Scottish Longitudinal Study
Development & Support Unit
Books & Book Chapters
Scotland’s Census as a Research Resource
Graham, E., Findlay, A., Manley, D., McCollum, D., Popham, F. & van Ham, M. (2011) In 'Scotland's Population 2010: The Registrar General's Annual Review of Demographic Trends' 156th Ed, Chapter 10, pp73-87. National Records of Scotland: Edinburgh, 5 August 2011. ISBN: 978-1-874451-81-5 [SLS]
Available online: In 'Scotland's Population 2010: The Registrar General's Annual Review of Demographic Trends'
Download output document: Full Report (PDF 2.2MB)
Social mixing as a cure for negative neighbourhood effects: Evidence based policy or urban myth?
Manley, D., van Ham, M. & Doherty, J. (2011) In Bridge, G, Butler, T & Lees, L (eds), 'Mixed Communities: Gentrification by Stealth?' Chapter 11, pp151-168. The Policy Press: Bristol, 19 October 2011. ISBN: 9781847424938 [SLS]
Neighbourhood effects, housing tenure, and individual employment outcomes
Manley, D. & van Ham, M. (2011) In van Ham, M, Manley, D, Bailey, N, Simpson, L & Maclennan, D. (eds). 'Neighbourhood Effects Research: New Perspectives' Chapter 7, pp147-174. Springer, Dordrecht. ISBN: 978-94-007-2309-2 [SLS]
There are a number of serious shortcomings in much of the existing neighbourhood effects literature, most notably selection bias. As a result, many existing studies are likely to show correlations between individual outcomes and neighbourhood characteristics, instead of real causal effects. The empirical section of this chapter investigates whether the level of unemployment in a neighbourhood is related to the employment outcomes of residents. The study uses data from the Scottish Longitudinal Study (SLS) and estimates the probability that an unemployed person in 1991 has a job in 2001, and the probability than an employed person in 1991 remains in employment by 2001. The models clearly show a correlation between neighbourhood characteristics and individual employment outcomes. However, separate models by housing tenure show that these correlations are significant only for homeowners, and not for social renters. It is argued that this can be explained by selection bias for homeowners, which was largely absent for social renters. The main conclusion of the chapter is that (self-) selection should be more fully explored in studies of neighbourhood effects. Wherever possible, models investigating the impact of neighbourhood contexts on individual outcomes should take into account the different routes through which households enter neighbourhoods.
Available online: 'Neighbourhood Effects Research: New Perspectives'
Output from project: 2007_006
Neighbourhood ethnic mix and the formation of mixed-ethnic unions in Britain
Feng, Z., van Ham, M., Raab, G., Stillwell, J. & van Ham, M. (2010) In Stillwell, J. & van Ham, M. (eds), 'Ethnicity and Integration' Chapter 5, pp83-104. Springer, Dordrecht. ISBN: 978-90-481-9102-4 [SLS][ONS LS]
Building on a long history of research on residential segregation, this chapter explores how mixed-ethnic couples contribute to changing ethnic geographies. The study uses data from the Longitudinal Study (LS) for England and Wales and is the first UK study to examine the influence of geographical context on the formation of mixed-ethnic unions. By using longitudinal data, the authors establish whether living in a mixed-ethnic neighbourhood makes it more likely for people to end up in mixed-ethnic unions.
Using migration microdata from the samples of anonymised records and the longitudinal studies
Norman, P. & Boyle, P. (2010) In Stillwell, J, Duke-Williams, O & Dennett, A (eds), 'Technologies for Migration and Commuting Analysis: Spatial Interaction Data Applications' Chapter 7, pp133-152. IGI Global. ISBN: 9781615207558 [SLS][ONS LS][NILS]
In this chapter we describe the Samples of Anonymised Records (SARs) and Longitudinal Studies (LSs). The SARs are cross-sectional data like the area and interaction data, but the LSs track people over time. These datasets differ from the United Kingdom’s other census outputs being individual-level ‘microdata’ and population samples. The microdata files are very versatile, allowing multi-way crosstabulations and statistical techniques and enabling application-relevant re-coded variables and study populations to be defined. The SARs files offer UK coverage although a UK-wide study is challenging because data for each country may be in separate files with different access arrangements and variable detail may be country specific. The Office for National Statistics (ONS) Longitudinal Study for England and Wales has underpinned a wide range of research since the 1970s. This well-established source is now complemented by longitudinal data for Scotland and Northern Ireland. Largely driven by the need to ensure respondent confidentiality, the SARs and LSs have some drawbacks for migration-related research. In addition to stringent access arrangements, the geographical area to which individuals are located in the SARs tend to be coarse and although the LS databases record the small area in which the LS member was living at each census, specific ‘place’ information is unlikely to be considered non-disclosive unless for large geographies. However, generic, contextual information about the ‘space’ in which people live is useful even though actual places are not identified. Whilst the SARs and LSs are samples, they are, however, very large samples in comparison with other national surveys and represent first rate resources to complement other sources. In the course of this chapter, along with other references to SARs and LS-based migration research, we review work which utilised these sources to investigate inter-relationships between health, deprivation and migration. The SARs data show that migration is health-selective by age and distance moved and that those persons living in the public housing tenure who are moving into or within deprived areas are most likely to be ill. The role of migration in changing health inequalities between differently deprived areas can be explored using longitudinal data on both origins and destinations. The ONS LS reveals that migrants into and between the least deprived areas have better health than non-migrants, but migrants into and between the most deprived areas have the worst health. The effect of these changes has been to increase the inequality in health between differently deprived areas. A sorting, largely driven by selective migration occurs.
Available online: 'Technologies for Migration and Commuting Analysis: Spatial Interaction Data Applications'
Output from project: 10347
Stepparenting and mental health
Boyle, P., Feijten, P., Feng, Z., Gayle, V. & Graham, E. (2009) In J. Stillwell, E. Coast, D. Kneale (Eds), 'Fertility, Living Arrangements, Care and Mobility'. Volume 1 of Understanding Population Trends and Processes. Chapter 8. Springer. ISBN: 978-1-4020-9682-2 [SLS]
Available online: In J. Stillwell, E. Coast, D. Kneale (Eds), 'Fertility, Living Arrangements, Care and Mobility'. Volume 1 of Understanding Population Trends and Processes.
Output from project: 2007_001
Insights into demography: the potential of the Scottish Longitudinal Study (SLS)
Boyle, P. (2006) In Lilley, L (ed), 'The Scene: The Social Sciences in Scotland' ESRC. [SLS]