[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/qss/dqsswp/1508.html
   My bibliography  Save this paper

When and why do initially high attaining poor children fall behind?

Author

Listed:
  • Claire Crawford

    (Department of Economics, University of Warwick and Institute for Fiscal Studies)

  • Lindsey Macmillan

    (Department of Quantitative Social Science, Institute of Education, University College London)

  • Anna Vignoles

    (Faculty of Education, University of Cambridge)

Abstract
The role of education as a potential driver of social mobility has been well established and it is critical that we understand how children from different socio-economic backgrounds fare in the education system. In this paper, we examine the trajectories of initially high- and low-achieving children from lower and higher socio-economic status families from age 7 through to the end of compulsory education (age 16) in England for the first time. This enables us to provide new insights into when initially high attaining poor children fall behind their better-off peers. We show that there are substantial differences in educational attainment by socio-economic background at age 7, and that these differences increase as children move through the education system. Our results indicate that pupils from poor backgrounds who score highly in primary school fall behind their better-off but lower achieving peers during secondary school. These findings are not caused by ''regression to the mean'' (where a child with 'high' or 'low' achievement on any given day may have over- or under-performed relative to their 'true' attainment, meaning that the next time they are tested they will look more like the average individual). This suggests that secondary school may be a critical period to intervene to ensure poor children do not fall behind their better-off peers. We also provide suggestive evidence on the extent to which these patterns can be explained by the types of schools that pupils from different backgrounds attend, and by the differing attitudes and aspirations of the pupils and their families. Our analysis suggests that there is less convergence amongst pupils who attend the same schools. And if all pupils had the attitudes and aspirations of the average pupil, there would be more convergence. While we remain cautious about the implications of these findings, they provide suggestive evidence that schools (or the sorting of pupils into schools) and the attitudes and aspirations held by children from different backgrounds may contribute to the convergence in attainment that we see.

Suggested Citation

  • Claire Crawford & Lindsey Macmillan & Anna Vignoles, 2015. "When and why do initially high attaining poor children fall behind?," DoQSS Working Papers 15-08, Quantitative Social Science - UCL Social Research Institute, University College London.
    • Handle: RePEc:qss:dqsswp:1508
    as

    Download full text from publisher

    File URL: https://repec.ucl.ac.uk/REPEc/pdf/qsswp1508.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gibbons, Steve & Machin, Stephen, 2003. "Valuing English primary schools," Journal of Urban Economics, Elsevier, vol. 53(2), pages 197-219, March.
    2. Jo Blanden & Paul Gregg & Lindsey Macmillan, 2007. "Accounting for Intergenerational Income Persistence: Noncognitive Skills, Ability and Education," Economic Journal, Royal Economic Society, vol. 117(519), pages 43-60, March.
    3. Paul Clarke & Claire Crawford & Fiona Steele & Anna Vignoles, 2010. "The Choice between fixed and random effects models: some considerations for educational research," The Centre for Market and Public Organisation 10/240, The Centre for Market and Public Organisation, University of Bristol, UK.
    4. A. B. Atkinson & S. P. Jenkins, 1984. "The Steady-State Assumption and the Estimation of Distributional and Related Models," Journal of Human Resources, University of Wisconsin Press, vol. 19(3), pages 358-376.
    5. Cunha, Flavio & Heckman, James J. & Lochner, Lance, 2006. "Interpreting the Evidence on Life Cycle Skill Formation," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 1, chapter 12, pages 697-812, Elsevier.
    6. Haroon Chowdry & Claire Crawford & Lorraine Dearden & Alissa Goodman & Anna Vignoles, 2013. "Widening participation in higher education: analysis using linked administrative data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 431-457, February.
    7. Jo Blanden, 2004. "Family Income and Educational Attainment: A Review of Approaches and Evidence for Britain," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 20(2), pages 245-263, Summer.
    8. Gary S. Becker & Nigel Tomes, 1994. "Human Capital and the Rise and Fall of Families," NBER Chapters, in: Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, Third Edition, pages 257-298, National Bureau of Economic Research, Inc.
    9. Rebecca Allen, 2007. "Allocating Pupils to Their Nearest Secondary School: The Consequences for Social and Ability Stratification," Urban Studies, Urban Studies Journal Limited, vol. 44(4), pages 751-770, April.
    10. Jo Blanden & Lindsey Macmillan, 2014. "Education and Intergenerational Mobility: Help or Hindrance?," CASE Papers case179, Centre for Analysis of Social Exclusion, LSE.
    11. Leon Feinstein, 2004. "Mobility in Pupils' Cognitive Attainment During School Life," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 20(2), pages 213-229, Summer.
    12. repec:cep:sticas:/179 is not listed on IDEAS
    13. Rebecca Allen & Simon Burgess & Tomas Key, 2010. "Choosing secondary school by moving house: school quality and the formation of neighbourhoods," The Centre for Market and Public Organisation 10/238, The Centre for Market and Public Organisation, University of Bristol, UK.
    14. John Jerrim & Anna Vignoles, 2013. "Social mobility, regression to the mean and the cognitive development of high ability children from disadvantaged homes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(4), pages 887-906, October.
    15. repec:bla:econom:v:70:y:2003:i:277:p:73-97 is not listed on IDEAS
    16. Rebecca Allen & Anna Vignoles, 2006. "What Should an Index of School Segregation Measure?," CEE Discussion Papers 0060, Centre for the Economics of Education, LSE.
    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. Gwyther Rees, 2018. "The Association of Childhood Factors with Children’s Subjective Well-Being and Emotional and Behavioural Difficulties at 11 years old," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 11(4), pages 1107-1129, August.

    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. Claire Crawford & Lindsey Macmillan & Anna Vignoles, 2015. "When and why do initially high attaining poor children fall behind?," DoQSS Working Papers 15-08, Quantitative Social Science - UCL Social Research Institute, University College London.
    2. repec:cep:spccrp:20 is not listed on IDEAS
    3. Crawford, Claire & Macmillan, Lindsey & Vignoles, Anna F., 2015. "When and why do initially high attaining poor children fall behind?," LSE Research Online Documents on Economics 121535, London School of Economics and Political Science, LSE Library.
    4. Jake Anders, 2012. "What's the link between household income and going to university?," DoQSS Working Papers 12-01, Quantitative Social Science - UCL Social Research Institute, University College London.
    5. Jo Blanden & Lindsey Macmillan, 2014. "Education and Intergenerational Mobility: Help or Hindrance?," CASE Papers case179, Centre for Analysis of Social Exclusion, LSE.
    6. Rebecca Allen & Simon Burgess & Leigh McKenna, 2010. "How should we treat under-performing schools? A regression discontinuity analysis of school inspections in England," DoQSS Working Papers 10-20, Quantitative Social Science - UCL Social Research Institute, University College London.
    7. Tharcisio Leone, 2019. "The Geography of Intergenerational Mobility: Evidence of Educational Persistence and the “Great Gatsby Curve" in Brazil," Documentos de Trabajo 17526, The Latin American and Caribbean Economic Association (LACEA).
    8. Teodora Boneva & Christopher Rauh, 2017. "Socio-Economic Gaps in University Enrollment: The Role of Perceived Pecuniary and Non-Pecuniary Returns," Working Papers 2017-080, Human Capital and Economic Opportunity Working Group.
    9. Cornelissen Thomas & Jirjahn Uwe & Tsertsvadze Georgi, 2008. "Parental Background and Earnings: German Evidence on Direct and Indirect Relationships," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(5-6), pages 554-572, October.
    10. Aina, Carmen & Nicoletti, Cheti, 2018. "The intergenerational transmission of liberal professions," Labour Economics, Elsevier, vol. 51(C), pages 108-120.
    11. Hellier, Joël, 2017. "Stratified higher education,social mobility at the top and efficiency: The case of the French ‘Grandes écoles’," MPRA Paper 76724, University Library of Munich, Germany.
    12. Major, Lee Elliott & Eyles, Andrew & Machin, Stephen, 2021. "Unequal learning and labour market losses in the crisis: consequences for social mobility," LSE Research Online Documents on Economics 114413, London School of Economics and Political Science, LSE Library.
    13. Rebecca Allen & Simon Burgess & Tomas Key, 2010. "Choosing secondary school by moving house: school quality and the formation of neighbourhoods," The Centre for Market and Public Organisation 10/238, The Centre for Market and Public Organisation, University of Bristol, UK.
    14. Cormac O'Dea & Ian Preston, 2012. "The distributional impact of public spending in the UK," IFS Working Papers W12/06, Institute for Fiscal Studies.
    15. Paul Gregg & Lindsey Macmillan & Claudia Vittori, 2019. "Intergenerational income mobility: access to top jobs, the low-pay no-pay cycle and the role of education in a common framework," Journal of Population Economics, Springer;European Society for Population Economics, vol. 32(2), pages 501-528, April.
    16. Leone, Tharcisio, 2019. "The geography of intergenerational mobility: Evidence of educational persistence and the "Great Gatsby Curve" in Brazil," GIGA Working Papers 318, GIGA German Institute of Global and Area Studies.
    17. Carmen Aina & Cheti Nicoletti, 2014. "The intergenerational transmission of liberal professions: nepotism versus abilities," Discussion Papers 14/14, Department of Economics, University of York.
    18. Paul Gregg & Lindsey Macmillan & Claudia Vittori, 2015. "Nonlinear Estimation of Lifetime Intergenerational Economic Mobility and the Role of Education," DoQSS Working Papers 15-03, Quantitative Social Science - UCL Social Research Institute, University College London.
    19. Nicoletti, Cheti & Aina, Carmen, 2014. "The intergenerational mobility of liberal professions: nepotism versus abilities," ISER Working Paper Series 2014-39, Institute for Social and Economic Research.
    20. Anna Christina D'Addio, 2007. "Intergenerational Transmission of Disadvantage: Mobility or Immobility Across Generations?," OECD Social, Employment and Migration Working Papers 52, OECD Publishing.
    21. Leone, Tharcisio, 2017. "The gender gap in intergenerational mobility: Evidence of educational persistence in Brazil," Discussion Papers 2017/27, Free University Berlin, School of Business & Economics.

    More about this item

    Keywords

    Social Mobility; Education Achievement; Regression to the mean;
    All these keywords.

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

    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:qss:dqsswp:1508. 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: Dr Neus Bover Fonts (email available below). General contact details of provider: https://edirc.repec.org/data/dqioeuk.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.