The use (and misuse) of statistics in understanding social mobility: regression to the mean and the cognitive development of high ability children from disadvantaged homes

John Jerrim () and Anna Vignoles
Additional contact information
John Jerrim: Department of Quantitative Social Science, Institute of Education, University of London. 20 Bedford Way, London WC1H 0AL, UK.

No 11-01, DoQSS Working Papers from Quantitative Social Science - UCL Social Research Institute, University College London

Abstract: Social mobility has emerged as one of the key academic and political topics in Britain over the last decade. Although economists and sociologists disagree on whether mobility has increased or decreased, and if this is a bigger issue in the UK than other developed countries, both groups recognise that education and skill plays a key role in explaining intergenerational persistence. This has led academics from various disciplines to investigate how rates of cognitive development may vary between children from rich and poor backgrounds. A number of key studies have definitively shown that a gap in cognitive skill between richer and poorer children is evident from a very early age. Some have also suggested that highly able children from disadvantaged homes are overtaken by their rich (but less able) peers before the age of 10 in terms of their cognitive skill. It is this last conclusion that we focus on in this paper, as it has become a widely cited “fact†within the academic literature on social mobility and child development, and has had a major influence on public policy and political debate. We investigate whether this latter finding is due to a spurious statistical artefact known as regression to the mean (RTM). Our analysis suggests that there are serious methodological problems plaguing the existing literature and that, after applying some simple adjustments for RTM, we obtain dramatically different results.

Keywords: Educational mobility; socio-economic gap; disadvantaged children; regression to the mean (search for similar items in EconPapers)
JEL-codes: C01 C54 I2 I28 (search for similar items in EconPapers)
Date: 2011-03-07, Revised 2011-04-20
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://repec.ucl.ac.uk/REPEc/pdf/qsswp1101.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:qss:dqsswp:1101

Access Statistics for this paper

More papers in DoQSS Working Papers from Quantitative Social Science - UCL Social Research Institute, University College London Quantitative Social Science, Social Research Institute, 55-59 Gordon Square, London WC1H 0NU. Contact information at EDIRC.
Bibliographic data for series maintained by Dr Neus Bover Fonts ().