Science and Technology CommitteeWritten evidence submitted by Professor Heather Joshi, Institute of Education (Census 10)
1. Introduction
My current affiliation is as a Professor Emerita of the Institute of Education, and the President of the Society for Lifecourse and Longitudinal Studies. The latter is an interdisciplinary international society of scholars interested in research on the lifecourse and the development of longitudinal data. Our members come from epidemiology, psychology, geography, sociology, demography, education and economics. I have formerly been president of both the British Society for Population Studies and of the European Society for Population Economics. My illustrations are taken only from my own work for economy of time, but I am sure I have the support of many colleagues in saying that social scientists working in and on the UK find the census a very valuable resource underpinning research as well as vital for informing central and local government.
2. Statement on Conflict of Interest
I have retired from my post at the Institute of Education, where from 2000 until earlier in 2011 I was director of the Millennium Cohort Study (MCS), making use of some census data as indicated in para 4 below. As also indicated in para 4, I was the head of the team providing academic access to the ONS Longitudinal Study, and I was involved in making the case for it to be linked to the 2001 census. In my retirement I am working part-time on research (education in social mobility, child residential mobility), which will make some use of existing census data. I, personally, would not expect to be a very extensive user of any data which might become available from any future census, but I do need to say that it would be very useful to colleagues in the social science community, as well as those responsible for making and administering policy and the public at large. I would hope you find my interest constructive rather than conflicted.
3. How do social scientists use Census data?
Turning to your questions, here are some examples, far from exhaustive, of how a social scientist uses the census, which are elaborated in paragraph 4:
To compare change over time in the demographic and social structure;
To make international comparisons;
To compare locations at various levels of geography, from regions down to very small neighbourhoods;
To track internal and external migration;
To compare workplaces and places of residence, and the generated “travel -to-work areas”;
To examine detailed breakdowns of characteristics of individuals;
To compare the combinations of individual characteristics found among members of the same family or household;
To chart the living arrangements of individuals at different ages;
To chart the demographic composition of detailed occupations;
To classify areas as rural or urban;
To inform the drawing up of sampling frames for sample surveys;
To inform the assessment of bias in social survey data;
To assist estimates and projections nationally and locally;
To perform micro-level analyses on Samples of Anonymised Records;
To perform—micro-level analyses using the ONS Longitudinal Study.
4. Here, I briefly amplify these points and give examples of such use from my own (and co-authors’) work. References are appended at the end of this document. I do not pretend to be offering a comprehensive account of the uses made by the social science community of the census. I am offering this eclectic exercise in self citation as the most cost-effective way I have, in the time available, of illustrating a wide range of uses on the basis of a sample of one user. I am not suggesting that the Select Committee needs to consult the publications cited, just to noting a “tip-of-the iceberg” selection of social science research which has used the census.
4.1
Censuses offer the building blocks for assessing long-term change over many decades in demographic, social and economic indicators. An example from my own work is the construction of secular time series of female economic participation rates.
4.2
Just as census offers the possibility to gauge continuity and change over time, they also enable comparisons of conditions cross-nationally. An example from my work includes comparing Britain and France on childbearing by women’s occupation. Ongoing work on residential instability as experienced by young children draws on comparison of US and British censuses.
4.3
The finer the level of geographical resolution—down to electoral wards, or smaller approximations of neighbourhood such as Output Areas, the more is social science dependent of census indicators on the social profile of inhabitants. Sample surveys cannot cover all areas in any detail, administrative data (even where reasonably accurate) do not record all relevant indicators, eg ethnicity, housing quality, educational attainment of adults, household composition etc. I have made various uses of census-based small area statistics, such as analyses of child outcomes in the Millennium Cohort and National Child Development Study second generation by census (and other) indicatorss of deprivation at ward and Lower Super Output Area level.
4.4
Though I have not used them myself the special census migration tables seem to me to be invaluable for identifying the characteristics of people moving between localities within the UK. Duration of residence data can provide one half of the demographic profile of international migration.
I have used less detailed census migration tables, by age, to inform patterns of non-response to Millennium cohort study.
4.5
Have supported other researchers using commuting data in the ONS Longitudinal StudyS (see below).
4.6
Examples include: economic activity or carer status, longstanding illness, educational qualifications, country of birth, ethnic group, type of household or housing into gender, details of age by single years and/or detailed geographies. Most valuable is the cross classifications among such characteristics.
For instance a comparison of the educational, occupational and health status of ethnic groups controlling for country of birth and duration of residence, and in different regions of the UK. I have not conducted such work myself. Although sample surveys may be adequate to provide details of these cross-classification at a national level, the results become statistically unreliable at more local levels, where they may be needed for planning services.
4.7
Besides looking at the distribution of paid work across dual, single and zero earner couples, this feature of the census will be used in ongoing work on gender and social mobility, where it will be necessary to compare the education and occupations of spouses.
4.8
Census evidence on the living arrangements and location of ethnic groups will be of academic as well as policy interest. I have not been involved in work on ethnic minorities or international migrants, but we have used longitudinal census data to look at different groups’ experience of lone parenthood over time.
4.9
I have used such results to identify, gender typed occupations in coding occupational data collected in sample surveys in the analysis of gender pay gaps.
<?oasys [pf10p0] ?>4.10
The Rural Evidence Research Centre at Birkbeck College has devised a classification of areas for DEFRA based upon the settlement pattern of the whole population (which could probably not be implemented from survey data). I have applied this Census-based indicator of rurality to the analysis of the Millennium Cohort and the ONS Longitudinal Study.
4.11
Although there may be alterative lists of addresses from which sample surveys could be drawn (eg postal or electoral) they do not contain much information on which to stratify samples. The over sampling of areas of high ethnic minority settlement for the Millennium Cohort was based upon ward-level census data for 1991, with adjustments for boundary changes provided by Professor Ludi Simpson.
4.12
One example is the study of attrition through mobility in the MCS.
4.13
Census data forms the benchmark for estimates and projections of population, households and pension population by marital status.
4.14
No personal use of SARS.
4.15
I was head of LS User Support for seven years, during which time many academics made use of the 1% sample of longitudinally linked individual census records, with their household at each census also linked to vital registration records. I presume there will be fuller evidence about this remarkable resource and rich resource from the CeLsius team currently responsible for access and from the user community. Its classic value, which should remain a raison d’être, is to provide valid denominators for estimating social inequalities in mortality. My own research on it includes a study of the timing of childbearing by the woman’s occupational attainment comparing Britain and France, social profile of movers between urban and rural England, analyses of the geographical and gender dimensions of health inequalities, and the dynamics of children’s living arrangements.
5. What impact will the ending of the Census have on social science research?
Just at the time when the technology and governance arrangements permit far better academic use of census data through micro data sets, the existence of this increasingly valuable source of evidence is going to be withdrawn. Given the range of uses to which is it currently put, this will be a blow to empirical academic research and the policy uses which flow from it, removing the bedrock on which much else is built.
6. What alternatives to the Census would provide population and socio-demographic data of equivalent or higher quality?
The routine recording of residential moves, including those out of the country, seems to me to be a top priority. This might be achieved through a better use of the NHS central register and better recording of movements across borders. Clearly the current system is inadequate.
The social and economic details collected at birth, and marriage registration could be improved. For births I would like to see true birth order, educational attainment and duration of residence at current address included in on the birth certificate. But without supplementary data on the size of the population at risk to give birth at each age and number of previous births, data on birth registration will be hard to interpret.
The most important priority for mortality analysis is to have adequate denominators of the population at risk.
7. What other existing sources of population and socio-demographic data could be improved upon?
The sample size of national surveys should be increased to allow for adequate coverage of small categories and cross classifications.
If the census goes, there should be better ways of sample surveys accounting for visitors and transient residents in households, and allowing for people (like children whose care is shared between separated parents, or weekly commuters) being covered.
The linkage of vital events from birth and death registration to the existing Longitudinal Studies’ databases could usefully be continued. Consideration might be given to collecting other information from their sample members, if a way could be found to safeguard confidentiality. This would need to be very carefully thought through but there may be an instructive example in France, which has just recruited a large fraction of its national birth cohort (ELFE) from the Echantillon Demographique Permanente (EDP)—the French equivalent of the LS.
References by Paragraph
4.1
Joshi, H E, Layard, P R G and Owen, S J (1985). Why are more women working in Britain? Journal of Labor Economics, Vol 3 January 1985, S147–S176.
Joshi, H E and Owen, S J (1987). How Long is a Piece of Elastic? The measurement of female activity rates in British censuses. Cambridge Journal of Economics, Vol 11, 1, 55–74.
Joshi, H E (1985). “Motherhood and Employment: Change and Continuity in Post
4.2
Rendall, M S, Ekert-Jaffé, O, Joshi, H, Lynch, K and Mougin, R (2009). Universal versus economically polarized change in age at first birth: A French-British comparison, Population and Development Review, Vol 35 Number 1, 89–115 and work currently in progress
4.3
McCulloch, A and Joshi, H (2001). Neighbourhood and family influences on the cognitive ability of children in the British National Child Development Study. Social Science and Medicine, 53, 5, 579–591.
4.4
Plewis, I, Ketende, S C, Joshi, H and Hughes, G (2008). The contribution of residential mobility to sample loss in a birth cohort study: evidence from the first two waves of the UK Millennium Cohort Study, Journal of Official Statistics, Vol.24, No.3, 2008. pp. 365–385.
4.5 and 4.6 nothing to report here at present
4.7
Joshi, H (1998). The opportunity costs of childbearing: more than mothers’ business. Journal of Population Economics, 11, 161–183.
Davies, H, Joshi, H, Peronaci, R (1998). Dual and Zero-earner Couples in Britain: Longitudinal Evidence on Polarization and Persistence. Discussion Paper in Economics 8/98, Birkbeck College, London.
4.8
Clarke, L and Joshi, H (2001). Accessions and Abdications: Men and women as family markers in linked data for England and Wales. In B. Zaba & J. Blacker (eds.) Brass Tacks, Essays in Medical Demography. Athlone Press, London, 207–230.
Rendall, M, Joshi H, Oh, J and Verropoulou, G (2001). Comparing the Childrearing Lifetimes of Britain’s Divorce-Revolution Men and Women. European Journal of Population, 17, 365–388.
4.9
Sullivan, A, Joshi, H, Leonard, D (2010 in press). Single-sex schooling and labour market outcomes’ Oxford Review of Education, Vol. 37, Number 3.
Paci, P, Joshi, H and Makepeace, G (1995). Pay gaps facing men and women born in 1958: differences within the labour market in J. Humphries and J. Rubery (eds) The Economics of Equal Opportunity, Manchester: Equal Opportunities Commission, 87–112.
4.10
Joshi, H, Dodgeon, B and Hughes, G (2008). A profile of population change in Rural England. CLS Working Paper 2008/4, London: Centre for Longitudinal Studies. http://www.cls.ioe.ac.uk/publications.asp?section=0001000100060009
4.11
Plewis (ed) et al (2007) Millennium Cohort Study: Technical Report on Sampling. CLS. IOE.
4.12 see 4.4
4.13
Diamond, I, Testaghiorghis, H and Joshi, H E (1990). The Uses and Users of Population Projections in Australia. Journal of the Australian Population Association, Vol 7, 2, 151–170.
Joshi, H E and Davies, H B (1992). Pensions, Divorce, and Wives’ Double Burden, International Journal of Law and the Family, 6, 289–320.
4.14 No personal use of SARS
4.15
Ekert, O, Joshi, H, Mougin, R and Rendall, M (2002). Fécondité, calendrier des naissances et milieu social en France et en Grande Bretagne: des évolutions contrastées. Population 2002 (3) 485–518 English edition: Fertility, Timing of Births and Socio-economic Status in France and Britain: Social Policies and Occupational Polarization 2002(3) 475–507.
Wiggins, R D, Joshi, H, Bartley, M, Gleave, S and Lynch, K, Cullis A (2002). Place and personal circumstances in a multilevel account of women’s long-term illness. Social Science and Medicine, 54, 5, 827–838.
<?oasys [pf10p0] ?>Wiggins, R D, Bartley, M, Gleave, H, Joshi, H, Lynch, K (1998). Limiting long-term illness: a question of where you live or who you are? A multilevel analysis of the 1971–1991 ONS longitudinal study. Risk Decision and Policy, 3,3, 181–198.
Gleave, S, Wiggins, R D, Joshi, H, Lynch, K (2004). Identifying Area Effects on Health: A Comparison of Single- and Multi-level Models in P Boyle, S Curtis, E Graham, E Moore, (eds.) The Geography of Health Inequalities in the Developed World, pp. 245–266, Ashgate ISBN 0 7546 1398 4.
Joshi, H, Wiggins, R D, Bartley, M, Mitchell, R, Gleave, S, Lynch, K (2000). Putting health inequalities on the map; does where you live matter? in H Graham (ed) Understanding Health Inequalities, Open University Press, 143–155.
Sloggett, A and Joshi, H (1998). Indicators of Deprivation in Longitudinal Perspective Environment and Planning A, 30, 1055–1076.
Sloggett, A and Joshi, H (1998). Indicators of Deprivation as Predictors of Life Events Journal of Epidemiology and Community Health 54, 4, 228–233.
Sloggett, A and Joshi, H (1994). Higher mortality in deprived areas: community or personal disadvantage? British Medical Journal, December, Vol 309, 1470–1474.
Weatherall, R, Joshi, H E and Macran, S (1994). Double Burden or Double Blessing? Employment, Motherhood and Mortality in the Longitudinal Study of England and Wales. Social Science and Medicine, 38, 2, 285–297.
Clarke, L and Joshi, H (2003). Children’s Changing Families and Family Resources. In Jensen and McKee (eds) Children and the Changing Family: between transformation and negotiation. London: Routledge Falmer, 15-26. ISBN 0 415 27773-6
Professor Heather Joshi
Institute of Education
November 2011