IDEAS home Printed from https://ideas.repec.org/a/nos/voprob/2020i4p85-112.html
   My bibliography  Save this article

School Socioeconomic Composition as a Factor of Educational Inequality Reproduction

Author

Abstract

Yuliya Kersha - Postgraduate Student, Research Assistant, Pinsky Centre of General and Extracurricular Education; Lecturer, Department of Educational Programs, Institute of Education, National Research University Higher School of Economics.Address: 20 Myasnitskaya Str., 10100 Moscow, Russian Federation. E-mail: ykersha@hse.ruIt can be inferred from international findings that school socioeconomic composition (SEC) is a major factor of educational inequality in secondary education at the school level. SEC is believed to have a positive relationship with student achievement along with individual student characteristics. However, a review of research methods used in most studies calls the existence of an influence into question.A study was carried out to evaluate causal relations between school SEC and student achievement. Multilevel regression analysis and propensity score matching (PSM) methods were applied to the panel study Trajectories in Education and Careers data in order to measure the effects of one year of study at schools with low vs. high socioeconomic composition. Correlational and quasi-experimental effect sizes were compared.Analysis results confirm that school SEC is a key factor of educational inequality in Russian secondary education, the inequality effects of school composition overlapping only partially with those of school location. Within a year of schooling, ninth-graders with similar individual characteristics may lose up to a quarter of standard error in PISA‑2012 scores if attending a school with low socioeconomic composition, while attending a high-SEC school would improve their educational outcomes by the end of the ninth grade. Negative effects were observed for two subject areas, which allows suggesting a systematic impact of SEC on student achievement. The final part of the article describes the theoretical and practical significance of the findings and presents the main directions of further research in this field.

Suggested Citation

  • Yuliya Kersha, 2020. "School Socioeconomic Composition as a Factor of Educational Inequality Reproduction," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 4, pages 85-112.
    • Handle: RePEc:nos:voprob:2020:i:4:p:85-112
    as

    Download full text from publisher

    File URL: https://vo.hse.ru/data/2021/01/15/1344142612/Kersha%20ENG.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jacob M. Markman & Eric A. Hanushek & John F. Kain & Steven G. Rivkin, 2003. "Does peer ability affect student achievement?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(5), pages 527-544.
    2. Gordey A. Yasterbov & Alexey R. Bessudnov & Marina A. Pinskaya & Sergey G. Kosaretsky, 2014. "Contextualizing Academic Performance In Russian Schools: School Characteristics, The Composition Of Student Body And Local Deprivation," HSE Working papers WP BRP 55/SOC/2014, National Research University Higher School of Economics.
    3. 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.
    4. Sergey G. Kosaretsky & Irina G. Grunicheva & Marina A. Pinskaya, 2014. "School System And Educational Policy In A Highly Stratified Post-Soviet Society: The Importance Of Social Context," HSE Working papers WP BRP 22/PA/2014, National Research University Higher School of Economics.
    5. Anastasia Kapuza & Yuliya Kersha & Andrey Zakharov & Tatiana Khavenson, 2017. "Educational Attainment and Social Inequality in Russia: Dynamics and Correlations with Education Policies," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 4, pages 10-35.
    6. David Konstantinovsky & Dmitry Kurakin & Yana Roshchina & Viktor Vakhshtayn, 2006. "The accessibility of quality education in Russia: opportunities and restrictions," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 2, pages 186-202.
    Full references (including those not matched with items on IDEAS)

    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. Керша Ю. Д., 2020. "Социально-Экономическая Композиция Школы Как Фактор Воспроизводства Неравенства В Образовании," Вопросы образования // Educational Studies Moscow, National Research University Higher School of Economics, issue 4, pages 85-112.
    2. Maria De Paola & Vincenzo Scoppa, 2010. "Peer group effects on the academic performance of Italian students," Applied Economics, Taylor & Francis Journals, vol. 42(17), pages 2203-2215.
    3. Anne Ardila Brenøe & Ulf Zölitz, 2020. "Exposure to More Female Peers Widens the Gender Gap in STEM Participation," Journal of Labor Economics, University of Chicago Press, vol. 38(4), pages 1009-1054.
    4. Oded Stark & Wiktor Budzinski, 2021. "A social‐psychological reconstruction of Amartya Sen’s measures of inequality and social welfare," Kyklos, Wiley Blackwell, vol. 74(4), pages 552-566, November.
    5. Tatiana Khavenson, 2019. "Integration of Schools in Latvia and Estonia Using Curriculum Reforms," Voprosy obrazovaniya / Educational Studies Moscow, National Research University Higher School of Economics, issue 3, pages 77-100.
    6. Steven N. Durlauf & Yannis M. Ioannides, 2010. "Social Interactions," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 451-478, September.
    7. Martin Schlotter & Guido Schwerdt & Ludger Woessmann, 2011. "Econometric methods for causal evaluation of education policies and practices: a non-technical guide," Education Economics, Taylor & Francis Journals, vol. 19(2), pages 109-137.
    8. repec:mpr:mprres:7547 is not listed on IDEAS
    9. Rhys Murrian & Paul A. Raschky & Klaus Ackermann, 2024. "Friends, Key Players and the Adoption and Use of Experience Goods," Monash Economics Working Papers 2024-17, Monash University, Department of Economics.
    10. Brian Beach & Martin Saavedra, 2015. "Mitigating the Effects of Low Birth Weight: Evidence from Randomly Assigned Adoptees," American Journal of Health Economics, MIT Press, vol. 1(3), pages 275-296, Summer.
    11. Clifton-Sprigg, Joanna, 2014. "Educational spillovers and parental migration," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-46, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    12. Marco Tonello, 2011. "Mechanisms of peer interactions between native and non-native students: rejection or integration?," Working Papers 2011/21, Institut d'Economia de Barcelona (IEB).
    13. Chin, Aimee & Daysal, N. Meltem & Imberman, Scott A., 2013. "Impact of bilingual education programs on limited English proficient students and their peers: Regression discontinuity evidence from Texas," Journal of Public Economics, Elsevier, vol. 107(C), pages 63-78.
    14. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
    15. ,, 2009. "Monopolistic group design with peer effects," Theoretical Economics, Econometric Society, vol. 4(1), March.
    16. Bet Caeyers, 2014. "Peer effects in development programme awareness of vulnerable groups in rural Tanzania," CSAE Working Paper Series 2014-11, Centre for the Study of African Economies, University of Oxford.
    17. Kang, Changhui, 2007. "Classroom peer effects and academic achievement: Quasi-randomization evidence from South Korea," Journal of Urban Economics, Elsevier, vol. 61(3), pages 458-495, May.
    18. Stark, Oded, 2021. "An optimal split of school classes," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 668-675.
    19. James Farrell, 2019. "Peer Effects Among Teachers: A Study of Retirement Investments," Journal of Family and Economic Issues, Springer, vol. 40(3), pages 486-497, September.
    20. Xu Lin, 2010. "Identifying Peer Effects in Student Academic Achievement by Spatial Autoregressive Models with Group Unobservables," Journal of Labor Economics, University of Chicago Press, vol. 28(4), pages 825-860, October.
    21. Adriaan R Soetevent & Peter Kooreman, 2005. "Social Ties within School Classes: The Roles of Gender, Ethnicity, and Having Older Siblings," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 21(3), pages 373-391, Autumn.

    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:nos:voprob:2020:i:4:p:85-112. 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: Marta Morozova (email available below). General contact details of provider: http://vo.hse.ru/en/ .

    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.