IDEAS home Printed from https://ideas.repec.org/a/spr/soinre/v157y2021i2d10.1007_s11205-021-02668-w.html
   My bibliography  Save this article

What School Factors are Associated with the Success of Socio-Economically Disadvantaged Students? An Empirical Investigation Using PISA Data

Author

Listed:
  • Tommaso Agasisti

    (Politecnico di Milano Graduate School of Business)

  • Francesco Avvisati

    (Organisation for Economic Co-operation and Development (OECD))

  • Francesca Borgonovi

    (Institute of Education – University College London)

  • Sergio Longobardi

    (University of Naples “Parthenope”)

Abstract

Many school-level policies, such as school funding formulae and teacher allocation mechanisms, aim at reducing the influence of students’ low socio-economic condition on academic achievement. Benchmarks and indicators based on large-scale international assessments can be used to measure academic success and identify if and when disadvantaged students are successful. We build on such work and develop a new method for identifying a cross-country comparable metric of the academic success of socio-economically disadvantaged students using data from the Programme for International Student Assessment (PISA). We estimate the prevalence of successful disadvantaged students in 56 countries, as well as changes over time between 2006 and 2015. In addition, we focus on the PISA 2015 edition and explore school factors associated with the probability that disadvantaged students will be successful academically in a subsample of 18 countries. Findings reveal that successful disadvantaged students attend schools with a better disciplinary climate and that provide additional time for instruction in key subjects.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:soinre:v:157:y:2021:i:2:d:10.1007_s11205-021-02668-w
    DOI: 10.1007/s11205-021-02668-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11205-021-02668-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11205-021-02668-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), 2011. "Handbook of the Economics of Education," Handbook of the Economics of Education, Elsevier, edition 1, volume 4, number 4, June.
    2. Hanushek, Eric A. & Woessmann, Ludger, 2011. "The Economics of International Differences in Educational Achievement," Handbook of the Economics of Education, in: Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), Handbook of the Economics of Education, edition 1, volume 3, chapter 2, pages 89-200, Elsevier.
    3. Tommaso Agasisti & Sergio Longobardi & Andrea Regoli, 2017. "A cross-country panel approach to exploring the determinants of educational equity through PISA data," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1243-1260, May.
    4. Nicholas Bloom & Renata Lemos & Raffaella Sadun & John Van Reenen, 2015. "Does Management Matter in schools?," Economic Journal, Royal Economic Society, vol. 0(584), pages 647-674, May.
    5. Ludger Wößmann, 2008. "Efficiency and equity of European education and training policies," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 15(2), pages 199-230, April.
    6. 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.
    7. Tommaso Agasisti & Sergio Longobardi, 2014. "Educational institutions, resources, and students' resiliency: an empirical study about OECD countries," Economics Bulletin, AccessEcon, vol. 34(2), pages 1055-1067.
    8. Eric A. Hanushek & Marc Piopiunik & Simon Wiederhold, 2019. "The Value of Smarter Teachers: International Evidence on Teacher Cognitive Skills and Student Performance," Journal of Human Resources, University of Wisconsin Press, vol. 54(4), pages 857-899.
    9. Robert Haveman & Barbara Wolfe, 1995. "The Determinants of Children's Attainments: A Review of Methods and Findings," Journal of Economic Literature, American Economic Association, vol. 33(4), pages 1829-1878, December.
    10. 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.
    11. 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.
    12. William Meredith, 1993. "Measurement invariance, factor analysis and factorial invariance," Psychometrika, Springer;The Psychometric Society, vol. 58(4), pages 525-543, December.
    13. Julie Berry Cullen & Steven D. Levitt & Erin Robertson & Sally Sadoff, 2013. "What Can Be Done to Improve Struggling High Schools?," Journal of Economic Perspectives, American Economic Association, vol. 27(2), pages 133-152, Spring.
    14. 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.
    15. John Jerrim, 2012. "The Socio‐Economic Gradient in Teenagers' Reading Skills: How Does England Compare with Other Countries?," Fiscal Studies, Institute for Fiscal Studies, vol. 33(2), pages 159-184, June.
    16. Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), 2011. "Handbook of the Economics of Education," Handbook of the Economics of Education, Elsevier, edition 1, volume 3, number 3, June.
    17. Sophia Rabe-Hesketh & Anders Skrondal, 2012. "Multilevel and Longitudinal Modeling Using Stata, 3rd Edition," Stata Press books, StataCorp LLC, edition 3, number mimus2, August.
    18. Todd Stinebrickner & Ralph Stinebrickner, 2001. "Peer Effects Among Students from Disadvantaged Backgrounds," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20013, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
    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. Francisco, Decereh R & Allorda, Althea I & Cruda, Chris Laurence M & Cruda, Zarena Nikka F & Dejado, Shainne Evanrose F & Dela Cruz, Cherry Mae S & Opisan, Anesa C & Pateǹo, Gian Vincent G. & Quirino, 2024. "The Influence of Parental Involvement and Socioeconomic Status on Academic Achievement among Special Science Class Students," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(4), pages 2380-2390, April.
    2. Faming Wang & Ronnel B. King & Shing On Leung, 2022. "Beating the odds: Identifying the top predictors of resilience among Hong Kong students," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 15(5), pages 1921-1944, October.
    3. Derya Topdağ & Ebru Çağlayan Akay, 2024. "The Bayesian Model Averaging (BMA) Approach for Determining the Factors Affecting the Achievement of Students with Low Socioeconomic Status," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul Journal of Economics-Istanbul Iktisat Dergisi, vol. 0(40), pages 1-11, June.
    4. Borgonovi, Francesca & Ferrara, Alessandro, 2022. "A longitudinal perspective on the effects of Covid-19 on students' resilience. The Effect of the pandemic on the reading and mathematics achievement of 8th and 5th graders in Italy," SocArXiv 94erb_v1, Center for Open Science.

    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. Tommaso Agasisti & Sergio Longobardi & Vincenzo Prete & Felice Russo, 2018. "Multidimensional poverty measures for analysing educational poverty in European countries," Working papers 73, Società Italiana di Economia Pubblica.
    2. Åsa Johansson, 2016. "Public Finance, Economic Growth and Inequality: A Survey of the Evidence," OECD Economics Department Working Papers 1346, OECD Publishing.
    3. Bernhard C. Dannemann, 2020. "Peer Effects in Secondary Education: Evidence from the 2015 Trends in Mathematics and Science Study Based on Homophily," Working Papers V-428-20, University of Oldenburg, Department of Economics, revised Feb 2020.
    4. Gradstein, Mark & Brückner, Markus, 2013. "Income and schooling," CEPR Discussion Papers 9365, C.E.P.R. Discussion Papers.
    5. Hanushek, Eric A., 2021. "Addressing cross-national generalizability in educational impact evaluation," International Journal of Educational Development, Elsevier, vol. 80(C).
    6. 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.
    7. Nathalie Picard & François-Charles Wolff, 2014. "Les inégalités intrafamiliales d'éducation en France," Revue économique, Presses de Sciences-Po, vol. 65(6), pages 813-840.
    8. Jerrim, J. & John Micklewright, 2013. "GINI DP 65: Socioeconomic gradients in children’s cognitive skills: are cross-country comparisons robust to who reports family background?," GINI Discussion Papers 65, AIAS, Amsterdam Institute for Advanced Labour Studies.
    9. 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.
    10. José M. Cordero & Víctor Cristóbal & Daniel Santín, 2018. "Causal Inference On Education Policies: A Survey Of Empirical Studies Using Pisa, Timss And Pirls," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 878-915, July.
    11. Eric A. Hanushek & Elizabeth Ettema, 2017. "Defining Productivity in Education: Issues and Illustrations," The American Economist, Sage Publications, vol. 62(2), pages 165-183, October.
    12. Dannemann, Bernhard C., 2019. "Peer effects in secondary education: Evidence from trends in mathematics and science study 2015 based on weak-tie bonds," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203485, Verein für Socialpolitik / German Economic Association.
    13. Ramos, Raul & Duque, Juan Carlos & Nieto, Sandra, 2016. "Decomposing the Rural-Urban Differential in Student Achievement in Colombia using PISA Microdata/Una descomposición del diferencial rural-urbano en los rendimientos educativos en Colombia a partir de ," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 34, pages 379-412, Mayo.
    14. John Jerrim & John Micklewright, 2012. "Socioeconomic gradients in children's cognitive skills: Are cross-country comparisons robust to who reports family background?," DoQSS Working Papers 12-06, Quantitative Social Science - UCL Social Research Institute, University College London.
    15. Gregorio Gimenez & Luis Vargas-Montoya, 2021. "ICT Use and Successful Learning: The Role of the Stock of Human Capital," Mathematics, MDPI, vol. 9(14), pages 1-15, July.
    16. Eric A. Hanushek & Jacob D. Light & Paul E. Peterson & Laura M. Talpey & Ludger Woessmann, 2022. "Long-run Trends in the U.S. SES-Achievement Gap," Education Finance and Policy, MIT Press, vol. 17(4), pages 608-640, Fall.
    17. Eyles, Andrew & Machin, Stephen & McNally, Sandra, 2017. "Unexpected school reform: Academisation of primary schools in England," Journal of Public Economics, Elsevier, vol. 155(C), pages 108-121.
    18. Eric A. Hanushek & Guido Schwerdt & Ludger Woessmann & Lei Zhang, 2017. "General Education, Vocational Education, and Labor-Market Outcomes over the Lifecycle," Journal of Human Resources, University of Wisconsin Press, vol. 52(1), pages 48-87.
    19. Catherine Haeck & Pierre Lefebvre, 2020. "The Evolution of Cognitive Skills Inequalities by Socioeconomic Status across Canada," Working Papers 20-04, Research Group on Human Capital, University of Quebec in Montreal's School of Management.
    20. Altinok, Nadir & Aydemir, Abdurrahman, 2017. "Does one size fit all? The impact of cognitive skills on economic growth," Journal of Macroeconomics, Elsevier, vol. 53(C), pages 176-190.

    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:spr:soinre:v:157:y:2021:i:2:d:10.1007_s11205-021-02668-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.