Log in
Southampton statisticians have made a valuable contribution to government policy formulation across the UK and further afield to areas of North America and Europe. Novel methods for delivering more accurate estimates of socio-economic indicators at neighbourhood level have given local authorities, national government agencies and MPs the tools to implement more effective policies designed to assist the poorest communities and strengthen community cohesion. The UK's Office for National Statistics (ONS) has described Southampton's contribution as `a breakthrough', while the Mexican government agency, CONEVAL, regards this work as `the most prestigious' of its kind.
Research at the Centre for Urban Policy Studies (CUPS) at the University of Manchester (UoM) has contributed significantly to the improvement and targeting of resources to deprived urban areas. Through the development of a matrix approach, this work has both informed and transformed the UK Government's `deprivation index', the measure used to direct resources to areas most in need. More recently, a functional typology for use in the classification of deprived neighbourhoods has been developed. This was subsequently used by central government, local authorities and city-regions to better inform the nature and scope of regeneration initiatives.
Research by the University of Southampton has led to an entirely new approach to the creation and management of small geographical areas for the publication of official statistics, including those from the 2001 and 2011 UK Censuses and the Neighbourhood Statistics Service. The software at the heart of this transformation is now used in 10 countries, while the academics responsible for it have helped inform government decisions, are integral to the policy and practice of the Office of National Statistics and have presented evidence to various influential committees. The research continues to deliver benefits to a large user community.
Coombes' research to advance spatial-analysis methodology has re-defined Travel-to-Work Areas (TTWAs) — the only official UK boundaries defined by academics — and produced three distinct strands of impact.
Since 1999, researchers at the Department of Social Policy and Intervention (DSPI) have undertaken a programme of research to produce small area level indices of deprivation, in the UK and South Africa. These indices are widely used in these nations by central and local government, regional bodies, civil society, academics and others, to analyse patterns of deprivation, to identify areas that would benefit from special initiatives or programmes, and as a tool to determine eligibility for specific funding, enabling governments and other bodies to target their resources more effectively. The methodology developed for England was subsequently used to produce indices for the other countries in the UK, as well as South Africa, and is increasingly being applied elsewhere in Africa and Asia.
The Scottish Longitudinal Study (SLS) is a pioneering study, combining census, civil registration, health and education data (administrative data). It has established an approach that allows the legal and ethical use of personal, sensitive information by maintaining anonymity within the data system. This approach has become a model for the national data linkage systems that are now being established across the UK. The SLS has also enabled policy analysts to monitor key characteristics of the Scottish population in particular health inequalities (alerting policy makers to Scotland's poor position within Europe), migration (aiding economic planning) and changing tenure patterns (informing house building decisions). Finally, the study has become fully embedded in Scotland's National Statistical agency, allowing it to produce new informative statistical series.
Successful planning in Scotland requires a set of geographical units for which data can be collected and analysed. Researchers at St Andrews have developed a new `small area' geography for Scotland. `Data zones' (DZs) provide a scientifically-based template for data mapping and has been adopted as the default geography used by public and private organisations to display and analyse data on topics as diverse as economic planning, health, education and transport, thus impacting how and where policy is enacted. To be statistically appropriate these units have to be compact, homogenous, with approximately the same size population and publically acceptable. This is not a trivial task, involving millions of potentially different solutions. In 2001, Scottish Neighbourhood Statistics (SNS) commissioned St Andrews to study how such units should be defined and to develop a methodology for creating them. Using the experience and skills developed over many years working in this area, the team developed a methodology and established the official small area geography of Scotland.
Small area estimation (SAE) describes the use of Bayesian modelling of survey and administrative data in order to provide estimates of survey responses at a much finer level than is possible from the survey alone. Over the recent past, academic publications have mostly targeted the development of the methodology for SAE using small-scale examples. Only predictions on the basis of realistically sized samples have the potential to impact on governance and our contribution is to fill a niche by delivering such SAEs on a national scale through the use of a scaling method. The impact case study concerns the use of these small area predictions to develop disease-level predictions for some 8,000 GPs in England and so to produce a funding formula for use in primary care that has informed the allocation of billions of pounds of NHS money. The value of the model has been recognised in NHS guidelines. The methodology has begun to have impact in other areas, including the BIS `Skills for Life' survey.
Statistical techniques developed at the University of Southampton have transformed the accuracy with which Census data can estimate the UK population's size and characteristics, delivering far-reaching socio-economic impact. The methodologies developed by Southampton have increased the accuracy and availability of the 2011 UK Census data, not only for the Office for National Statistics but for central government, local authorities, the NHS and the private sector, who all use the data as a basis for policy decisions. Preserving the privacy of the UK population, Southampton's work allowed, for the first time, the release of highly localised data, which is used by local authorities to target resources efficiently and meet the demands imposed by the Localism and Equality Acts.
In the mid-2000s the Ministry of Justice (MoJ) devised a new measure to compare area variations in reconviction rates across the Probation Service in England and Wales so that these differences could be taken into account when allocating resources. A number of Probation Trust Chief Executives have used Hedderman's research successfully to argue for revisions to the reconviction 'performance measure'. Her findings also influenced the Justice Select Committee's recommendation that the original measure should be replaced, as she showed that it led to unfair comparisons, was easy to manipulate, and failed to provide information which could be used by areas to improve their impact on reoffending. She has since worked directly with Kent, London and Hertfordshire Probation Trusts to address this last point.