Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-02T23:21:37.742Z Has data issue: false hasContentIssue false

Origins of Social Immobility and Inequality: Parenting and Early Child Development

Published online by Cambridge University Press:  26 March 2020

John Ermisch*
Affiliation:
Institute for Social and Economic Research, University of Essex

Abstract

There is growing evidence that differences in children's intellectual, emotional and behavioural development by parents' socio-economic status emerge at early ages and that these differences cast a long shadow over subsequent achievements. This article demonstrates with the Millennium Cohort Study that differences by parents‘ income group in cognitive and behavioural development emerge by the child's third birthday. It shows that an important part of these differences can be accounted for by ‘what parents do’ in terms of educational activities and parenting style.

Type
Articles
Copyright
Copyright © 2008 National Institute of Economic and Social Research

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

I am grateful for financial support from the UK Economic and Social Research Council and from the Russell Sage Foundation, through its Visiting Scholar programme. I have benefited from discussions with Markus Jäntti, comments from Heather Joshi, Hilary Metcalf, an anonymous referee and participants in seminars at the Russell Sage Foundation and Columbia University.

References

Almond, D., Chay, K. and Lee, D. (2005), ‘The costs of low birth weight’, Quarterly Journal of Economics, 120, pp. 1031–83.Google Scholar
Barker, D. (1995), ‘Fetal origins of coronary heart disease’, British Medical Journal, 311, pp. 171–4.CrossRefGoogle ScholarPubMed
Black, S., Devereux, P. and Salvanes, K. (2005), ‘From the cradle to the grave? The effect of birth weight on adult outcomes of children’, University of California -Los Angeles.Google Scholar
Behrman, J. and Rosenzweig, M. (2004), ‘Returns to birthweight’, The Review of Economics and Statistics, 86, pp. 586601.CrossRefGoogle Scholar
Carnegie Task Force on Meeting the Needs of Young Children (1994), Starting Points: Meeting the Needs of Our Youngest Children, New York, Carnegie Corporation of New York.Google Scholar
Case, A., Fertig, A. and Paxson, C. (2005), ‘The lasting impact of childhood health and circumstance’, Journal of Health Economics, 24,pp.365–89.CrossRefGoogle ScholarPubMed
Cunha, F. and Heckman, J.J. (2007), ‘The technology of skill formation’, American Economic Review, 97 (Papers and Proceeding), 97, pp. 3147.CrossRefGoogle Scholar
Dearden, L., Machin, S. and Reed, H. (1997), ‘Intergenerational mobility in Britain’, The Economic Journal, 107, pp. 4756.CrossRefGoogle Scholar
Ermisch, J., Francesconi, M. and Siedler, T. (2006), ‘Intergenerational economic mobility and assortative mating’, The Economic Journal, 116, pp. 659–79.CrossRefGoogle Scholar
Feinstein, L. (2003), ‘Inequality in the early cognitive development of British children in the 1970 cohort’, Economica, 70, pp. 73- 98.CrossRefGoogle Scholar
Hansen, K. (2006), Millennium Cohort Study First and Second Surveys. A Guide to the Datasets, First Edition (July), London, Centre for Longitudinal Studies, Institute of Education, University of London.Google Scholar
Heckman, J.J., Stixrud, J. and Urzua, S. (2006), ‘The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior’, Journal of Labor Economics, 24, pp. 411- 82.CrossRefGoogle Scholar
Illsley, R. (2002), ‘A city's schools: from inequality of input to inequality of outcome’, Oxford Review of Education, 28, pp. 427- 45.CrossRefGoogle Scholar
Jakubson, G. (1991), ‘Estimation and test of the union wage effect using panel data’, Review of Economic Studies, 58, pp. 971–91.CrossRefGoogle Scholar
Plomin, R. (1999), ‘Genetics and general cognitive ability’, Nature, 402, pp. C25C29.CrossRefGoogle ScholarPubMed
Plomin, R. et al. (1997), Behavioral Genetics, New York, W.H. Freeman and Co.Google Scholar
Pudney, S.E. (1982), ‘Estimating latent variable systems when specification is uncertain: generalized component analysis and the eliminant method’, Journal of the American Statistical Association, 77(380), pp. 883–9.CrossRefGoogle Scholar
Rowe, D.C. et al. (1999), ‘Genetic and environmental influences on vocabulary IQ: parental education as moderator’, Child Development, 70, pp, 1151–62.CrossRefGoogle ScholarPubMed
Royer, H. (2005), ‘Separated at girth: estimating the long-run intergenerational effects of birthweight using twins’, School of Public Health, University of Michigan.Google Scholar
Rutter, M. (2006), Genes and Behavior: Nature-Nuture Interplay Explained, Oxford, Blackwell.Google Scholar
Shonkoff, J.P. and Philips, D.A. (eds.) (2000), From Neurons to Neighborhoods: The Science of Early Child Development, Washington DC, National Academies Press.Google Scholar
Sylva, K., Melhuish, E., Sammons, P., Siraj-Blatchford, I. and Taggart, B. (2004), The Effective Provision of Pre-School Education (EPPE) Project: Findings from the Pre-school to end of Key Stage 1, London, DfESGoogle Scholar
Turkheimer, E. et al. (2003), ‘Socioeconomic status modified heritability of IQ in young children’, Psychological Science, 14, pp. 623–8.CrossRefGoogle Scholar