Georeferencing socio-demographic information: postcodes, addresses, land parcels and geographical information systems

The collection and dissemination of population related data requires that all database records are georeferenced. First we consider household residential populations in Great Britain before noting some differences in Northern Ireland and for institutional populations. We then outline the situation for mobility, both migration and commuting and in relation to the latter, place of work. Ultimately, all these circumstances are geographically inter-related so should be considered as part of a whole statistical system

Demographic and health time-series analysis of small areas in GB: the development of area measures and population estimates

This paper reports on previous work to create time-series of demographic related data for small areas within the UK and how these have been used in research. The development of an updated set of resources is outlined

Estimating age-specific fertility rates by ethnic group for population projections

Population projections with an ethnic group dimension can inform the provision of relevant goods and services, such as appropriate housing and language support, and can help set targets for take-up of equal opportunities. Projections by ethnic group can also inform policy debates on international migration and diversity. To understand past population change by ethnic group and to inform projections of future populations we need demographic rates appropriate to each ethnic group. Whilst estimates of ethnic-specific migration and mortality rates have been calculated here we focus on data sources which can help us understand fertility trends by ethnic group

Sub-national projection methods for Scotland and Scottish areas: a review and recommendations

This report responds to a request for advice by National Records of Scotland (NRS) on how to adapt and improve the methodology used for the Scotland Sub-National Population Projections (SNPP). The 2014- based Scotland SNPP are currently being prepared

Exploring the utility of Acxiom’s Research Opinion Poll data for use in social science research

Acxiom’s Research Opinion Poll (ROP), a voluntary survey designed to capture detailed information about household consumption and expenditure across Great Britain, has the potential to provide information valuable for social science research. This paper provides a review of the ROP, indicating that the survey in undertaken through a number of channels which enable Acxiom to generate over one million household responses a year. The ROP micro data collected are used in the construction of many of Acxiom’s aggregate products including its geo-demographic classification system called ‘PersonicX’. The ROP is found to compare favourably in areas such as sample size, geographic detail, consistency and data quality and accuracy when compared against government datasets including the 2001 Census, the Living Costs and Food Survey, the Labour Force Survey, the British Household Panel Survey, the General Lifestyle Survey and the English Housing Survey

A synthetic Longitudinal Study dataset for England and Wales

This article describes the new synthetic England and Wales Longitudinal Study ‘spine’ dataset designed for teaching and experimentation purposes. In the United Kingdom, there exist three Census-based longitudinal micro-datasets, known collectively as the Longitudinal Studies. The England and Wales Longitudinal Study (LS) is a 1% sample of the population of England and Wales (around 500,000 individuals), linking individual person records from the 1971 to 2011 Censuses. The synthetic data presented contains a similar number of individuals to the original data and accurate longitudinal transitions between 2001 and 2011 for key demographic variables, but unlike the original data, is open access

Not social mobility but deprivation mobility: places change their characteristics and people change their places

Many studies which link to areas use deprivation measures cross-sectionally and assume this cross-section applies over time. This presentation shows how area deprivation has been measured in a way which allows changing levels to be captured. Using these data individual level studies can be carried out whereby changes in people's area circumstances over time can be related to their health

Selective mobility: it depends which groups you compare with

For ‘Social selection’, there is a debate about cause/effect, but healthier people are more likely to experience upward social mobility and less healthy people more likely to move down the social hierarchy. For ‘Deprivation selection’ there is a similar cause/effect debate, but healthier people more likely to move to less deprived areas and people in poorer health more likely to move to more deprived areas. Might these mobilities lead to widening or easing of health inequalities

Using the 2011 Census Microdata Teaching File

Various Samples of Anonymised Records (SARs) have been extracted from the 1991 and 2001 Censuses and these have provided an invaluable research resource. Three levels of microdata are planned to be extracted from the 2011 Census: a Teaching file; Safeguarded files and Virtual Microdata Laboratory (VML) files available in an ONS safe setting. The SARs complement census area data: by allowing the user to derive custom variables; to create versatile crosstabulations; and to use statistical models which, for example, help avoid the ecological fallacy (Norman & Boyle 2010). Whilst large and complex files, the SARs microdata are not so much of a challenge to the user as the Office for National Statistics (ONS) Longitudinal Study for England & Wales (and the Scotland and Northern Ireland equivalents) and allow a study coverage of more than just England & Wales, or Scotland or Northern Ireland. Other datasets which a user might access in census years and during inter- and post-censal years are area data from administrative records and large scale government surveys such as the Labour Force Survey (LFS). The SARs though are a much larger sample than a source such as the LFS and cover both household and institutional residents. The SARs have underpinned a wide range of research which includes: Boyle et al. (2002), Norman & Purdam (2013) Norman (2008) and Norman et al. (2014). The Office for National Statistics (ONS) has devised a 2011 Census Microdata Teaching File to help users learn how to use microdata and prepare initial analyses for the use of the other SAR releases. This document first steps through the use of a ‘customised’ version of the 2011 Census Microdata Teaching File and provides SPSS syntax to first read in the original file to SPSS and label the variables and then to revise some of the variables to improve their utility in the context here