implications.

Suggested Citation

  • Agasisti, Tommaso & Longobardi, Sergio, 2014. "Inequality in education: Can Italian disadvantaged students close the gap?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 52(C), pages 8-20.
  • Handle: RePEc:eee:soceco:v:52:y:2014:i:c:p:8-20
    DOI: 10.1016/j.socec.2014.05.002
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    Cited by:

    1. Abdulmumini Baba Alfa & Abdulmumini Baba Alfa & Mohd Zaini Abd Karim, 2016. "Student Enthusiasm as a Key Determinant of their Performance," International Review of Management and Marketing, Econjournals, vol. 6(2), pages 237-245.
    2. Sergio Longobardi & Margherita Maria Pagliuca & Andrea Regoli, 2018. "Can problem-solving attitudes explain the gender gap in financial literacy? Evidence from Italian students’ data," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1677-1705, July.
    3. Tommaso Agasisti & Sergio Longobardi & Andrea Regoli, 2014. "Does public spending improve educational resilience? A longitudinal analysis of OECD-PISA data," Working papers 3, Società Italiana di Economia Pubblica.
    4. Huebener, Mathias & Kuger, Susanne & Marcus, Jan, 2017. "Increased instruction hours and the widening gap in student performance," Labour Economics, Elsevier, vol. 47(C), pages 15-34.
    5. Paolo Liberati & Raffaele Lagravinese & Giuliano Resce, 2017. "How Does Economic Social And Cultural Status Affect The Efficiency Of Educational Attainments? A Comparative Analysis On Pisa Results," Departmental Working Papers of Economics - University 'Roma Tre' 0217, Department of Economics - University Roma Tre.
    6. Sergio Longobardi & Patrizia Falzetti & Margherita Maria Pagliuca, 2018. "Quis custiodet ipsos custodes? How to detect and correct teacher cheating in Italian student data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(3), pages 515-543, August.
    7. Ishizaka, Alessio & Resce, Giuliano, 2021. "Best-Worst PROMETHEE method for evaluating school performance in the OECD's PISA project," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    8. Oscar David Marcenaro-Gutierrez & Luis Alejandro Lopez-Agudo, 2021. "The back of the coin in resilience: on the characteristics of advantaged low-achieving students," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(1), pages 323-383, April.
    9. Tommaso Agasisti & Francesco Avvisati & Francesca Borgonovi & Sergio Longobardi, 2021. "What School Factors are Associated with the Success of Socio-Economically Disadvantaged Students? An Empirical Investigation Using PISA Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(2), pages 749-781, September.
    10. Tommaso Agasisti & Sergio Longobardi, 2017. "Equality of Educational Opportunities, Schools’ Characteristics and Resilient Students: An Empirical Study of EU-15 Countries Using OECD-PISA 2009 Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 134(3), pages 917-953, December.
    11. Giuseppe Coco & Raffaele Lagravinese & Giuliano Resce, 2020. "Beyond the weights: a multicriteria approach to evaluate inequality in education," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(4), pages 469-489, December.
    12. 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).
    13. Vicente, Iván & Pastor, José M. & Soler, Ángel, 2021. "Improving educational resilience in the OECD countries: Two convergent paths," Journal of Policy Modeling, Elsevier, vol. 43(6), pages 1149-1166.
    14. Angelica Hobjilă, 2019. "The Idea of “Inequality” in Alternative Textbooks for Primary School," Revista romaneasca pentru educatie multidimensionala - Journal for Multidimensional Education, Editura Lumen, Department of Economics, vol. 11(1), pages 301-311, March.
    15. Yan Yan & Xiaosong Gai, 2022. "High Achievers from Low Family Socioeconomic Status Families: Protective Factors for Academically Resilient Students," IJERPH, MDPI, vol. 19(23), pages 1-13, November.

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    More about this item

    Keywords

    Inequality; Disadvantaged schools; Resilient students; School-level policies; Educational production functions;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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