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Using the Longitudinal Study of Young People in England for research into Higher Education access

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Listed author(s):
  • Jake Anders

    ()

    (Institute of Education, University of London)

Abstract

The Longitudinal Study of Young People in England (LSYPE) has the potential to be an important new resource for addressing research questions regarding access to Higher Education. This paper outlines the data available in the LSYPE and assesses its quality, particularly relative to other datasets that have been used to address similar questions in the past. The paper finds many positive features of the data. These include data collection from parents (including much information on family background characteristics) and good family income measurement compared with many previous studies. The LSYPE also measures a greater depth of HE-related outcomes than some previous datasets, including application, entry, subject studied and institution attended. However, comparison with official statistics suggests that this may be undermined by a large overestimation of the proportion of young people who enter Higher Education (as much as ten percentage points) than we would see in a truly nationally representative sample. There is also some evidence of underreporting of family income. Nevertheless, the paper concludes that analysis of the LSYPE has the potential to shed new light on university access in England.

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Paper provided by Department of Quantitative Social Science - UCL Institute of Education, University College London in its series DoQSS Working Papers with number 12-13.

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Date of creation: 20 Dec 2012
Handle: RePEc:qss:dqsswp:1213
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Department of Quantitative Social Science. UCL IOE, 20 Bedford Way London WC1H 0AL

Phone: (44) (0)20 7612 6654. Eliminate (44) and add (0) if calling from inside the UK. Add (44) and eliminate (0) if calling from abroad.
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Web page: http://www.ioe.ac.uk/research/departments/qss/35445.html

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Keywords: : Higher Education; Socioeconomic Gradient; Intergenerational Mobility; Longitudinal Research; Survey Data.;

Find related papers by JEL classification:

  • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
  • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion

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  1. Simon Burgess & Carol Propper & John A. Rigg, 2004. "The Impact of Low Income on Child Health: Evidence from a Birth Cohort Study," CASE Papers 085, Centre for Analysis of Social Exclusion, LSE.
  2. John Micklewright & Sylke V. Schnepf, 2010. "How reliable are income data collected with a single question?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 409-429.
  3. Fernando Galindo-Rueda & Oscar Marcenaro-Gutierrez & Anna Vignoles, 2004. "The Widening Socio-Economic Gap in UK Higher Education," National Institute Economic Review, National Institute of Economic and Social Research, vol. 190(1), pages 75-88, October.
  4. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  5. Alfonso Miranda & Sophia Rabe-Hesketh, 2014. "Missing ordinal covariate with informative selection," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(2), pages 319-344, 02.
  6. 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.
  7. John Jerrim, 2011. "Disadvantaged children’s ``low'' educational expectations: Are the US and UK really so different to other industrialized nations?," DoQSS Working Papers 11-04, Department of Quantitative Social Science - UCL Institute of Education, University College London.
  8. Evans, William N & Oates, Wallace E & Schwab, Robert M, 1992. "Measuring Peer Group Effects: A Study of Teenage Behavior," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 966-991, October.
  9. Donna Ginther & Robert Haveman & Barbara Wolfe, 2000. "Neighborhood Attributes as Determinants of Children's Outcomes: How Robust Are the Relationships?," Journal of Human Resources, University of Wisconsin Press, vol. 35(4), pages 603-642.
  10. Oscar Marcenaro-Gutierrez & Fernando Galindo-Rueda & Anna Vignoles, 2007. "Who actually goes to university?," Empirical Economics, Springer, vol. 32(2), pages 333-357, May.
  11. Ermisch, John & Francesconi, Marco, 2001. "Family Matters: Impacts of Family Background on Educational Attainments," Economica, London School of Economics and Political Science, vol. 68(270), pages 137-156, May.
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Cited by:

  1. Daniel Gladwell & Gurleen Popli & Aki Tsuchiya, 2015. "A Dynamic Analysis of Skill Formation and NEET status," Working Papers 2015016, The University of Sheffield, Department of Economics.
  2. Jake Anders & John Micklewright, 2013. "Teenagers' expectations of applying to university: how do they change?," DoQSS Working Papers 13-13, Department of Quantitative Social Science - UCL Institute of Education, University College London.
  3. Jake Anders, 2014. "Does an aptitude test affect socioeconomic and gender gaps in attendance at an elite university?," DoQSS Working Papers 14-07, Department of Quantitative Social Science - UCL Institute of Education, University College London.

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